Neural dynamics and brain function

Temporal Gating by Chandelier Cells Encodes Signed Prediction Errors

The paper demonstrates how chandelier cells encode signed prediction errors through temporal gating in a computational model and validates this with in vivo recordings from mouse visual cortex.

A human-specific genetic modifier reconfigures large-scale cortical network dynamics underlying behavioral performance

This study shows that a human-specific gene duplication alters cortical network dynamics in mice, improving task performance through reconfigured interhemispheric correlations and distributed encoding.

Subsecond whole-brain neural dynamics identified by hidden Markov modeling reflect value-based decision making in humans

The paper uses hidden Markov modeling on whole-brain MEG data to show subsecond neural dynamics correlate with value-based decision variables in humans.

The Importance of Synchrony in the Neural Control of Movement

This study shows that neural synchrony, not firing rate, is critical for movement generation by stimulating a small number of motor cortex neurons.

A reduced multicompartment network model of CA1 theta-gamma oscillations under extracellular stimulation

This paper develops a reduced multicompartment model of hippocampal CA1 to study how deep brain stimulation affects theta-gamma oscillations and memory-related neural dynamics.

Alpha oscillations support attentional orienting while beta supports perceptual decision-making.

The paper investigates how alpha and beta oscillations relate to attentional orienting and perceptual decision-making, finding distinct roles for each rhythm in these processes.

Bayesian Nonparametric Identification of Frequency-Selective Neural Oscillatory States

This paper introduces a Bayesian nonparametric method to identify frequency-selective neural oscillatory states without predefining frequency bands or fixing the number of states.

Stimulus and circuit contributions to the information geometry of neural manifolds

The paper develops a differential geometric framework to analyze how neural manifold geometry is shaped by feedforward and recurrent connectivity, showing feedforward connectivity determines representational geometry.

Deviance detection via competitive inhibition between local neocortical ensembles

This paper proposes a computational model of deviance detection in neocortical circuits based on competitive inhibition between neural ensembles, showing it can encode short-term stimulus memory and explain experimental observations.

Power-Law Adaptation Stabilizes Primary Sensory Encoding of Natural Variance

The paper shows how a multi-timescale sensory model with fractional adaptation tracks natural environmental fluctuations to maintain stable encoding and maximize coding efficiency.

Intrinsic representational drift from predictive excitatory-inhibitory plasticity

This study shows that representational drift in neural networks arises from predictive excitatory-inhibitory plasticity, with changes in neuron preferences and stable ensemble coding.

Area- and Layer-Specific Organization of Timescales in Macaque Motor Cortex

The paper uses single-unit spiking and LFP data to show M1 has longer temporal timescales than PMd, with LFP showing layer-dependent temporal dynamics.

Homeostatic Plasticity Enables Stable, Flexible, and Tunable Assemblies

This study shows that combining Hebbian plasticity with homeostatic inhibition allows for stable, tunable neuronal assemblies rather than binary outcomes.

How stimulation waveform shape affects collective oscillations in the brain networks

This study investigates how different tACS waveform shapes affect brain network oscillations, finding that sinusoidal and pulsed waveforms enhance global synchrony and reduce metastability, while others have weaker effects.

Decision signals in the absence of spiking activity in primate visual cortex

The paper investigates decision-related signals in primate visual cortex using LFPs, finding that high-frequency LFPs correlate with decisions and are causally involved, while lower frequencies reflect non-causal feedback and trial history.

Meta-learning leading to homeostatic plasticity stabilizes synaptic weights together with predictable activity levels

This paper introduces an extended meta-plasticity mechanism that stabilizes synaptic weights and activity levels while enabling adaptation to changing environments.

Bifurcation dynamics in a shared network beyond sensory areas characterize conscious auditory perception independently of report

The paper identifies shared neural networks and bifurcation dynamics across sensory and extra-sensory regions that predict conscious auditory perception regardless of task.

Modulation index-based phase-amplitude coupling does not encode temporal polarity

The paper shows that the modulation index (MI) in phase-amplitude coupling (PAC) does not capture temporal polarity, as inverting the phase of low-frequency oscillations does not change MI values.

A human intracranial map of consciousness returning from anesthesia

This study maps the electrophysiological changes in the human brain as consciousness returns from anesthesia, identifying key neural dynamics associated with the transition from unconsciousness to wakefulness.

Neural acceleration drives adaptations in working memory encoding speed

The paper identifies an accelerated neural code underlying adaptations in visual working memory encoding speed using EEG data analysis.

Revisiting post-stimulus theta activity: evidence for an aperiodic rather than oscillatory origin

This study challenges conventional time-frequency analyses by showing that post-stimulus theta power increases may reflect changes in aperiodic activity rather than genuine oscillations.

Inhibitory Gain and Hub Architecture Confer Dynamic Resilience to Microcircuit Degeneration

The paper investigates how inhibitory gain and hub architecture contribute to neural circuit resilience against degeneration by analyzing spiking networks with controlled pruning strategies.

BAYESIAN STATE-SPACE MODEL FOR JOINT INFERENCE OF OSCILLATORY DYNAMICS AND POINT-PROCESS COUPLING

This paper introduces a Bayesian state-space model to jointly infer oscillatory dynamics and spike-field coupling, showing improved frequency-specific estimates compared to classical methods.

A detailed investigation of Shared Variance Component Analysis as a tool to characterize neural dimensionality

The paper investigates SVCA and PCA to determine reliable neural dimensionality, finding that reliable dimensionality saturates with increasing neuron count and decreases with higher correlation.

Single-cell, single-shot stimulation reveals heterogeneous network recruitment not explained by standard functional properties.

The paper shows that single-cell stimulation in cortical networks leads to transient, heterogeneous responses not explained by the stimulated cell's functional state.

Spectral decompositions of neural voltage recordings are susceptible to model misspecifications that cause meaningful estimation error

This paper shows that common assumptions in spectral decomposition of neural voltage data lead to estimation errors and introduces a corrected method that improves accuracy in analyzing brain state changes.

Dynamic geometry remapping of neural activity within frontal and subcortical areas during decision-making

The paper shows that during decision-making, neural activity in frontal and subcortical areas dynamically changes, with geometry shifts reflecting decision difficulty and option evaluation.

A microcircuit model of astrocytic potassium buffering and neural synchronization

This study develops a microcircuit model to investigate how astrocytic potassium buffering and gap-junction coupling influence neuronal synchronization and prevent pathological states in the hippocampus.

Coordination of spike timing among the neurons of the cerebellum

The paper investigates how electrical coupling among inhibitory neurons in the cerebellum coordinates spike timing to enhance temporal precision in downstream neurons.

Disrupted Hippocampal Theta-Gamma Coupling and Spike-Field Coherence Following Experimental Traumatic Brain Injury

This study investigates changes in hippocampal oscillations after TBI, finding disrupted theta-gamma coupling and altered spike-field coherence in injured rats.