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Showing 1–3 of 3 results
Advanced filters: Author: Manuel Beiran Clear advanced filters

  • The authors show that connectome datasets alone are generally not sufficient to predict neural activity. However, pairing connectivity information with neural recordings can produce accurate predictions of activity in unrecorded neurons.

    • Manuel Beiran
    • Ashok Litwin-Kumar
    Research
    Nature Neuroscience
    Volume: 28, P: 2561-2574

  • A ‘programming’-like approach provides a one-step algorithm to find network parameters for recurrent neural networks that can model complex dynamical systems.

    • Manuel Beiran
    • Camille A. Spencer-Salmon
    • Kanaka Rajan
    News & Views
    Nature Machine Intelligence
    Volume: 5, P: 570-571

  • Neural computations are envisioned as arising from either distinct function subpopulations or distributed collective dynamics. Dubreuil and Valente et al. examined recurrent neural networks trained on various cognitive tasks and found that a mixed-selective yet non-random subpopulation structure enabled flexible responding through gain-modulated latent dynamics.

    • Alexis Dubreuil
    • Adrian Valente
    • Srdjan Ostojic
    Research
    Nature Neuroscience
    Volume: 25, P: 783-794