A large-scale optogenetic neurophysiology platform for improving accessibility in non-human primate behavioral experiments

Domain: chemistry
Published: 2026-02-24
Editorial outcome: major_revision

Abstract
Optogenetics has been a powerful scientific tool for two decades, yet its integration with non-human primate (NHP) electrophysiology has been limited due to several technical challenges. These include a lack of electrode arrays capable of supporting large-scale and long-term optical access, inaccessible viral vector delivery methods for transfection of large regions of cortex, a paucity of hardware designed for large-scale patterned cortical illumination, and limited designs for multi-modal experimentation. To address these gaps, we introduce a highly accessible platform integrating optogenetics and electrophysiology for behavioral and neural modulation with neurophysiological recording in NHPs. We employed this platform in two rhesus macaques and showcased its capability of optogenetically disrupting reaches, while simultaneously monitoring ongoing electrocorticography activity underlying the stimulation-induced behavioral changes. The platform exhibits long-term stability and functionality, thereby facilitating large-scale electrophysiology, optical imaging, and optogenetics over months, which is crucial for translationally relevant multi-modal studies of neurological and neuropsychiatric disorders.

Introduction
Optogenetics is unique among neuromodulation technologies because it allows for cell-type-specific manipulation of neural networks with high spatial and temporal precision. This enables the precise manipulations needed for research in fundamental neuroscience1–5, such as investigating relationships between neural activity and behavior4–8, monitoring changes in neural circuitry over time7,9, understanding the neural changes associated with brain dysfunction10,11 and developing therapies for neurological disorders1,3,5,12,13.

The evolutionary proximity between the neurophysiology of non-human primates (NHPs) and humans14–16 spurs us to apply optogenetics to NHPs to better understand the human brain and strengthen translational medical research, especially in the context of neurological and neuropsychiatric disorders. However, studying neurological disease models in NHPs is challenging because NHP neuropathology and anomalous neural activity are often spatiotemporally complex, spanning multiple brain areas and months or years of development, much like in humans. These challenges, along with the scientific opportunities afforded by optogenetics, call for the development of large-scale, chronically stable optogenetic platforms for NHPs.

Although the development of optogenetic techniques in NHPs emerged soon after the debut of optogenetics17,18, its wide-spread adoption has remained a challenge. We dissect key contributing factors below that are addressed in our platform.

While optogenetics alone is a potent technique for functional neuropathological studies, the integration of optogenetics with an electrical platform, such as electrocorticography (ECoG) recordings, can enable precise optical control over specific cell types with concurrent measurement of neural activity at high spatiotemporal resolution. Merging of optogenetic and electrical recording platforms has been demonstrated in rodent work19,20, however, similar attempts in NHP work have come with limitations. Systems where skin is closed over the implant require surgeries for device replacements or modifications and prevent ongoing assessment of both optical occlusions between the light source and the brain, as well as optogenetic expression21, which is typically confirmed with optical techniques. Such limitations make these systems experimentally inflexible.

In contrast, modular chambers enabling chronic access to the cortical surface have been developed. In particular, in vivo optical imaging of NHP brains through cranial windows has been a small but vibrant field with decades of development with techniques such as calcium imaging22, voltage-sensitive dyes23,24, intrinsic signal optical imaging24,25, and epifluoresence imaging9,26, among others. Optical windows to the NHP brain are often covered with a transparent, silicone-based artificial dura to protect the brain while providing optical access to the cortex23–26. The artificial dura has been combined with optical stimulation methods such as infrared neural stimulation27 and optogenetics25,28. In a previous effort, we have taken a similar approach and performed simultaneous electrical recording and optogenetic stimulation using a µECoG array in an optical window. However, long-term optical access stability using this approach remained an unmet challenge. One approach relied on daily explantation of an artificial dura and implantation of a µECoG array to perform experiments, but the frequent manipulation of the cortical surface stimulated tissue growth over the cortex and obscured optical access26,29. Another approach relied on chronic co-implantation of both an artificial dura and a µECoG array between the artificial dura and the brain, but tissue growth between the artificial dura and the µECoG array obscured optical access29,30. To take full advantage of optogenetics in NHPs, there is a need for innovative platforms with chronic stability in both electrophysiology and optical access to empower widespread adoption.

One obstacle in NHP optogenetics, not present in rodent models, is the size of NHP brains, which renders widespread viral delivery of optogenetic vectors impractical via traditional, diffusion-based methods. In contrast, convection-enhanced delivery (CED) is a pressure-based approach of infusion allowing for large-scale and even distribution of viral expression in comparison to diffusion-based approaches26,31. Previously published CED protocols relied on live magnetic resonance imaging (MRI) to monitor infusions26,32, making these methods technically challenging and only accessible to the institutions capable of MRI-guided viral infusions in the NHP brain.

Given the challenges of attaining large-scale optogenetic coverage and maintaining optical access, large-scale optical stimulation techniques have been largely undeveloped—optogenetic stimulation in NHPs is generally performed by fiber optics or optrodes coupled to lasers33, which are not optimized for large-area optogenetic coverage. Light emitting diode (LED) arrays, both with21 and without34,35 simultaneous electrophysiological recording, have also been used, but with limited cortical coverage or access. Optogenetic transduction and stimulation methods, that are both experimentally flexible and widely accessible, are necessary to capitalize on large-scale optogenetics in NHPs.

In this paper, we address the above challenges by designing accessible tools and integrating them into a single platform. We demonstrate large-scale, chronically stable optogenetics and ECoG in an imaging window on NHP cortex. We present an optogenetic platform comprised of five complementary state-of-the-art technological advancements, enhancing both experimental flexibility and accessibility to researchers with diverse technical backgrounds. Our advancements are: (1) a platform designed to be modular and flexible for varied, multi-modal use-cases; (2) a chronically implanted integration of an ECoG array and an artificial dura, which we refer to as a multi-modal artificial dura (MMAD); (3) optical hardware scalable from single lasers up to large arrays of LEDs for complex patterned stimulation across multiple brain areas; (4) improved ECoG-compatible optical access with the MMAD, facilitating long-term multi-modal experimentation; and (5) CED without live-MRI guidance, which is an accessible viral vector delivery method for achieving large-scale expression. These technologies are synergistic yet maintain functional modularity, i.e., no one technology requires all the others to function, thus keeping our platform relevant for experiments requiring fewer than our full suite of technologies, while maintaining forward compatibility. Our work is poised to bridge the gap between rodents and humans by facilitating powerful, multi-modal studies in NHPs.

We demonstrated the efficacy of our advancements by three complimentary measures: optical imaging, electrophysiology, and behavior. We present months of continuous optical clarity with the MMAD and years of chamber stability, which open opportunities for translational studies of models of neurological diseases and disorders such as stroke recovery36. The optical clarity empowered verification of large-scale epifluorescence, the product of our viral delivery process, and our ECoG recordings confirmed the flexibility of our scalable optical stimulation setup for optogenetic experimentation. We demonstrated our platform’s relevance for behavioral studies by optogenetically disrupting a center-out reach task by modulating the posterior parietal cortex (PPC). This showcases the applicability of our platform for complex behavioral experiments. This work provides a milestone proof-of-concept for NHP behavior experiments with inhibitory opsins which, up to this point, have not been successfully applied to reaching behavior.

The ability to link millisecond-resolution neural activity with behavioral effects and optogenetic neuronal manipulation is an invaluable addition to the NHP researcher’s toolbox. Therefore, we took measures to ensure the accessibility of our methods for a diverse range of specialties: design files are provided for parts and equipment that are not commercially available, our in-house fabrication processes require only generic equipment and modest skill, and our neural processing code is publicly available. Collectively, our work enables large-scale and long-term interrogation of cortical areas in awake behaving NHPs37,38.

Results
Hardware
We designed and implemented our platform for two healthy adult male rhesus macaques (Macaca mulatta, Monkeys H and L). We used magnetic resonance imaging (MRI)-based methods to plan a craniotomy with a diameter (Ø) of 25 mm over the left PPC and to design a custom chamber with a curvature precisely fitting the surface of the skull around the craniotomy for each monkey (Fig. 1a, c). We have previously published these methods as step-by-step protocols for accessibility39,40. The custom chamber was designed to provide a sturdy base for experimental equipment and protect the brain when the monkey is freely moving between experiments. The chamber is further described in Methods. We implanted the chamber along with our multi-modal artificial dura (MMAD; Fig. 1b, d41;) in both animals. The chambers continue to be stable and used for studies after >4.6 and >3.8 years following implantation for Monkeys H and L, respectively, and we have not observed behavioral or health deficits.

We designed the MMAD to serve both as an optical window to the brain and as an electrocorticography (ECoG) array. The MMAD is composed of a flexible and corrosion-resistant electrode array molded in silicone into a “top-hat” shape common for traditional artificial duras40,42. The opaque, conductive traces of the MMAD are layered on top of each other to maximize the optical access to the brain through the transparent polymer of the MMAD41. Like traditional artificial duras, the MMAD protects the brain and keeps the brain moist during experiments. Unlike traditional artificial duras, cables extend from the “top-hat” of the MMAD to hardware for electrophysiological recordings, as described below. We packaged the MMAD cables inside the chamber between experiments (Fig. 1d). The MMAD, as well as the commercially available electrode array (Ripple Neuro, Salt Lake City, UT) from which the MMAD was fabricated, are further described in Methods.

The MMAD cables require adapters, called clamp connectors, to be used with external electrophysiology equipment. We designed a stack-up of parts to attach to the chamber and support the clamp connectors (Fig. 1e, f). All parts are designed to be modular for flexible experimentation and design iterations as needed. Further descriptions of parts can be found in Methods, and design files are publicly available (see Data and Code Availability).

We designed and tested our platform for both laser- and LED-based optical stimulation. The lasers and optical fibers were commercially sourced and can support a variety of light wavelengths (see Methods for further laser system details). We designed an LED array and its driving circuitry in-house (Fig. 2, Supplementary Fig. 1) to be compatible with high temporal resolution (sub-millisecond) requirements (Supplementary Movie 1). While pulse-width modulation is a popular technique for driving LEDs, we designed our driving circuitry to be controlled by analog signals. Specifically, we drove our LEDs with continuous voltage signals to avoid high-frequency photo-induced artifacts in our electrophysiology recordings. We selected LEDs for optimal tissue penetration and powered our circuitry with two rechargeable 9V batteries to mitigate line noise (Supplementary Fig. 1). We designed and fabricated two versions of an LED array for patterned stimulation, a 4 × 4 array with individually drivable LED columns43. and a 3 × 5 array with independently drivable LEDs (Fig. 2a). An example stimulation pattern demonstrating spatial, temporal, and optical power complexity is provided (Supplementary Movie 1). Both boards used identical schematics for the driving circuitry except for the number of LEDs driven by each driving circuit (Supplementary Fig. 1). We fabricated our LED arrays in two wavelengths (634 nm and 485 nm). The LED array was protected from potential moisture from the brain by a cover glass between the LED array and the MMAD (Figs. 1e–g, 2b). This also provided a small air gap between the LEDs and the cover glass to mitigate conductive heating of the brain (Fig. 2b). Our benchtop temperature measurement data indicate our stimulation design limits the cortical temperature change to less than 1 °C during our stimulation protocols (Supplementary Fig. 2), which is below the safe limit for brain44–47 and has minimal impact on neuronal activity48,49. We did not observe any tissue damage (e.g., brain discoloration) or behavioral deficits over the years in our animals.

We commercially sourced our custom printed circuit boards (PCBs) and assembled the LED array and driver PCBs in-house with common soldering methods. (For more details, see Methods).

Optical stability
To demonstrate the stability of optical access through the MMAD we used both optical epifluorescence imaging and stimulation. With our MMAD, we achieved 10 to 14 consecutive weeks of optical access in our monkeys before tissue growth began to obstruct light penetration (Supplementary Fig. 3). After tissue had matured, we resected the tissue and reimplanted the MMAD for additional experiments.

As aforementioned, both implanted monkeys have been stable for ~4 years following surgery, and the chambers have supported optical experiments, displaying the platform’s ability to facilitate long-term NHP studies. Over this period, we have repeated the dura resection and reimplantation of the MMAD for both monkeys, each allowing us windows of >10 weeks of optical access for experimentation. In some instances, we observed accelerated tissue growth when we explanted the MMAD to test other recording and stimulation systems. For example, following a tissue resection in Monkey H approximately two years after first implantation, the MMAD was replaced and clear optical access was maintained for 7 weeks. At week 7, while optical access was still clear, the MMAD was removed to test other stimulation and recording devices that impacted tissue growth. Approximately one week later, tissue began to grow over the cortex. For another example, one and a half years after the first implantation in Monkey L, a similar procedure provided clear optical access for at least 5.5 weeks during which we ran experiments. Similarly, the MMAD was removed for another experiment that led to tissue growth. These results collectively show the stability of optical access with our design for several months and the modularity of our platform to test other recording and stimulation devices. In addition, our results caution that explantation and implantation of the MMAD must be minimized, because it is known that mechanical manipulation on the surface of the brain causes irritation of the cortical surface and can lead to accelerated tissue growth that obscures optical access.

CED during chamber implantation surgery, we used CED (similar to9,26,50,51) to infuse up to 50 µL of a pan-neuronal inhibitory optogenetic viral vector (AAV8-hSyn-Jaws-GFP, 5.4 × 1012 genome copies per milliliter (gc/mL))52,53 at several locations across the craniotomy (Fig. 3). We delivered viral vector at rates up to 5 µL/min using our custom-built stepped-tip cannula26. Further descriptions of parts, equipment, and protocols are provided in Methods.

We infused the optogenetic viral vector in the surgery suite immediately prior to chamber implantation. This allowed us to visually inspect any potential reflux on the surface of the brain from the cannula without live-MRI, which we had used in previous protocols. For our presented protocol, we had eleven successful and two unsuccessful infusions as determined by epifluorescent expression near the locations of cannula insertion. We canceled one infusion before its completion because the brain did not seal against the cannula and we observed fluid buildup, likely reflux (Fig. 3c, d). We reattempted that infusion nearby and successfully generated expression (Fig. 3d). In the first surgery (Monkey H), we had difficulty determining the depth of cannula penetration into the brain with stereotactic instruments alone because of the brain’s tendency to dimple during cannula insertion. To address this in our second surgery (Monkey L), we marked the cannula prior to surgery at a set distance distal from the cannula’s tip to facilitate measurement of penetration depth during surgery. This technique correlated with an improvement in success rate between our first and second surgeries (62% and 100%, respectively; Fig. 3c, d).

Our long-term and large-scale optical access provided by the MMAD empowered us to monitor optogenetic expression over time for both monkeys. Monkey H underwent initial imaging for epifluorescence two weeks after viral infusion. Expression was evident during the first imaging session and increased in coverage and intensity until the fifth week after infusion, when expression plateaued at 92 mm2 coverage (Fig. 3b, d). Similarly, we confirmed 76 mm2 expression coverage in Monkey L (Fig. 3d). Although we did not see a change in epifluorescent expression during the initial months following the plateau in viral expression area, approximately two years after infusion we observed a strong reduction of expression in both monkeys.

Photo-induced artifact removal
Our optical stimulation system generated artifacts in the ECoG data. To remove artifacts from ECoG data, we generated a dataset of artifacts, in the absence of any neural signals, by optically stimulating an MMAD submerged in a saline bath. We modeled the photo-induced artifact using these saline data, fit the model to the in vivo ECoG data, and removed the estimated photo-induced artifact (see Methods for details). The results demonstrate that the method effectively removes photo-induced artifacts (Fig. 4a). As a control, we tested the artifact removal method on data without stimulation and found that the method had negligible effect, as intended (Fig. 4b, c).

Stimulation at rest
To demonstrate our platform’s ability to integrate optogenetics and ECoG, we applied optical stimulation protocols (Fig. 5a, b) and recorded evoked neural activity. We removed photo-induced artifact as described above and in Methods. Statistical tests were run by comparing the neural activity to the baseline recording before the onset of stimulation (Bonferroni correction applied to p < 0.05).

We stimulated an opsin-expressing area of Monkey L during rest with one of the red LEDs of the 3 × 5 LED array (634 nm, 75 mW, 900 ms; Fig. 5a). The stimulation produced a significant increase in ECoG power across most frequencies and weaker effects persisted after the end of stimulation (Fig. 5a, c, e) probably due to spatiotemporal complexities of neural networks, including the possibly of rebound effects54. The effects of stimulation were similar but weaker at nearby electrodes (Fig. 5a, c, g, i) (0 mm vs 2 mm p = 7.7e–6, 0 mm vs 2 mm p = 4.6e−8). In addition to testing our LED array, we also tested traditional laser stimulation. We stimulated neural tissue of Monkey L with fiber optic cable connected to a laser (638 nm, 45 mW, 900 ms; Fig. 5b). Again, the stimulation produced a significant increase in ECoG power across high frequencies and weaker effects persisted after the end of stimulation (Fig. 5b, d, f). However, the persisting effects were more pronounced than with LED stimulation, likely due to the focal nature of collimated laser stimulation as opposed to the less focal, uncollimated LED stimulation. Effects were primarily local (Fig. 5b, d, f, h, j), which aligned with our expectation that laser stimulation would have a more focal effect than LED stimulation (0 mm vs 2 mm p = 5.5e−7, 0 mm vs 4 mm p = 1.2e−6). A similar experiment with Monkey H produced similar results (Supplementary Fig. 4).

However, we expected that inhibitory optogenetics would cause ECoG power to decrease in general, not increase. To validate the light-evoked responses observed, we have performed a series of control experiments described below.

We investigated the spatial nature of the neural responses with respect to opsin-expressing and opsin deficient areas (Fig. 6). To test the spatial nature of the neural responses, we stimulated all 16 red LEDs of the 4 × 4 array (634 nm, ~12 mW/mm2) during rest and separated recording channels based on the expression in their vicinity. A control animal, Monkey C, which had never been genetically altered, did not show statistically significant changes in neural activity (p = 0.53; Fig. 6d). For both optogenetic monkeys, ECoG power evoked by red LEDs was statistically stronger in the opsin expressing areas than the opsin deficient areas (Monkey H: p = 0.012; Monkey L: p = 8.3e−9; Fig. 6a, c). We repeated the experiment with sub-optimal stimulation techniques in Monkey L, being red LED stimulation with tissue growth over the brain and blue (485 nm) LED stimulation of a clear window, and found there was no significant difference between the opsin expressing and opsin deficient areas (tissue p = 0.47; blue light p = 0.90; Fig. 6c). Responses when optical access was clear produced significantly higher power in opsin expressing areas compared to conditions of tissue growth and the use of blue light (tissue p = 1.8e−4, blue p = 3.0e−59). Repeating the red light stimulation experiment with the full LED array and clear optical access in Monkey H ~2 years after initial infusion, when most of the epifluorescence had dissipated, produced no statistically significant changes from natural fluctuations in a baseline activity without optical stimulation (p = 0.76; Fig. 6b).

