Perpendicular neuromorphic channels facilitate lateral inhibition for tactile location

Domain: neuroscience
Published: 2026-01-07
Editorial outcome: major_revision

Abstract
Lateral inhibition refers to the inhibition of neurons as caused by excitation of its neighboring neurons, which helps increase the contrast and sharpness of touch, and pinpoint exact touch position. However, such important operational logic has not yet been realized in neuromorphic sensing systems at the device level. Herein, we demonstrate a cross-channel synaptic transistor (CST) that possesses two perpendicularly-integrated channels with separate source and drain electrodes but the same geometrical middle points. The architecture is fabricated by electro-hydrodynamically printed indium zinc oxide (IZO) nanowires with digital control. When one channel is excited, it attenuates the charge-carrier transport in its perpendicular channel, fundamentally realizing the lateral inhibition behavior on the device level, forming a competitive charge-transport mechanism. The device was successfully applied to precise localization of the touch point on an electronic skin, and the position can be visually displayed simultaneously. The special device architecture can be used to generate a lateral-inhibition-encryption (LIE) key that encrypts Morse code, which ensures 100% accurate decryption by traversal decryption of all letters and encryption types. This work demonstrates a new strategy to emulate bioinspired operation logic on device level for the construction of future bioinspired electronics.

Introduction
When our skin is subjected to a sudden touch at some point, our event-driven neural information processing can precisely pick out this information from a variety of tactile information1–7. This frequently occurs in our daily life, essential for tremendous everyday tasks8–10. The precise localization of touch attributes to lateral inhibition, which is an important neural processing mechanism that refers to the excitable activities of a neuron upon stimulation results in inhibitory effects on neighboring neurons11,12. Lateral inhibition enhances the accuracy of perception, recognition, and spatial localization of stimuli by reducing the response of peripheral neurons by reducing background noise and interference13–15. Lateral inhibition mechanism has inspired a variety of research fields, for improving the functions of artificial senses16–18. Lateral inhibition is applicable to a variety of bioinspired applications19. In artificial intelligence, “algorithmic lateral inhibition” assists neural networks to focus visual attention for objective recognition20, real-time motion recognition21. This mechanism also inspires some preliminary research on functional device sets for constructing visual processing. Different terminals in the same synaptic transistor are used to emulate the competition between horizontal cells, by employing the lateral gates of an anti-ferroelectric field-effect transistor22. Other attempts include the combination of a controlling transistor with a sensing unit, where light and olfactory responses are inhibited by tuning the gate voltage inputs to restrict the charge injected into the parasitic drain capacitor of the sensor unit23,24. However, these implementations of lateral inhibition either rely on the inherent properties of conventional transistors that require manual intervention for inhibitory stimulus regulation, or they depend on the collaboration of different types of functional modules, which do not represent inhibitory effect between similar neurons, and thus difficult to fully replicate the complete functionality of biological lateral inhibition. All the above processes are modulated by artificial electrical pulses, whereas lateral inhibition is usually caused by the sense of surrounding environment to result in the inhibitory effect. Moreover, further exploration is needed on how lateral inhibition assists tactile perception in electronic skin, which is essential in constructing bioinspired and bio-integrated interfaces.

Herein, we demonstrate a tactile nervous system that involves lateral inhibition behavior, for precise localization of tactile information, which is also visually displayed simultaneously. This is realized by a specially designed key information processing unit, a cross-channel synaptic transistor (CST) with two crossed indium zinc oxide (IZO) nanowires as perpendicular but jointed channel as digitally printed by electrohydrodynamic nanowire printing technique, gated by a shared ion gel sheet. When one channel is excited, the other channel is laterally attenuated, serving as the inhibitory channel and implying lateral inhibition. CST was used to develop a lateral inhibition key for secure communication with 100% decryption accuracy. This work offers a new insight to the construction of bioinspired systems and electronics.

Results
Design concept
When our skin is touched, several adjacent receptors can be activated25. A layer of interneurons between sensory cells and neurons leading to the central nervous system can transmit excitatory signals from receptor cells, and send inhibitory signals to other nearby interneurons, to concentrate our focus on the central contact region. This phenomenon is known as lateral inhibition26,27. We demonstrate an artificial tactile nervous system that is composed of cross-channel synaptic transistors to replicate the above phenomenon. We fabricated a pair of perpendicularly aligned IZO nanowires (NWs) for the synaptic transistors using electrohydrodynamic nanowire printing (e-NWP) process, and used the device to process the perceived tactile information, which is centralized by the lateral inhibition mechanism and simultaneously displayed visually (Fig. 1).

Design and fabrication of CST
A CST with perpendicular IZO-channels was fabricated to demonstrate the lateral inhibition phenomenon (Fig. 2a): A tungsten probe in contact with ion gel emulated the biological axon and presynaptic membrane to conduct presynaptic spikes. The ion gel rich in mobile ions that could migrate to the channel region in response to the presynaptic spike, inducing the change of charge carrier amounts in the channels. One of the IZO channels emulated synaptic cleft, through which neurotransmitters are released to cause postsynaptic currents (PSC) as controlled by resting potential (V_DS1) of 1V and the stimulation potential (V_GS). The other IZO channel served as the laterally inhibitory side, receiving information from neighboring neurons through the second drain.

Digitally-aligned long and continuous IZO NWs were printed using e-NWP, which is a cost-effective, eco-friendly and precise printing technique28. Cross-structured NW arrays were mass produced, showing high transparency (Fig. 2b). The NW arrays exhibited a straight and uniform morphology with consistent diameters (Fig. 2c, d), and the spacing between the arrays was precisely controlled, with a minimum spacing of 20 μm (Fig. 2e–h). The intersections of the NWs changed from a stacked to a flat morphology after sintering (Fig. 2i, j). The typical diameter of a single NW was ~250 nm (Fig. 2k). Elemental mapping demonstrated the evenly distributed indium (In), zinc (Zn), and oxygen (O) in a NW (Fig. 2l).

Sensory cells can improve acuity through the lateral inhibition mechanism29. When there is overlap of receptive fields, this mechanism works. A single stimulus, e.g., slight press of a pencil tip on skin, can activate several adjacent receptors near the tip. Normally, all these cells might pass on a stimulatory message to the central nervous system, making it difficult to determine the exact location of the touch point. However, if lateral inhibition is applicable, then there is a layer of interneurons that lie between the sensory cells and the neurons that lead to the central nervous system. These interneurons relay excitatory signals from the receptor cells, but they also employ axonal branches that can send inhibitory signals to other interneurons nearby. This set up allows the interneuron that receives the strongest signal from a sensory cell to amplify the stimulatory message to the central nervous system while inhibiting the signals from nearby interneurons30. As a result, the signal to the central nervous system is more focused (Fig. 3a). Similar phenomenon was simulated by CST. When the applied lateral inhibition voltage (V_DS2) increased, the transfer curves of inhibitory side showed potentiation trend, while output attenuation trend (Supplementary Fig. S1a–c and Fig. S2). Under shared top gate, the gate current was significantly smaller than the channel current (Supplementary Fig. S1d). To elucidate the lateral-inhibition mechanism, finite-element simulations of the electric-field (Supplementary Fig. S3a) and potential distributions (Supplementary Fig. S3b) were performed under varied V_DS2, confirming the progressive suppression of the output side and the eventual reversal of the inhibitory channel current. When applied single presynaptic spike (4V, 50 ms), PSCs were induced to simulate transmission of neurotransmitters in the synaptic cleft. With the increase of V_DS2, PSC from output side exhibited an attenuation of amplitude (Supplementary Fig. S4).

As an essential type of short-term plasticity (STP), paired-pulse facilitation (PPF) plays a pivotal role in neural information processing. Its functionalities encompass the transmission of information across synapses and the temporal filtering of bioinformation, etc.31–36. The CST has replicated the functionality of PPF. Two consecutive presynaptic spikes (4V, 50 ms) were applied under different V_DS2, the first spike induced an action response A1, and the second produced a response A2, the interval time Δt between the two spikes was 50 ms. PPF index (100% × A2/A1) of output side were calculated as 155.27%, 153.83%, 163.88% and 159.03% when under V_DS2 of 0, 0.2, 0.5 and 1V, which certified that the application of lateral inhibition only changes the amplitude of PSCs but has negligible effect on the plasticity (Supplementary Fig. S5).

Figure 3b illustrates the PSC of the output side in CST under no lateral inhibition (V_DS2 = 0V) and with lateral inhibition (V_DS2 = 1V). Despite the enhancement of PSC after 20 presynaptic spikes of 4V in both cases, the synaptic input from the inhibitory side results in a significant attenuation of the amplitude compared to the synapse without lateral inhibition. Furthermore, through the drain terminal of the inhibitory side, PSC originating from the inhibitory side can also be observed (Fig. 3c). The patterns of enhancement and attenuation were opposite to those observed in the PSC from the output side, in accordance with Kirchhoff’s current law (KCL)37. This provides additional synaptic weight evidence for tracking changes in data within the internal system.

Suppressive input of different intensities from inhibitory side can regulate synaptic weights in response to fixed spikes. We investigated the inhibitory-strength-dependent plasticity of CST by varying V_DS2 ranging from 0 to 1V. As the inhibitory voltage increased, the output PSC peak showed a nearly linear reduction, with a maximum reduction of 43% compared to the non-inhibited state within this range (Supplementary Fig. S6). To further quantify the influence of V_DS2 on the temporal dynamics of synaptic plasticity, the PSC-retention curves were fitted using a simple first-order stretched exponential function (SEF)38:

I = (I0 - I∞) × exp[-(t/τ)^β] + I∞ (1)

where t is the time that the pulse finishes, I0 is the initial PSC when the presynaptic spike finishes, I∞ is the final PSC at equilibrium, 0 ≤ β ≤ 1 is a stretch index, and τ is the retention time. In the CST, as V_DS2 increases from 0 to 1V, τ initially decreases and then increases, forming an approximately symmetric relationship around the inhibitory voltage of 0.5V. The fluctuation range of τ value is not significant, which is attributed to the two perpendicular IZO-channels sharing the same gate, thereby ensuring comparable synaptic plasticity in these channels (Supplementary Fig. S7). The device was tested under different humidity from 20% to 60%, and back to 20% (Supplementary Fig. S8).

The electric field and current distribution in CST were simulated using COMSOL Multiphysics (Fig. 3g–j)39, where the arrow size and direction represent the magnitude and direction of the current in the NWs at the simulation time of 2s, respectively. The electric field and current distributions under different V_DS2 were consistent with the trend in PSC (Supplementary Fig. S9). Current-voltage (I-V) contour maps from output side and from inhibitory side elucidates the operation mechanism of the CST with IZO cross-channels (Supplementary Fig. S10).

Furthermore, a series of spike trains at different frequencies were applied to investigate frequency-dependent plasticity under the influence of different levels of lateral inhibition (Supplementary Fig. S11). As the pulse frequency increased, both PSCs from the output side and inhibitory side increased (Fig. 3e, f); this was due to the high-frequency stimulation driving more cations to migrate towards the channel region, inducing larger electron flow40. Through the synergistic interaction of spike frequency and inhibitory voltage, the regulatory range of synaptic weights on the output side could be increased by up to 270% (Fig. 3e). Moreover, when a sufficiently large bias voltage of 1V was applied by the inhibitory side, it caused an inversion of the output PSC of this side (Fig. 3f). A similar phenomenon was observed for PSCs triggered by presynaptic stimuli with different numbers of spikes (Supplementary Fig. S12). This characteristic can be utilized in signal processing applications to determine whether sufficient lateral inhibition is present simply by assessing the polarity of the PSC41.

We validated the processing capability of CST in response to stimulus signals by applying a series of alternating inhibitory pulses at 0V and 1V. It was observed that the polarity of the inhibitory-side PSC switched instantly with the variation of inhibitory bias voltage (Supplementary Fig. S13b). Furthermore, unlike the conventional approach of modulating synaptic weights through applied gate spikes, the output-side PSC was regulated by the inhibitory bias voltage, achieving potentiation-depression regulation (Supplementary Fig. S13a). This provides a new approach for synaptic weight update. After over 150 cycles of testing, CST exhibited stable PSC of a negligible decay, indicating its great encoding potential.

