Scholars@Duke
Nicolas Brunel

Nicolas Brunel

Adjunct Professor of Neurobiology
Neurobiology
nicolas.brunel@duke.edu
311 Research Drive, Durham, NC 27710

Selected Publications

Inter- and Intrahemispheric Sources of Vestibular Signals to V1.

Journal Article bioRxiv · November 18, 2024 Head movements are sensed by the vestibular organs. Unlike classical senses, signals from vestibular organs are not conveyed to a dedicated cortical area but are broadcast throughout the cortex. Surprisingly, the routes taken by vestibular signals to reach ... Full text Link to item Cite

Behavioral state and stimulus strength regulate the role of somatostatin interneurons in stabilizing network activity.

Journal Article bioRxiv · September 10, 2024 Inhibition stabilization enables cortical circuits to encode sensory signals across diverse contexts. Somatostatin-expressing (SST) interneurons are well-suited for this role through their strong recurrent connectivity with excitatory pyramidal cells. We d ... Full text Open Access Link to item Cite

Dynamic control of sequential retrieval speed in networks with heterogeneous learning rules.

Journal Article Elife · August 28, 2024 Temporal rescaling of sequential neural activity has been observed in multiple brain areas during behaviors involving time estimation and motor execution at variable speeds. Temporally asymmetric Hebbian rules have been used in network models to learn and ... Full text Link to item Cite

Attractor neural networks with double well synapses.

Journal Article PLoS Comput Biol · February 2024 It is widely believed that memory storage depends on activity-dependent synaptic modifications. Classical studies of learning and memory in neural networks describe synaptic efficacy either as continuous or discrete. However, recent results suggest an inte ... Full text Link to item Cite

Mechanisms underlying reshuffling of visual responses by optogenetic stimulation in mice and monkeys.

Journal Article Neuron · December 20, 2023 The ability to optogenetically perturb neural circuits opens an unprecedented window into mechanisms governing circuit function. We analyzed and theoretically modeled neuronal responses to visual and optogenetic inputs in mouse and monkey V1. In both speci ... Full text Open Access Link to item Cite

Interplay between external inputs and recurrent dynamics during movement preparation and execution in a network model of motor cortex.

Journal Article Elife · May 11, 2023 The primary motor cortex has been shown to coordinate movement preparation and execution through computations in approximately orthogonal subspaces. The underlying network mechanisms, and the roles played by external and recurrent connectivity, are central ... Full text Link to item Cite

Bayesian reconstruction of memories stored in neural networks from their connectivity.

Journal Article PLoS Comput Biol · January 2023 The advent of comprehensive synaptic wiring diagrams of large neural circuits has created the field of connectomics and given rise to a number of open research questions. One such question is whether it is possible to reconstruct the information stored in ... Full text Link to item Cite

Forgetting Leads to Chaos in Attractor Networks

Journal Article Physical Review X · January 1, 2023 Attractor networks are an influential theory for memory storage in brain systems. This theory has recently been challenged by the observation of strong temporal variability in neuronal recordings during memory tasks. In this work, we study a sparsely conne ... Full text Cite

From the Statistical Physics of Disordered Systems to Neuroscience

Chapter · January 1, 2023 This chapter studies the bridges and differences between the statistical physics of disordered systems, as developed notably in the context of spin glass theory, and problems in neuroscience. In a first contribution (Sec. 25.1), Nicolas Brunel, Rémi Monass ... Full text Cite

Multiple forms of working memory emerge from synapse-astrocyte interactions in a neuron-glia network model.

Journal Article Proc Natl Acad Sci U S A · October 25, 2022 Persistent activity in populations of neurons, time-varying activity across a neural population, or activity-silent mechanisms carried out by hidden internal states of the neural population have been proposed as different mechanisms of working memory (WM). ... Full text Link to item Cite

Non-monotonic effects of GABAergic synaptic inputs on neuronal firing.

Journal Article PLoS Comput Biol · June 2022 GABA is generally known as the principal inhibitory neurotransmitter in the nervous system, usually acting by hyperpolarizing membrane potential. However, GABAergic currents sometimes exhibit non-inhibitory effects, depending on the brain region, developme ... Full text Open Access Link to item Cite

Storage capacity of networks with discrete synapses and sparsely encoded memories.

Journal Article Phys Rev E · May 2022 Attractor neural networks are one of the leading theoretical frameworks for the formation and retrieval of memories in networks of biological neurons. In this framework, a pattern imposed by external inputs to the network is said to be learned when this pa ... Full text Open Access Link to item Cite

Emergence of Irregular Activity in Networks of Strongly Coupled Conductance-Based Neurons.

Journal Article Phys Rev X · 2022 Cortical neurons are characterized by irregular firing and a broad distribution of rates. The balanced state model explains these observations with a cancellation of mean excitatory and inhibitory currents, which makes fluctuations drive firing. In network ... Full text Open Access Link to item Cite

Storage capacity of networks with discrete synapses and sparsely encoded memories

Journal Article · December 13, 2021 Attractor neural networks (ANNs) are one of the leading theoretical frameworks for the formation and retrieval of memories in networks of biological neurons. In this framework, a pattern imposed by external inputs to the network is said to be learned when ... Open Access Link to item Cite

Forgetting leads to chaos in attractor networks

Journal Article · November 30, 2021 Attractor networks are an influential theory for memory storage in brain systems. This theory has recently been challenged by the observation of strong temporal variability in neuronal recordings during memory tasks. In this work, we study a sparsely conne ... Open Access Link to item Cite

From synapse to network: models of information storage and retrieval in neural circuits.

