High-throughput two-photon volumetric brain imaging in freely moving mice

Domain: physics
Published: 2025-11-29
Editorial outcome: major_revision

Abstract
Imaging neural activities across large volumes at subcellular resolution without impeding animal behaviors remains difficult. Here, we develop a high-throughput miniature Bessel-beam two-photon microscope (miniBB2p) capable of imaging calcium dynamics from neurons and dendrites over a volume of 420 × 420 × 80 μm³ during free behavior. We share a full description of miniBB2p and demonstrate its ability to perform large-scale recordings of the calcium activities of more than 1000 neurons at a time in anterior cingulate cortex and secondary motor cortex of freely moving mice in various behavioral paradigms. Our results position miniBB2p to advance the design of miniature multiphoton microscopes, facilitating precise monitoring of neural activities across large populations within a three-dimensional volume in freely moving animals.

Introduction
Head-mounted miniature multiphoton microscopy offers a promising avenue for investigating neural activity during free and naturalistic behavior in mice and rats, thanks to its inherent optical sectioning and deep tissue penetration capabilities1. Recent advancements in optical fibers, miniature detectors, laserscanners, focus-tunable lenses, and objectives have significantly improved the performance of miniature multiphoton microscopes2–10, leading to a substantial increase in the number of neurons that can be imaged in freely moving animals in practical neurobiological investigations10–13. However, several limitations are presented in existing miniature multiphoton microscopes. First, rapid volumetric imaging is challenging due to the sequential acquisition of each voxel, especially when using high numerical aperture (NA) objectives that offer superior lateral and axial resolution. While advanced platforms with fast focus-tunable lenses can scan the focus axially in milliseconds5,10, a restricted number of thin optical sections within a volume can be imaged at a time, albeit at the expense of imaging speed and resolution. Second, the shallow depth of field of the microscope makes imaging susceptible to brain tissue movement, particularly axial movement. This issue is a common concern in imaging head-fixed animals14 and would be exacerbated when imaging freely moving animals, as brain movement is less constrained8. Finally, while customized optics such as miniature objectives have been utilized to achieve higher resolution and larger field of view (FOV), achieving diffraction-limited resolution across the FOV remains difficult6,8,10. This challenge arises from the need to fit all optics into a compact space of a few cubic centimeters, which poses extra hurdles for lens design and assembly.

A Bessel beam can address these limitations. In recent years, tabletop two-photon microscopes (2PM) utilizing Bessel beams have shown several distinct features over the widely used Gaussian beams15–20. Gaussian-beam 2PM records a stack of 2D optical sections across the depth to achieve 3D imaging; it favors resolving the fine structures in the axial dimension at a compromised imaging speed. In contrast, Bessel-beam 2PM captures projected views of volume structures by scanning an axially elongated focus in 2D. This process transfers the 2D scan rate into a volumetric imaging rate, increases the information throughput, and reduces the data size. It is an effective tool for volumetric calcium imaging in vivo, as the position of neurons and their fine structures remains stable during imaging17. In addition, if needed, the axial coordinates of structures in the 2D projection scan can be retrieved with a full 3D reference image from a Gaussian-beam 2PM. The extended depth of field also makes imaging resistant to axial movements of brain tissue17, which is preferred in monitoring neural circuits in freely moving animals. Moreover, in comparison to Gaussian-beam 2PM, Bessel-beam 2PM achieves better lateral resolution at the same excitation NA17,18 and is mainly sensitive to astigmatism among all primary optical aberrations, indicating the potential of designing simple lenses for miniature microscopes20,21.

In this work, taking advantage of these unique features of Bessel beams in two-photon imaging, we develop a head-mounted miniature Bessel-beam two-photon microscope (miniBB2p) and demonstrate high-throughput volumetric calcium imaging in secondary motor cortex (M2) and in anterior cingulate cortex (ACC) in freely moving mice.

Results
Bessel beam simplifies the optical design in miniBB2p
Among all primary optical aberrations, including spherical aberration, coma, astigmatism, field curvature, and distortion, the Bessel beam is mainly sensitive to astigmatism20,21. Leveraging this characteristic, we utilized a systematic approach in miniBB2p to eliminate astigmatism while minimizing other primary aberrations. Briefly, we adopted a symmetric design for the scan and tube lenses, each comprising two identical plano-convex lenses (Fig. 1a). This symmetry minimizes coma, distortion, and lateral color aberration. Uncorrected astigmatism was fully compensated by the objective formed by two plano-convex lenses (Fig. 1b). In parallel, other aberrations in the objective were well-contained under the low excitation NA of 0.3, leading to near-diffraction-limited performance over a FOV of Ø600 μm (Fig. 1c). Throughout the entire FOV, we found negligible blurring of the Bessel focus from the residual spherical aberration and coma, in contrast to the blurring observed with a Gaussian focus (Supplementary Fig. 1). We noted that the residual field curvature and distortion simply shift the focal position without blurring the focus (Fig. 1d and Supplementary Fig. 1). The systematic design approach focused on astigmatism correction in miniBB2p significantly reduced the number of lenses in the microscope compared to conventional designs that seek to correct all major aberrations for individual lenses. This reduction not only lowered manufacturing costs but also simplified assembly and alignment, while still maintaining high image quality (Supplementary Table 1).

System design and performance testing of miniBB2p
The headpiece of miniBB2p weighed a total of 2.6 grams and was about 2.4 × 0.9 × 2.0 cm³ in size, making it well suited for brain imaging in freely moving mice (Fig. 2a-d, Supplementary Fig. 2 and Methods). We used a 1-meter large-mode-area photonic crystal fiber (LMA-12, NKT Photonics) to transmit the 920-nm femtosecond laser pulses for two-photon excitation. This endlessly single-mode photonic crystal fiber supports single-mode delivery over a broad spectral range from 700 to 1700 nm22. The pulse in the fiber was broadened by material dispersion and nonlinear effects (e.g., self-phase modulation)23. Benefitting from the large mode area (~Ø10 µm), nonlinear effects in the fiber were substantially reduced. The pulse width after dispersion pre-compensation at the fiber output end was less than 200 fs at laser powers below 40 mW and less than 300 fs at laser powers below 100 mW (Supplementary Fig. 2b and Methods). To generate the Bessel beam, we engineered a custom micro-axicon with an apex angle of 120° at the fiber tip (Fig. 2b, Supplementary Fig. 2c and Methods). A microelectromechanical systems (MEMS) mirror was used as the scanner, enabling a maximum square FOV of 420 × 420 μm² and a frame size of 512 × 512 pixels at 9 frames per second.

The miniBB2p featured a working distance of 1 mm in water, an excitation NA of 0.26, and a collection NA of 0.95. Lateral and axial resolution measured with 500-nm fluorescent beads were 0.97–0.99 μm and 80–90 μm across the FOV (Fig. 2e and Supplementary Fig. 3). The lateral resolution obtained is equivalent to the diffraction-limited resolution using a Gaussian beam at a higher NA of 0.35. Notably, fluorescence collection efficiency is 2–4 times greater than that in the state-of-the-art platforms with a comparable FOV and lateral resolution8–10 (Supplementary Figs. 4a–d and Supplementary Table 1). In addition, fluorescence was directly detected after the objective and filters using an onboard silicon photomultiplier, which offered higher detection efficiency and less tethered burden than fluorescence collection using thick fibers as a relay unit6.

Imaging comparison between miniBB2p and tabletop Gaussian-beam 2PM
We first imaged Thy1-GFP-M mouse brain slices to demonstrate the throughput and resolution of miniBB2p (Fig. 2f-g). Using a commercial tabletop Gaussian-beam 2PM (0.3 NA, axial resolution 22.9 μm), a stack of at least 4 images is required to cover all structures within an 80-μm thick volume. In comparison, miniBB2p captured the same information in one image, with a fourfold increase in depth of field. Moreover, the higher resolution in Bessel focus allowed easier visualization of dendritic spines (Fig. 2g). These observations were also found in a head-fixed mouse brain (Supplementary Fig. 5). We then employed miniBB2p to image spontaneous neural activities in freely moving mice. We resolved calcium dynamics of 1015 neurons at a time in ACC (Fig. 2h-j and Supplementary Video 1). This result was validated through structural imaging at same region and neural activity imaging in the top, middle, and bottom layers within the same volume using the tabletop 2PM on head-fixed mice (Fig. 2k, l). The latter approach identified 534 neurons across the three layers, approximately half the number of neurons resolved with miniBB2p. Beyond that, miniBB2p was able to image calcium transients in dendritic trees and spines along multiple dendritic branches in an axially extended volume (Supplementary Figs. 6, 7 and Supplementary Videos 2–4). These measurements underscored the benefits of high-resolution volumetric imaging enabled by miniBB2p.

MiniBB2p enables longitudinal recordings with minimal constraints on animal behavior
To assess the impact of carrying miniBB2p during imaging on animal behavior and mobility, we compared the movements between the naive mice carrying nothing and the mice carrying the dummy microscope with the same weight, fiber and cables as miniBB2p (Fig. 3 and Methods). While the mice freely exploring the behavioral arena, no significant difference were found in the total distance traveled (Fig. 3e, g), mean and median running speed (Fig. 3b, c, f), and the number of entries into the central coverage (Fig. 3d) between the naive mice and mice with dummy. In addition, we did not observe any notable variations of the running distance in the central and corner area of the arena following installation of the dummy microscope (Fig. 3g). These observations suggested that carrying miniBB2p along with the fiber and cables did not significantly impede the animal behavior. In addition, we evaluated the feasibility of conducting longitudinal studies using miniBB2p by imaging the same FOV and examining the number of identical cells recorded over multiple days. Our results revealed that the same neuronal populations could be monitored for weeks, with minimal photobleaching and photodamage (Supplementary Figs. 8–10), highlighting miniBB2p’s suitability for chronic imaging applications.

Using miniBB2p for high-throughput imaging of the neural activities across different behavioral paradigms
We used miniBB2p to record high-throughput proof-of-principle data from neuronal populations in M2 and ACC of freely moving mice in a variety of behavioral paradigms. First, we investigated the response of pyramidal neurons in M2 to locomotion over a 30-minute recording period in freely moving mice. (Fig. 4a-c and Supplementary Video 5). Running increased the mean ΔF/F in most neurons (Fig. 4d), with a running modulation index (MI) showing increased activity during running (Fig. 4e; n = 878 neurons, running MI 0.156 ± 0.006, mean ± s.e.m.). In addition, we inspected the average fluorescence changes aligned with running onsets and found that 38.2% of the neurons recorded significantly increased their activities upon running onset (Fig. 4f and Methods), resembling the study from recordings in primary somatosensory cortex (S1)24.

Next, we examined the neural activity in ACC under different pain stimulation paradigms in freely moving mice. We imaged the calcium activity of 673 ± 104 (n = 5 mice, mean ± s.e.m.) pyramidal neurons both before and after administrating a peripheral stimulus, either a noxious 27G pinprick or control, non-noxious 0.4 g von-Frey filament, to the paw contralateral to the recording site of the brain (Fig. 5a, b, Supplementary Video 6 and Methods). After signal processing and identification of active neurons (Fig. 5c), we observed that ACC neurons exhibited only low-level calcium activity in response to non-noxious stimuli. In contrast, these neurons showed an increase in calcium activity when subjected to noxious stimuli (Fig. 5d). We then analyzed the average peak ΔF/F in response to both non-noxious and noxious stimuli, which revealed a significantly higher response to noxious stimuli in comparison to non-noxious stimuli (Fig. 5e). Furthermore, more neurons reacted to the noxious stimuli than to the non-noxious stimuli (Fig. 5f). Specifically, 13.10% of the neurons recorded responded to the noxious stimuli, whereas 8.53% responded to the non-noxious stimuli (Fig. 5g, h). These observations are consistent with previous studies showing increased firing rates in ACC neurons during noxious stimuli25,26.

Last, we imaged calcium activity of interneurons in ACC upon receiving pinprick stimuli, both before and after chemogenetic inhibition of neural activity in S1 (Supplementary Figs. 11a, b and Methods). S1 and ACC are well-known brain regions for processing the sensory and affective components of pain. The S1→ACC pyramidal neuron projection allows sensory pain information to be transmitted to a higher-order cortical center that regulates the affective experience26. However, it is not well understood whether ACC interneurons also receive nociceptive information from S1. Using miniBB2p, we found that interneurons in ACC became more sensitive to pinprick after the inactivation of S1 (Supplementary Figs. 11b, c), suggesting they receive nociceptive information from S126. This relationship highlights the role of these neurons in processing the sensory and affective aspects of pain.

Methods
Microscope setup and system control
A fiber-based femtosecond laser (FemtoFiber ultra 920, Toptica) with a built-in dispersion precompensation unit (−40000 to +1000 fs²) was used to produce femtosecond laser pulses at a center wavelength of 920 nm (920 ± 10 nm, 100 fs, 80 MHz, 1.2 W). Using an objective (LMPLFLN20×, Olympus), the laser was coupled into the LMA-12 fiber. Dispersion from the 1-meter fiber was fully compensated with the precompensation parameter set to −26000 fs². In miniBB2p, fiber tip with the custom axicon was aligned with a collimating lens (45-956, Edmund Optics) to generate the ring-shaped beam. The MEMS scanner (A3I12.2-1200AL, Mirrorcle) provided a 1.2-mm diameter mirror with the first resonant frequency of both axes at ~2.6 kHz and it was used at a 30° incidence angle. After the scan lens and tube lens, which were formed by four identical plano-convex lenses (48-704, Edmund Optics) in a symmetrical configuration, a dichroic mirror (DMR-805SP, LBTEK; 1 mm thick; cut into pieces of 7 × 7 mm² by Sunlight) was used to separate the laser beam and fluorescence. The objective, consisting of two plano-convex lenses (47-850 and 65-300, Edmund Optics), was used to generate the Bessel focus in the specimen. Fluorescence was collected through the objective, dichroic mirror, and filters, and was detected with an onboard miniature, low-cost silicon photomultiplier (3 × 3 mm², S13360-3075PE, Hamamatsu). A reflective filter (FIL-800, 450–650 nm transmission, 6 × 6 mm², 0.2 mm thick, Sunlight) and a colored glass filter (FGB37-A, Thorlabs; 2 mm thick; cut into pieces of 6 × 6 mm² by Sunlight) were placed before the detector to reject the strong infrared laser. The microscope housing was made of carbon-fiber-enhanced plastic (PEEK-CF30) to reduce the weight of the headpiece.

