Functional Neural Networks Underlying Latent Inhibition

University Of Texas At Austin, Austin TX

Investigators

Abstract

[unreadable] DESCRIPTION (provided by applicant): Functional brain networks underlying a learning effect can provide insight into the neural basis of learned behavior and into the disruption of normal learning functions in the brain. Latent inhibition is a learning effect in which repeated exposure to a stimulus results in the inhibition of an appropriate behavioral response when that familiar stimulus is paired with some consequence. The latent inhibition effect has been demonstrated in many behavioral paradigms, including Pavlovian conditioning, and is disrupted in individuals with schizophrenia. The potential of the latent inhibition paradigm as a model of the behavioral deficits associated with schizophrenia has prompted the investigation of the neural mechanisms underlying the effect. Lesion studies have identified single brain regions, such as the nucleus accumbens and the entorhinal cortex, that play an important role in the latent inhibition paradigm; however, neural functions that mediate associative learning are likely dependent on interactions between and within brain systems. Thus, we ask the question what are the underlying functional neural networks in latent inhibition? We will approach this question by first completing a comprehensive metabolic map of brain regions involved with latent inhibition using cytochrome oxidase histochemistry. We will then use structural equation modeling to determine causal influences in an anatomical network of regions involved in latent inhibition. We plan to compare our functional network model to other theoretical models of latent inhibition and schizophrenia. We will also investigate how functional neural networks are affected when we change the optimal training parameters to attenuate the latent inhibition effect. Lastly, we also look at changes in the functional neural network when an attenuated latent inhibition effect is facilitated with the metabolic enhance methylene blue, which has previously been shown to improve memory retention in our lab. At the completion of these studies, we expect to have a better understanding of the neural mechanisms underlying latent inhibition learning. We will gain insight to changes in metabolic capacity associated with sensory gating in normal, attenuated, and facilitated latent inhibition. The proposed research is expected to provide an understanding of the neural basis of the behavioral deficits observed in schizophrenia and in therapuetic approaches through the use of metabolic enhancers such as metheylene blue. [unreadable] [unreadable] [unreadable]