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Generalization
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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.
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.
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