Comparing light-evoked responses from opsin expressing and opsin deficient regions across days yielded statistically significant differences in Monkey L (Fig. 6e). Note that after 540 days for monkey L and 686 days for monkey H we saw decreased expression as measured by both epifluorescence and insignificant light-evoked responses (H: p = 0.89, L: p = 0.92; Fig. 6e, f). We then reinjected 838 days after initial injection in Monkey L and 1,435 days after in initial injection in Monkey H (Fig. 6e, f) and generated approximately the same stimulation-evoked activity levels as the first injection in both opsin expressing and opsin deficient areas although with smaller expression regions (Fig. 6e, f). Collectively, the differences between light-evoked responses of opsin expression and opsin deficient regions, the light evoked responses after reinjection, and the lack of response in control experiments (a naïve monkey, tissue growth, blue light) support our finding that optical stimulation of neural tissue expressing Jaws increased ECoG power, despite Jaws being an inhibitory opsin. This increase could be due to disinhibition of neurons in lower cortical layers following inhibition of upper cortical layers—we reason the disinhibition is reflected in the ECoG signal through apical dendrites from the lower layers.

Given the increase of ECoG power when inhibition was applied in vivo, we examined the potential underlying mechanism by performing a simulation experiment, investigating the effect of stimulation across different cortical depths. We used VERTEX55, a simulation tool based on detailed cortical neuronal data56 used for modeling and simulating large-scale networks of neurons, which were recently updated to support optogenetic stimulations57. We found that pan-neuronal stimulation of Jaws-expressing neurons led to decreased spiking in upper layers (L2/3 and L4) and increased spiking in layer 5 (L5; Supplementary Fig. 5a, b). Similar changes are observed in local field potential (LFP) spectrograms from different cortical layers (Supplementary Fig. 5c). The observation of rebound effect in simulation also corroborates in vivo laser stimulation data (e.g., Fig. 5f), where neural responses can persist to some degree after stimulation terminates. These simulation results further confirm our hypothesis that inhibition of upper cortical layers generated disinhibition of neurons in lower cortical layers.

Stimulation during behavior
To demonstrate our platform’s applicability for behavioral neuroscience experiments, we trained the monkeys to perform a center-out reach task using their right hand (Fig. 7a) collecting data over multiple sessions (e.g., Supplementary Fig. 6). To begin, the monkey held his finger at a start target in the center of a screen, and then the end target displayed on the screen randomly in four locations: right, up, left, and down. We applied optical stimulation for 900 ms with all LEDs of our red 4 × 4 array (~12 mW/mm2) simultaneously for a randomly selected 50% of the trials with the expectation that optogenetic inhibition would impede reach. The onset of the stimulation aligned with the appearance of the end target. After a random delay, an audial “go-tone” would play, signaling the monkey to reach for the end target. Monkeys typically completed the reach before the end of stimulation.

Optogenetic inhibition led to significantly longer reach times in both monkeys (H: p = 0.04, L: p = 0.009; Fig. 7c, f); however, trajectories of the reaches during stimulated and non-stimulated conditions do not look qualitatively different (Fig. 7b, e). To better investigate these delays, we analyzed reach times for each movement direction individually (Fig. 7c, f). We found direction-specific effects in both animals. In Monkey L, reaches in the down and left directions were significantly impacted by stimulation (down p = 0.0001, left p = 0.03, up p = 0.33, right p = 1.0) (Fig. 7f). In Monkey H, significant delays were observed in the downward direction as well (down p = 0.03, left p = 0.23, up p = 0.99, right p = 0.13) (Fig. 7c). Additional analyses of path length were consistent with these findings (H all directions p = 0.40, down p = 0.04, left p = 0.35, up p = 0.08, right p = 0.32; L all directions p = 4.2e−6, down p = 1.1e−11, left p = 3.1e−5, up p = 0.45, right p = 0.71) (Fig. 7d, g).

We analyzed the neural activity recorded during reaches with and without optogenetic stimulation to identify the change in neural activity underlying the reach disruption (see Methods for details on the neural data analysis; data adapted from ref. 58). We plotted heatmaps of theta-band activity (4–10 Hz) during rest and during the planning phase of the task just before go-tone (Fig. 8a, b). The theta band is known to be reflective of behaviorally relevant cortical activity. We found that area 7 exhibits increased activity during the planning phase.

Next, we selected example electrodes in opsin expressing and deficient regions of area 7 and analyzed the signal during the planning period of the task with and without stimulation (Fig. 8c–e). To assess the changes in local activity of the selected electrodes, we analyzed high-gamma band activity. For both animals, both electrodes exhibited similar increases in baseline-normalized high-gamma-band activity during the task in the absence of stimulation. For each monkey, both electrodes had statistically significant increases in activity when stimulated (H expressing: p = 8.9e−29 deficient: p = 1.0e−5; L: expressing: p = 2.5e−114; deficient: p = 8.9e−13, Fig. 8f, g). Additionally, for both monkeys we found that the stimulation-evoked activity of the electrode over the opsin expressing area was more pronounced than the electrode over the opsin deficient area to a statistically significant degree (Monkey H: p = 2.8e−15; Monkey L: p = 8.9e−104), which was not the case in the absence of stimulation (Monkey H: p = 0.40; Monkey L: p = 0.08; Fig. 8f, g). These results support our finding that optical stimulation of neural tissue expressing Jaws increased ECoG power both during behavior and at rest (Fig. 6).

Methods
Multi-modal artificial dura (MMAD)
We embedded a multi-modal artificial dura (ECoG array), similar to past work41, into a traditional artificial dura (Fig. 1b). Briefly, the MMAD consisted of four conductive layers sandwiched between five transparent layers of medical-grade copolymer, where the conductive layers were aligned with each other to maximize optical access. Conductive layers were composed of platinum particles dispersed in a matrix within the polymer for mechanical flexibility. This design eliminated the need for attached printed circuit boards (PCBs), enabling long-term implantation without the challenges of protecting PCBs from moisture and fluids within the chamber. The MMAD was developed in close collaboration with Ripple Neuro (Salt Lake City, UT, USA), which manufactured the arrays. The company’s sales team may be contacted for ordering details.

A traditional artificial dura is typically described as “top-hat” shaped: a single silicone piece is composed of a cylindrical wall with an optical window at the lower end and a flange extending under the native dura to reduce regrowth of the native dura (Fig. 1b)24–26. Here, we embedded the MMAD into the artificial dura with a simple molding process40,42. The molded device is an artificial dura (skirt Ø: 31.2 mm; skirt thickness: 0.4 mm; wall outer Ø: 21.0 mm; wall inner Ø: 18.6 mm; height: 11.9 mm) with a fully embedded MMAD to allow for electrical recording and stimulation from 32 electrodes (Fig. 1b).

We designed the entire MMAD, including the cables, as a corrosion-resistant single piece. We housed the cables of the MMAD in the chamber between experiments, and during experiments, we attached the cables to the electrophysiological recording and stimulation hardware.

Chamber
The chamber is a cylinder (internal Ø 23 mm), 3D-printed and milled from titanium (Ti-6Al-4V, Hybex Innovations, Anjou, Quebec, Canada), which provides a sturdy base for experimental equipment and protect the brain when the monkey is freely moving between experiments, similar to previous work26. To design the chamber to fit the skull of each monkey, we developed a software pipeline (MATLAB, MathWorks, Natick, MA, USA; Solidworks, Waltham, MA, USA) to extract the skull curvature from an MRI file and then used the curvature to design a chamber with a unique skull-fitting skirt (Fig. 1a, c; Supplementary Fig. 7)39,40. We included an intra-cranial rim under the skirt (Supplementary Fig. 7) to aid in positioning the chamber on the skull during surgery and to reduce bone growth around the wall of the craniotomy, and included 12 holes in the skirt (Supplementary Fig. 7) for titanium screws (Crist Instrument Company, Hagerstown, MD, USA). We incorporated concentric tracks within the chamber to store the MMAD cables between experiments (Fig. 1b–d). We threaded the chamber with a high thread pitch (M38 × 1.5) to allow either affixation of experimental equipment or a cap to close the chamber between experiments (Fig. 1c; Supplementary Fig. 7).

Cap
We designed a cap (stainless steel 304, machined by Hybex Innovations) to close off the chamber between experiments. We applied polytetrafluoroethylene (PTFE) tape to the threads before each closure to prevent binding of the threads. We used a set screw (not shown) (HSS11400187HD, #4-40 × 3/16) to fasten the cap shut against the top rim of the chamber.

Electrophysiology hardware
Our electrophysiology setup included a ring, a clamp connector tray, and PCB clamp connectors (Fig. 1e, f). To prepare our platform for recording and stimulation, we screwed the ring onto the chamber and secured the clamp connector tray onto the ring with 2-4 screws (M2.5 × 6). The ring was machined from stainless steel (304; Hybex Innovations) and the clamp connector tray was 3D printed with titanium (TI-64; i.materialise, Leuven, Belgium).

The ring had 32 screw holes (M2.5) around its rim to offer optimal flexibility in the orientation of attachments. The upper face of the ring included a slight recess just above the threads for additional hardware to be easily aligned with the ring for fastening.

The bottom of the clamp connector tray included an intra-ring rim around the window to fit into the recess of the ring. The base of the tray included a right-angled outer rim for grounding electronics as well as four elevated screw holes (M2.5 or 4–40 thread) designed for optical stimulation equipment to be secured to the tray. We designed the tray to be compatible with both this work’s LED-based optical stimulation setup and our lab’s previously described fiber optic-based setup26. We designed the arms of the tray to be low weight and provide support for the MMAD cables as they extended from the artificial dura walls at 45°. The distal end of the tray arm was approximately 9.5 cm away from the cranial window.

The arms of the tray supported PCB clamp connectors (Fig. 1e, f; Ripple Neuro) held in place by rubber bands (not shown), which secured the MMAD cables approximately 4.5 cm away from the brain and provided an electrical connection between the cables and commercial neurophysiology equipment (Grapevine Nomad, Ripple Neuro). Two of these setups may be simultaneously deployed bilaterally, although this work is exclusive to the left hemisphere.

Optical stimulation hardware
To optically stimulate across large cortical areas (~1 cm2), we incorporated either a 4 × 4 or a 3 × 5 LED array (Fig. 2). The full 4 × 4 array was used for stimulation during reaches. To prevent LED arrays from moving when in use, we designed a system involving a rod, tube, coverslip, and stimulation holder (Fig. 1g). We custom designed and 3D printed the rod, tube, and stimulation holder in-house with FDM PLA (M2 rev G, MakerGear LLC, Beachwood, OH, USA). We glued (Better Ultimate Adhesive, slow dry, Cemedine Co. Ltd., Shinagawa City, Tokyo, Japan) the coverslip (Ø 16 mm, ORSAtec, Bobingen, Germany) to one end of the tube. The base, which we affixed to the clamp connector tray, secured the coverslip against the top side of the MMAD and a set screw (HSS11400187HD, #4–40 × 3/16) secured the rod inside the tube. The rod positioned the LED array over the brain and above the coverslip. Our setup created an air gap between the LEDs and the coverslip, which protected the brain from conductive heating. Four screws in the base secure the tube in place.

The LED array consisted of a circular custom rigid printed circuit board (PCB; Ø 15.5 mm; OSH Park, Portland, OR, USA). The LEDs (L1C1-RED1 or L1C1-BLU1, Lumileds, Schipol, Netherlands) of the 3 × 5 array were individually addressable, while the 4 × 4 array was wired to drive four individually addressable columns of LEDs. Both PCB versions included an internal copper plane for heat dissipation. We soldered the LEDs on one side of the PCB and a connector (501331-0807, Molex Inc., Lisle, IL, USA) on the other side. We drove the LEDs with a custom external PCB (OSH Park) connected to the LED array by a cable assembly (151330806, Molex Inc.). The external PCB consisted of voltage-controlled current sources. Each driving circuit consisted of a high output current op amp (TLE2301, Texas Instruments, Dallas, TX, USA) with a capacitor between the compensation network terminals and a resistor (15 Ω, 5 W, SMW515RJT, TE Connectivity, Schaffhausen, Switzerland), where the resistor value controls the ratio of input voltage to output current. The input voltage is provided by our neurophysiology system’s analog voltage output (Ripple Neuro) and is prevented from floating high (e.g., when the neurophysiology system is turned off) by a pull-down resistor (10 kΩ). We powered our PCBs with two in-series batteries (9 V Li-ion rechargeable, Keenstone, Industry, CA, USA) to reduce line noise in our electrophysiological recordings. We depict our circuit and arrays in Fig. 2 and Supplementary Fig. 1.

We also designed our clamp connector tray to be compatible with our previous laser stimulation setup30, and its slightly modified version is briefly described here. Our setup was composed of a base similar to the base for the LED array setup, and a stimulation ring, both FDM 3D-printed in-house with black PLA. The base was screwed to the clamp connector tray. The stimulation ring guided telescoping cannulas (HTX-13R, HTX-16T, and HTX-18T, Component Supply Co., Sparta, TN, USA) to different stimulation locations, and optical fibers were slid through the cannulas. We coupled lasers (520 nm or 638 nm, LDFLS_520_520_638_638, Doric Lenses, Quebec, Canada) to the optical fibers.

Animals
We recruited two healthy, socially housed male rhesus macaques (Macaca mulatta; Monkey H: 9 y, 13 kg; Monkey L: 9 y, 11 kg) for this study. Water was available ad libitum and standard food rations were provided after experimental sessions. All animal care and experiments were approved by the University of Washington’s Office of Animal Welfare, the University of Washington’s Institutional Animal Care and Use Committee, and the Washington National Primate Research Center.

Surgical procedures
We performed surgical procedures on both monkeys similar to procedures in other work26. We sedated the monkey and shaved its head before anesthetizing and head-fixing him in a stereotactic frame. The respiratory rate, heart rate, and body temperature of the monkey were monitored throughout the procedure. We created an incision several cm long to the left of the head’s midline and used elevators to peel back the skin, musculature, and muscle fascia. We confirmed the location of the center of the craniotomy with stereotactic coordinates. Using a Ø 25-mm trephine, we created the craniotomy. Then we resected the dura by lifting the dura with a curved needle and trimming with ophthalmic scissors, revealing the posterior parietal cortex. After test-fitting the titanium chamber to the skull, we placed a flat transparent silicone artificial dura on the brain to keep the brain moist.

With the craniotomy complete, we performed convection-enhanced delivery (CED) of Jaws (rAAV8/hSyn-Jaws-KGC-GFP-ER2, 5.4 × 1012 genome copies per milliliter (gc/mL), University of North Carolina Vector Core), a red-shifted inhibitory viral vector52. Prior to surgery, we had manufactured a 1-mm stepped-tip silica cannula (inner cannula: inner Ø 320 µm, outer Ø 435 µm; outer cannula: inner Ø 450 µm, outer Ø 673 µm; Polymicro Technologies, Phoenix, AZ, USA) for CED similar to our previous work26,51 by applying cyanoacrylate (superglue) to the inner cannula, sliding the outer cannula over the inner cannula, and using a razor blade to trim the inner cannula extending from one side of the outer cannula to make a 1-mm stepped-tip. We removed the artificial dura from the brain, punched a hole through the artificial dura to be used for our injection, laid the artificial dura back on the brain to keep the brain moist, and then inserted the cannula tip through the hole approximately 2 mm into the cortex (Fig. 3a, left) and began the infusion protocol using convection-enhanced delivery similar to previous work26. We infused up to 50 µL at each of several locations across the cortex. Once complete, we placed a new artificial dura on the brain.

Unlike previous work where live-MRI was performed during infusions26,50, we performed the infusions without live-MRI. This allowed CED to be performed in the surgery suite, while we were able to visually inspect the location of the infusion for any reflux. It also eliminates the need for MRI-compatible syringe pumps or complicated fluid line setups—the syringe and cannula were attached directly to the pump, and a stereotactic arm was used for cannula insertion during CED.

Following CED, we used a piezo-drill (5120063AS animal science package, insert tips IM1-AL and IM1S, Piezosurgery Inc., Columbus, OH) to drill screw holes and used titanium tap screws (Crist Instrument Company) to secure the chamber to the skull. We removed the artificial dura and placed the MMAD on the brain and housed the cables in the slots of the chamber (Fig. 1d). Finally, we applied PTFE tape to the threads, closed the cap, secured the set screw, and applied bone wax to the set screw. Having secured and closed the chamber, we closed the wound using standard surgical techniques.

We had implanted a titanium headpost (Crist Instrument Company) on each monkey prior to this study39.

Chamber cleaning and hardware assembly
We developed a process of cleaning the chamber at least three times each week, starting one week after the surgery. We briefly describe the processes here. After head-fixing the monkey, we cleaned the cap, chamber margin, surrounding scalp and outside of the ear. Once clean, we removed the cap and cleaned the margin. We used sterile cotton-tipped applicators dipped in saline to clean the threads and the rim of the chamber. To clean the inside of the chamber, we used a sterile syringe and blunt-tipped needle to irrigate warm sterile saline on and in the MMAD, its cables, and the storage area for the cables.

To prepare for electrophysiological recording, we screwed a sterile ring onto the chamber and screwed a sterile clamp connector tray to the ring with sterile screws. Then we removed the cables from the chamber and placed them into the clamp connectors, and rubber banded the clamp connectors to the clamp connector tray arms.

To prepare for optical stimulation, we attached the stimulation holder for either the LED array or the lasers. In the case of laser stimulation, we slid the stimulation ring down around the stimulation holder and inserted the fiber optic cable through the cannula and placed the cannula on top of the brain through the stimulation ring. In the case of LED stimulation, we assembled the LED array, rod, and tube with coverslip, and secured them together with a set screw. Then we lowered the assembly down through the stimulation holder and into the MMAD, and secured the tube into place with set screws. Black foil was wrapped around the stimulation equipment to prevent the monkey from seeing any lighting changes in the experimental rig due to stimulation.

When the experiment was complete, we removed the stimulation and recording equipment, cleaned the MMAD, and used sterile forceps to return the cables back into the chamber. Then we cleaned the chamber using sterile saline irrigation and applied an antibiotic to the center of the MMAD. To avoid building antibiotic resistance, we rotated through polymyxin B sulfate, gentamicin, and amikacin sulfate antibiotics, applying one for 4-5 weeks and then switching to the next. To prevent the cap from binding to the chamber between cleanings, we wrapped a strip of sterile PTFE around a portion of the threads. Then we screwed on a sterile cap and a set screw.

Epifluorescence imaging
We performed epifluorescence imaging of green fluorescence protein (GFP) by using a blue light for the excitation wavelength of GFP (NIGHTSEA stereo microscope fluorescence adapter, SFA-RB royal blue, Electron Microscopy Sciences, Hatfield, PA) in combination with a DSLR camera (Nikon D5300, Minato City, Tokyo, Japan) and a lens based on the emission wavelength of the GFP (Nikon DX AF-S NIKKOR 35mm 1:1.8G, SWM Aspherical ∞-0.3m/0.98ft Ø 52) for imaging. We illuminated the brain from multiple angles to fully cover the optical window. The camera was fixed throughout the illumination process, which eased stitching the photos together with image editing software.