The control signals for x-y scanning were generated from a MEMS controller (USB-SL MZ, Mirrorcle), which was also used to drive the acousto-optic modulator in the laser for power control and to trigger the data acquisition. The scanner was operated in resonance mode along the x-axis at 2304 Hz, scanning 4608 lines every second in bi-directional mode. This operation resulted in an image of 512 × 512 pixels at 9 frames per second. The x-axis scanning range was about √2 times the y-axis scanning range to achieve an early square FOV10. The silicon photomultiplier was wired by a thin coaxial cable (Ø 260 μm) to the driver circuit (C12332-01, Hamamatsu). The fluorescence signal was amplified by the same circuit and sampled with a digitizer (20 MS/s, M2p.5921-x4, Spectrum Instrumentation). The entire system was controlled by custom software based on the MATLAB (R2022a) platform.

Micro-axicon design
We customized a micro-axicon at the tip of the LMA-12 fiber (Comcore, China). Specifically, the tip of the photonic crystal fiber was collapsed and polished to form an axicon lens (apex angle = 120°). The laser from the photonic crystal region in the fiber was spread out at the collapsed region (~1 mm length) and transformed into a diverged ring beam by the axicon (Supplementary Fig. 2c). After the collimating lens, a focused ring beam was generated at the back focal plane of the scan lens, where the MEMS mirror was located. The maximum diameter of the ring beam that the mirror can accommodate is 1 mm, corresponding to a maximum excitation NA of 0.3. In this work, the diameter of the ring beam was measured to be 0.85 mm and it resulted in an excitation NA of 0.26.

Resolution and FOV calibration
We ascertained the resolution of miniBB2p by imaging 500-nm fluorescent beads (F8813, Thermo Fisher Scientific), with a pixel size of 0.1 μm to measure lateral resolution and an axial step size of 6 μm to measure axial resolution. The resolutions were evaluated as the full width at half maximum of the point spread functions (Supplementary Fig. 3). We calibrated the FOV of miniBB2p by imaging a 50-μm grid standard (RTR1Ee-P, LBTEK). Field distortion due to optical aberrations (Fig. 1d) and MEMS scan was corrected with the software DistortionCleaner (Supplementary Figs. 4e, f)10. All data in this study was displayed after distortion correction.

Tabletop Gaussian-beam 2PM
A tabletop Gaussian-beam 2PM (AX R MP, Nikon) with a water immersion objective (CFI Plan Fluor 10× W, NA 0.3, Nikon) was used to evaluate the performance of the miniBB2p. Lateral and axial resolution of the tabletop 2PM measured from 500-nm fluorescent beads were 1.34 ± 0.02 μm and 22.90 ± 0.47 μm (mean ± s.d., n = 5).

Animals
C57BL/6J wild-type mice (Jackson Laboratory stock No. 000664) were obtained and housed at the Laboratory Animal Resource Center (LARC) within the Chinese Institute for Brain Research, Beijing (CIBR). Thy1-GFP-M (STOCK Tg(Thy1-EGFP)MJrs/J, Jackson Laboratory stock No. 007788) and VGAT-Cre (B6J.129S6(FVB)-Slc32a1tm2(cre)Lowl/MwarJ, Jackson Laboratory stock No. 028862) transgenic mice were generously donated by Wenzhi Sun at CIBR. All mice were acquired at 5 weeks of age and allowed an average of 2 weeks to acclimatize to their new environment before the experiments began. Mice were housed in groups of up to 5 pre-surgery and 1-3 post-surgery. Housing conditions: 12 h reversed light/dark cycle (testing during dark phase); 23–25°C; 40–50% humidity; free access to food and water. All experimental procedures were approved by the Institutional Animal Care and Use Committee (IACUC) of CIBR (AP# CIBR-IACUC-063), in accordance with the governmental regulations of China.

Wild-type mice were used for locomotion behavior tests (n = 12; 5F (female)/7M (male); Fig. 3) and Thy1-GFP-M transgenic mice were used for structural imaging (n = 3; 1F/2M; Supplementary Fig. 5). Dendritic and spine calcium imaging was performed in wild-type male mice pre-injected in the ACC with rAAV2/9-hSyn-Cre and rAAV2/9-hSyn-DIO-jGCaMP8s (n = 6 for Supplementary Fig. 6; n = 1 for Supplementary Fig. 7). Neuronal calcium imaging was performed in wild-type male mice pre-injected in ACC/M2 with rAAV2/9-CaMKIIα-jGCaMP7f (n = 5 for Fig. 2h, i; n = 1 for Fig. 4; n = 5 for Fig. 5; n = 2 for Supplementary Fig. 8) and in VGAT-Cre transgenic male mice pre-injected in ACC with rAAV2/9-hSyn-DIO-jGCaMP8s and in S1 with rAAV2/9-CaMKIIα-hM4D(Gi)-mCherry (n = 3 for Supplementary Fig. 11).

Viral construction and packaging
Recombinant adeno-associated virus (rAAV) vectors were serotyped with AAV9 coat proteins and packaged at BrainCase viral vector manufacturing facilities. The viral titers were approximately 3.3 × 10¹² particles per milliliter for rAAV2/9-CaMKIIα-hM4D(Gi)-mCherry and 5.2 × 10¹² particles per milliliter for rAAV2/9-CaMKIIα-jGCaMP7f. Sparse expression was achieved by injecting a mixture of diluted rAAV2/9-hSyn-Cre particles (original titer: ~1.3 × 10¹³ particles per milliliter, diluted 5,000-fold in sterilized phosphate-buffered saline) and high-titer, Cre-dependent GCaMP8s virus (rAAV2/9-hSyn-DIO-jGCaMP8s, 5.2 × 10¹² infectious units per milliliter). Viral aliquots were stored in a light-protected freezer until use.

Surgical procedures
Mice were anesthetized with 1.5–2% isoflurane, and viral vectors were delivered to the ACC, M2, or S1 regions of the brain. A fitted plunger controlled by a hydraulic manipulator (Beijing Xinglin Life Tech., China) was inserted into a glass pipette to load and slowly inject 50 nL of viral vectors at a rate of 2 nL/5 s. Injections were performed bilaterally in the ACC at anteroposterior (AP) +1.3 mm, mediolateral (ML) ±0.3 mm, and dorsoventral (DV) −0.6 mm; bilaterally in S1 at AP −0.59 mm, ML ±1.5 mm, and DV −0.4 mm; and unilaterally in M2 at AP 0.6 mm, ML ±0.75 mm, and DV -0.5 mm. Following the injection, the microinjection needles were left in place for 10 minutes to allow viral diffusion and minimize the spread of viral particles along the injection tract. The pipette was then left in position for an additional 5 minutes before being slowly raised out of the brain.

After 3 weeks of expression, the mice were anesthetized with 1.5% isoflurane for cranial window implantation. Analgesic compound lidocaine cream was applied to the skin 10 minutes before the surgical incision, and ophthalmic ointment was used to prevent eye drying. The body temperature was maintained at 36°C using a feedback-controlled heating pad (FHC, USA). A craniotomy with a diameter of 4.3 mm was performed over either the ACC or M2, leaving the dura intact. A glass coverslip of matching diameter was placed over the cranial window, and the gap between the glass window and the skull was sealed with Vetbond (3M, USA). After that, the isoflurane concentration was reduced to 0.5–1%. The miniBB2p, with a custom titanium baseplate attached, was adjusted relative to the glass window to find the target plane for free-moving imaging. The baseplate was then secured with dental acrylic, and a custom cover was placed on the baseplate, fixed with screws, to protect the cranial window when not in use. Before surgery and testing, the mice were handled and pre-trained in the recording environment until they were acclimated and foraged freely within the box.

Mice handling and pretraining
Mice were habituated to the experimental environment for 3 days prior to the locomotion test or free-moving imaging. During the same period, they also underwent daily handling sessions to acclimate to head-mounted procedures. Handling included gentle head-cap pressing, back stroking, and holding the headcap firmly for approximately 10 seconds. Each session lasted 5–10 minutes and was designed to reduce stress and facilitate later dummy or real miniBB2p mounting in the awake state. All handling and behavioral procedures were conducted under simulated nighttime conditions.

For the locomotion test, awake mice were fitted with a dummy miniBB2p (or not, for controls) and allowed to habituate to the experimental environment for 30 minutes. They were then gently transferred to the open field arena for a 5-minute exploratory adaptation, followed by a 30-minute free-movement recording session (EthoVision XT 16, 10 Hz sampling). For free-moving imaging, the real miniBB2p was mounted while the mice were awake, followed by a habituation period in the imaging chamber placed over a mesh table. Once the animal exhibited stable and naturalistic movements, imaging recordings were initiated.

Imaging procedures
At the beginning of each imaging session, the mice were head-fixed, and the miniBB2p was mounted on the baseplate. Behavior of freely moving mice were recorded with a camera (MV-CS013-60GN, HIKROBOT) during the entire experiment. Initially, spontaneous neural activity was recorded while the mice habituated to the testing environment, freely exploring the 30 cm × 20 cm × 20 cm recording chamber without any experimenter-delivered sensory stimuli.

For noxious stimulation, the plantar surface of the hind paw contralateral to the brain recording site was pricked with a 27-gauge needle (pinprick) while the mice were freely moving. The stimulation ceased upon the withdrawal of the paw. Non-noxious stimulation was delivered to the same hind paw using a 0.4 g von Frey filament. In most cases, there was no withdrawal response to the von Frey filament. Each recording session included approximately 10 trials with variable inter-trial intervals of around 30 seconds to prevent sensitization. Throughout the sessions, no signs of behavioral sensitization or physical damage to the paws were observed.

Motion correction and image analysis
To eliminate motion artifacts in the calcium imaging data from each session, piecewise non-rigid motion correction was applied using NoRMCorre28 or Flow-Registration29 (used in Supplementary Fig. 7). The motion-corrected 9 Hz calcium activity videos were saved as .TIFF files and subsequently used for cell identification.

For C57BL/6J mice injected with rAAV2/9-CaMKIIα-jGCaMP7f, calcium signals were extracted using Suite2P, which constrains the instances of calcium activity for each neuron30. The analysis produced three traces for each identified region of interest (ROI), corresponding to putative cell somata: the raw fluorescence signal F_cell(t), the neuropil fluorescence signal F_np(t), and the deconvolved calcium activity E(t). F_cell(t) and F_np(t) represent the weighted averages of activity within the ROI and the surrounding neuropil, respectively, excluding pixels overlapping with other ROIs. To correct for neuropil contamination, the neuropil signal was subtracted from the raw calcium signal using a fixed coefficient31, yielding the corrected signal: F_corr(t) = F_cell(t) - 0.7 × F_np(t). To mitigate the effects of slow fluctuations such as photobleaching on F_corr, a running baseline F_0(t) was extracted. The calcium activity was then expressed as the fractional change in fluorescence relative to the baseline ΔF/F, calculated as ΔF/F = (F_corr(t) - F_0(t))/F_0(t).

For VGAT-Cre transgenic mice injected with rAAV2/9-hSyn-DIO-jGCaMP8s, the calcium imaging data from VGAT+ cells were analyzed using the commercial image-analysis platform AIVIA 11.0 (DRVision Technologies LLC, Bellevue, WA) in conjunction with the Cellpose plugin. The segmentations from Cellpose were converted into masks for individual neurons, and the averaged fluorescence signal within each mask was used to calculate calcium transients.

Locomotion test
Custom-made dummy miniscopes (2.6 g) were utilized to assess the impact of miniBB2p on the behavior of mice during imaging. These dummies replicated the shape and weight distribution of the actual miniBB2p and were mounted onto implanted head bars, accompanied by one fiber and two cables. Twelve adult C57BL/6 mice (n = 6, 4 M/2 F, real implants with ACC cranial windows; n = 6, 3 M/3 F, sham implants with head bar-only) were co-housed (2–3 per cage) under a 12 h reversed light/dark cycle. All mice underwent two counterbalanced trial phases: a control phase involving open-field exploration in a white acrylic arena (97.6 cm × 45 cm × 38 cm) without attachments, and a dummy phase following the same procedure but with a mounted dummy miniscope. Each subject completed one trial type per 24 h cycle. Locomotor parameters, including total distance traveled, mean/median velocity, central zone entries, and distance distribution (central vs corner zones) were quantified using the EthoVision XT 16 tracking software.

Brain slice preparation
Mice were deeply anesthetized with isoflurane and then transcardially perfused with ice-cold phosphate-buffered saline (PBS) followed by paraformaldehyde (PFA). After extraction, the brains were fixed overnight in PFA. The fixed brains were then sectioned into 85 µm-thick slices using a vibratome (Leica VT1200S). These brain slices were mounted onto slides using a mounting medium containing DAPI (Solarbio, China) to preserve the fluorescence signal for long-term storage.

Calcium response analyses
For the pain stimulation experiments, trial-averaged calcium fluorescence traces were generated for individual neurons by z-scoring each trial from −5 to 5 seconds, with 0 indicating the time of stimulation. Z-scoring involved subtracting the mean and dividing by the standard deviation of a baseline period from −5 to −3 seconds prior to pinprick stimulation. The z-scored trials were then summed and divided by the total number of trials, resulting in a single trial-averaged calcium fluorescence trace for each neuron.

To obtain a session-level analysis, trial-averaged calcium fluorescence traces from individual neurons were combined and averaged across all neurons, producing a single representative trace of neuronal activity. The peak calcium fluorescence for each neuron was identified within the post-stimulation window of 0 to 5 seconds. Each trial was z-scored as described and then binned into 1-second intervals. A 2-second moving window was applied to determine the maximum average calcium fluorescence for each trial. The peak values from all trials were then averaged to yield a singular value representing the peak post-stimulus activity of each neuron in a given session.

To evaluate the effect of running on neural activity in M2, we binarized the behavior of the mice into running/resting states and compared their mean ΔF/F values for each neuron. The running modulation index (MI) is calculated as (ΔF/F_run - ΔF/F_rest)/(ΔF/F_run + ΔF/F_rest). A running onset was detected when a period of at least 400 ms of resting was followed by at least 400 ms of running24. For the investigation of neuronal response to running onsets, we inspected the ΔF/F responses with onsets that met two criteria simultaneously: (1) the onset had to be at least 10 seconds away from previous onset, and (2) the running episode had to last at least 1 second. This operation ensured that only well-separated and sustained running episodes were analyzed, minimizing the influence of transient or ambiguous movement signals.

