Neural dynamics and brain function

This study shows that L6CT neuron activation induces high gamma oscillations in the cortex through cortico-thalamo-cortical and intracortical pathways, with the latter shaping oscillation frequency.

This study identifies high-dimensional rotational dynamics in neural activity during working memory tasks in monkeys, challenging existing theories of persistent or feedforward activity.

This paper introduces a framework for geometry-constrained coupling between neural manifolds, showing how inter-manifold interactions reorganize dynamics and produce critical transitions in brain activity.

This study investigates sequential working memory using MEG data, finding that neural subspaces organize memory during retention but not during encoding, while no sequential replay was observed.

The paper introduces an integrated Ising model with global inhibition to explain decision-making, showing it can improve accuracy and has unique learning properties.

This paper identifies universal dynamic routing modes in human cortical activity that are consistent across individuals and brain states, and links their disruption to Alzheimer's disease.

This study investigates how rats adjust the timescale of evidence evaluation in the posterior parietal cortex during auditory change detection tasks, finding transient neuronal responses and gain changes linked to decision urgency.

The paper proposes a model where calcium signaling regulates excitatory and inhibitory synapses to maintain balanced cortical activity through homeostatic plasticity.

The paper investigates frequency tuning in human neurons using intracranial recordings and finds 27% of neurons show firing preferences within specific oscillatory frequencies, particularly low-theta.

This study identifies a drift in neural activity in the posterior parietal cortex during delay periods as a key factor in short-term memory errors in mice.

Mice infer stimulus-side priors from recent choices; prior signals are decodable pre-stimulus in 24.0% to 30.2% of 242 brain regions, including early visual and motor areas.

The paper presents a brain-wide neural activity map from 621,733 neurons across 139 mice performing a decision-making task, showing how neural activity encodes task variables across brain regions.

This study compares a dopamine-modulated mean-field model with its corresponding spiking network to evaluate the model's accuracy in capturing network dynamics.

This paper introduces PRISM plasticity, a unified model of synaptic plasticity rules, and shows it enables rapid learning of flexible neural dynamics and solves temporal credit assignment in machine learning.

The paper analyzes intrinsic neural timescales across the entire mouse brain, revealing spatial patterns and a multiscale architecture of timescale diversity.

This study shows higher baseline alpha power is linked to faster visual search performance, challenging the idea that alpha oscillations reduce visual processing.

This paper investigates how nonlinear neural manifolds are learned in feed-forward networks using spike-timing dependent plasticity, showing that simple plasticity mechanisms can generate structured receptive fields.

The paper analyzes EEG data from a large cohort to show aperiodic neural activity decreases monotonically with age, while periodic activity increases then decreases, mapping to distinct biological processes.

The paper develops a new motif detection algorithm to analyze neural activity in auditory cortex, revealing parallel encoding schemes at single neuron and population levels.

The paper investigates how rhythmic network states influence communication subspaces between hippocampal and prefrontal cortex regions during a spatial memory task in rats, finding that shared subspaces rather than local activity correlate with behavior.

The paper shows that synchronous bimodal sensory stimulation at 5 Hz transiently increases the oscillation frequency in basolateral amygdala neurons.

The paper investigates how semantic elaboration affects alpha-beta oscillations during narrative memory encoding and retrieval, finding increased desynchronisation with information accumulation and negative correlation with retrieval success.

This paper develops a gated recurrent variational autoencoder to decode decision-making from neuronal data in monkeys, showing comparable accuracy in multidimensional feature space.

This study identifies coordinated multi-level neural adaptations in mouse neocortical areas during task learning, showing increased neuronal responses, population-level changes, and inter-area interactions.

The paper proposes a novel mechanism of heterogeneous synaptic upscaling during wakefulness that enhances information propagation in the cortex.

The paper develops a biophysical model of the mouse thalamocortical circuit to show that closed-loop connectivity best reproduces thalamic activity during wakefulness and sleep.

The paper uses a computational model of delay-coupled oscillators to match MEG functional connectivity patterns, finding that meta-stable dynamics with small delays explain observed oscillatory coupling.

This paper investigates how the geometry of neural activity in recurrent networks depends on connectivity structure and input dimensionality, revealing how activity subspace dimensions relate to connectivity rank and input configuration.

This study investigates the relationship between theta oscillations and attentional exploration in spatial and feature-based attention using EEG in humans.

This study shows that parvalbumin interneurons regulate spontaneous hemodynamic fluctuations by linking gamma oscillations to cerebral blood flow dynamics.