Journal Article Curr Opin Neurobiol · October 2021 The mechanisms of information storage and retrieval in brain circuits are still the subject of debate. It is widely believed that information is stored at least in part through changes in synaptic connectivity in networks that encode this information and t ... Full text Open Access Link to item Cite

Bayesian reconstruction of memories stored in neural networks from their connectivity

Journal Article PLOS Computational Biology 19(1): e1010813 2023 · May 16, 2021 The advent of comprehensive synaptic wiring diagrams of large neural circuits has created the field of connectomics and given rise to a number of open research questions. One such question is whether it is possible to reconstruct the information stored in ... Open Access Link to item Cite

Synaptic plasticity rules with physiological calcium levels.

Journal Article Proc Natl Acad Sci U S A · December 29, 2020 Spike-timing-dependent plasticity (STDP) is considered as a primary mechanism underlying formation of new memories during learning. Despite the growing interest in activity-dependent plasticity, it is still unclear whether synaptic plasticity rules inferre ... Full text Open Access Link to item Cite

Characteristics of sequential activity in networks with temporally asymmetric Hebbian learning.

Journal Article Proc Natl Acad Sci U S A · November 24, 2020 Sequential activity has been observed in multiple neuronal circuits across species, neural structures, and behaviors. It has been hypothesized that sequences could arise from learning processes. However, it is still unclear whether biologically plausible s ... Full text Open Access Link to item Cite

Emergence of irregular activity in networks of strongly coupled conductance-based neurons

Journal Article · September 25, 2020 Cortical neurons are characterized by irregular firing and a broad distribution of rates. The balanced state model explains these observations with a cancellation of mean excitatory and inhibitory currents, which makes fluctuations drive firing. In network ... Open Access Link to item Cite

Response nonlinearities in networks of spiking neurons.

Journal Article PLoS Comput Biol · September 2020 Combining information from multiple sources is a fundamental operation performed by networks of neurons in the brain, whose general principles are still largely unknown. Experimental evidence suggests that combination of inputs in cortex relies on nonlinea ... Full text Open Access Link to item Cite

Inhibition stabilization is a widespread property of cortical networks.

Journal Article Elife · June 29, 2020 Many cortical network models use recurrent coupling strong enough to require inhibition for stabilization. Yet it has been experimentally unclear whether inhibition-stabilized network (ISN) models describe cortical function well across areas and states. He ... Full text Open Access Link to item Cite

Acetylcholine Modulates Cerebellar Granule Cell Spiking by Regulating the Balance of Synaptic Excitation and Inhibition.

Journal Article J Neurosci · April 1, 2020 Sensorimotor integration in the cerebellum is essential for refining motor output, and the first stage of this processing occurs in the granule cell layer. Recent evidence suggests that granule cell layer synaptic integration can be contextually modified, ... Full text Open Access Link to item Cite

Firing rate of the leaky integrate-and-fire neuron with stochastic conductance-based synaptic inputs with short decay times

Journal Article · February 25, 2020 We compute the firing rate of a leaky integrate-and-fire (LIF) neuron with stochastic conductance-based inputs in the limit when synaptic decay times are much shorter than the membrane time constant. A comparison of our analytical results to numeric simula ... Open Access Link to item Cite

Coupled ripple oscillations between the medial temporal lobe and neocortex retrieve human memory.

Journal Article Science · March 1, 2019 Episodic memory retrieval relies on the recovery of neural representations of waking experience. This process is thought to involve a communication dynamic between the medial temporal lobe memory system and the neocortex. How this occurs is largely unknown ... Full text Open Access Link to item Cite

Unsupervised Learning of Persistent and Sequential Activity.

Journal Article Front Comput Neurosci · 2019 Two strikingly distinct types of activity have been observed in various brain structures during delay periods of delayed response tasks: Persistent activity (PA), in which a sub-population of neurons maintains an elevated firing rate throughout an entire d ... Full text Open Access Link to item Cite

Cerebellar learning using perturbations.

Journal Article Elife · November 12, 2018 The cerebellum aids the learning of fast, coordinated movements. According to current consensus, erroneously active parallel fibre synapses are depressed by complex spikes signalling movement errors. However, this theory cannot solve the credit assignment ... Full text Open Access Link to item Cite

Attractor Dynamics in Networks with Learning Rules Inferred from In Vivo Data.

Journal Article Neuron · July 11, 2018 The attractor neural network scenario is a popular scenario for memory storage in the association cortex, but there is still a large gap between models based on this scenario and experimental data. We study a recurrent network model in which both learning ... Full text Open Access Link to item Cite

Correlations between synapses in pairs of neurons slow down dynamics in randomly connected neural networks.

Journal Article Phys Rev E · June 2018 Networks of randomly connected neurons are among the most popular models in theoretical neuroscience. The connectivity between neurons in the cortex is however not fully random, the simplest and most prominent deviation from randomness found in experimenta ... Full text Open Access Link to item Cite

Bistability and up/down state alternations in inhibition-dominated randomly connected networks of LIF neurons.

