A systems model of alternating theta sweeps via firing rate adaptation

Current Biology, Год журнала: 2025, Номер unknown

Опубликована: Фев. 1, 2025

Highlights•Shows how firing rate adaptation produces left-right theta sweeps in grid cells•Models the interaction between internal signals for direction and location•Explains relate to skipping cells•Predicts phase coding of turning angle head-direction cellsSummaryPlace cells provide a neural system self-location tend fire sequences within each cycle hippocampal rhythm when rodents run on linear track. These correspond decoded location animal sweeping forward from its current ("theta sweeps"). However, recent findings open-field environments show alternating propose circuit their generation. Here, we present computational model this circuit, comprising theta-modulated cells, conjunctive × pure based continuous attractor dynamics, adaptation, modulation by medial-septal rhythm. Due ring exhibits direction, providing an input cell network shifted along via intermediate layer producing position cells. Our explains empirical findings, including alignment dependence sweep length spacing. It makes predictions relationships precession during turning, skipping, anticipatory firing, directional tuning width, several which verify experimental data anteroventral thalamus. The also predicts sweeps, running speed, dorsal-ventral entorhinal cortex. Overall, simple intrinsic mechanism complex dynamics signal formation, with testable predictions.

Язык: Английский

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High-order sensory processing nanocircuit based on coupled VO2 oscillators

Nature Communications, Год журнала: 2024, Номер 15(1)

Опубликована: Фев. 24, 2024

Abstract Conventional circuit elements are constrained by limitations in area and power efficiency at processing physical signals. Recently, researchers have delved into high-order dynamics coupled oscillation utilizing Mott devices, revealing potent nonlinear computing capabilities. However, the intricate yet manageable population of multiple artificial sensory neurons with spatiotemporal coupling remain unexplored. Here, we present an experimental hardware demonstration featuring a capacitance-coupled VO 2 phase-change oscillatory network. This network serves as continuous-time dynamic system for pre-processing encodes information phase differences. Besides, decision-making module special post-processing through software simulation is designed to complete bio-inspired system. Our experiments provide compelling evidence that this transistor-free excels tasks such touch recognition gesture recognition, achieving significant advantages fewer devices lower energy-delay-product compared conventional methods. work paves way towards efficient compact neuromorphic based on nano-scale dynamics.

Язык: Английский

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Unveiling serotonergic dysfunction of obsessive-compulsive disorder on prefrontal network dynamics: a computational perspective

Cerebral Cortex, Год журнала: 2024, Номер 34(6)

Опубликована: Июнь 1, 2024

Abstract Serotonin (5-HT) regulates working memory within the prefrontal cortex network, which is crucial for understanding obsessive-compulsive disorder. However, mechanisms how network dynamics and serotonin interact in disorder remain elusive. Here, we incorporate 5-HT receptors (5-HT1A, 5-HT2A) dopamine into a multistable model, replicating experimentally observed inverted U-curve phenomenon. We show two antagonize neuronal activity modulate multistability. Reduced binding of 5-HT1A increases global firing, while reduced 5-HT2A deepens attractors. The obtained results suggest reward-dependent synaptic plasticity may attenuate related impairments. Integrating serotonin-mediated release circuit, observe that decreased concentration triggers deep attractor state, expanding domain attraction stable nodes with high firing rate, potentially causing aberrant reverse learning. This suggests hypothesis wherein elevated concentrations might result from primary deficits levels. Findings this work underscore pivotal role serotonergic dysregulation modulating through pathways, contributing to learned obsessions. Interestingly, reuptake inhibitors antidopaminergic potentiators can counteract over-stable state high-firing points, providing new insights treatment.

Язык: Английский

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Brain-inspired artificial intelligence research: A review

Science China Technological Sciences, Год журнала: 2024, Номер 67(8), С. 2282 - 2296

Опубликована: Июль 30, 2024

Artificial intelligence (AI) systems surpass certain human abilities in a statistical sense as whole, but are not yet the true realization of these and behaviors. There differences, even contradictions, between cognition behavior AI humans. With goal achieving general AI, this study contains review role cognitive science inspiring development three mainstream academic branches based on three-layer framework proposed by David Marr, limitations current explored analyzed. The differences inconsistencies mechanisms brain computation They found to be cause contradictions Additionally, eight important research directions their scientific issues that need focus brain-inspired proposed: highly imitated bionic information processing, large-scale deep learning model balances structure function, multi-granularity joint problem solving bidirectionally driven data knowledge, models simulate specific structures, collaborative processing mechanism with physical separation perceptual interpretive analysis, embodied integrates mechanisms, simulation from individual group (social intelligence), AI-assisted intelligence.