Chemogenetics
Clozapine N-oxide (CNO; APExBIO, China) was prepared as a suspension in 0.9% saline, achieving a final concentration of 0.2 mg/mL. The solution was administered via intraperitoneal injection at a dose of 1 mg/kg. To activate the hM4D(Gi) DREADD, imaging was conducted 30 minutes following the systemic (intraperitoneal) injection of CNO.

Behavior tracking
The raw tracking video recorded during free-moving imaging was initially analyzed using DeepLabCut (DLC)32, which provided the positional data for specific body parts of the animal across each frame. Three key body parts were selected for analysis: the head, the body center, and the tail base. The DLC model was trained on a minimum of 20 frames, following the default training protocol, and underwent 30 thousand iterations. This training resulted in a final loss of approximately 0.003, with a training error of 1.48 pixels and a test error of 3.33 pixels. The animal’s position was recorded in x-y coordinates as x(t) and y(t). To smooth the positional traces, a low-pass filter was applied to both x(t) and y(t). The instantaneous movement speed was subsequently calculated by dividing the displacement of the head between consecutive frames by the time interval (1/frame rate), yielding a speed in centimeters per second (cm/s). Two-photon imaging was synchronized with the animal tracking camera in hardware, enabling precise temporal alignment between neuronal activity and behavioral tracking data. Calcium fluorescence traces were captured with the same number of frames as the tracking signals, ensuring that time points were pre-aligned across both datasets.

Multi-day registration and cross-validation with a Gaussian-beam 2PM
We recorded neuronal activity in vivo using miniBB2p and later acquired the high-resolution 3D morphological data from the same imaging volume using the tabletop Gaussian-beam 2PM with a 0.8 NA objective (CFI Apo NIR 40×, Nikon) on the same day. This paired acquisition protocol was repeated for the same imaging volume across multiple recording days.

Cell registration across multiple recording days was performed using the ROIMatchPub MATLAB package (https://github.com/ransona/ROIMatchPub) after functional segmentation with Suite2p. The registration pipeline consisted of three main steps: (1) manual labeling of reference cells and landmarks across multi-day recordings, (2) automatic detection of potential cell matches based on a 50% overlap ratio threshold10, and (3) manual validation of matched cell candidates through morphological analysis to eliminate false positives. The registration reliability was further assessed through cross-validation between the 2D volumetric projections from miniBB2p with high-resolution 3D images from a tabletop Gaussian-beam 2PM. The 3D images were first segmented using Cellpose333, with subsequent refinement through AI-trainable segmentation in Imaris (v10.2) and manual verification based on morphological criteria. After that, the miniBB2p cell registrations generated by ROIMatchPub were systematically validated against their corresponding 3D segmented counterparts.

Statistical tests
For imaging data, paired neuronal recordings from a single session were compared using a two-tailed paired Student’s t-test, while unpaired data from separate sessions were analyzed using a two-tailed unpaired Student’s t-test. Changes in neuron populations before and after drug administration were assessed with a two-tailed Fisher’s exact test. To determine pain-responsive neurons, a one-tailed Wilcoxon rank sum test was conducted on pre- and post-stimulus values for all peripheral stimulations during pain stimulus sessions, with significance set at p < 0.025. A similar one-tailed Wilcoxon rank sum test was employed to identify the neurons that responded to running onsets by comparing calcium activity during resting and running periods. One-way repeated measures ANOVA with Tukey post hoc tests was used to assess the effects of photodamage in chronic recordings.

Data processing
Images were visualized and processed using the open-source software ImageJ. Unless stated otherwise, all images presented here were unprocessed raw images without smoothing, denoising, or deconvolution. “Green hot” lookup table in ImageJ was used for all miniBB2p captured images. Cross-section profiles, statistical graphs, and other coordinate graphs were drawn with Origin 2022, Graphpad Prism 9, and MATLAB (R2022b). All neural activities and behaviors were collected at 9 and 27 fps, respectively. The supplementary videos were made at 25 fps using Adobe Premiere Pro 2024.