Journal Article Sci Rep · September 20, 2017 Electrophysiological recordings in cortex in vivo have revealed a rich variety of dynamical regimes ranging from irregular asynchronous states to a diversity of synchronized states, depending on species, anesthesia, and external stimulation. The average po ... Full text Open Access Link to item Cite

Toward a Neurocentric View of Learning.

Journal Article Neuron · July 5, 2017 Synaptic plasticity (e.g., long-term potentiation [LTP]) is considered the cellular correlate of learning. Recent optogenetic studies on memory engram formation assign a critical role in learning to suprathreshold activation of neurons and their integratio ... Full text Open Access Link to item Cite

Mechanisms and functional roles of glutamatergic synapse diversity in a cerebellar circuit.

Journal Article Elife · September 19, 2016 Synaptic currents display a large degree of heterogeneity of their temporal characteristics, but the functional role of such heterogeneities remains unknown. We investigated in rat cerebellar slices synaptic currents in Unipolar Brush Cells (UBCs), which g ... Full text Open Access Link to item Cite

Astrocytes: Orchestrating synaptic plasticity?

Journal Article Neuroscience · May 26, 2016 Synaptic plasticity is the capacity of a preexisting connection between two neurons to change in strength as a function of neural activity. Because synaptic plasticity is the major candidate mechanism for learning and memory, the elucidation of its constit ... Full text Open Access Link to item Cite

Is cortical connectivity optimized for storing information?

Journal Article Nat Neurosci · May 2016 Cortical networks are thought to be shaped by experience-dependent synaptic plasticity. Theoretical studies have shown that synaptic plasticity allows a network to store a memory of patterns of activity such that they become attractors of the dynamics of t ... Full text Open Access Link to item Cite

Burst-Dependent Bidirectional Plasticity in the Cerebellum Is Driven by Presynaptic NMDA Receptors.

Journal Article Cell Rep · April 5, 2016 Numerous studies have shown that cerebellar function is related to the plasticity at the synapses between parallel fibers and Purkinje cells. How specific input patterns determine plasticity outcomes, as well as the biophysics underlying plasticity of thes ... Full text Open Access Link to item Cite

Storing structured sparse memories in a multi-modular cortical network model.

Journal Article J Comput Neurosci · April 2016 We study the memory performance of a class of modular attractor neural networks, where modules are potentially fully-connected networks connected to each other via diluted long-range connections. On this anatomical architecture we store memory patterns of ... Full text Open Access Link to item Cite

Modulation of Synaptic Plasticity by Glutamatergic Gliotransmission: A Modeling Study.

Journal Article Neural Plast · 2016 Glutamatergic gliotransmission, that is, the release of glutamate from perisynaptic astrocyte processes in an activity-dependent manner, has emerged as a potentially crucial signaling pathway for regulation of synaptic plasticity, yet its modes of expressi ... Full text Open Access Link to item Cite

Inferring learning rules from distributions of firing rates in cortical neurons.

Journal Article Nat Neurosci · December 2015 Information about external stimuli is thought to be stored in cortical circuits through experience-dependent modifications of synaptic connectivity. These modifications of network connectivity should lead to changes in neuronal activity as a particular sti ... Full text Open Access Link to item Cite

A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks.

Journal Article PLoS Comput Biol · August 2015 Understanding the theoretical foundations of how memories are encoded and retrieved in neural populations is a central challenge in neuroscience. A popular theoretical scenario for modeling memory function is the attractor neural network scenario, whose pr ... Full text Open Access Link to item Cite

Neuronal morphology generates high-frequency firing resonance.

Journal Article J Neurosci · May 6, 2015 The attenuation of neuronal voltage responses to high-frequency current inputs by the membrane capacitance is believed to limit single-cell bandwidth. However, neuronal populations subject to stochastic fluctuations can follow inputs beyond this limit. We ... Full text Open Access Link to item Cite

Modulation of network excitability by persistent activity: how working memory affects the response to incoming stimuli.

Journal Article PLoS Comput Biol · February 2015 Persistent activity and match effects are widely regarded as neuronal correlates of short-term storage and manipulation of information, with the first serving active maintenance and the latter supporting the comparison between memory contents and incoming ... Full text Open Access Link to item Cite

Stimulus dependence of local field potential spectra: experiment versus theory.

Journal Article J Neurosci · October 29, 2014 The local field potential (LFP) captures different neural processes, including integrative synaptic dynamics that cannot be observed by measuring only the spiking activity of small populations. Therefore, investigating how LFP power is modulated by externa ... Full text Open Access Link to item Cite

Memory maintenance in synapses with calcium-based plasticity in the presence of background activity.

Journal Article PLoS Comput Biol · October 2014 Most models of learning and memory assume that memories are maintained in neuronal circuits by persistent synaptic modifications induced by specific patterns of pre- and postsynaptic activity. For this scenario to be viable, synaptic modifications must sur ... Full text Open Access Link to item Cite

Memory capacity of networks with stochastic binary synapses.

