Yann Zerlaut

The paper identifies distinct dendritic integration strategies in two types of cortical interneurons that lead to different temporal dynamics of inhibition.

The paper shows that locomotor activity recruits SST-INs in S1 but not V1 cortex, suggesting feedforward sensory pathways and neuromodulation influence their activity during behavioral state transitions.

The paper develops a method to classify network states from local field potentials in awake mice, showing that population signals predict single-cell activity across different network states.

The paper shows that vesicular zinc modulates NMDA receptor activity in cortical neurons, affecting dendritic function and synaptic plasticity under in vivo-like conditions.

The paper develops a mean-field formalism to predict the collective dynamics of large networks of complex spiking neurons, linking population models to electrophysiology.

This paper demonstrates how spiking neuron networks with moderate recurrent interactions generate a spectrum of non-rhythmic waking states in the neocortex, showing how different states encode presynaptic activity or afferent input strength.

The paper investigates how suppressive waves in V1 shape the representation of long-range apparent motion using voltage-sensitive dye imaging in monkeys.

The paper develops a mean-field model of neural networks to simulate and predict voltage-sensitive dye imaging signals in the visual cortex.

The paper develops a theoretical framework to analyze how firing responses in layer V pyramidal neurons vary with presynaptic activity, revealing heterogeneous coupling mechanisms.