Expression coverage was measured by outlining the extent of expression in the stitched epifluorescent image manually, counting the number of pixels within the outlined areas, and converting to mm2 based on known distances in the image, i.e., the distance between electrodes.

Behavioral task
Our center-out reach task (Fig. 7a) was controlled by custom software in MATLAB using Psychophysics Toolbox version 3123–125, similar to previous work126. A reflective sticker, placed on the middle finger of the monkey’s right hand, contralateral to the implant, was tracked by a motion capture system (Motive, OptiTrack, NaturalPoint Inc., Corvallis, OR, USA). These tracking data were processed in real-time by MATLAB. The monkey was rewarded for successful trials with juice (5-RLD-D1 D.A.R.I.S., Crist Instrument Company). The monkey was head-fixed and seated in a monkey chair inside a dark experimental rig. The visual and audio stimuli were provided by a monitor with built-in speakers within reaching distance of the monkey.

Monkeys performed several hundred trials each session (Monkey H: mean trials per session: 557.7, standard deviation: 217.6; Monkey L: mean trials per session: 715.7, standard deviation: 266.0). For Monkey H, there were 4522 analyzed reach trials split over 8 sessions, while for Monkey L there were 11,101 trials split over 13 sessions.

Behavioral analysis
We analyzed reaches from the behavioral trials. All successful trials from all sessions were labeled with reach direction (right, down, left, or up) and stimulation condition (stimulation or no stimulation). Data groups were compared statistically by Mann–Whitney U test of the distribution of reach times. Our experimental design focused on examining how stimulation would affect behavioral metrics, including reach time, path length and direction, which we carefully recorded. For these hypotheses, we did not adjust p-values as the nature of our analysis was not exploratory.

We tracked the reach path and reach time and analyzed movement in three-dimensional space for both stimulation and control (no stimulation) conditions. We measured the time between the go-tone and the finger’s entry into the end target, and we call this time the “reach time”.

Behavioral data preprocessing
All reach trials were aggregated over all dates and conditions for each monkeys individually. Trials were excluded from analysis if the reach was unsuccessful or if the trail was a warm up trial as judged from a wait time before the go-tone <0.3 s, or a circle size >50 pixels radius (approx. 25 mm diameter).

The neural data were screened to remove malfunctioning electrodes by measuring the impedance of the electrodes and by visual inspection of the voltage traces. Additionally, the standard deviation of the raw neural signal was computed for each trial, and if the z-score of the standard deviation was >6, the trial was excluded.

Neural data analysis
Neural activity was recorded during behavior and stimulation (1 kHz sampling frequency, Grapevine Nomad, Ripple Neuro). All neural data analyses were conducted separately for the two monkeys. High impedance electrodes were excluded from analyses.

The process involved segregating all trials into stimulation and non-stimulation trials. Each trial was then split into three epochs: before stimulation, during stimulation (or during when the stimulation would have occurred), and after stimulation. We analyzed 500 ms of local field potential (LFP) activity immediately preceding the onset of stimulation (“before stimulation”). The “during stimulation” period encompassed the 900 ms of LFP recorded during stimulation, and the “after stimulation” period covered the 900 ms following the end of stimulation. Artifact removal was applied to each epoch (see “Photo-Induced Artifact Removal” section below).

After removing photo-induced artifact, we quantified the effect of stimulation by analyzing the time-frequency content of the data. Multitaper spectrograms of ECoG data from each trial were calculated with 50-ms non-overlapping windows, five tapers and a 128-sample length Fast Fourier Transform (FFT) between 1 and 200 Hz. The values of each bin are normalized by the 500-ms pre-stimulation activity. The 50 ms immediately following the start and termination of stimulation are excluded from analysis to avoid including any residual artifact in the signal at these times.

To quantify the changes due to stimulation, we calculated the average values of the spectrogram per frequency bin. Spectrograms were normalized to the 500 ms preceding stimulation and the resulting values were used to determine if statistically significant changes were induced before, during, and after stimulation using the Mann–Whitney U test. For control experiments, the data processing matched the stimulated condition, although the stimulation did not occur.

Photo-induced artifact removal
To isolate photo-induced artifacts from the electrocorticography acquired during simultaneous optical stimulation in vivo, we generated a dataset of these artifacts, absent any neural signals, by optically stimulating an electrode array submerged in a saline bath. We modeled the photo-induced artifact using these saline data, fit the model to the in vivo ECoG, and removed the estimated photo-induced artifact. The procedure involved the following steps (Supplementary Fig. 8):

1. The time surrounding each stimulation in the saline data was isolated, from 100 ms before the onset of stimulation to one second after the end of stimulation. Each of the 32 channels were stacked with their 100 corresponding stimulation pulses to form a matrix (32 × 100 × length of time).

2. The matrix was split along the time axis into three matrices corresponding to before stimulation, during stimulation, and after stimulation.

3. The saline data at the time of stimulation onset and offset (data point time=0 for matrices “during stimulation” and “after stimulation,” respectively) were set to 0 mV and the whole traces were shifted accordingly.

4. Photo-induced artifact was modeled from these data using principal component analysis (PCA) conducted separately on the “during stimulation” and “after stimulation” matrices, with the top three components extracted from each.

This model was subsequently employed to eliminate the artifact from the in vivo data as follows:

5. The in vivo data were isolated and stacked in the same way as the saline data, such that a data matrix (channels × pulses × length of time), with identical time length, was formed.

6. The matrix was split along the time axis into three matrices corresponding to before stimulation, during stimulation, and after stimulation.

7. The ECoG data at the time of stimulation onset and offset (data point time=0 for matrices “during stimulation” and “after stimulation”) were set to 0 mV and the whole traces were shifted accordingly.

8. The ECoG data from the “during stimulation” and “after stimulation” matrices were projected onto the corresponding models derived from saline, and the estimated photo-induced artifact was regressed out of the NHP data using linear regression.

9. The three matrices were rejoined along the time axis, adding an offset to the later matrices such that the average LFP value of the last 50 ms of the preceding matrix and the first 50 ms of the later matrix had the same average value.

This procedure enabled the separation of the photo-induced artifact from neural activity, and retaining the neural activity in the recorded signal (Fig. 4; Supplementary Fig. 8), as confirmed by controls (Fig. 4).

