Memory Maintenance during Sleep: a Neural Network Model
نویسندگان
چکیده
Simulations using a neural network model of the thalamocortical loop were performed. The simulations were to show whether random stimulation of the model could account for maintenance of neuronal assemblies (self-repair). Three simulations were done: (a) self-repair with continuous stimulation, (b) self-repair with 40 Hz frequency stimulation, and (c) self-repair with 60 Hz frequency stimulation. The results indicate that simulations (b) and (c) are better at maintaining neuronal assemblies than simulation (a). This result may be extended to the brain, suggesting that 40-60 Hz oscillations in the brain activate memory representations and thus maintain memory. The results also indicate that further studies to the exact mechanism of self-repair have to be done. Due to constrains on model size and simulation time the results regarding the self-repair mechanism used in these simulations remain inconclusive.
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