The response speed of output side and inhibitory side was measured, showing a rise period (t_on) of 39.9 ms, 42.2 ms and a drop period (t_off) of 656.8 ms, 43.3 ms, respectively (Supplementary Fig. S14). The extended t_off is a result of the synaptic plasticity in the device, which is essential for in-sensor information processing. Energy consumption of the device is evaluated as E = AIW, where A is driving voltage, I is channel current, and W is duration of presynaptic spike. For a single channel, the minimal E of output side was ~0.108 fJ per synaptic event, with A = 0.01 mV, I = 0.215 nA, and W = 50 ms (Supplementary Fig. S15a). Spike-number-dependent plasticity (SNDP) was also emulated using consecutive presynaptic spikes (Supplementary Fig. S15b). Applying a consecutive sequence of presynaptic spikes to CST, the stimulus enhancement from the inhibitory side and the attenuation from the output side (Supplementary Fig. S16) significantly improves the ratio between EPSC, which contributes to the differential processing between pixels. The wafer-level device fabrication process to verify the scalability of the cross-channel printing process (Supplementary Fig. S17). The nanowire array-based CST had a device pitch of 180 μm (Supplementary Fig. S18). The electrical properties of the CST are compared with state-of-art lateral inhibition-based neuromorphic systems (Table S1)22,23,42–45. The cross-coupled nanowire architecture of CST encodes data in the form that cannot be retrieved by a single channel, providing physically built-in information protection without extra encryption circuit. The device shows high energy-efficiency. The system could be improved by further improving the response time asymmetry and reducing the pitch size.

The uniformity of response across the CST array was systematically evaluated. Under identical presynaptic spikes (4V, 50 ms) with lateral inhibition under V_DS2 = 0.5V, highly reproducible currents from output side and inhibitory side were observed across all 3×3 devices (Supplementary Fig. S19). The device-to-device (D2D) variations were examined using data statistics. The variation coefficient (σ/μ) for peak currents A1, A5, and A20 were calculated to be 4.09%, 3.57%, and 4.25% at the output side, and to be 2.57%, 2.16%, and 1.97% at the inhibitory side, respectively, where σ denotes the standard deviation and μ is the mean value (Supplementary Fig. S20).

We further investigated the application of CST in secure communication by applying different bias voltages to the inhibitory side. Using the PSC from inhibitory side as the encryption key (Fig. 3i) and the PSC from output side as the encrypted PSC (Fig. 3j), then the original PSC response without inhibitory bias can be reconstruct by weighting the two PSCs. Remarkably, even under different inhibitory states, the decryption method yielded highly accurate signal reconstruction compared to the unencrypted signal (Fig. 3k).

Encryption and decryption of Morse letters
The CST was used to respond to electrical impulses that represented international Morse code, and thereby demonstrated potential application in encrypted signal coding46. Stimulated by encoded short “dot” signals (4V, 0.1s) and long “dash” signals (4V, 0.15s), the CST efficiently generated distinct PSC amplitudes on the output side corresponding to English letters (Fig. 4a, b and Supplementary Fig. S21). Notably, the amplitude of the inhibition-encryption side PSC remained stable throughout the decoding process (Figs. 4a, b).

Additionally, due to its exclusive lateral inhibition function, CST can encrypt Morse letters by modulating the bias voltage on the inhibitory side, serving as the lateral-inhibition-encryption (LIE) key. The negative encryption key represents unencrypted, while positive one represents encrypted (Fig. 4c, left). This LIE method can suppress the large PSC peaks of representing “dash” signals to a level equivalent to the small peaks of short “dot” signals, thus Morse letters containing one or more “dash” signals can receive varying degrees of encryption (Fig. 4c, d). Using the letter “J” as an example, it can be transformed into 7 other encrypted signals by encrypting the “dash” signals in different positions (Fig. 4e). The total of 8 possible outputs makes it very challenging to trace back to their original signals without the LIE key. This method can increase the confidentiality of communication, potentially applicable to such as aviation lighthouses, to transmit information to aircraft, and provides solutions for setting the direction of information transmission in smart-home devices such as electronic locks. A confusion matrix in Fig. 4f summarizes the LIE of 26 letters. For letters containing only “dot” signals, they cannot be encrypted and only produce unique possible signals, with a low security level of only 1; As the number of “dash” signals increases, the potential output type after encryption also increases, with the security level progressively rising to a maximum of 8. Randomized encryption of phrase “nankai” was also achieved by this method (Supplementary Fig. S22).

With the assistance and weighting of the encryption key (Fig. 3i–k), the encrypted letters can also be decrypted and the PSC peaks corresponding to ‘dot’ and ‘dash’ can be reconstructed (Fig. 4g). After traversing and decrypting all the letters and encryption types, it was verified that this method could achieve 100% accurate decryption (Fig. 4h). Compared with the state-of-the-art devices with encryption functions, CST not only achieves instantaneous large-signal transmission and encryption with just one single input, but also instantly outputs key signals through an additional lateral inhibition output, benefiting from the symmetric channels and the shared gate. Furthermore, owing to the unique characteristics of cross-coupled dual channels, CST represents the first instance where measurable key signals are weighted to achieve high-accuracy decryption (Table S2)47–55.

Accurate Morse coding for the long sentence “I LOVE NEUROMORPHIC DEVICE” was achieved by representing combinations of “dot” and “dash” signals to represent different letters. Based on the LIE method, the original long sentence was randomly encrypted. By randomly suppressing the encryption key on the inhibitory side, each letter was randomly encrypted to generate an encrypted signal: “I LDHE IESSKNUSHHIB SEHIFE”. Using decryption process to achieve lossless backtracking of the original contents of the encrypted signal (Fig. 4i). In addition, employing a 10N pressure as an encryption key and utilizing the above described decryption procedure, the phrase “Nankai” was encrypted and decrypted effectively (Supplementary Fig. S23). This coding system based on lateral suppression encryption provided a secure encryption and decryption method, which protected the confidentiality of sensitive information. This system has potential applications in protecting data security and privacy, potentially applicable to secure wearable devices, internet of things (IoT), etc.

Lateral inhibition in an artificial tactile nervous system
Under the effect of somatosensory lateral inhibition, when a skin region is stimulated, the unstimulated regions around it are also affected, which can reduce the excitation level of the surrounding regions, thereby helping people perceive and localize the source of stimulation more accurately (Fig. 5a). To achieve this, an artificial tactile nervous system was fabricated to achieve real-time perception and signal processing of external stimuli at different locations under lateral inhibition, and to execute visual sensing of the stimulation location through display unit (Fig. 5b and Supplementary Fig. S24). In our tactile nervous system, pressure signals acting at different locations were captured and converted into electrical signals by the responding pressure-sensitive units as bias voltages applied to the inhibitory side of CST. In this process, PSC on the inhibitory side increased, representing an increase in pressure in the center region, and the PSC on the output side decreased, representing that the surrounding region was affected to present an inhibitory effect. PSC was converted to voltage by the amplification module, read by the control module, and transmitted to the display unit through the display encoding to visualize and locate the pressure lateral inhibition.

People can accurately locate stimuli on the skin through lateral inhibition. Analogously, for our tactile nervous system, when different position units of the sensor are pressed with pressures up to 10N, the bias voltage of the inhibitory side of the CST increases from 0.5 to 1V, peak values of the PSC of the output side and inhibitory side change from 45 μA, controlling the change of the color of the display unit. When pressed one sensitive unit, PSC on the inhibitory side rapidly increased to ~66 μA, PSC on the output side decreased to ~25 μA, the color of the corresponding unit of the display device deepened, and the color of the surrounding area became lighter (event #1, 6s). When pressed the adjacent pressure-sensitive unit, the color change at another location was accurately displayed (event #2, 12s). When continuously pressed the pressure-sensitive unit, PSC of the inhibitory side continued to increase, the color of the display area deepened (event #3, 6s). When the pressure is released, PSC quickly returned to the initial state, the display device restored (event #4, 12s) (Fig. 5c). In addition, calibration curves of ΔPSCs under various pressures were constructed to discern the impact of pressure magnitude (Figure S25). This lateral inhibition mechanism facilitates more accurate touch localization. (Supplementary Fig. S26).

Additionally, to enhance the robustness of our LIE-based encryption/decryption strategy against device non-idealities, we integrated it with a reservoir computing process (Supplementary Fig. S27a). We introduced random sampling offsets of ±0.15s and ±3% noise into the signals, creating a training set with 2058 non-ideal samples (Supplementary Fig. S27b). The LIE-RC system achieved 100% recognition accuracy, demonstrating its strong compensatory capabilities and potential for adaptive calibration under non-ideal conditions (Supplementary Fig. S27c).

Methods
e-NWP of IZO NWs
Zinc acetate dihydrate (Zn(CH3COO)2·2H2O, ZnACD, metallic precursors), indium nitrate hydrate (In(NO3)3·xH2O, InNH, metallic precursors) and polyvinyl pyrrolidone (PVP, sacrificial polymer) were dissolved in a mixture of N,N-dimethylformamide (DMF, common solvent) and chlorobenzene, and then stirring for 12 h at room temperature. Crossed IZO NW arrays were printed on the heat-resistant polyimide (PI) substrate. The distance between PI substrate and nozzle tip was set to 3 mm, and the electric field generated between the nozzle and the collector was 1 kV. The blended NWs were converted to IZO NWs by calcination in a muffle furnace at 450 °C in air.

Fabrication of CST
A pair of templated 80-nm gold source and drain electrodes was evaporated on the NWs. Ion gel was fabricated from poly(vinylidene fluoride-hexafluoropropylene) (P(VDF-HFP)) block copolymer and 1-ethyl-3-methylimidazolium bis(trifluoromethyl sulfonyl) imide ([EMIM]-[TFSI]) that covered on the IZO channel and part of the source and drain electrodes. A Pt probe was in contact with the ion gel sheet as the shared presynaptic input terminal.

Characterization. The morphological structure of NWs and were observed using a FEI Apreo S microscope. The arrangement of IZO NWs arrays was simply observed using the Leica DM2700M optical microscope (OM). Atomic force microscopy (AFM) images and height profiles of the 2D materials were collected using a Bruker dimension icon microscope operated in tapping mode. High-resolution transmission electron microscopy (HRTEM) images were obtained using a FEI Talos F200X microscope. Elemental mapping was acquired using a built-in Energy-dispersive X-ray spectroscopy (EDXS) measurement module in the TEM system. All electrical measurements were obtained using a Keithley 4200 SCS semiconductor analyzer in an N2-filled glovebox.

