Mikio Aoi

The paper shows that changes in gaze behavior over time can induce representational drift in visual cortex by altering neural responses to the same stimuli.

This study uses C. elegans to show that foraging decisions involve a switch from exploration to exploitation based on sensory input, satiety, and learned environmental statistics.

The paper analyzes neural activity in marmoset frontal cortex during natural vocal behaviors using a GLM model, finding distributed functional organization rather than distinct subfield specialization.

The paper introduces a model-free measure called effective number of shared dimensions (ENSD) to quantify shared structure between datasets, demonstrating its utility across neural networks and neuroscience data.

This paper develops a theoretical framework explaining individual variability in decision-making by analyzing neural and behavioral data from rats performing a context-dependent task.

The paper trains a recurrent neural network to model decision-making in monkeys, revealing grid-like fixed points in network dynamics for context-dependent tasks.

The paper investigates multi-dimensional dynamic encoding in prefrontal cortex during decision-making in monkeys, revealing time-evolving representations of decision variables and context.

This paper introduces SNP-GPFA, a Gaussian process factor model to separate signal and noise in neural population activity, showing noise perturbs activity orthogonal to signal.

The paper develops scalable Bayesian methods for estimating high-dimensional neural receptive fields, achieving fast and memory-efficient inference.