Behavioral time scale synaptic plasticity underlies CA1 place fields

Science, Journal Year: 2017, Volume and Issue: 357(6355), P. 1033 - 1036

Published: Sept. 7, 2017

Learning is primarily mediated by activity-dependent modifications of synaptic strength within neuronal circuits. We discovered that place fields in hippocampal area CA1 are produced a potentiation notably different from Hebbian plasticity. Place could be vivo single trial input arrived seconds before and after complex spiking. The potentiated was not initially coincident with action potentials or depolarization. This rule, named behavioral time scale plasticity, abruptly modifies inputs were neither causal nor close to postsynaptic activation. In slices, five pairings subthreshold presynaptic activity calcium (Ca

Language: Английский

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Synaptic Plasticity Forms and Functions

Annual Review of Neuroscience, Journal Year: 2020, Volume and Issue: 43(1), P. 95 - 117

Published: Feb. 20, 2020

Synaptic plasticity, the activity-dependent change in neuronal connection strength, has long been considered an important component of learning and memory. Computational engineering work corroborate power through directed adjustment weights. Here we review fundamental elements four broadly categorized forms synaptic plasticity discuss their functional capabilities limitations. Although standard, correlation-based, Hebbian primary focus neuroscientists for decades, it is inherently limited. Three-factor rules supplement with neuromodulation eligibility traces, while true supervised types go even further by adding objectives instructive signals. Finally, a recently discovered hippocampal form combines above elements, leaving behind requirement. We suggest that effort to determine neural basis adaptive behavior could benefit from renewed experimental theoretical investigation more powerful plasticity.

Language: Английский

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Noninvasive brain stimulation: from physiology to network dynamics and back

Nature Neuroscience, Journal Year: 2013, Volume and Issue: 16(7), P. 838 - 844

Published: June 25, 2013

Language: Английский

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SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks

Neural Computation, Journal Year: 2018, Volume and Issue: 30(6), P. 1514 - 1541

Published: April 13, 2018

A vast majority of computation in the brain is performed by spiking neural networks. Despite ubiquity such spiking, we currently lack an understanding how biological circuits learn and compute vivo, as well can instantiate capabilities artificial silico. Here revisit problem supervised learning temporally coding multilayer First, using a surrogate gradient approach, derive SuperSpike, nonlinear voltage-based three-factor rule capable training networks deterministic integrate-and-fire neurons to perform computations on spatiotemporal spike patterns. Second, inspired recent results feedback alignment, compare performance our under different credit assignment strategies for propagating output errors hidden units. Specifically, test uniform, symmetric, random feedback, finding that simpler tasks be solved with any type while more complex require symmetric feedback. In summary, open door obtaining better scientific advancing ability train them solve problems involving transformations between time

Language: Английский

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Intrinsic Coupling Modes: Multiscale Interactions in Ongoing Brain Activity

Neuron, Journal Year: 2013, Volume and Issue: 80(4), P. 867 - 886

Published: Nov. 1, 2013

Language: Английский

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Alpha Power Increase After Transcranial Alternating Current Stimulation at Alpha Frequency (α-tACS) Reflects Plastic Changes Rather Than Entrainment

Brain stimulation, Journal Year: 2014, Volume and Issue: 8(3), P. 499 - 508

Published: Dec. 20, 2014

Periodic stimulation of occipital areas using transcranial alternating current (tACS) at alpha (α) frequency (8-12 Hz) enhances electroencephalographic (EEG) α-oscillation long after tACS-offset. Two mechanisms have been suggested to underlie these changes in oscillatory EEG activity: tACS-induced entrainment brain oscillations and/or circuits by spike-timing dependent plasticity.We tested what extent plasticity can account for tACS-aftereffects when controlling "echoes." To this end, we used a novel, intermittent tACS protocol and investigated the strength aftereffect as function phase continuity between successive episodes, well match endogenous α-frequency.12 healthy participants were stimulated around individual α-frequency 11-15 min four sessions or sham. Successive events either phase-continuous phase-discontinuous, 3 8 s long. α-phase power compared episodes α-tACS across conditions against sham.α-aftereffects successfully replicated 8-s but not 3-s trains. These aftereffects did reveal any characteristics echoes that they independent phase-continuity showed neither prolonged alignment nor synchronization exact frequency.Our results indicate are sufficient explain α-aftereffects response α-tACS, inform models circuits. Modifying with holds promise clinical applications disorders involving abnormal neural synchrony.