Journal Article PLoS Comput Biol · August 2014 In standard attractor neural network models, specific patterns of activity are stored in the synaptic matrix, so that they become fixed point attractors of the network dynamics. The storage capacity of such networks has been quantified in two ways: the max ... Full text Open Access Link to item Cite

A cerebellar learning model of vestibulo-ocular reflex adaptation in wild-type and mutant mice.

Journal Article J Neurosci · May 21, 2014 Mechanisms of cerebellar motor learning are still poorly understood. The standard Marr-Albus-Ito theory posits that learning involves plasticity at the parallel fiber to Purkinje cell synapses under control of the climbing fiber input, which provides an er ... Full text Open Access Link to item Cite

Single neuron dynamics and computation.

Journal Article Curr Opin Neurobiol · April 2014 At the single neuron level, information processing involves the transformation of input spike trains into an appropriate output spike train. Building upon the classical view of a neuron as a threshold device, models have been developed in recent years that ... Full text Open Access Link to item Cite

On the relationship between persistent delay activity, repetition enhancement and priming.

Journal Article Front Psychol · 2014 Human efficiency in processing incoming stimuli (in terms of speed and/or accuracy) is typically enhanced by previous exposure to the same, or closely related stimuli-a phenomenon referred to as priming. In spite of the large body of knowledge accumulated ... Full text Open Access Link to item Cite

Analytical approximations of the firing rate of an adaptive exponential integrate-and-fire neuron in the presence of synaptic noise.

Journal Article Front Comput Neurosci · 2014 Computational models offer a unique tool for understanding the network-dynamical mechanisms which mediate between physiological and biophysical properties, and behavioral function. A traditional challenge in computational neuroscience is, however, that sim ... Full text Open Access Link to item Cite

Optimal properties of analog perceptrons with excitatory weights.

Journal Article PLoS Comput Biol · 2013 The cerebellum is a brain structure which has been traditionally devoted to supervised learning. According to this theory, plasticity at the Parallel Fiber (PF) to Purkinje Cell (PC) synapses is guided by the Climbing fibers (CF), which encode an 'error si ... Full text Open Access Link to item Cite

Dynamics of neural networks

Chapter · January 1, 2013 © 2013 by Taylor & Francis Group, LLC. Animals are constantly submitted to a bombardment of information through their sensory systems. This information is transmitted to the central nervous system (CNS) in the form of spike trains. Traditional views of h ... Full text Cite

Calcium-based plasticity model explains sensitivity of synaptic changes to spike pattern, rate, and dendritic location.

Journal Article Proc Natl Acad Sci U S A · March 6, 2012 Multiple stimulation protocols have been found to be effective in changing synaptic efficacy by inducing long-term potentiation or depression. In many of those protocols, increases in postsynaptic calcium concentration have been shown to play a crucial rol ... Full text Open Access Link to item Cite

Storage of correlated patterns in standard and bistable Purkinje cell models.

Journal Article PLoS Comput Biol · 2012 The cerebellum has long been considered to undergo supervised learning, with climbing fibers acting as a 'teaching' or 'error' signal. Purkinje cells (PCs), the sole output of the cerebellar cortex, have been considered as analogs of perceptrons storing in ... Full text Open Access Link to item Cite

On the distribution of firing rates in networks of cortical neurons.

Journal Article J Neurosci · November 9, 2011 The distribution of in vivo average firing rates within local cortical networks has been reported to be highly skewed and long tailed. The distribution of average single-cell inputs, conversely, is expected to be Gaussian by the central limit theorem. This ... Full text Open Access Link to item Cite

From spiking neuron models to linear-nonlinear models.

Journal Article PLoS Comput Biol · January 20, 2011 Neurons transform time-varying inputs into action potentials emitted stochastically at a time dependent rate. The mapping from current input to output firing rate is often represented with the help of phenomenological models such as the linear-nonlinear (L ... Full text Open Access Link to item Cite

Dynamics of networks of excitatory and inhibitory neurons in response to time-dependent inputs.

Journal Article Front Comput Neurosci · 2011 We investigate the dynamics of recurrent networks of excitatory (E) and inhibitory (I) neurons in the presence of time-dependent inputs. The dynamics is characterized by the network dynamical transfer function, i.e., how the population firing rate is modul ... Full text Open Access Link to item Cite

Cortical dynamics during naturalistic sensory stimulations: experiments and models.

Journal Article J Physiol Paris · 2011 We report the results of our experimental and theoretical investigations of the neural response dynamics in primary visual cortex (V1) during naturalistic visual stimulation. We recorded Local Field Potentials (LFPs) and spiking activity from V1 of anaesth ... Full text Open Access Link to item Cite

Estimating network parameters from combined dynamics of firing rate and irregularity of single neurons.

Journal Article J Neurophysiol · January 2011 High firing irregularity is a hallmark of cortical neurons in vivo, and modeling studies suggest a balance of excitation and inhibition is necessary to explain this high irregularity. Such a balance must be generated, at least partly, from local interconne ... Full text Open Access Link to item Cite

Understanding the relationships between spike rate and delta/gamma frequency bands of LFPs and EEGs using a local cortical network model.

Journal Article Neuroimage · September 2010 Despite the widespread use of EEGs to measure the large-scale dynamics of the human brain, little is known on how the dynamics of EEGs relates to that of the underlying spike rates of cortical neurons. However, progress was made by recent neurophysiologica ... Full text Open Access Link to item Cite

Sensory neural codes using multiplexed temporal scales.

