OBJECTIVE The purpose of this study is to utilize functional MRI (fMRI) to identify structural brain regions and activation patterns involved in deception in order to determine whether illness deception can be differentiated from involuntary conversion disorders. We intend to compare the brain activations of functional movement disorder (FMD) patients against those of healthy volunteers in order to determine whether various aspects of the disorder are under volitional control, suggesting a component of illness deception, or are involuntary as hypothesized in conversion disorders. STUDY POPULATION We intend to use up to 35 right-hand dominant adult healthy volunteers (the first five subjects will be used to develop this method) and 30 functional movement disorder patients. DESIGN Using a slow event-related design, we will scan subjects using a 3T fMRI scanner while they are visually presented with survey-based stimuli which require a yes/no response using a key press. Information used to create the stimuli will be pseudo-randomly derived from one of two databases. The first database will be created from the information garnered in the survey subjects will complete during their screening visit (i.e. subjects eye color or height). The second database will be a collection of non-specific information (i.e. current year, season, etc.) that intentionally does not apply to the subjects. For each question displayed, subjects will receive a visual instruction to respond either truthfully or deceptively. Correct answers to responses will be evaluated based upon the survey the subjects completed. In addition to the BOLD data collected, we plan to calculate reaction times and acquire autonomic data in order to identify possible correlates with the brain responses. OUTCOME MEASURES The primary outcome measure is the BOLD-fMRI data collected from subjects while answering yes-no type questions. Secondary outcome measures will include reaction times and autonomic data that will be collected simultaneously with the fMRI data. Standard univariate general linear model analysis will be performed on the fMRI data as well as the use of multivariate methods, including support vector machine learning. Subgroup analyses will be conducted to characterize the correlation between reaction times, autonomic data, and fMRI results as well as potential differences in activation patterns for subject-referenced questions and questions which are unrelated to the subject.
- INCLUSION CRITERIA: PATIENTS: - Age 18 to 65 - Subjects willing to abstain from caffeine or alcohol for 48 hours prior to the fMRI scanning - Diagnosis of a functional movement disorder confirmed by a study investigator HEALTHY VOLUNTEERS: - Age 18 to 65 EXCLUSION CRITERIA: - Subjects with any abnormal findings on neurological exam consistent with an organic disorder - Subjects with a positive urine pregnancy test - Subjects with a positive urine drug screen - Subjects who are pregnant - Subjects with any finding on the MRI safety questionnaire which prevents them from safely undergoing an MRI scan - Subjects with metallic dental fillings which are likely to enhance MRI artifacts - Subjects with any history of dementia, brain tumor, stroke, head trauma or a vascular malformation as obtained by history or from imaging studies - Subjects with moderate to severe brain atrophy on imaging studies, as assessed by a study investigator - Subjects with any history of a severe medical condition, such as cardiovascular disease, which would prevent them from lying flat for up to 120 minutes - Subjects without the capacity to give informed consent - Subjects with claustrophobia or other restrictions which prevent them from undergoing a scan in a confined space for up to 120 minutes - Subjects using beta-blocker medications or other chronotropes which may inhibit the cardiac responsivity - Patient whose movement frequency and severity prevents them from undergoing MRI safely and effectively for the purposes of data collection - Patient with a pending medical-legal case - Subjects with suicidal ideation