A neuronal least-action principle for real-time learning in cortical circuits DOI Creative Commons
Walter Senn, Dominik Dold, Ákos F. Kungl

et al.

eLife, Journal Year: 2023, Volume and Issue: 12

Published: Aug. 22, 2023

One of the most fundamental laws physics is principle least action. Motivated by its predictive power, we introduce a neuronal least-action for cortical processing sensory streams to produce appropriate behavioral outputs in real time. The postulates that voltage dynamics pyramidal neurons prospectively minimizes local somato-dendritic mismatch error within individual neurons. For output neurons, implies minimizing an instantaneous error. deep network it prospective firing overcome integration delays and correct possible errors right neuron-specific are extracted apical dendrites through microcircuit tries explain away feedback from periphery, trajectory on fly. Any motor moving equilibrium with input during ongoing sensory-motor transform. Online synaptic plasticity reduces somatodendritic each neuron performs gradient descent cost at any moment offers axiomatic framework derive global real-time computation learning brain.

Language: Английский

A Neural Device Inspired by Neuronal Oscillatory Activity with Intrinsic Perception and Decision‐Making DOI Creative Commons

Congtian Gu,

Guoliang Ma,

Mengze Zhang

et al.

Advanced Science, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 4, 2025

Abstract Bionic neural devices often feature complex structures with multiple interfaces, requiring extensive post‐processing. In this paper, a device intrinsic perception and decision‐making (NDIPD), inspired by neuronal oscillatory activity is introduced. The utilizes alternating signals generated coupling the human body power‐frequency electromagnetic field as both signal source energy source, mimicking activity. peaks valleys of are differentially modulated to replicate baseline shift process in By comparing amplitude NDIPD's electrical output signal, achieves regarding location mechanical stimulation. This accomplished using single interface, which reduces data transmission, simplifies functionality, eliminates need for an external power supply. NDIPD demonstrates low‐pressure detection limit (<0.02 N), fast response time (<20 ms), exceptional stability (>200 000 cycles). It shows great potential applications such game control, UAV navigation, virtual vehicle driving. innovative supply method sensing mechanism expected open new avenues development bionic devices.

Language: Английский

Citations

2
Decoding the brain: From neural representations to mechanistic models DOI Creative Commons
Mackenzie Weygandt Mathis, Adriana Perez Rotondo, Edward F. Chang

et al.

Cell, Journal Year: 2024, Volume and Issue: 187(21), P. 5814 - 5832

Published: Oct. 1, 2024

Language: Английский

Citations

6
Acquiring musculoskeletal skills with curriculum-based reinforcement learning DOI Creative Commons
Alberto Silvio Chiappa, Pablo Tano, Nisheet Patel

et al.

Neuron, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 1, 2024

Language: Английский

Citations

4
The roles of internal dynamics and proprioceptive feedback in motor cortex during movement execution DOI
Hongru Jiang,

Xiangdong Bu,

Zhiyan Zheng

et al.

Neurocomputing, Journal Year: 2025, Volume and Issue: unknown, P. 129551 - 129551

Published: Feb. 1, 2025

Language: Английский

Citations

0
Proprioceptive engagement of the human cerebellum studied with 7T-fMRI DOI Creative Commons

Emma J.P. Brouwer,

Nikos Priovoulos,

Julie Hashimoto

et al.

Imaging Neuroscience, Journal Year: 2024, Volume and Issue: 2, P. 1 - 12

Published: Jan. 1, 2024

Abstract Proprioception, the process of perceiving our bodies in space, is a key aspect self-perception. The cerebellar cortex believed to play critical role proprioception. However, understanding functional involvement cerebellum proprioception remains limited due intricate, thin, and highly folded structure human cortex, which more challenging resolve using in-vivo MRI compared cerebral cortex. In this study, we employed high-resolution, B1-shimmed, magnetic resonance imaging (fMRI) at 7T investigate proprioceptive humans. We used two tasks designed differentially require information processing: midline-contralateral-finger-touch simultaneous-unilateral-finger-flexing. assessed responses these across three gradient directions inspired by mesoscale organisation, akin laminar columnar fMRI approaches Movements requiring higher engagement, task, elicited stronger activations both anterior posterior lobe motor areas (lobules V VIIIa/b). identified distinct activation patterns for within regions, may reflect differing roles areas. Midline-contralateral-finger-touch were found medial than simultaneous-unilateral-finger-flexing lobule deeper into fissures VIII. These findings contribute offer insights addressing deficits associated with neurological conditions.

Language: Английский

Citations

3
Biomaterials for neuroengineering: Applications and challenges DOI Creative Commons

Huanghui Wu,

E.J. Feng,

Huazong Yin

et al.