Reporting summary
Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "In this paper Qian et al. present a Bessel beam two-photon miniature fluorescence microscope capable of imaging in vivo a volume of 420x420x80um at 5 fps. The novelty of the paper is in the use of Bessel beam in the design of the miniscope, which allows to increase the data throughput and frame rate compared to Gaussian beam based designs, and it is less sensitive to axial brain motion.\n\nBessel beam two-photo microscopy exist for some years now, and recovering volume information from Bessel beam scanning has been shown feasible (for example see paper doi: 10.1364/OE.27.012147). In the miniBB2p design, volume information is not recovered, this has some concerns. In essence, the authors treat the entire 80um volume as a single 2D plane, when labeling is sparse, resolving fine structures such as dendritic spines is possible, which the authors shown in Figure 2f and 2g, using brain fixed slices, and in supplemental figure 5 and 6 in vivo. One can clearly see that in vivo without recovering volume information, some fine structures are visible but other not as well. I know the authors want to show the resolution of their miniBB2p is comparable to gaussian two-photon system, but the catch here is that when labeling density is low, it seems OK, but when labeling density is high, gaussian two-photon miniscopes will outperform miniBB2p. if I would to design neuroscience experiments to perform in vivo spine or dendrite imaging, miniBB2p will likely not be my first choice.\n\nMiniaturization of microscopes, either single photon or two-photon, is to reduce the weight of the system so one can image neural circuit activity while animals perform natural behavior, instead of the widely used head-fixed design. Considering this point, I would say that the miniBB2p design has some advantages over gaussian beam two-photon miniscopes, mainly in gaining speed, but the gaussian two-photon miniscopes that is capable of volume imaging retains volume information, which the authors fail to acknowledge. I can easily envision that in neuron dense brain regions, treating the entire 80um volume as one single plane will lead to registration issues, especially over weeks or months, the 5 day registration shown in supplemental figure 7 is not very convincing already, I cannot find more information about multiple day registration in methods, the figure legends stated that overlap ratio of 50% the authors would consider as same neuron? If neurons are within the 80um volume and overlap over 50% in xy dimension, it will be treated as single neuron? This will not be an issue with gaussian two-photon miniscope volume imaging but will be a serious issue with current miniBB2p system.\n\nIt is my opinion that while miniBB2p offers some advantage in gaining speed, it’s incremental technical improvement that comes with other concerns in neuroscience applications. Therefore, I would not endorse publication of this paper in Nature Communications, it will be more suitable for a more specialized journal reporting incremental technical advancements.", "reviewer_2": "The manuscript describes the development and application of a miniature Bessel-beam two-photon microscope (miniBB2p), designed for volumetric calcium imaging in freely moving mice. The authors highlight its lightweight, simplify, and cost-effective design, enhanced imaging stability, and high-throughput capabilities, providing a thorough evaluation of its application in both locomotion and pain-response behavioral paradigms. While the manuscript describes an innovative system with potential, there are significant concerns about its advantages claimed over existing technologies. Below, I outline major and minor concerns that should be addressed before the manuscript could be considered for publication and to clarify its contributions to the field.\n\nMajor concerns\n1. L14-20. The authors claim that the miniBB2p achieves high-throughput imaging by capturing an 80-μm Z-depth at 9 Hz and resolving ~1000 neurons. However, systems like (Zong et al., 2022) mentioned in Supp. Table 1, already demonstrate similar capabilities with four-plane volumetric imaging covering 80 μm at stack rate of 10 Hz (frame rate 40 MHz for single plane), resolving ~1000 neurons. The manuscript does not convincingly establish miniBB2p’s novelty or improvements in throughput/volumetric imaging compared to these systems. A comparison of miniBB2p and previous existing miniscopes, to highlight the advantages of miniBB2p, would be helpful to see the potential of this miniscopes over existing ones.\n2. L46-47. While the authors assert that the extended depth of field of Bessel beams reduces sensitivity to axial movements, these movements are typically minimal in freely moving animals. Instead, XY movements are more prominent and are adequately managed in existing head-mounted miniscopes. If this can be an advantage over head-fixed animal tabletop experiments, I do not understand the benefit of a Bessel beam for freely moving experiment. I would suggest demonstrate/characterizing axial movement impact in freely moving mice in existing miniscopes and comment on the capability of using tunable lenses to compensate for these possible movements.\n3. L112-113 and L130-132. When cross-validating miniBB2p with a tabletop microscope, it is unclear how many neurons imaged with miniBB2p during several days were also observed in the tabletop system for the Z depth characterization. Without this information, the claim of resolving twice as many neurons (~1000 vs. 500) is not sufficiently substantiated. I suggest quantifying not only the neurons recorded in miniBB2p and benchtop system but the overlay, that would give the idea of the actual number of same recorded neurons in both systems over several recorded days.\n\nMinor concerns\n1. L49: The claim that Bessel beams are “insensitive to optical aberrations” is overstated, as the manuscript later acknowledges sensitivity to astigmatism and other aberrations.\n2. L54: Specify which behavioral paradigms were tested for clarity.\n3. Fig. 1C: The X-axis label should be corrected to “Distance from center” instead of “FOV.”\n4. L78-81, L188-195: The chosen fiber (LMA-12) is noted for its broad spectral range, but this range is not demonstrated in experiments. I would suggest, if claimed as an advantage, the use of another wavelength other than 920 nm in the miniscope. Otherwise, clarify why this fiber was chosen over alternatives like HC-920, which offers better pulse management at 920 nm for high average powers.\n5. L83-85. The manuscript mentions pulse broadening at high laser powers (up to 300 fs at 100 mW), but there is no discussion of the cause (maybe self-phase modulation?) and its impact on image quality or photobleaching. Photobleaching is mentioned only in the methods to correct the fluorescence baseline and not characterized in the main results.\n6. L87: Provide more details on the fabrication and mounting of the axicon at the fiber tip, as this is a key novelty.\n7. Fig. 2G and L102-105: A lateral fluorescence profile in Fig. 2G would help quantify the fourfold throughput increase claimed. Also, match scanning frequencies (9 Hz vs. 0.16 Hz) and average powers (80 mW vs. 25 mW) for a fair comparison between miniBB2p and the tabletop system.\n8. Fig. 3A: Add a scale bar to the behavioral arena image for reference.\n9. Fig. 3 and L300: Clarify why training and imaging experiments were conducted in different-sized boxes (40 × 40 cm2 vs. 30 × 20 × 20 cm3).\n10. L122-128 and Fig. 3. The behavioral paradigms were performed in a small box (~40 × 40 cm2). While the authors claim no behavioral impairment, the confined space and low average speeds (~3 cm/s) suggest possible effects of the system on locomotion. Published studies often use larger arenas (~80 × 80 cm2 or 100 × 26 cm2) for such evaluations, where mice exhibit higher average speeds (~5-6 cm/s). I would suggest conducting behavioral experiments in larger arenas and compare results with established benchmarks to ensure valid conclusions on locomotion and behavioral freedom.\n11. L202-204: Discuss the feasibility of upgrading the system for larger FOV experiments, given the current low NA (0.3).\n12. L216, L223. Key customizations, such as filter resizing (6 × 6 mm2) and dichroic mirror modifications are mentioned briefly but lack detail. Additionally, the GitHub repository lacks critical information such as alignment protocols, and some of the content appears to be non-English.\n13. L294-295. The manuscript briefly mentions handling and pre-training but lacks details about the duration, protocols, and confirmation of successful training.\n14. Supp. Fig. 8: The data quality is poor, with missing quantifications and statistics of enhancement responses. Consider optogenetics experiments or other controls to improve this section.\n15. Correct minor language errors such as \"weighing\" (L331).\n16. Indicate depth from brain surface of the different recordings performed.\n\nThis manuscript describes a promising technological advancement for miniature two-photon imaging. However, the claims of originality, high-throughput, and advantages over existing systems lack sufficient substantiation. The experiments performed in S1, and ACC do not demonstrate that miniBB2p offers capabilities beyond those of previous systems. To highlight the potential of this system, the authors should leverage, for example, its higher lateral resolution, as shown in Supp. Fig. 6, to resolve fine subcellular structures or perform experiments in freely moving mice that existing systems cannot achieve. With these additional comparison experiments and clarifications, the manuscript could make a valuable technological contribution to the field.", "reviewer_3": "The manuscript entitled “High-throughput two-photon volumetric brain imaging in freely moving mice” by Quin et al., submitted to Nature Communications presents a new method for imaging volumes of neural tissue that are expressing genetically encoded fluorescent indicators in freely moving mice, utilizing a novel bessel beam approach for 2P excitation. Overall, I find the approach an advance for certain types of imaging in the freely moving animal, but I would like to focus the review on the ability of the microscope to isolate activity from individual elements within the image. One of the key steps that both 2- and 3-photon imaging allowed is the assignment of detected activity to the very structures that the activity originated from, especially in densely labelled tissue. This ability relies on both optical sectioning to separate spatially near structures from each other and reasonable frame duty-cycle speeds to make sense of the resulting activity traces. The current microscope does not demonstrate this ability convincingly in the densely labelled tissue, yet. I’m also struggling to find the number of animals used and the numbers of animals in the comparisons and statistics in the imaging sections. The manuscript would benefit from many more comparisons and stronger statistical comparisons between groups.\n\n1) The argument in the introduction justifying bessel beam excitation vs optical sectioning is not compelling and should be revised, especially given that optical sectioning has been shown to enable single cell resolution, especially in the axial plane, something that, the current bessel beam approach cannot fully claim without clearer demonstrations.\n2) There are many instances that the wrong reference is cited, for example, statement on line 36 that “…..freely moving animals as brain movement is less constrained [1]….” This is not strictly true, freely moving animals have been shown to have less brain movement displacement than head-fixed, see Sawinski et al 2009 PNAS. The cited reference (Helmchen et al) never recorded from freely moving animals, please revise. The rest of the paragraph is a bit vague and the argument is somehow weak concerning optical sectioning being an issue. Optical sectioning approaches have been successfully applied to extract neuronal activity from large neuronal populations in freely moving animals, even when jumping, without loss of signals or motion artifacts.\n3) Given the ~80 – 90 micron axial resolution, how were vertically aligned neurons separated into individual neurons? How were the transients extracted from the populations of neurons without contamination? What is the measure of surety that each pixel claimed to be from a separate neuron was indeed from a separate neuron? There was some effort to address these questions in the section that starts at line 100, but there are no statistics, comparisons, or compelling demonstrations showing a clear one-to one relationship between Bessel beam imaged (x-y) pixels and 3D optical sectioning collected images from the same volume showing the same neurons. Please show a z-stack of the imaged area using a conventional microscope and then a matched image from the Bessel beam approach showing where the neurons are located within the volume.\n4) In the methods section starting at line 310, there were three traces extracted for each identified ROI. Please show examples in the main figures how the traces were extracted from the raw data to end up with activity from each soma. As it is written in the methods, it is a bit mysterious and given the axial resolution is extremely large, showing convincingly how each soma was isolated and how the activity was extracted and separated from other contaminating structures would be important.\n5) I’m not sure what the point of the noxious stimulation is. It is claimed to be freely moving but in the methods the paw was pricked with a needle, presumably by holding the paw, which is not very freely moving.\n6) I’m not sure that Supplementary figure 7 makes a very compelling case for stable recording over multiple days, the image quality in a, seems to be degrading over the 5 days. Can the authors provide a cell health quantification to compare between imaging days? Many studies have done this."}, "author_response": "Nature Communications Manuscript [NCOMMS-24-73654]\n\" High-throughput two-photon volumetric brain imaging in freely moving mice\"\nAuthors' response to Reviewer's comments\nWe would like to express our gratitude for the Reviewers’ valuable comments and suggestions on\nour manuscript. To address their concerns, we have incorporated additional cross-validating\nexperiments, expanded our data analysis, and revised the manuscript accordingly. Major\nimprovements include:\n We extended the long-term stability test from days to weeks and validated the neuron\nregistrations from the miniBB2p with a tabletop Gaussian-beam 2PM.\n We added new behavioral tests, analyzed the photobleaching and photodamage\neffects during long-term imaging, and included a comprehensive assembly guide for\nthe miniBB2p system.\n We improved the in vivo dendritic spine imaging to further justify the miniBB2p's\nresolution performance.\nWe revised our manuscript extensively and included the new results. Please see our detailed replies\nto the Reviewers' comments below.\nReviewer #1 (Remarks to the Author):\n1. “In this paper Qian et al. present a Bessel beam two-photon miniature fluorescence microscope\ncapable of imaging in vivo a volume of 420x420x80um at 5 fps. The novelty of the paper is in the\nuse of Bessel beam in the design of the miniscope, which allows to increase the data throughput\nand frame rate compared to Gaussian beam based designs, and it is less sensitive to axial brain\nmotion.”\nReply: We thank the Reviewer’s comments on the miniBB2p. We have improved the manuscript\naccording to the comments and suggestions. Please see below for the detailed responses.\n2. “Bessel beam two-photo microscopy exist for some years now, and recovering volume\ninformation from Bessel beam scanning has been shown feasible (for example see paper doi:\n10.1364/OE.27.012147). In the miniBB2p design, volume information is not recovered, this has\nsome concerns. In essence, the authors treat the entire 80um volume as a single 2D plane, when\nlabeling is sparse, resolving fine structures such as dendritic spines is possible, which the authors\nshown in Figure 2f and 2g, using brain fixed slices, and in supplemental figure 5 and 6 in vivo. One\n1\ncan clearly see that in vivo without recovering volume information, some fine structures are visible\nbut other not as well. I know the authors want to show the resolution of their miniBB2p is comparable\nto gaussian two-photon system, but the catch here is that when labeling density is low, it seems OK,\nbut when labeling density is high, gaussian two-photon miniscopes will outperform miniBB2p. if I\nwould to design neuroscience experiments to perform in vivo spine or dendrite imaging, miniBB2p\nwill likely not be my first choice.”\nReply: We agree with the Reviewer’s comment that miniBB2p captures a 2D projected view of a\nvolumetric structure, which inherently compromises axial information. Nevertheless, in brain imaging\nin vivo, the positions of neurons and their fine structures (e.g., dendrites and spines) most likely\nremain stable during imaging, eliminating the need for continuous 3D imaging. Additionally, if\nneeded, we can always acquire high-resolution 3D reference images of the volumetric structure\nusing a standard Gaussian-beam 2PM. This approach has been adopted in tabletop Bessel-beam\n2PM systems for calcium imaging in vivo for both sparsely and densely labelled samples, as\nextensively demonstrated by Na Ji’s group in UC Berkeley under various applications paradigms [1-\n3]. Accordingly, we believe that the features of Bessel beam presented in the tabletop 2PMs could\nalso be applied to miniBB2p.