Stronger inhibitory-to-excitatory synapses in working-memory RNNs reproduce inhibitory dominance, excitatory hypofunction, and task impairment, while resilience training preserves performance at the cost of generalization to longer delays.
Recurrent neural network models for working memory of continuous variables: activity manifolds, connectivity patterns, and dynamic codes
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Modelling chronic stress as an excitatory-inhibitory perturbation in recurrent working-memory networks
Stronger inhibitory-to-excitatory synapses in working-memory RNNs reproduce inhibitory dominance, excitatory hypofunction, and task impairment, while resilience training preserves performance at the cost of generalization to longer delays.