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Showing 1–6 of 6 results
Advanced filters: Author: Taliah Muhammad 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
  • 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
  • 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 authors develop a deep learning approach that enables an efficient search of the input space to find the best stimuli for modeled neurons. When tested, these stimuli are most effective at driving their matching cells in the brain.

    • Edgar Y. Walker
    • Fabian H. Sinz
    • Andreas S. Tolias
    Research
    Nature Neuroscience
    Volume: 22, P: 2060-2065
  • Dense calcium imaging combined with co-registered high-resolution electron microscopy reconstruction of the brain of the same mouse provide a functional connectomics map of tens of thousands of neurons of a region of the primary cortex and higher visual areas.

    • J. Alexander Bae
    • Mahaly Baptiste
    • Chi Zhang
    ResearchOpen Access
    Nature
    Volume: 640, P: 435-447