Biology subjects

Hatsopoulos, N.

Publications and source records attributed to Hatsopoulos, N..

10 recordsLinked to original sources

bioRxiv2026

A Spatially Structured Spiking Network Model of Beta Traveling Waves and Their Attenuation in Motor Cortex

Beta-band oscillations in primate motor cortex propagate as planar traveling waves whose amplitude attenuates with spatial gradients across the cortical sheet just before movement onset. How local excitatory-inhibitory (E-I) interactions and spatial connectivity jointly generate these waves, their attenuation patterns, and their stereotyped rostro-caudal bias remains unclear. Here we address this question by implementing a spatially structured network of leaky integrate-and-fire neurons with distance-dependent connectivity, conduction delays, and realistic synaptic dynamics. Through linear stability analysis and large-scale simulations validated against macaque electrophysiology, we show that planar beta waves emerge as Turing-Hopf spatiotemporal instabilities, where global beta oscillations coexist with irregular single-neuron firing. When the network operates near the boundary between oscillatory and asynchronous regimes, internally generated fluctuations produce the irregular, transient beta bursts characteristic of single-trial local field potentials. A rapid, spatially homogeneous increase in external drive pushes the circuit into an asynchronous state, reproducing the beta power reduction and spatial attenuation gradients seen at movement onset, alongside the irregular spatiotemporal dynamics of movement execution. By introducing anisotropic excitatory-to-excitatory connectivity, we recover the observed rostro-caudal propagation bias. Our results suggest that motor cortical traveling waves are intrinsic dynamical modes of local E-I circuits, recruited and modulated by behaviorally relevant inputs to organize movement initiation.

neuroscience↗

bioRxiv2025

A Generalist Intracortical Motor Decoder

Mapping the relationship between neural activity and motor behavior is a central aim of sensori-motor neuroscience and neurotechnology. While most progress to this end has relied on restricting complexity, the advent of foundation models instead proposes integrating a breadth of data as an alternate avenue for broadly advancing downstream modeling. We quantify this premise for motor decoding from intracortical microelectrode data, pretraining an autoregressive Transformer on 2000 hours of neural population spiking activity paired with diverse motor covariates from over 30 monkeys and humans. The resulting model is broadly useful, benefiting decoding on 8 downstream decoding tasks and generalizing to a variety of neural distribution shifts. However, we also highlight that scaling autoregressive Transformers seems unlikely to resolve limitations stemming from sensor variability and output stereotypy in neural datasets. Code: https://github.com/joel99/ndt3

neuroscience↗

bioRxiv2023

Tessellation Of Artificial Touch Via Microstimulation Of Human Somatosensory Cortex

When we interact with objects, we rely on signals from the hand that convey information about the object and our interaction with it. A basic feature of these interactions, the locations of contacts between the hand and object, is often only available via the sense of touch. Information about locations of contact between a brain-controlled bionic hand and an object can be signaled via intracortical microstimulation (ICMS) of somatosensory cortex (S1), which evokes touch sensations that are localized to a specific patch of skin. To provide intuitive location information, tactile sensors on the robotic hand drive ICMS through electrodes that evoke sensations at skin locations matching sensor locations. This approach requires that ICMS-evoked sensations be focal, stable, and distributed over the hand. To systematically investigate the localization of ICMS-evoked sensations, we analyzed the projected fields (PFs) of ICMS-evoked sensations - their location and spatial extent - from reports obtained over multiple years from three participants implanted with microelectrode arrays in S1. First, we found that PFs vary widely in their size across electrodes, are highly stable within electrode, are distributed over large swaths of each participants hand, and increase in size as the amplitude or frequency of ICMS increases. Second, while PF locations match the locations of the receptive fields (RFs) of the neurons near the stimulating electrode, PFs tend to be subsumed by the corresponding RFs. Third, multi-channel stimulation gives rise to a PF that reflects the conjunction of the PFs of the component channels. By stimulating through electrodes with largely overlapping PFs, then, we can evoke a sensation that is experienced primarily at the intersection of the component PFs. To assess the functional consequence of this phenomenon, we implemented multi-channel ICMS-based feedback in a bionic hand and demonstrated that the resulting sensations are more localizable than are those evoked via single-channel ICMS.

neuroscience↗

bioRxiv2023

Biomimetic multi-channel microstimulation of somatosensory cortex conveys high resolution force feedback for bionic hands