\nWe also agree with the Reviewer that dense labeling could complicate imaging in Bessel-beam\n2PMs. However, if neural activity is sparse, temporally unmixing the signals of spatially overlapping\nneurons remains feasible1. Furthermore, our analysis of imaging sparsity in the state-of-the-art\nminiature multiphoton microscopes indicates that neurons recorded typically occupy just a fraction\nof the field of view (see the Table below). When acquiring 2D projections using Bessel beams in\nthese applications, this sparsity would substantially reduce the occurrence of complete axial overlap\nbetween neurons.\nImaging sparsity in the state-of-the-art miniature multiphoton microscopes\nKlioutchnikov, A. Klioutchnikov, Zhao, C. et al. Zhao, C. et al. Madruga, B.A.\nZong, W. et al. This\nReference et al. Nat A. et al. Nat Nat Methods Opt Express et al.\nCell (2022) work\nMethods (2020) Methods (2023) (2023) (2023) bioRxiv (2024)\nMax filling\n~18.3% ~27.5% ~26.0% ~8.9% ~59.3% ~11.5% ~96.5%\nfactor*\n* Filling factor = (the number of neurons imaged × area per neuron) ÷ field of view; the neuron diameter is assumed to be 15 μm.\nTo further highlight the potentials of miniBB2p in dendritic spine imaging, we have updated the\nin vivo imaging results in the revised manuscript (see Supplementary Figs. 5-6 and\nSupplementary Video 3). These results demonstrate the advantage of miniBB2p in imaging\ndendrites and spines as demonstrated in the tabletop Bessel-beam 2PMs [1-3].\n1“For studies of densely labeled brains where single neuron resolution is required, Bessel scanning may also be applied,\nif the activity pattern is sparse and spatially overlapping calcium responses can be unmixed temporally.” by R. Lu et al. [1]\nis quoted here.\nbrain. a, Image of a ~80-μm thick volume in ACC by miniBB2p. b, Lateral projection of an image stack at 3-\nμm step collected by a tabletop Gaussian-beam 2PM from the same volume, with structures colored by depth\n(left); cross section view across the dashed line (right). c-d, Zoom-in imaging of the boxed areas in a-b. e,\nOptical section at the middle-depth in d. Data are from a single representative experiment (n=3 animals, one\nexperiment per animal).\nSupplementary Fig. 6 | Imaging of the activities of dendrites and spines in ACC of awake mouse\nexpressing GCaMP8s. a, FOV, 420 × 420 µm2. b, FOV, 60 × 60 µm2. Data in a-b are from a separate\nrepresentative experiment (n=6 animals, one experiment per animal).\n3\n3. “Miniaturization of microscopes, either single photon or two-photon, is to reduce the weight of the\nsystem so one can image neural circuit activity while animals perform natural behavior, instead of\nthe widely used head-fixed design. Considering this point, I would say that the miniBB2p design has\nsome advantages over gaussian beam two-photon miniscopes, mainly in gaining speed, but the\ngaussian two-photon miniscopes that is capable of volume imaging retains volume information,\nwhich the authors fail to acknowledge. I can easily envision that in neuron dense brain regions,\ntreating the entire 80um volume as one single plane will lead to registration issues, especially over\nweeks or months, the 5 day registration shown in supplemental figure 7 is not very convincing\nalready,”\nReply: We thank the Reviewer for bringing this matter out. In the INTRODUCTION, we added the\nfollowing sentences to describe the constraints of miniBB2p compared with Gaussian-beam 2PMs:\n“…Gaussian-beam 2PM records a stack of 2D optical sections across the depth to achieve 3D\nimaging, it favors resolving the fine structures in the axial dimension at a compromised imaging\nspeed. In contrast, Bessel-beam 2PM…”\n“It is an effective tool for volumetric calcium imaging in vivo, as the position of neurons and their fine\nstructures remain stable during imaging [17]. In addition, if needed, the axial coordinates of\nstructures in the 2D projections can be retrieved with a full 3D reference image from a Gaussian-\nbeam 2PM.”\nWe agree with the Reviewer that in neuron-dense brain regions, miniBB2p encounters greater\nchallenges in neuronal registration compared to miniature Gaussian-beam 2PMs. In response to\nthe Reviewer’s comments, we have updated our registration results in densely labelled samples by\nadding one-to-one registrations between single 2D projections from miniBB2p and high-resolution\n3D image references from a tabletop Gaussian-beam 2PM (Supplementary Figs. 7-8 in the revised\nmanuscript). These new results validated the performance of miniBB2p in resolving neurons in these\nsamples (refer to our response to Reviewer #2’s major comment #3 and Reviewer #3’s\ncomments # 3-4).\n4. “I cannot find more information about multiple day registration in methods, the figure legends\nstated that overlap ratio of 50% the authors would consider as same neuron? If neurons are\nwithin the 80um volume and overlap over 50% in xy dimension, it will be treated as single neuron?\nThis will not be an issue with gaussian two-photon miniscope volume imaging but will be a serious\nissue with current miniBB2p system.”\nReply: We thank the Reviewer for pointing this out. In our original manuscript, cell registration was\nperformed using the ROIMatchPub MATLAB package [4] and Suite2p functional segmentation\npipeline [5]. Adopting an approach analogous to Zong et al. [6], we implemented a cross-day cell\nregistration pipeline with three key steps:\nStep 1: Neuronal activity results from Suite2p were loaded into ROIMatchPub; multiple\nmatching cells or other landmarks in multi-day recordings were then manually labeled as references.\nthreshold (50% in our analysis, following Zong et al. [6]). This threshold classified cells recorded on\ndifferent days as matched candidates if their spatial footprints overlapped by more than 50%.\nStep 3: The morphological structure of matched cell candidates was manually validated to filter\nout false positives (see the figure below).\nValidating matched cell candidates with ROIMatchPub based on its morphological structure\nThe revised manuscript now includes an additional validation step in which ROIMatchPub's cell\nregistrations are cross-validated against ground-truth cell identities derived from high-resolution 3D\nimages acquired with a tabletop Gaussian-beam 2PM. In the METHODS, we added the following\nsection to describe the multi-day registration and cross-validation protocols.\n“Multi-day registration and cross-validation with a Gaussian-beam 2PM. We first recorded\nneuronal activity in vivo using miniBB2p and later acquired the high-resolution 3D morphological\ndata from the same imaging volume using a tabletop Gaussian-beam 2PM (objective: CFI Apo NIR\n40×, NA 0.8, Nikon) on the same day. This paired acquisition protocol was repeated for the same\nimaging volume across multiple recording days.\nCell registration across multiple recording days was performed using the ROIMatchPub\nMATLAB package (https://github.com/ransona/ROIMatchPub) after functional segmentation with\nSuite2p. The registration pipeline consisted of three main steps: (1) manual labeling of reference\ncells and landmarks across multi-day recordings, (2) automatic detection of potential cell matches\nbased on a 50% overlap ratio threshold [10], and (3) manual validation of matched cell candidates\nthrough morphological analysis to eliminate false positives. The registration reliability was further\nassessed through cross-validation between the 2D volumetric projections from miniBB2p with high-\nresolution 3D images from a tabletop Gaussian-beam 2PM. The 3D images were first segmented\nusing Cellpose3 [31], with subsequent refinement through AI-trainable segmentation in Imaris (v10.2)\nand manual verification based on morphological criteria. After that, the miniBB2p cell registrations\ngenerated by ROIMatchPub were systematically validated against their corresponding 3D\nsegmented counterparts.”\n5. “It is my opinion that while miniBB2p offers some advantage in gaining speed, it’s incremental\ntechnical improvement that comes with other concerns in neuroscience applications. Therefore, I\n5\nwould not endorse publication of this paper in Nature Communications, it will be more suitable for a\nmore specialized journal reporting incremental technical advancements.”\nReply: The volumetric (or extended depth-of-field) imaging capabilities of Bessel beams have been\nwell-documented in various tabletop two-photon imaging platforms for neuroscience applications.\nThe miniBB2p represents the first implementation of Bessel beams in miniature two-photon imaging\nplatforms. Furthermore, this work represents the first attempt to leveraging the properties of Bessel\nbeam for microscope design, resulting in a much simpler lens architecture than existing approaches.\nBeyond achieving high-throughput synaptic-resolution volumetric imaging, we expect the system's\nsimplicity and cost-effectiveness will lower the barriers to broader applications of head-mounted\nmultiphoton microscopy for studying neural dynamics in freely moving animals. We believe these\nadvances represent an important contribution worthy of publication in Nature Communications.\nReviewer #2 (Remarks to the Author):\n“The manuscript describes the development and application of a miniature Bessel-beam two-photon\nmicroscope (miniBB2p), designed for volumetric calcium imaging in freely moving mice. The authors\nhighlight its lightweight, simplify, and cost-effective design, enhanced imaging stability, and high-\nthroughput capabilities, providing a thorough evaluation of its application in both locomotion and\npain-response behavioral paradigms. While the manuscript describes an innovative system with\npotential, there are significant concerns about its advantages claimed over existing technologies.\nBelow, I outline major and minor concerns that should be addressed before the manuscript could\nbe considered for publication and to clarify its contributions to the field.”\nReply: We thank the Reviewer’s generous comments on the miniBB2p. We have improved the\nmanuscript according to the comments and suggestions. Please see below for the detailed\nresponses.\nMajor concerns：\n“1. L14-20. The authors claim that the miniBB2p achieves high-throughput imaging by capturing an\n80-μm Z-depth at 9 Hz and resolving ~1000 neurons. However, systems like (Zong et al., 2022)\nmentioned in Supp. Table 1, already demonstrate similar capabilities with four-plane volumetric\nimaging covering 80 μm at stack rate of 10 Hz (frame rate 40 MHz for single plane), resolving ~1000\nneurons. The manuscript does not convincingly establish miniBB2p’s novelty or improvements in\nthroughput/volumetric imaging compared to these systems. A comparison of miniBB2p and previous\nexisting miniscopes, to highlight the advantages of miniBB2p, would be helpful to see the potential\nof this miniscopes over existing ones.”\nMEMS scanners for imaging, its throughput in terms of pixel rate is mainly limited by the scanning\nbandwidth. Consequently, all miniature 2PMs using comparable MEMS scanners achieve similar\nthroughput. The miniBB2p has an imaging throughput of 512 × 512 pixels at 9 Hz, comparable to\nthe MINI2P system developed by Zong et al. [6] (512 × 512 pixels at 10 Hz). While MINI2P uses a\nμTlens to image four planes near the same time at 10 Hz (resolving ~1000 neurons), this comes at\nthe cost of halved x-y resolution (256 × 256 pixels). In contrast, miniBB2p images an 80 μm thick\nvolume simultaneously without depth scanning, resolving ~1000 neurons at 512 × 512 pixels (9 Hz)\nwithin similar FOVs. By maintaining full pixel resolution, miniBB2p provides nearly fourfold greater\neffective imaging throughput.\nTo comply with the Reviewer’s suggestion, in the revised manuscript, we have listed the pixel\nrate of various miniature 2PMs in the Supplementary Table 1 and in the DISCUSSION, we added:\n“Similar to existing MEMS-based miniature Gaussian-beam 2PMs, miniBB2p achieves an imaging\nthroughput (effective pixel rate) of 2.4 megapixels per second, mainly constrained by the bandwidth\nof the MEMS scanners. However, miniBB2p delivers a 4–8× improvement in information throughput,\nenabled by its extended depth of field.”\n“2. L46-47. While the authors assert that the extended depth of field of Bessel beams reduces\nsensitivity to axial movements, these movements are typically minimal in freely moving animals.\nInstead, XY movements are more prominent and are adequately managed in existing head-mounted\nminiscopes. If this can be an advantage over head-fixed animal tabletop experiments, I do not\nunderstand the benefit of a Bessel beam for freely moving experiment. I would suggest\ndemonstrate/characterizing axial movement impact in freely moving mice in existing miniscopes and\ncomment on the capability of using tunable lenses to compensate for these possible movements.”\nReply: We thank the Reviewer for the valuable insights regarding the brain tissue motion artifacts\nin imaging freely moving animals. While state-of-the-art miniature microscopes have made\nsignificant progress in managing axial movements, it remains a persistent challenge in imaging\nfreely moving animals. Unlike lateral displacements that can be corrected computationally, axial\ndisplacements in 2D imaging present unique difficulties for post-processing. This is because\nfluorescence intensity variations caused by axial movements are indistinguishable from calcium-\ndependent signal fluctuations in the neural activity recordings [1].\nAxial motion artifacts in freely moving animals were systematically quantified by Zhao et al. [7]\n(Extended Data Fig. 8e-f in their paper), showing considerably greater axial displacement in freely\nbehaving conditions compared to head-fixed preparations. Their measurements revealed axial\ndisplacement ranges of ~ [-4, +8] μm in PPC L5 and ~ [-6, +10] μm in hippocampal CA1 in freely\nbehaving mice. In addition, Sawinski et al. [8] have also encountered axial motion artifacts in freely\nmoving animals (Fig. S3 in their paper), necessitating exclusion of affected imaging data.\nthe impact of axial movements on calcium imaging with versus without extended depth of field. Our\nresults show that extended depth of field significantly improves fluorescence signal stability against\naxial displacement (see the Figure below). For example, at a 10 μm axial displacement, 2P imaging\nwith an 80 μm depth of field resulted in only an 8.2% signal decrease, while 2P imaging with a 20\nμm depth of field produced a 65.7% decrease. These findings indicate that the extended depth of\nfield in miniBB2p substantially suppresses the axial motion artifacts compared to Gaussian-beam\nminiature 2PMs, particularly during periods of larger axial displacements.\nSimulation of axial motion artifacts. a, Axial cross sections of the Gaussian and Bessel PSFs, with the\nneuron of a diameter of 15 μm located in the center. PSFs in the x-axis were not drawn to scale. b-c:\nFluorescence changes due the axial displacement in one-photon (b) and two-photon (c) microscopes. Note\nthat one-photon imaging is more resistant to motion artifacts.\nWhile axial movement compensation using electrotuneable lens [9] or acousto-optic lens [10]\nhas been successfully implemented in closed-loop tabletop microscopes for head-fixed preparations,\nimplementing real-time z-axis correction in miniscopes presents greater challenges. These\nlimitations stem from both the constrained physical dimensions of miniscope systems and the\nunpredictable motion patterns characteristic of freely behaving animals. As an alternative approach,\nmulti-plane imaging using high-speed tunable lenses enables simultaneous neuronal activity\nrecording across different depths, facilitating post hoc estimation and correction of axial motion\nartifacts [11,12].\n“3. L112-113 and L130-132. When cross-validating miniBB2p with a tabletop microscope, it is\nunclear how many neurons imaged with miniBB2p during several days were also observed in the\ntabletop system for the Z depth characterization. Without this information, the claim of resolving\ntwice as many neurons (~1000 vs. 500) is not sufficiently substantiated. I suggest quantifying not\nonly the neurons recorded in miniBB2p and benchtop system but the overlay, that would give the\nidea of the actual number of same recorded neurons in both systems over several recorded days.”\nReply: We thank the Reviewer for this comment. To comply with the Reviewer’s suggestion, we\nhave updated the multi-day registrations and added cross-validations between 2D projections from\nminiBB2p and high-resolution 3D images from a tabletop Gaussian-beam 2PM (Supplementary\nFig. 7) (also refer to our response to Reviewer #3’s comment #3). These validations further\nhighlight the performance of miniBB2p in somatic calcium imaging at high throughput.\nSupplementary Fig. 7 | Stability of miniBB2p imaging. a, Recording the same volume in ACC across\nmultiple days. b, Cell registration across sessions: Day 1 cells (green), Day 8 or Day15 cells (pink),\noverlapping regions (white). Total cell counts: Day 1 (572), Day 8 (628), Day 15 (670). 65% of Day 1 cells\nremained detectable after 14 days (372 matched to Day 8; 370 to Day 15), with 53% (301 cells) persisting\nacross all three sessions. c, Spatial distribution of the 301 cells persisting across all three sessions,\nreconstructed from a tabletop Gaussian-beam 2PM 3D imaging data (Methods). d, 20 example cells identified\nacross all recordings, showing similar cell morphology. Data are from a single representative experiment (n=2\nanimals, one experiment per animal).\nMinor concerns:\n“1. L49: The claim that Bessel beams are “insensitive to optical aberrations” is overstated, as the\nmanuscript later acknowledges sensitivity to astigmatism and other aberrations.”\n“…in comparison to Gaussian-beam 2PM, Bessel-beam 2PM achieves better lateral resolution at\nsame excitation NA [17-18] and is mainly sensitive to astigmatism among all primary optical\naberrations…”\n“2. L54: Specify which behavioral paradigms were tested for clarity.”