Fabrication of artificial tactile nervous system
The artificial tactile nervous system comprises an information processing unit and a signal acquisition and display unit. Information Processing Unit: A matrix thin-film pressure sensor (IMM00092A, i-Motion sensor) serves as the pressure-sensing module, whose electrical resistance (Rsensor) decreases with increasing applied pressure. Rsensor is connected in series with a voltage divider resistor (Rs). Consequently, the drain voltage (V_DS2) of the synaptic transistor increases/decreases as Rsensor increases/decreases. The two output currents (I_out1 and I_out2) from the artificial synaptic device are converted into corresponding output voltages (V_out1 and V_out2) using operational amplifiers (LM358). Signal Acquisition and Display Unit: A microcontroller unit (MCU, ATmega328P, Microchip) digitizes the analog signals V_out1 and V_out2. Subsequently, these digital signals undergo threshold comparison. The results of this threshold comparison are then converted into voltage signals and transmitted to the liquid crystal display screen (ILI9431) for visualization.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The manuscript \"Perpendicular neuromorphic channels facilitate lateral inhibition for tactile location\" demonstrates a new strategy to simulate biomimetic operating logic at the device level for precise localization of touch points for applications. This is an interesting work that is able to replicates the lateral inhibition mechanism in our skin. However, there are some questions need to well address, and I would like to recommend acceptance of this work after major revisions.\n1)The originality and novelty of the work need to be further improved. The bioinspired tactile device has been broadly studied over the past few years. Numerous research papers of this topic have been published before. The authors had better highlight one most novel breakthrough of the device. What is the most unique and important feature of the proposed devices? What is the most suitable application scenario for this proposed device?\n2)The gate leakage current of both the transfer characteristics is needed in Fig. S1.\n3)To further validate the stability and scalability of the device, additional experiments are needed to observe how the performance varies with the size of the active area or the distance between the electrodes.\n4)The properties of ion gel dielectric can be influenced by external environment, such as humidity, temperature, thus the operating environment of artificial tactile nervous system should introduce.\n5)Please explain why ion gates are used. What are its advantages compared to other gate dielectrics? Are there any stability issues? Especially after arraying, as the resistance increases, the device performance degrades due to heat.\n6)The mechanism of lateral inhibition behavior should be explained in more details.\n7)The authors do not clearly describe the working principle of the device and the specific carrier transport mechanism. It is suggested that in addition to finite element simulation, other characterization methods can be used to demonstrate the influence of the structure on carrier transport.\n8)In the final application section, the authors are suggested to provide the photograph of the experimental setup for electrical testing, including specific test parameters, test procedures, etc.\n9)In Figure 5b, the authors used this system to capture neural-like tactile signals and then compared them in a database. How would the results be different if the signals were obtained directly from the PVDF sensor and compared in a corresponding database? Would it be easier to identify neural-like signals than PVDF output signals?\n10)The effect of different frequencies and pressures on the output signal should be further explained. If both the amplitude and frequency of the applied force affect the output signal (Fig. 5c), it is important to clarify how to decouple the output signal to accurately determine the amplitude and frequency of the input force.\n11)Could the author demonstrate the stability of the sensor over a period of time?\n12)Did the authors prepare an array of devices or just a group of devices? If it is an array, how is the homogeneity and stability of the devices guaranteed?", "reviewer_2": "In this work, the authors report cross-channel synaptic transistors (CST) based on perpendicularly aligned indium zinc oxide nanowire channels to emulate lateral inhibition for tactile localization. This unique architecture enables the development of a lateral-inhibition-encryption (LIE) key, that can encrypt Morse code and achieve 100% accurate decryption across all letters and encryption types. Furthermore, the device facilitates precise touch-point localization with simultaneous visual display. While the work is intriguing, several important issues need to be addressed. The comments are as follows:\n1. The authors mentioned that the lateral inhibition of the CST is achieved through a competitive charge-transport mechanism, where excitation of one channel attenuates charge-carrier transport in the perpendicular channel. Therefore, it is crucial to provide detailed descriptions and corresponding schematic diagrams of this charge-transport mechanism. This should include the underlying physical principles, the specific roles of mobile ions in the ion gel layer, the interaction between channels, and other relevant factors.\n2. The authors demonstrated the application of the CST to encrypt and decrypt Morse code. However, according to Fig. 3b (left panel), the postsynaptic currents on the output side exhibit inherent short-term plasticity, which could be directly used for encryption and decryption of Morse code. Therefore, the authors should provide the advantages of using the LIE key for this process. Additionally, a comparison of classification accuracy between the cases with and without LIE processing is required.\n3. Since the theme of this manuscript highlights perpendicular neuromorphic channels facilitate lateral inhibition for tactile localization, it is essential to demonstrate the relationship between the encryption/decryption of Morse code and tactile location.\n4. Line 279, 280: \"The leakage current of the inhibitory side of the CST increases from 0.5 to 1 V.\" There is a mismatch between the current and its unit in this sentence. The authors should correct this.\n5. The authors have provided limited information regarding the pressure sensor and display modules. To enhance the clarity of the manuscript, additional details are needed, including the device structure, fabrication methods, a detailed circuit schematic diagram, and photographs of the actual system.\n6. According to Fig. 5b, each pixel of the sensor unit is connected to a 3 × 3 pixel array on the display to emulate lateral inhibition, which increases circuit complexity and energy consumption. However, it seems that connecting each sensor pixel directly to a single display pixel through the inhibitory side, without involving the output side, could also achieve accurate pressure localization. In this scenario, only the transistors corresponding to the stimulated pixels in the pressure sensor would increase their current, deepening the color of the corresponding display pixels. Therefore, the authors should provide comparative experiments to validate the advantages of their artificial tactile nervous system and demonstrate whether the contrast between stimulated and non-stimulated pixels can be improved using their design.\n7. Line 497: \"and m) the decryption weighted PSC in secure communication\". In this sentence \"m)\" should be corrected to \"m\"."}, "author_response": "Response to Reviewers’Comments\nMany thanks for the reviewers’ valuable comments and constructive suggestions\nto our manuscript. Revision has been made point-to-point to comply with the\nreviewer’s remarks as follows. The remarks of the reviewers are in black, our\nresponses are in blue, and the revised parts were marked in red color in revised\nmanuscript.\nReviewer#1:\nThe manuscript \"Perpendicular neuromorphic channels facilitate lateral inhibition for\ntactilelocation\" demonstrates a newstrategy to simulatebiomimeticoperating logic at\nthe device level for precise localization of touch points for applications. This is an\ninteresting work that is able to replicates the lateral inhibition mechanism in our skin.\nHowever, there are some questions need to well address, and I would like to\nrecommend acceptance of thiswork after majorrevisions.\nRESPONSE：\nThanks to the reviewer for all comments. The manuscript has been carefully\nrevised according to the comments to further improve our work. We hope that now\nthemanuscript and thesupporting information can meet your requirements.\n1. The originality and novelty of the work need to be further improved. The\nbioinspired tactile device has been broadly studied over the past few years. Numerous\nresearch papers of this topic have been published before. The authors had better\nhighlight one most novel breakthrough of the device. What is the most unique and\nimportant feature of the proposed devices? What is the most suitable application\nscenario for thisproposed device?\nRESPONSE：\nOur work demonstrated a cross-channel synaptic transistor (CST) that features\ntwo perpendicular channels. These channels have distinct source and drain electrodes\nbut share the same geometrical midpoint. The unique structure is created through\nelectro-hydrodynamic printing of indium zinc oxide (IZO) nanowires, which is\ndigitally controlled. When one channel is activated, it reduces the charge-carrier flow\nin the perpendicular channel. This effectively mimics lateral inhibition at the device\nlevel, creating a competitive charge-transport mechanism. Our CST applies to\nelectronic skin that precisely localize the touch point, which is simultaneously\nvisuallydisplayed.\nThe previously reported bioinspired tactile devices achieve tactile perception by\nconnecting tactile sensors with artificial synapsesR1-R5. Their working principle\ninvolves the artificial synapses converting the stimulation signals from tactile sensors\ninto postsynaptic current signals, which is analogous to the transmission of neural\nsignals. However, they do not involve the simulation of lateral inhibition between\nneurons.\nCompared with other bioinspired tactile devices, our tactile nervous system not\nonly realizes the perception of touch but also mimics the lateral inhibition function of\nthe human tactile system. Specifically, stimulation of a particular area of the skin\nleads to the inhibition of the excitability of neurons in the adjacent unstressed regions,\nthereby making the brain more sensitive to the stimulation of that area. By integrating\nCST with tactile sensors and a displayer, we can visually observe the simulation\nresults of the tactile lateral inhibition phenomenon. In this setup, the pressed area\ndeepened, while thesurrounding areas appear in lightercolors.\nOur tactile nervous system can serve as a processing unit for high-precision\ntactile perception systems. By simulating the phenomenon of tactile lateral inhibition,\nit enhances the intensity of tactile stimulus signals while attenuating the surrounding\nedge signals. This edge-enhancing effect improves the ability to identify the source of\ntactilestimuli.\nReferences\n(R1) Wang W. et al. Neuromorphic sensorimotor loop embodied by monolithically\nintegrated, low-voltage, soft e-skin. Science 380,735-742 (2023).\n(R2) Zhang Y. et al. A dual-organic-transistor-based tactile-perception system with\nsignal-processing functionality.Adv. Mater. 29,1606088(2017).\n(R3) Wang M. et al. 2D piezo-ferro-opto-electronic artificial synapse for bio-inspired\nmultimodal sensory integration. Adv. Mater. 2500049(2025).\n(R4) Wu M. et al. Stretchable, skin-conformable neuromorphic system for tactile\nsensory recognizingand encoding. InfoMat. 5,e12472 (2023).\n(R5) Kumar M. et al. An artificial piezotronic synapse for tactile perception. Nano\nEnergy 73,104756(2020).\n2.Thegate leakage current of both thetransfer characteristics is needed in Fig. S1.\nRESPONSE：\nThank you very much for the helpful comment. In the revised manuscript, we\nhave provided transfer characteristics of gate leakage current. Additional figure\n(Figure S1d) has been added in supporting information. In our device, the two\nchannels share a common top gate and exhibit symmetry. Therefore, we fixed V at\nDS2\nDS1 GS\nobserved a change in the drain current, which was significantly smaller than the\nchannel current, thereby having aminimal impact ontheoperating current.\nRevised parts in themanuscript:\nOn page 6 of the revised manuscript, the following discussion has been added (in\nred):\nSimilar phenomenon was simulated by CST. When the applied lateral inhibition\nvoltage (V increased, the transfer curves of inhibitory side showed potentiation\nDS2\ntrend, while output attenuation trend (Supplementary Fig. S1a-c). Under shared top\ngate, the gate current was significantly smaller than the channel current\n(Supplementary Fig. S1d).\nAdditionalfigure has beenadded in therevised supporting information (in red):\nFig. S1 | Device Schematic and transfer curves. a Schematic of CST with\ncross-IZO-channels, gated by the same ion gel sheet. Transfer curves of b output\nchannel, c inhibitory channel and d gate leakage current under V = 1 V with\nDS1\ndifferent initialV and V .\nGS DS2\n3.To further validate the stability and scalability of the device, additional experiments\nare needed to observe how the performance varies with the size of the active area or\nthedistance between theelectrodes.\nRESPONSE：\nThank you very much for your constructive comment. We have tested the\ntransfer characteristic curves of the device under different electrode distance (Figure\nR1). As the distance increased from 10 to 65 μm, peak currents of the output side\nwithout lateral inhibition decreased from 3025.15 to 869.2 μA. The results\ndemonstrate that the device maintains stability even when scaled down to smaller\ndimensions.\nFigure R1. The peak currents of the transfer characteristics under V = 1 V with\nDS1\ndifferent electrode distance.\n4.The properties of ion gel dielectric can be influenced by external environment, such\nas humidity, temperature, thus the operating environment of artificial tactile nervous\nsystem should introduce.