AO_SCPLOWBSTRACTC_SCPLOWManual interactions with objects are supported by tactile signals from the hand. This tactile feedback can be restored in brain-controlled bionic hands via intracortical microstimulation (ICMS) of somatosensory cortex (S1). In ICMS-based tactile feedback, contact force can be signaled by modulating the stimulation intensity based on the output of force sensors on the bionic hand, which in turn modulates the perceived magnitude of the sensation. In the present study, we gauged the dynamic range and precision of ICMS-based force feedback in three human participants implanted with arrays of microelectrodes in S1. To this end, we measured the increases in sensation magnitude resulting from increases in ICMS amplitude and participants ability to distinguish between different intensity levels. We then assessed whether we could improve the fidelity of this feedback by implementing "biomimetic" ICMS-trains, designed to evoke patterns of neuronal activity that more closely mimic those in natural touch, and by delivering ICMS through multiple channels at once. We found that multi-channel biomimetic ICMS gives rise to stronger and more distinguishable sensations than does its single-channel counterpart. Finally, we implemented biomimetic multi-channel feedback in a bionic hand and had the participant perform a compliance discrimination task. We found that biomimetic multi-channel tactile feedback yielded improved discrimination over its single-channel linear counterpart. We conclude that multi-channel biomimetic ICMS conveys finely graded force feedback that more closely approximates the sensitivity conferred by natural touch.

neuroscience↗

bioRxiv2022

Spatial Evolution of Information Dynamics in the Primary Motor Cortex During Reach

The primary motor cortex (M1) is known to be spatially organized in terms of muscles and body parts, notwithstanding some overlap. However, the classical view is largely static, neglecting potential representational changes on a fast time scale. To address potential representational dynamics, we probed the mutual information between M1 signals recorded across the cortical sheet and electromyography (EMG) activity from a set of muscles while a macaque monkey performed planar reaches. Here, we demonstrated that the spatial organization of the M1 encoding was in fact quite dynamic throughout the course of a reaching movement such that a given cortical site maximally encoded different muscles at different times. Despite these rapid representational changes, a proximal-to-distal gradient of the upper limb representation was preserved particularly close to movement onset. Representation was most stable close to movement onset, with characteristic topographic maps, possibly serving functional needs. This study bridges the important gap between flexible motor encoding and static motor maps, emphasizing the importance of considering space and time together in motor representation studies.

neuroscience↗

bioRxiv2022

Microstimulation of human somatosensory cortex evokes task-dependent, spatially patterned responses in motor cortex

AO_SCPLOWBSTRACTC_SCPLOWMotor (M1) and somatosensory (S1) cortex play a critical role in motor control but the nature of the signaling between these structures is not known. To fill this gap, we recorded - in three human participants whose hands were paralyzed as a result of a spinal cord injury - the responses evoked in the hand and arm representations of primary motor cortex (M1) while we delivered ICMS to the somatosensory cortex (S1). We found that ICMS of S1 activated some M1 neurons at short, fixed latencies, locked to each pulse in a manner consistent with monosynaptic activation. However, most of the changes in M1 firing rates were much more variable in time, suggesting a more indirect effect of the stimulation. The spatial pattern of M1 activation varied systematically depending on the stimulating electrode: S1 electrodes that elicited percepts at a given hand location tended to activate M1 neurons with movement fields at the same location. However, the indirect effects of S1 ICMS on M1 were strongly context dependent, such that the magnitude and even sign relative to baseline varied across tasks. We tested the implications of these effects for brain-control of a virtual hand, in which ICMS was used to convey tactile feedback about object interactions. While ICMS-evoked activation of M1 disrupted decoder performance, this disruption could be minimized with biomimetic stimulation, which emphasizes contact transients at the onset and offset of grasp, reduces sustained stimulation, and has been shown to convey useful contact-related information. SO_SCPLOWIGNIFICANCEC_SCPLOWMotor (M1) and somatosensory (S1) cortex play a critical role in motor control but the nature of the signaling between these structures is not known. To fill this gap, we recorded from M1 while delivering intracortical microstimulation (ICMS) to S1 of three human participants, whose hands were paralyzed by spinal cord injury. We found that ICMS activates M1 and that the motor fields of activated M1 neurons match the sensory fields of the stimulated S1 electrodes. These findings have important implications for using ICMS to convey tactile feedback for brain-controlled bionic hands. Indeed, the ICMS-evoked M1 activity worsens control of the hand. Fortunately, this effect is minimized by using biomimetic tactile feedback, which emphasizes contact transients and reduces sustained ICMS.

