Neural mechanisms underlying subsequent memory for personal beliefs:An fMRI study
Abstract
Many fMRI studies have examined the neural mechanisms supporting emotional memory for stimuli that generate emotion rather automatically (e.g., a picture of a dangerous animal or of appetizing food). However, far fewer studies have examined how memory is influenced by emotion related to social and political issues (e.g., a proposal for large changes in taxation policy), which clearly vary across individuals. In order to investigate the neural substrates of affective and mnemonic processes associated with personal opinions, we employed an fMRI task wherein participants rated the intensity of agreement/disagreement to sociopolitical belief statements paired with neural face pictures. Following the rating phase, participants performed an associative recognition test in which they distinguished identical versus recombined face–statement pairs. The study yielded three main findings: behaviorally, the intensity of agreement ratings was linked to greater subjective emotional arousal as well as enhanced high-confidence subsequent memory. Neurally, statements that elicited strong (vs. weak) agreement or disagreement were associated with greater activation of the amygdala. Finally, a subsequent memory analysis showed that the behavioral memory advantage for statements generating stronger ratings was dependent on the medial prefrontal cortex (mPFC). Together, these results both underscore consistencies in neural systems supporting emotional arousal and suggest a modulation of arousal-related encoding mechanisms when emotion is contingent on referencing personal beliefs.
Keywords
Amygdala Emotion Episodic memoryNotes
Acknowledgements
This work was supported by a grant from the National Institutes on Aging (R01-AG34580-03) awarded to R.C. and a National Science Foundation (NSF) Graduate Research Fellowship (Grant Number 110640) awarded to V.I. We thank Alexandra Atkins for assistance with programming and piloting the paradigm, David Chou for assisting in data management and analysis, and Kerry Townsend for assisting in data collection.
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