Michael Okun

Heteroskedasticity of neuronal population responses

The paper identifies heteroskedasticity in neuronal population responses across conditions, showing it reflects biophysical variance and influences optimal readout strategies.

Disassociating cerebral vasomotion from low frequency spontaneous neurovascular coupling

This study investigates cerebral vasomotion in anaesthetised rats, finding it driven by the arterial tree and largely independent of neural activity.

Multi-day Neuron Tracking in High Density Electrophysiology Recordings using EMD

This paper introduces a neuron tracking method using non-rigid alignment of spike sorted clusters to identify the same neurons across multiple days in high density electrophysiology recordings, achieving an 84% average recovery rate.

Stretching and squeezing of neuronal log firing rate distribution by psychedelic and intrinsic brain state transitions

This study examines how psychedelic drugs and intrinsic brain state transitions affect neuronal firing rate distributions in mice, revealing a common pattern of stretching and squeezing in log-rate distributions across different brain states.

Neuropixels 2.0: A miniaturized high-density probe for stable, long-term brain recordings

The paper introduces Neuropixels 2.0, a high-density probe for long-term brain recordings, and demonstrates its stability across months in multiple labs and species.

Equations governing dynamics of excitation and inhibition in the mouse corticothalamic network

The paper shows that mean-field models of cortical dynamics require inclusion of thalamic interactions to accurately predict responses to optogenetic stimulation in awake mice.

Neural basis of learning guided by sensory confidence and reward value

This study investigates how mice integrate sensory confidence and reward value in decision-making and learning, revealing distinct roles for frontal and dopamine neurons.

Distinct structure of cortical population activity on fast and infraslow timescales

The paper analyzes cortical spiking dynamics across fast and infraslow timescales in mice, revealing distinct coupling patterns between individual neurons and population activity.

Inhibitory control of shared variability in cortical networks

This study develops a deterministic spiking network model to analyze multi-neuron recordings and shows that feedback inhibition controls noise correlations in cortical networks.

Long term recordings with immobile silicon probes in the mouse cortex

This study shows that immobile silicon probes can provide stable, long-term neuronal recordings in mice for several months without microdrives.