Alain Destexhe

CNRS and the European Institute for Theoretical Neuroscience (Paris) · UNIC

Age-related brain changes affect sleep and are reflected in properties of sleep slow-waves, however the precise mechanisms behind these changes are still not completely understood. Here, we adapt a previously established whole-brain model relating structural connectivity changes to resting state dynamics, and extend it to a slow-wave sleep brain st...

The resting primate brain is traversed by spontaneous functional connectivity patterns that show striking differences between conscious and unconscious states. Transcranial direct current stimulation, a non-invasive neuromodulatory technique, can improve signs of consciousness in disorders of consciousness, but can it influence conscious and uncons...

The resting primate brain is traversed by spontaneous functional connectivity patterns that show striking differences between conscious and unconscious states. Transcranial direct current stimulation, a non-invasive neuromodulatory technique, can improve signs of consciousness in disorders of consciousness, but can it influence conscious and uncons...

Resting-state functional magnetic resonance imaging evolves through a repertoire of functional connectivity patterns which might reflect ongoing cognition, as well as the contents of conscious awareness. We investigated whether the dynamic exploration of these states can provide robust and generalizable markers for the state of consciousness in hum...

Learning to make adaptive decisions involves making choices, assessing their consequence, and leveraging this assessment to attain higher rewarding states. Despite vast literature on value-based decision-making, relatively little is known about the cognitive processes underlying decisions in highly uncertain contexts. Real world decisions are rarel...

The development of biologically realistic models of brain microcircuits and regions constitutes currently a very relevant topic in computational neuroscience. One of the main challenges of such models is the passage between different scales, going from the microscale (cellular) to the meso (microcircuit) and macroscale (region or whole-brain level)...

To model the dynamics of neuron membrane excitability many models can be considered, from the most biophysically detailed to the highest level of phenomenological description. Recent works at the single neuron level have shown the importance of taking into account the evolution of slow variables such as ionic concentration. A reduction of such a mo...

The striatum is the largest structure in the basal ganglia, and is known for its key role in functions such as learning and motor control. Studying these aspects requires investigating cellular/microcircuits mechanisms, in particular related to learning, and how these small-scale mechanisms affect large-scale behavior, and its interactions with oth...

The striatum is the largest structure in the basal ganglia, and is known for its key role in functions such as learning and motor control. Studying these aspects requires investigating cellular/microcircuits mechanisms, in particular related to learning, and how these small-scale mechanisms affect large-scale behavior, and its interactions with oth...

We are pleased to announce that the presentations and posters of the Annual Computational Neuroscience Meeting (CNS*2023) have become available. Discover the detailed program on the official website https://cns2023.sched.com ... Join us at Annual Computational Neuroscience Meeting.

In patients suffering absence epilepsy, recurring seizures can significantly decrease their quality of life and lead to yet untreatable comorbidities. Absence seizures are characterized by spike-and-wave discharges on the electroencephalogram associated with a transient alteration of consciousness. However, it is still unknown how the brain respond...

Assessing the impact of pharmaceutical compounds on brain activity is a critical issue in contemporary neuroscience. Currently, no systematic approach exists for evaluating these effects in whole-brain models, which typically focus on macroscopic phenomena, while pharmaceutical interventions operate at the molecular scale. Here, we address this iss...

In patients suffering absence epilepsy, recurring seizures can significantly decrease their quality of life and lead to yet untreatable comorbidities. Absence seizures are characterized by spike-and-wave discharges on the electroencephalogram associated with a transient alteration of consciousness. However, it is still unknown how the brain respond...

Mean-field models are a class of models used in computational neuroscience to study the behavior of large populations of neurons. These models are based on the idea of representing the activity of a large number of neurons as the average behavior of mean-field variables. This abstraction allows the study of large-scale neural dynamics in a computat...

The development of biologically realistic models of brain microcircuits and regions is currently a very relevant topic in computational neuroscience. From basic research to clinical applications, there is an increasing demand for accurate models that incorporate local cellular and network specificities, able to capture a broad range of dynamics and...

In recent years, brain research has indisputably entered a new epoch, driven by substantial methodological advances and digitally enabled data integration and modelling at multiple scales— from molecules to the whole brain. Major advances are emerging at the intersection of neuroscience with technology and computing. This new science of the brain c...

Sensory information must be integrated across a distributed brain network for stimulus processing and perception. Recent studies have revealed specific spatiotemporal patterns of cortical activation for the early and late components of sensory-evoked responses, which are associated with stimulus features and perception, respectively. Here, we inves...

