Zhiwei Ding

Functional connectomics reveals general wiring rule in mouse visual cortex

Functionally similar neurons in mouse visual cortex connect preferentially across layers and areas, including feedback, and feature tuning, not receptive-field position, predicts synapses beyond axon-dendrite proximity.

Foundation model of neural activity predicts response to new stimulus types and anatomy

This paper trains a foundation model on neural activity data to predict responses to new stimuli and anatomical features, showing strong generalization across mice and tasks.

Bipartite invariance in mouse primary visual cortex

The paper identifies a novel bipartite invariance in mouse V1 neurons, where receptive fields encode shift-invariant high-frequency textures and fixed low-frequency patterns, contributing to segmentation.

Pattern completion and disruption characterize contextual modulation in the visual cortex

The paper uses CNNs to analyze contextual modulation in visual cortex by synthesizing surround patterns, finding that pattern completion enhances responses while disruption suppresses them, consistent across mice and macaques.

It takes neurons to understand neurons: Digital twins of visual cortex synthesize neural metamers

The paper synthesizes neural metamers for the mouse visual system using deep encoding models and shows they reproduce neural activity across different animals.

Digital twin reveals combinatorial code of non-linear computations in the mouse primary visual cortex

The paper uses digital twins to characterize the functional organization of mouse V1, revealing a combinatorial code of nonlinear response properties across 30 modes.

A flow-based latent state generative model of neural population responses to natural images

This paper introduces a flow-based generative model to capture neural population responses to natural images, outperforming existing models in predicting variability and learning latent factors related to behavior and brain area.