Decoding Spontaneous Emotional States in the Human Brain.
Abstract
Pattern classification of human brain activity provides unique insight into the neural
underpinnings of diverse mental states. These multivariate tools have recently been
used within the field of affective neuroscience to classify distributed patterns of
brain activation evoked during emotion induction procedures. Here we assess whether
neural models developed to discriminate among distinct emotion categories exhibit
predictive validity in the absence of exteroceptive emotional stimulation. In two
experiments, we show that spontaneous fluctuations in human resting-state brain activity
can be decoded into categories of experience delineating unique emotional states that
exhibit spatiotemporal coherence, covary with individual differences in mood and personality
traits, and predict on-line, self-reported feelings. These findings validate objective,
brain-based models of emotion and show how emotional states dynamically emerge from
the activity of separable neural systems.
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https://hdl.handle.net/10161/12775Published Version (Please cite this version)
10.1371/journal.pbio.2000106Publication Info
Kragel, PA; Knodt, AR; Hariri, AR; & LaBar, KS (2016). Decoding Spontaneous Emotional States in the Human Brain. PLoS Biol, 14(9). pp. e2000106. 10.1371/journal.pbio.2000106. Retrieved from https://hdl.handle.net/10161/12775.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Ahmad Hariri
Professor of Psychology and Neuroscience
Integrating psychology, neuroimaging, pharmacology and molecular genetics in the search
for biological pathways mediating individual differences in behavior and related risk
for psychopathology.
Kevin S. LaBar
Professor of Psychology and Neuroscience
My research focuses on understanding how emotional events modulate cognitive processes
in the human brain. We aim to identify brain regions that encode the emotional properties
of sensory stimuli, and to show how these regions interact with neural systems supporting
social cognition, executive control, and learning and memory. To achieve this goal,
we use a variety of cognitive neuroscience techniques in human subject populations.
These include psychophysiological monitoring, functional magnetic
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