Zeinab Mohammadi

This study examines age-related changes in neural and behavioural variability during a decision-making task in mice, finding increased neural variability and reduced variability quenching in specific brain regions.

The paper develops an internal state model to analyze decision-making in mice, finding that behavior is governed by four states with distinct performance and bias characteristics.

The paper presents a brain-wide neural activity map from 621,733 neurons across 139 mice performing a decision-making task, showing how neural activity encodes task variables across brain regions.

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.

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

The paper introduces GEMsort, a multichannel neural spike sorting algorithm that reduces data volume and improves sorting speed using signal processing modifications.