Alejandro Pan-Vazquez

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.

This study investigates how VTA dopamine neuron activity shapes stimulus and action value representations in the striatum through conditioned reinforcement in mice.

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.

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.

The paper investigates how direct and indirect basal ganglia pathways influence cortical activity during decision-making, finding that they oppositely modulate a subset of neurons encoding decision variables.

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.

The paper shows that postingestive malaise signals reactivate amygdala flavor representations, strengthening memory and resolving temporal credit assignment in aversive learning.

UnitRefine automates spike sorting curation using machine learning models trained on expert annotations, achieving human-level performance across species and datasets.

The paper shows that pre-existing visual responses in dopamine terminals predict individual learning trajectories in mice during a visual task.

The paper shows that heightened lateral habenula activity during stress leads to lasting brainwide and behavioral susceptibility in mice.

The paper introduces two public websites for exploring large-scale electrophysiology data from the International Brain Laboratory, enabling cross-platform access to behavioral trials and neuronal data.

The paper introduces an infinite hidden semi-Markov model to analyze learning curves in mice, finding three major learning stages and behavior changes after rest periods.

This paper develops a standardized task for measuring decision-making in mice, showing reproducible results across multiple laboratories and providing a public dataset and tools.

This study shows that homeostatic plasticity rules govern axo-axonic synapse formation in chandelier cells, with activity changes during specific developmental windows altering synaptic connectivity.