The PMNLV model extends single-neuron overdispersion to populations via matrix-normal gain priors, showing shared co-variability highest in V1 and declining along the mouse visual hierarchy.
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V1 digital twins with comparable neural prediction accuracy differ in linear probe performance, unit tuning, and hidden-layer eigenspectra.
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Partitioning Neural Co-Variability
The PMNLV model extends single-neuron overdispersion to populations via matrix-normal gain priors, showing shared co-variability highest in V1 and declining along the mouse visual hierarchy.
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Beyond Neural Activity Prediction: Probing Latent Representations in Mouse V1 Digital Twins
V1 digital twins with comparable neural prediction accuracy differ in linear probe performance, unit tuning, and hidden-layer eigenspectra.