\nRESPONSE：\nOur artificial tactile nervous system was operated in an indoor environment with\na temperature of approximately 22°C and a humidity of approximately 21%. To\nevaluate the impact of external environmental factors on the CST, we utilized an air\nhumidifier to simulate a range of humidity conditions and tested the electrical\nperformance of the device. As the ambient humidity increased from 20% to 60%,\nΔPSC of the output side and the inhibitory side without lateral inhibition induced by\n20 presynaptic spikes (4 V, 50 ms) decreased from 87.03 to 72.86 μAand from 65.49\nto 50.04 μA, respectively.When humidity was restored to 20% again,ΔPSC peak also\nrestored to 85.95 and 62.31 μA, implying recovery of the device to a certain degree\n(Figure S7). These results indicate that the device exhibits a certain degree of\nhumiditystability.\nRevised parts in themanuscript:\nOn page 8 of the revised manuscript, the following discussion has been added (in\nred):\nThe device was tested under different humidity from 20% to 60%, and back to 20%\n(Supplementary Fig. S7).\nAdditionalfigure has beenadded in therevised supporting information (in red):\nFig. S7 | Environmental stability. ΔPSC of the output side and the inhibitory side\nunderdifferent working humidityconditions.\n5. Please explain why ion gates are used. What are its advantages compared to other\ngate dielectrics? Are there any stability issues? Especially after arraying, as the\nresistance increases, thedevice performance degrades due toheat.\nRESPONSE：\nIon gates are primarily used because they can more directly simulate the\nmechanisms of biological neurons.The transmission of biological signals relies on the\nactivity of ions, and ion gates can effectively simulate this process through the\nmigration-accumulation process of ions in the ion gel, thereby achieving key synaptic\nbehaviors such as lateral inhibition. Moreover, the relaxation characteristics of ion\ngates also correspond to the memory characteristics of biological information, further\nenhancing theiradvantages in simulatingbiological neuronal behavior.\nIn addition to being more suitable for simulating bionic devices, ion gates also\nhave several other advantages compared with other gate dielectrics. Firstly, ion gates\ntypically operate at lower voltages, which helps to improve energy efficiency and\nreduce power consumption of electronic devices. Secondly, due to the high ion\nconcentration intheion gel, ion gates can provide higher capacitance, which enhances\nthe response and sensitivity to applied voltages of device, and is particularly\nbeneficial forapplications requiring high-sensitivitysignal processing.\nAlthough the movement of ions in the ion gel may lead to fatigue and drift\nphenomena, these issues can be mitigated through careful material selection and\ndevice design. In this work, the ion gel with extremely high stability is used, and the\nworking voltage is small, so theperformance and reliabilityof thedevice are ensured.\n6.Themechanism oflateral inhibition behavior shouldbe explained inmore details.\nRESPONSE：\nIn the revised manuscript, we have provided the mechanism of lateral inhibition\nbehavior.Additionalfigure (Figure S2)has been added in supporting information.\nRevised parts in themanuscript:\nThe following discussion and additional figure have been added in the revised\nsupportinginformation (in red):\nFig. S2 | Mechanism of lateral inhibition behavior. Schematic diagram of charge\ncarrier transport in the cross-channels of CST. a without and b with lateral-inhibition\nvoltage.\nNote: In the cross-structured IZO nanowire synaptic transistor, top-gate ion-induced\ncharge migration refers to the process where the ion gel gate causes ions to migrate to\nthe IZO channel region, altering the conductivity of channels.The lateral IZO channel\nserves as the output side, transmitting the postsynaptic current, while the longitudinal\nIZO channel acts as the inhibitory side, suppressing the output current of adjacent\nneurons, thereby simulating the lateral inhibition characteristics. When no bias is\napplied to the inhibitory side input terminal (D2), the output side (D1) is not affected\nby lateral inhibition.At this point, a constant bias is applied to D1 as the read voltage,\nand the potentials of the other three terminals (S1/D2/S2) are 0. The potential at the\nchannel intersection point N is determined by the voltage drop from D1 to N.\nAccording to circuit principles, the three terminals S1, D2, and S2 can all receive\nreversecurrent signals from D1 (Supplementary Fig. S2a).\nWhen a bias is applied to the D2 terminal, the D1 terminal will be affected by lateral\ninhibition.Although the same bias is applied to the D1 terminal as the reading voltage,\ndue to the influence of the D2 terminal bias, the potential at point N increases, the\nvoltage drops from the D1 terminal to point N decreases, and the current transmission\nat the D1 terminal is suppressed. Additionally, when the potential at point N is less\nthan the bias applied to the D2 terminal, the current transmission direction at the\nD2 terminal switches (Supplementary Fig. S2b).\n7. The authors do not clearly describe the working principle of the device and the\nspecific carrier transport mechanism. It is suggested that in addition to finite element\nsimulation, other characterization methods can be used to demonstrate the influence\nofthestructure oncarrier transport.\nRESPONSE：\nTo further elaborate on the working principle of the device and the specific\ncarrier transport mechanism, we conducted additional tests and supplemented the\nCurrent-voltage (I-V) contour maps from the output side and the inhibitory side\n(Figure S9). The results are consistent with the finite element simulation: In the\ncross-structured indium zinc oxide (IZO) nanowire synaptic transistor, top-gate\nion-induced charge migration refers to the process where the ion gel gate causes ions\nto migrate to the IZO channel region, thereby altering the conductivity of channel.As\nthe pulse applied to the ion gate increases, the conductivity of the entire IZO channel\nregion increases. The lateral IZO channel serves as the output side, transmitting the\npostsynaptic current, while the longitudinal IZO channel acts as the inhibitory side,\nsuppressing the output current of adjacent neurons, thereby simulating the lateral\ninhibition characteristic.\nWhen no bias is applied to the inhibitory side input terminal (D2) (V = 0 V),\nDS2\nthe output side (D1) is not affected by lateral inhibition.At this point, a constant V\nDS1\nof 1Vis applied to the D1 terminal as the read voltage, and the potentials of the other\nthree terminals (S1/D2/S2) are 0, resulting in the maximum current onthe output side.\nThe potential at the channel intersection point N is determined by the voltage drop\nfrom D1 to N. According to circuit principles, the three ports S1, D2, and S2 evenly\ndistribute the reverse current signals from D1. Therefore, the inhibitory side outputs a\nrelatively small negative current.\nWhen a bias is applied to the D2 terminal (V > 0 V), the D1 terminal is\nDS2\naffected bylateral inhibition.Although thesame bias (V = 1V) is applied to the D1\nDS1\nterminal as the read voltage, due to the influence of the D2 terminal bias, the potential\nat point N increases, the voltage drops from the D1 terminal to point N decreases, and\nthe current transmission at the D1 terminal is suppressed. Correspondingly, the\ncurrent outputfrom theinhibitory sidegradually increases.\nAs V further increases, the output side current continues to decrease, and\nDS2\nwhen V increases to a value greater than the potential at point N, the current\nDS2\ntransmission direction at the D2 terminal changes, and the inhibitory side output\ncurrent transitions from negativeto positive.\nRevised parts in themanuscript:\nOn page 8 of the revised manuscript, the following discussion has been added (in\nred):\nCurrent-voltage (I-V) contour map from output side and from inhibitory side\nelucidates the operation mechanism of the CST with IZO cross-channels\n(Supplementary Fig. S9).\nAdditionalfigure has beenadded in therevised supporting information (in red):\nFig. S9 | Current-voltage (I-V) contour map. Current-voltage (I-V) contour map\nfrom output sideand from inhibitory side.\n8. In the final application section, the authors are suggested to provide the photograph\nof the experimental setup for electrical testing, including specific test parameters,\ntest procedures, etc.\nRESPONSE：\nThank you very much for thehelpful comments. For the tactilenervous system, a\ncommercial matrix thin-film pressure sensor (IMM00092A, i-Motion Sensor) was\nemployed as the pressure sensing module. To control the drain voltage (V ) applied\nDS2\nto the synaptic transistor, the sensor was connected in series with a voltage-dividing\nresistor (R). The high and low voltage levels (V and V ) were set to 1.2V and 0.5 V,\ns H L\nrespectively.Abias voltage of output side (V ) of 0.5 V was applied to the drain of\nDS1\nCST, while a continuous pulses with V (4 V, 50 ms) were applied to the gate. In the\nGS\nabsenceof pressure, bias voltages applied to theinhibitory side(V )was set to 0.5V;\nDS2\nwhen pressure was applied (~10 N) to a specific sensor, V was increased to 1.0 V,\nDS2\nPSC on the inhibitory side increased, PSC on the output side decreased. The output\nsignals were processed through a current-to-voltage conversion circuit using an\noperational amplifier (LM358). This circuit transformed the postsynaptic currents of\noutput side and inhibitory side into voltage signals, which were then fed into a\nmicrocontroller (MCU,ATmega328P, Microchip). The microcontroller was interfaced\nwith a USB-to-serial converter (FT232RL) to convert USB signals into universal\nasynchronous receiver/transmitter (UART) serial signals, enabling communication\nwith external devices. The microcontroller was used for threshold determination of\nthe voltage signals and control of a liquid crystal display screen (ILI9431).\nCurrent-limiting resistors (10 kΩ) were connected in series between the\nmicrocontroller and the interface pins of the display screen. The programming utilized\nthe \"Adafruit_ILI9341\" library for pin definitions. Athreshold encoding strategy was\nimplemented, where the obtained enhancement and inhibition signals were compared\nwith their respective set thresholds. When the value of the enhancement signal\nexceeded the enhancement threshold, the color in the pressure center region on the\ndisplay was deepened. Conversely, when the value of the inhibition signal fell below\nthe inhibition threshold, the color of the surrounding area became lighter. Additional\nexplanationsondetailed experimentshave been added in therevised manuscript.\nRevised parts in themanuscript:\nOn page 11 of the revised manuscript, the following discussion has been added\n(in red):\nFor this purpose, an artificial tactile nervous system was fabricated to achieve\nreal-time perception and signal processing of external stimuli of different locations\nunder lateral inhibition, and to execute visual sensing of the stimulation location\nthrough display unit(Figure 5b;Supplementary Fig. S16).\nOn page 13 of the revised manuscript, the experimental setup for electrical\ntestinghas beenadded (inred):\nFabrication of artificial tactile nervous system. A commercial matrix thin-film\npressure sensor (IMM00092A, i-Motion Sensor) was employed as the pressure\nsensing module. To control the drain voltage (V ) applied to the synaptic transistor,\nDS2\nthe sensor was connected in series with a voltage-dividing resistor (R). The output\ns\ncurrents were processed through a current-to-voltage conversion circuit using an\noperational amplifier (LM358), and then fed into a microcontroller (MCU,\nATmega328P, Microchip) for threshold determination of the voltage signals and\ncontrol theliquid crystal display screen (ILI9431).\nAdditionalfigure has beenadded in therevised supporting information (in red):\nFig. S16 | Tactile nervous system. a Photograph and b circuit schematic diagram of\ntactilenervous system.\n9. In Figure 5b, the authors used this system to capture neural-like tactile signals and\nthen compared them in a database. How would the results be different if the signals\nwere obtained directly from the PVDF sensor and compared in a corresponding\ndatabase?Would itbe easier to identifyneural-like signals than PVDFoutput signals?\nRESPONSE：\nIn our tactile nervous system, pressure signals acting at different locations are\ncaptured and converted into electrical signals by the corresponding pressure-sensitive\nunits, which serve as bias voltages applied to the inhibitory side of CST. Therefore,\nwhen a specific location of the sensor is pressed, the pressure signal is translated into\na deeper color intensity at the corresponding region on the display, while the\nsurrounding edge areas exhibit a lighter color. This enhanced color contrast\neffectively mimics the phenomenon of lateral inhibition in tactile perception. In\ncontrast, utilizing only PVDF sensors and a display for tactile localization would fail\ntocapture theinformation regarding theedge signals.\nTofurther verify therole ofthelateral inhibitory characteristics ofCSTinpattern\nrecognition, we conducted imaging demonstrations using image systems with and\nwithout CST, and extracted the gray weights of the same region for comparative\nanalysis. In the image system without CST, the stimulated sensor only output its own\nsignal, and the adjacent sensors are not inhibited, resulting in a less pronounced signal\noutput (figure S18a). In contrast, in the image system with CST, when a sensor is\nstimulated, the adjacent output singles are inhibited, which not only drives the change\nin the output signals of a larger range but also makes the signal amplitude of the\nstimulated sensing unit more prominent (figure S18b). This mechanism helps to\nseparate the continuous surface of an object from the background, aiding humans in\nmoreaccurately localizingtouch.\nRevised parts in themanuscript:\nOn page 12 of the revised manuscript, the following discussion has been added\n(in red):\nThis lateral inhibition mechanism facilitates more accurate touch localization.\n(Supplementary Fig. S18).\nAdditionalfigure has beenadded in therevised supporting information (in red):\nFig. S18 | Imaging demonstration. a Imaging demonstration using image systems\nand extracted gray weights from the imaging demonstration without CST. b Imaging\ndemonstration using image systems and extracted gray weights from the imaging\ndemonstration with CST.