Journal Article Trends Neurosci · March 2010 Determining how neuronal activity represents sensory information is central for understanding perception. Recent work shows that neural responses at different timescales can encode different stimulus attributes, resulting in a temporal multiplexing of sens ... Full text Link to item Cite

Mechanisms of induction and maintenance of spike-timing dependent plasticity in biophysical synapse models.

Journal Article Front Comput Neurosci · 2010 We review biophysical models of synaptic plasticity, with a focus on spike-timing dependent plasticity (STDP). The common property of the discussed models is that synaptic changes depend on the dynamics of the intracellular calcium concentration, which its ... Full text Link to item Cite

Semantic priming in a cortical network model.

Journal Article J Cogn Neurosci · December 2009 Contextual recall in humans relies on the semantic relationships between items stored in memory. These relationships can be probed by priming experiments. Such experiments have revealed a rich phenomenology on how reaction times depend on various factors s ... Full text Link to item Cite

How connectivity, background activity, and synaptic properties shape the cross-correlation between spike trains.

Journal Article J Neurosci · August 19, 2009 Functional interactions between neurons in vivo are often quantified by cross-correlation functions (CCFs) between their spike trains. It is therefore essential to understand quantitatively how CCFs are shaped by different factors, such as connectivity, sy ... Full text Link to item Cite

Synchronization properties of networks of electrically coupled neurons in the presence of noise and heterogeneities.

Journal Article J Comput Neurosci · June 2009 We investigate how synchrony can be generated or induced in networks of electrically coupled integrate-and-fire neurons subject to noisy and heterogeneous inputs. Using analytical tools, we find that in a network under constant external inputs, synchrony c ... Full text Link to item Cite

Very long transients, irregular firing, and chaotic dynamics in networks of randomly connected inhibitory integrate-and-fire neurons.

Journal Article Phys Rev E Stat Nonlin Soft Matter Phys · March 2009 We present results of an extensive numerical study of the dynamics of networks of integrate-and-fire neurons connected randomly through inhibitory interactions. We first consider delayed interactions with infinitely fast rise and decay. Depending on the pa ... Full text Link to item Cite

Electrical coupling mediates tunable low-frequency oscillations and resonance in the cerebellar Golgi cell network.

Journal Article Neuron · January 15, 2009 Tonic motor control involves oscillatory synchronization of activity at low frequency (5-30 Hz) throughout the sensorimotor system, including cerebellar areas. We investigated the mechanisms underpinning cerebellar oscillations. We found that Golgi interne ... Full text Link to item Cite

Encoding of naturalistic stimuli by local field potential spectra in networks of excitatory and inhibitory neurons.

Journal Article PLoS Comput Biol · December 2008 Recordings of local field potentials (LFPs) reveal that the sensory cortex displays rhythmic activity and fluctuations over a wide range of frequencies and amplitudes. Yet, the role of this kind of activity in encoding sensory information remains largely u ... Full text Link to item Cite

The statistics of repeating patterns of cortical activity can be reproduced by a model network of stochastic binary neurons.

Journal Article J Neurosci · October 15, 2008 Calcium imaging of the spontaneous activity in cortical slices has revealed repeating spatiotemporal patterns of transitions between so-called down states and up states (Ikegaya et al., 2004). Here we fit a model network of stochastic binary neurons to dat ... Full text Link to item Cite

Can attractor network models account for the statistics of firing during persistent activity in prefrontal cortex?

Journal Article Front Neurosci · July 2008 Persistent activity observed in neurophysiological experiments in monkeys is thought to be the neuronal correlate of working memory. Over the last decade, network modellers have strived to reproduce the main features of these experiments. In particular, at ... Full text Link to item Cite

High-frequency organization and synchrony of activity in the purkinje cell layer of the cerebellum.

Journal Article Neuron · June 12, 2008 The cerebellum controls complex, coordinated, and rapid movements, a function requiring precise timing abilities. However, the network mechanisms that underlie the temporal organization of activity in the cerebellum are largely unexplored, because in vivo ... Full text Link to item Cite

Sparsely synchronized neuronal oscillations.

Journal Article Chaos · March 2008 We discuss here the properties of fast global oscillations that emerge in networks of neurons firing irregularly at a low rate. We first provide a simple introduction to these sparsely synchronized oscillations, then show how they can be studied analytical ... Full text Link to item Cite

Daniel Amit (1938-2007).

Journal Article Network · 2008 Full text Link to item Cite

Temporal decorrelation of collective oscillations in neural networks with local inhibition and long-range excitation.

Journal Article Phys Rev Lett · December 7, 2007 We consider two neuronal networks coupled by long-range excitatory interactions. Oscillations in the gamma frequency band are generated within each network by local inhibition. When long-range excitation is weak, these oscillations phase lock with a phase ... Full text Link to item Cite

What can we learn from synaptic weight distributions?

Journal Article Trends Neurosci · December 2007 Much research effort into synaptic plasticity has been motivated by the idea that modifications of synaptic weights (or strengths or efficacies) underlie learning and memory. Here, we examine the possibility of exploiting the statistics of experimentally m ... Full text Link to item Cite

Lapicque's 1907 paper: from frogs to integrate-and-fire.

