Hideaki Shimazaki

The paper investigates how stimulus information in high-dimensional neural activity scales with population size in mouse V1, finding that scale-invariant noise does not limit information as population size increases.

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.

This paper uses active inference to model zebrafish neuronal dynamics during a go/no-go task, predicting individual learning trajectories and behavioural changes.

This paper shows canonical neural networks perform active inference by minimizing variational free energy through delayed plasticity and threshold adaptation.

The paper uses a neuron model to infer hidden microcircuit structures from neuronal activity data by analyzing input-output relations and interaction patterns.

This paper introduces a generative model for natural scenes that uses complex domain signals and non-uniform phase priors, showing improved performance in blind source separation and revealing phase-sensitive complex cells in the visual cortex.

This study shows adult zebrafish use future state prediction errors to guide active avoidance behavior in a virtual reality setup.