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Generalization                                                        [back]
Learning and generalization go hand-in-hand. All fields in psychology dealing with learning and inference have also explored generalization. We study both dimensional generalization, or how learning about a stimulus is transferred to new stimuli that differ from the original along continuous dimensions, and compound generalization, or how learning about one stimulus is transferred to new compounds comprising that stimulus.

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In the past, these two forms of generalization have been studied largely independently, and researchers have shown little interest in developing a unified theoretical framework to understand both. We have  developed just such a unified framework (Soto, Gershman, & Niv, 2014; Soto et al., 2015), by extending Shepard’s rational theory of dimensional generalization to the explanation of compound generalization. The model explains many results from the literature on causal and associative learning.

We are currently working on a neurocomputational model of the interaction between PFC and hippocampus during generalization of fear conditioning. This model proposes that PFC controls encoding of stimuli in the hippocampus, which in turn influences the extent to which fear learning and extinction are generalized.