Medicine and Health Sciences Commons^™

Usage Of Swi (Susceptibility Weighted Imaging) Acquired At 7t For Qualitative Evaluation Of Temporal Lobe Epilepsy Patients With Histopathological And Clinical Correlation: An Initial Pilot Study., Benjamin Y M Kwan, Fateme Salehi, Pavlo Ohorodnyk, Donald H Lee, Jorge G Burneo, Seyed M Mirsattari, David Steven, Robert Hammond, Terry M Peters, Ali R Khan

Brain and Mind Institute Researchers' Publications

OBJECTIVES: Ultra high field MRI at 7T is able to provide much improved spatial and contrast resolution which may aid in the diagnosis of hippocampal abnormalities. This paper presents a preliminary experience on qualitative evaluation of 7T MRI in temporal lobe epilepsy patients with a focus on comparison to histopathology.

METHODS: 7T ultra high field MRI data, using T1-weighted, T2*-weighted and susceptibility-weighted images (SWI), were acquired for 13 patients with drug resistant temporal lobe epilepsy (TLE) during evaluation for potential epilepsy surgery. Qualitative evaluation of the imaging data for scan quality and presence of hippocampal and temporal lobe abnormalities were …

Category Learning In Older Adulthood: A Study Of The Shepard, Hovland, And Jenkins (1961) Tasks., Rahel Rabi, John Paul Minda

Brain and Mind Institute Researchers' Publications

Shepard, Hovland, and Jenkins (1961) examined the categorization abilities of younger adults using tasks involving single-dimensional rule learning, disjunctive rule learning, and family resemblance learning. The current study examined category learning in older adults using this well-known category set. Older adults, like younger adults, found category tasks with a single relevant dimension the easiest to learn. In contrast to younger adults, older adults found complex disjunctive rule-based categories harder to learn than family resemblance based categories. Disjunctive rule-based category learning appeared to be the most difficult for older adults to learn because this category set placed the heaviest demands on …

Structural Brain Injury In Patients With Disorders Of Consciousness: A Voxel-Based Morphometry Study., Pieter Guldenmund, Andrea Soddu, Katherine Baquero, Audrey Vanhaudenhuyse, Marie-Aurélie Bruno, Olivia Gosseries, Steven Laureys, Francisco Gómez

Brain and Mind Institute Researchers' Publications

MAIN OBJECTIVE: Disorders of consciousness (DOC; encompassing coma, vegetative state/unresponsive wakefulness syndrome (VS/UWS) and minimally conscious state minus/plus (MCS-/+)) are associated with structural brain injury. The extent of this damage remains poorly understood and merits a detailed examination using novel analysis techniques. Research design/methods and procedures: This study used voxel-based morphometry (VBM) on structural magnetic resonance imaging scans of 61 patients with DOC to examine grey and white matter injury associated with DOC, time spent in DOC, aetiology and diagnosis.

MAIN OUTCOMES AND RESULTS: DOC and time spent in DOC were found to be associated with widespread structural brain injury, …

Fusion Analysis Of Functional Mri Data For Classification Of Individuals Based On Patterns Of Activation., Mahdi Ramezani, Purang Abolmaesumi, Kris Marble, Heather Trang, Ingrid Johnsrude

Brain and Mind Institute Researchers' Publications

Classification of individuals based on patterns of brain activity observed in functional MRI contrasts may be helpful for diagnosis of neurological disorders. Prior work for classification based on these patterns have primarily focused on using a single contrast, which does not take advantage of complementary information that may be available in multiple contrasts. Where multiple contrasts are used, the objective has been only to identify the joint, distinct brain activity patterns that differ between groups of subjects; not to use the information to classify individuals. Here, we use joint Independent Component Analysis (jICA) within a Support Vector Machine (SVM) classification …

Deficits In Audiovisual Speech Perception In Normal Aging Emerge At The Level Of Whole-Word Recognition., Ryan A Stevenson, Caitlin E Nelms, Sarah H Baum, Lilia Zurkovsky, Morgan D Barense, Paul A Newhouse, Mark T Wallace

Brain and Mind Institute Researchers' Publications

Over the next 2 decades, a dramatic shift in the demographics of society will take place, with a rapid growth in the population of older adults. One of the most common complaints with healthy aging is a decreased ability to successfully perceive speech, particularly in noisy environments. In such noisy environments, the presence of visual speech cues (i.e., lip movements) provide striking benefits for speech perception and comprehension, but previous research suggests that older adults gain less from such audiovisual integration than their younger peers. To determine at what processing level these behavioral differences arise in healthy-aging populations, we administered …

The Effect Of Dopamine Therapy On Ventral And Dorsal Striatum-Mediated Cognition In Parkinson's Disease: Support From Functional Mri., Penny A Macdonald, Alex A Macdonald, Ken N Seergobin, Ruzbeh Tamjeedi, Hooman Ganjavi, Jean-Sebastien Provost, Oury Monchi

Brain and Mind Institute Researchers' Publications

The central aim of our study was to elucidate functions mediated by the ventral and dorsal striatum, respectively, to better understand the cognitive effects of dopamine replacement in Parkinson's disease. We proposed that the ventral striatum underlies general learning of stimulus associations, whereas the dorsal striatum promotes integration of various influences on selecting. In Parkinson's disease, dopamine depletion is substantially less notable in the ventral relative to the dorsal striatum, and therefore greater improvements are expected for dorsal striatum-mediated functions with dopamine replacement. Using a simple selection task, we found that dopamine replacement impaired encoding and facilitation of consistent stimulus-stimulus …

Freesurfer-Initiated Fully-Automated Subcortical Brain Segmentation In Mri Using Large Deformation Diffeomorphic Metric Mapping., Ali R Khan, Lei Wang, Mirza Faisal Beg

Brain and Mind Institute Researchers' Publications

Fully-automated brain segmentation methods have not been widely adopted for clinical use because of issues related to reliability, accuracy, and limitations of delineation protocol. By combining the probabilistic-based FreeSurfer (FS) method with the Large Deformation Diffeomorphic Metric Mapping (LDDMM)-based label-propagation method, we are able to increase reliability and accuracy, and allow for flexibility in template choice. Our method uses the automated FreeSurfer subcortical labeling to provide a coarse-to-fine introduction of information in the LDDMM template-based segmentation resulting in a fully-automated subcortical brain segmentation method (FS+LDDMM). One major advantage of the FS+LDDMM-based approach is that the automatically generated segmentations generated are …