Richard Naud

Sep 13, 2024 | biorxiv.org | Michael Lynn |Richard Naud |Jean-Claude Béïque |Len Maler

AbstractThe serotonergic dorsal raphe nucleus (DRN) receives diverse long-range synaptic inputs, yet the processing rules governing their contribution to DRN output spiking patterns are largely unknown. Here, we use electrophysiological, optogenetic and computational approaches to compare electrophysiological features of two major excitatory inputs onto DRN 5-HT neurons - the lateral habenula (LHb) and medial prefrontal cortex (mPFC).

Jul 23, 2024 | biorxiv.org | Richard Naud

AbstractThe field of neuromorphic engineering addresses the high energy demands of neural networks through brain-inspired hardware for efficient neural network computing. For on-chip learning with spiking neural networks, neuromorphic hardware requires a local learning algorithm able to solve complex tasks. Approaches based on burst-dependent plasticity have been proposed to address this requirement, but their ability to learn complex tasks has remained unproven.

Dec 10, 2023 | physoc.onlinelibrary.wiley.com | Richard Naud |Andre Longtin

André Longtin Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON, Canada Department of Physics, University of Ottawa, Ottawa, ON, Canada Center for Neural Dynamics, University of Ottawa, Ottawa, ON, Canada Brain and Mind Research Institute, University of Ottawa, Ottawa, ON, CanadaSearch for more papers by this author

Oct 2, 2023 | biorxiv.org | Xingyun Wang |Jean-Claude Béïque |Richard Naud

AbstractSynaptic plasticity is a core basis for learning and adaptation. Determining how synapses are altered by local signals, the learning rules, is the hinge about which brain activity pivots.