Background: Transcranial direct current stimulation (tDCS) is a non-invasive neuromodulation approach that has been reported to perturb task activity and to benefit patients with a variety of diseases. Nevertheless, the effects of tDCS on brain dynamics and transitions in brain patterns across states of consciousness remain poorly understood. Objec...

Gamma oscillations are widely seen in the cerebral cortex in different states of the wake-sleep cycle and are thought to play a role in sensory processing and cognition. Here, we study the emergence of gamma oscillations at two levels, in networks of spiking neurons, and a mean-field model. At the network level, we consider two different mechanisms...

A central challenge of neuroscience is to elucidate how brain function supports consciousness. Here, we combine the specificity of focal deep brain stimulation with fMRI coverage of the entire cortex, in awake and anaesthetised non-human primates. During propofol, sevoflurane, or ketamine anaesthesia, and subsequent restoration of responsiveness by...

Global neural dynamics emerge from multi-scale brain structures, with nodes dynamically communicating to form transient ensembles that may represent neural information. Neural activity can be measured empirically at scales spanning proteins and subcellular domains to neuronal assemblies or whole-brain networks connected through tracts, but it has r...

Absence seizures are characterized by regular and generalized spike-and-wave electrical patterns in the brain, resulting in unresponsiveness to environmental stimuli. In patients suffering absence epilepsy, recurring seizures can significantly decrease their quality of life and lead to yet untreatable comorbidities. The whole-brain spatial and temp...

Thanks to the availability of connectome data that map connectivity between multiple brain areas, it is now possible to build models of whole-brain activity. At the same time, advances in mean-field techniques have led to biologically based population models that integrate biophysical features such as membrane conductances or synaptic conductances....

Building large-scale simulations of neuronal activity is currently a main challenge in neuroscience research. An efficient approach has been recently adopted which is based on the use of mean-field models to build whole-brain simulations, where large neuronal populations are represented by single mean-field models. However, these methods are normal...

Sleep slow-waves have been reported to vary with age in human subjects, as well as in mouse, but the underlying mechanisms remain unclear. Here, we perform a precise quantification of the effect of aging on the shape and dynamics of sleep slow waves, in a large cohort of human subjects recorded with the electro-encephalogram (EEG) during sleep. The...

Resting-state functional magnetic resonance imaging evolves through a repertoire of functional connectivity patterns which might reflect ongoing cognition, as well as the contents of conscious awareness. We investigated whether the dynamic exploration of these states can provide robust and generalizable markers for the state of consciousness in hum...

Resting-state functional magnetic resonance imaging evolves through a repertoire of functional connectivity patterns which might reflect ongoing cognition, as well as the contents of conscious awareness. We investigated whether the dynamic exploration of these states can provide robust and generalizable markers for the state of consciousness in hum...

The study of brain activity spans diverse scales and levels of description, and requires the development of computational models alongside experimental investigations to explore integrations across scales. The high dimensionality of spiking networks presents challenges for understanding their dynamics. To tackle this, a mean-field formulation offer...

The thalamus is the brain’s central relay station, orchestrating sensory processing and cognitive functions. However, how thalamic function depends on internal and external states, is not well understood. A comprehensive understanding would necessitate the integration of single cell dynamics with their collective behavior at population level. For t...

Gamma oscillations are widely seen in the cerebral cortex in different states of the wake-sleep cycle and are thought to play a role in sensory processing and cognition. Here, we study the emergence of gamma oscillations at two levels, in networks of spiking neurons, and in a mean-field model. At the network level, we consider two different mechani...

To simulate whole brain dynamics with only a few equations, biophysical, mesoscopic models of local neuron populations can be connected using empirical tractography data. The development of mesoscopic mean-field models of neural populations, in particular, the Adaptive Exponential (AdEx mean-field model), has successfully summarized neuron-scale ph...

Psychotic drugs such as ketamine induce symptoms close to schizophrenia and stimulate the production of γ oscillations, as also seen in patients, but the underlying mechanisms are still unclear. Here, we have used computational models of cortical networks generating γ oscillations, and have integrated the action of drugs such as ketamine to partial...

Sensory information must be integrated across a distributed brain network for stimulus processing and perception. Recent studies have revealed specific spatiotemporal patterns of cortical activation for the early and late components of sensory-evoked responses, which are associated with stimulus features and perception, respectively. However, our u...

Absence seizures are characterized by regular and generalized spike-and-wave electrical patterns in the brain, resulting in unresponsiveness to environmental stimuli. In patients suffering absence epilepsy, recurring seizures can significantly decrease their quality of life and lead to yet untreatable comorbidities. The mechanism underlying the red...