Journal Article Biol Cybern · December 2007 Exactly 100 years ago, Louis Lapicque published a paper on the excitability of nerves that is often cited in the context of integrate-and-fire neurons. We discuss Lapicque's contributions along with a translation of the original publication. ... Full text Link to item Cite

STDP in a bistable synapse model based on CaMKII and associated signaling pathways.

Journal Article PLoS Comput Biol · November 2007 The calcium/calmodulin-dependent protein kinase II (CaMKII) plays a key role in the induction of long-term postsynaptic modifications following calcium entry. Experiments suggest that these long-term synaptic changes are all-or-none switch-like events betw ... Full text Link to item Cite

Efficient supervised learning in networks with binary synapses.

Journal Article Proc Natl Acad Sci U S A · June 26, 2007 Recent experimental studies indicate that synaptic changes induced by neuronal activity are discrete jumps between a small number of stable states. Learning in systems with discrete synapses is known to be a computationally hard problem. Here, we study a n ... Full text Link to item Cite

Irregular persistent activity induced by synaptic excitatory feedback.

Journal Article Front Comput Neurosci · 2007 Neurophysiological experiments on monkeys have reported highly irregular persistent activity during the performance of an oculomotor delayed-response task. These experiments show that during the delay period the coefficient of variation (CV) of interspike ... Full text Link to item Cite

Efficient supervised learning in networks with binary synapses.

Journal Article Proc. Natl. Acad. Sci. USA · 2007 Full text Cite

Rate models with delays and the dynamics of large networks of spiking neurons

Conference Progress of Theoretical Physics Supplement · June 28, 2006 We investigate the dynamics of a one-dimensional network of spiking neurons with spatially modulated excitatory and inhibitory interactions through extensive numerical simulations. We find that the network displays a rich repertoire of dynamical states as ... Full text Cite

How noise affects the synchronization properties of recurrent networks of inhibitory neurons.

Journal Article Neural Comput · May 2006 GABAergic interneurons play a major role in the emergence of various types of synchronous oscillatory patterns of activity in the central nervous system. Motivated by these experimental facts, modeling studies have investigated mechanisms for the emergence ... Full text Link to item Cite

Contributions of intrinsic membrane dynamics to fast network oscillations with irregular neuronal discharges.

Journal Article J Neurophysiol · December 2005 During fast oscillations in the local field potential (40-100 Hz gamma, 100-200 Hz sharp-wave ripples) single cortical neurons typically fire irregularly at rates that are much lower than the oscillation frequency. Recent computational studies have provide ... Full text Link to item Cite

Role of delays in shaping spatiotemporal dynamics of neuronal activity in large networks.

Journal Article Phys Rev Lett · June 17, 2005 We study the effect of delays on the dynamics of large networks of neurons. We show that delays give rise to a wealth of bifurcations and to a rich phase diagram, which includes oscillatory bumps, traveling waves, lurching waves, standing waves arising via ... Full text Link to item Cite

Dynamics of the instantaneous firing rate in response to changes in input statistics.

Conference J Comput Neurosci · June 2005 We review and extend recent results on the instantaneous firing rate dynamics of simplified models of spiking neurons in response to noisy current inputs. It has been shown recently that the response of the instantaneous firing rate to small amplitude osci ... Full text Link to item Cite

A continuous attractor network model without recurrent excitation: maintenance and integration in the head direction cell system.

Journal Article J Comput Neurosci · 2005 Motivated by experimental observations of the head direction system, we study a three population network model that operates as a continuous attractor network. This network is able to store in a short-term memory an angular variable (the head direction) as ... Full text Link to item Cite

Course 10 Network models of memory

Journal Article · January 1, 2005 Full text Cite

Optimal information storage and the distribution of synaptic weights: perceptron versus Purkinje cell.

Journal Article Neuron · September 2, 2004 It is widely believed that synaptic modifications underlie learning and memory. However, few studies have examined what can be deduced about the learning process from the distribution of synaptic weights. We analyze the perceptron, a prototypical feedforwa ... Full text Link to item Cite

How spike generation mechanisms determine the neuronal response to fluctuating inputs.

Journal Article J Neurosci · December 17, 2003 This study examines the ability of neurons to track temporally varying inputs, namely by investigating how the instantaneous firing rate of a neuron is modulated by a noisy input with a small sinusoidal component with frequency (f). Using numerical simulat ... Full text Link to item Cite

Dynamics and plasticity of stimulus-selective persistent activity in cortical network models.

Journal Article Cereb Cortex · November 2003 Persistent neuronal activity is widespread in many areas of the cerebral cortex of monkeys performing cognitive tasks with a working memory component. Modeling studies have helped understanding of the conditions under which persistent activity can be susta ... Full text Link to item Cite

Retrospective and prospective persistent activity induced by Hebbian learning in a recurrent cortical network.

Journal Article Eur J Neurosci · October 2003 Recordings from cells in the associative cortex of monkeys performing visual working memory tasks link persistent neuronal activity, long-term memory and associative memory. In particular, delayed pair-associate tasks have revealed neuronal correlates of l ... Full text Link to item Cite

Firing rate of the noisy quadratic integrate-and-fire neuron.