\nReply: We have revised the sentence in the INTRODUCTION:\n“…and demonstrated high-throughput volumetric calcium imaging in secondary motor cortex (M2)\nand in anterior cingulate cortex (ACC) in freely moving mice.”\n“3. Fig. 1C: The X-axis label should be corrected to ‘Distance from center’ instead of ‘FOV’.”\nReply: We have corrected it.\n“4. L78-81, L188-195: The chosen fiber (LMA-12) is noted for its broad spectral range, but this range\nis not demonstrated in experiments. I would suggest, if claimed as an advantage, the use of another\nwavelength other than 920 nm in the miniscope. Otherwise, clarify why this fiber was chosen over\nalternatives like HC-920, which offers better pulse management at 920 nm for high average powers.”\nReply: The LAM-12 fiber is an endlessly single-mode photonic crystal fiber suitable for single mode\nlaser delivery within the transparency window of silica [13]. However, since the laser source in\nminiBB2p (FemtoFiber ultra 920, Toptica) operates exclusively at 920 nm, we are constrained to\nthis specific wavelength for imaging. In response to the Reviewer's comment, in the System design\nand performance testing of miniBB2p section in RESULT, we have revised the fiber description and\nadded a supporting reference.\n“This endlessly single-mode photonic crystal fiber supports single-mode delivery over a broad\nspectral range from 700 to 1700 nm [22].”\n“5. L83-85. The manuscript mentions pulse broadening at high laser powers (up to 300 fs at 100\nmW), but there is no discussion of the cause (maybe self-phase modulation?) and its impact on\nimage quality or photobleaching. Photobleaching is mentioned only in the methods to correct the\nfluorescence baseline and not characterized in the main results.”\nReply: Self-phase modulation represents the predominate mechanism of pulse broadening in large-\nmode-area photonic crystal fibers (Flusberg et al. [14]). This nonlinear effect is difficult to\ncompensate for, as observed in the LMA-12 photonic crystal fiber. In the System design and\nperformance testing of miniBB2p section in RESULT, we added a reference (Flusberg et al. [14])\nfor the nonlinear effect in the fiber.\n“The pulse in the fiber was broadened by material dispersion and nonlinear effects [23].”\n(40–100 mW) comparable to that used in tabletop Bessel-beam 2PMs for all imaging experiments.\nThis indicates better pulse management could further enhance the sensitivity through improved\nfluorescence excitation efficiency from shorter laser pulses. For somatic calcium imaging, miniBB2p\ntypically operated at 40 mw laser power, comparable to state-of-the-art miniature Gaussian-beam\n2PMs. Additionally, the axially elongated focus further reduces the power density on the sample,\nwhich would make miniBB2p resistant to photobleaching. In response to the Reviewer’s comment,\nwe analyzed the photobleaching effect during 30-min continuous recordings and the results\nsuggested a minimal photobleaching in miniBB2p (Supplementary Fig. 9 in the revised manuscript).\nSupplementary Fig. 9 | Minimal photobleaching and photodamage in miniBB2p. a-c, Neuronal soma\nfluorescence baselines (20th percentile intensity values) during the first and last 10% of the 30-minute\nrecording period (raw data in Supplementary Fig. 7). d, Average peak ΔF/F of calcium transients measured\nin the same neuronal populations (Day 1, 0.89 ± 0.35; Day 8, 0.90 ± 0.35; Day 15, 0.90 ± 0.32; mean ± s.d.).\nNo significant differences were observed in the three recordings over two weeks (One-way repeated\nmeasures ANOVA with Tukey post hoc tests, Day 1 versus Day 8: p = 0.747, Day 8 versus Day 15: p = 0.998,\nDay 1 versus Day 15: p = 0.781).\n“6. L87: Provide more details on the fabrication and mounting of the axicon at the fiber tip, as this is\na key novelty.”\nReply: We have included a detailed protocol covering micro-axicon evaluation and fiber integration\ninto miniBB2p in Supplementary Data (https://github.com/WuLab-CIBR/miniBB2p). Regarding the\nmicro-axicon fabrication at fiber tip, it was likely fabricated using a protocol similar to that described\nby Grosjean et al. [15]. We cannot get the technical details from the manufacturer.\n11\n“7. Fig. 2G and L102-105: A lateral fluorescence profile in Fig. 2G would help quantify the fourfold\nthroughput increase claimed. Also, match scanning frequencies (9 Hz vs. 0.16 Hz) and average\npowers (80 mW vs. 25 mW) for a fair comparison between miniBB2p and the tabletop system.”\nReply: Thank the Reviewer for this comment. Fig. 2g mainly compares the depth of field and\nresolving power between the miniBB2p and conventional tabletop Gaussian-beam 2PM. Other\nperformance parameters, such as imaging speed and signal-to-noise ratio, fall outside the scope of\nthis comparative analysis. We have revised the sentence to describe the fourfold throughput\nincrease to make the claim more accurate.\n“In comparison, miniBB2p captured the same information in one image, with a fourfold increase in\ndepth of field.”\n“8. Fig. 3A: Add a scale bar to the behavioral arena image for reference.”\nReply: We have added a scale bar in the revised manuscript.\n“9. Fig. 3 and L300: Clarify why training and imaging experiments were conducted in different-sized\nboxes (40 × 40 cm2 vs. 30 × 20 × 20 cm3).”\nReply: We appreciate the Reviewer’s attention to this detail. The 40 × 40 cm² open-field box was\nselected to evaluate the impact of the miniBB2p device on animal movement in a standard open-\nfield test. This arena features a solid, enclosed floor, which is optimal for general locomotion analysis.\nIn contrast, the 30 × 20 × 20 cm³ mesh-floor box was used for pain-related behavioral assays, as\nthe mesh design allows precise mechanical stimulation of the hind paw from below. While the use\nof different box sizes for training and imaging was not empirically motivated, we note that this\napproach aligns with established methodologies in similar behavioral studies. For reference, the\ntable below summarizes box sizes employed in locomotion and behavioral assessments across\ndifferent works.\nTable: Box sizes used for locomotion and behavior assessments in different studies\nReference Type Locomotion test (cm) Free-moving test (cm)\nZong et al. 80 × 80/\n2PM 80 × 80\nCell, 2022 [6] 55 × 55\nZong et al. Social behavior: 56 × 24\n2PM 30 × 20\nNat Methods, 2021 [16] Electric footshock: ~20 × 20\nZong et al.\n2PM 29 × 17 30 × 30\nNat Methods, 2017 [17]\nKlioutchnikov et al.\n3PM 96 × 9.7 96 × 9.7\nNat Methods, 2023 [18]\nZhang et al.\n1PM 40 × 40 20 × 20\nNat Biomed Eng, 2024 [19]\n97.6 x 45\nOur work 2PM 30 × 20\nin the revised manuscript\n12\n10. L122-128 and Fig. 3. The behavioral paradigms were performed in a small box (~40 × 40 cm2).\nWhile the authors claim no behavioral impairment, the confined space and low average speeds (~3\ncm/s) suggest possible effects of the system on locomotion. Published studies often use larger\narenas (~80 × 80 cm2 or 100 × 26 cm2) for such evaluations, where mice exhibit higher average\nspeeds (~5-6 cm/s). I would suggest conducting behavioral experiments in larger arenas and\ncompare results with established benchmarks to ensure valid conclusions on locomotion and\nbehavioral freedom.”\nReply: We thank the Reviewer for the valuable comment. In response, we have conducted\nadditional behavioral experiments in an expanded arena (97.6 × 45 cm²) to better evaluate the\neffects of carrying miniBB2p on animals’ locomotion and behavioral freedom. As shown in the\nupdated Fig. 3, these new experimental results consistently reproduce our original findings.\nFig. 3 | Minimal impact of miniBB2p on animal movement. a, Representative trajectories of mice\nrunning in a 97.6 cm × 45 cm behavioral arena in a 30-min trail; with dummy, mice carrying the 2.6 g\ndummy microscope, fiber, and cables; control, mice carrying nothing; running speed is color coded; red\ndashed box indicates the central area. b-c, Average speed (b) and median speed (c) in each condition\n(30 min each); p = 0.4156 and 0.7429, paired t test. d, Number of entries into the central area. p =\n0.8543, paired t test. e, Mean accumulated distance over the 30-min test, shaded areas show s.e.m. f,\nCumulative speed distribution over the 30-min test among all trails. g, Total distance traveled (left),\ndistance traveled in the central and corner area (right) in each condition (30 min each); p = 0.4141,\n0.6408 and 0.3394, paired t test. NS, no significant; data in b-d and g are presented as mean ± s.e.m.\nData represent measurements collected from 12 individual animals.\n13\n“11. L202-204: Discuss the feasibility of upgrading the system for larger FOV experiments, given\nthe current low NA (0.3).”\nReply: The field of view of current miniBB2p is primarily limited by the scan product (beam size at\nscanner × maximum optical scan angle) of the MEMS scanner. We anticipate that using a MEMS\nscanner with a higher scan product—i.e., a larger mirror size and scan angle—combined with a high\nspace-bandwidth-product optical design would expand the field of view. Furthermore, compared to\nminiature Gaussian-beam 2PMs, miniBB2p achieves higher lateral resolution at same NA. At same\nlateral resolution, this implies that miniBB2p could achieve a larger field of view than miniature\nGaussian-beam 2PMs using same MEMS scanners. However, as field of view increases, improved\nfluorescence excitation and detection efficiency become essential to compensate for the signal\nreduction caused by shorter pixel dwell times. In the DISCUSSION, we added:\n“Further increases in imaging throughput and FOV would require MEMS scanners with a larger\nmirror size and wider optical scan angle without compromising the scanning speed. Note that, as\nthe imaging throughput and FOV increases, higher fluorescence excitation and detection efficiency\nbecome essential to compensate for the signal loss resulting from reduced pixel dwell times.”\n“12. L216, L223. Key customizations, such as filter resizing (6 × 6 mm2) and dichroic mirror\nmodifications are mentioned briefly but lack detail. Additionally, the GitHub repository lacks critical\ninformation such as alignment protocols, and some of the content appears to be non-English.”\nReply: Filter resizing and dichroic mirror modification were performed by the supplier. We have\nadded the information of the supplier in the revised manuscript. In addition, we have added more\ndetails about alignment protocols in Supplementary Data (https://github.com/WuLab-\nCIBR/miniBB2p) and have corrected non-English content.\n“13. L294-295. The manuscript briefly mentions handling and pre-training but lacks details about the\nduration, protocols, and confirmation of successful training.”\nReply: We thank the Reviewer for pointing this out. We have added a section in MEHTODS to\ndescribe the mice handling and pre-training procedures.\n“Mice handling and pretraining. Mice were habituated to the experimental environment for 3 days\nprior to locomotion test or free-moving imaging. During the same period, they also underwent daily\nhandling sessions to acclimate to head-mounted procedures. Handling included gentle headcap\npressing, back stroking, and holding the headcap firmly for approximately 10 seconds. Each session\nlasted 5–10 minutes and was designed to reduce stress and facilitate later dummy or real miniBB2p\nmounting in the awake state. All handling and behavioral procedures were conducted under\nsimulated night time conditions. For locomotion test, awake mice were fitted with a dummy miniBB2p\n(or not, for controls) and allowed to habituate to the experimental environment for 30 minutes. They\nwere then gently transferred to the open field arena for a 5-minute exploratory adaptation, followed\nby a 30-minute free-movement recording session (EthoVision XT 16, 10 Hz sampling). For free-\n14\nmoving imaging, the real miniBB2p was mounted while the mice were awake, followed by a\nhabituation period in the imaging chamber placed over a mesh table. Once the animal exhibited\nstable and naturalistic movements, imaging recordings were initiated.”\n“14. Supp. Fig. 8: The data quality is poor, with missing quantifications and statistics of enhancement\nresponses. Consider optogenetics experiments or other controls to improve this section.”\nReply: We appreciate the Reviewer’s comment regarding the data quality and need for more\nquantitative analysis. Previous electrophysiological study [20] has showed that activation of S1\ninputs selectively increased the firing rates of ACC neurons in response to noxious stimuli. However,\ndue to the limitations of electrophysiology, it is challenge to distinguish between pyramidal and\nGABAergic neurons. While it is well established that pyramidal neurons in the ACC exhibit increased\nsynaptic plasticity under persistent or chronic pain conditions, it remains unclear whether GABAergic\nneurons in the ACC also contribute to the processing of S1 input.\nSupplementary Fig. 10 | Inhibition of S1 inputs enhances nociceptive responses in ACC a, Schematic\nof the experiment. b, Imaging of ACC using miniBB2p (left), example ΔF/F traces of color-outlined neurons\nbefore (middle) and after (right) CNO injection; dashed lines indicate pin prick timings. c, Mean calcium\nresponses (± s.d.) of eight neurons color-outlined in b during pin prick. Traces with unstable baselines before\npin prick (grey dashed lines in b) were excluded. Data are from a single representative experiment (n=3\nanimals, one experiment per animal).\nIn the current study, we used miniBB2p to investigate this question. Although GABAergic\nneurons often display synchronous, seemingly homogeneous activity, which may give the\nimpression of poor data quality [21], we performed further analyses to explore this in more detail.\nNotably, after inhibiting S1 pyramidal neurons, we observed a considerable increase in calcium\n15\nactivity in the same GABAergic neurons in the ACC compared to their baseline levels\n(Supplementary Fig. 10c in the revised manuscript). This suggests a functional relationship\nbetween S1 inputs and ACC GABAergic neurons.\nWe agree with the Reviewer that incorporating optogenetic manipulations would strengthen this\nsection. However, due to the size of our current imaging system, implanting an additional optical\nfiber for optogenetic stimulation presents technical challenges and would require further\ninstrumental development, which is beyond the scope of this study.\n“15. Correct minor language errors such as \"weighing\" (L331).”\nReply: We have corrected it.\n“16. Indicate depth from brain surface of the different recordings performed.”\nReply: We have updated our depth annotation in the figures and provided the depth information of\nall experiments in the Supplementary Table 2.\n“This manuscript describes a promising technological advancement for miniature two-photon\nimaging. However, the claims of originality, high-throughput, and advantages over existing systems\nlack sufficient substantiation. The experiments performed in S1, and ACC do not demonstrate that\nminiBB2p offers capabilities beyond those of previous systems. To highlight the potential of this\nsystem, the authors should leverage, for example, its higher lateral resolution, as shown in Supp.\nFig. 6, to resolve fine subcellular structures or perform experiments in freely moving mice that\nexisting systems cannot achieve. With these additional comparison experiments and clarifications,\nthe manuscript could make a valuable technological contribution to the field.”\nReply: We thank the Reviewer for the encouraging comments on miniBB2p. The aim of this work\nis to introduce the Bessel beam into the miniature 2PM field and demonstrate its advantages in high-\nthroughput volumetric imaging that has been extensively demonstrated in tabletop Bessel-beam\n2PMs. This can be supported by the results from imaging M2 and ACC. Furthermore, this work\nhighlights the utility of Bessel beam properties for designing simplified optical systems capable of\nachieving diffraction-limited performance (Supplementary Table 2).\nTo comply with the Reviewer’s suggestion on imaging the activities of fine structures, we have\nupdated dendrites and spines imaging data on head-fixed mice (Supplementary Fig. 6b). However,\ndue to the small field of views (60 × 60 μm2) resulted from the increasingly sampling rate necessary\nto use the full resolving power of the optics, the high power required to visualize the small structures,\nthe current miniBB2p is not optimized for high-throughput imaging of the fine subcellular structures\n(e.g. spines) in freely moving animals. Future works on increasing NA of the excitation optics and\npulse management for higher resolution and sensitivity would be essential for high-throughput in\nvivo imaging at synaptic resolution that challenges existing technologies.\n“The manuscript entitled “High-throughput two-photon volumetric brain imaging in freely moving\nmice” by Quin et al., submitted to Nature Communications presents a new method for imaging\nvolumes of neural tissue that are expressing genetically encoded fluorescent indicators in freely\nmoving mice, utilizing a novel bessel beam approach for 2P excitation.”\nReply: We thank the Reviewer’s comments. We have improved the manuscript according to the\ncomments and suggestions. Please see below for the detailed responses.\n“Overall, I find the approach an advance for certain types of imaging in the freely moving animal,\nbut I would like to focus the review on the ability of the microscope to isolate activity from individual\nelements within the image. One of the key steps that both 2- and 3-photon imaging allowed is the\nassignment of detected activity to the very structures that the activity originated from, especially in\ndensely labelled tissue. This ability relies on both optical sectioning to separate spatially near\nstructures from each other and reasonable frame duty-cycle speeds to make sense of the resulting\nactivity traces. The current microscope does not demonstrate this ability convincingly in the\ndensely labelled tissue, yet. I’m also struggling to find the number of animals used and the numbers\nof animals in the comparisons and statistics in the imaging sections. The manuscript would benefit\nfrom many more comparisons and stronger statistical comparisons between groups.”