\n10. The effect of different frequencies and pressures on the output signal should be\nfurther explained. If both the amplitude and frequency of the applied force affect the\noutput signal (Fig. 5c), it is important to clarify how to decouple the output signal to\naccuratelydetermine theamplitudeand frequency oftheinput force.\nRESPONSE：\nIn our tactile nervous system, pressure stimuli are detected by pressure-sensitive\nunits and converted into electrical signals acting as bias voltages onthe inhibitory side\nof CST. Given the extended duration of the applied pressure, the system has sufficient\ntime to respond to frequency changes, making the influence of pressure frequency on\ntheoutput signal clearly observable, as shown in Figure R2.When pressure is applied,\nthe output current on the inhibitory side increases regularly, while the output current\non the measurement side decreases correspondingly. This indicates that pressure\nfrequency canbeconsidered independently.\nWhen the magnitude of the pressure applied to the pressure-sensitive unit\nchanged from 10 N to 3 N, the drain voltage decreased from ~1 V to ~0.68 V. The\noutput signal on the inhibitory side decreased from 66.81 μA to 50.73 μA, while the\nsignal on the output side increased from 26.09 μAto 34.63 μA(Figure R3). We made\na calibrating curve forΔPSCs variation at different pressure (Figure S17). In this way,\ntheeffects ofpressure can bedistinguished.\nFigure R2. Drain voltage and PSC of CST triggered by different pressing frequencies\nofthepressure sensor.\nFigure R3. Drain voltage and PSC of CST triggered by different pressing magnitudes\nofthepressure sensor.\nRevised parts in themanuscript:\nOn page 12 of the revised manuscript, the following discussion has been added\n(in red):\nIn addition, calibration curves of ΔPSCs under various pressures were\nconstructed todiscern the impact ofpressure magnitude(Figure S17).\nAdditionalfigure has beenadded in therevised supporting information (in red):\nFig. S17|Effects of pressures. ΔPSCfittingcurve underpressure variation.\n11.Couldthe authordemonstrate thestabilityof thesensorover aperiod oftime?\nRESPONSE：\nWe performed repetitive pressing tests on the pressure sensor.After 5000 cycles\nofrepeated pressing, theoutput voltage ofthe device exhibited nosignificant decrease,\nindicating thegood stability ofthe pressure sensor(FigureR4).\nFigure R4.Theoutput voltage of thesensorafter 5000cycles ofrepeated pressing.\n12. Did the authors prepare an array of devices or just a group of devices? If it is an\narray,howisthe homogeneity and stabilityof thedevices guaranteed?\nResponse:\nThank you for your constructive suggestions. The devices we tested consist of a\ngroup of devices, each containing an array of cross-channels. We performed stability\ntests using 10 such devices and plotted the EPSC values as error bars to illustrate the\nhomogeneity and stabilityof themeasurements (Figure R5).\nFigure R5.EPSC values oftheoutput sideand theinhibitory sideof ten devices.\nReviewer#2:\nIn this work, the authors report cross-channel synaptic transistors (CST) based on\nperpendicularly aligned indium zinc oxide nanowire channels to emulate lateral\ninhibition for tactile localization. This unique architecture enables the development of\na lateral-inhibition-encryption (LIE) key, that can encrypt Morse code and achieve\n100% accurate decryption across all letters and encryption types. Furthermore, the\ndevice facilitates precise touch-point localization with simultaneous visual display.\nWhile the work is intriguing, several important issues need to be addressed. The\ncomments are as follows:\nRESPONSE：\nThanks to the reviewer for all comments. The manuscript has been carefully\nrevised according to the comments. We also provided more experimental details in\nthe revised manuscript. We believe that the revised manuscript and the supporting\ninformation have been improved.\n1. The authors mentioned that the lateral inhibition of the CST is achieved through a\ncompetitive charge-transport mechanism, where excitation of one channel attenuates\ncharge-carrier transport in the perpendicular channel. Therefore, it is crucial to\nprovide detailed descriptions and corresponding schematic diagrams of this\ncharge-transport mechanism. This should include the underlying physical principles,\nthe specific roles of mobile ions in the ion gel layer, the interaction between channels,\nand other relevant factors.\nRESPONSE：\nThe lateral inhibition of the cross-channel synaptic transistor (CST) is achieved\nthrough a competitive charge-transport mechanism, where the excitation of one\nchannel attenuates the charge-carrier transport in the perpendicular channel.\nAdditionally, the movement of ions in the ion gel layer also plays a crucial role in\nregulating charge transport in theIZO channels.\nWhen a voltage is applied to the gate, it causes ions in the ion gel to migrate\ntowards the channel region, changing the number of charge carriers in the channel and\nthus affecting its conductivity. The specific role of mobile ions in the ion gel layer is\nto induce charge migration and accumulation in the IZO channels, thereby regulating\ncurrent flow.\nThe interaction between the two channels is as follows: 1) The lateral IZO\nchannel serves as the output side, transmitting the postsynaptic current, while the\nlongitudinal IZO channel acts as the inhibitory side, suppressing the output current of\nadjacent neurons, thereby simulating the lateral inhibition characteristic. When no\nbias is applied to the inhibitory side input terminal (D2), the output side (D1) is not\naffected by lateral inhibition. At this point, a constant bias is applied to D1 as the read\nvoltage, and the potentials of the other three terminals (S1/D2/S2) are 0. The potential\nat the channel intersection point N is determined by the voltage drop from D1 to N.\nAccording to circuit principles, the three terminals S1, D2, and S2 can all receive\nreverse current signals from D1. 2) When a bias is applied to the D2 terminal, the D1\nterminal will be affected by lateral inhibition. Although the same bias is applied tothe\nD1 terminal as the read voltage, due to the influence of the D2 terminal bias, the\npotential at point N increases, the voltage drops from the D1 terminal to point N\ndecreases, and the current transmission at the D1 terminal is suppressed. 3)\nAdditionally, when the potential at point N is less than the bias applied to the D2\nterminal, thecurrent transmission direction at theD2 terminal switches.\nIn the revised manuscript, we have provided the mechanism of lateral inhibition\nbehavior.Additionalfigure (Figure S2)has been added in supporting information.\nRevised parts in themanuscript:\nThe following discussion and additional figure have been added in the revised\nsupportinginformation (in red):\nIn the cross-structured IZO nanowire synaptic transistor, top-gate ion-induced\ncharge migration refers to the process where the ion gel gate causes ions to migrate to\nthe IZO channel region, altering the conductivity of channels.The lateral IZO channel\nserves as the output side, transmitting the postsynaptic current, while the longitudinal\nIZO channel acts as the inhibitory side, suppressing the output current of adjacent\nneurons, thereby simulating the lateral inhibition characteristic. When no bias is\napplied to the inhibitory side input terminal (D2), the output side (D1) is not affected\nby lateral inhibition.At this point, a constant bias is applied to D1 as the read voltage,\nand the potentials of the other three terminals (S1/D2/S2) are 0. The potential at the\nchannel intersection point N is determined by the voltage drop from D1 to N.\nAccording to circuit principles, the three terminals S1, D2, and S2 can all receive\nreversecurrent signals from D1 (Supplementary Fig. S2a).\nWhen a bias is applied to the D2 terminal, the D1 terminal will be affected by\nlateral inhibition. Although the same bias is applied to the D1 terminal as the read\nvoltage, due to the influence of the D2 terminal bias, thepotential at point Nincreases,\nthe voltage drops from the D1 terminal to point N decreases, and the current\ntransmission at the D1 terminal is suppressed. Additionally, when the potential at\npoint N is less than the bias applied to the D2 terminal, the current transmission\ndirection at the D2 terminal switches (Supplementary Fig. S2b).\nFig. S2 | Mechanism of lateral inhibition behavior. Schematic diagram of carrier\ntransport in the cross-channels of CST. a without and b with\nlateral-inhibition-voltage.\n2. The authors demonstrated the application of the CST to encrypt and decrypt Morse\ncode. However, according to Fig. 3b (left panel), the postsynaptic currents on the\noutput side exhibit inherent short-term plasticity, which could be directly used for\nencryption and decryption of Morse code. Therefore, the authors should provide the\nadvantages of using the LIE key for this process. Additionally, a comparison of\nclassificationaccuracy between thecases with and without LIE processing is required.\nRESPONSE：\nThe postsynaptic currents on the output side do indeed possess inherent\nshort-term plasticity, which can be directly utilized for Morse code encoding.\nHowever, this only represents normal Morse code encoding without encryption.\nAlthough the encoding accuracy can reach 100%, it does not provide any encryption\nfunctionality. On theother hand, the lateral inhibition encryption (LIE) key introduces\nan additional layer of security by modulating the bias voltage on the inhibitory side.\nThis modulation generates encrypted signals that are unrecognizable without the key.\nFor instance, the letter \"J\" can be transformed into 8 different encrypted signals by\nencrypting the \"dash\" signals in various positions. Without the LIE key, the\nrecognition rate of the encrypted Morse code for 26 letters is only 44%. However, due\nto the linear relationship between the inhibitory-side and output-side currents, using\nthe LIE key can increase the recognition rate to 100% after decryption, allowing for\ncomplete reconstruction of the encoded signals. Therefore, the LIE key significantly\nenhances thesecurity and confidentiality of communication.\n3. Since the theme of this manuscript highlights perpendicular neuromorphic channels\nfacilitate lateral inhibition for tactile localization, it is essential to demonstrate the\nrelationship between theencryption/decryption of Morsecode and tactile location.\nRESPONSE：\nThe encryption and decryption of Morse code and the determination of tactile\nlocation represent two distinct applications that we have developed leveraging CST.\nTo substantiate the interrelation between these two applications, we have integrated\ntactile sensors to ascertain the correlation between Morse code cryptographic\nprocesses and haptic feedback. The phrases “Nankai” was randomly encrypted byLIE\nmethod. When the sensitive unit was randomly pressed using a force of 10 N, the\nvoltage of the inhibitory side of the CST increases, peak values of the PSC of the\ninhibitory side (the encryption key) increase to ~17 μA, PSC of the output side (the\nencrypted PSC) decrease to ~50 μA, each letter was randomly encrypted to generate\nan encrypted signal: \"IINKII\". Using decryption process to achieve lossless\nbacktracking of the original contents of the encrypted “NANKAI” signal. In the\nrevised manuscript, we have included a description of the relationship between\npressure and the encryption/decryption of Morse code.Additional figure (Figure S15)\nhas been added insupporting information.\nRevised parts in themanuscript:\nOn page 10 of the revised manuscript, the following discussion has been added\n(in red):\nIn addition, employing a 10 N pressure as an encryption key and utilizing the\nabove described decryption procedure, the phrase \"Nankai\" was encrypted and\ndecrypted effectively (Supplementary Fig. S15).\nAdditionalfigure has beenadded in therevised supporting information (in red):\nFig. S15 | Pressure coding of “Nankai”. Pressure coding of phrase “Nankai” from\nthe inhibitory side as the encryption key, the output side as the encrypted output PSC,\nand thedecryption weighted PSCin secure communication.\n4. Line 279, 280: \"The leakage current of the inhibitory side of the CST increases\nfrom 0.5to 1V.\"There is a mismatch between the current and its unit in this sentence.\nTheauthors shouldcorrect this.\nRESPONSE：\nThank you for your valuable comments. We regret our oversight. In the revised\nmanuscript, we have rectified the mistake and conducted a thorough review of the\nentiretext.\nRevised parts in themanuscript:\nIn line279,thefollowing discussion has been revised (inred):\nAnalogously, for our tactile nervous system, when the different position units of the\nsensor are pressed and pressure is applied up to 10 N, the bias voltage of the\ninhibitory side of the CST increases from 0.5 to 1 V, peak values of the PSC of the\noutput side and inhibitory side changes from 45 μA, controlling the change of the\ncolorof thedisplay unit.\n5. The authors have provided limited information regarding the pressure sensor and\ndisplay modules. To enhance the clarity of the manuscript, additional details are\nneeded, including the device structure, fabrication methods, a detailed circuit\nschematic diagram, and photographs ofthe actual system.\nRESPONSE：\nThank you very much for thehelpful comments. For the tactilenervous system, a\ncommercial matrix thin-film pressure sensor (IMM00092A, i-Motion Sensor) was\nemployed as the pressure sensing module. To control the drain voltage (V ) applied\nDS2\nto the synaptic transistor, the sensor was connected in series with a voltage-dividing\nresistor (R). The high and low voltage levels (V and V ) were set to 1.2V and 0.5 V,\ns H L\nrespectively.Abias voltage of output side (V ) of 0.5 V was applied to the drain of\nDS1\nCST, while a continuous pulses with V (4 V, 50 ms) were applied to the gate. In the\nGS\nabsenceof pressure, bias voltages applied to theinhibitory side(V )was set to 0.5V;\nDS2\nwhen pressure was applied (~10 N) to a specific sensor, V was increased to 1.0 V,\nDS2\nPSC on the inhibitory side increased, PSC on the output side decreased. The output\nsignals were processed through a current-to-voltage conversion circuit using an\noperational amplifier (LM358). This circuit transformed the postsynaptic currents of\noutput side and inhibitory side into voltage signals, which were then fed into a\nmicrocontroller (MCU,ATmega328P, Microchip). The microcontroller was interfaced\nwith a USB-to-serial converter (FT232RL) to convert USB signals into universal\nasynchronous receiver/transmitter (UART) serial signals, enabling communication\nwith external devices. The microcontroller was used for threshold determination of\nthe voltage signals and control of a liquid crystal display screen (ILI9431).