Connectome-based reservoir computing with the conn2res toolbox.

Journal: Nature communications
PMID: 38253577

Abstract

The connection patterns of neural circuits form a complex network. How signaling in these circuits manifests as complex cognition and adaptive behaviour remains the central question in neuroscience. Concomitant advances in connectomics and artificial intelligence open fundamentally new opportunities to understand how connection patterns shape computational capacity in biological brain networks. Reservoir computing is a versatile paradigm that uses high-dimensional, nonlinear dynamical systems to perform computations and approximate cognitive functions. Here we present conn2res: an open-source Python toolbox for implementing biological neural networks as artificial neural networks. conn2res is modular, allowing arbitrary network architecture and dynamics to be imposed. The toolbox allows researchers to input connectomes reconstructed using multiple techniques, from tract tracing to noninvasive diffusion imaging, and to impose multiple dynamical systems, from spiking neurons to memristive dynamics. The versatility of the conn2res toolbox allows us to ask new questions at the confluence of neuroscience and artificial intelligence. By reconceptualizing function as computation, conn2res sets the stage for a more mechanistic understanding of structure-function relationships in brain networks.

Authors

  • Laura E Suarez
    Department of Industrial Engineering, Universidad de los Andes, Bogotá, Colombia; Department of Materials Science and Engineering, University of Florida, Gainesville, FL 32601, USA. Electronic address: laura.suarez@mail.mcgill.ca.
  • Agoston Mihalik
    Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom; Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom. Electronic address: a.mihalik@ucl.ac.uk.
  • Filip Milisav
    McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC, Canada.
  • Kenji Marshall
    Department of Bioengineering, Stanford University, Stanford, CA, USA.
  • Mingze Li
    College of Intelligent Systems Science and Engineering, Harbin Engineering University, Nantong street, Harbin 150001, China.
  • Petra E Vértes
    Department of Psychiatry, University of Cambridge, Cambridge, CB2 0SZ, UK.
  • Guillaume Lajoie
    UW Institute for Neuroengineering, University of Washington, Seattle, Washington, US.
  • Bratislav Misic
    McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada.

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