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Topic: raphe nucleus

Seminar
1 seminar

In Artificial Intelligence and Behavioral Neuroscience

Seminar · Computational Neuroscience

Recurrent network models of adaptive and maladaptive learning

Kanaka Rajan · Icahn School of Medicine at Mount Sinai

Wed, Apr 8, 2020 · 13:00 UTC

During periods of persistent and inescapable stress, animals can switch from active to passive coping strategies to manage effort-expenditure. Such normally adaptive behavioural state transitions can become maladaptive in disorders such as depression. We developed a new class of multi-region recurrent neural network (RNN) models to infer brain-wide interactions driving such maladaptive behaviour. The models were trained to match experimental data across two levels simultaneously: brain-wide neural dynamics from 10-40,000 neurons and the realtime behaviour of the fish. Analysis of the trained R