Язык: Английский

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A generalized Spiking Locally Competitive Algorithm for multiple optimization problems

Neurocomputing, Год журнала: 2025, Номер unknown, С. 129392 - 129392

Опубликована: Янв. 1, 2025

Язык: Английский

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Biophysical modeling and experimental analysis of the dynamics of C. elegans body-wall muscle cells

PLoS Computational Biology, Год журнала: 2025, Номер 21(1), С. e1012318 - e1012318

Опубликована: Янв. 27, 2025

This study combines experimental techniques and mathematical modeling to investigate the dynamics of C. elegans body-wall muscle cells. Specifically, by conducting voltage clamp mutant experiments, we identify key ion channels, particularly L-type voltage-gated calcium channel (EGL-19) potassium channels (SHK-1, SLO-2), which are crucial for generating action potentials. We develop Hodgkin-Huxley-based models these integrate them capture cells’ electrical activity. To ensure model accurately reflects cellular responses under depolarizing currents, a parallel simulation-based inference method determining model’s free parameters. performs rapid sampling across high-dimensional parameter spaces, fitting cells specific stimuli yielding accurate estimates. validate our comparing its predictions against various current in experiments show that approach effectively determines suitable parameters cases. Additionally, discover an optimal response frequency cells, corresponds burst firing mode rather than regular mode. Our work provides first experimentally constrained biophysically detailed cell , analytical framework combined with robust efficient parametric estimation can be extended construction other species.

Язык: Английский

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A Heterogeneous Attractor Model for Neural Dynamical mechanism of Movement Preparation

International Journal of Neural Systems, Год журнала: 2025, Номер 35(05)

Опубликована: Фев. 7, 2025

Preparatory activity is crucial for voluntary motor control, reducing reaction time and enhancing precision. To understand the neurodynamic mechanisms behind this, we construct a dynamical model within cortex, which comprises coupled heterogeneous attractors to simulate delayed reaching tasks. This replicates neural patterns observed in macaque distinct attractor spaces preparatory executive activities. It can capture transition from preparation execution through shifts an orthogonal subspace combined with thresholding mechanism. Results show that duration modulates behavioral accuracy, optimal intervals performance. External inputs primarily shape activity, while synaptic connections dominate execution. Our analysis of network’s multi-stable dynamics reveals external reshape stable points modules both before after preparation, strength affects stability input sensitivity, allowing rapid precise actions. Additionally, sensitivity perturbations decreases as increases, emphasizing importance during preparation. Overall, this study provides insights into underlying underscores significance accurate control.

Язык: Английский

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Integrating physical units into high-performance AI-driven scientific computing

Nature Communications, Год журнала: 2025, Номер 16(1)

Опубликована: Апрель 16, 2025

Язык: Английский

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Differentiable simulation enables large-scale training of detailed biophysical models of neural dynamics

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Авг. 21, 2024

Abstract Biophysical neuron models provide insights into cellular mechanisms underlying neural computations. However, a central challenge has been the question of how to identify parameters detailed biophysical such that they match physiological measurements at scale or perform computational tasks. Here, we describe framework for simulation in neuroscience—J axley —which addresses this challenge. By making use automatic differentiation and GPU acceleration, J opens up possibility efficiently optimize large-scale with gradient descent. We show can learn several hundreds voltage two photon calcium recordings, sometimes orders magnitude more than previous methods. then demonstrate makes it possible train recurrent network working memory tasks, feedforward morphologically neurons 100,000 solve computer vision task. Our analyses dramatically improves ability build data- task-constrained models, creating unprecedented opportunities investigating computations across multiple scales.

Язык: Английский

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Spindle Oscillation Emerges at the Critical State of the Electrically Coupled Network in Thalamic Reticular Nucleus

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Янв. 1, 2024

Spindle oscillation is a waxing-and-waning neural observed in the brain, initiated at thalamic reticular nucleus (TRN) and typically occurring 7-15 Hz. Experiments have shown that adult electrical synapses, rather than chemical dominate between TRN neurons, suggesting traditional view of spindle generation via synapses may need reconsideration. Based on known experimental data, we develop computational model network, where heterogeneous neurons are connected by synapses. The shows interplay synchronizing desynchronizing heterogeneity leads to multiple synchronized clusters with slightly different frequencies, whose summed activity produces as seen local field potentials. Our results suggest during oscillation, network operates critical state, which for facilitating efficient information processing. This study provides insights into underlying mechanism its functional significance.

Язык: Английский

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