Development of multisensory integration from the perspective of the individual neuron

Nature reviews. Neuroscience, Journal Year: 2014, Volume and Issue: 15(8), P. 520 - 535

Published: July 18, 2014

Language: Английский

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A review of learning in biologically plausible spiking neural networks

Neural Networks, Journal Year: 2019, Volume and Issue: 122, P. 253 - 272

Published: Oct. 12, 2019

Language: Английский

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Activity-Dependent Synaptic Plasticity of a Chalcogenide Electronic Synapse for Neuromorphic Systems

Scientific Reports, Journal Year: 2014, Volume and Issue: 4(1)

Published: May 9, 2014

Nanoscale inorganic electronic synapses or synaptic devices, which are capable of emulating the functions biological brain neuronal systems, regarded as basic building blocks for beyond-Von Neumann computing architecture, combining information storage and processing. Here, we demonstrate a Ag/AgInSbTe/Ag structure chalcogenide memristor-based synapses. The memristive characteristics with reproducible gradual resistance tuning utilised to mimic activity-dependent plasticity that serves basis memory learning. Bidirectional long-term Hebbian modulation is implemented by coactivity pre- postsynaptic spikes sign degree affected assorted factors including temporal difference, spike rate voltage. Moreover, saturation observed be an adjustment rules stabilise growth weights. Our results may contribute development highly functional plastic further construction next-generation parallel neuromorphic architecture.

Language: Английский

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Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity

PLoS Computational Biology, Journal Year: 2013, Volume and Issue: 9(4), P. e1003037 - e1003037

Published: April 25, 2013

The principles by which networks of neurons compute, and how spike-timing dependent plasticity (STDP) synaptic weights generates maintains their computational function, are unknown. Preceding work has shown that soft winner-take-all (WTA) circuits, where pyramidal inhibit each other via interneurons, a common motif cortical microcircuits. We show through theoretical analysis computer simulations Bayesian computation is induced in these network motifs STDP combination with activity-dependent changes the excitability neurons. fundamental components this emergent priors result from adaptation neuronal implicit generative models for hidden causes created STDP. In fact, surprising able to approximate powerful principle fitting such high-dimensional spike inputs: Expectation Maximization. Our results suggest experimentally observed spontaneous activity trial-to-trial variability essential features information processing capability, since functional role represent probability distributions rather than static neural codes. Furthermore it suggests modules as new model distributed cortex.

Language: Английский

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Emerging Memristive Artificial Synapses and Neurons for Energy‐Efficient Neuromorphic Computing

Advanced Materials, Journal Year: 2020, Volume and Issue: 32(51)

Published: Oct. 1, 2020

Abstract Memristors have recently attracted significant interest due to their applicability as promising building blocks of neuromorphic computing and electronic systems. The dynamic reconfiguration memristors, which is based on the history applied electrical stimuli, can mimic both essential analog synaptic neuronal functionalities. These be utilized node terminal devices in an artificial neural network. Consequently, ability understand, control, utilize fundamental switching principles various types device architectures memristor necessary for achieving memristor‐based hardware Herein, a wide range memristors memristive‐related synapses neurons highlighted. structures, principles, applications functionalities are sequentially presented. Moreover, recent advances memristive networks implementations introduced along with overview learning algorithms. Finally, main challenges toward high‐performance energy‐efficient briefly discussed. This progress report aims insightful guide research neuromorphic‐based computing.

Language: Английский

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A large fraction of neocortical myelin ensheathes axons of local inhibitory neurons

eLife, Journal Year: 2016, Volume and Issue: 5

Published: July 6, 2016

Myelin is best known for its role in increasing the conduction velocity and metabolic efficiency of long-range excitatory axons. Accordingly, myelin observed neocortical gray matter thought to mostly ensheath axons connecting subcortical regions distant cortical areas. Using independent analyses light electron microscopy data from mouse neocortex, we show that a surprisingly large fraction (half layer 2/3 quarter 4) ensheathes inhibitory neurons, specifically parvalbumin-positive basket cells. This differs significantly distribution protein composition. on unlikely meaningfully hasten arrival spikes at their pre-synaptic terminals, due patchy short path-lengths observed. Our results thus highlight need exploring alternative roles circuits.

Language: Английский

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Sensory-evoked LTP driven by dendritic plateau potentials in vivo

Nature, Journal Year: 2014, Volume and Issue: 515(7525), P. 116 - 119

Published: Aug. 31, 2014

Language: Английский

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Opposing Effects on Na V 1.2 Function Underlie Differences Between SCN2A Variants Observed in Individuals With Autism Spectrum Disorder or Infantile Seizures

Biological Psychiatry, Journal Year: 2017, Volume and Issue: 82(3), P. 224 - 232

Published: Jan. 27, 2017

Variants in the SCN2A gene that disrupt encoded neuronal sodium channel NaV1.2 are important risk factors for autism spectrum disorder (ASD), developmental delay, and infantile seizures. observed seizures predominantly missense, leading to a gain of function increased excitability. How variants associated with ASD affect excitability unclear.We examined properties 11 ASD-associated heterologous expression systems using whole-cell voltage-clamp electrophysiology immunohistochemistry. Resultant data were incorporated into computational models developing mature cortical pyramidal cells express NaV1.2.In contrast contribute seizure, we found all dampened or eliminated function. Incorporating these electrophysiological results compartmental model excitatory neurons demonstrated variants, regardless their mechanism action, resulted deficits Corresponding analysis predicted minimal change excitability.This functional characterization thus identifies mutation dysfunction as most frequently factor detectable by exome sequencing suggests changes excitability, particularly neurons, may etiology.

Language: Английский

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Theta-burst LTP

Brain Research, Journal Year: 2014, Volume and Issue: 1621, P. 38 - 50

Published: Oct. 27, 2014

Language: Английский

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Amygdala Inhibitory Circuits Regulate Associative Fear Conditioning

Biological Psychiatry, Journal Year: 2017, Volume and Issue: 83(10), P. 800 - 809

Published: Oct. 14, 2017

Associative memory formation is essential for an animal's survival by ensuring adaptive behavioral responses in ever-changing environment. This particularly important under conditions of immediate threats such as fear learning. One the key brain regions involved associative learning amygdala. The basolateral amygdala main entry site sensory information to complex, and local plasticity excitatory principal neurons considered be crucial conditioned responses. However, activity circuits are tightly controlled inhibitory interneurons a spatially temporally defined manner. In this review, we provide updated view on how distinct interneuron subtypes contribute acquisition extinction memories.

Language: Английский

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