Simulation
We simulated large-scale neural spiking activity and LFPs across cortical layers using the extended VERTEX model, which allows for optogenetic stimulation and neural activity recording57. The tissue model was 1.5 × 1.5 × 2.6 mm deep with LFP recording sites arranged in a 3 × 3 × 6 grid, and a 200 µm optical fiber placed orthogonally at the center of the cortical surface (Supplementary Fig. 9). We used the VERTEX Jaws opsin model, which hyperpolarizes neuronal membrane currents when optically evoked. Optogenetic inhibition was modeled with a train of optical pulses matching our experimental conditions (594 nm wavelength, 10 pulses, 900 ms on/2900 ms off). To examine local firing rates around the optic fiber, Supplementary Fig. 5a, b show neuron firing rates along the z-axis within a 400 µm cylinder around the optical fiber. Supplementary Fig. 5c shows the time-frequency spectrogram of the LFP recording sites centered in each layer.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "I enjoyed reading this manuscript by the Yazdan-Shahmorad group at UofWashington. The research details new\ntechnological developments on a cranial window that this group has been optimizing for several years. The cranial window\nallows a combination of techniques that together provide a powerful means of investigation of the primate brain. The platform\nallows for both optical imaging, electrophysiology, and optogenetic stimulation simultaneously. The authors demonstrate the\nability to conduct optogenetic stimulation using an array of LED lights that can be controlled individually. They also\ndemonstrate the ability of this LED stimulation in combination with opsin expression to alter motor behaviour in macaque\nmonkeys. I specifically note the efforts of the authors to make their hardware and software publicly available for the larger\ncommunity of researchers.\nI believe one of the main strength of this technique is the ability to observe the cortex, including its fluorescence, over the\ncourse of experiments. This allows confirming that the viral vector expression is successful and still active during\nexperiments. The authors did notice a change in opsin expression over time, which emphasizes the importance of this\nmonitoring. The main limitations of the paper are, in my opinion, linked to the electrophysiological and behavioural proof of\nconcepts, which are not perfect. However, I believe these limitations are more a function of the opsin (Jaws) they chose for\nthose proofs of concept rather than the hardware they are presenting as the main purpose of this manuscript. I have only a\nminor concerns below.\npage 3, 3rd paragraph: Merging of optogenetic and electrical (recording) platforms ...\np.4, 3rd para: disrupting a center-ou(t) reach task\np5. 2nd para: \"The MMAD, as well as the commercially available electrode array (Ripple Neuro, Salt Lake City, UT)\". I could\nnot find the MMAD on the Ripple Neuro website. Can you please add details on how to obtain this product in the Methods?\np7, Fig.2A: Consider rotating middle left subpanel 90° to be consistent with top view\np7, \"Optical Stability\": The optical stability section is an important section that, unfortunately, lack supporting images and\nfigures. I would appreciate to see pictures of the experiments described in this paragraph to let the readers understand the\nissue of tissue growth better, including it’s speed. Could some metric of “opacity” could be derived quantitatively from the\npictures? It would be nice to show this metric over time following implantations/explantations of MMAD.\np8, 2nd para: \"optogenetic viral vector (AAV8-hSyn-Jaws-(*GFP*))\" .\nI understand more details are in the STAR methods, but it would be nice to include the total volume injected at each site, and\nthe viral solution titter in the main text.\np8, 3rd para: \"eliminating the need for live-MRI,\" . To be fair, the use of MRI is not just to monitor reflux, but also to confirm\nvolume of diffusion live and targeting accuracy. Please nuance this statement.\nI did not see a reference to Fig. 3A in the text.\np8, 4th para: \"two years after infusion we observed a significant reduction of expression in both monkeys (data not shown).\"\nThis is a very important information only available to authors using this technology. I strongly encourage adding some data\non this in the Supplement.\np10, 2nd para: \"We observed increased ECoG power with the control wavelength (Fig. 4D, M), but to a significantly lesser\nextent than our standard wavelength \" : I am not convinced by that test, since I do not know what was the response expected\nto blue light for this specific opsin. Should it be zero? If so, this would suggest that the effects observed are heat-driven, or\nother artefacts.\n\"This suggests ECoG responses are primarily optogenetically-evoked, and not thermally-evoked\" : Does blue light really\ngenerate the same amount of heat artefacts? A more thorough test would be to stimulate over a non-transduced area to see\nif heat is a culprit. (I can see the authors did that in the next figure)\nAlso, what to make of the different effect of light stimulation as a function of frequencies between the blue and red light?\n(especially in lower frequencies)\np10, 5th para: \"For both monkeys, ECoG power evoked by red LEDs was stronger in the expressing areas than the opsin\ndeficient areas\" Shoudn’t we expect to see “no” response in opsin free areas? What might be causing this residual\nresponse?\n\"where there was no significance between the opsin expressing and opsin deficient areas \" This was not clear from reading\nthe previous section. I saw no mention to this comparison. I think this should be represented clearly, as it comes as a\nsurprise reading this sentence here.\nFig 4. Resolution of this figure is insufficient given size of font. This may be an error in format conversion.\nPlease better represent on this figure the light stimulation period and frequency over time with a coloured bar above the plots\nFig 5 legend: \"recordings from during verses before stimulation\" : Unclear what is meant here.\nP12. first para: \"red 4 × 4 array (~12 mW/mm2) simultaneously\" : This power information should also be written for the above\nexperiments.\np14, first para: \"frequency bins exhibiting significant (Bonferroni correction applied to p < 0.05) modulation from stimulation\".\nI don’t remember seeing a multiple comparison correction for the previous analysis in Fig 4. And is the highly restrictive\nBonferroni the most appropriate correction for this study? I personally prefer FDR correction for those analyses.\nNo in-text reference to Fig 7A-C\nFig 7: Please add references to onset/ of reaches in the plot.\np15, first para: \"and efficient viral vector delivery without live-MRI monitoring\" It’s not clear how this technology enables\ndoing a CED injection without MRI. Could anyone just stick a needle inside a craniotomy and inject CED, even without this\nplatform? If your technology assists with needle placement and stability, or reflux monitoring, then I think it is a better selling\npoint.\np16, first para: \"with traditional window-less approaches, like Utah arrays\" I recommend citing the latest Angelucci Opto-\nUtah Array paper.\n\", is much more challenging in comparison to our window-based method. \" I am not sure this is a fair comparison. I can think\nof several ways in which a fully closed approach is safer and easier… (e.g. infection risks, human translation). Maybe the\nmain selling point of your approach is the constant visualization and monitoring, including with ephys, of the tested sites?\np16, 4th para: \"Early works attempting to integrate electrode arrays and large-scale optical windows did not result in long-\nterm optical access \" I would like to see data about pressure on the cortex caused by the window, and related depression,\nas shown in Yazdan, Neuron 2016. Has this been resolved?.\nI also do not see any histological data in this paper. I assume the NHPs are still alive and performing tasks? Previous papers\nfrom this group included much useful histological verification. This would be even more useful in this case given the strange\nbehavior of the Jaws opsin on ephys (excitation rather than inhibition, positive effects even on non-transduced sites).\nThoughts: Jaws is a very sensitive opsin. Could the positive effects even on non-transduced sites be a result of stimulation\nof nearby transduced sites by distant LEDs? Even a small amount of light could trigger those distant sites, and through\nnetwork effects, influence ephys readings at the stimulated, non-transduced site? Is it possible to run some tests in a non-\ninjected monkey?\nIs it also possible that epifluorescence is not a perfect indicator of transduced vs non-transduced sites? Maybe at sites where\nepifluorescence is not visible (at the threshold used), there are still a number of neurons or axon terminals expressing the\nJaws opsin?\nOverall, great study combining cutting edge optogenetics and clever hardware developments that are much needed to boost\ncausal, cell-type specific neuro research in the primate brain. Looking forward to the revised paper.", "reviewer_2": "The manuscript by Griggs et al. presents a cost-effective and scalable platform capable of multimodal optogenetic and\nneurophysiological studies in behaving macaques positioned in a primate chair. In contrast to other published macaque\nchamber-mounted systems, the key advances of this platform include its scalability, the integration of LFP/ECoG capabilities\ninto the artificial dura (the MMAD), and its ability to perform patterned optogenetic stimulation. The authors demonstrate the\nsystem’s functionality by showcasing its capability to monitor epifluorescence (optogenetic expression) over several months,\nas well as its ability to modulate LPFs and reaching behavior through optogenetic stimulation. I commend the authors for\nacknowledging that the clear view of the brain through the artificial dura typically lasts only a couple of months, after which a\ntissue removal procedure is required to regain visual access for further studies. While this limitation, along with others (e.g.,\nrisk of infection, optogenetic light artifacts in neurophysiological signals, and the focus on surface-level recordings),\nconstrains its ability to fully reveal the circuitry underlying behavior, the utilization of this platform can set the stage for\nsignificant advancements in primate cognitive neuroscience.\nMajor Comments\n(1) Reproducibility of results across days is not addressed in the manuscript. This is true for (a)\nepifluorescence, since only the collection but not quantitation was described in the Star Methods; (b) consistency of the\noptical window, since alignment procedures for the FOV, blood vessel changes across days and weeks (e.g. Figure 3 top row)\nwere not discussed; (c) LFP signals, in Figure 4 it is unclear as to the sample size of the LFP data (e.g. number of trials),\nlet alone whether it was collected across multiple days or weeks); (d) behavioral measures, how consistence were the effects\nof optogenetic stimulation on behavior across days.\n(2) Information provided in Supp Figure 5 on the removal of light-induced artifact should be promoted to the main manuscript.\nWith modeling, could the onset 50ms and offset 50ms LFP, discarded in subsequent analyses, be recovered as suggested\nby Supp Figure 5D?\n(3) A briefer summary of the behavioral results (Figure 6). Reducing even further the behavioral data would help focus the\nmanuscript onto the device. Actually, once the behavioral data was introduced, this reader was looking for a more in-depth\nanalysis and interpretation of those results (as well as wondering about the next obvious experiments that must have been\nperformed) than that provided in the manuscript and supplemental materials. For instance, examining the effects on behavior\nof varying the pattern targeting different functional cortical areas (or amplitude or duration or timing) of optogenetic\nstimulation would have really brought home the utility of the large-scale platform.\n(4) With the usage of the term ‘optical imaging’ this reader expected that functional intrinsic optical imaging would be one of\nthe major modalities of this large-scale platform. Instead, what is advanced here is visual access to the surface of the brain\nunder the term of ‘optical imaging’. The authors should clarify this distinction early on and suggest (e.g., in the Discussion)\nthat intrinsic optical imaging, combined with behavioral studies, is feasible with the current platform—though without the\nother modalities, as the hardware for those may interfere with intrinsic optical imaging.\nModerate and Minor Comments:\n(1) Figure 1D. Please provide a mm scale bar to Figure 1D. This will provide to the reader a good reference of the sizes of the\noutside of the chamber and area of surface of the brain available for study. This will also allow the reader to appreciate the\nspace dedicated to store the ECOG cabling.\n(2) The assembly of the LED array was designed to minimize conductive heating of the brain. However, the manuscript did\nnot report the actual heat transfer with typical full array LED stimulation through the cover glass or through the MMAD,\ngauging the success of these efforts. Thus it is unclear whether without obvious airflow that an Air Gap was effective.\n(3) The manuscript reports chamber stability for 2-3 years, with MMAD re-implantations for additional experiments. However,\nit is unclear if the chamber remains in use or has been removed. Clarifying whether the chamber is still in use or has been\nremoved would help the reader understand the platform’s longevity and suitability for even longer-term studies.\n(4) Figure 4. Upon printout (this reviewer still works with hard copy), the small font size of Figure 4 was unreadable. Please\nreformat Figure 4 so it can be reproduced nicely on the printed page.\n(5) Results related to Figure 4. Data from Monkey L. How many ECoG sites were included in this data set? Were both opsin\nexpressing and opsin deficient sites included? How many stimulation trails were included? Were similar findings obtained\nfrom Monkey H. May I recommend reporting the statistics throughout the manuscript using the APA Style Guidelines.\n(6) Results related to Figure 4D. The manuscript reports a red LED energy of ~12 mW/mm2, but does not report the energy\ndirected towards the brain for either the red laser or blue (485 nm) LED. Without information on the Blue LEDs and the\nabsorption spectrum of the JAWs opsin for these two wavelengths, it is difficult for the reader to assess whether the\ndifferences in PSD power observed in Figure 4D are smaller than expected based on theoretical modeling. In other words, it\nis unclear whether or not the blue LED sub-optimally drives the JAWs opsin.\n(7) Results related to Figure 4G-O. The Spectrograms show an increase in activity during the 900 ms after stimulation offset\nrelative to the 500 ms of pre-stimulus activity. This apparently interesting long-lasting effect of stimulation though shown in\nFigure 4D was not discussed in the Results. Also, what is the authors’ interpretation of the relatively uniform increase in\nactivity across frequencies?\n(8) Results related to Figure 4I. The Frequency spectrogram suggests the duration of laser stimulation lasted about 150 ms\nlonger than the targeted 900 ms for the LEDs. Could this have happened? If not, the authors should make an account for the\nlaser eliciting a longer lasting response than the LED.\n(9) Results related to Figure 4D-E-F. The Median PSD Ratio y-axis scale is not linear (and not a standard log scale);\nwhereas the Power ratio is graphed linearly in Figure 5CD. Is that non-linearity intended? If yes, what is that scaling?\n(10) Results related to Figure 4E-F. The 95% CI of the medians in some instances fall below a ratio of 1. Is this valid?\n(11) Results related to Figure 4 (and Figure 5 data). What was the interstimulus interval?\n(12) Figure 5. Legend title: “Map of neural responses…” is inaccurate as the locations of the ECoG recordings are not shown\n(as in Supp Figure 2).\n(13) Results related to Figure 5CD. How many trials and ECoG sites were used to generate these graphs, and over what\ntime period? Additionally, in this figure, the whiskers represent the standard error of the mean, while in Figure 4, whiskers\nrepresent 95% confidence intervals. What is the reason for this inconsistency between Figures?\n(14) Behavioral task. What was the size of the target windows and distance in cm between the start and end targets? Maybe\nadd a cm scale bar to Figure 6A, B, or C.\n(15) Behavioral task. The reporting of some of the statistical results might be questioned. For instance, this reader questions\nthe validity of reporting the last decimal places of some of the values. For example, ‘total: p = 0.0001560’, should the reader\nplace any credence in the last ‘560’ or is that just a computer output without validation of the number of significant digits that\nshould validly be reported? Again, may I recommend reporting the statistics according to APA Style Guidelines.\n(16) Results related to Figure 6. Given the focus of the manuscript, this Figure in this reader’s opinion seemed a little overkill\nand difficult to interpret during the presentation of the Reach Times (Figure 6F-G). Since Path Lengths (Figure 6D) and reach\nonsets seem to be the major variables affected by optogenetic stimulation, maybe just present those results in the main\nmanuscript.\n(17) Results related to Figure 6. “Whiskers are described as representing the standard error of the mean, and asterisks\ndenote p < 0.05 using a Mann-Whitney U-test”. Since the Mann-Whitney U-test is a non-parametric test used to assess\nsignificant differences between two independent, non-normally distributed groups, why are means, rather than medians and\nconfidence intervals, presented in the graphs? Alternatively, if the data groups are normally distributed, why weren’t t-tests\nemployed instead?\n(18) Results related to Figure 7. Again, how many trials and ECoG sites were used to generate the graphs in panels D and\nH? The whiskers are described as representing 95% confidence intervals of the average, but they appear quite small for\n95% CIs. Is this correct? Additionally, why was there a switch to a.u. for Average Power? If th reason for this was mentioned\nin the manuscript, it may have been unclear to this reader.\n(19) The manuscript’s usage of ‘slow reach’ reads awkwardly to this reader. My general interpretation of this word pairing is\nthat the actual movement is slower (e.g., like a sloth). Instead, based on the presentation of the results it appears (but I could\nbe mistaken) that reach onset and reach trajectory lengths were affected by the optogenetic stimulation (and not movement\nvelocity). Thus the usage of ‘slow reach’ is not ideal.\n(20) The manuscript emphasizes that previously published CED protocols relied on MRI to monitor infusions, whereas this is\nnot required with the current platform. However, aside from visual inspection of the surface, there is a noticeable lack of\nsubsequent monitoring of CED infusion, as indicated by the few failed attempts reported. In this reader’s opinion, this\ndifference in the CED protocol is relatively minor and does not represent a significant advancement as advocated for in the\nmanuscript (I would tone that down).\n(21) Discussion. The manuscript reports an unexpected increase in ECoG power during optogenetic stimulation with an\ninhibitory opsin. A more in-depth discussion of possible reasons for this observation is warranted. Similarly, given the\nbehavioral results, a more in-depth discussion on these outcomes would be anticipated given the suspected roles of area 5\nand area 7 in reaching behavior.\n(22) Discussion. Upon a single reading, it seemed to this reviewer that there were sentences/paragraphs in the Discussion\nthat were nearly identical to those written either in the Introduction or Results. Please revise/edit accordingly to reduce such\nrepetition.\n(23) Supp Figure 2D. Again, why was a Mann-Whitney U-test used if means and standard errors are being graphed (see\nprevious comment)? Again, how many trials and ECoG sites were used to generate these graphs? Graphing such small\nstandard errors is far less informative to the reader than 95% confidence intervals would be. Were similar findings seen for\nMonkey H?\n(24) Supp Figure 3. Am I correct in assuming the results for the 4-arrow symbol (top row) is the vector sum of the individual\nreach directions (next 4 rows)? If that assumption is true, then for Monkey H for the y-dimension there appears to be\nsomething way off. Same for Monkey L.\n(25) Supp Figure 5. Shouldn’t Suppl Figure 5 E-F lower graphs (after artifact removal) be identical to graphs Figure 7E and\nFigure 7F? They are similar but also different in visually significant ways, even when one takes into account the different\nscale for Suppl Figure 5F.\n(26) Supp Fig 5A: What was the source of the LFP time courses (n=13)? Were they from a single animal, a single trial, or\naveraged over multiple trials? What was the experimental session type, and were the time courses located over opsin-\nexpressing or opsin-deficient sites? Additionally, for all the analysese, were certain ECoG sites preferentially included or\nexcluded, and if so, what criteria were used for selection? Finally, was the goodness of fit of the regression used to evaluate\nthe effectiveness of photo-induced artifact removal for individual ECoG sites?\n(27) Supp Fig 5C. Please also show the ‘fit’ during the after-stimulation period as well.\n(28) Figure 6 and Supp Fig 3: Given the large number of null hypotheses tested, there is a risk of Type 1 statistical errors.\nPlease ensure appropriate corrections are applied to account for multiple comparisons.\nTypos:\n1. Page 4, line 31: “center-our reach task” – should be “center-out reach task”.\n2. Page 10, line 25: \"it’s compatibility with lasers\" –should be \"its\".\n3. StarMethods: Resister – should be resistor?\n4. StarMethods: “Christ Instruments” – should be” Crist Instrument Company”.\n5. Term ‘LED’ is not defined.", "reviewer_3": "The manuscript presents a comprehensive account of a large-scale optogenetic neurophysiology platform designed for non-\nhuman primates (NHP) and illustrates its application in a behavioral study. While the organization and clarity of the\nmanuscript are commendable, I have considerable reservations about the novelty and scientific importance of this work,\nparticularly in relation to its potential publication in Nature Communications.\nOne of the main challenges facing optogenetics in primate research is the effective outcome of behavioral manipulation,\nespecially regarding motor actions. In its current form, the study utilizing the assembled platform does not significantly\nadvance this field. Although it shows some impact on reaching behaviors, I question the practicality of the platform as\npresented, regardless of its apparent complexity.\nFurthermore, if the objective is to utilize this device for exploring the neural mechanisms behind specific cognitive functions\nor understanding network dynamics, the existing design offers no distinct advantages over current technologies. The ECoG\narray is limited to capturing local field potentials, and the extensive LED array suffers from inadequate spatial resolution and\nsubstantial interference artifacts. Together, these limitations render the system less appealing.\nTo enhance the design, I propose the following suggestions:\n1. Consider replacing the LED array with a micro-LED array to improve spatial resolution (doi.org/10.1038/s41592-021-\n01238-9). This micro-LED array could be programmed for high temporal resolution, theoretically producing lower artifacts\nand thereby increasing the likelihood of capturing transient changes in neural activity. Additionally, implementing an LED\narray with dual wavelengths could facilitate simultaneous activation and deactivation using one device.\n2. I recommend mapping the finger and arm zones prior to light stimulation. Random stimulation tends to be less effective in\neliciting behavioral responses. I encourage the authors to adopt a different strategy: record neural activity during reaching\ntasks across a broad cortical area, and subsequently program the micro-LED array to illuminate the brain in alignment with\nthe recorded activation patterns. Given that these patterns will vary in both space and time, mastering the programming of\nthe LED array is crucial.\nSpecific concerns include:\n1. I find the rationale behind the unexpected increase in ECoG signals unconvincing. A straightforward verification could be\nconducted through single-unit recordings.\n2. Although the authors conducted control experiments to indicate that responses were largely optogenetically induced, they\nwere unable to completely eliminate the thermal effects. Therefore, an additional control trial involving non-expressing\nmonkeys (or the same monkey before viral injection) remains necessary. While I acknowledge the associated challenges,\nthe experiment, as it stands, lacks thoroughness.