We present an original neural network model, based on oscillating neural masses, to investigate mechanisms at the basis of working memory in different conditions. Simulations show that the trained network is able to desynchronize up to nine items without a fixed order using the gamma rhythm. Moreover, the network can replicate a sequence of items using a gamma rhythm nested inside a theta rhythm. The reduction in some parameters, mainly concerning the strength of GABAergic synapses, induce memory alterations which mimic neurological deficits. Finally, the network, isolated from the external environment simulates an“imagination phase”.
Model Type: Neural mass; Synapse; Realistic Network
Model Concept(s): Gamma oscillations
Simulation Environment: MATLAB
Implementer(s): Ursino, Mauro [mauro.ursino at unibo.it]
References:
Ursino M, Cesaretti N, Pirazzini G. (2022). A model of working memory for encoding multiple items and ordered sequences exploiting the theta-gamma code Cognitive Neurodynamics.