\nReply: We thank the Reviewer’s encouraging comments. As noted by Reviewer #1, Bessel-beam\n2PM has been established for some years. Its advantages and limitations have been extensively\ncharacterized in prior research, particularly in foundational work by Na Ji's group at UC Berkeley.\nTheir systematic evaluations across conventional tabletop 2PM platforms have demonstrated\nconsistent performance in both sparsely and densely labeled specimens [1-3].\nThe major aims of this study were to adapt the Bessel-beam technology for miniature 2PM and\nto explore its advantage in miniscope design. In response to the Reviewer’s comment, we imaged\nmore densely labeled samples and validated the miniBB2p’s capability to resolve individual neurons\nin these samples using high-resolution 3D reference images from a tabletop Gaussian-beam 2PM\n(refer to our response to Reviewer #2’s major comment #3). We also thank the Reviewer for\nhighlighting the important statistical consideration. We have now explicitly stated the number of\nanimals used in each experiment throughout the manuscript, ensuring all statistical comparisons\nclearly indicate the corresponding sample sizes where applicable.\n“Fig. 2 | System design and test of miniBB2p … Data in h are from a single representative\nexperiment (n=5 animals, one experiment per animal).”\n“Fig. 3 | Minimal impact of miniBB2p on animal movement… Data represent measurements\ncollected from 12 individual animals.”\n17\n“Fig. 4 | Imaging the response of pyramidal neurons in M2 to locomotion… Data represent one\nof three experiments in one animal.”\n“Fig. 5 | Imaging neuronal populations in ACC under different pain stimulation paradigms…\nData in b-d are from a single representative experiment (n=5 animals, one experiment per animal);\ndata in e-h are statistics derived from all five experiments.”\n“Supplementary Fig. 5 | Imaging of dendrites and spines in the head-fixed awake Thy1-GFP\nmouse brain… Data are from a single representative experiment (n=3 animals, one experiment per\nanimal).”\n“Supplementary Fig. 6 | Imaging of the activities of dendrites and spines in ACC of awake\nmouse expressing GCaMP8s…Data in a-b are from a separate representative experiment (n=6\nanimals, one experiment per animal).”\n“Supplementary Fig. 7 | Stability of miniBB2p imaging… Data are from a single representative\nexperiment (n=2 animals, one experiment per animal).\n“Supplementary Fig. 10 | Inhibition of S1 inputs enhance the nociceptive response in ACC…\nData are from a single representative experiment (n=3 animals, one experiment per animal).”\n“1) The argument in the introduction justifying bessel beam excitation vs optical sectioning is not\ncompelling and should be revised, especially given that optical sectioning has been shown to enable\nsingle cell resolution, especially in the axial plane, something that, the current bessel beam\napproach cannot fully claim without clearer demonstrations.”\nReply: We thank the Reviewer for bringing this matter to our attention. To comply with Reviewer’s\ncomment, in the INTRODUCTION, we have revised the justification of Bessel beam excitation vs\noptical sectioning.\n“…Gaussian-beam 2PM records a stack of 2D optical sections across the depth to achieve 3D\nimaging, it favors resolving the fine structures in the axial dimension at a compromised imaging\nspeed. In contrast, Bessel-beam 2PM…”\n“It is an effective tool for volumetric calcium imaging in vivo, as the position of neurons and their fine\nstructures remain stable during imaging [17]. In addition, if needed, the axial coordinates of\nstructures in the 2D projections can be retrieved with a full 3D reference image from a Gaussian-\nbeam 2PM.”\n“2) There are many instances that the wrong reference is cited, for example, statement on line 36\nthat “…..freely moving animals as brain movement is less constrained [1]….” This is not strictly true,\nfreely moving animals have been shown to have less brain movement displacement than head-fixed,\nsee Sawinski et al 2009 PNAS. The cited reference (Helmchen et al) never recorded from freely\n18\nmoving animals, please revise. The rest of the paragraph is a bit vague and the argument is\nsomehow weak concerning optical sectioning being an issue. Optical sectioning approaches have\nbeen successfully applied to extract neuronal activity from large neuronal populations in freely\nmoving animals, even when jumping, without loss of signals or motion artifacts.”\nReply: We appreciate the Reviewer’s comment and have corrected the cited reference accordingly.\nWith advancements in technology, state-of-the-art miniscopes have effectively minimized axial\nmovements. However, when they do occur, these movements can confound measurements. In\nSawinski et al. [8], imaging freely moving animals indeed were subject to axial brain tissue\ndisplacements (Fig. S3 in their paper), and the data affected by motion artifacts were excluded2. In\nanother work, Zhao et al. [7] systematically quantified axial motion artifacts in miniscope imaging,\nshowing considerably larger axial displacement in freely behaving mice compared to head-fixed\nmice (Extended Data Fig. 8e-f in their paper). Their measurements revealed axial displacements\nranging approximately [-4, +8] μm in PPC L5 and [-6, +10] μm in hippocampal CA1 during\nunrestrained behavior.\nOur simulations showed that imaging with an extended depth of field significantly improves the\nfluorescence signal stability against axial displacement (please see our response to Reviewer #2’s\nmajor comment #2). Accordingly, we believe miniBB2p can significantly suppresses the axial\nmotion artifacts compared to Gaussian-beam miniature 2PMs, particularly during periods of\nvigorous behavioral activity.\n“3) Given the ~80 – 90 micron axial resolution, how were vertically aligned neurons separated into\nindividual neurons? How were the transients extracted from the populations of neurons without\ncontamination? What is the measure of surety that each pixel claimed to be from a separate neuron\nwas indeed from a separate neuron? There was some effort to address these questions in the\nsection that starts at line 100, but there are no statistics, comparisons, or compelling demonstrations\nshowing a clear one-to one relationship between Bessel beam imaged (x-y) pixels and 3D optical\nsectioning collected images from the same volume showing the same neurons. Please show a z-\nstack of the imaged area using a conventional microscope and then a matched image from the\nBessel beam approach showing where the neurons are located within the volume.”\nReply: We appreciate the Reviewer’s comment. In Suite2p, the “allow_overlap” parameter\ndetermines whether the overlapping regions are included in calcium signal extraction. For our\nanalysis, we set allow_overlap = 0, thereby excluding overlapping pixels from calcium trace\ngeneration (see the figure below). This operation minimizes signal-contamination from adjacent cells\n(also refer to our response to the next comment).\n2 “However, some irregular motion during chewing or vigorous head shaking occurred occasionally. Frames (≈2% of\ntotal) were excluded whenever small structures suddenly appeared or disappeared” by Sawinski et al. [8] is quoted here.\nIdentified cells (randomly colored for visualization).\nWhite arrow highlights a Suite2p-identified cell, with\ncalcium traces extracted exclusively from its non-\noverlapping region (white). Lower panel: Suite2p-\ngenerated traces showing neuropil signal (red), raw\ncalcium activity (white), and deconvolved activity\n(blue) over a 30-minute recording period.\nTo comply with the Reviewer’s suggestion, we have updated our registration results by adding\none-to-one registrations between single 2D projections from miniBB2p and high-resolution 3D\nimage references from a tabletop Gaussian-beam 2PM (Supplementary Fig. 8) (also refer to our\nresponse to Reviewer #2’s major comment #3).\nSupplementary Fig. 8 | Validation of cellular registration in miniBB2p with a tabletop Gaussian-beam\n2PM. a, Imaging of the same volume using miniBB2p (top) and tabletop Gaussian-beam 2PM at an axial\ninterval of 3-μm, with structures colored by depth (bottom) (Day 15 data in Supplementary Fig. 7). b, Zoom-\nin view of the boxed areas in a. Note that weak signals (e.g., from dendrites and spines) in miniBB2p become\nobscured by stronger somatic signals due to axial signal integration, which is an inherent limitation in Bessel-\nbeam 2PMs. c, Cells identified by Suite2p from the miniBB2p imaging data (top); cells identified by Cellpose3\nfrom the Gaussian-beam imaging data (bottom). Cells are randomly colored for visualization. d, 3D spatial\ndistribution of the cells in the Gaussian-beam imaging data.\n“4) In the methods section starting at line 310, there were three traces extracted for each identified\nROI. Please show examples in the main figures how the traces were extracted from the raw data to\nend up with activity from each soma. As it is written in the methods, it is a bit mysterious and given\nthe axial resolution is extremely large, showing convincingly how each soma was isolated and how\nthe activity was extracted and separated from other contaminating structures would be important.”\nextracted using Suite2p. Our neuronal signal processing pipeline follows established imaging\nmethodologies, as previously demonstrated in Zong et al. [6]. The traces correspond to: (1) the\nneuropil signal, (2) raw calcium activity, and (3) deconvolved calcium activity [22] (as illustrated in\nour response to comment #3).\nIn miniBB2p, the 2D image has a higher likelihood of somatic overlap compared to conventional\nminiature Gaussian-beam 2PMs, which typically have a smaller depth of field. In our current study,\nthe somatic ROIs were defined by excluding overlapping regions from neighboring somas (also refer\nto our response to the last comment). This approach simplifies signal extraction and reduces cross-\ncontamination from adjacent cells, albeit at the cost of a reduced signal-to-noise ratio. Despite this\ntrade-off, miniBB2p remains capable of detecting calcium activity in partially overlapping somas,\nowing to its high fluorescence detection efficiency and the use of high-performance calcium\nindicators. However, we anticipate that somatic overlap could pose a greater challenge when\nimaging indicators with low functional dynamic range (e.g., ~10% ΔF/F as voltage indicators). In\nsuch cases, more advanced signal extraction algorithms may be necessary to resolve signals from\noverlapping pixels.\n“5) I’m not sure what the point of the noxious stimulation is. It is claimed to be freely moving but in\nthe methods the paw was pricked with a needle, presumably by holding the paw, which is not very\nfreely moving.”\nReply: We would like to clarify that the noxious and non-noxious stimulation were indeed performed\nin freely moving mice. The animals were placed in a chamber on top of a mesh table, which allowed\nus to deliver the noxious mechanical stimulations (28 g needle pin prick) or non-noxious stimulations\n(0.4 g von Frey) from below through the mesh openings without restraining or handling the animals\nduring the procedure. This setup permits natural movement and minimizes stress during stimulation.\nSimilar approaches have been described in previous studies [23].\n“6) I’m not sure that Supplementary figure 7 makes a very compelling case for stable recording over\nmultiple days, the image quality in a, seems to be degrading over the 5 days. Can the authors\nprovide a cell health quantification to compare between imaging days? Many studies have done\nthis.”\nReply: We thank the reviewer for the insightful comment. We have extended the long-term stability\ntest from days to weeks and validated the neuron registrations from miniBB2p with a tabletop\nGaussian-beam 2PM. These new results validated the performance of miniBB2p in long-term\nimaging (refer to our response to Reviewer #2’s major comment #3). To comply with the\nReviewer’s suggestion, we evaluated the cell health by comparing the calcium activity of the neurons\nrecorded between imaging days (Supplementary Fig. 9). We found the ΔF/F of calcium spikes, a\nmetric has been used for photodamage quantification [24], has minimal variations across imaging\ndays (i.e., photodamage are minimal and cells are healthy).\nexisting miniature Gaussian-beam 2PMs. The axially elongated focus further reduces the power\ndensity on neurons, which may make miniBB2p less prone to photodamage (refer to our response\nto Reviewer #2’s minor comment #5). In the MiniBB2p enables longitudinal recordings with\nminimal constraints on animal behavior section in the RESULTS, we revised the sentence\ndescribing the long-term imaging stability of miniBB2p.\n“Our results revealed that the same neuronal populations could be monitored for weeks, with\nminimal photobleaching and photodamage (Supplementary Figs. 7-9), highlighting miniBB2p's\nsuitability for chronic imaging applications.”\nReferences:\n1. Lu, Rongwen, et al. \"Video-rate volumetric functional imaging of the brain at synaptic resolution.\"\nNature Neuroscience 20.4 (2017): 620-628. https://doi.org/10.1038/nn.4516.\n2. Lu, Rongwen, et al. \"Rapid mesoscale volumetric imaging of neural activity with synaptic\nresolution.\" Nature Methods 17.3 (2020): 291-294. https://doi.org/10.1038/s41592-020-0760-9\n3. Chen, Wei, et al. \"High-throughput volumetric mapping of synaptic transmission.\" Nature\nMethods 21.7 (2024): 1298-1305. https://doi.org/10.1038/s41592-024-02309-3\n4. Adam Ranson, https://github.com/ransona/ROIMatchPub\n5. Pachitariu, Marius, et al. \"Suite2p: beyond 10,000 neurons with standard two-photon\nmicroscopy.\" BioRxiv (2016): 061507. https://doi.org/10.1101/061507\n6. Zong, Weijian, et al. \"Large-scale two-photon calcium imaging in freely moving mice.\" Cell\n185.7 (2022): 1240-1256. https://doi.org/10.1016/j.cell.2022.02.017\n7. Zhao, Chunzhu, et al. \"Miniature three-photon microscopy maximized for scattered fluorescence\ncollection.\" Nature Methods 20.4 (2023): 617-622. https://doi.org/10.1038/s41592-023-01777-3\n8. Sawinski, Juergen, et al. \"Visually evoked activity in cortical cells imaged in freely moving\nanimals.\" Proceedings of the National Academy of Sciences 106.46 (2009): 19557-19562.\nhttps://doi.org/10.1073/pnas.0903680106\n9. Chen, Jerry L., et al. \"Online correction of licking-induced brain motion during two-photon\nimaging with a tunable lens.\" The Journal of physiology 591.19 (2013): 4689-4698.\nhttps://doi.org/10.1113/jphysiol.2013.259804\n10. Griffiths, Victoria A., et al. \"Real-time 3D movement correction for two-photon imaging in\nbehaving animals.\" Nature methods 17.7 (2020): 741-748.\nhttps://doi.org/10.1038/s41592-020-0851-7\n11. Aghayee, Samira, et al. \"Particle tracking facilitates real time capable motion correction in 2d or\n3d two-photon imaging of neuronal activity.\" Frontiers in neural circuits 11 (2017): 56.\nhttps://doi.org/10.3389/fncir.2017.00056\n12. Flores-Valle, Andres, and Johannes D. Seelig. \"Axial motion estimation and correction for\nsimultaneous multi-plane two-photon calcium imaging.\" Biomedical Optics Express 13.4 (2022):\n2035-2049. https://doi.org/10.1364/BOE.445775\n22\n13. Birks, Tim A., Jonathan C. Knight, and P. St J. Russell. \"Endlessly single-mode photonic crystal\nfiber.\" Optics letters 22.13 (1997): 961-963. https://doi.org/10.1364/OL.22.000961\n14. Flusberg, Benjamin A., et al. \"Fiber-optic fluorescence imaging.\" Nature methods 2.12 (2005):\n941-950. https://doi.org/10.1038/nmeth820\n15. Grosjean, Thierry, et al. \"Fiber microaxicons fabricated by a polishing technique for the\ngeneration of Bessel-like beams.\" Applied optics 46.33 (2007): 8061-8067.\nhttps://doi.org/10.1364/AO.46.008061\n16. Zong, Weijian, et al. \"Miniature two-photon microscopy for enlarged field-of-view, multi-plane\nand long-term brain imaging.\" Nature methods 18.1 (2021): 46-49.\nhttps://doi.org/10.1038/s41592-020-01024-z\n17. Zong, Weijian, et al. \"Fast high-resolution miniature two-photon microscopy for brain imaging in\nfreely behaving mice.\" Nature methods 14.7 (2017): 713-719.\nhttps://doi.org/10.1038/nmeth.4305\n18. Klioutchnikov, Alexandr, et al. \"A three-photon head-mounted microscope for imaging all layers\nof visual cortex in freely moving mice.\" Nature methods 20.4 (2023): 610-616.\nhttps://doi.org/10.1038/s41592-022-01688-9\n19. Zhang, Yuanlong, et al. \"A miniaturized mesoscope for the large-scale single-neuron-resolved\nimaging of neuronal activity in freely behaving mice.\" Nature Biomedical Engineering 8.6 (2024):\n754-774. https://doi.org/10.1038/s41551-024-01226-2\n20. Singh, Amrita, et al. \"Mapping cortical integration of sensory and affective pain pathways.\"\nCurrent Biology 30.9 (2020): 1703-1715. https://doi.org/10.1016/j.cub.2020.02.091\n21. Meng, Guanghan, et al. \"High-throughput synapse-resolving two-photon fluorescence\nmicroendoscopy for deep-brain volumetric imaging in vivo.\" Elife 8 (2019): e40805.\nhttps://doi.org/10.7554/eLife.40805\n22. Pachitariu, Marius, et al. \"Suite2p: beyond 10,000 neurons with standard two-photon\nmicroscopy.\" BioRxiv (2016): 061507. https://doi.org/10.1101/061507\n23. Talay, Robert S., et al. \"Pharmacological restoration of anti-nociceptive functions in the\nprefrontal cortex relieves chronic pain.\" Progress in neurobiology 201 (2021): 102001.\nhttps://doi.org/10.1016/j.pneurobio.2021.102001\n24. Ji, Na, Jeffrey C. Magee, and Eric Betzig. \"High-speed, low-photodamage nonlinear imaging\nusing passive pulse splitters.