Alain Destexhe A

The paper investigates how gamma oscillations affect cortical responsiveness to hippocampal inputs, finding that low-amplitude gamma enhances communication in prefrontal cortex but not retrosplenial cortex.

BRIDGE is a Python pipeline that reconstructs and validates mean-field models from single neuron dynamics, enabling reproducible and reusable large-scale brain simulations.

This study develops a computational model showing how circadian rhythms modulate excitation-inhibition balance to drive seizure-like dynamics in neuronal networks.

The paper investigates asynchronous states in cerebral cortex networks using computational models and identifies two families of states with different responsiveness properties.

The paper introduces a method to convert detailed morphological neuron models into point-neuron models by analyzing transfer function parameters under in vivo conditions.

This paper introduces a biophysically plausible decision-making model using interacting neural populations in cortical layer 2/3, tested on human and macaque experiments.

The paper shows that cortical population events are generated by hierarchical modularity and distance-dependent connectivity, not attractor dynamics.

This study uses a whole-brain model to show that cholinergic heterogeneity enhances synchronization and information flow in brain dynamics.

The paper presents a biophysically-based model simulating 5-HT2A receptor activation effects, showing increased spontaneous complexity and altered spectral power without significant change in perturbational complexity.

This pilot study found that listening to personalized sound sequences derived from individual slow-wave brain activity improved sleep quality and quantity in adults with insomnia.

The paper analyzes how neuromodulators reshape neuronal feature spaces across different brain regions and states.

The paper presents a mean field model of spiking neural networks with fast and slow inhibitory synapses, showing how GABAB conductance affects gamma oscillations and seizure stability.

The paper systematically investigates the dynamics and bifurcation structure of a mean-field model of Adaptive Exponential integrate-and-fire networks to aid in interpreting results.

This study profiles neural dynamics across species during anaesthesia, finding conserved dynamical changes and linking them to molecular mechanisms.

The paper introduces an extended Adaptive Exponential integrate-and-fire model to simulate ionic regulation impairment and demonstrates its ability to generate normal and epileptic neural network activity.

This paper develops a mean-field model of the thalamus to study state-dependent responsiveness across awake and sleep-like states, showing how neuromodulators, cortical input, and noise influence thalamic function.

This study identifies dynamic structure-function correlations as robust markers of consciousness in humans across different unconscious states.

This paper models how the brain computes delayed consequences in decision-making without explicit feedback, showing how neural dynamics and learning mechanisms adapt over time.

This study uses EEG-fMRI and simulations in awake rats to show that absence seizures suppress brain responsiveness to sensory stimuli.

The paper adapts a mean-field model to quadratic integrate-and-fire neuron models with adaptation and conductance-based synapses, validating it against a spiking network model.

This paper introduces a multiscale modelling framework for hippocampal CA1 that bridges micro and macro scales using a novel mean-field model, validated against spiking network models.

This study shows that anesthesia levels affect the spatiotemporal features and functional connectivity of sensory-evoked responses in the mouse cortex, with the late component persisting under anesthesia.

This study shows that prefrontal cortex transcranial direct current stimulation alters brain dynamics in both awake and anesthetized non-human primates, affecting functional connectivity patterns and structure-function relationships.

This paper develops a mean-field model of gamma oscillations in neuronal networks and shows it matches spiking network activity and frequencies when synaptic delays are included.

The paper builds brain-wide models of mouse, macaque, and human cerebral cortex using connectome data and mean-field techniques, showing species differences in slow-wave synchrony due to axonal propagation delays.

This paper develops a multiscale model of striatum microcircuit dynamics, capturing responses to brain rhythms, dopamine effects, and reinforcement learning.

The paper quantifies age-related changes in sleep slow waves using EEG data and a computational model, finding slowed dynamics, increased variability, and reduced amplitude with age.

The paper explores the TVB-AdEx model's parameter space to understand how adaptation and neuromodulation drive brain state transitions between conscious and unconscious states.

The paper uses computational models to show that NMDA receptor antagonists like ketamine paradoxically increase gamma oscillations and network responsiveness by preferentially affecting inhibitory interneurons.