- Title Information
- Title
- Detecting Biomarkers of OCD Through the Use of Behavioral Tasks: Pilot Data Analysis and Task Validation
- Type of Resource (primo)
- dissertations
- Name:
Personal
- Name Part
- Acuff, William Luke
- Role
- Role Term:
Text
- creator
- Name:
Personal
- Name Part
- McLaughlin, Nicole
- Role
- Role Term:
Text
- Advisor
- Name:
Personal
- Name Part
- Borton, David
- Role
- Role Term:
Text
- Reader
- Name:
Personal
- Name Part
- Harrison, Matthew
- Role
- Role Term:
Text
- Reader
- Name:
Corporate
- Name Part
- Brown University. Biology and Medicine: Biomedical Engineering
- Role
- Role Term:
Text
- sponsor
- Origin Information
- Copyright Date
- 2022
- Physical Description
- Extent
- ix, 56 p.
- digitalOrigin
- born digital
- Note:
thesis
- Thesis (Sc. M.)--Brown University, 2022
- Genre (aat)
- theses
- Abstract
- Obsessive-compulsive disorder (OCD) is a neuropsychiatric disorder characterized by unwanted thoughts (obsessions) and repetitive behaviors (compulsions) which significantly disrupt an individual’s daily life. Psychological distress as a resultant and driver of the disorder is critical to the behavioral and neurological motivations which enable the disease, and the induction of obsessive-compulsive (OC) distress could be used to isolate activity related to the disorder. Detecting neural mechanisms, or biomarkers, which lead to OC distress is also critical to advancing treatment of the disorder, as neuromodulation therapies such as adaptive deep brain stimulation (aDBS) could be tailored to modulate brain regions responsible for OCD in real time. In this study, the PROVOC project is updated and implemented to capture those biomarkers by recording electroencephalogram (EEG) and other electrophysiological signals alongside subjective distress (SUDS) ratings in participants with OCD exposed to the object of their obsession by a virtual computer provocation task and an in vivo conveyor belt provocation task. Data from the project’s first participant indicate that provocation is induced by both the computer and conveyor belt stimulus. This leads EEG analysis down two paths, direct state comparison between power spectral density (PSD) of provoking and neutral stimuli for each task and frequency band, and SUDS correlation between increasing SUDS ratings and PSD for each task and frequency band. Statistical analysis suggests decreased frontal gamma power (30-45 Hz) to be the most significant initial finding among the results, but the data analysis pipeline and task structure are more importantly validated for future work.
- Subject (fast)
(authorityURI="http://id.worldcat.org/fast", valueURI="http://id.worldcat.org/fast/01036493")
- Topic
- Neuropsychology
- Subject (fast)
(authorityURI="http://id.worldcat.org/fast", valueURI="http://id.worldcat.org/fast/01042960")
- Topic
- Obsessive-compulsive disorder
- Subject
- Topic
- EEG biomarker
- Subject
- Topic
- Neural Engineering
- Language
- Language Term (ISO639-2B)
- English
- Record Information
- Record Content Source (marcorg)
- RPB
- Record Creation Date
(encoding="iso8601")
- 20220706