\" Nature methods 5.2 (2008): 197-202.\nhttps://doi.org/10.1038/nmeth.1175\n23"}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have significantly improved their manuscript. While I remain concerned that the inability to recover complete volumetric information could lead to misinterpretations in brain regions with high neuron density and activity, I believe this will be a valuable tool for the neuroscience research community. Therefore, I have no objection to its publication in Nature Communications.\n\nHowever, I strongly recommend that the authors expand their discussion to include the limitations of projecting an 80µm volume into a single z-plane. Currently, the discussion only addresses temporal pulse dispersion under high-power conditions. It would be very useful to inform readers and potential future users about the possibility of misidentifying two or more neurons along the z-dimension as a single neuron when using their current approach, and possibly cite existing literature on table top Bessel beam TP systems offering solutions for recovering volumetric information.", "reviewer_2": "Thank you for the revisions and for addressing many of the previous comments. I have a few remaining concerns. The use of a 1 m fiber may still be limiting, as longer and more flexible cables (e.g., 2.5 m in Zong et al., 2022) have been shown to better preserve natural behavior and without observable axial movements even with jumping behavior. It would be helpful to show a video of the mouse in the full 97.6 × 45 cm arena (not just smaller enclosures), and to explain why a longer fiber was not used. If multicolor imaging is not supported with the current laser/fiber combination, please clarify the reason for this fiber choice (and not other like HC-920 that support higher power). It would also be important to mention potential 2P efficiency losses at high powers due to self-phase modulation (SPM), as previously described (e.g., Helmchen, Tank, and Denk, 2002), and whether alternative fibers could help mitigate this.\n\nThe imaging depth now included (but not in previous version) appears relatively shallow compared to what is typically achievable with 2P systems—please clarify whether this reflects a limitation of the setup. The term “high throughput” might also be reconsidered, since ~600–1000 neurons are reported, while the term usually refers to recordings of well over 1000 neurons. From the data shown, it seems that achieving higher (subcellular) resolution requires reducing the field of view, and that recordings focus mainly on dendrites, spines, or boutons. This suggests that the system is particularly well-suited for sparse, volumetric, high-resolution subcellular imaging, rather than large-scale imaging. However, more activity traces of subcellular structures (such as in FigS6) would demonstrate the advantage of miniBB2p for subcellular recordings in freely moving mice.\n\nIn Supplementary Figure 7, most neurons appear in just two planes, which raises the question of whether acquiring two 2D planes at a higher frame rate (e.g., 20 Hz in mini2p at 258x258 pixels or 10 Hz at 512x512 pixels) might be more efficient than scanning a larger volume (80 µm) at 9 Hz (which might add neuropil contamination). While I appreciate the quantification of photodamage of cell bodies at 40 mW, the powers used for smaller FOVs (subcellular recordings) go up to 80–100 mW. Please consider testing or discussing photodamage under these conditions. Finally, if no direct comparison was made with benchtop 2P systems, I suggest avoiding statements like “In comparison, miniBB2p…fourfold increase….” which may imply such a comparison was performed (for same parameters).\n\nIn conclusion, this system represents an alternative for volumetric (hundreds of cells) recording in freely moving mice. Importantly, this system shows subcellular recordings in freely moving mice and, with a more in-depth analysis of subcellular activity, this system could have a big impact on the field. After the revisions, I am looking forward to the next version of the manuscript."}, "author_response": "Nature Communications Manuscript [NCOMMS-24-73654A]\n\"High-throughput two-photon volumetric brain imaging in freely moving mice\"\nAuthors' response to Reviewer's comments\nWe thank the Reviewers for their insightful and constructive comments, which have greatly\nstrengthened our manuscript. Major improvements include:\n We added a discussion regarding the limitation of axial neuron overlaps in miniBB2p,\nalong with potential strategies to address this issue.\n We performed dendritic spine imaging in freely moving mice to further demonstrate\nthe advantage of miniBB2p for subcellular recordings.\nPlease see our detailed replies to the Reviewers' comments below.\nReviewer #1 (Remarks to the Author):\n1. “The authors have significantly improved their manuscript. While I remain concerned that the\ninability to recover complete volumetric information could lead to misinterpretations in brain regions\nwith high neuron density and activity, I believe this will be a valuable tool for the neuroscience\nresearch community. Therefore, I have no objection to its publication in Nature Communications.”\nReply: We thank the Reviewer’s generous comments on miniBB2p. We added a discussion\nregarding the limitation of axial neuron overlaps in miniBB2p, along with potential strategies to\naddress this issue. Please see below for the detailed response.\n2. “However, I strongly recommend that the authors expand their discussion to include the limitations\nof projecting an 80µm volume into a single z-plane. Currently, the discussion only addresses\ntemporal pulse dispersion under high-power conditions. It would be very useful to inform readers\nand potential future users about the possibility of misidentifying two or more neurons along the z-\ndimension as a single neuron when using their current approach, and possibly cite existing literature\non table top Bessel beam TP systems offering solutions for recovering volumetric information.”\nReply: We thank the Reviewer for bringing this matter out. In the DISCUSSION, we added:\n“The extended depth of field in our miniBB2p system, as in tabletop Bessel-beam 2PM, is essential\nfor high-throughput volumetric imaging but inherently raises the possibility of misinterpreting axially\noverlapped neurons, particularly in samples with dense labeling. To mitigate this limitation,\nadvanced computational demixing methods, such as constrained nonnegative matrix factorization\n1\n(CNMF), can be applied to leverage the temporal sparsity of neural activity and separate signals\nfrom superimposed neurons [19, 27]. The accuracy of this spatiotemporal signal separation can be\nfurther improved by integrating prior structural information acquired from a tabletop Gaussian-beam\n2PM, which provides a high-resolution anatomical reference for precise segmentation. Finally, while\naxially overlapped neurons could lead to noise cross talk, the high sensitivity of advanced genetically\nencoded calcium indicators renders this effect minimal for resolving individual neurons in calcium\nimaging [19].”\nReviewer #2 (Remarks to the Author):\n1. “Thank you for the revisions and for addressing many of the previous comments. I have a few\nremaining concerns. The use of a 1 m fiber may still be limiting, as longer and more flexible cables\n(e.g., 2.5 m in Zong et al., 2022) have been shown to better preserve natural behavior and without\nobservable axial movements even with jumping behavior. It would be helpful to show a video of the\nmouse in the full 97.6 × 45 cm arena (not just smaller enclosures), and to explain why a longer fiber\nwas not used. If multicolor imaging is not supported with the current laser/fiber combination, please\nclarify the reason for this fiber choice (and not other like HC-920 that support higher power). It would\nalso be important to mention potential 2P efficiency losses at high powers due to self-phase\nmodulation (SPM), as previously described (e.g., Helmchen, Tank, and Denk, 2002), and whether\nalternative fibers could help mitigate this.”\nReply: We appreciate the Reviewer's constructive and insightful feedback. In miniBB2p, a 1-meter\nfiber was used to image a 30 × 20 cm² arena, a scale comparable to previous studies that used a\n1-meter fiber for a 30 × 30 cm² arena [R1]. We agree with the Reviewer that this fiber length could\nbe limiting in larger enclosures. This constraint was implemented to control pulse broadening. While\nthe laser’s built-in dispersion pre-compensation unit (range: up to -40, 000 fs²) is capable of fully\ncompensating the dispersion induced by up to 1.5 meters of LMA-12 fiber (~ -27, 000 fs² / m at 920\nnm), the self-phase modulation effect in the fiber can broaden the excitation pulses, particularly at\nhigh powers (> 100 mW after the fiber). To maintain a short pulse at the sample for optimal two-\nphoton excitation, the fiber length was conservatively limited to 1 meter to mitigate the nonlinear\neffect induced pulse broadening.\nThe LMA-12 fiber was chosen primarily due to its low cost and the compatibility of its dispersion\nwith the laser's built-in dispersion pre-compensation unit. This combination eliminated the need for\nextra dispersion compensation, allowing us to simplify the system design and reduce costs.\nIn the RESULT, we revised the sentence to describe the pulse broadening effect in the fiber.\n“The pulse in the fiber was broadened by material dispersion and nonlinear effects (e.g., self-phase\nmodulation) [23]”\nfiber and potential alternatives.\n“While the large-mode-area fiber used in this work can effectively deliver femtosecond laser pulses\nover a broad spectral range, a promising feature for imaging indicators with different excitation\nwavelengths, we noted that the pulse is substantially broadened at high power due to nonlinear\neffects within the fiber (Supplementary Fig. 2b). This shortcoming would compromise performance\nof the microscope when utilizing a power exceeding 100 mW. Future developments using hollow-\ncore photonic bandgap fiber (HC-920, NKT Photonics) can address this issue and further enhance\nthe sensitivity of miniBB2p in imaging GFP-based indicators [2].”\n2. “The imaging depth now included (but not in previous version) appears relatively shallow\ncompared to what is typically achievable with 2P systems—please clarify whether this reflects a\nlimitation of the setup. The term “high throughput” might also be reconsidered, since ~600–1000\nneurons are reported, while the term usually refers to recordings of well over 1000 neurons. From\nthe data shown, it seems that achieving higher (subcellular) resolution requires reducing the field of\nview, and that recordings focus mainly on dendrites, spines, or boutons. This suggests that the\nsystem is particularly well-suited for sparse, volumetric, high-resolution subcellular imaging, rather\nthan large-scale imaging. However, more activity traces of subcellular structures (such as in FigS6)\nwould demonstrate the advantage of miniBB2p for subcellular recordings in freely moving mice.”\nReply: The working distance of miniBB2p’s objective is ~1 mm, which sets the ultimate limit for\nimaging depth. In response to the Reviewer's comment, we have imaged a Thy1-GFP mouse brain\nacross a range of depths from 100 to 650 µm. As shown in the figure below, the results demonstrate\nrobust system performance across a substantial portion of the cortex.\nImaging across different imaging depths in the head-fixed awake Thy1-GFP mouse brain. a, -100 μm\nimaging depth in RSPd (dorsal retrosplenial cortex). b, -400 μm imaging depth in RSPd. c, -650 μm imaging\ndepth in M1. Top: Single frame of the raw data (9 fps); Bottom: 50-frame averaged images. All images were\nacquired at the power of 60 mW.\ninformation acquisition enabled by the Bessel beam's extended depth of field. In accordance with\nthe Reviewer's suggestion, we have replaced \"high-throughput\" with \"large-scale\" throughout the\nrevised manuscript when referring to the number of neurons imaged.\n“We share a full description of miniBB2p and demonstrate its ability to perform large-scale\nrecordings of the calcium activities of more than 1000 neurons at a time…”\nTo comply with the Reviewer’s comment on subcellular structures recordings, we performed\ndendritic spine imaging in freely moving mice with miniBB2p. In the revised manuscript, the result\nis presented in Supplementary Fig. 7 and Supplementary Video 4.\nSupplementary Fig. 7 | Imaging of the activities of dendrites and spines in ACC expressing GCaMP8s\nin a free-moving mouse over a 30-minute period. Image of a ~80-μm thick volume in ACC by miniBB2p\n(top) and representative calcium traces of dendrite and spines (bottom). Data represent one of three\nexperiments in one animal.\n4\n3. “In Supplementary Figure 7, most neurons appear in just two planes, which raises the question\nof whether acquiring two 2D planes at a higher frame rate (e.g., 20 Hz in mini2p at 258x258 pixels\nor 10 Hz at 512x512 pixels) might be more efficient than scanning a larger volume (80 µm) at 9 Hz\n(which might add neuropil contamination). While I appreciate the quantification of photodamage of\ncell bodies at 40 mW, the powers used for smaller FOVs (subcellular recordings) go up to 80–\n100 mW. Please consider testing or discussing photodamage under these conditions. Finally, if no\ndirect comparison was made with benchtop 2P systems, I suggest avoiding statements like “In\ncomparison, miniBB2p…fourfold increase….” which may imply such a comparison was performed\n(for same parameters).”\nReply: We thank the Reviewer’s comments and suggestions. If neurons appeared in only two\nplanes (each with 20 µm thickness) within the 80 µm depth of field, the performance of miniBB2p\nwould be compromised because half of the laser power is wasted. However, from a throughput\nperspective, its advantage remains evident, since imaging both planes requires only a single scan.\nAnalysis of the new dendritic spine imaging data (see our response to Comment #2) shows stable\nfluorescence baselines of dendrites and spines throughout the 30-minute recording in freely moving\nmice (see figure below), demonstrating minimal photodamage at laser powers up to 80 mW. This\nresult is aligned with the findings of Zhao et al. [R3], who demonstrated that the elongated focus\nreduces photobleaching and phototoxicity in volumetric imaging when compared to standard\nGaussian-beam 2PM.\nRaw data of the four representative calcium traces from dendrites and spines marked in\nSupplementary Fig. 7 (last figure)\nIn Fig. 2 in the manuscript, we compared the depth of field of miniBB2p (0.26 NA) with a tabletop\nGaussian-beam 2PM (0.3 NA). Similar comparisons were also described by Lu et al. [R4] in tabletop\nBessel-beam 2PM1.\n1“Compared to the 0.6 numerical aperture Gaussian focus, the Bessel focus elongated the axial extent of two-photon\nexcitation by approximately 18-fold.” by R. Lu et al. [R4] is quoted here.\n5\n4. “In conclusion, this system represents an alternative for volumetric (hundreds of cells) recording\nin freely moving mice. Importantly, this system shows subcellular recordings in freely moving mice\nand, with a more in-depth analysis of subcellular activity, this system could have a big impact on the\nfield. After the revisions, I am looking forward to the next version of the manuscript.”\nReply: We appreciate the Reviewer’s encouraging feedback and insightful comments. We have\nadded dendritic spine imaging results in freely moving mice to further demonstrate the advantage\nof miniBB2p for subcellular recordings. We believe these revisions have significantly improved the\nmanuscript and hope they meet your expectations.\nReferences:\nR1. Zong, W., Wu, R., Li, M. et al. Fast high-resolution miniature two-photon microscopy for brain\nimaging in freely behaving mice. Nat. Methods 14, 713–719 (2017).\nhttps://doi.org/10.1038/nmeth.4305\nR2. Meng, G. et al. High-throughput synapse-resolving two-photon fluorescence microendoscopy\nfor deep-brain volumetric imaging in vivo. eLife 8, e40805 (2019).\nhttps://doi.org/10.7554/eLife.40805\nR3. Zhao, Z. et al. Two-photon synthetic aperture microscopy for minimally invasive fast 3D\nimaging of native subcellular behaviors in deep tissue. Cell 186, 2475-2491(2023).\nhttps://doi.org/10.1016/j.cell.2023.04.016\nR4. Lu, R., Liang, Y., Meng, G. et al. Rapid mesoscale volumetric imaging of neural activity with\nsynaptic resolution. Nat. Methods 17, 291–294 (2020).\nhttps://doi.org/10.1038/s41592-020-0760-9\n6"}, {"round": 3, "reviewer_comments": {"reviewer_2": "The authors have substantially polished their manuscript and carefully addressed the reviewer comments, including clarifying technical choices and limitations. I agree that the system represents a valuable and innovative tool for the neuroscience research community. The demonstration of subcellular recordings in freely moving mice is particularly compelling and highlights the unique strengths of the approach."}, "author_response": "Nature Communications Manuscript [NCOMMS-24-73654B]\n\"High-throughput two-photon volumetric brain imaging in freely moving mice\"\nAuthors' response to Reviewer's comments\nReviewer #2 (Remarks to the Author):\n1. “The authors have substantially polished their manuscript and carefully addressed the reviewer\ncomments, including clarifying technical choices and limitations. I agree that the system represents\na valuable and innovative tool for the neuroscience research community. The demonstration of\nsubcellular recordings in freely moving mice is particularly compelling and highlights the unique\nstrengths of the approach.”\nReply: We thank the Reviewer for the insightful and constructive comments, which were essential\nto strengthening the manuscript.\n1"}]

Decision letter