Regenerative Biomaterials, Journal Year: 2025, Volume and Issue: 12

Published: Jan. 1, 2025

Abstract Neurological injuries and diseases are a leading cause of disability worldwide, underscoring the urgent need for effective therapies. Neural regaining enhancement therapies seen as most promising strategies restoring neural function, offering hope individuals affected by these conditions. Despite their promise, path from animal research to clinical application is fraught with challenges. Neuroengineering, particularly through use biomaterials, has emerged key field that paving way innovative solutions It seeks understand treat neurological disorders, unravel nature consciousness, explore mechanisms memory brain’s relationship behavior, tissue engineering, interfaces targeted drug delivery systems. These including both natural synthetic types, designed replicate cellular environment brain, thereby facilitating repair. This review aims provide comprehensive overview biomaterials in neuroengineering, highlighting functional across basic practice. covers recent developments biomaterial-based products, 2D 3D bioprinted scaffolds cell organoid culture, brain-on-a-chip systems, biomimetic electrodes brain–computer interfaces. also explores artificial synapses networks, discussing applications modeling microenvironments repair regeneration, modulation manipulation integration traditional Chinese medicine. serves guide role advancing neuroengineering solutions, providing insights into ongoing efforts bridge gap between innovation application.

Language: Английский

Citations

0
Evaluating Heart Rate Variability as a Biomarker for Autonomic Function in Parkinson’s Disease Rehabilitation: A Clustering-Based Analysis of Exercise-Induced Changes DOI Creative Commons
Ahmed M. Basri, Ahmad F. Turki

Medicina, Journal Year: 2025, Volume and Issue: 61(3), P. 527 - 527

Published: March 17, 2025

Background: Heart rate variability (HRV) is a key biomarker reflecting autonomic nervous system (ANS) function and neurocardiac regulation. Reduced HRV has been associated with cardiovascular risk, neurodegenerative disorders, dysfunction. In Parkinson’s disease (PD), impairments indicate altered balance, which may be modifiable through structured exercise interventions. This study investigates the effects of aerobic on in patients PD evaluates adaptations to rehabilitation. Methods: A total 110 (55 male, 55 female) participated supervised three-month program. was assessed pre- post-intervention using electrocardiogram (ECG) recordings. Time-domain frequency-domain metrics, including standard deviation RR intervals (SDRR), very-low-frequency (VLF), low-frequency (LF), high-frequency (HF) power, LF/HF ratio, were analyzed. Principal Component Analysis (PCA) clustering techniques applied identify subgroups responders based adaptation. Results: Significant improvements observed post-intervention, reduction ratio (p < 0.05), indicating improved balance. Cluster analysis identified four distinct response subgroups: Strong Responders, Moderate Mixed/Irregular Low Responders. These findings highlight individual exercise. PCA revealed that parameters contribute differently regulation, emphasizing complexity changes Conclusions: demonstrates induces beneficial patients, as reflected by changes. The identification suggests need for personalized rehabilitation strategies optimize function. Further research warranted explore long-term impact HRV-guided interventions management.

Language: Английский

Citations

0
Local muscle pressure stimulates the principal receptors for proprioception DOI Creative Commons
Frida Torell, Michael Dimitriou

Cell Reports, Journal Year: 2024, Volume and Issue: 43(9), P. 114699 - 114699

Published: Aug. 30, 2024

Language: Английский

Citations

3
Artificial intelligence meets body sense: task-driven neural networks reveal computational principles of the proprioceptive pathway DOI Creative Commons
Leonard E. van Dyck, Frank Bremmer, Katharina Dobs

et al.

Signal Transduction and Targeted Therapy, Journal Year: 2024, Volume and Issue: 9(1)

Published: July 8, 2024

In a recent study published in Cell, Marin Vargas and Bisi et al. 1 present an innovative approach to unravel the computational principles underlying proprioceptive processing non-human primates.Their findings showcase utility of task-driven modeling advancing neuroscience offer translational potential by providing seminal insights into goals mechanisms which brain encodes body position movements.Proprioception allows us perceive movement our parts is crucial for motor control coordination, such as when reaching light switch dark.Proprioceptive signals originate from specialized mechanoreceptors muscles, tendons, joints, travel through dorsal column-medial lemniscus pathway.Within this pathway, cuneate nucleus (CN) plays pivotal role sensory information upper limbs trunk.It then directs thalamus reach both primary (S1) secondary somatosensory cortices.In these cortical areas, are integrated with other information, typically shaping perception unconsciously.Despite understanding, precise involved proprioception still unclear.In particular, what how does it encode support goals?Marin address questions advanced modeling.Artificial neural networks have become powerful tools studying across pathways. 2,3These models not only achieve high predictive accuracy but also deep responses.By training on various tasks comparing learned representations actual activity, researchers can explore specific functions that responses may serve, potentially unlocking new understandings mechanisms. 4uilding concept, developed normative framework uncover pathway.Using multifaceted strategy, they several techniques: (i) simulating inputs musculoskeletal modeling, (ii) optimizing network based hypotheses

Language: Английский

Citations

1
Modeling Sensorimotor Processing with Physics-Informed Neural Networks DOI Creative Commons
Adriana Perez Rotondo, Alessandro Marin Vargas, Michael Dimitriou

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 15, 2024

Proprioception is essential for planning and executing precise movements. Muscle spindles, the key mechanoreceptors proprioception, are principle sensory neurons enabling this process. Emerging evidence suggests spindles act as adaptable processors, modulated by gamma motor to meet task demands. Yet, specifics of modulation remain unknown. Here, we present a novel, physics-informed neural network model that integrates biomechanics dynamics capture spindle function with high fidelity efficiency, while maintaining computational tractability. Through validation across multiple experimental datasets species, our not only outperforms existing approaches but also reveals drivers variability in responses, offering new insights into proprioceptive mechanisms.

Language: Английский

Citations

1