Title :
Hippocampal lesions may impair, spare, or facilitate latent inhibition: a neural network explanation
Author :
Buhusi, Catalin V. ; Schmajuk, N.A.
Author_Institution :
Dept. of Psychol. Exp., Duke Univ., Durham, NC, USA
Abstract :
Although until recently experimental data suggested that hippocampal lesions impair latent inhibition (LI), the use of more selective lesion techniques and different behavioral protocols indicates that the lesions might impair, spare, or even facilitate the phenomenon. We apply a neural network model to explain these apparently contradictory experimental results. In the context of the present neural network model, the contradictory pattern of results is the effect of the interactions between the information encoding mechanisms (cognitive mapping) and the attentional feedback mechanisms (tracking the total novelty in the environment) under the assumption that hippocampal lesions hinder information encoding. We demonstrate through computer simulations that, under conditions corresponding to specific experimental procedures, the model counterintuitively predicts a facilitation of LI after hippocampal lesions. A parametric study suggests that the main factors in the above interaction are: (a) the preexposure time, and (b) the experimental procedure. The study shows that both selective and nonselective hippocampal lesions impair LI under experimental parameters that do not favor LI in normal animals, preserve LI with experimental parameters that do favor LI in normal animals, and facilitate LI under experimental procedures that impair LI during conditioning in normal animals
Keywords :
biology computing; brain models; digital simulation; neural nets; neurophysiology; physiological models; attentional feedback mechanisms; behavioral protocols; classical conditioning; cognitive mapping; computer simulations; hippocampal lesions; information encoding mechanisms; latent inhibition; neural network model; selective lesion techniques; Animals; Computer simulation; Context modeling; Encoding; Lesions; Neural networks; Neurofeedback; Parametric study; Predictive models; Protocols;
Conference_Titel :
Neural Networks,1997., International Conference on
Print_ISBN :
0-7803-4122-8
DOI :
10.1109/ICNN.1997.611685