Lin Zhong

A critical initialization for biological neural networks

The paper shows that large-scale neural recordings in mice exhibit dynamical properties similar to those of a critically normalized random symmetric matrix, suggesting a critical initialization for biological neural networks.

Linking neural representations to behavior using generalization

The paper links neural representations to behavior by testing mice's responses to new stimuli and finding that neural discrimination correlates with behavioral performance in specific visual areas.

Orofacial behaviors, not eye movements, govern neural activity in mouse visual cortex

This study shows that orofacial movements, not eye movements, primarily drive neural activity in mouse visual cortex during free viewing.

Dendritic computation for rule-based flexible categorization

The paper shows that dendritic computation in ET cortical neurons enables rule-dependent flexible categorization by integrating sensory input and inferred task rules.

Rastermap: a discovery method for neural population recordings

Rastermap is a visualization method for neural data that sorts neurons along a one-dimensional manifold to reveal activity patterns in high-dimensional recordings.

Equivariant neuronal populations enable simultaneous tuning and invariance

The paper investigates how neuronal populations encode visual scenes invariant to perspective changes, finding equivariant structures in higher-order visual areas.

Distinct streams for supervised and unsupervised learning in the visual cortex

The paper investigates whether perceptual learning in mice is due to supervised or unsupervised learning by analyzing neural activity in visual cortex during task learning and unrewarded exposure.

Facemap: a framework for modeling neural activity based on orofacial tracking

Facemap models neural activity using orofacial tracking, improving prediction accuracy and explaining more variance in visual cortex neurons.

Dynamic and causal contribution of parietal circuits to perceptual decisions during category learning

This study investigates the role of parietal circuits in decision-making during category learning using mice, showing their dynamic and causal contribution to categorizing new auditory stimuli.