Neural dynamics and brain function

Dynamic shifts in brain criticality support cognitive processing

This study examines how critical dynamics in the hippocampus shift during learning and sleep to support cognitive functions.

Resting state periodic and aperiodic brain oscillations from birth to preschool years: Aperiodic maturity predicts developmental course

This study examines resting-state brain oscillations in children aged 2 to 68 months, finding that aperiodic measures mature nonlinearly and predict developmental outcomes.

Spatially targeted inhibitory rhythms differentially affect neuronal integration

The paper investigates how spatially targeted inhibitory rhythms affect neuronal integration in a layer 5 pyramidal neuron model.

Global error signal guides local optimization in mismatch calculation

The paper introduces a three-factor learning rule to model how global signals guide local synaptic updates for mismatch computation in sensory areas.

Online supervised learning of temporal patterns in biological neural networks under feedback control

This paper develops a closed-loop biological neural network system that learns and generates temporal patterns through feedback control, demonstrating adaptability and reduced synchronization.

Instantaneous Beta Frequency Regulates Self-Generated Timing in Humans

This study shows that instantaneous beta frequency in humans dynamically controls self-generated timing by predicting duration production.

Baseline activity of V1 interneurons connects pupil-linked arousal to engaged behavioral state

The paper shows that baseline activity of V1 interneurons mediates the relationship between pupil-linked arousal and engaged behavioral state in mice and humans.

Inferring state-dependent functional circuit motifs using higher-order interactions analysis

The paper introduces CHOIR, a method to analyze higher-order interactions in neuronal recordings, revealing circuit motifs associated with different brain states and activity patterns in mice.

Rebound Relays and Inhibitory Vetoes Stabilize Sparse Sequential Activity in HVC

The paper develops a biophysically grounded model of HVC network dynamics to explain how inhibition structures sparse sequential activity in songbirds.

Stiefel Manifold Dynamical Systems for Tracking Representational Drift

This paper introduces SMDS, a model that accounts for representational drift in neural data, outperforming LDS in log-likelihood and requiring fewer latent dimensions.

Switching from tonic to burst firing creates an attractor in synaptic weight dynamics

The paper shows that switching between tonic and burst firing in neural networks creates a burst-induced attractor in synaptic weight dynamics, which stabilizes synapses and supports memory consolidation.

Computing the effects of excitatory-inhibitory balance on neuronal input-output properties

The paper derives probabilistic rules for combining excitatory and inhibitory inputs in neural circuits to explain how neurons respond to stimuli and modulate their input-output properties.

A flexible quality metric for electrophysiological recordings across brain regions and species

The paper introduces a new quality metric for electrophysiological recordings that adapts to varying refractory period durations across brain regions and species.

Selective control of prefrontal neural timescales by parietal cortex

This study investigates how parietal cortex inactivation affects intrinsic neural timescales in the frontal eye field, revealing distinct neuronal dynamics and functional roles.

A transition-prone brain state precedes spontaneous behavioral switching

The paper identifies a whole-brain transition-prone state that predicts spontaneous behavioral switches in mice using functional ultrasound imaging and optogenetics.

Arousal elicits a brain-wide hemodynamic wave independent of locus coeruleus noradrenergic tone

The paper identifies a brain-wide hemodynamic wave associated with arousal that occurs independently of locus coeruleus noradrenergic activity.

Education Shapes the Link Between EEG Aperiodic Components and Cognitive Aging

This study shows that education moderates the relationship between age-related changes in EEG aperiodic components and cognitive performance, with different patterns observed in individuals with varying education levels.

An Efficient Computing Theory of Prefrontal Structured Working Memory Representations

The paper develops an efficient computing theory to explain optimal representations in prefrontal cortex working memory tasks, showing compositional and contextual codes as extremes of a spectrum determined by task structure.

Cortical Field Model of Complex Spiral Traveling Waves

The paper proposes a spatiotemporal cortical field model to simulate complex spiral traveling waves and their dynamics in local cortical circuits.

Linking Neural Manifolds to Circuit Structure in Recurrent Networks

This paper connects cortical circuit models with low-dimensional population dynamics using a recurrent spiking network model and demonstrates a method to retrieve circuit structure from recordings.

An energy information trade-off explains hidden structure in the neuronal parameter space

The paper shows that neuronal parameter diversity is structured by energy-information trade-offs, forming a Pareto front in parameter space.

Functional reorganization of motor cortex connectivity during learning

This study shows how rapid learning in mice involves structured changes in motor cortex connectivity, rerouting preparatory activity to control a conditioned neuron.

Inhibitory feedback enables predictive learning of multiple sequences in neural networks

This study shows that inhibitory feedback combined with predictive learning allows neural networks to efficiently anticipate and classify multiple spike sequences.

The Geometry of Cognitive Difficulty: A Dynamical Manifold Theory in Excitable Neural Networks

The paper introduces a dynamical manifold theory of cognitive difficulty using excitable neural networks, showing difficulty emerges as a multidimensional structure rather than a single scalar value.

Cascades and convergence: dynamic signal flow in a synapse-level brain network

The paper simulates sensory signal propagation in the Drosophila connectome to study modality-specific cascades and neuron classification based on dynamic response profiles.

Distributional invariance and proportional scaling in axonal conduction

The paper quantifies conduction velocity changes along axonal branches and finds a right-skewed distribution of velocity ratios that is invariant across branch lengths and neuron positions.

Self-Organizing Neural Networks in Organoids Reveal Principles of Forebrain Circuit Assembly

This study uses mouse forebrain organoids to show how variations in cellular composition influence the self-organization of neural circuits, revealing intrinsic principles of forebrain circuit assembly.

Simplified model of intrinsically bursting neurons

The paper introduces a simplified model of intrinsically bursting neurons that balances biological realism with practical usability for circuit simulations.

Data-derived agents reveal dynamical reservoirs in mouse cortex for adaptive behavior

The paper uses data-derived agents to study neural dynamics in mouse cortex, revealing chaotic attractors that support robust and adaptable behavior.

Alpha oscillations track the projection of reactivated memories into conscious awareness

The paper investigates whether hippocampal memory reactivation ensures overt recall, finding that alpha oscillations predict recall rather than reactivation alone.