Preserved neural dynamics across animals performing similar behaviour

Nature, Journal Year: 2023, Volume and Issue: 623(7988), P. 765 - 771

Published: Nov. 8, 2023

Abstract Animals of the same species exhibit similar behaviours that are advantageously adapted to their body and environment. These shaped at level by selection pressures over evolutionary timescales. Yet, it remains unclear how these common behavioural adaptations emerge from idiosyncratic neural circuitry each individual. The overall organization circuits is preserved across individuals 1 because evolutionarily specified developmental programme 2–4 . Such circuit may constrain activity 5–8 , leading low-dimensional latent dynamics population 9–11 Accordingly, here we suggested shared circuit-level constraints within a would lead suitably individuals. We analysed recordings populations monkey mouse motor cortex demonstrate in surprisingly when they perform behaviour. Neural were also animals consciously planned future movements without overt behaviour 12 enabled decoding ongoing movement different Furthermore, found extend beyond cortical regions dorsal striatum, an older structure 13,14 Finally, used network models similarity necessary but not sufficient for this preservation. posit emergent result on brain development thus reflect fundamental properties basis

Language: Английский

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Neuromorphic hardware for somatosensory neuroprostheses

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: Jan. 16, 2024

Abstract In individuals with sensory-motor impairments, missing limb functions can be restored using neuroprosthetic devices that directly interface the nervous system. However, restoring natural tactile experience through electrical neural stimulation requires complex encoding strategies. Indeed, they are presently limited in effectively conveying or sensations by bandwidth constraints. Neuromorphic technology, which mimics behavior of neurons and synapses, holds promise for replicating touch, potentially informing neurostimulation design. this perspective, we propose incorporating neuromorphic technologies into neuroprostheses could an effective approach developing more human-machine interfaces, leading to advancements device performance, acceptability, embeddability. We also highlight ongoing challenges required actions facilitate future integration these advanced technologies.

Language: Английский

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Going beyond primary motor cortex to improve brain–computer interfaces

Trends in Neurosciences, Journal Year: 2022, Volume and Issue: 45(3), P. 176 - 183

Published: Jan. 22, 2022

Language: Английский

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Microfluidic‐Assembled Covalent Organic Frameworks@Ti₃C₂T_x MXene Vertical Fibers for High‐Performance Electrochemical Supercapacitors

Advanced Materials, Journal Year: 2023, Volume and Issue: 35(46)

Published: Aug. 24, 2023

The delicate design of innovative and sophisticated fibers with vertical porous skeleton eminent electrochemical activity to generate directional ionic pathways good faradic charge accessibility is pivotal but challenging for realizing high-performance fiber-shaped supercapacitors (FSCs). Here, hierarchically ordered hybrid fiber combined vertical-aligned conductive Ti3 C2 Tx MXene (VA-Ti3 ) interstratified electroactive covalent organic frameworks LZU1 (COF-LZU1) by one-step microfluidic synthesis developed. Due the incorporation channels, abundant redox active sites large accessible surface area throughout electrode, VA-Ti3 @COF-LZU1 express exceptional gravimetric capacitance 787 F g-1 in a three-electrode system. Additionally, solid-state asymmetric FSCs deliver prominent energy density 27 Wh kg-1 , 398 cycling life 20 000 cycles. key high storage ability originates from decreased ions adsorption ameliorative distribution vertically aligned fiber, accelerating transportation/accommodation interfacial electrons transfer. Benefiting excellent performance, offer sufficient supply power watches, flags, digital display tubes as well be integrated sensors detect pulse signals, which opens promising route architecting advanced toward carbon neutrality market beyond energy-storage technology.

Language: Английский

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

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Feb. 18, 2023

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

Language: Английский

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Nonlinear manifolds underlie neural population activity during behaviour

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: July 19, 2023

There is rich variety in the activity of single neurons recorded during behaviour. Yet, these diverse neuron responses can be well described by relatively few patterns neural co-modulation. The study such low-dimensional structure population has provided important insights into how brain generates Virtually all studies have used linear dimensionality reduction techniques to estimate population-wide co-modulation patterns, constraining them a flat “neural manifold”. Here, we hypothesised that since nonlinear and make thousands distributed recurrent connections likely amplify nonlinearities, manifolds should intrinsically nonlinear. Combining recordings from monkey, mouse, human motor cortex, mouse striatum, show that: 1) are nonlinear; 2) their nonlinearity becomes more evident complex tasks require varied patterns; 3) manifold varies across architecturally distinct regions. Simulations using network models confirmed proposed relationship between circuit connectivity nonlinearity, including differences Thus, underlying generation behaviour inherently nonlinear, properly accounting for nonlinearities will critical as neuroscientists move towards studying numerous regions involved increasingly naturalistic behaviours.

