Neural dynamics and brain function

The paper analyzes neuronal avalanche dynamics in resting-state MEG data to show temporal persistence and structural organization in brain activity.

This paper shows that prioritization in working memory reduces interference by transforming the unprioritized item into an 'unprioritized' state, linked to low-beta frequency oscillations.

NEURON-based platform that stochastically adds dendritic spines, astrocyte nanoprocesses and a dynamic extracellular space; example simulations show spines widen input-output range and myelin Kir4.1 sustains high-frequency conduction.

The paper examines the coupling between respiration and neural oscillations by analyzing breath-by-breath waveform shapes in human brain recordings.

The paper introduces a plasticity-switching recurrent neural network (psRNN) that models synaptic state-dependent plasticity and shows it improves learning efficiency in cognitive tasks.

This study examines polysynaptic signal propagation in neural mass models across different dynamical regimes and benchmarks results against empirical data.

The paper investigates how theta mechanisms in the primate prefrontal-V4 network mediate target enhancement and distractor suppression during spatial attention.

The paper develops a virtual reality task to study how learned temporal regularities influence decision-making about when to act, showing behavioral and neural adaptations.

The paper investigates differences in gamma band activity in S1 between noxious and innocuous stimuli in mice, finding more transient gamma events after noxious stimulation.

The paper shows that visual experience enhances SST interneuron activity and suppresses VIP interneurons, leading to increased excitatory neuron selectivity and network synchrony.

The paper investigates excitation-inhibition balance dynamics in brain networks during naturalistic behavior in rats, finding coordinated E-I dynamics and transient imbalances linked to behavioral changes.

This study identifies a broadband EEG phase synchronization network supporting interhemispheric visual integration in healthy adults during a visual task.

The paper uses a connectome-constrained model to identify neurons and synapses sustaining spontaneous activity in Drosophila.

The paper introduces DIFF, a method to map directed information flow in cortical networks, and shows it reveals distinct trajectories from traveling waves in simulations and electrophysiological recordings.

This paper introduces ShaReD, a method for analyzing multi-subject neural data without requiring temporal or anatomical alignment, and demonstrates its effectiveness on synthetic and animal data.

This study uses a brain-computer interface to show animals can regulate prefrontal cortex activity through real-time neurofeedback, reducing neural fluctuations and linking this to arousal regulation.

The paper shows that cognitive tasks alter resting-state EEG markers like iAPF and aperiodic exponent across adult ages, with age-dependent changes in aperiodic shifts.

The paper investigates how behavioral states reconfigure neuronal networks in mice, finding that locomotion leads to structured sparsification of signal transmission, enhancing sensory coding efficiency.

The paper shows that watching movies causes widespread adaptation in human cortex, with neurons adjusting their activity levels during rest periods after viewing.

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.

This paper develops a theoretical framework to quantify information stored in synaptic connections of neural networks, showing synergistic interactions among synapses.

This study shows that brain geometry and cognitive inputs shape neural dynamics and topology, with bioRNNs capturing empirical brain activity and spatial patterns.

The paper develops a theoretical framework to determine optimal temporal scales for neural information representation based on signal and noise autocorrelation dynamics.

The paper examines how different electrophysiological protocols reveal distinct but partially shared organizational structures of cell-type responses in mouse visual cortex.

This study examines consciousness transitions in rats using multiple modalities, finding scale-dependent reversibility in local dynamics but distinct global patterns during loss and recovery of consciousness.

The paper infers the structure of a neuronal circuit in the orbitofrontal cortex involved in economic decisions using network analysis and finds a reproducible, state-dependent network structure.

This study examines how aperiodic EEG dynamics change in chronic epilepsy, showing they reflect both network reorganization and waveform shape effects across different brain states.

This study examines how anesthesia affects cortical traveling waves across different states, finding frequency-specific changes and a paradoxical state resembling wakefulness during deep anesthesia.

The paper investigates how sensorimotor remapping affects modularity in the medial prefrontal cortex across different task paradigms, finding increased modularity with full remapping and reduced modularity with partial remapping.

This study examines how neural alpha oscillations and head movements contribute to auditory spatial attention in humans, finding that both mechanisms work together to improve task accuracy.