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Showing 1–5 of 5 results
Advanced filters: Author: Jiakun Fu Clear advanced filters
  • This study uses the inception loop framework to map neuronal invariances in mouse V1, revealing a bipartite receptive-field organization linked to segmentation and a synaptic-level hierarchy of increasing invariance supported by the MICrONS dataset.

    • Zhiwei Ding
    • Dat Tran
    • Andreas S. Tolias
    ResearchOpen Access
    Nature Neuroscience
    P: 1-13
  • A foundation model trained on neural activity of visual cortex from multiple mice accurately predicts responses to video stimuli and cell types, dendritic features and connectivity within the MICrONS functional connectomics dataset.

    • Eric Y. Wang
    • Paul G. Fahey
    • Andreas S. Tolias
    ResearchOpen Access
    Nature
    Volume: 640, P: 470-477
  • The MICrONS mouse visual cortex dataset shows that neurons with similar response properties preferentially connect, a pattern that emerges within and across brain areas and layers, and independently emerges in artificial neural networks where these ‘like-to-like’ connections prove important for task performance.

    • Zhuokun Ding
    • Paul G. Fahey
    • Andreas S. Tolias
    ResearchOpen Access
    Nature
    Volume: 640, P: 459-469
  • Cortical activity is modulated by an intricate network of feedforward and feedback connectivity. Here the authors demonstrate distinct organizational rules govern feedback projections from lateral medial area to V1 versus projections from vibrissal M1 to vibrissal S1.

    • Shan Shen
    • Xiaolong Jiang
    • Andreas S. Tolias
    ResearchOpen Access
    Nature Communications
    Volume: 13, P: 1-14