\nCurrent-limiting resistors (10 kΩ) were connected in series between the\nmicrocontroller and the interface pins of the display screen. The programming utilized\nthe \"Adafruit_ILI9341\" library for pin definitions. Athreshold encoding strategy was\nimplemented, where the obtained enhancement and inhibition signals were compared\nwith their respective set thresholds. When the value of the enhancement signal\nexceeded the enhancement threshold, the color in the pressure center region on the\ndisplay was deepened. Conversely, when the value of the inhibition signal fell below\nthe inhibition threshold, the color of the surrounding area became lighter. Additional\nexplanationsondetailed experimentshave been added in therevised manuscript.\nRevised parts in themanuscript:\nOn page 11 of the revised manuscript, the following discussion has been added\n(in red):\nFor this purpose, an artificial tactile nervous system was fabricated to achieve\nreal-time perception and signal processing of external stimuli of different locations\nunder lateral inhibition, and to execute visual sensing of the stimulation location\nthrough display unit(Figure 5b;Supplementary Fig. S16).\nOn page 13 of the revised manuscript, the experimental setup for electrical\ntestinghas beenadded (inred):\nFabrication of artificial tactile nervous system. A commercial matrix thin-film\npressure sensor (IMM00092A, i-Motion Sensor) was employed as the pressure\nsensing module. To control the drain voltage (V ) applied to the synaptic transistor,\nDS2\nthe sensor was connected in series with a voltage-dividing resistor (R). The output\ns\ncurrents were processed through a current-to-voltage conversion circuit using an\noperational amplifier (LM358), and then fed into a microcontroller (MCU,\nATmega328P, Microchip) for threshold determination of the voltage signals and\ncontrol theliquid crystal display screen (ILI9431).\nAdditionalfigure has beenadded in therevised supporting information (in red):\nFig. S16 | Tactile nervous system. a Photograph and b circuit schematic diagram of\ntactilenervous system.\n6.According to Fig. 5b, each pixel of the sensor unit is connected to a 3×3 pixel array\non the display to emulate lateral inhibition, which increases circuit complexity and\nenergy consumption. However,it seems that connecting each sensor pixel directly to a\nsingle display pixel through the inhibitory side, without involving the output side,\ncould also achieve accurate pressure localization. In this scenario, only the transistors\ncorresponding to the stimulated pixels in the pressure sensor would increase their\ncurrent, deepening the color of the corresponding display pixels. Therefore, the\nauthors should provide comparative experiments to validate the advantages of their\nartificial tactile nervous system and demonstrate whether the contrast between\nstimulatedand non-stimulated pixels canbeimproved usingtheir design.\nRESPONSE：\nIn our tactile nervous system, pressure signals acting at different locations are\ncaptured and converted into electrical signals by the corresponding pressure-sensitive\nunits, which serve as bias voltages applied to the inhibitory side of CST. Therefore,\nwhen a specific location of the sensor is pressed, the pressure signal is translated into\na deeper color intensity at the corresponding region on the display, while the\nsurrounding edge areas exhibit a lighter color. This enhanced color contrast\neffectively mimics the phenomenon of lateral inhibition in tactile perception. In\ncontrast, utilizing only pressure sensors, single artificial synaptic device and a display\nfor tactile localization would fail to capture the information regarding the edge\nsignals.\nTofurther verify therole ofthelateral inhibitory characteristics ofCSTinpattern\nrecognition, we conducted imaging demonstrations using image systems with and\nwithout CST, and extracted the gray weights of the same region for comparative\nanalysis. In the image system without CST, the stimulated sensor only output its own\nsignal, and the adjacent sensors are not inhibited, resulting in a less pronounced signal\noutput (figure S18a). In contrast, in the image system with CST, when a sensor is\nstimulated, the adjacent output singles are inhibited, which not only drives the change\nin the output signals of a larger range but also makes the signal amplitude of the\nstimulated sensing unit more prominent (figure S18b). This mechanism helps to\nseparate the continuous surface of an object from the background, aiding humans in\nmoreaccurately localizingtouch.\nRevised parts in themanuscript:\nOn page 12 of the revised manuscript, the following discussion has been added\n(in red):\nThis lateral inhibition mechanism facilitates more accurate touch localization.\n(Supplementary Fig. S18).\nAdditionalfigure has beenadded in therevised supporting information (in red):\nFig. S18 | Imaging demonstration. a Imaging demonstration using image systems\nand extracted gray weights from the imaging demonstration without CST. b Imaging\ndemonstration using image systems and extracted gray weights from the imaging\ndemonstration with CST.\n7. Line 497: \"and m) the decryption weighted PSC in secure communication\". In this\nsentence \"m)\" shouldbe corrected to\"m\".\nRESPONSE：\nThanks again for your valuable advice. We apologize for our carelessness. In the\nrevised manuscript, we corrected the error and further checked thefull textin detail.\nRevised parts in themanuscript:\nIn line496,thefollowing discussion has been revised (inred):\nFig. 3 | Electrical properties of the five-terminal cross-channel device. a\nSchematic diagram of tactile lateral inhibition. PSC from b the output side and c the\ninhibitory side triggered by 20 consecutive presynaptic spikes (4 V, 50 ms) without\nand with lateral inhibition. d PSC peaks from the output side of CST triggered by 20\nconsecutive presynaptic spikes (4 V, 50 ms) under different inhibitory voltages.\nHistograms of PSC from e the output side and f the inhibitory side triggered by\ndifferent frequency of presynaptic spikes under different inhibitory voltages. Electric\nfield and current distributions in IZO-NWs under V = g 0, h 0.4, i 0.7, and j 1 V at\nDS2\nthe simulation time of 2 s. PSC outputs from k the inhibitory side, l the output side,\nand mthe decryption weighted PSC in secure communication."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The issues raised by the reviewers have been addressed. I believe the manuscript can be published in its present form.", "reviewer_2": "The authors have provided a comprehensive and largely satisfactory rebuttal to the comments raised by the reviewer. All major scientific concerns—particularly those regarding the charge transport mechanism, encryption functionality, system-level integration, and visualization strategy—have been addressed with additional explanations, figures, and supporting experiments. Nevertheless, there remain several areas where further clarification and enhancement could strengthen the manuscript and provide greater confidence in its scientific rigor and practical relevance:\n1. Mechanistic Depth and Physical Modeling: While the lateral inhibition mechanism is described qualitatively with supporting schematics (Fig. S2), the physical insight into inter-channel electrostatic coupling and carrier transport remains somewhat superficial. The addition of finite element simulations or electrostatic potential maps illustrating field interactions at the channel intersection would substantiate the claimed mechanism and mitigate ambiguity regarding device physics.\n2. Quantitative Benchmarking: The manuscript would benefit from comparative benchmarking against existing lateral inhibition-based or tactile neuromorphic systems. Metrics such as response time, spatial resolution, contrast enhancement ratio, or energy consumption should be briefly compared to prior art to contextualize the novelty and performance of the proposed CST-based system.\n3. Scalability and Fabrication Considerations: Although group-level reproducibility was reported (Fig. R5), the authors provide limited discussion on the scalability of the cross-channel printing process, device uniformity, and system-level yield. Such information is vital to evaluate the feasibility of practical deployment, particularly in array-scale tactile sensors or neuromorphic interfaces.\n4. Encryption Robustness and Device Variability: The LIE-based encryption/decryption strategy assumes consistent linear correlations between output and inhibitory currents. However, the rebuttal lacks discussion on the impact of device non-idealities (e.g., ion gel hysteresis, variability, noise) on encryption fidelity. An assessment of robustness or compensatory strategies (e.g., calibration) would be helpful.\n5. Integration of Supplementary Visuals and Circuit Clarity: The supplementary figures, while informative, would benefit from better annotation and clearer integration into the main text. Schematic illustrations (e.g., Fig. S2) could be enhanced with color-coded potential paths and field lines to assist readers in visualizing complex multi-terminal operation.\n6. Language and Technical Precision: Some technical descriptions, particularly regarding voltage configurations and circuit behavior, could be more rigorously phrased using formal notation and unambiguous terminology. This would ensure precision, especially for readers unfamiliar with unconventional device geometries."}, "author_response": "Response to Reviewers’Comments\nMany thanks for the reviewers’ valuable comments and constructive suggestions\nto our manuscript. Revision has been made point-to-point to comply with the reviewer’s\nremarks as follows. The remarks of the reviewers are in black, our responses are in blue,\nand the revised parts were marked in red color in revised manuscript.\nReviewer #1:\nThe issues raised by the reviewers have been addressed. I believe the manuscript can\nbepublished in itspresent form.\nRESPONSE：\nWe would like to express our heartfelt gratitude for the time, effort, and careful\nattention you have devoted to reviewing our manuscript.Your insightful feedback and\nconsistent support throughout the entire review process have had an immeasurable\nimpact on the quality of this work. We are truly thankful for the significant role you\nhave played in shaping the manuscript and helping it reach its current level. We\ndeeply appreciate your guidance with ourwork.\nReviewer #2:\nThe authors have provided a comprehensive and largely satisfactory rebuttal to the\ncomments raised by the reviewer. All major scientific concerns—particularly those\nregarding the charge transport mechanism, encryption functionality, system-level\nintegration, and visualization strategy — have been addressed with additional\nexplanations, figures, and supporting experiments. Nevertheless, there remain several\nareas where further clarification and enhancement could strengthen the manuscript\nand provide greater confidence in itsscientific rigor andpractical relevance:\nRESPONSE：\nWesincerely appreciate the reviewer’s positive feedback and acknowledgment of\nour efforts to address the previous concerns. We are glad that the additional\nexplanations and demonstrations have made the work more complete and systematic.\nBeloware ourpoint-by-point responses toyour questions.\n1. Mechanistic Depth and Physical Modeling: While the lateral inhibition mechanism\nis described qualitatively with supporting schematics (Fig. S2), the physical insight\ninto inter-channel electrostatic coupling and carrier transport remains somewhat\nsuperficial. The addition of finite element simulations or electrostatic potential maps\nillustrating field interactions at the channel intersection would substantiate the\nclaimed mechanism and mitigate ambiguity regarding device physics.\nRESPONSE：\nWesincerely thank the reviewer for the insightful comments, which help a lot on\nimproving our manuscript. We supplemented the physical analysis of electrostatic\ncoupling and carrier transport from the vector field (electric field) and scalar field\n(electric potential) using finite element analysis models (Figure S3). We again thank\nthe reviewer for his/her insightful suggestions to enhance the quality of our\nmanuscript.\nRevised parts in themanuscript:\nOn page 7 of the revised manuscript, the experimental setup for electrical testing\nhas been added (in red):\nSimilar phenomenon was simulated by CST. When the applied lateral inhibition\nvoltage (V increased, the transfer curves of inhibitory side showed potentiation\nDS2\ntrend, while output attenuation trend (Supplementary Fig. S1a-c; Fig. S2). Under\nshared top gate, the gate current was significantly smaller than the channel current\n(Supplementary Fig. S1d). To elucidate the lateral-inhibition mechanism,\nfinite-element simulations of the electric-field (Supplementary Fig. S3a) and potential\ndistributions (Supplementary Fig. S3b) were performed under varied V , confirming\nDS2\nthe progressive suppression of the output side and the eventual reversal of the\ninhibitorychannel current.\nThe following discussion and additional figure have been added in the revised\nsupportinginformation (in red):\nFig. S3 | Analysis of electric field and electric potential. Physical analysis in IZO\ncross channel of a vector field (electric field) and b scalar field (electric potential)\nunderV =0,0.4,0.7,and 1V.\nDS2\nNote: As the potential at the inhibitory side input terminal (D ) gradually\n2\nincreases, the electric field effect from the D terminal to the channel intersection\n2\npoint N is enhanced. The potential enhance at D terminal elevates the potential at N\n2\npoint from 0V to 0.5V, causing more charges to flow from N to D under the effect of\n2\nelectrostatic coupling (Supplementary Fig. S3a). Due to the reduced voltage drop\nbetween the output side (D ) end and the N end, the electrostatic coupling effect is\n1\nweakened. This will also weaken the electric field effect from D to N, reduce the\n1\ntransport of charge carriers from D to N (Supplementary Fig. S3b). The electric field\n1\nstrength at the output side (from D to N) gets weaker, with the electric field at the\n1\ninhibitory side (from D to N) gets increased. When the potential applied at the D\n2 2\nterminal is higher than that at point N, it causes a reversal in the direction of the\nelectric field. This leads to a switch in the direction of the inhibitory side current.