Matthew R Whiteway

This paper introduces a framework for multi-view animal pose estimation that improves accuracy and uncertainty estimation with limited labeled data, validated across multiple species.

Mice infer stimulus-side priors from recent choices; prior signals are decodable pre-stimulus in 24.0% to 30.2% of 242 brain regions, including early visual and motor areas.

This study investigates the neural mechanisms of cooperation in mice, showing that the medial prefrontal cortex encodes leadership dynamics and social value maps in an asymmetric, role-specific manner.

The paper shows that mice with ASD-related mutations exhibit similar computational and neural anomalies in prior updating during decision-making.

This study evaluates the reproducibility of electrophysiological measurements across ten labs using standardized protocols and finds that variability in electrode targeting and statistical methods affects reproducibility.

This study investigates turn-taking aggressive behavior in Siamese fighting fish, identifying a brain region involved in persistence but not coordination of social interactions.

The paper uses SCAPE microscopy to analyze neural activity in Drosophila brains during different behaviors, revealing both behavior-related and residual high-dimensional activity patterns.

The paper describes a modular data architecture for a neuroscience collaboration, enabling data contribution, access, and analysis across multiple labs.

This paper introduces a video analysis tool that combines supervised pose estimation with unsupervised dimensionality reduction to extract interpretable behavioral features from animal videos, improving downstream analyses.

Each recorded population gets its own latent dynamics, a discrete state sets how the populations couple, and the switch rules say which population triggers the change.

This paper introduces a decoding framework that leverages low-dimensional latent variables to improve decoding performance in neural population activity.

This paper introduces nonlinear latent variable models to analyze shared variability in neural populations and finds that different brain regions exhibit distinct nonlinear structures.

The paper examines how visual motion affects behavioral responses and neural coding in the mouse visual thalamus, finding that back-to-front motion biases population responses during stillness.

The paper uses automated image segmentation to study spatial organization of sound dynamics in mouse auditory cortex, revealing differences in response to sound onset and offset.

This paper introduces a rectified latent variable model to identify unobserved factors influencing cortical activity in neural recordings and shows it outperforms traditional methods.