\nTypos:\nline 94: accessibly->accessibility\nline 112: center-our->center-out", "reviewer_4": "Griggs and colleagues present an integrated optogenetic and electrocorticography (ECoG) platform designed for use in\nmacaques. This is an impressive technical achievement, combining optogenetic modulation with large-scale neural\nrecordings. While similar techniques have been proposed individually or with more complex approaches, this tool seems\nrelatively straightforward to implement in a lab with enough technical expertise. I highly commend the authors for developing\nand utilizing such an innovative piece of technology. I’m convinced many will be interested in these tools.\nHowever, I find myself less convinced by the neuroscientific aspects of the manuscript. As the authors themselves highlight,\nit is puzzling to observe a net increase in LFP power following Jaws stimulation. While optogenetic stimulation with a\nhyperpolarizing opsin is known to induce a mixture of inhibitory and excitatory effects at the single-unit level, population-\nlevel effects should generally lead to net inhibition. The weak behavioral effects observed also suggest that the output of the\nstimulated region might be slightly reduced, which contradicts the observed increase in LFP power. In my view, this\nunexpected result warrants further explanation and exploration. Given the substantial light-induced artifacts observed in\nsaline (Fig. S5), I am still uncertain whether these effects are truly neuronal, despite the authors’ counter-arguments.\nI was surprised that the authors averaged their results across all ECoG channels (Fig. 4 G-O; 7). Surely, in Figure 5, they\ndistinguish between transduced and non-transduced sectors. I recommend that they apply a similar analysis based on the\nfunctional properties of the cortex under the electrodes. For example, by using task-induced neuronal activity (such as\nreaching-related activity) from both transduced and non-transduced areas, they could define regions of interest (ROIs)\nacross 4 different cortical regions (transduced or not, functionally relevant or not). This would allow for a more refined\nanalysis of the data.\nMoreover, it would be valuable to replicate these experiments using a penetrating electrode (e.g., a laminar probe) to\ncompare the surprising ECoG data with single- or multi-unit recordings, providing additional insight into the neuronal effects.\nIn summary, this is a highly interesting technical paper that somehow should be published, but I believe it should be\nconsidered for its methodological contributions rather than its neuroscientific conclusions. As such, I am presently\nunconvinced it is suitable for publication in Nature Communications. IMHO, a more thorough investigation of the neuronal\nand behavioral effects (see below) is warranted, but I refrain to the editors to make that call.\nMinor Comments:\n1. Method Limitations: The authors highlight the advantages of their new method but should also mention its limitations. For\nexample, the method is limited to recording from superficial, easily accessible parts of the cortex and cannot capture data\nfrom structures buried in sulci or from deeper cortical areas that are not accessible with the current setup. Surely, more\nlimitations can be listed.\n2. Neuronal Data with Dura Resection: The authors mention that their MMAD allows recording for 10-14 weeks, after which\ndura growth requires resection. While stability of GFP expression is clearly illustrated in Figure 3, it would be informative to\ninclude raw neuronal traces for the same periods, along with both GFP and neuronal data after multiple dura resections\n(e.g., approximately 2-3 years post-implant).\n3. Figure 3C: This figure requires more explanation. It is unclear what point the authors are trying to make, and further\nclarification would be helpful.\n4. Figure 4: The fonts and arrowheads in this figure are barely visible. Please increase their size for better clarity.\n5. Figure 4 Statistical Analysis: I suspect the statistics in Figure 4 use a Wilcoxon signed-rank test. It is unusual to observe\nsignificant changes in the pre-stimulation period. Was a correction for multiple comparisons applied? If not, this should be\ndone. If a correction was applied, could the authors explain the pre-stimulation differences?\n6. Non-Neuronal Effects: The authors argue that the ECoG responses are “primarily” optogenetically evoked (non-thermal).\nHowever, control experiments indicate substantial non-neuronal effects. Can the authors estimate the contributions of these\ntwo effects (neuronal vs. non-neuronal) to the observed in vivo data?\n7. Behavioral Data Statistical Analysis: Was a correction for multiple comparisons applied to the behavioral data? If not, I\nsuggest this be done to ensure the robustness of the results.\n8. Spatially-Specific Behavioral Effects: I was surprised by the lack of consistent spatially-specific behavioral effects. How\nreliable were these effects across sessions or across trial blocks within the same session? Test-retest reliability should be\nshown to strengthen the findings.\n9. Figure 6 Significance Indicators: The asterisks indicating significance in Figure 6 do not always match the descriptions in\nthe text. Please check for accuracy. Were all trials included in the analysis for this figure?\n10. Figure 7: As mentioned earlier, it would be highly informative to show time-frequency plots for four different electrode\nsites (transduced vs. non-transduced and task-modulated vs. non-task-modulated sites).\n11. Interpretation of Reaching Behavior: The authors interpret the stimulation-induced changes in reaching behavior as\nchanges in motor dynamics. However, this region of the parietal cortex is involved in a variety of interrelated functions,\nincluding but not restricted to e.g. attention, multisensory integration, and decision-making. How do the authors disentangle\nthese contributions from the motor changes observed in the reaching task?", "reviewer_5": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature\nCommunications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career\nResearchers who co-review manuscripts."}, "author_response": "RESPONSE TO REVIEWER COMMENTS (responses in italics)\nWe thank the Reviewers for their thoughtful and constructive feedback. We have incorporated the\nmajority of their suggestions, and we believe the manuscript has significantly improved as a result.\nIn response to the comments, we collected substantial additional data from previously used animals as\nwell as from a naïve animal, and performed further electrophysiological analyses. We also restructured\nthe manuscript to better highlight the versatility of our platform and refined the presentation of our\nbehavioral data. Additionally, we conducted a comprehensive neural simulation analysis to further\ninvestigate the effects of stimulation on cortical layers.\nOur point-by-point responses to the Reviewers’ comments are provided below in italics.\nReviewer #1 (Remarks to the Author):\nI enjoyed reading this manuscript by the Yazdan-Shahmorad group at UofWashington. The research\ndetails new technological developments on a cranial window that this group has been optimizing for\nseveral years. The cranial window allows a combination of techniques that together provide a powerful\nmeans of investigation of the primate brain. The platform allows for both optical imaging,\nelectrophysiology, and optogenetic stimulation simultaneously. The authors demonstrate the ability to\nconduct optogenetic stimulation using an array of LED lights that can be controlled individually. They also\ndemonstrate the ability of this LED stimulation in combination with opsin expression to alter motor\nbehaviour in macaque monkeys. I specifically note the efforts of the authors to make their hardware and\nsoftware publicly available for the larger community of researchers.\nI believe one of the main strength of this technique is the ability to observe the cortex, including its\nfluorescence, over the course of experiments. This allows confirming that the viral vector expression is\nsuccessful and still active during experiments. The authors did notice a change in opsin expression over\ntime, which emphasizes the importance of this monitoring. The main limitations of the paper are, in my\nopinion, linked to the electrophysiological and behavioural proof of concepts, which are not perfect.\nHowever, I believe these limitations are more a function of the opsin (Jaws) they chose for those proofs\nof concept rather than the hardware they are presenting as the main purpose of this manuscript. I have\nonly a minor concerns below.\nWe thank the Reviewer for their enthusiasm about our paper and below have responded to their\ncomments.\npage 3, 3rd paragraph: Merging of optogenetic and electrical (recording) platforms ...\nWe have made the suggested improvement.\np.4, 3rd para: disrupting a center-ou(t) reach task\nIt is corrected.\np5. 2nd para: \"The MMAD, as well as the commercially available electrode array (Ripple Neuro, Salt Lake\nCity, UT)\". I could not find the MMAD on the Ripple Neuro website. Can you please add details on how to\nobtain this product in the Methods?\nTo address this comment, we added a recommendation to contact the sales team for ordering\ndetails.\np7, Fig.2A: Consider rotating middle left subpanel 90° to be consistent with top view\nIt is corrected.\np7, \"Optical Stability\": The optical stability section is an important section that, unfortunately, lack\nsupporting images and figures. I would appreciate to see pictures of the experiments described in this\nparagraph to let the readers understand the issue of tissue growth better, including it’s speed. Could\nsome metric of “opacity” could be derived quantitatively from the pictures? It would be nice to show this\nmetric over time following implantations/explantations of MMAD.\nTo address this comment, we have included example images demonstrating optical stability over\ntime (Supp. Fig. 3). While we are currently unable to provide a quantitative measure of opacity\ndue to day-to-day variations in lighting conditions (Supp. Fig. 3), we present daily light-evoked\nresponses to optogenetic stimulation as a proxy for assessing optical access (Fig. 6).\np8, 2nd para: \"optogenetic viral vector (AAV8-hSyn-Jaws-(*GFP*))\" .\nIt is corrected.\nI understand more details are in the STAR methods, but it would be nice to include the total volume\ninjected at each site, and the viral solution titter in the main text.\nWe have added the information as suggested.\np8, 3rd para: \"eliminating the need for live-MRI,\" . To be fair, the use of MRI is not just to monitor reflux,\nbut also to confirm volume of diffusion live and targeting accuracy. Please nuance this statement.\nWe have revised the text (in paragraph 2 of 'CED and epifluorescence' and elsewhere) to clarify\nthat live MRI was not used in this study. To further refine this point, we now reference our\nprevious work, which outlines a comprehensive bench-side technique for modeling the CED\ninfusion profile prior to surgery [1]. This method, informed by prior MRI-based infusion data and\ncomplemented by our ability to visualize reflux during surgery, highlights the broader\napplicability and accessibility of our approach—even without the use of live MRI (see Discussion,\nparagraph 7).\nI did not see a reference to Fig. 3A in the text.\nWe have improved our figure callouts in the text accordingly.\np8, 4th para: \"two years after infusion we observed a significant reduction of expression in both\nmonkeys (data not shown).\" This is a very important information only available to authors using this\ntechnology. I strongly encourage adding some data on this in the Supplement.\nWe have added the data to show both the reduction of expression as well regain of expression\nafter re-injection (see Figure 6).\np10, 2nd para: \"We observed increased ECoG power with the control wavelength (Fig. 4D, M), but to a\nsignificantly lesser extent than our standard wavelength \" : I am not convinced by that test, since I do not\nknow what was the response expected to blue light for this specific opsin. Should it be zero? If so, this\nwould suggest that the effects observed are heat-driven, or other artefacts.\nBlue light can activate Jaws, but significantly less effectively than red light. For instance, as\nreported by Chuong et al. [2], 635 nm (red) light generates approximately twice the photocurrent\ncompared to 485 nm (blue) light. Therefore, while sufficient blue light can evoke neural\nresponses, they are expected to be weaker than those produced by red light. Moreover, blue light\npenetrates tissue less efficiently than red light and likely induces more localized heating. If\nthermal effects were the dominant mechanism, we would expect blue light to produce stronger\nneuronal responses. However, our data show that red light elicits greater neural activity than\nblue light (Fig. 6C), supporting our interpretation that the responses are primarily\noptogenetically, rather than thermally, driven. To improve clarity, we have relocated the blue\nlight stimulation data to Fig. 6 and revised the text accordingly, adding relevant citations in\n“Stimulation at rest” (paragraph 4) and the “Discussion” (paragraph 11). In addition, our bench-\ntop temperature measurements show that the change in temperature resulting from our\nstimulation is less than 1°C (Supp. Fig. 2), which is below the reported threshold for neural\nactivation [3], [4].\n\"This suggests ECoG responses are primarily optogenetically-evoked, and not thermally-evoked\" : Does\nblue light really generate the same amount of heat artefacts? A more thorough test would be to\nstimulate over a non-transduced area to see if heat is a culprit. (I can see the authors did that in the next\nfigure)\nTo address this comment, we revised Figure 6C to better highlight the responses in opsin-deficient\nareas, which may reflect heat-related artifacts. As shown in Figure 6C, blue light stimulation\nelicits similar responses in both opsin-expressing and opsin-deficient areas, with no statistically\nsignificant difference between them. Additionally, blue light and red light stimulation produce\ncomparable responses in opsin-deficient areas, but not in opsin-expressing areas without tissue\novergrowth. In addition, our bench-top temperature measurements show that the change in\ntemperature resulting from our stimulation is less than 1°C (Supp. Fig. 2), which is below the\nreported threshold for neural activation. These findings further support the notion that the\nobserved effects in opsin-expressing regions are primarily optogenetic rather than thermal. We\nhave also revised the text for improved clarity in “Stimulation at rest” (paragraph 4) and\n“Discussion” (paragraph 11).\nAlso, what to make of the different effect of light stimulation as a function of frequencies between the\nblue and red light?\nWhile blue light can activate Jaws, it does so significantly less effectively than red light. For\nexample, Chuong et al. [2] report that 635 nm (red, 472 THz) light produces approximately twice\nthe photocurrent of 485 nm (blue, 618 THz) light. Therefore, while blue light can evoke neural\nresponses, its efficacy is notably lower than that of red light. The Reviewer’s specific point about\nlower light frequencies is especially relevant, as red light penetrates brain tissue more effectively\nthan blue light. This greater penetration likely contributes to the stronger electrophysiological\nresponses observed with red light compared to blue light, as shown in Figure 6C. To address this\npoint, we have revised the text and added citations for clarity (see “Stimulation at rest,”\nparagraph 4, and “Discussion,” paragraph 11).\nPlease also note that the blue light stimulation data has been moved to Figure 6 to improve the\nflow of the manuscript.\np10, 5th para: \"For both monkeys, ECoG power evoked by red LEDs was stronger in the expressing areas\nthan the opsin deficient areas\" Shoudn’t we expect to see “no” response in opsin free areas? What\nmight be causing this residual response?\nWe anticipated that the strongest effects would occur in opsin-expressing areas, with weaker\neffects potentially present in opsin-deficient regions. These weaker responses could arise from:\n(1) low levels of opsin expression that are not detectable by epifluorescence imaging; (2)\npropagation of neural activity from opsin-expressing regions to adjacent areas via network\neffects; and (3) potential thermal artifacts in opsin-deficient regions. We have now incorporated\nthese considerations into the text (see “Discussion,” paragraph 8).\n\"where there was no significance between the opsin expressing and opsin deficient areas \" This was not\nclear from reading the previous section. I saw no mention to this comparison. I think this should be\nrepresented clearly, as it comes as a surprise reading this sentence here.\nWe have clarified the text (in paragraph 4 of “Stimulation at rest”) to say “We repeated the\nexperiment with sub-optimal stimulation techniques in Monkey L, being red LED stimulation with\ntissue growth over the brain and blue (485 nm) LED stimulation of a clear window, and found\nthere was no significance between the opsin expressing and opsin deficient areas (tissue: p =\n0.44; blue light: p = 0.80; Fig. 6c).”\nFig 4. Resolution of this figure is insufficient given size of font. This may be an error in format conversion.\nPlease better represent on this figure the light stimulation period and frequency over time with a\ncoloured bar above the plots\nWe have enlarged Fig. 5 (formerly Fig. 4) and improved its resolution, and light stimulation bars\nhave been added over each spectrogram, and the wavelength of the light used has been added\nto the caption.\nFig 5 legend: \"recordings from during verses before stimulation\" : Unclear what is meant here.\nWe have updated the caption of Fig. 6 (formerly Fig. 5) to say “The power ratios of responses are\ncalculated by taking the ECoG power during stimulation and dividing by the ECoG power from\nbefore stimulation. The stimulation protocol was a pulse train of 900 ms stimulation followed by\n5 s rest.”\nP12. first para: \"red 4 × 4 array (~12 mW/mm2) simultaneously\" : This power information should also be\nwritten for the above experiments.\nThank you for catching this omission. We have added the power information.\np14, first para: \"frequency bins exhibiting significant (Bonferroni correction applied to p < 0.05)\nmodulation from stimulation\". I don’t remember seeing a multiple comparison correction for the\nprevious analysis in Fig 4. And is the highly restrictive Bonferroni the most appropriate correction for this\nstudy? I personally prefer FDR correction for those analyses.\nOur correction for multiple comparisons is now mentioned in the Fig. 5 caption (formerly Fig. 4\ncaption).\nAlso, thank you for the thoughtful suggestion of FDR correction. Given the nature of our data, we\nhave concerns with the FDR method, where p-values are compared to each other with a ranked-\nbased threshold to determine significance. We believe it is important for each bin to be assessed\nfor significance based on the baseline values in its frequency alone. Bonferroni takes the number\nof bins into account, but not the values of the bins as FDR does. Thus, we believe that Bonferroni\nbetter aligns with our intentions for multiple comparison correction in this specific case. In an\nexploratory analysis such as this, where we find specific time-frequency bins that are modulated\nby the opsin expression, we aim to be more restrictive as to not make any bold claims that are\nnot backed up by a prior hypothesis.\nNo in-text reference to Fig 7A-C\nWe have improved our figure callouts in the text accordingly.\nFig 7: Please add references to onset/ of reaches in the plot.\nSince these spectrograms are averaged over trails, and the trials are aligned to the beginning of\nstimulation, the onset of reaches vary in the spectrograms due to the variation in time between\nthe start of stimulation and the go-tone.\nBased on the feedback from Reviewers, we have substantially reorganized the presentation of\nour data. Consequently, the original Fig. 7 has been removed and its data has been used to\nsupport our new Fig. 8.\np15, first para: \"and efficient viral vector delivery without live-MRI monitoring\" It’s not clear how this\ntechnology enables doing a CED injection without MRI. Could anyone just stick a needle inside a\ncraniotomy and inject CED, even without this platform? If your technology assists with needle placement\nand stability, or reflux monitoring, then I think it is a better selling point.\nIndeed, CED without live MRI can be performed independently of the other technological\nadvancements we report. We view this as a strength of our work—that while our innovations do\nnot rely on one another, their combined synergy enhances the overall applicability of our\nplatform.\nAdditionally, we appreciate your suggestion to emphasize reflux monitoring, which is a notable\nadvantage of our platform and is addressed in the “CED and epifluorescence” section, paragraph\n2.\nFurthermore, the CED infusion profile can be modeled bench-side prior to surgery, based on our\nprevious publication introducing a model for MRI-guided injections [1]. The integration of this\npredictive modeling with intraoperative reflux monitoring further enhances the accessibility and\nutility of our platform. This clarification is now included in Discussion paragraph 7.\np16, first para: \"with traditional window-less approaches, like Utah arrays\" I recommend citing the latest\nAngelucci Opto-Utah Array paper.\nThank you for the suggestion – we agree that the Opto-Utah Array is an important contribution\nto the field. We have added the citation.\n\", is much more challenging in comparison to our window-based method. \" I am not sure this is a fair\ncomparison. I can think of several ways in which a fully closed approach is safer and easier… (e.g.\ninfection risks, human translation). Maybe the main selling point of your approach is the constant\nvisualization and monitoring, including with ephys, of the tested sites?\nTo clarify this, we updated the text to say, “Replacing or updating electrophysiological or optical\nstimulation hardware implanted with traditional window-less approaches, like Utah array-style\ndevices or LED arrays sutured to the native dura, is more surgically complex in comparison to our\nwindow-based method”.\np16, 4th para: \"Early works attempting to integrate electrode arrays and large-scale optical windows did\nnot result in long-term optical access \" I would like to see data about pressure on the cortex caused by\nthe window, and related depression, as shown in Yazdan, Neuron 2016. Has this been resolved?.\nIn both the Yazdan-Shahmorad et al. Neuron (2016 [5]) and eLife (2018 [6]) papers, experiments\nwere conducted on the same two monkeys. In Neuron, histological analysis of one monkey\nrevealed a potential concern, as noted by the Reviewer. However, histological data from the\nother monkey, analyzed in the eLife study, did not replicate this finding.\nBased on these observations, and given that our current work prolongs optical access—thereby\nreducing the number and frequency of explantations and dural resections compared to previous\nstudies—we do not anticipate seeing the dura thinning reported in the 2016 Neuron paper.\nOur ongoing behavioral studies with these monkeys preclude histological analysis at this time,\nbut once the animals are eventually euthanized, we plan to assess the health and integrity of the\ncortical tissue.\nI also do not see any histological data in this paper. I assume the NHPs are still alive and performing\ntasks? Previous papers from this group included much useful histological verification. This would be even\nmore useful in this case given the strange behavior of the Jaws opsin on ephys (excitation rather than\ninhibition, positive effects even on non-transduced sites).\nThe NHPs in this study are still alive and actively participating in ongoing experiments. We have\nrevised the text to clarify the following:\n“The chambers continue to be stable and used for studies after >4.0 and >3.3 years following\nimplantation for Monkeys H and L, respectively.”\nWe consider our implanted monkeys extremely valuable for in vivo research, and as such, we are\nprioritizing ongoing studies over post-mortem histological analysis at this time. This decision\naligns with NIH ethical guidelines emphasizing the principles of Reuse and Reduction. That said,\nwe fully intend to perform histological assessments in the future, once in vivo studies are\ncomplete.\nWe also believe that the long-term data we are providing on implant longevity and stability\noffers valuable insights for the neuroscience community—potentially more so than histology at\nthis stage—especially since we have previously validated viral expression histologically in earlier\nwork, as the Reviewer noted. For example, our previous publications (e.g., [5]) demonstrated\nboth the efficacy of viral infusions and the reliable relationship between epifluorescence imaging\nand opsin expression.