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<https://discovery.ucl.ac.uk/id/eprint/18760> <http://purl.org/ontology/bibo/abstract> "One of the fundaments of associative learning theories is that surprising events drive\r\nlearning by signalling the need to update one’s beliefs. It has long been suggested\r\nthat plasticity of connection strengths between neurons underlies the learning of\r\npredictive associations: Neural units encoding associated entities change their\r\nconnectivity to encode the learned associative strength. Surprisingly, previous\r\nimaging studies have focused on correlations between regional brain activity and\r\nvariables of learning models, but neglected how these variables changes in interregional\r\nconnectivity. Dynamic Causal Models (DCMs) of neuronal populations and\r\ntheir effective connectivity form a novel technique to investigate such learning\r\ndependent changes in connection strengths.\r\nIn the work presented here, I embedded computational learning models into DCMs to\r\ninvestigate how computational processes are reflected by changes in connectivity.\r\nThese novel models were then used to explain fMRI data from three associative\r\nlearning studies. The first study integrated a Rescorla-Wagner model into a DCM\r\nusing an incidental learning paradigm where auditory cues predicted the\r\npresence/absence of visual stimuli. Results showed that even for behaviourally\r\nirrelevant probabilistic associations, prediction errors drove the consolidation of\r\nconnection strengths between the auditory and visual areas. In the second study I\r\ncombined a Bayesian observer model and a nonlinear DCM, using an fMRI\r\nparadigm where auditory cues differentially predicted visual stimuli, to investigate\r\nhow predictions about sensory stimuli influence motor responses. Here, the degree of\r\nstriatal prediction error activity controlled the plasticity of visuo-motor connections.\r\nIn a third study, I used a nonlinear DCM and data from a fear learning study to\r\ndemonstrate that prediction error activity in the amygdala exerts a modulatory\r\ninfluence on visuo-striatal connections.\r\nThough postulated by many models and theories about learning, to our knowledge\r\nthe work presented in this thesis constitutes the first direct report that prediction\r\nerrors can modulate connection strength."^^<http://www.w3.org/2001/XMLSchema#string> .
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