Neural dynamics and brain function

This paper shows that hierarchical mouse behavior can emerge from localized cortical dynamics without requiring a hierarchically organized brain.

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 recurrent cortical networks in mouse visual cortex encode natural sensory statistics by filtering input sequences rather than generating them.

The paper examines how REM sleep affects large-scale brain network dynamics and links this to its reduced epileptogenicity by analyzing SEEG recordings from epilepsy patients.

The paper shows that temporal predictions in vision are linked to motor readouts and content-specific encoding in early visual areas during timing judgments.

This study develops a spiking network model of auditory novelty detection and shows how SCZ-related cellular changes impair mismatch negativity.

This study shows corticothalamic layer 6 can bidirectionally modulate cortical and thalamic activity through optogenetic manipulation in mice.

This paper compares methods for estimating aperiodic parameters in M/EEG data and finds that allowing more peaks reduces reliability, proposing a censored regression approach to improve estimates.

The paper shows that different anesthetics destabilize neural dynamics similarly, affecting recovery and low-frequency power, and linking this to unconsciousness.

The paper improves the FOOOF toolbox to better analyze aperiodic components in mouse hippocampal sub-regions, finding significant differences between CA1 and DG.

The paper quantifies the stability of a neuronal network using intrinsic noise and shows that synaptic modifications do not affect its stability.

The paper examines how structural brain features relate to functional activity across individuals and brain regions, finding distinct mechanisms for intra- and inter-individual variability in alpha power.

The paper investigates how neural oscillations relate to predictive processing in visual statistical learning, finding that alpha-band traveling waves correlate with cognitive strategies rather than specific prediction mechanisms.

The paper shows that neural rhythmicity aids memory retrieval when the number of candidate items exceeds four, based on reaction time and electrophysiological data.

This paper uses in vivo recordings and a neural mass model to show how thalamocortical excitatory-inhibitory dynamics generate α-wave patterns during anesthesia, linking EEG oscillations to network dynamics.

This paper uses LMM-TFCE to analyze beta-bursting in older adults during inhibitory control tasks, revealing distinct spatiotemporal patterns not captured by averaged beta-power.

The paper investigates how diffuse predictions affect neural representations during working memory encoding, finding that they stabilize the neural code and alter its geometric layout.

This study investigates how theta and alpha frequency neural activity modulates susceptibility to distractors during visual attention tasks using EEG in humans.

The paper examines long-term neuromodulatory effects on ionic conductance parameter space in pyloric neurons, finding that neuromodulators and activity constrain this space in a cell-type-specific manner.

The paper shows that multi-frequency amplitude co-fluctuations, called spectral motifs, better explain glutamatergic activity than single-frequency power, revealing opponent dynamics in cortical oscillations.

This paper models post-lesional slow waves in brain networks, identifying mechanisms for their generation and propagation.

The paper shows that dendritic calcium-mediated action potentials enable single neurons to disentangle mixed inputs by clustering temporally correlated synapses.

This paper modifies the PING mechanism to produce more realistic gamma oscillations by introducing biophysically motivated changes that reduce synchronization and increase transient activity.

This study investigates how alpha-band oscillations affect visual sensitivity by combining power and phase in a model of pulsed-inhibition, finding that power suppresses sensitivity more than phase.

The paper evaluates six binding operations in neural networks to determine which produce factorized representational geometries observed in neural recordings.

CROCOpy is a Python toolbox for analyzing neuronal oscillations and functional connectivity metrics in electrophysiological data.

The paper simulates learning in a spiking cortico-basal ganglia-thalamic model to show how subnetworks reshape decision dynamics through dopamine-dependent plasticity, shifting strategies from deliberation to commitment.

The paper investigates beta-band oscillations in the LGN and V1 of macaques, finding they are suppressed by visual stimulation and attention, suggesting they represent signal suppression rather than enhancing visual processing.

The paper uses information theory to analyze neural population dynamics and finds that stable neurons show higher redundancy and synergy in pairwise interactions with other neurons.

This paper investigates whether selective sampling of external and internal information shares a theta-rhythmic neural process using EEG and a dual-task design in humans.