\nTo address the Reviewer’s comment regarding the unexpected results from Jaws, we conducted\nextensive control experiments as well as a simulation study to better understand and explain\nthese observations. The details of these efforts are outlined throughout this response letter—\nwhere similar concerns were raised by other Reviewers—and are also incorporated into the\nrevised manuscript.\nThoughts: Jaws is a very sensitive opsin. Could the positive effects even on non-transduced sites be a\nresult of stimulation of nearby transduced sites by distant LEDs? Even a small amount of light could\ntrigger those distant sites, and through network effects, influence ephys readings at the stimulated, non-\ntransduced site? Is it possible to run some tests in a non-injected monkey?\nIn response to your comment, we collected data from a naïve monkey with no viral vector\ninjection, as well as from both monkeys about two years post-injection, at which point\nepifluorescent expression was nearly undetectable (Fig. 6). In both cases, we did not observe\nsignificant light-evoked responses, further supporting our findings in high-expressing areas.\nAdditionally, we appreciate your insightful comment on the complexity of network effects and\nhave revised paragraph 8 of the “Discussion” to incorporate this important consideration.\nIs it also possible that epifluorescence is not a perfect indicator of transduced vs non-transduced sites?\nMaybe at sites where epifluorescence is not visible (at the threshold used), there are still a number of\nneurons or axon terminals expressing the Jaws opsin?\nWe agree that lower levels of expression may not be detectable with our epifluorescent imaging.\nWe have updated the text in “Discussion,” paragraph 8, to reflect this point.\nOverall, great study combining cutting edge optogenetics and clever hardware developments that are\nmuch needed to boost causal, cell-type specific neuro research in the primate brain. Looking forward to\nthe revised paper.\nReviewer #2 (Remarks to the Author):\nThe manuscript by Griggs et al. presents a cost-effective and scalable platform capable of multimodal\noptogenetic and neurophysiological studies in behaving macaques positioned in a primate chair. In\ncontrast to other published macaque chamber-mounted systems, the key advances of this platform\ninclude its scalability, the integration of LFP/ECoG capabilities into the artificial dura (the MMAD), and its\nability to perform patterned optogenetic stimulation. The authors demonstrate the system’s\nfunctionality by showcasing its capability to monitor epifluorescence (optogenetic expression) over\nseveral months, as well as its ability to modulate LPFs and reaching behavior through optogenetic\nstimulation. I commend the authors for acknowledging that the clear view of the brain through the\nartificial dura typically lasts only a couple of months, after which a tissue removal procedure is required\nto regain visual access for further studies. While this limitation, along with others (e.g., risk of infection,\noptogenetic light artifacts in neurophysiological signals, and the focus on surface-level recordings),\nconstrains its ability to fully reveal the circuitry underlying behavior, the utilization of this platform can\nset the stage for significant advancements in primate cognitive neuroscience.\nWe thank the Reviewer for their enthusiasm for our paper and for their constructive feedback,\nbelow we have provided responses to their comments.\nMajor Comments\n(1) Reproducibility of results across days is not addressed in the manuscript. This is true for (a)\nepifluorescence, since only the collection but not quantitation was described in the Star Methods; (b)\nconsistency of the optical window, since alignment procedures for the FOV, blood vessel changes across\ndays and weeks (e.g. Figure 3 top row) were not discussed; (c) LFP signals, in Figure 4 it is unclear as to\nthe sample size of the LFP data (e.g. number of trials), let alone whether it was collected across multiple\ndays or weeks); (d) behavioral measures, how consistence were the effects of optogenetic stimulation on\nbehavior across days.\nIn response to your comments regarding epifluorescence, window transparency, and behavioral\nreproducibility over time, we have incorporated additional data and revisions to address these\npoints:\nWe have added new data showing changes in the optical window over several weeks (Supp. Fig.\n3). Unlike some other recording and stimulation platforms, ours enables researchers to monitor\nand adapt to cortical changes as they arise. While tracking blood vessel changes was not the\nprimary aim of this study, our platform is well-suited for such investigations. Notably, it is\ncompatible with optical coherence tomography angiography – a technique we have previously\ndemonstrated for studying vasculature. We have updated the Discussion (paragraph 3) to reflect\nthis.\nAs suggested, we now include light-evoked responses across time, which demonstrate consistent\neffects over repeated sessions (Fig. 6e). In addition, we have added sample size details to Fig. 5\n(formerly Fig. 4), per your request.\nWe have also included new data on optogenetically-evoked behavioral responses recorded across\nmultiple days (Supp. Fig. 6).\nFinally, in response to your note about epifluorescence quantification, we have added the\nrelevant methodological details to the final paragraph of the \"Epifluorescence imaging\"\nsubsection in the Methods section.\n(2) Information provided in Supp Figure 5 on the removal of light-induced artifact should be promoted to\nthe main manuscript. With modeling, could the onset 50ms and offset 50ms LFP, discarded in\nsubsequent analyses, be recovered as suggested by Supp Figure 5D?\nWe appreciate the Reviewer’s comments. The figure has been improved with the addition of new\ntime series data, and the figure has been split into a figure for the main text (Fig. 4) and a\nsupplemental figure (Supp. Fig. 8). Related text has been updated accordingly, including the\naddition of a new Results section titled “Photo-induced artifact removal.”\nIn regard to the Reviewer’s question: While the neural responses during the 50 ms windows\nimmediately following stimulation onset and offset can be recovered to a degree, we did not\ninclude those 50 ms windows to conservatively protect against edge-case artifacts potentially\nbiasing our data. Future novel modeling methods may resolve this issue, and thus in the future\nprovide high fidelity data immediately after the onset and offset of stimulation.\n(3) A briefer summary of the behavioral results (Figure 6). Reducing even further the behavioral data\nwould help focus the manuscript onto the device. Actually, once the behavioral data was introduced, this\nreader was looking for a more in-depth analysis and interpretation of those results (as well as wondering\nabout the next obvious experiments that must have been performed) than that provided in the\nmanuscript and supplemental materials. For instance, examining the effects on behavior of varying the\npattern targeting different functional cortical areas (or amplitude or duration or timing) of optogenetic\nstimulation would have really brought home the utility of the large-scale platform.\nWe thank the Reviewer for their thoughtful comments. As suggested, the behavioral data and\nsupporting text have been reorganized substantially to better focus on the platform we are\npresenting.\nNote that Fig. 6. has been renumbered to Fig. 7.\n(4) With the usage of the term ‘optical imaging’ this reader expected that functional intrinsic optical\nimaging would be one of the major modalities of this large-scale platform. Instead, what is advanced\nhere is visual access to the surface of the brain under the term of ‘optical imaging’. The authors should\nclarify this distinction early on and suggest (e.g., in the Discussion) that intrinsic optical imaging,\ncombined with behavioral studies, is feasible with the current platform—though without the other\nmodalities, as the hardware for those may interfere with intrinsic optical imaging.\nTo address this comment and emphasize the multimodality of our interface, we have clarified\nand expanded the discussion of compatible imaging methods—including intrinsic signal optical\nimaging—in Introduction paragraph 4 and Discussion paragraph 3.\nModerate and Minor Comments:\n(1) Figure 1D. Please provide a mm scale bar to Figure 1D. This will provide to the reader a good\nreference of the sizes of the outside of the chamber and area of surface of the brain available for study.\nThis will also allow the reader to appreciate the space dedicated to store the ECOG cabling.\nWe have updated the figure as requested.\n(2) The assembly of the LED array was designed to minimize conductive heating of the brain. However,\nthe manuscript did not report the actual heat transfer with typical full array LED stimulation through the\ncover glass or through the MMAD, gauging the success of these efforts. Thus it is unclear whether\nwithout obvious airflow that an Air Gap was effective.\nTo address this point, we conducted bench-side temperature measurements through the cover\nglass and found no temperature increases exceeding 1°C, a level considered safe for brain tissue\n[7], [8], [9], [10]and appropriate for minimal influence on neuronal spiking [3], [4] (see the final\nparagraph of “Hardware,” paragraph 3 of “Discussion,” and Supp. Fig. 2).\nAs a qualitative assessment, we did not observe any signs of tissue damage (e.g., brain\ndiscoloration) or behavioral changes in the animals during these experiments. We have updated\nthe text accordingly (see the final paragraph of “Hardware”).\n(3) The manuscript reports chamber stability for 2-3 years, with MMAD re-implantations for additional\nexperiments. However, it is unclear if the chamber remains in use or has been removed. Clarifying\nwhether the chamber is still in use or has been removed would help the reader understand the\nplatform’s longevity and suitability for even longer-term studies.\nThank you for pointing out this important oversight. The text in “Hardware,” paragraph 1, has\nbeen updated to report, “The chambers continue to be stable and used for studies after >4.0 and\n>3.3 years following implantation for Monkeys H and L, respectively.”\n(4) Figure 4. Upon printout (this reviewer still works with hard copy), the small font size of Figure 4 was\nunreadable. Please reformat Figure 4 so it can be reproduced nicely on the printed page.\nWe have provided an enlarged, higher resolution image.\nPlease note that Fig. 4. has been renumbered to Fig. 5.\n(5) Results related to Figure 4. Data from Monkey L. How many ECoG sites were included in this data set?\nWere both opsin expressing and opsin deficient sites included? How many stimulation trails were\nincluded? Were similar findings obtained from Monkey H. May I recommend reporting the statistics\nthroughout the manuscript using the APA Style Guidelines.\nThank you for your detailed observations regarding Fig. 5 (formerly Fig. 4). We have revised the\ntext and figures to improve clarity as follows:\nThe distinction between single-electrode and group-electrode plots is now clarified in the\nupdated Figs. 5 and 6.\nIn Fig. 5, stimulation was targeted to electrodes positioned over opsin-expressing regions. The\nfull LED array illumination results (previously in Fig. 5), which included both opsin-expressing and\nopsin-deficient regions, has been moved to Fig. 6. The corresponding electrode counts for each\nregion are now included in the caption.\nThe number of trials used has been reported in both the main text and figure captions.\nNew data showing consistent evoked activity in Monkey L using the full red 4X4 LED array are\nnow presented in Fig. 6c.\nAdditional data showing similar evoked activity in Monkey H using a red laser have been added\nin Supp. Fig. 4.\nThe manuscript has been revised to follow APA style guidelines.\n(6) Results related to Figure 4D. The manuscript reports a red LED energy of ~12 mW/mm2, but does not\nreport the energy directed towards the brain for either the red laser or blue (485 nm) LED. Without\ninformation on the Blue LEDs and the absorption spectrum of the JAWs opsin for these two wavelengths,\nit is difficult for the reader to assess whether the differences in PSD power observed in Figure 4D are\nsmaller than expected based on theoretical modeling. In other words, it is unclear whether or not the\nblue LED sub-optimally drives the JAWs opsin.\nPower information has been added throughout the “Stimulation at rest” section and the spectral\ncharacteristics of Jaws is provided in the “Stimulation at rest” section and in the Discussion,\nparagraph 11, explaining the blue light is a sub-optimal wavelength for activating Jaws.\nPlease note that Fig. 4. has been renumbered to Fig. 5.\n(7) Results related to Figure 4G-O. The Spectrograms show an increase in activity during the 900 ms after\nstimulation offset relative to the 500 ms of pre-stimulus activity. This apparently interesting long-lasting\neffect of stimulation though shown in Figure 4D was not discussed in the Results. Also, what is the\nauthors’ interpretation of the relatively uniform increase in activity across frequencies?\nGiven the spatiotemporal complexities of neural networks, we anticipated that some residual\neffects of stimulation might persist following stimulation offset, and our findings were consistent\nwith this expectation. We have clarified this point in the text (“Stimulation at rest,” paragraph 2).\nTo our knowledge, this is the first report of large-scale inhibitory optogenetic stimulation\nrecorded with ECoG. In developing our platform, we anticipated optogenetically-evoked\nresponses and have performed extensive analyses to support this. Based on our prior experience,\nwe recognize that stimulation parameters can influence frequency-specific responses. While a\ndetailed investigation of these relationships is beyond the scope of this study, we agree that this\nis an important area for future research and have noted this in the text (“Stimulation at rest”,\nparagraph 2 and “Discussion,” paragraph 10).\nPlease also note that Fig. 4 has been renumbered to Fig. 5, and the panel previously labeled Fig.\n4D is now summarized in the new Fig. 6c.\n(8) Results related to Figure 4I. The Frequency spectrogram suggests the duration of laser stimulation\nlasted about 150 ms longer than the targeted 900 ms for the LEDs. Could this have happened? If not, the\nauthors should make an account for the laser eliciting a longer lasting response than the LED.\nAs mentioned above, although the duration of laser stimulation was 900 ms, we observe neural\nresponses that extend beyond this period. We attribute this to the spatiotemporal complexities of\nneural networks, which aligns with our expectations. We have added this clarification to the\n“Stimulation at rest” section, paragraph 2, and the “Discussion,” paragraph 8.\nPlease note that Fig. 4 has been renumbered to Fig. 5.\n(9) Results related to Figure 4D-E-F. The Median PSD Ratio y-axis scale is not linear (and not a standard\nlog scale); whereas the Power ratio is graphed linearly in Figure 5CD. Is that non-linearity intended? If\nyes, what is that scaling?\nThank you for helping us understand the non-linear y-axis was not helpful in this case. We now\nplot the Fig. 5 (formerly Fig. 4) bar charts in decibels (dB) and with a linear (as opposed to log-\nscale) y-axis.\n(10) Results related to Figure 4E-F. The 95% CI of the medians in some instances fall below a ratio of 1. Is\nthis valid?\nFor better clarity, the y-axes of the bar charts have been changed to dB, and so the “ratio of 1” is\nnow equivalent to “dB of 0”.\nTo answer the question: Yes. In fact, we originally expected that inhibitory optogenetics would\nreduce the ECoG activity with respect to baseline, which would have produced a ratio less than 1,\nor equivalently, a dB less than 0.\nPlease note that Fig. 4. has been renumbered to Fig. 5.\n(11) Results related to Figure 4 (and Figure 5 data). What was the interstimulus interval?\nThe interstimulus interval was 5 s. Captions have been updated accordingly.\nPlease note that Figs. 4 and 5 have been renumbered to Figs. 5 and 6, respectively.\n(12) Figure 5. Legend title: “Map of neural responses…” is inaccurate as the locations of the ECoG\nrecordings are not shown (as in Supp Figure 2).\nWe have removed “Map of…” from the text accordingly.\nPlease note that Fig. 5. has been renumbered to Fig. 6.\n(13) Results related to Figure 5CD. How many trials and ECoG sites were used to generate these graphs,\nand over what time period? Additionally, in this figure, the whiskers represent the standard error of the\nmean, while in Figure 4, whiskers represent 95% confidence intervals. What is the reason for this\ninconsistency between Figures?\nThank you for catching these mistakes. We updated our analysis to 95% confidence intervals and\nthe numbers of electrodes and the trial and timing information have been added to the caption.\nPlease note that Figs. 4 and 5. have been renumbered to Figs. 5 and 6, respectively.\n(14) Behavioral task. What was the size of the target windows and distance in cm between the start and\nend targets? Maybe add a cm scale bar to Figure 6A, B, or C.\nWe have added size and distance information to the caption. Note that our behavioral task\nschematic is not drawn to scale, and this information has also been added to the caption.\nPlease note that Fig. 6. has been renumbered to Fig. 7.\n(15) Behavioral task. The reporting of some of the statistical results might be questioned. For instance,\nthis reader questions the validity of reporting the last decimal places of some of the values. For example,\n‘total: p = 0.0001560’, should the reader place any credence in the last ‘560’ or is that just a computer\noutput without validation of the number of significant digits that should validly be reported? Again, may\nI recommend reporting the statistics according to APA Style Guidelines.\nAPA style guidelines now enhance our manuscript.\n(16) Results related to Figure 6. Given the focus of the manuscript, this Figure in this reader’s opinion\nseemed a little overkill and difficult to interpret during the presentation of the Reach Times (Figure 6F-\nG). Since Path Lengths (Figure 6D) and reach onsets seem to be the major variables affected by\noptogenetic stimulation, maybe just present those results in the main manuscript.\nBased on the feedback from Reviewers, we have substantially reorganized the presentation of\nour behavioral data to focus on our platform.\nPlease note that Fig. 6. has been renumbered to Fig. 7.\n(17) Results related to Figure 6. “Whiskers are described as representing the standard error of the mean,\nand asterisks denote p < 0.05 using a Mann-Whitney U-test”. Since the Mann-Whitney U-test is a non-\nparametric test used to assess significant differences between two independent, non-normally\ndistributed groups, why are means, rather than medians and confidence intervals, presented in the\ngraphs? Alternatively, if the data groups are normally distributed, why weren’t t-tests employed instead?\nWe have revised our plots to show medians and confidence intervals, as suggested. T-tests were\nnot used because of the non-normal nature of the data distribution, as the Reviewer comments.\nPlease note that Fig. 6. has been renumbered to Fig. 7.\n(18) Results related to Figure 7. Again, how many trials and ECoG sites were used to generate the graphs\nin panels D and H? The whiskers are described as representing 95% confidence intervals of the average,\nbut they appear quite small for 95% CIs. Is this correct? Additionally, why was there a switch to a.u. for\nAverage Power? If th reason for this was mentioned in the manuscript, it may have been unclear to this\nreader.\nIn response to a series of suggestions from the Reviewers, we conducted extensive data analysis\nand additional data collection to explore area-specific responses as well as longitudinal light-\nevoked responses. As a result, this figure was no longer necessary to support our findings and\nhas been removed from the manuscript.\n(19) The manuscript’s usage of ‘slow reach’ reads awkwardly to this reader. My general interpretation of\nthis word pairing is that the actual movement is slower (e.g., like a sloth). Instead, based on the\npresentation of the results it appears (but I could be mistaken) that reach onset and reach trajectory\nlengths were affected by the optogenetic stimulation (and not movement velocity). Thus the usage of\n‘slow reach’ is not ideal.\nThank you for your comment regarding the use of “slowing,” which is often intuitively understood\nas reducing velocity. We have now replaced this term with “impeding” reaches to better reflect\nthe intended meaning.\n(20) The manuscript emphasizes that previously published CED protocols relied on MRI to monitor\ninfusions, whereas this is not required with the current platform. However, aside from visual inspection\nof the surface, there is a noticeable lack of subsequent monitoring of CED infusion, as indicated by the\nfew failed attempts reported. In this reader’s opinion, this difference in the CED protocol is relatively\nminor and does not represent a significant advancement as advocated for in the manuscript (I would\ntone that down).\nTo address this comment, we have reworded paragraph 2 of the “CED and epifluorescence”\nsection. We have also emphasized that the improvements to our CED technique between the first\nand second surgeries led to complete success in the second procedure. Additionally, we have\nincluded information about our previously published MRI-guided injection model, which, when\ncombined with the reflux monitoring enabled by the new technique, enhances the accessibility\nand applicability of our platform [1](see “CED and epifluorescence,” paragraph 2 and Fig. 3\ncaption).\n(21) Discussion. The manuscript reports an unexpected increase in ECoG power during optogenetic\nstimulation with an inhibitory opsin. A more in-depth discussion of possible reasons for this observation\nis warranted. Similarly, given the behavioral results, a more in-depth discussion on these outcomes\nwould be anticipated given the suspected roles of area 5 and area 7 in reaching behavior.\nFeedback from this Reviewer, as well as others, has led to substantial revisions throughout the\npaper. The major contributions are summarized below:\n1. We have added a completely new simulation arm to investigate the unexpected increase in ECoG\npower in greater depth (see the final paragraph of the “Stimulation at rest” section, Supp. Fig. 5,\nand the updated Discussion, particularly paragraphs 9 and 10). The simulation results align well\nwith our in vivo findings.\n2. Additional data examining the effect of opsin expression on neural activity during reaching\nmovements have been included (see the final paragraph of the Results section and Fig. 8).\n3. Fig. 6 (formerly Fig. 5) has been updated with longitudinal stimulation data and results from a\nnaïve (opsin-free) animal.\n4. We expanded the Discussion (paragraph 9) to include further explanation and citations related\nto cortical circuitry, focusing on the interplay between layers and the excitatory/inhibitory\nneuronal balance.\n5. The roles of areas 5 and 7 in reaching behavior have been elaborated upon, with relevant\nliterature citations added as suggested (see Discussion paragraph 12).\n(22) Discussion. Upon a single reading, it seemed to this reviewer that there were\nsentences/paragraphs in the Discussion that were nearly identical to those written either in the\nIntroduction or Results. Please revise/edit accordingly to reduce such repetition.\nWe have improved the paper accordingly.\n(23) Supp Figure 2D. Again, why was a Mann-Whitney U-test used if means and standard errors are being\ngraphed (see previous comment)? Again, how many trials and ECoG sites were used to generate these\ngraphs? Graphing such small standard errors is far less informative to the reader than 95% confidence\nintervals would be. Were similar findings seen for Monkey H?\nBased on the Reviewers’ feedback, the behavioral data and supporting text have been\nsubstantially reorganized to better highlight our platform. While the supplemental figure in its\noriginal form has been removed, data supporting the original supplemental figure are now\nsupporting an improved Fig. 6 and a newly added Fig. 8. Given the non-normal distribution of our\ndata, we used the Mann-Whitney U-test for statistical analysis. In line with the Reviewer’s\nsuggestion, we now also display 95% confidence intervals in the updated figure. The number of\ntrials and other details are added to the figure caption.\n(24) Supp Figure 3. Am I correct in assuming the results for the 4-arrow symbol (top row) is the vector\nsum of the individual reach directions (next 4 rows)? If that assumption is true, then for Monkey H for\nthe y-dimension there appears to be something way off. Same for Monkey L.\nBased on the Reviewers’ feedback, the behavioral data and supporting text have been\nsubstantially reorganized to better highlight our platform. Consequently, the supplemental figure\nin question has been removed.\n(25) Supp Figure 5. Shouldn’t Suppl Figure 5 E-F lower graphs (after artifact removal) be identical to\ngraphs Figure 7E and Figure 7F? They are similar but also different in visually significant ways, even when\none takes into account the different scale for Suppl Figure 5F.