Destination Areas (DAs)

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https://hdl.handle.net/10919/78629
Destination Areas provide faculty and students with new tools to identify and solve complex, 21st-century problems in which Virginia Tech already has significant strengths and can take a global leadership role. The initiative represents the next step in the evolution of the land-grant university to meet economic and societal needs of the world. DAs connect the full span of relevant knowledge necessary for addressing issues comprehensively. Humanistic, scientific, and technological perspectives are addressed in relationship to one another and they are treated as complementary to overcome traditional academic boundaries, such as those that separate the STEM fields and liberal arts. [http://provost.vt.edu/destination-areas.html]

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Browsing Destination Areas (DAs) by Department "Biomedical Engineering and Sciences"

Now showing 1 - 3 of 3
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    In Cocaine Dependence, Neural Prediction Errors During Loss Avoidance Are Increased With Cocaine Deprivation and Predict Drug Use
    Wang, John M.; Zhu, Lusha; Brown, Vanessa M.; De La Garza, Richard II; Newton, Thomas F.; Casas, Brooks; Chiu, Pearl H. (Elsevier, 2018-08-03)
    Background: In substance-dependent individuals, drug deprivation and drug use trigger divergent behavioral responses to environmental cues. These divergent responses are consonant with data showing that short- and long-term adaptations in dopamine signaling are similarly sensitive to state of drug use. The literature suggests a drug state–dependent role of learning in maintaining substance use; evidence linking dopamine to both reinforcement learning and addiction provides a framework to test this possibility. Methods: In a randomized crossover design, 22 participants with current cocaine use disorder completed a probabilistic loss-learning task during functional magnetic resonance imaging while on and off cocaine (44 sessions). Another 54 participants without Axis I psychopathology served as a secondary reference group. Within-drug state and paired-subjects’ learning effects were assessed with computational model–derived individual learning parameters. Model-based neuroimaging analyses evaluated effects of drug use state on neural learning signals. Relationships among model-derived behavioral learning rates (α+, α−), neural prediction error signals (δ+, δ−), cocaine use, and desire to use were assessed. Results: During cocaine deprivation, cocaine-dependent individuals exhibited heightened positive learning rates (α+), heightened neural positive prediction error (δ+) responses, and heightened association of α+ with neural δ+ responses. The deprivation-enhanced neural learning signals were specific to successful loss avoidance, comparable to participants without psychiatric conditions, and mediated a relationship between chronicity of drug use and desire to use cocaine. Conclusions: Neurocomputational learning signals are sensitive to drug use status and suggest that heightened reinforcement by successful avoidance of negative outcomes may contribute to drug seeking during deprivation. More generally, attention to drug use state is important for delineating substrates of addiction. © 2018
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    Neural computations underlying social risk sensitivity
    Lauharatanahirun, Nina; Christopoulos, George I.; Casas, Brooks (Frontiers, 2012-08-02)
    Under standard models of expected utility, preferences over stochastic events are assumed to be independent of the source of uncertainty. Thus, in decision-making, an agent should exhibit consistent preferences, regardless of whether the uncertainty derives from the unpredictability of a random process or the unpredictability of a social partner. However, when a social partner is the source of uncertainty, social preferences can influence decisions over and above pure risk attitudes (RA). Here, we compared risk-related hemodynamic activity and individual preferences for two sets of options that differ only in the social or non-social nature of the risk. Risk preferences in social and non-social contexts were systematically related to neural activity during decision and outcome phases of each choice. Individuals who were more risk averse in the social context exhibited decreased risk-related activity in the amygdala during non-social decisions, while individuals who were more risk averse in the non-social context exhibited the opposite pattern. Differential risk preferences were similarly associated with hemodynamic activity in ventral striatum at the outcome of these decisions. These findings suggest that social preferences, including aversion to betrayal or exploitation by social partners, may be associated with variability in the response of these subcortical regions to social risk.
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    Opponent Effects of Hyperarousal and Re-experiencing on Affective Habituation in Posttraumatic Stress Disorder
    McCurry, Katherine L.; Frueh, B. Christopher; Chiu, Pearl H.; Casas, Brooks (2020-02)
    BACKGROUND: Aberrant emotion processing is a hallmark of posttraumatic stress disorder (PTSD), with neurobiological models suggesting both heightened neural reactivity and diminished habituation to aversive stimuli. However, empirical work suggests that these response patterns may be specific to subsets of those with PTSD. This study investigates the unique contributions of PTSD symptom clusters (re-experiencing, avoidance and numbing, and hyperarousal) to neural reactivity and habituation to negative stimuli in combat-exposed veterans. METHODS: Ninety-five combat-exposed veterans (46 with PTSD) and 53 community volunteers underwent functional magnetic resonance imaging while viewing emotional images. This study examined the relationship between symptom cluster severity and hemodynamic responses to negative compared with neutral images (NEG>NEU). RESULTS: Veterans exhibited comparable mean and habituation-related responses for NEG>NEU, relative to civilians. However, among veterans, habituation, but not mean response, was differentially related to PTSD symptom severity. Hyperarousal symptoms were related to decreased habituation for NEG>NEU in a network of regions, including superior and inferior frontal gyri, ventromedial prefrontal cortex, superior and middle temporal gyri, and anterior insula. In contrast, re-experiencing symptoms were associated with increased habituation in a similar network. Furthermore, re-experiencing severity was positively related to amygdalar functional connectivity with the left inferior frontal gyrus and dorsal anterior cingulate cortex for NEG>NEU. CONCLUSIONS: These results indicate that hyperarousal symptoms in combat-related PTSD are associated with decreased neural habituation to aversive stimuli. These impairments are partially mitigated in the presence of re-experiencing symptoms, such that during exposure to negative stimuli, re-experiencing symptoms are positively associated with amygdalar connectivity to prefrontal regions implicated in affective suppression.