Neural dynamics and brain function

This study examines how the human alpha rhythm and intrinsic neural timescales develop across the sensorimotor-to-association cortical hierarchy in epilepsy patients.

This paper develops a multiscale computational framework to study how brain criticality at local and global scales interacts through structural connectivity.

This paper evaluates the universality and reliability of a spectrolaminar motif in primate neocortex, finding it not universal and methods unreliable.

The paper investigates how intrinsic neural timescales develop across adolescence in multiple species, finding reductions linked to improved cognitive function and structural changes.

The paper introduces a graph embedding algorithm to identify symmetries in neural connectomes, demonstrating its ability to detect rotational, translational, and toroidal symmetries in Drosophila and synthetic grid cell connectomes.

This paper introduces a multi-modal, multi-species, and multi-task latent-space model to decode consciousness levels from neural recordings, achieving cross-species and zero-shot transfer.

The paper shows that cortical population events are generated by hierarchical modularity and distance-dependent connectivity, not attractor dynamics.

This paper integrates the Larter-Breakspear model into a mouse brain connectome to study chaotic dynamics and ion-channel effects on network behavior.

The paper shows that co-tuned neuronal ensembles in the auditory cortex rapidly rebalance their activity in response to stimulation to maintain consistent perceptual processing.

The paper investigates how parvalbumin interneurons contribute to the development of gamma oscillations and crosshemispheric synchrony in the prefrontal cortex during aging.

The paper introduces FDTest, a method to detect memory effects in brain dynamics by violating the Fluctuation-Dissipation Theorem, showing stronger memory in wakefulness than sleep.

This study shows that causal spike-timing-dependent plasticity (STDP) prevents neuronal assemblies from merging when they share neurons, maintaining their distinct identities.

The paper tests methods for deriving connectivity from spiking activity in detailed cortical microcircuits and finds that activation paradigms significantly affect derivation accuracy.

The paper decodes stimulus identity and network state from calcium imaging in mice across different anesthesia states, showing preserved stimulus information even during deep anesthesia.

This study identifies high-frequency activity bursts as markers of fast, long-range brain communication during spatial attention tasks, showing their role in behavioral accuracy and network synchronization.

This study investigates how the locus coeruleus-norepinephrine system influences the coupling between pupil-linked arousal and cortical state using optogenetics, EEG, and machine learning.

The study examines how neurophysiological traits evolve across the lifespan using MEG data from 1,000 individuals, finding age-related shifts in brain regions associated with individuality and genetic influences.

This study investigates neural markers of auditory working memory load using EEG, finding that alpha-band oscillations, not lateralized responses like CDA, reflect dynamic coding of load.

The paper examines alpha modulation of spiking activity in multiple brain regions of mice during a tactile detection task, finding differences in modulation across regions and cell types, and a correlation with task performance.

The paper investigates how internal states affect decision-making by inactivating the posterior parietal cortex in mice and analyzing behavioral and neural changes.

This study investigates the claustrum's role in modulating prefrontal cortex neuronal activity, finding it enhances variability and network homogeneity through optogenetic stimulation and silencing.

This study shows that preprocessing steps in electrophysiological data can significantly affect spike correlation analysis results and proposes a correction method.

This paper introduces split-trial analysis to quantify information-limiting noise in neural population codes, finding substantial noise in the mouse head direction system and consistent noise in macaque prefrontal cortex.

This study trains a bimodular spiking actor-critic network on an economic choice task to explore how value and action representations emerge in distributed neural circuits.

The paper investigates how coordinated activity across multiple layers of macaque motor cortex encodes task-relevant information during a delayed match-to-sample task.

The paper identifies a timescale hierarchy in marmoset neocortex using ECoG data and develops a multi-regional model to explain signal integration and propagation.

This study examines age-related changes in theta and alpha oscillations during working memory tasks, finding that older adults use alpha-mediated compensation to maintain performance despite reduced theta activity.

This paper improves neural decoding by exploiting correlations across trials and sessions, showing better accuracy for four behaviors in mice using interpretable models.

This study identifies a cholinergic mechanism that modulates task-dependent cortical activity during evidence accumulation in mice.