Journal Article Neural Comput · October 2003 We calculate the firing rate of the quadratic integrate-and-fire neuron in response to a colored noise input current. Such an input current is a good approximation to the noise due to the random bombardment of spikes, with the correlation time of the noise ... Full text Link to item Cite

What determines the frequency of fast network oscillations with irregular neural discharges? I. Synaptic dynamics and excitation-inhibition balance.

Journal Article J Neurophysiol · July 2003 When the local field potential of a cortical network displays coherent fast oscillations ( approximately 40-Hz gamma or approximately 200-Hz sharp-wave ripples), the spike trains of constituent neurons are typically irregular and sparse. The dichotomy betw ... Full text Link to item Cite

Firing-rate resonance in a generalized integrate-and-fire neuron with subthreshold resonance.

Journal Article Phys Rev E Stat Nonlin Soft Matter Phys · May 2003 Neurons that exhibit a peak at finite frequency in their membrane potential response to oscillatory inputs are widespread in the nervous system. However, the influence of this subthreshold resonance on spiking properties has not yet been thoroughly analyze ... Full text Link to item Cite

From subthreshold to firing-rate resonance.

Journal Article J Neurophysiol · May 2003 Many types of neurons exhibit subthreshold resonance. However, little is known about whether this frequency preference influences spike emission. Here, the link between subthreshold resonance and firing rate is examined in the framework of conductance-base ... Full text Link to item Cite

Neuroscience and computation.

Journal Article J Physiol Paris · 2003 Full text Link to item Cite

Dynamics of the firing probability of noisy integrate-and-fire neurons.

Journal Article Neural Comput · September 2002 Cortical neurons in vivo undergo a continuous bombardment due to synaptic activity, which acts as a major source of noise. Here, we investigate the effects of the noise filtering by synapses with various levels of realism on integrate-and-fire neuron dynam ... Full text Link to item Cite

Effects of synaptic noise and filtering on the frequency response of spiking neurons.

Journal Article Phys Rev Lett · March 5, 2001 Noise can have a significant impact on the response dynamics of a nonlinear system. For neurons, the primary source of noise comes from background synaptic input activity. If this is approximated as white noise, the amplitude of the modulation of the firin ... Full text Link to item Cite

Effects of neuromodulation in a cortical network model of object working memory dominated by recurrent inhibition.

Journal Article J Comput Neurosci · 2001 Experimental evidence suggests that the maintenance of an item in working memory is achieved through persistent activity in selective neural assemblies of the cortex. To understand the mechanisms underlying this phenomenon, it is essential to investigate h ... Full text Link to item Cite

Persistent activity and the single-cell frequency-current curve in a cortical network model.

Journal Article Network · November 2000 Neurophysiological experiments indicate that working memory of an object is maintained by the persistent activity of cells in the prefrontal cortex and infero-temporal cortex of the monkey. This paper considers a cortical network model in which this persis ... Link to item Cite

Synaptic mechanisms and network dynamics underlying spatial working memory in a cortical network model.

Journal Article Cereb Cortex · September 2000 Single-neuron recordings from behaving primates have established a link between working memory processes and information-specific neuronal persistent activity in the prefrontal cortex. Using a network model endowed with a columnar architecture and based on ... Full text Link to item Cite

Phase diagrams of sparsely connected networks of excitatory and inhibitory spiking neurons

Conference Neurocomputing · June 1, 2000 The dynamics of networks of sparsely connected excitatory and inhibitory integrate-and-fire neurons is studied analytically. The 'phase diagrams' of such systems include: synchronous states in which neurons fire regularly; Asynchronous states with stationa ... Full text Cite

Dynamics of networks of randomly connected excitatory and inhibitory spiking neurons.

Conference J Physiol Paris · 2000 Recent advances in the understanding of the dynamics of populations of spiking neurones are reviewed. These studies shed light on how a population of neurones can follow arbitrary variations in input stimuli, how the dynamics of the population depends on t ... Full text Link to item Cite

Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons.

Journal Article J Comput Neurosci · 2000 The dynamics of networks of sparsely connected excitatory and inhibitory integrate-and-fire neurons are studied analytically. The analysis reveals a rich repertoire of states, including synchronous states in which neurons fire regularly; asynchronous state ... Full text Link to item Cite

Fast global oscillations in networks of integrate-and-fire neurons with low firing rates.

Journal Article Neural Comput · October 1, 1999 We study analytically the dynamics of a network of sparsely connected inhibitory integrate-and-fire neurons in a regime where individual neurons emit spikes irregularly and at a low rate. In the limit when the number of neurons --> infinity, the network ex ... Full text Link to item Cite

Firing frequency of leaky intergrate-and-fire neurons with synaptic current dynamics.

Journal Article J Theor Biol · November 7, 1998 We consider a model of an integrate-and-fire neuron with synaptic current dynamics, in which the synaptic time constant tau' is much smaller than the membrane time constant tau. We calculate analytically the firing frequency of such a neuron for inputs des ... Full text Link to item Cite

Mutual information, Fisher information, and population coding.

Journal Article Neural Comput · October 1, 1998 In the context of parameter estimation and model selection, it is only quite recently that a direct link between the Fisher information and information-theoretic quantities has been exhibited. We give an interpretation of this link within the standard fram ... Full text Link to item Cite

Nonlinear feedforward networks with stochastic outputs: infomax implies redundancy reduction.

