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4 seminars

Newest first

How Brain Circuits Function in Health and Disease: Understanding Brain-wide Current Flow

Kanaka Rajan · Icahn School of Medicine at Mount Sinai, New York

…across multiple brain regions— called Current-Based Decomposition (CURBD). This new approach enables the computation of excitatory and inhibitory input currents that drive a given neuron, aiding in the discovery of how entire populations of neurons behave across multiple interacting brain regions. Dr. Rajan’s team has applied this method to studying the neur

Wed, Apr 14, 2021 · 16:00 UTC

Computational Neuroscience

Inferring brain-wide interactions using data-constrained recurrent neural network models

Matthew Perich · Rajan lab, Icahn School of Medicine at Mount Sinai

…In this talk, I will introduce Current-Based Decomposition (CURBD), an approach for inferring multi-region interactions using data-constrained recurrent neural network models. I will first show that CURBD accurately isolates inter-region currents in simulated networks with known dynamics. I will

Wed, Mar 24, 2021 · 17:00 UTC

Computational Neuroscience

…We call this framework CURrent-Based Decomposition (CURBD). CURBD employs recurrent neural networks (RNNs) directly constrained, from the outset, by time series measurements acquired experimentally, such as Ca2+ imaging or electrophysiological data. Once trained, these da

Fri, Mar 12, 2021 · 06:00 UTC

Computational Neuroscience

Inferring brain-wide current flow using data-constrained neural network models

Kanaka Rajan · Icahn School of Medicine at Mount Sinai

…We call this framework CURrent-Based Decomposition (CURBD). CURBD employs recurrent neural networks (RNNs) directly constrained, from the outset, by time series measurements acquired experimentally, such as Ca2+ imaging or electrophysiological data. Once trained, these dat

Wed, Nov 18, 2020 · 05:00 UTC

Computational Neuroscience