\nTherefore, the current in cross-structured nanowires device exhibits selectivity\nbetween theoutput sideand theinhibition sideunder V .\nDS2\n2. Quantitative Benchmarking: The manuscript would benefit from comparative\nbenchmarking against existing lateral inhibition-based or tactile neuromorphic\nsystems. Metrics such as response time, spatial resolution, contrast enhancement ratio,\nor energy consumption should be briefly compared to prior art to contextualize the\nnovelty and performance ofthe proposed CST-based system.\nRESPONSE：\nThank you very much for your constructive comment. Our work demonstrated\nthe fabrication of a artificial tactile nervous system based on digitally aligned\ncross-channel synaptic transistor (CST), which effectively mimics lateral inhibition at\nthe device level. By integrating this device into the artificial tactile nervous system,\nthe positioning of the tactile sensation was achieved and its location was visualized\nand displayed onthe displayscreen.\nMost studies of lateral inhibition rely on algorithmic implementations in spiking\nneural networks (SNNs). In contrast to conventional neuromorphic systems that\nrequire externally applied artificial electrical pulses, our CST achieves lateral\ninhibition behavior by selectively exciting one channel to suppress its orthogonal\nchannel, thereby simulating in principle the inhibitory effect of a central neuron on its\nsurrounding neurons after stimulation.\nWe evaluated the response time, spatial resolution, energy consumption of CST\nand the contrast enhancement ratio of the displayer. The response time of output side\nwas measured with the rise period (t ) of 39.9 ms and the drop period (t ) of 656.8\non off\nms, while inhibitory side was measured with t of 42.2 ms and t of 43.3 ms (Figure\non off\nS14). The t is higher than t is a result of the device exhibiting synaptic transistor\noff on\nbehavior. Neuromorphic systems need to integrate sensing and computing to achieve\nin-sensor computing. To achieve this, artificial synapse devices need to have a\ncontrollable synapticplasticity,which is used to emulate the memory retention timeof\nbiological synapses for neuromorphic computing. Therefore, unlike other sensor\ndevices, response timeis not used as an evaluation criterion in thisresearch field.\nIn addition, when under low operating voltage of 0.01 mV, CST showed a\nrelatively low energy consumption E = AIW, where Ais driving voltage, I is channel\ncurrent, and W is duration of pre-synaptic spike. Without lateral inhibition, the\nminimal E of output side was ~0.108 fJ per synaptic event, with A = 0.01 mV, I =\n0.215 nA, and W = 50 ms (Figure S15a). We also verified spike-number-dependent\nplasticity(SNDP) ofCSTunderlowoperating voltage of 0.01mV(Figure S15b).\nWhen applying a continuous sequence of presynaptic spikes to CST, the stimulus\nenhancement from the inhibitory side with the attenuation from the output side\nsignificantly improves the ratio between EPSC.Whenunder V of0.2V, EPSCpeak\nDS2\nratio reached 4.40, which contributes to the differential processing between pixels\n(Figure S16).\nBased on precise printing and high alignment characteristics of\nelectrohydrodynamic nanowire printing (e-NWP) process, the array-based CST\nachieving a device pitch of180μm(Figure S18).\nTo clearly show the advantages of our systems, we compared our results with\nother reported lateral inhibition-based neuromorphic systems in the revised\nmanuscript (Table S1).\nRevised parts in themanuscript:\nOnpage 9,thefollowing discussionhas been revised (in red):\nThe response speed of output side and inhibitory side was measured, showing a\nrise period (t ) of 39.9 ms, 42.2 ms and a drop period (t ) of 656.8 ms, 43.3 ms,\non off\nrespectively (Supplementary Fig. S14). The extended t is a result of the synaptic\noff\nplasticity in the device, which is essential for in-sensor information processing.\nEnergy consumption of the device is evaluated as E = AIW, where A is driving\nvoltage, I is channel current, and W is duration of pre-synaptic spike. For a single\nchannel, the minimal E of output side was ~0.108 fJ per synaptic event, with A = 0.01\nmV, I = 0.215 nA, and W = 50 ms (Supplementary Fig. S15a).\nSpike-number-dependent plasticity (SNDP) was also emulated using consecutive\npresynaptic spikes (Supplementary Fig. S15b). Applying a consecutive sequence of\npresynaptic spikes to CST, the stimulus enhancement from the inhibitory side and the\nattenuation from the output side (Supplementary Fig. S16) significantly improves the\nratio between EPSC, which contributes to the differential processing between pixels.\nThe wafer-level device fabrication process to verify the scalability of the\ncross-channel printing process (Supplementary Fig. S17). The nanowire array-based\nCST had a device pitch of 180 μm (Supplementary Fig. S18).The electrical properties\nof the CST are compared with state-of-art lateral inhibition-based neuromorphic\nsystems (TableS1)22,23,52-55.\nAdditionalfigure has beenadded in therevised supporting information (in red):\nFig. S14 | Response time. EPSC of a output side and b inhibitory side triggered by 1\npre-synapticspike(4V,50ms) under V =1V,V =0V.\nDS1 DS2\nFig. S15 | Energy consumption. a EPSC of output side triggered by one pre-synaptic\nspike (0.1 V, 50 ms) under V = 0.01 mV. b SNDPof output side under V = 0.01\nDS1 DS1\nmV.\nFig. S16 | EPSC peak ratio. PSC peaks from the output side and the inhibitory side\nof CST triggered by 20 consecutive presynaptic spikes (4 V, 50 ms) under different\ninhibitoryvoltages.\nFig. S18|OMimage. OM image ofthe cross-channel devicearrays.\nAdditionaltable has been added in therevised supporting information (inred):\nTable S1. Comparison of recent works relating to lateral inhibition-based\nneuromorphic systems\nContrast\nSensory Lateralinhibition Energy\nChanneltype enhancement Ref.\nmodality emulation consumption\nratio\nV frequency\nG\nolfactory B-dopedSisingle-channel 165μW / [23]\nmodulation\nlightpotentiation conductance\nvisual IGZOframesingle-channel ~40nJ [52]\nandnaturaldecay ratio:3.81\nvoltagespike relative\nZnPc/MoS /h-BN/graphene\n2\nvisual waveform ~55pJ inhibitory [53]\nfilmsingle-channel\nregulation weights:0.25\nmain/lateralgate\nvisual ITZOfilmsingle-channel ~0.25μJ / [54]\nmodulation\nlightpulses\nvisual IGZOfilmsingle-channel ~80nJ / [55]\nmodulation\nHf Zr O film V amplitude\n0.2 0.8 2 G\n/ 37fJ / [22]\nsingle-channel modulation\nchargecarrier\ncross-coupledIZO EPSCratio: This\ntactile transportation 0.108fJ\nnano-wirechannel 4.40 work\nincross-channel\nReferences\n23. Han, J. K. et al. Artificial olfactory neuron for an in-sensor neuromorphic nose.\nAdv. Sci.9,2106017(2022).\n52. He, B. et al. Frame-channel engineered multimodal transistor integrating\nneuromorphic computing with cross-modal edge intelligence. Adv. Funct.\nMater. 2506332(2025).\n53. Hu, M. et al. A non-linear two-dimensional float gate transistor as a lateral\ninhibitory synapse for retinal early visual processing. Mater. Horiz. 9,\n2335-2344(2022).\n54. Liu, X. et al. Heterointerface-modulated synthetic synapses exhibiting complex\nmultiscaleplasticity. Adv. Sci. e17237 (2025).\n55. Hu. Z. et al. The optoelectronic synergistic properties based on\nindium-gallium-zinc oxide neuromorphic transistors. Nanotechnology 36\n235703(2025).\n22. Cao, R. et al. Compact artificial neuron based on anti-ferroelectric transistor. Nat.\nCommun. 13,7018(2022).\n3. Scalability and Fabrication Considerations: Although group-level reproducibility\nwas reported (Fig. R5), the authors provide limited discussion on the scalability of the\ncross-channel printing process, device uniformity, and system-level yield. Such\ninformation is vital to evaluate the feasibility of practical deployment, particularly in\narray-scaletactilesensors orneuromorphic interfaces.\nRESPONSE：\nMany thanks for the reviewer’s valuable suggestion. We supplemented the\nwafer-level device fabrication process to verify the scalability of the cross-channel\nprinting process (Figure S17). Subsequently, we systematically evaluated the\nvariations of the response of the individual devices in the 33 synaptic array. Under\nidentical presynaptic spikes (4 V, 50 ms) without lateral inhibition, highly\nreproducible currents of output side (Figure S19a) and inhibitory side (Figure S19b)\nwere observed across all devices. The device-to-device (D2D) variations using data\nstatistics were examined. The variation coefficient (σ/μ) for peak currents A , A , and\n1 5\nA were calculated to be 4.09%, 3.57%, and 4.25% at the output side, and to be\n20\n2.57%, 2.16%, and 1.97% at the inhibitory side, respectively, where σ denotes the\nstandard deviation and μ is the mean value (Figure S20). The relatively small\nvariation coefficient indicates a well-uniformity of our fabricated synaptic device\narray.\nRevised parts in themanuscript:\nOnpage 10,thefollowing discussionhas been revised (in red):\nThe wafer-level device fabrication process to verify the scalability of the\ncross-channel printingprocess (Supplementary Fig.S17).\nOnpage 10,thefollowing discussionhas been revised (in red):\nThe uniformity of response across the CST array was systematically evaluated. Under\nidentical presynaptic spikes (4 V, 50 ms) with lateral inhibition under V = 0.5 V,\nDS2\nhighly reproducible currents of output side and inhibitory side were observed across\nall 33 devices (Supplementary Fig. S19). The device-to-device (D2D) variations\nusing data statistics were examined. The variation coefficient (σ/μ) for peak currents\nA , A , and A were calculated to be 4.09%, 3.57%, and 4.25% at the output side, and\n1 5 20\nto be 2.57%, 2.16%, and 1.97% at the inhibitory side, respectively, where σ denotes\nthestandard deviation and μis themean value (Supplementary Fig. S20).\nAdditionalfigure has beenadded in therevised supporting information (in red):\nFig. S17|Device arrays. Photograph of wafer-level CSTarrays.\nFig. S19 | device uniformity. EPSC of 9 devices in the array from a the output side\nand b the inhibitory side triggered by 20 consecutive presynaptic spikes without\nlateral inhibition.\nFig. S20 | Device-to-device variations. Device-to-device variations of PSC peaks in\nCTSarrays.\n4. Encryption Robustness and Device Variability: The LIE-based\nencryption/decryption strategy assumes consistent linear correlations between output\nand inhibitory currents. However, the rebuttal lacks discussion on the impact of\ndevice non-idealities (e.g., ion gel hysteresis, variability, noise) on encryption fidelity.\nAn assessment of robustness or compensatory strategies (e.g., calibration) would be\nhelpful.\nRESPONSE：\nThanks for the your constructive feedback. We fully agree that device\nnon-idealities are inevitable and can impact encryption fidelity. To address these\nconcerns, we have developed a novel reservoir computing system to enhance the\nrobustness of our LIE-based encryption/decryption strategy against such\nnon-idealities.\nSpecifically, we utilized the LIE devices to sample EPSC signals from fixed time\nregions for reservoir computing (RC) when encoding dot and dash signals in Morse\ncode (Figure S27a). In the standard temporal signal classification, each signal is\ntransformed into weight features by an LIE-RC system with 10 reservoir nodes. The\nLIE units dynamically adapt tothe changing signals when different standard digits are\ninput. The output layer trains the node currents, and the results are used as inputs for\nthe exponential operation in the Softmax function to calculate the probability values\nfor each category and index them to the label with the maximum probability value,\nwhich is thesystem's final predicted category.\nTo simulate the impact of device non-idealities on encryption, we introduced\nrandom sampling offsets of ±0.15 s and ±3% random noise into all sampled signals,\nthereby constructing a training set with 2058 non-ideal samples (Figure S27b). The\nresults demonstrate that our LIE-reservoir computing process exhibits excellent\ncompensatory characteristics against non-idealities, achieving 100% recognition\naccuracy for these samples (Figure S27c). This highlights the system's outstanding\npotential foradaptive calibrationin thepresence ofnon-ideal encoding.\nWe have detailed the compensatory strategies and the system's performance\nundernon-ideal conditions in therevised manuscript.\nRevised parts in themanuscript:\nOnpage 13,thefollowing discussionhas been revised (in red):\nAdditionally, to enhance the robustness of our LIE-based encryption/decryption\nstrategy against device non-idealities, we integrated it with a reservoir computing\nprocess (Supplementary Fig. S27a). We introduced random sampling offsets of ±0.15\ns and ±3% noise into the signals, creating a training set with 2058 non-ideal samples\n(Supplementary Fig. S27b).The LIE-RC system achieved 100% recognition accuracy,\ndemonstrating its good compensatory capabilities and potential for adaptive\ncalibrationunder non-ideal conditions (Supplementary Fig. S27c).\nAdditionalfigure has beenadded in therevised supporting information (in red):\nFig. S27 | Reservoir computing process. a Schematic illustration of the integration\nof the LIE-based encryption/decryption strategy with the reservoir computing process.\nb Construction of unencrypted, encrypted, and decrypted Morse code databases\nincorporating non-idealities factors. c Convergence curves for the identification of the\nnon-idealities Morse codedatabase bythe LIE- reservoircomputing process.\n5. Integration of Supplementary Visuals and Circuit Clarity: The supplementary\nfigures, while informative, would benefit from better annotation and clearer\nintegration into the main text. Schematic illustrations (e.g., Fig. S2) could be\nenhanced with color-coded potential paths and field lines to assist readers in\nvisualizing complex multi-terminaloperation.\nRESPONSE：\nThank you for your constructive suggestions. The schematic illustrations in\nFigure S2have been replaced with color-coded potential paths and field-line diagrams\nand incorporated intothemain textas Figure 3d.