Neural dynamics and brain function

This paper introduces a method to quantify neuronal network function using vector fields derived from synaptic weights and neuronal activity, showing how structural richness enables behavioral flexibility.

The paper identifies four factors that contribute to high depolarization baseline offsets in conductance-based neuronal models and discusses their physiological implications.

The paper shows that bilateral integration in somatosensory cortex is controlled by behavioral relevance through coordinated neural activity during reward-associated stimuli.

The paper presents a network model of cortical circuits that explains how parvalbumin neurons enhance neural discriminability of dynamic stimuli through distinct temporal coding mechanisms.

This study identifies the emergence of a synergistic scaffold in the human brain around birth, influenced by environmental factors and linked to later neurocognitive development.

This paper introduces Dynamical Independence (DI) to identify emergent macroscopic dynamics in a biophysical neural model by analyzing the balance between integration and segregation.

This study evaluates piecewise-linear dynamical system models for cognitive neural dynamics, finding they outperform linear models in artificial data but not in monkey perceptual decision data.

This study shows dendritic nonlinearities, particularly NMDA receptors, can drive Up-Down states in cortical neurons independently of network activity.

The paper analyzes whole-brain calcium activity in zebrafish to show scale-invariant neural activity patterns explained by Euclidean Random Matrix theory.

This study analyzes neural responses to visual stimuli in Near and Far flanker conditions using EEG, finding differences in firing rates, frequency band dynamics, and synchrony between conditions.

The paper examines how stimulus-induced gamma sources change with healthy aging in EEG, finding reduced power but not spatial extent.

This study shows that ketamine and dexmedetomidine induce similar cortical phase alignment patterns in nonhuman primates, suggesting a common mechanism for loss of responsiveness.

The paper shows that synaptic plasticity, not intrinsic circuit structure, enables oscillations in a mouse V1 cortical column model with multiple interneuron types.

This study investigates how beta oscillations in motor and frontal brain areas change with physical fatigue, finding enhanced power at rest and reduced power during contraction, and links these changes to the status quo theory.

This study shows caffeine increases brain complexity and shifts neural dynamics towards criticality during sleep, with age-dependent effects observed in REM sleep.

The paper investigates how inactivating currents modulate dendritic synaptic integration modes under in vivo-like conditions, finding that potassium currents favor coincidence detection while calcium and sodium currents promote integration.

This paper develops a mean field theory for pulse-coupled oscillators using phase response curves to predict network synchronization stability and frequency.

The paper compares the robustness of neural circuits to changes in intrinsic versus synaptic conductances and finds that intrinsic conductances have greater sensitivity.

This study shows that beta power returns to baseline levels 4-5 seconds after movement, advocating for longer inter-stimulus intervals in PMBR research.

This paper uses evolutionary strategies to meta-learn plasticity rules in spiking networks, finding stable rules for synapse types but facing challenges with complex co-active rules.

The paper investigates whether somatosensory perception excitability depends on feedforward neuronal spikes, finding no evidence for such a link using HFO metrics and Bayesian analysis.

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 develops a spiking network model of a mouse V1 cortical column to study how feedforward and feedback inputs affect neural dynamics under different network states.

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 paper shows that Hebbian and anti-Hebbian inhibitory STDP rules enable stable memory encoding and modularity in spiking neural networks without control mechanisms.

This paper investigates how the cerebellum and basal ganglia coordinate reinforcement learning through synchronized neural responses and cortical oscillations in rats.

The paper models spike coding in feedforward networks with convergence and divergence, showing structural bottlenecks prefer spike timing over expansion layers and linking network structure to coding strategies.

The paper shows that cortical alpha rhythms interpolate occluded motion in natural scenes based on context.

The paper identifies neural traveling waves evoked by single-pulse brain stimulation using intracranial recordings and shows they propagate with biologically plausible velocities.

This study shows respiration modulates sensory evidence in neural activity during visual tasks, influencing cognitive performance.