Neural dynamics and brain function

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.

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.

This paper develops a mechanistic neuron model with plasticity that explains how neurons process and store time-varying signals using an electric-circuit equivalent, revealing a simple learning rule and replicating key biological characteristics.

This study uses a fully coupled EMI model to investigate extracellular stimulation and ephaptic coupling in Purkinje and pyramidal neurons, showing how external fields affect neural activity and synchronization.

This paper introduces a modular neural mass model incorporating neuromodulation, specifically dopamine dynamics, and analyzes its effects on oscillatory states.

The paper models neural dynamics on an attractor landscape to show how attentional states and contexts alter the geometry of brain activity trajectories.

This paper proposes a mechanism for sustained balanced neural activity through short-term synaptic depression, showing it can maintain irregular activity without external inputs.

The paper shows that human brains rhythmically sample decision alternatives at 11 Hz, with attention shifts occurring at troughs and focus deepening at peaks.

This paper presents a spiking neural network model showing how mechanical tension affects memory recall speed, inter-regional synchrony, and memory association in neural networks.

This study uses advanced EEG analysis to assess cortical maturation in preterm infants by examining oscillatory dynamics during different vigilance states.

The paper investigates synergistic interactions mediating long-range correlations in the visual cortex of awake mice during visual stimulation.

The paper develops a method to analyze the relative timing and coupling of neural population bursts across brain regions in mice, finding consistent and variable patterns of activity.

This study investigates the role of neural oscillations in working memory prioritization using EEG, finding that beta power scales with priority shift magnitude and predicts memory fidelity.

This study shows that local infrared stimulation modulates slow-wave dynamics in anesthetized rats by altering neuronal excitability through temperature changes.

The paper introduces {xi}-Net, a generative model of cortical activity that estimates EEG components and connectivity across lifespan using rsEEG data.

This paper shows how autapses in spiking neural networks enable temporal pattern recognition by enabling state transitions and memory.

This study shows that alpha-band sensory entrainment enhances crossmodal memory by preparing the brain for optimal multisensory integration.

This study demonstrates goal-directed learning in cortical organoids using a closed-loop electrophysiology framework and artificial reinforcement learning.

The paper investigates network structure changes during sleep and anesthesia at single-cell and mesoscales, finding increased modularity at the single-cell level and spatially intermixed modules across states.

The paper introduces a computational model integrating cortical and subcortical processing to better replicate brain behavior in decision-making tasks.

The paper examines age-related differences in EEG aperiodic exponents during verbal working memory tasks and links them to neural inefficiency in younger and older adults.

This study uses multivariate PAC analysis to show that older adults have reduced theta-gamma coupling during learning, suggesting impaired working memory function.

The paper studies a modular neural network model to show how symmetry breaking leads to different avalanche shapes and critical behavior in brain dynamics.

The paper investigates how Hebbian-like plasticity and stochastic synaptic changes contribute to representational drift in mouse auditory cortex neurons.

The paper examines how pre-stimulus alpha power affects theta rhythmic multisensory entrainment and memory formation in a human memory task using MEG.

The paper compares task information encoding in adolescent and adult mouse frontal cortex, finding stronger population-level encoding in adolescents despite similar single-cell encoding.

This paper introduces a neural circuit model that learns to segment relevant stimuli from continuous sensory input using reinforcement learning in spiking neuron populations.