Séverine Durand

The paper shows that moving visual stimuli elicit topographic and directional responses in most entorhinal neurons, revealing visual input's role in shaping their activity.

This study shows psilocybin disrupts visual change detection by altering cortical dynamics, particularly in SST interneurons, leading to increased surprise signals.

The paper presents a database of spiking activity in the mouse visual system during an image change detection task, revealing task-specific coding patterns across brain regions.

The paper identifies a sparse set of neurons in the mouse visual cortex that mediate illusory contour inference through recurrent pattern completion.

The paper analyzes neuronal variability across brain states to understand how factors like internal dynamics, behavior, and stimuli influence sensory processing over time.

The paper challenges the conventional view of mouse higher visual cortex by proposing a unified-V2 hypothesis and presents a dataset for testing alternative models.

This study challenges hierarchical predictive coding models by showing that prediction error responses in visual cortex do not involve feedforward processing and that predictive suppression is not mediated by inhibitory interneurons.

The paper uses population network models and public datasets to analyze how cortical circuits adapt to stimulus novelty, finding weaker connections and shifts in neural population dynamics.

SHIELD enables large-scale electrophysiological recordings in mice by providing a skull-shaped implant for repeated multi-probe insertions across brain regions.

This study compares neuronal responses in visual cortex using electrophysiology and two-photon imaging in awake mice, finding differences in responsiveness and selectivity and exploring data transformations to reconcile them.

The paper presents a dataset and analysis of spiking activity across multiple mouse visual areas, revealing that functional connectivity mirrors anatomical hierarchy.

The paper tracks spiking activity across six levels of the mouse visual hierarchy to identify two multi-regional communication modules with distinct signal flow and functional roles.

The paper investigates how neural representations transform from dLGN to V1 in mice, finding evidence for both sparse coding and linear separability.

The paper identifies direction-reversing neurons in the mouse visual system that change their preferred motion direction under different spatiotemporal stimuli, supported by an asymmetric filter model.

The paper develops a biophysically detailed in silico model of layer 4 of the mouse primary visual cortex, showing how functional synaptic connectivity reproduces experimental observations of neuronal responses to visual stimuli.