Neural dynamics and brain function

This study shows that traveling waves in the brain support attentional search by causally linking neural activity to behavioral performance.

This study uses tRAS to manipulate aperiodic neural activity and shows it improves visual working memory precision in younger adults.

The paper shows high-frequency oscillations in the human cortex reflect encoding and retrieval of specific word concepts across tasks and time.

This study investigates the development of visual phase-amplitude coupling (PAC) using MEG in children and adults, finding that PAC increases with age in adults but is absent in children.

The paper identifies positive and negative prediction error neurons in mouse somatosensory cortex during an oddball paradigm, showing how they encode stimulus features and statistical context in a hierarchical predictive processing framework.

The paper evaluates four E/I balance metrics using field potential recordings from rat and mouse brain regions, finding broadband and high gamma power consistently correlate with E/I.

This study quantifies information-processing-like properties of human cortical organoids using a functional phenotyping framework, linking network function to disease-related mutations and pharmacological perturbations.

This paper introduces HERO, a sonification pipeline that converts neural spike trains into reproducible, event-faithful audio, aiding in the analysis of population activity.

The paper analyzes neural activity and eye movements during naturalistic movie viewing to show group-level coupling between neural populations and eye-movement states.

This study shows that hippocampo-septal feedback inhibits the medial septal circuit based on hippocampal activity and movement speed, without being essential for theta rhythm generation.

This study shows continuous attractor networks can simultaneously compute model evidence and posterior sampling in distinct subspaces, advancing understanding of neural computation.

The paper investigates how synaptic weights are sorted in a conductance-based neuronal model through spike timing-dependent plasticity, finding that stronger synapses receive more potentiation during bursts.

This study shows that a common connectivity profile in recurrent networks generates diverse neural sequences, which are maintained across brain regions and species.

The paper describes distinct in vivo electrophysiological profiles of three subdivisions of the mediodorsal thalamus in mice, showing differences in waveform amplitude, firing rate, and burst firing.

The paper shows that brain regions use a shared ring manifold to represent time, with population activity evolving along a common trajectory to encode elapsed time through traversal speed modulation.

The paper identifies cell-type-specific spiking patterns during cortical ripples in macaque and human V1, showing conserved circuit mechanisms across species and conditions.

This paper introduces a network-based method to detect neuronal assemblies from spike train data using the van Rossum distance and Louvain algorithm, validated on synthetic and real datasets.

The paper shows that decision-making variability in C. elegans arises from slow modulation of brain states rather than random noise, using calcium imaging and optogenetics.

This study examines human hippocampal neuron activity during working memory, finding distinct tuning properties between posterior and anterior regions.

The paper isolates human cortical tissue to show that rhythmic synchrony increases while network integration decreases, suggesting local circuits generate gamma activity and long-range inputs support complex dynamics.

In a mouse whole-brain co-simulation with a spiking olivocerebellar network, cutting mossy-fiber input to cerebellar nuclei lowers M1-S1 gamma coherence, while removing Purkinje inhibition raises it.

The paper shows that working memory operations involve dynamic changes in neural subspace geometry, driven by aperiodic activity and slow oscillations.

The paper introduces a population-level GLM (pop-GLM) to detect cross-population coupling, showing reduced V1 to higher visual area connectivity during locomotion.

This paper shows that excitatory-inhibitory networks with local plasticity can perform predictive inference without explicit error representations, using a BCM-like rule to maintain weights on a consistency manifold.

The paper develops a nonlinear theory to predict cortical responses to optogenetic perturbations and identifies a feature-tuned inhibition pathway involving SST interneurons.

This study shows acetylcholine modulates spontaneous activity in the developing mouse visual cortex in relation to behavioral states, with effects on network synchrony and activity levels.

This study shows that the cortical hierarchy dynamically organizes large-scale neural propagation, with a periodic timescale and adaptation to behavior and aging.

The paper uses PID to analyze how stimulus information is distributed and shared across cortical networks in ferrets during perceptual decisions, finding that faster decisions involve more redundant information across functionally coupled sites.

This study shows that dopamine depletion in subcortical circuits drives widespread beta-band oscillatory disruptions in the mouse brain through cortico-subcortical resonance.

The paper introduces methods to disentangle latent variables driving neural activity by identifying bidirectional local matrices in neural data, applied to reveal movement-driven structures in motor cortex.