\nThe panels in question (now found in Fig. 4) are ECoG data from two different example trials of\nreach, and the caption now clarifies this. Trail-by-trial differences mean these spectrograms and\nthe average spectrograms of the figure formerly numbered Fig. 7 may be similar, but not\nidentical. Please note that Fig. 7 has been removed due to significant reorganization of the paper\nin response to the Reviewers, although it’s data now supports our new Fig. 8.\nPlease note that Supp. Fig. 5. has been split and renumbered to Supp. Fig. 8, and Fig. 4.\n(26) Supp Fig 5A: What was the source of the LFP time courses (n=13)? Were they from a single animal, a\nsingle trial, or averaged over multiple trials? What was the experimental session type, and were the time\ncourses located over opsin-expressing or opsin-deficient sites? Additionally, for all the analysese, were\ncertain ECoG sites preferentially included or excluded, and if so, what criteria were used for selection?\nFinally, was the goodness of fit of the regression used to evaluate the effectiveness of photo-induced\nartifact removal for individual ECoG sites?\nPlease see our responses, below:\n1. The LFP time course is from a single example trial with optical stimulation, across\nmultiple electrodes. Electrodes were over both opsin expressing and opsin deficient\nareas. High impedance electrodes were excluded. These details have been added to the\ncaption.\n2. Since we do not have the electrophysiological ground truth, goodness of fit of regression\ncould be misinterpreted. Instead, we opted to validate the artifact removal technique by\nperforming the technique on non-stimulated data (see Fig. 4) to confirm that the artifact\nremoval technique minimally impacted the neural data.\nPlease note that Supp. Fig. 5. has been split and renumbered to Supp. Fig. 8, and Fig. 4.\n(28) Figure 6 and Supp Fig 3: Given the large number of null hypotheses tested, there is a risk of Type 1\nstatistical errors. Please ensure appropriate corrections are applied to account for multiple comparisons.\nOur initial experimental design focused on examining how stimulation would affect behavioral\nmetrics, including reach time and path length, which we carefully recorded. For these\nhypotheses, we did not adjust p-values as the nature of our analysis were not exploratory.\nWe have updated the manuscript to clarify this. Additionally, in response to the Reviewers'\ncomments, we have substantially reorganized the behavioral data and corresponding text to\nbetter highlight the technological contributions of our platform. This restructuring also helps\nmitigate the risk of Type I statistical errors in the behavioral analysis, as the Reviewer rightly\npoints out. Consequently, the supplemental figure in question has been removed.\nPlease note that Fig. 6. has been renumbered to Fig. 7.\nTypos:\n1. Page 4, line 31: “center-our reach task” – should be “center-out reach task”.\nThis is now fixed.\n2. Page 10, line 25: \"it’s compatibility with lasers\" –should be \"its\".\nThis is now fixed.\n3. StarMethods: Resister – should be resistor?\nThis is now fixed.\n4. StarMethods: “Christ Instruments” – should be” Crist Instrument Company”.\nThis is now fixed.\n5. Term ‘LED’ is not defined.\n“LED” is now defined in the text as a light emitting diode.\nReviewer #3 (Remarks to the Author):\nThe manuscript presents a comprehensive account of a large-scale optogenetic neurophysiology\nplatform designed for non-human primates (NHP) and illustrates its application in a behavioral study.\nWhile the organization and clarity of the manuscript are commendable, I have considerable reservations\nabout the novelty and scientific importance of this work, particularly in relation to its potential\npublication in Nature Communications.\nOne of the main challenges facing optogenetics in primate research is the effective outcome of\nbehavioral manipulation, especially regarding motor actions. In its current form, the study utilizing the\nassembled platform does not significantly advance this field. Although it shows some impact on reaching\nbehaviors, I question the practicality of the platform as presented, regardless of its apparent complexity.\nFurthermore, if the objective is to utilize this device for exploring the neural mechanisms behind specific\ncognitive functions or understanding network dynamics, the existing design offers no distinct advantages\nadvantages\nover current technologies. The ECoG array is limited to capturing local field potentials, and the extensive\nLED array suffers from inadequate spatial resolution and substantial interference artifacts. Together,\nthese limitations render the system less appealing.\nWe thank the Reviewer for their comments and constructive feedback. We have added\nclarifications in response to your points, summarized below:\n1. Large-scale, stable optical and electrophysiological access: Our platform provides stable optical\naccess to approximately 2 cm² of cortex, with electrode coverage over 1 cm². This is a distinct\nadvantage over many current technologies. Existing approaches often lack long-term, large-scale\naccess, limiting the ability to both monitor and modulate brain activity over wide networks. As\ndiscussed in Introduction paragraph 2, such access is essential for studying brain function and\ndysfunction, and for developing therapies for neurological and neuropsychiatric disorders.\n2. Importance and potential of ECoG: We emphasize ECoG’s translational relevance, long-term\nsignal stability, and its value in studying network dynamics. While the current version of our\nMMAD does not record action potentials from the cortical surface, we expect future iterations\nwill be able to do so—as demonstrated by us and others. We now clarify this point in Discussion\nparagraph 2 and provide relevant citations.\n3. Optogenetic modulation and system accessibility: Our current LED array demonstrates that\noptogenetic stimulation at this resolution can influence behavior. While we are also pursuing\nhigher-resolution LED arrays in separate efforts, this work focuses on developing an accessible,\neasy-to-build system that other non-human primate (NHP) researchers can readily adopt. A key\nchallenge in neuroscience today is that many advanced tools remain confined to the labs that\ndeveloped them. In contrast, we designed our system to be widely adoptable, which we view as a\nstrength—especially given the relatively small size of the NHP research community. As noted,\nlaser-based stimulation remains an option in our platform for high-resolution, targeted\napplications, and we now cite a high-resolution LED solution (as the Reviewer suggested) that\nusers may integrate if desired.\n4. Photo-induced artifact removal: We recognized and addressed photo-induced artifacts in ECoG\nsignals by developing an effective artifact removal method. A brief description is now included in\nthe Results section (“Photo-induced artifact removal”), with a detailed explanation provided in\nthe Methods section (“Photo-induced artifact removal”).\nTo enhance the design, I propose the following suggestions:\n1. Consider replacing the LED array with a micro-LED array to improve spatial resolution\n(doi.org/10.1038/s41592-021-01238-9). This micro-LED array could be programmed for high temporal\nresolution, theoretically producing lower artifacts and thereby increasing the likelihood of capturing\ntransient changes in neural activity. Additionally, implementing an LED array with dual wavelengths could\nfacilitate simultaneous activation and deactivation using one device.\nWe provide further clarification below:\n1. High temporal resolution of LED array: Our LED array and driving circuitry support sub-\nmillisecond temporal resolution. We have updated “Hardware,” paragraph 4, to emphasize this\npoint. Additionally, we have included new data (Supp. Vid. 1) to demonstrate the array’s ability\nto support stimulation with spatiotemporal complexity and dynamic control of optical power.\n2. Artifact considerations with long stimulation: While we recognize that shorter stimulation\ndurations reduce photo-artifact amplitude, longer durations were intentionally used in this study\nto investigate reach behaviors under continuous stimulation. Importantly, we have developed an\neffective artifact rejection method (see “Photo-induced artifact removal” in Results and\nMethods), allowing us to analyze neural activity during stimulation, as shown throughout the\nmanuscript (e.g., Fig. 8).\n3. Support for multiple wavelengths: Our LED array is designed with flexibility in mind—LEDs of\ndifferent colors but with a consistent footprint to ours are commercially available and allow for\neasy customization of multi-color arrays. We have clarified this in Discussion paragraph 3, noting\nthat our design can support step-function opsins and, indeed, two wavelengths were tested in\nthis study.\n4. Accessibility vs. complexity in array design: While we appreciate the Reviewer highlighting the\npotential of advanced micro-LED technologies, including those cited, our focus is on developing\nan optogenetic platform that is accessible, reproducible, and feasible for labs with modest\ntechnical resources. This goal is central to our manuscript, as reflected in the title and overall\napproach.\n2. I recommend mapping the finger and arm zones prior to light stimulation. Random stimulation tends\nto be less effective in eliciting behavioral responses. I encourage the authors to adopt a different\nstrategy: record neural activity during reaching tasks across a broad cortical area, and subsequently\nprogram the micro-LED array to illuminate the brain in alignment with the recorded activation patterns.\nGiven that these patterns will vary in both space and time, mastering the programming of the LED array\nis crucial.\nThe primary goal of this paper is to introduce a novel platform that enables simultaneous\nelectrophysiological recording and optogenetic stimulation across large cortical areas. Based on\nfeedback throughout the review process, we have further revised the manuscript to emphasize\nthe various components and capabilities of the technology itself.\nWith regard to the behavioral effects, our intent is to demonstrate the feasibility of using this\nplatform to induce measurable behavioral changes through optogenetic stimulation—an\nachievement that has been particularly challenging, as noted in the literature. As the Reviewer\nsuggests, more sophisticated experiments such as patterned or closed-loop stimulation represent\nexciting directions for future work, and our platform is well-suited to support such studies.\nWe also appreciate your comment on the importance of understanding activation patterns. To\naddress this, we have added a heatmap in Fig. 8 showing behaviorally relevant neural activity,\nwhich reveals preparatory signals in the posterior parietal cortex (PPC), consistent with our\nexpectations. This activity spans a broad region of the network, although it is not localized to\nmusculoskeletal-specific areas such as arm zones in the motor cortex. As shown in Fig. 8b, the\nmajority of electrodes cover areas significantly modulated by reaching behavior. We speculate\nthat finger and arm representations may be less distinct in the PPC compared to primary motor\nand premotor regions, which are more directly involved in motor control.\nTo clarify our stimulation protocol is not random: we employed two types of stimulation in this\nstudy. The first is open-loop stimulation, which is delivered independently of behavior or neural\nactivity and is used to broadly assess stimulation effects on cortical activity. The second\nis behaviorally-informed stimulation, triggered after the monkey acquires the start target, to\nexamine potential behavioral correlates of stimulation. This design aligns with established\napproaches in behavioral neuroscience.\nAlthough we did not implement closed-loop stimulation in this study, the hardware and software\nused (Ripple Neuro) are fully compatible with such applications. Our goal in this paper is to\nintroduce and validate the capabilities of the platform, laying the groundwork for more\nadvanced experiments in future research.\nFinally, we emphasize that our LED array and driving circuitry are capable of sub-millisecond\ntemporal resolution. We have updated the “Hardware” section (paragraph 4) to make this clear\nand added new demonstration data (Supp. Vid. 1) showing the system’s capacity for complex\nspatiotemporal stimulation with adjustable optical power.\nSpecific concerns include:\n1. I find the rationale behind the unexpected increase in ECoG signals unconvincing. A straightforward\nverification could be conducted through single-unit recordings.\nWe recognize that the observed increase in ECoG signal was unexpected, and in response, we\nhave conducted extensive control experiments, added a simulation study, and substantially\nexpanded our discussion of this finding, as also suggested by other Reviewers. These efforts have\nsignificantly strengthened our manuscript in several key ways:\n1. We introduced a novel spiking-based simulation component to investigate the mechanisms\nunderlying the increase in ECoG power. The results of this simulation are consistent with our in\nvivo findings and provide further validation of the phenomenon. (See Results section\n“Stimulation at rest,” paragraph 5; Supp. Fig. 5; Methods section “Simulation”; and Discussion,\nparagraphs 9 and 10.)\n2. In addition to the new data, we have incorporated relevant literature to contextualize and\nsupport our findings. In particular, we reference our previous work, where we simultaneously\nrecorded from multiple cortical depths while stimulating and recording from the brain surface\nusing ECoG electrodes [11], [12]. Those results align well with the present findings and further\nsupport the observed increase in ECoG activity.\nTaken together, these new data, analyses, and manuscript improvements—along with the\ncontrol experiments (e.g., Fig. 5 and Fig. 6)—provide robust support for our conclusion and help\nclarify the underlying mechanisms behind this unexpected result.\n2. Although the authors conducted control experiments to indicate that responses were largely\noptogenetically induced, they were unable to completely eliminate the thermal effects. Therefore, an\nadditional control trial involving non-expressing monkeys (or the same monkey before viral injection)\nremains necessary. While I acknowledge the associated challenges, the experiment, as it stands,\nlacks thoroughness.\nTo address your comment, we repeated the stimulation experiments in a naïve monkey that had\nnot received any optogenetic vector injection. We also added new data from another monkey\nwhose opsin expression had largely faded two years after viral vector infusion. These results, now\nincluded in Fig. 6 (formerly Fig. 5), show comparable stimulation responses in both cases, with no\nstatistically significant increases in evoked activity relative to baseline. These findings in\ncombination with our other control experiments, support our claim that the statistically significant\nstimulation-evoked activity reported throughout the paper is specific to cortical regions expressing\nthe opsin.\nTypos:\nline 94: accessibly->accessibility\nWe have fixed this.\nline 112: center-our->center-out\nWe have fixed this.\nReviewer #4 (Remarks to the Author):\nGriggs and colleagues present an integrated optogenetic and electrocorticography (ECoG) platform\ndesigned for use in macaques. This is an impressive technical achievement, combining optogenetic\nmodulation with large-scale neural recordings. While similar techniques have been proposed individually\nor with more complex approaches, this tool seems relatively straightforward to implement in a lab with\nenough technical expertise. I highly commend the authors for developing and utilizing such an innovative\npiece of technology. I’m convinced many will be interested in these tools.\nHowever, I find myself less convinced by the neuroscientific aspects of the manuscript. As the authors\nthemselves highlight, it is puzzling to observe a net increase in LFP power following Jaws stimulation.\nWhile optogenetic stimulation with a hyperpolarizing opsin is known to induce a mixture of inhibitory\nand excitatory effects at the single-unit level, population-level effects should generally lead to net\ninhibition.\nWe thank the Reviewer for their thoughtful and constructive feedback and have addressed their\nconcern through several key additions and analyses:\n1. We introduced a new simulation arm to further investigate the unexpected increase in ECoG\npower. The results of this simulation are consistent with our in vivo findings and are presented in\nthe final paragraph of the “Stimulation at rest” section, Supp. Fig. 5, and the updated Discussion\n(paragraphs 9 and 10).\n2. We added new data to Fig. 6 (formerly Fig. 5) comparing stimulation responses in a naïve\nmonkey (with no optogenetic vector injection) and another monkey in which opsin expression\nhad largely faded two years post-infusion. In both cases, stimulation-evoked activity did not\nsignificantly increase relative to baseline, supporting our claim that the statistically significant\nevoked responses reported throughout the paper originate from opsin-expressing cortical\nregions\n3. We revised the Discussion (paragraphs 8 and 9) to provide a more detailed explanation of the\nobserved ECoG signal increases, supported by relevant literature. We also reference our previous\nwork [11], [12], in which we simultaneously recorded from multiple cortical depths while\nstimulating and recording from the surface using ECoG electrodes. Those findings are consistent\nwith the present results and further validate the reported increase in ECoG activity.\nThese changes, along with our controls (e.g., Fig. 5, Fig. 6), support our finding of an increase in\nECoG signals.\nThe weak behavioral effects observed also suggest that the output of the stimulated region might be\nslightly reduced, which contradicts the observed increase in LFP power. In my view, this unexpected\nresult warrants further explanation and exploration. Given the substantial light-induced artifacts\nobserved in saline (Fig. S5), I am still uncertain whether these effects are truly neuronal, despite the\nauthors’ counter-arguments.\nThank you for your interesting and thoughtful interpretations. We address these concerns in\nmultiple ways:\n1. In our observed data, optogenetic stimulation of the posterior parietal cortex (PPC)—a\nregion indirectly involved in reaching—produced behavioral effects comparable to those\nreported in other non-human primate (NHP) studies using electrical stimulation of motor or\npremotor areas that are directly involved in reach control. As noted in the literature,\noptogenetically evoked behavioral effects have been difficult to achieve. The fact that we\nobserved such effects from PPC stimulation, despite it not being a primary motor area,\nhighlights the strength of our interface: it is capable of optically modulating circuits on a\nsufficiently large scale to induce measurable behavioral outcomes. We have clarified this\ndistinction in the Discussion, paragraphs 12 and 13.\n2. Our behavioral measures demonstrate impaired reaching performance following optogenetic\nstimulation. As discussed above, the observed delays are comparable to those reported with\nexcitatory stimulation (e.g., electrical stimulation), suggesting that in both cases, circuit\ndisruption is the likely underlying mechanism. Understanding the precise downstream neural\neffects would require additional experiments, which are beyond the scope of the current\nstudy.\n3. We recognized that photo-induced artifacts are apparent in the ECoG signals, and therefore\nwe developed an effective method of removing photo-induced artifacts. We now include a\nbrief description of the method in the Results section (“Photo-induced artifact removal”) as\nwell as a more detailed description in the Methods section (“Photo-induced artifact\nremoval”).\n4. In response to the general concern regarding our unexpected finding that activation of an\ninhibitory opsin led to increased ECoG power, we have made substantial revisions to the\nmanuscript. These additions—including new data and improved contextual explanations—\ncollectively strengthen the validity of our findings:\na. We introduced a new simulation model to further investigate the observed increase in\nECoG power. The simulation results are consistent with our in vivo data (see the final\nparagraph of the “Stimulation at rest” section, Supp. Fig. 5, and Discussion paragraphs 9\nand 10).\nb. We added data examining the relationship between opsin expression and neural\nactivity during reach behavior (see the final paragraph of the Results section and Fig. 8).\nc. We expanded Fig. 6 (formerly Fig. 5) to include longitudinal stimulation data.\nd. We also included stimulation results from a naïve (non-expressing) animal (Fig. 6d).\nThis animal, along with another in which opsin expression had faded over time, showed\nno significant stimulation-evoked activity relative to baseline. These data further support\nour claim that significant responses were specific to opsin-expressing regions.\ne. We expanded our discussion of the functional roles of areas 5 and 7 in reaching\nbehavior, incorporating relevant literature as suggested (see Discussion, paragraph 12).\nTogether with our control data (e.g., Figs. 5 and 6), these revisions provide a more\ncomprehensive and well-supported interpretation of the observed increase in ECoG activity.\nPlease note that Supp. Fig. 5 has been split into two new places: Fig. 4 and Supp. Fig. 8.\nI was surprised that the authors averaged their results across all ECoG channels (Fig. 4 G-O; 7). Surely, in\nFigure 5, they distinguish between transduced and non-transduced sectors. I recommend that they apply\na similar analysis based on the functional properties of the cortex under the electrodes. For example, by\nusing task-induced neuronal activity (such as reaching-related activity) from both transduced and non-\ntransduced areas, they could define regions of interest (ROIs) across 4 different cortical regions\n(transduced or not, functionally relevant or not). This would allow for a more refined analysis of the\ndata.\nIn response, we have revised the manuscript to include data from individual electrodes,\nseparated by opsin expression status, behavioral and stimulation state and removed the previous\nFig. 7, which pooled data across conditions. We believe that the revised Figs. 5 and 6, and newly\nadded Fig. 8, now address the Reviewer’s concerns more effectively.\nSpecifically, Fig. 6 (formerly Fig. 5) now distinguishes between electrodes located in opsin-\nexpressing versus non-expressing regions. In addition, we have collected and incorporated new\ndata comparing reach-related activity between stimulated and non-stimulated conditions, and\nbetween opsin-expressing and non-expressing areas, as suggested by the Reviewer (Fig. 8).\nAs shown in Fig. 8b, ECoG signals from the majority of electrodes are modulated by reach\nbehavior. This is consistent with the role of the PPC, which is known to support complex\nmultisensory integration for goal-directed actions. Unlike the motor and somatosensory\ncortices—which are more precisely subdivided by body part—the PPC integrates information\nacross modalities and effectors, and such broad activation is expected.\nPlease note that Figs. 4 and 5 have been renumbered as Figs. 5 and 6, respectively.\nMoreover, it would be valuable to replicate these experiments using a penetrating electrode (e.g., a\nlaminar probe) to compare the surprising ECoG data with single- or multi-unit recordings, providing\nadditional insight into the neuronal effects.\nWhile we agree that this is an exciting direction, it is unfortunately beyond the scope of the\ncurrent study, as our present platform design does not support simultaneous ECoG and depth\nrecordings during optical stimulation.\nHowever, to further investigate the unexpected increase in ECoG power, we have added a new\noptogenetic simulation model to the study. This model allows for simulated recordings of both\nspikes and LFPs at multiple cortical depths during surface optical stimulation. The simulation\nresults are consistent with our in vivo findings (see the final paragraph of the “Stimulation at\nrest” section, Supplementary Fig. 5, and Discussion paragraphs 9 and 10).\nIn addition, we compare our results to previous work in which we recorded simultaneously from\nvarious cortical depths and the brain surface using ECoG during surface stimulation [11], [12].\nThose findings also align well with the observations reported in this study.\nIn summary, this is a highly interesting technical paper that somehow should be published, but I believe\nit should be considered for its methodological contributions rather than its neuroscientific conclusions.\nAs such, I am presently unconvinced it is suitable for publication in Nature Communications. IMHO, a\nmore thorough investigation of the neuronal and behavioral effects (see below) is warranted, but I\nrefrain to the editors to make that call.