Absence seizures are characterized by regular and generalized spike-and-wave electrical patterns in the brain, resulting in unresponsiveness to environmental stimuli. In patients suffering absence epilepsy, recurring seizures can significantly decrease their quality of life and lead to yet untreatable comorbidities. The mechanism underlying the red...

Whole-brain simulations have been proposed previously to simulate global properties such as brain states or functional connectivity. Here, our aim is to build a whole-brain model to simulate a paradigm involving multiple brain areas, for instance auditory discrimination, using a paradigm designed for the macaque cortex. We are interested in the neu...

Mean-field (MF) models are computational formalism used to summarize in a few statistical parameters the salient biophysical properties of an inter-wired neuronal network. Their formalism normally incorporates different types of neurons and synapses along with their topological organization. MFs are crucial to efficiently implement the computationa...

Learning to make decisions depends on exploring options, experiencing their consequence, and reassessing the strategy. Several studies have analyzed various aspects of value-based decision-making, focusing on cued and immediate gratification. By contrast, how the brain gauges delayed consequence for decision-making remains poorly understood. We des...

Thanks to the availability of connectome data that map connectivity between multiple brain areas, it is now possible to build models of whole brain activity. At the same time, advances in mean-field techniques have led to biologically based population models that integrate biophysical features such as membrane conductances or synaptic conductances....

Absence seizures are characterized by regular and generalized spike-and-wave electrical patterns in the brain, resulting in unresponsiveness to environmental stimuli. In patients suffering absence epilepsy, recurring seizures can significantly decrease their quality of life and lead to yet untreatable comorbidities. The mechanism underlying the red...

In the awake brain, cerebral cortex displays asynchronous-irregular (AI) states, where neurons fire irregularly and with low correlation. Neural networks can display AI states that are self-sustained through recurrent connections, or in some cases, need an external input to sustain activity. In this paper, we aim at comparing these two dynamics and...

A central challenge of neuroscience is to elucidate how the orchestration of brain function is modulated by different states of consciousness. Here, we investigate the link between distributed structural and functional brain organisation in functional MRI signals of non-human primates, through bi-directional causal manipulations of consciousness. D...

Mean-field models are a class of models used in computational neuroscience to study the behaviour of large populations of neurons. These models are based on the idea of representing the activity of a large number of neurons as the average behaviour of "mean field" variables. This abstraction allows the study of large-scale neural dynamics in a comp...

Biophysically-grounded whole-brain models were built recently using tractography data to interconnect multiple mesoscopic models, which can simulate the dynamics of neuronal populations with only a few equations. Mean-field models of neural populations, specifically the Adapting AdEx meanfield, was used for this purpose because it can integrate key...

Functional magnetic resonance imaging relies on the coupling between neuronal and vascular activity, but the mechanisms behind this coupling are still under discussion. Recent experimental evidence suggests that calcium signaling may play a significant role in neurovascular coupling. However, it is still controversial where this calcium signal is l...

Here we recorded from Utah arrays chronically implanted in the ventrolateral prefrontal (vlPFC) and posterior parietal (PPC) cortices, in two male macaque monkeys, respectively. Scalp potentials were also recorded simultaneously from eleven EEG channels. In two sets of experiments, intracortical microstimulation was delivered to the center of the 1...

Conscious and unconscious states are characterized by differences in whole brain dynamics as well as differences in the microscale of single neurons. The awake brain generates high-frequency, asynchronous neuronal activity, corresponding to sustained but irregular firing patterns of single neurons, defined as Asynchronous Irregular (AI). On the con...

Neuronal cable theory is usually derived from an electric analogue of the membrane, which contrasts with the slow movement of ions in aqueous media. We show here that it is possible to derive neuronal cable equations from a different perspective, based on the laws of hydrodynamic motion of charged particles (Navier–Stokes equations). This results i...

Brain research has in recent years indisputably entered a new epoch, driven by substantial methodological advances and digitally enabled data integration and modeling at multiple scales – from molecules to the whole system. Major advances are emerging at the intersection of neuroscience with technology and computing. This new science of the brain i...

We present a new AdEx mean-field framework to model two networks of excitatory and inhibitory neurons, representing two cortical columns, and interconnected with excitatory connections contacting both Regularly Spiking (excitatory) and Fast Spiking (inhibitory) cells. This connection scheme is biophysically plausible since it is based on intercolum...