Language: Английский

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Structure, Function, and Pharmacology of Glutamate Receptor Ion Channels

Pharmacological Reviews, Journal Year: 2021, Volume and Issue: 73(4), P. 1469 - 1658

Published: Oct. 1, 2021

Many physiologic effects of l-glutamate, the major excitatory neurotransmitter in mammalian central nervous system, are mediated via signaling by ionotropic glutamate receptors (iGluRs). These ligand-gated ion channels critical to brain function and centrally implicated numerous psychiatric neurologic disorders. There different classes iGluRs with a variety receptor subtypes each class that play distinct roles neuronal functions. The diversity iGluR subtypes, their unique functional properties roles, has motivated large number studies. Our understanding advanced considerably since first subunit gene was cloned 1989, research focus expanded encompass facets biology have been recently discovered exploit experimental paradigms made possible technological advances. Here, we review insights from more than 3 decades studies an emphasis on progress occurred past decade. We cover structure, function, pharmacology, neurophysiology, therapeutic implications for all assembled subunits encoded 18 genes. SIGNIFICANCE STATEMENT: Glutamate important virtually aspects either involved mediating some clinical features neurological disease or represent target treatment. Therefore, pharmacology this will advance our many at molecular, cellular, system levels provide new opportunities treat patients.

Language: Английский

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Plasticity of Cortical Excitatory-Inhibitory Balance

Annual Review of Neuroscience, Journal Year: 2015, Volume and Issue: 38(1), P. 195 - 219

Published: April 21, 2015

Synapses are highly plastic and modified by changes in patterns of neural activity or sensory experience. Plasticity cortical excitatory synapses is thought to be important for learning memory, leading alterations representations cognitive maps. However, these must coordinated across other within local circuits preserve coding schemes the organization inhibitory inputs, i.e., excitatory-inhibitory balance. Recent studies indicate that also controlled directly a large number neuromodulators, particularly during episodes learning. Many modulators transiently alter balance decreasing inhibition, thus disinhibition has emerged as major mechanism which neuromodulation might enable long-term synaptic modifications naturally. This review examines relationships between plasticity, focusing on induction collectively enhance improving perception behavior.

Language: Английский

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Dendritic Spines: The Locus of Structural and Functional Plasticity

Physiological Reviews, Journal Year: 2014, Volume and Issue: 94(1), P. 141 - 188

Published: Jan. 1, 2014

The introduction of high-resolution time lapse imaging and molecular biological tools has changed dramatically the rate progress towards understanding complex structure-function relations in synapses central spiny neurons. Standing issues, including sequence structural processes leading to formation, morphological change, longevity dendritic spines, as well functions spines neurological/psychiatric diseases are being addressed a growing number recent studies. There still unsettled issues with respect spine formation plasticity: Are formed first, followed by synapse or emergence spine? What immediate long-lasting changes properties following exposure plasticity-producing stimulation? Is volume/shape indicative its function? These other this review, which highlights complexity pathways involved regulation structure function, contributes synaptic interactions health disease.

Language: Английский

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Equilibrium Propagation: Bridging the Gap between Energy-Based Models and Backpropagation

Frontiers in Computational Neuroscience, Journal Year: 2017, Volume and Issue: 11

Published: May 4, 2017

We introduce Equilibrium Propagation, a learning framework for energy-based models. It involves only one kind of neural computation, performed in both the first phase (when prediction is made) and second training (after target or error revealed). Although this algorithm computes gradient an objective function just like Backpropagation, it does not need special computation circuit phase, where errors are implicitly propagated. Propagation shares similarities with Contrastive Hebbian Learning Divergence while solving theoretical issues algorithms: our well defined function. Because terms local perturbations, corresponds to nudging (fixed point, stationary distribution) towards configuration that reduces error. In case recurrent multi-layer supervised network, output units slightly nudged their perturbation introduced at layer propagates backward hidden layers. show signal 'back-propagated' during propagation derivatives encodes function, when synaptic update standard form spike-timing dependent plasticity. This work makes more plausible mechanism similar Backpropagation could be implemented by brains, since leaky integrator performs inference back-propagation model. The difference between two phases whether changes allowed not. also experimentally recurrently connected networks 1, 2 3 layers can trained on permutation-invariant MNIST task.

Language: Английский

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