| dc.identifier.uri | http://hdl.handle.net/11401/76575 | |
| dc.description.sponsorship | This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree. | en_US |
| dc.format | Monograph | |
| dc.format.medium | Electronic Resource | en_US |
| dc.language.iso | en_US | |
| dc.publisher | The Graduate School, Stony Brook University: Stony Brook, NY. | |
| dc.type | Dissertation | |
| dcterms.abstract | Anxiety disorders affect about 40 million American adults yearly. Recent conceptualization suggests that abnormal brain connectivity of the corticolimbic network underlies anxiety-related maladaptive behaviors. However, it is still unclear which brain circuits mediate specific behaviors, as well as how such brain-behavior based mechanisms contribute to the pathophysiology of anxiety. In this dissertation, we used both neurobiology and behavior to investigate the etiology of generalized anxiety disorder. Specifically, we hypothesized that distinct neural mechanisms may exist in two different constructs of the negative valence system: reactivity to imminent threat (fear) and to distal and uncertain threat (anxiety). We used behavioral paradigms targeted to elicit reactivity to either fear or anxiety, and identified brain circuitry that may underlie each state using multi-modal MRI and statistical modeling. First, we found that the amygdala-prefrontal connectivity explains individual differences of attentional bias towards threat (induced using affect-valence faces), and that BDNF Val66Met polymorphism, a genetic risk factor of anxiety, has an indirect impact on this behavior by modulating connectivity. Second, we identified circuit-wide neural features (grey and white matter structural and functional connectivity) that account for maladaptive ventromedial prefrontal cortical threat reactivity in clinical anxiety. Finally, we found novel evidence that abnormal dopaminergic signaling, from the midbrain ventral tegmental area to the corticolimbic system, may underlie patients' lack of specificity (`over-generalization') in threat-detection. Together, the studies presented in this dissertation provide a circuit-based model for the neural underpinnings of clinical anxiety. | |
| dcterms.available | 2017-09-20T16:50:41Z | |
| dcterms.contributor | Mujica-Parodi, Lilianne | en_US |
| dcterms.contributor | Role, Lorna | en_US |
| dcterms.contributor | Fontanini, Alfredo | en_US |
| dcterms.contributor | Aprajita, Mohanty. | en_US |
| dcterms.creator | Cha, Jiook | |
| dcterms.dateAccepted | 2017-09-20T16:50:41Z | |
| dcterms.dateSubmitted | 2017-09-20T16:50:41Z | |
| dcterms.description | Department of Neuroscience. | en_US |
| dcterms.extent | 206 pg. | en_US |
| dcterms.format | Application/PDF | en_US |
| dcterms.format | Monograph | |
| dcterms.identifier | http://hdl.handle.net/11401/76575 | |
| dcterms.issued | 2015-08-01 | |
| dcterms.language | en_US | |
| dcterms.provenance | Made available in DSpace on 2017-09-20T16:50:41Z (GMT). No. of bitstreams: 1
Cha_grad.sunysb_0771E_11584.pdf: 5368179 bytes, checksum: e160624635d9607c7f4afbfcec5f20e2 (MD5)
Previous issue date: 2013 | en |
| dcterms.publisher | The Graduate School, Stony Brook University: Stony Brook, NY. | |
| dcterms.subject | Neurosciences | |
| dcterms.subject | Anxiety, Connectivity, Fear Generalization, Multi-modal MRI, Negative Attention Bias, Neuroimaging | |
| dcterms.title | Neural Underpinnings of Anxiety: Multi-modal Magnetic Resonance Imaging Approach | |
| dcterms.type | Dissertation | |
