Neural dynamics and brain function

This paper introduces a neuroscience-inspired spiking neural network with feedback inhibition that enhances pattern separation and demonstrates its application in cognitive robotics.

The paper shows that inhibitory neurons with fewer recurrent connections can reduce synchrony caused by over-represented excitatory motifs in neuronal networks.

The paper uses a whole-brain model of an anesthetized macaque to simulate and restore consciousness through thalamic stimulation, showing how brain states transition during loss and recovery of consciousness.

The paper decodes temporal dynamics in frontostriatal circuits during decision making, identifying two dynamical motifs and a selective reorganization in the frontal orienting field at decision commitment.

This paper uses MEG data to create cross-frequency neurophysiological gradients that represent cortical organization, showing alignment with known functional and structural axes and disruptions in Parkinson's disease.

The paper examines how neural activity in the prelimbic cortex correlates with attentional behavior in mice during the rodent continuous performance test.

This study shows how task congruence affects neural coding geometry and population dynamics in mouse ALM, linking rule-switching complexity to cognitive flexibility.

This paper develops a model combining cortical state signals and visual stimuli to better predict neural responses in the visual cortex, showing improved accuracy for neurons with higher response variability.

The paper develops a PLSR framework to decompose neural activity in mouse V1 into stimulus and population subspaces, finding conserved coding schemes across layers.

This study shows rhythmic light stimulation elicits multiple neural responses at different frequencies that separately affect perception, with implications for neuromodulatory techniques.

The paper introduces Cleo, a simulation testbed for systems neuroscience experiments, integrating optogenetics, electrophysiology, and closed-loop control to improve experimental design and model validation.

The paper develops new statistical tools to analyze high-dimensional neural responses in mouse visual cortex, revealing a broken power law structure and highlighting the role of inhibitory neurons in shaping population representations.

This study shows D-amphetamine changes ECoG activity patterns in rat neocortex, reducing network organization and affecting multiple dimensions of principal component space.

The paper identifies hidden spiral dynamics underlying traveling waves in human neural activity during memory tasks using a new computational framework.

The paper investigates ephaptic-axonal interactions in developing cortical tissue and finds radial biases in neural activity patterns during self-organization.

This paper introduces Hierarchical Amplitude Modulation (HAM) as a mechanism for hierarchical information processing in the brain, showing how it produces observed spectral features through log-spaced frequency bands and 1/f power laws.

This paper presents a spiking network model of Layer 2/3 in V1 that computes sign-specific prediction errors through compartmentalized neurons without synaptic weight updates.

This paper shows that incorporating neurotransmitter receptor densities improves biophysically informed models of intracranial EEG spectra, linking molecular characteristics to cortical population dynamics.

The paper investigates whether cortical neurons projecting to the same target form specialized population codes, finding structured correlations that enhance information transmission during correct behavioral choices.

The paper shows that human working memory is supported by transient, burst-like neural activity rather than sustained firing, with distinct roles for cell types.

The paper identifies hierarchical replay of cross-region spiking motifs during working memory tasks in mice, revealing their role in maintaining perceptual memory.

The paper models how arousal drives behavioural state transitions in mice using a dynamical systems approach, showing arousal affects engagement in a visual decision-making task.

The paper shows that slow oscillations in the olfactory bulb and medial prefrontal cortex encode working memory representations through enhanced connectivity and bidirectional information transfer.

This study shows that perceptual judgments in mice are coupled to actions in the premotor cortex, with some cells encoding block identity during a vibrotactile detection task.

The paper shows that after distractions, neural activity in the prefrontal cortex returns to pre-disruption patterns through state-space rotations and traveling waves.

This study shows that cortical surface electrical stimulation in awake mice initially activates L2/3 neurons and then causes prolonged inhibition, altering sensory processing and neuronal selectivity.

The paper shows that recurrent neuronal networks near a phase transition amplify slow fluctuations during free recall, supported by simulations and human EEG data.

This study uses a whole-brain model to show that cholinergic heterogeneity enhances synchronization and information flow in brain dynamics.

The paper shows that a deterministic drive across brain regions predicts action timing, which synergizes with trial-specific and within-trial noise to time self-initiated actions.