neuroscience↗

bioRxiv2022

Dynamic Structure Of Motor Cortical Neuron Co-Activity Carries Behaviorally Relevant Information

Skillful, voluntary movements are underpinned by computations performed by networks of interconnected neurons in the primary motor cortex (M1). Computations are reflected by patterns of co-activity between neurons. Using spike time correlations, co-activity can be represented as functional networks (FNs). Here, we show that the structure of FNs constructed from instructed-delay reach trials in non-human primates are behaviorally specific: low dimensional embedding and graph alignment scores show that FNs constructed from closer target reach distances are also closer in network space. We next constructed temporal FNs using short intervals across a trial. We find that temporal FNs traverse a low-dimensional subspace in a reach-specific trajectory. Alignment scores show that FNs become separable and correspondingly, decodable shortly after the instruction cue. Finally, we observe that reciprocal connections in FNs transiently decrease following the instruction cue, suggesting the network momentarily switches from a recurrent system to one that is more feedforward.

neuroscience↗

bioRxiv2022

Interplay between external inputs and recurrent dynamics during movement preparation and execution in a network model of motor cortex

The primary motor cortex has been shown to coordinate movement preparation and execution through computations in approximately orthogonal subspaces. The underlying network mechanisms, and the roles played by external and recurrent connectivity, are central open questions that need to be answered to understand the neural substrates of motor control. We develop a recurrent neural network model that recapitulates the temporal evolution of neuronal activity recorded from the primary motor cortex of a macaque monkey during an instructed delayed-reach task. In particular, it reproduces the observed dynamic patterns of covariation between neural activity and the direction of motion. We explore the hypothesis that the observed dynamics emerges from a synaptic connectivity structure that depends on the preferred directions of neurons in both preparatory and movement-related epochs, and we constrain the strength of both synaptic connectivity and external input parameters from data. While the model can reproduce neural activity for multiple combinations of the feedforward and recurrent connections, the solution that requires minimum external inputs is one where the observed patterns of covariance are shaped by external inputs during movement preparation, while they are dominated by strong direction-specific recurrent connectivity during movement execution, in agreement with recent experimental findings on the relationship between motor-cortical and motor-thalamic activity, both before and during movement execution. Our model also demonstrates that the way in which single-neuron tuning properties change over time can explain the level of orthogonality of preparatory and movement-related subspaces.

neuroscience↗

bioRxiv2021

Chronic wireless neural population recordings with common marmosets

Marmosets are an increasingly important model system for neuroscience in part due to genetic tractability and enhanced cortical accessibility, due to a lissencephalic neocortex. However, many of the techniques generally employed to record neural activity in primates inhibit the expression of natural behaviors in marmosets precluding neurophysiological insights. To address this challenge, we developed methods for recording neural population activity in unrestrained marmosets across multiple ethological behaviors, multiple brain states, and over multiple years. Notably, our flexible methodological design allows for replacing electrode arrays and removal of implants providing alternative experimental endpoints. We validate the method by recording sensorimotor cortical population activity in freely moving marmosets across their natural behavioral repertoire and during sleep. HIGHLIGHTS- Simultaneous and chronic wireless neural population recordings in multiple freely moving marmosets - Neural recording approach enables studies of natural repertoire of behaviors and sleep - Methyl-methacrylate free surgical approach designed to promote biocompatibility and longitudinal success of the implant - Modular headstage configuration requires minimal daily animal handling for daily neural recordings - Alternative experimental endpoints: implant removal, healing, and electrode array replacement

neuroscience↗

bioRxiv2020

Integrating XMALab and DeepLabCut for high-throughput XROMM

Marker tracking is a major bottleneck in studies involving X-ray Reconstruction of Moving Morphology (XROMM). Here, we tested whether DeepLabCut, a new deep learning package built for markerless tracking, could be applied to videoradiographic data to improve data processing throughput. Our novel workflow integrates XMALab, the existing XROMM marker tracking software, and DeepLabCut while retaining each programs utility. XMALab is used for generating training datasets, error correction, and 3D reconstruction, whereas the majority of marker tracking is transferred to DeepLabCut for automatic batch processing. In the two case studies that involved an in vivo behavior, our workflow achieved a 6 to 13-fold increase in data throughput. In the third case study, which involved an acyclic, post mortem manipulation, DeepLabCut struggled to generalize to the range of novel poses and did not surpass the throughput of XMALab alone. Deployed in the proper context, this new workflow facilitates large scale XROMM studies that were previously precluded by software constraints.

animal behavior and cognition↗