Brain states, such as wake, sleep, or different depths of anesthesia are usually assessed using electrophysiological techniques, such as the local field potential (LFP) or the electroencephalogram (EEG), which are ideal signals for detecting activity patterns such as asynchronous or oscillatory activities. However, it is technically challenging to...

Learning to make adaptive decisions depends on exploring options, experiencing their consequence, and reassessing one’s strategy for the future. Although several studies have analyzed various aspects of value-based decision-making, most of them have focused on decisions in which gratification is cued and immediate. By contrast, how the brain gauges...

Although classically Rapid-Eye Movement (REM) sleep is thought to generate desynchronized activity similar to wakefulness, it was found that some brain regions can express Slow Wave activity (SWA), a pattern which is normally typical of slow-wave sleep. To investigate possible underlying mechanisms, we analyze experimental recordings and introduce...

Hallmarks of neural dynamics during healthy human brain states span spatial scales from neuromodulators acting on microscopic ion channels to macroscopic changes in communication between brain regions. Developing a scale-integrated understanding of neural dynamics has therefore remained challenging. Here, we perform the integration across scales us...

Cortical neurons in vivo function in highly fluctuating and seemingly noisy conditions, and the understanding of how information is processed in such complex states is still incomplete. In this perspective article, we first overview that an intense “synaptic noise” was measured first in single neurons, and computational models were built based on s...

Brain states, such as wake, sleep, or different depths of anesthesia are usually assessed using electrophysiological techniques, such as the local field potential (LFP) or the electro-encephalogram (EEG), which are ideal signals for detecting activity patterns such as asynchronous or oscillatory activities. However, it is technically challenging to...

Mean-field (MF) models can be used to summarize in a few statistical parameters the salient properties of an inter-wired neuronal network incorporating different types of neurons and synapses along with their topological organization. MF are crucial to efficiently implement the modules of large-scale brain models maintaining the specificity of loca...

To evaluate the long-distance magnetic field generated by neurons, we propose a reformulation of the brain’s magneto-quasistatic approximation based on the Jefimenko’s time-dependent generalization of the Biot–Savart law. This differs from the traditional approach relying on Maxwell’s equations and not on their general solution. Instead of a typica...

Epilepsies are characterized by paroxysmal electrophysiological events and seizures, which can propagate across the brain. One of the main unsolved questions in epilepsy is how epileptic activity can invade normal tissue and thus propagate across the brain. To investigate this question, we consider three computational models at the neural network s...

Cable theory is fundamental to understand the electric behavior of neurons and their extended dendritic structure. This theory was introduced by Wilfrid Rall more than half a century ago, and is widely used today for modeling the voltage and current flow in neuronal and dendritic structures. The classic cable theory was derived assuming that the ex...

Neural activity in the sensory cortex combines stimulus responses and ongoing activity, but it remains unclear whether these reflect the same underlying dynamics or separate processes. In the present study, we show in mice that, during wakefulness, the neuronal assemblies evoked by sounds in the auditory cortex and thalamus are specific to the stim...

The use of mean-field models to describe the activity of large neuronal populations has become a very powerful tool for large-scale or whole brain simulations. However, the calculation of brain signals from mean-field models, such as the electric and magnetic fields, is still under development. Thus, the emergence of new methods for an accurate and...

We present a method to convert neural signals into sound sequences, with the constraint that the sound sequences precisely reflect the sequences of events in the neural signal. The method consists in quantifying the wave motifs in the signal and using these parameters to generate sound envelopes. We illustrate the procedure for sleep delta waves in...

Cable theory is fundamental to understand the electric behavior of neurons and their extended dendritic structure. This theory was introduced by Wilfrid Rall more than half a century ago, and is widely used today for modeling the voltage and current flow in neuronal and dendritic structures. The classic cable theory was derived assuming that the ex...

Cortical events of correlated neuronal firing are thought to underlie sensorimotor and associative functions. In the dominant theory, events are attractors of cortical dynamics, pulled by strong mutual connections between recurrently active – core – neurons. Here, we exhaustively measured core connectivity, using a unique dataset with co-registered...

Abstract. The brain is characterized by a prominent ongoing activity occurring in the form of large coactive groups of neurons defining neuronal ensembles which has been proposed as a general substrate for a wide variety of physiological computations and behaviours. For example, it was suggested, mostly based on local recording studies performed un...

Understanding the human brain is a "Grand Challenge" for 21st century research. Computational approaches enable large and complex datasets to be addressed efficiently, supported by artificial neural networks, modeling and simulation. Dynamic generative multiscale models, which enable the investigation of causation across scales and are guided by pr...