Journal Article Network · May 1998 We prove that maximization of mutual information between the output and the input of a feedforward neural network leads to full redundancy reduction under the following sufficient conditions: (i) the input signal is a (possibly nonlinear) invertible mixtur ... Link to item Cite

Slow stochastic Hebbian learning of classes of stimuli in a recurrent neural network.

Journal Article Network · February 1998 We study unsupervised Hebbian learning in a recurrent network in which synapses have a finite number of stable states. Stimuli received by the network are drawn at random at each presentation from a set of classes. Each class is defined as a cluster in sti ... Link to item Cite

Modeling memory: what do we learn from attractor neural networks?

Conference C R Acad Sci III · 1998 In this paper we summarize some of the main contributions of models of recurrent neural networks with associative memory properties. We compare the behavior of these attractor neural networks with empirical data from both physiology and psychology. This ty ... Full text Link to item Cite

Plasticity of directional place fields in a model of rodent CA3.

Journal Article Hippocampus · 1998 We propose a computational model of the CA3 region of the rat hippocampus that is able to reproduce the available experimental data concerning the dependence of directional selectivity of the place cell discharge on the environment and on the spatial task. ... Full text Link to item Cite

Time to detect the difference between two images presented side by side.

Journal Article Brain Res Cogn Brain Res · June 1997 The time to locate a difference between two artificial images presented side by side on a CRT screen was studied as a function of their complexity. The images were square lattices of black or white squares or quadrangles, in some cases delineated by a blue ... Full text Link to item Cite

Model of global spontaneous activity and local structured activity during delay periods in the cerebral cortex.

Journal Article Cereb Cortex · 1997 We investigate self-sustaining stable states (attractors) in networks of integrate-and-fire neurons. First, we study the stability of spontaneous activity in an unstructured network. It is shown that the stochastic background activity, of 1-5 spikes/s, is ... Full text Link to item Cite

Dynamics of a recurrent network of spiking neurons before and following learning

Journal Article Network: Computation in Neural Systems · January 1, 1997 Extensive simulations of large recurrent networks of integrate-and-fire excitatory and inhibitory neurons in realistic cortical conditions (before and after Hebbian unsupervised learning of uncorrelated stimuli) exhibit a rich phenomenology of stochastic n ... Full text Cite

Cross-correlations in sparsely connected recurrent networks of spiking neurons

Conference Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · January 1, 1997 We study the dynamics of sparsely connected recurrent networks composed of excitatory and inhibitory integrate-and-fire (IF) neurons firing at low rates, and in particular cross-correlations (CC) between spike times of pairs of neurons using both numerical ... Full text Cite

Hebbian learning of context in recurrent neural networks.

Journal Article Neural Comput · November 15, 1996 Single electrode recording in the inferotemporal cortex of monkeys during delayed visual memory tasks provide evidence for attractor dynamics in the observed region. The persistent elevated delay activities could be internal representations of features of ... Full text Link to item Cite

Learning internal representations in an attractor neural network with analogue neurons

Journal Article Network: Computation in Neural Systems · August 1, 1995 Full text Cite

Learning internal representations in an analog attractor neural network

Conference INTERNATIONAL JOURNAL OF NEURAL SYSTEMS, SUPPLEMENTARY ISSUE, 1995 · January 1, 1995 Link to item Cite

Quantitative modeling of local Hebbian reverberations in primate cortex

Conference INTERNATIONAL JOURNAL OF NEURAL SYSTEMS, SUPPLEMENTARY ISSUE, 1995 · January 1, 1995 Link to item Cite

Storage capacity of neural networks: Effect of the fluctuations of the number of active neurons per memory

Journal Article Journal of Physics A: Mathematical and General · December 1, 1994 The storage capacity in an attractor neural network with excitatory couplings is shown to depend not only on the fraction of active neurons per pattern (or coding rate), but also on the fluctuations around this value, in the thermodynamical limit. The capa ... Full text Cite

Dynamics of an attractor neural network converting temporal into spatial correlations

Journal Article Network: Computation in Neural Systems · November 1, 1994 Full text Cite

Correlations of cortical Hebbian reverberations: theory versus experiment.

Journal Article J Neurosci · November 1994 Interpreting recent single-unit recordings of delay activities in delayed match-to-sample experiments in anterior ventral temporal (AVT) cortex of monkeys in terms of reverberation dynamics, we present a model neural network of quasi-realistic elements tha ... Full text Link to item Cite

Response functions improving performance in analog attractor neural networks.

Journal Article Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics · March 1994 Full text Link to item Cite

Adequate input for learning in attractor neural networks

Journal Article Network: Computation in Neural Systems · January 1, 1993 In the context of learning in attractor neural networks (ANN) the authors discuss the issue of the constraints imposed by there requirements that the afferents arriving at the neurons in the attractor network from the stimulus, compete successfully with th ... Full text Cite

Information capacity of a perceptron

Journal Article Journal of Physics A: Mathematical and General · December 1, 1992 The authors study the information storage capacity of a simple perceptron in the error regime. For random unbiased patterns the geometrical analysis gives a logarithmic dependence for the information content in the asymptotic limit. In this case, the stati ... Full text Cite