Matthew N. McCarroll

This paper introduces a high-throughput 24-camera array microscope for automated 3D behavioral analysis of zebrafish larvae, enabling accurate tracking and morphological dynamics at high frame rates.

The paper trains a deep metric learning model on zebrafish behavioral profiles to identify neuroactive compounds, achieving better performance than correlation distance and validating predictions with in vitro assays.

This paper introduces a novel single objective light-sheet microscope that achieves high resolution, large field of view, and multi-view imaging for various biological systems.

This paper introduces an open platform for classifying neuroactive compounds in zebrafish using phenotypic responses and provides a large dataset of drug effects.