\nMinor Comments:\n1. Method Limitations: The authors highlight the advantages of their new method but should also\nmention its limitations. For example, the method is limited to recording from superficial, easily\naccessible parts of the cortex and cannot capture data from structures buried in sulci or from deeper\ncortical areas that are not accessible with the current setup. Surely, more limitations can be listed.\nWhile we do not include a formal limitations section, we have acknowledged the limitations of\nour system throughout the Discussion. These include finite temporal and spatial optical access,\na restriction to 32 recording channels, the invasiveness of the chamber implantation procedure,\nand other practical considerations.\n2. Neuronal Data with Dura Resection: The authors mention that their MMAD allows recording for 10-14\nweeks, after which dura growth requires resection. While stability of GFP expression is clearly illustrated\nin Figure 3, it would be informative to include raw neuronal traces for the same periods, along with both\nGFP and neuronal data after multiple dura resections (e.g., approximately 2-3 years post-implant).\nIn response, we have:\n1. Added ECoG traces in Fig. 4.\n2. Added epifluorescence data after 97 weeks in Monkey H (Fig. 6b) and before and after\nreinjection in Monkey L (Fig. 6e, insets).\n3. Added ECoG data of electrodes in opsin expressing and deficient regions across time (Fig. 6e).\nThe data include stimulation-evoked ECoG responses after initial injection, reinjection, and\ndura resection. Please note that most of the sessions report statistically significant responses.\n3. Figure 3C: This figure requires more explanation. It is unclear what point the authors are trying to\nmake, and further clarification would be helpful.\nThe figure has been reconfigured as a pie-graph for clarity.\n4. Figure 4: The fonts and arrowheads in this figure are barely visible. Please increase their size for better\nclarity.\nWe have enlarged Fig. 5 (formerly Fig. 4) and improved its resolution.\n5. Figure 4 Statistical Analysis: I suspect the statistics in Figure 4 use a Wilcoxon signed-rank test. It is\nunusual to observe significant changes in the pre-stimulation period. Was a correction for multiple\ncomparisons applied? If not, this should be done. If a correction was applied, could the authors explain\nthe pre-stimulation differences?\nWe reviewed and improved our analysis: Fig. 5 (formerly Fig. 4) now does not contain any\nsignificance prior to the onset of stimulation. Bonferroni correction was applied, and this is now\nstated in the figure caption.\n6. Non-Neuronal Effects: The authors argue that the ECoG responses are “primarily” optogenetically\nevoked (non-thermal). However, control experiments indicate substantial non-neuronal effects. Can the\nauthors estimate the contributions of these two effects (neuronal vs. non-neuronal) to the observed in\nvivo data?\nFirstly, we have revised our text for improved nuance and clarity in the “Stimulation at rest”\nsection and throughout the paper.\nSecondly, we provide controls which demonstrate that these ECoG data, including the\noptogenetically-evoked responses, are neuronal, and we have improved our paper to support\nthese claims:\n1. We provided data with stimulation in expressing and non-expressing areas (Fig. 6)\nsuggesting significant optogenetic effects.\n2. The blue light stimulation results (Fig. 6c) are better explained by optogenetics than thermal\neffects (see Discussion paragraph 11 and “Stimulation at rest” paragraph 4).\n3. Additional data now added to Fig. 6 (formerly Fig. 5) shows similar stimulation results\nbetween a monkey with no expression (the monkey was never injected with optogenetic\nvector) and a monkey with expression that had mostly faded 2 years following viral vector\ninfusion – both had non-significant increases in stimulation-evoked activity with respect to\nbaseline, which supports our claims throughout the paper of recording statistically significant\noptogenetically-evoked activity from opsin expressing areas.\n4. Other controls (e.g., Fig. 5, Fig. 6) further support our finding of an increase in ECoG signals\nin response to stimulation of opsin expressing areas.\nThirdly, we have a few comments regarding disentangling “neuronal vs. non-neuronal” effects:\n1. The light-evoked artifact in the ECoG signals is non-neuronal and is rejected with a rigorous\nprocess that estimates and then rejects non-neuronal signals with a rigorous PCA-based\nalgorithm which estimates light-evoked in vivo ECoG artifacts with ECoG recordings of light-\nevoked artifacts generated in a neuron-free environment (see the “Photo-induced artifact\nremoval” sections in both the Results and Methods).\n2. We have updated the text to explain that we expected neural network effects to propagate\noptogenetically-evoked neural activity after the end of stimulation (see “Stimulation at rest”\nparagraph 4), and into opsin deficient regions (see Discussion paragraph 8), which makes\nsome neuronal responses difficult to predict.\n3. Regarding the distinction between thermal and optogenetically evoked responses, we have\nconducted extensive experiments and included multiple controls—such as stimulation with\ndifferent wavelengths, a naïve animal with no viral injection, brain areas lacking opsin\nexpression, and time points after expression had decayed. Across all these conditions, our\nfindings consistently support that the observed responses are optogenetically evoked. If any\nthermal effects are present, they are minimal and not significant.\nDue to these data and discussion points, we conclude that we have removed a substantial\namount of non-neuronal light-evoked artifact and while the net result may contain some small\ndegree of thermally-evoked neuronal responses, our controls and simulation work indicate that\nwe have recorded a substantial amount of optogenetically-evoked neuronal data. Elsewhere in\nthis response and in the updated paper (e.g., Discussion paragraphs 8 and 9) we reason why the\nECoG recordings were unexpectedly increased due to the activation of Jaws, rather than\ndecreased.\n7. Behavioral Data Statistical Analysis: Was a correction for multiple comparisons applied to the\nbehavioral data? If not, I suggest this be done to ensure the robustness of the results.\nOur initial experimental design focused on examining how stimulation would affect behavioral\nmetrics, including reach time, path length and reach direction, which we carefully recorded. For\nthese hypotheses, we did not adjust p-values as the nature of our hypotheses were not\nexploratory.\nWe have updated the manuscript to clarify this distinction. Additionally, in response to the\nReviewers' comments, we have substantially reorganized the behavioral data and corresponding\ntext to better highlight the technological contributions of our platform.\n8. Spatially-Specific Behavioral Effects: I was surprised by the lack of consistent spatially-specific\nbehavioral effects. How reliable were these effects across sessions or across trial blocks within the same\nsession? Test-retest reliability should be shown to strengthen the findings.\nWe have added new data on optogenetically-evoked behavioral responses across days in Supp.\nFig. 6, which illustrates variability across days and within a session. Please also see the revised\nDiscussion, paragraph 13, where we explain how our findings are comparable to previous non-\nhuman primate reaching studies involving neural stimulation in motor areas.\nRegarding the observation of spatially specific behavioral effects—such as certain reach\ndirections being impaired while others are unaffected—we agree that this is an intriguing finding\nthat warrants further investigation. We speculate that differences in opsin expression patterns\nacross the two animals may underlie the variability in these effects.\n9. Figure 6 Significance Indicators: The asterisks indicating significance in Figure 6 do not always match\nthe descriptions in the text. Please check for accuracy. Were all trials included in the analysis for this\nfigure?\nWe have updated the figure and caption to include detailed information about the plots to match\nthe text. The counts of successful trials (and thus the number of trials used to generate the bar\nplots) are reported in Supp. Table 1.\nPlease note that Fig. 6. has been renumbered to Fig. 7.\n10. Figure 7: As mentioned earlier, it would be highly informative to show time-frequency plots for four\ndifferent electrode sites (transduced vs. non-transduced and task-modulated vs. non-task-modulated\nsites).\nTo address your comment, newly added data (Fig. 8) more deeply explores activity of example\nelectrodes in opsin deficient and opsin expressing areas in the context of reach. As shown in Fig.\n8b, the majority of electrodes cover areas significantly modulated by reaching behavior.\nBased on the feedback from Reviewers, we have substantially reorganized the presentation of\nour data, and in doing so have removed the figure the Reviewer references (“Figure 7”) and\ninstead include a new, and more detailed, Fig. 8.\n11. Interpretation of Reaching Behavior: The authors interpret the stimulation-induced changes in\nreaching behavior as changes in motor dynamics. However, this region of the parietal cortex is involved\nin a variety of interrelated functions, including but not restricted to e.g. attention, multisensory\nintegration, and decision-making. How do the authors disentangle these contributions from the motor\nchanges observed in the reaching task?\nThe text (Discussion paragraph 12) has been updated to address this concern. Our study is meant\nto be a proof-of-concept that cortical areas modulated with an inhibitory opsin can, indeed,\neffect behavior and thus could be a powerful outcome for the sorts of disentanglement\nexperiments the Reviewer, and others, may devise. Disentangling such functions is an interesting\nquestion that is unfortunately out of scope for this paper as it would require other behavioral\ntasks to be performed in conjunction with optogenetic stimulation. Newly added data (Fig. 8,\nincluded in the manuscript due to inspiration from the Reviewer) is another proof of concept of\nhow our interface can be used to intervene with the brain function and study network dynamic in\ncorrelation with behavioral modulation.\nReviewer #4 (Remarks on code availability):\nNA\nReviewer #5 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of\nthe Nature Communications initiative to facilitate training in peer review and to provide appropriate\nrecognition for Early Career Researchers who co-review manuscripts.\nThe authors thank Reviewer #5 for their contributions.\nREFERECNES (specific to this Response to Reviewers document)\n[1] D. J. Griggs et al., ‘Improving the Efficacy and Accessibility of Intracranial Viral Vector Delivery in\nNon-Human Primates’, Pharmaceutics, vol. 14, no. 7, 2022, doi:\n10.3390/pharmaceutics14071435.\n[2] A. S. Chuong et al., ‘Noninvasive optical inhibition with a red-shifted microbial rhodopsin’, Nat\nNeurosci, vol. 17, no. 8, pp. 1123–1129, 2014, doi: 10.1038/nn.3752.\n[3] A. Galvan et al., ‘Nonhuman Primate Optogenetics: Recent Advances and Future Directions’, The\nJournal of Neuroscience, vol. 37, no. 45, p. 10894, Nov. 2017, doi: 10.1523/JNEUROSCI.1839-\n17.2017.\n[4] L. Acker, E. N. Pino, E. S. Boyden, and R. Desimone, ‘FEF inactivation with improved optogenetic\nmethods’, Proceedings of the National Academy of Sciences, vol. 113, no. 46, pp. E7297–E7306,\n2016, doi: 10.1073/pnas.1610784113.\n[5] A. Yazdan-Shahmorad et al., ‘A Large-Scale Interface for Optogenetic Stimulation and Recording in\nNonhuman Primates’, Neuron, vol. 89, no. 5, pp. 927–939, Mar. 2016, doi:\n10.1016/j.neuron.2016.01.013.\n[6] A. Yazdan-Shahmorad, D. B. Silversmith, V. Kharazia, and P. N. Sabes, ‘Targeted cortical\nreorganization using optogenetics in non-human primates’, Elife, vol. 7, p. e31034, 2018, doi:\n10.7554/eLife.31034.\n[7] I. Ozden et al., ‘A coaxial optrode as multifunction write-read probe for optogenetic studies in\nnon-human primates’, J Neurosci Methods, vol. 219, no. 1, pp. 142–154, 2013, doi:\nhttps://doi.org/10.1016/j.jneumeth.2013.06.011.\n[8] N. McAlinden et al., ‘Thermal and optical characterization of micro-LED probes for in vivo\noptogenetic neural stimulation’, Opt Lett, vol. 38, no. 6, pp. 992–994, 2013.\n[9] P. Andersen and E. I. Moser, ‘Brain temperature and hippocampal function’, Hippocampus, vol. 5,\nno. 6, pp. 491–498, 1995.\n[10] R. R. Price, ‘The AAPM/RSNA physics tutorial for residents: MR imaging safety considerations’,\nRadiographics, vol. 19, no. 6, pp. 1641–1651, 1999.\n[11] A. Yazdan-Shahmorad, D. R. Kipke, and M. J. Lehmkuhle, ‘Polarity of cortical electrical stimulation\ndifferentially affects neuronal activity of deep and superficial layers of rat motor cortex’, Brain\nStimul, vol. 4, no. 4, pp. 228–241, 2011, doi: https://doi.org/10.1016/j.brs.2010.11.004.\n[12] A. Yazdan-Shahmorad, D. R. Kipke, and M. J. Lehmkuhle, ‘High gamma power in ECoG reflects\ncortical electrical stimulation effects on unit activity in layers V/VI’, J Neural Eng, vol. 10, no. 6, p.\n066002, 2013, doi: 10.1088/1741-2560/10/6/066002.\nResponse to reviewers\nResponse to reviewer 1:\nThe authors have answered all my questions and comments satisfactorily.\nWe thank reviewer 1 for their support.\nResponse to reviewer 2:\nN/A\nResponse to reviewer 3:\nI acknowledge the authors’ efforts in addressing my previous concerns and enhancing\nthe manuscript’s clarity.\nWe thank reviewer 3 for their continued consideration of this manuscript.\nNonetheless, I remain unconvinced by the explanation provided for the observed\nincrease in ECoG power during rest. The authors attribute this rise to “disinhibition of\nneurons in lower cortical layers following inhibition of upper cortical layers,” yet no direct\nrecordings from distinct cortical layers were conducted to substantiate this claim.\nMoreover, given that the results were obtained after removing stimulation artifacts\nthrough a modeled approach, the possibility that this increase represents an artifact\ncannot be dismissed. This issue is pivotal for the robust validation of the platform.\nTherefore, I strongly recommend that the authors pursue a more rigorous experimental\napproach rather than relying solely on simulations to confirm this phenomenon. For\ninstance, injecting the same virus into a naive monkey and examining neural responses\nacross cortical layers during light stimulation would provide more definitive evidence.\nWe appreciate the Reviewer’s thoughtful suggestion regarding the additional\nexperiment. At this stage, however, it is not feasible for us to perform this\nexperiment in our current animals because our platform is not designed for depth\nrecordings, and conducting the work in a new naïve animal would raise ethical\nconcerns relative to the 3Rs principles.\nThat said, we took the previous round of Reviewer feedback very seriously. In\nresponse to the detailed comments and questions, we carried out extensive\nadditional data collection and analysis using both previously studied animals and\na naïve animal, and we substantially revised and reorganized the manuscript and\nfigures. We believe these new additions further confirm that the neural responses\nwe observe are optogenetically induced. In addition, in this recent version of the\nmanuscript, we have included data from the second monkey (H) after reinjection\n(fig. 6f) which further strengthens our results. As a reminder, below we are listing\nall additional data and changes to the manuscript in response to the reviewer’s\nfirst round of comments.\nHighlights of new data added to the manuscript include:\n• Control data from a naïve monkey.\n• Control data from one of our animals approximately two years after injection.\n• Evidence of renewed optogenetic-evoked activity following reinjection of the\noptogenetic viral vector.\n• Data and analyses showing how opsin-expressing and opsin-deficient areas\ninfluence neural activity with and without behavior.\n• Additional longitudinal neural and behavioral data.\n• Measurements of optically induced temperature changes.\n• Expanded details on our artifact-rejection method.\nHighlights of new analyses and discussion include:\n• A new simulation component that supports our in vivo ECoG findings.\n• Refined behavioral analyses and strengthened comparisons with related\nliterature.\n• A clearer mechanistic explanation for why inhibitory opsin stimulation could\nincrease ECoG activity, supported by new in vivo and simulation data, additional\nanalyses, and an expanded literature review.\nAdditionally, I suggest the authors broaden their investigation to elucidate the differential\neffects observed between LED and laser stimulation. Specifically, it is important to\nclarify why laser stimulation, as shown in Figure 5, produces a more focal yet prolonged\nactivation compared to LED. Addressing these points will significantly strengthen the\nmanuscript’s scientific rigor and impact.\nFrom a hardware perspective, we believe that the focal, collimated nature of\nlaser stimulation will naturally produce different effects than the less focal,\nuncollimated nature of LED stimulation. With that, we believe it is possible for the\nhighly focal effects of laser stimulation to evoke local neural responses that\npersist, to some degree, after the termination of stimulation. We have updated\nthe results and discussion sections accordingly.\nFrom the perspective of neuronal circuitry, we believe the prolonged neural\nresponse is probably the result of neural network complexities, including the\npossibility of rebound effect (Shapiro et al., 2025, J Physiology). The observation\nof rebound effect in simulation also corroborates in vivo stimulation data. This is\nnow added to the results section.\nWe also realized that the differences in the colorbar scales between the laser\nand LED stimulation conditions could be confusing and might lead to incorrect\nvisual comparisons. To avoid this and improve clarity, we adjusted the scales so\nthey are now consistent across both conditions.\nResponse to reviewer 4:\nThe authors addressed all my comments.\nI commend them for this impressive methodology.\nWe thank reviewer 4 for their support.\nResponse to reviewer 5:\nN/A"}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have answered all my questions and comments satisfactorily.", "reviewer_3": "I acknowledge the authors’ efforts in addressing my previous concerns and enhancing the manuscript’s clarity. Nonetheless,\nI remain unconvinced by the explanation provided for the observed increase in ECoG power during rest. The authors\nattribute this rise to “disinhibition of neurons in lower cortical layers following inhibition of upper cortical layers,” yet no direct\nrecordings from distinct cortical layers were conducted to substantiate this claim. Moreover, given that the results were\nobtained after removing stimulation artifacts through a modeled approach, the possibility that this increase represents an\nartifact cannot be dismissed. This issue is pivotal for the robust validation of the platform. Therefore, I strongly recommend\nthat the authors pursue a more rigorous experimental approach rather than relying solely on simulations to confirm this\nphenomenon. For instance, injecting the same virus into a naive monkey and examining neural responses across cortical\nlayers during light stimulation would provide more definitive evidence.\nAdditionally, I suggest the authors broaden their investigation to elucidate the differential effects observed between LED and\nlaser stimulation. Specifically, it is important to clarify why laser stimulation, as shown in Figure 5, produces a more focal yet\nprolonged activation compared to LED. Addressing these points will significantly strengthen the manuscript’s scientific rigor\nand impact.", "reviewer_4": "The authors addressed all my comments.\nI commend them for this impressive methodology."}, "author_response": "Response to reviewers\nResponse to reviewer 1:\nThe authors have answered all my questions and comments satisfactorily.\nWe thank reviewer 1 for their support.\nResponse to reviewer 2:\nN/A\nResponse to reviewer 3:\nI acknowledge the authors’ efforts in addressing my previous concerns and enhancing\nthe manuscript’s clarity.\nWe thank reviewer 3 for their continued consideration of this manuscript.\nNonetheless, I remain unconvinced by the explanation provided for the observed\nincrease in ECoG power during rest. The authors attribute this rise to “disinhibition of\nneurons in lower cortical layers following inhibition of upper cortical layers,” yet no direct\nrecordings from distinct cortical layers were conducted to substantiate this claim.\nMoreover, given that the results were obtained after removing stimulation artifacts\nthrough a modeled approach, the possibility that this increase represents an artifact\ncannot be dismissed. This issue is pivotal for the robust validation of the platform.\nTherefore, I strongly recommend that the authors pursue a more rigorous experimental\napproach rather than relying solely on simulations to confirm this phenomenon. For\ninstance, injecting the same virus into a naive monkey and examining neural responses\nacross cortical layers during light stimulation would provide more definitive evidence.\nWe appreciate the Reviewer’s thoughtful suggestion regarding the additional\nexperiment. At this stage, however, it is not feasible for us to perform this\nexperiment in our current animals because our platform is not designed for depth\nrecordings, and conducting the work in a new naïve animal would raise ethical\nconcerns relative to the 3Rs principles.\nThat said, we took the previous round of Reviewer feedback very seriously. In\nresponse to the detailed comments and questions, we carried out extensive\nadditional data collection and analysis using both previously studied animals and\na naïve animal, and we substantially revised and reorganized the manuscript and\nfigures. We believe these new additions further confirm that the neural responses\nwe observe are optogenetically induced. In addition, in this recent version of the\nmanuscript, we have included data from the second monkey (H) after reinjection\n(fig. 6f) which further strengthens our results. As a reminder, below we are listing\nall additional data and changes to the manuscript in response to the reviewer’s\nfirst round of comments.\nHighlights of new data added to the manuscript include:\n• Control data from a naïve monkey.\n• Control data from one of our animals approximately two years after injection.\n• Evidence of renewed optogenetic-evoked activity following reinjection of the\noptogenetic viral vector.\n• Data and analyses showing how opsin-expressing and opsin-deficient areas\ninfluence neural activity with and without behavior.\n• Additional longitudinal neural and behavioral data.\n• Measurements of optically induced temperature changes.\n• Expanded details on our artifact-rejection method.\nHighlights of new analyses and discussion include:\n• A new simulation component that supports our in vivo ECoG findings.\n• Refined behavioral analyses and strengthened comparisons with related\nliterature.\n• A clearer mechanistic explanation for why inhibitory opsin stimulation could\nincrease ECoG activity, supported by new in vivo and simulation data, additional\nanalyses, and an expanded literature review.\nAdditionally, I suggest the authors broaden their investigation to elucidate the differential\neffects observed between LED and laser stimulation. Specifically, it is important to\nclarify why laser stimulation, as shown in Figure 5, produces a more focal yet prolonged\nactivation compared to LED. Addressing these points will significantly strengthen the\nmanuscript’s scientific rigor and impact.\nFrom a hardware perspective, we believe that the focal, collimated nature of\nlaser stimulation will naturally produce different effects than the less focal,\nuncollimated nature of LED stimulation. With that, we believe it is possible for the\nhighly focal effects of laser stimulation to evoke local neural responses that\npersist, to some degree, after the termination of stimulation. We have updated\nthe results and discussion sections accordingly.\nFrom the perspective of neuronal circuitry, we believe the prolonged neural\nresponse is probably the result of neural network complexities, including the\npossibility of rebound effect (Shapiro et al., 2025, J Physiology). The observation\nof rebound effect in simulation also corroborates in vivo stimulation data. This is\nnow added to the results section.\nWe also realized that the differences in the colorbar scales between the laser\nand LED stimulation conditions could be confusing and might lead to incorrect\nvisual comparisons. To avoid this and improve clarity, we adjusted the scales so\nthey are now consistent across both conditions.\nResponse to reviewer 4:\nThe authors addressed all my comments.\nI commend them for this impressive methodology.\nWe thank reviewer 4 for their support.\nResponse to reviewer 5:\nN/A"}]

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