\nRevised parts in themanuscript:\nOnpage 7,thefollowing discussionhas been revised (in red):\nWhen the applied lateral inhibition voltage (V ) increased, the transfer curves\nDS2\nof inhibitory side showed potentiation trend, while output attenuation trend\n(Supplementary Fig. S1a-c; Fig. S2). Under shared top gate, the gate current was\nsignificantly smaller than the channel current (Supplementary Fig. S1d). To elucidate\nthe lateral-inhibition mechanism, finite-element simulations of the electric-field\n(Supplementary Fig. S3a) and potential distributions (Supplementary Fig. S3b) were\nperformed under varied V , confirming the progressive suppression of the output\nDS2\nside and the eventual reversal of the inhibitory channel current. Electric-field\ndistributions of the cross-structured transistor (CST) in the absence and presence of\nlateral-inhibitionbias were schematically depicted inFigure 3d.\nAdditionalfigure has beenupdated inthe revised supportinginformation:\nFig. 3 | Electrical properties of the five-terminal cross-channel device. a\nSchematic diagram of tactile lateral inhibition. PSC from b the output side and c the\ninhibitory side triggered by 20 consecutive presynaptic spikes (4 V, 50 ms) without\nand with lateral inhibition. d Electric-field schematics of CST without and with\nlateral-inhibition voltage. Histograms of PSC from e the output side and f the\ninhibitory side triggered by different frequency of presynaptic spikes under different\ninhibitory voltages. Electric field and current distributionsinIZO-NWs under V = g\nDS2\n0, h 0.4, i 0.7, and j 1 V at the simulation time of 2 s. PSC outputs from k the\ninhibitory side, l the output side, and m the decryption weighted PSC in secure\ncommunication.\n6. Language and Technical Precision: Some technical descriptions, particularly\nregarding voltage configurations and circuit behavior, could be more rigorously\nphrased using formal notation and unambiguous terminology. This would ensure\nprecision,especially for readers unfamiliar with unconventional device geometries.\nRESPONSE：\nThank you very much for your constructive comment.Weregret our lack of rigor.\nIn the revised manuscript, we have provided clear definitions and conducted a\nthorough review oftheentire text.\nRevised parts in themanuscript:\nOnpage 15,thefollowing discussionhas been revised (in red):\nFabrication of artificial tactile nervous system. The artificial tactile nervous\nsystem comprises an information processing unit and a signal acquisition and display\nunit. Information Processing Unit: A matrix thin-film pressure sensor (IMM00092A,\ni-Motion sensor) serves as the pressure sensing module, whose electrical resistance\n(R ) decreases with increasing applied pressure. R is connected in series with a\nsensor sensor\nvoltage divider resistor (R). Consequently, the drain voltage (V ) of the synaptic\ns DS2\ntransistor increases/decreases as R increases/decreases. The two output currents\nsensor\n(I and I ) from the artificial synaptic device are converted into corresponding\nout1 out2\noutput voltages (V and V ) using operational amplifiers (LM358). Signal\nout1 out2\nAcquisition and Display Unit:Amicrocontroller unit (MCU,ATmega328P,Microchip)\ndigitizes the analog signals V and V . Subsequently, these digital signals undergo\nout1 out2\nthreshold comparison. The results of this threshold comparison are then converted\ninto voltage signals and transmitted to the liquid crystal display screen (ILI9431) for\nvisualization.\nAdditionalfigure has beenupdated inthe revised supportinginformation:\nFig. S24 | Artificial tactile nervous system. a Photograph and b circuit schematic\ndiagram of theartificial tactilenervous system."}, {"round": 3, "reviewer_comments": {"reviewer_2": "The manuscript has been improved. While the revisions are substantial, a few minor improvements would further strengthen the manuscript as follows:\n1. Benchmarking Discussion: While Table S1 is included, the authors should explicitly highlight CST’s unique advantages (sub-femtojoule energy consumption, secure communication capability) and candidly acknowledge its limitations (response time asymmetry, relatively large pitch size compared to state-of-the-art tactile arrays).\n2. Encryption Section: The LIE encryption/decryption demonstration is strong, but the manuscript should better link its novelty to practical applications (e.g., IoT, secure wearable devices). This would enhance impact.\n3. Language and Readability: Although improved, the manuscript still has dense sections with repeated technical terms (e.g., “postsynaptic current” appears excessively). A round of language polishing will help with readability for a broader audience."}, "author_response": "Response to Reviewers’ Comments\nMany thanks for the reviewers’ valuable comments and constructive suggestions\nto our manuscript. Revision has been made point-to-point to comply with the reviewer’s\nremarks as follows. The remarks of the reviewers are in black, our responses are in blue,\nand the revised parts were marked in red color in revised manuscript.\nReviewer #2:\nThe manuscript has been improved. While the revisions are substantial, a few minor\nimprovements would further strengthen the manuscript as follows:\nRESPONSE：\nWe sincerely appreciate the reviewer’s help on improving the manuscript. Below\nare our point-by-point responses to your comments.\n1. Benchmarking Discussion: While Table S1 is included, the authors should explicitly\nhighlight CST’s unique advantages (sub-femtojoule energy consumption, secure\ncommunication capability) and candidly acknowledge its limitations (response time\nasymmetry, relatively large pitch size compared to state-of-the-art tactile arrays).\nRESPONSE：\nWe sincerely thank the reviewer for the insightful comments, which help a lot on\nimproving the manuscript. We summarized and compared the advantages and\nlimitations of CST, as commented by the reviewer.\n(i) Merits of this work: Sub-femtojoule energy consumption per spike of 0.108 fJ;\nthe cross-coupled nanowire architecture encodes information in the form that is\nunreadable via single-channel measurements, affording physical-level information\nprotection without any additional encryption circuit.\n(ii) Limitations of this work: The system could be improved by further improving\nthe response time asymmetry and reducing the pitch size.\nWe added the analysis of the advantages and disadvantages of CST and made\ncorresponding descriptions.\nRevised parts in the manuscript:\nOn page 10 of the revised manuscript, the following discussion has been revised\n(in red):\n“The electrical properties of the CST are compared with state-of-art lateral\ninhibition-based neuromorphic systems (Table S1)22, 23, 52-55. The cross-coupled\nnanowire architecture of CST encodes data in the form that cannot be retrieved by a\nsingle channel, providing physically built-in information protection without extra\nencryption circuit. The device shows high energy-efficiency. The system could be\nimproved by further improving the response time asymmetry and reducing the pitch\nsize.”\n2. Encryption Section: The LIE encryption/decryption demonstration is strong, but the\nmanuscript should better link its novelty to practical applications (e.g., IoT, secure\nwearable devices). This would enhance impact.\nRESPONSE：\nWe appreciate the reviewer's constructive suggestion regarding the practical\napplications of the LIE mechanism. While the current study primarily focuses on\ndemonstrating the fundamental working principles and encryption capabilities, we\nacknowledge that further exploration of application contexts could enhance the\ntranslational impact of this work. Accordingly, we have revised the discussion section\nto connect these scenarios to the LIE’s novelty.\nRevised parts in the manuscript:\nOn page 10 of the revised manuscript, the following discussion has been revised\n(in red):\n“This coding system based on lateral suppression encryption provided a secure\nencryption and decryption method, which protected the confidentiality of sensitive\ninformation. This system has potential applications in protecting data security and\nprivacy, potentially applicable to secure wearable devices, internet of things (IoT), etc.”\n3. Language and Readability: Although improved, the manuscript still has dense\nsections with repeated technical terms (e.g., “postsynaptic current” appears\nexcessively). A round of language polishing will help with readability for a broader\naudience.\nRESPONSE：\nThanks for your valuable advice. We have checked through and refined the\nmanuscript.\nRevised parts in the manuscript:\nIn the revised manuscript, the following discussion has been revised (in red):\n“However, such important operational logic has not yet been realized in\nneuromorphic sensing systems at the device level.”\n“When one channel is excited, it attenuates the charge-carrier transport in its\nperpendicular channel, fundamentally realizing the lateral inhibition behavior on the\ndevice level, forming a competitive charge-transport mechanism. The device was\nsuccessfully applied to precise localization of the touch point on an electronic skin, and\nthe position can be visually displayed simultaneously.”\n“When our skin is subjected to a sudden touch at some point, our event-driven\nneural information processing can precisely pick out this information from a variety of\ntactile information1-7.”\n“This mechanism also inspires some preliminary research on functional device\nsets for constructing visual processing. Different terminals in the same synaptic\ntransistor are used to emulate the competition between horizontal cells, by employing\nthe lateral gates of an anti-ferroelectric field-effect transistor22.”\n“All the above processes are modulated by artificial electrical pulses, whereas\nlateral inhibition is usually caused by the sense of surrounding environment to result in\nthe inhibitory effect.”\n“Herein, we demonstrate a tactile nervous system that involves lateral inhibition\nbehavior, for precise localization of tactile information, which is also visually displayed\nsimultaneously.”\n“When one channel is excited, the other channel is laterally attenuated, serving as\nthe inhibitory channel and implying lateral inhibition.”\n“The ion gel rich in mobile ions that could migrate to the channel region in\nresponse to the presynaptic spike, inducing the change of charge carrier amounts in the\nchannels. One of the IZO channels emulated synaptic cleft, through which\nneurotransmitters are released to cause postsynaptic currents (PSC) as controlled by\nresting potential (V ) of 1 V and the stimulation potential (V ).”\nDS1 GS\n“Cross-structured NW arrays were mass produced, showing high transparency\n(Figure 2b).”\n“The intersections of the NWs changed from a stacked to a flat morphology after\nsintering (Figure 2i,j). The typical diameter of a single NW was ~250 nm (Figure 2k).\nElemental mapping demonstrated the evenly distributed indium (In), zinc (Zn), and\noxygen (O) in a NW (Figure 2l).”\n“Sensory cells can improve acuity through the lateral inhibition mechanism29.”\n“When the applied lateral inhibition voltage (V ) increased, the transfer curves\nDS2\nof inhibitory side showed potentiation trend, while output attenuation trend\n(Supplementary Fig. S1a-c; Fig. S2).”\n“When applied single presynaptic spike (4 V, 50 ms), PSCs were induced to\nsimulate transmission of neurotransmitters in the synaptic cleft.”\n“Furthermore, through the drain terminal of the inhibitory side, PSC originating\nfrom the inhibitory side can also be observed (Figure 3c).”\n“We investigated the inhibitory-strength-dependent plasticity of CST by varying\nV ranging from 0 to 1 V.”\nDS2\n“Current-voltage (I-V) contour maps from output side and from inhibitory side\nelucidates the operation mechanism of the CST with IZO cross-channels\n(Supplementary Fig. S10).”\n“Furthermore, a series of spike trains at different frequencies were applied to\ninvestigate frequency-dependent plasticity under the influence of different levels of\nlateral inhibition (Supplementary Fig. S11). As the pulse frequency increased, both\nPSCs from the output side and inhibitory side increased (Figure 3e and 3f); this was\ndue to the high-frequency stimulation driving more cations to migrate towards the\nchannel region, inducing larger electron flow40.”\n“A similar phenomenon was observed for PSCs triggered by presynaptic stimuli\nwith different numbers of spikes (Supplementary Fig. S12). This characteristic can be\nutilized in signal processing applications to determine whether sufficient lateral\ninhibition is present simply by assessing the polarity of the PSC41.”\n“Furthermore, unlike the conventional approach of modulating synaptic weights\nthrough applied gate spikes, the output-side PSC was regulated by the inhibitory bias\nvoltage, achieving potentiation-depression regulation (Supplementary Fig. S13a).”\n“The uniformity of response across the CST array was systematically evaluated.\nUnder identical presynaptic spikes (4 V, 50 ms) with lateral inhibition under V = 0.5\nDS2\nV, highly reproducible currents from output side and inhibitory side were observed\nacross all 33 devices (Supplementary Fig. S19). The device-to-device (D2D)\nvariations were examined using data statistics.”\n“Under the effect of somatosensory lateral inhibition, when a skin region is\nstimulated, the unstimulated regions around it are also be affected, which can reduce\nthe excitation level of the surrounding regions, thereby helping people perceive and\nlocalize the source of stimulation more accurately (Figure 5a). To achieve this, an\nartificial tactile nervous system was fabricated to achieve real-time perception and\nsignal processing of external stimuli at different locations under lateral inhibition, and\nto execute visual sensing of the stimulation location through display unit (Figure 5b;\nSupplementary Fig. S24).”\n“People can accurately locate stimuli on the skin through lateral inhibition.\nAnalogously, for our tactile nervous system, when different position units of the sensor\nare pressed with pressures up to 10 N.”\n“When the pressure is released, PSC quickly returned to the initial state, the\ndisplay device restored (event #4, 12 s) (Figure 5c).”\n“We fabricated an artificial tactile nervous system that replicates the lateral\ninhibition mechanism in human skin, which assists locating the touch point precisely.\nThis was realized at the device level by a cross-channel synaptic transistor in which the\nexcitation of one conductive channel attenuates the other channel, improve the contrast\nin sensing the touch point, which is simultaneously displayed visually.”\n“This work provides an innovative approach for designing and regulating intricate\nfunctionalities in the field of biomimetics and bioelectronics.”\n“Elemental mapping was acquired using a built-in Energy-dispersive X-ray\nspectroscopy (EDXS) measurement module in the TEM system.”"}]

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