Language: Английский

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

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: Nov. 10, 2023

Abstract The primary motor (M1) and somatosensory (S1) cortices play critical roles in control but the signaling between these structures is poorly understood. To fill this gap, we recorded – three participants an ongoing human clinical trial (NCT01894802) for people with paralyzed hands responses evoked hand arm representations of M1 during intracortical microstimulation (ICMS) representation S1. We found that ICMS S1 activated some neurons at short, fixed latencies consistent monosynaptic activation. Additionally, most ICMS-evoked were more variable time, suggesting indirect effects stimulation. spatial pattern activation varied systematically: electrodes elicited percepts a finger preferentially excited finger’s movement. Moreover, on context dependent, such magnitude even sign relative to baseline across tasks. tested implications brain-control virtual hand, which conveyed tactile feedback. While disrupted decoder performance, disruption was minimized using biomimetic stimulation, emphasizes contact transients onset offset grasp, reduces sustained

Language: Английский

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Development of an Integrated System of sEMG Signal Acquisition, Processing, and Analysis with AI Techniques

Signals, Journal Year: 2024, Volume and Issue: 5(3), P. 476 - 493

Published: July 26, 2024

The development of robust circuit structures remains a pivotal milestone in electronic device research. This article proposes an integrated hardware–software system designed for the acquisition, processing, and analysis surface electromyographic (sEMG) signals. analyzes sEMG signals to understand muscle function neuromuscular control, employing convolutional neural networks (CNNs) pattern recognition. electrical analyzed on healthy unhealthy subjects are acquired using meticulously developed featuring biopotential acquisition electrodes. captured database extracted, classified, interpreted by application CNNs with aim identifying patterns indicative problems. By leveraging advanced learning techniques, proposed method addresses non-stationary nature recordings mitigates cross-talk effects commonly observed interference sensors. integration AI algorithm signal enhances qualitative outcomes eliminating redundant information. reveals their effectiveness accurately deciphering complex data from signals, problems high precision. paper contributes landscape biomedical research, advocating computational techniques unravel physiological phenomena enhance utility analysis.

Language: Английский

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Motor somatotopy impacts imagery strategy success in human intracortical brain-computer interfaces

Journal of Neural Engineering, Journal Year: 2025, Volume and Issue: 22(2), P. 026004 - 026004

Published: Feb. 24, 2025

Objective:The notion of a somatotopically organized motor cortex, with movements different body parts being controlled by spatially distinct areas is well known. However, recent studies have challenged this and suggested more distributed representation movement control. This shift in perspective has significant implications, particularly when considering the implantation location electrode arrays for intracortical brain-computer interfaces (iBCIs). We sought to evaluate whether neural recordings from precentral gyrus, thus underlying somatotopy, any impact on imagery strategies that can enable successful iBCI control.Approach:Three individuals spinal cord injury were enrolled an ongoing clinical trial iBCI. Participants had two microelectrode implanted arm and/or hand gyrus based presurgical functional imaging. Neural data recorded while participants attempted perform hand, wrist, elbow, shoulder.Main results:We found located medially significantly activity during proximal (elbow, shoulder) than did lateral arrays, which captured related distal (hand, wrist). also evaluated relative contribution each participant decoding accuracy calibration decoder translation grasping tasks. For both task types, strategy (e.g. reaching vs wrist movements) contributions array decoding. Overall, we some evidence broad tuning movements; however, there was clear bias amount information accessible about type cortex.Significance:These results demonstrate classical concepts somatotopy real consequences use, highlight importance planning implantation.

Language: Английский

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Stabilizing brain-computer interfaces through alignment of latent dynamics

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2022, Volume and Issue: unknown

Published: April 8, 2022

Abstract Intracortical brain-computer interfaces (iBCIs) restore motor function to people with paralysis by translating brain activity into control signals for external devices. In current iBCIs, instabilities at the neural interface result in a degradation of decoding performance, which necessitates frequent supervised recalibration using new labeled data. One potential solution is use latent manifold structure that underlies population facilitate stable mapping between and behavior. Recent efforts unsupervised approaches have improved iBCI stability this principle; however, existing methods treat each time step as an independent sample do not account dynamics. Dynamics been used enable high performance prediction movement intention, may also help improve stabilization. Here, we present platform Nonlinear Manifold Alignment (NoMAD), stabilizes recurrent network models NoMAD uses distribution alignment update nonstationary data consistent set dynamics, thereby providing input decoder. applications from monkey cortex collected during tasks, enables accurate behavioral unparalleled over weeks-to months-long timescales without any recalibration.

Language: Английский

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