Abstract
The present chapter assumes that the amount of information stored in the brain at a given moment is proportional to the mismatch between internally predicted events and the actual events ocurring in the external world. We have proposed ([29], [30]) that the hippocampus is involved in the computation of the “aggregate prediction” of ongoing events. This prediction is compared with information from the external world in order to determine the amount of information to be stored in the brain.
According to the “aggregate prediction” hypothesis (a) the effect of hippocampal lesions (HL) is an impairment in the integration of the aggregate prediction used to compute attentional variables (b) the effect of the induction of hippocampal long-term potentiation (LTP) is an increase in the value of the aggregate prediction by way of increasing the value of CS-CS associations and (c) that neural activity in hippocampus is proportional to the instantaneous value of the aggregate prediction. In addition, the present chapter introduces the hypothesis that medial septum activity is proportional to the sum of the values of different attentional variables.
The present chapter presents computer simulations for delay conditioning, conditioned inhibition, extinction, latent inhibition, and blocking for normal and HL cases. The “aggregate prediction” hypothesis proved capable of simulating most, but not all, experimental data regarding hippocampal manipulations in the rabbit nictitating membrane response preparation.
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Schmajuk, N.A. (1989). The Hippocampus and the Control of Information Storage in the Brain. In: Arbib, M.A., Amari, Si. (eds) Dynamic Interactions in Neural Networks: Models and Data. Research Notes in Neural Computing, vol 1. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-4536-0_4
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DOI: https://doi.org/10.1007/978-1-4612-4536-0_4
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