UMD Data Collection

Permanent URI for this collectionhttp://hdl.handle.net/1903/27670

University of Maryland faculty and researchers can upload their research products in DRUM for rapid dissemination, global visibility and impact, and long-term preservation. Depositing data in DRUM can assist in compliance with data management and sharing requirements from the NSF, NIH, and other funding agencies and journals. You can also deposit code, documents, images, supplemental material, and other research products. DRUM tracks views and downloads of your research, and all DRUM records are indexed by Google and Google Scholar. Additionally, DRUM assigns permanent DOIs for your items, making it easy for other researchers to cite your work.

Submissions to the Data Collection

To add files to the UMD Data Collection, submit a new item through your associated department or program's DRUM collection and check the box indicating your upload contains a dataset.

Find more information and guidelines for depositing into the Data Collection on the University of Maryland Libraries' DRUM for Data page.

Assistance

Please direct questions regarding the UMD Data Collection or assistance in preparing and depositing data to: lib-research-data@umd.edu.

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Author: search.filters.author.Brodbeck, ChristianSubject: search.filters.subject.cognition

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    Post-Stroke Acute Dysexecutive Syndrome, a Disorder Resulting from Minor Stroke due to Disruption of Network Dynamics - Dataset
    (2020) Marsh, Elisabeth B.; Brodbeck, Christian; Llinas, Rafael H.; Mallick, Dania; Kulasingham, Joshua P.; Llinas, Rodolfo R.; Simon, Jonathan Z.
    Stroke patients with small CNS infarcts often demonstrate an acute dysexecutive syndrome characterized by difficulty with attention, concentration, and processing speed, independent of lesion size or location. We use magnetoencephalography (MEG) to show that disruption of network dynamics may be responsible. Nine patients with recent minor stroke and 8 age-similar controls underwent cognitive screening using the Montreal Cognitive Assessment (MoCA) and MEG to evaluate differences in cerebral activation patterns. During MEG, subjects participated in a visual picture-word matching task. Task complexity was increased as testing progressed. Cluster based permutation tests determined differences in activation patterns within the visual cortex, fusiform gyrus, and lateral temporal lobe. At visit 1, MoCA scores were significantly lower for patients than controls (median (IQR)=26.0 (4) versus 29.5 (3), p=0.005), and patient reaction times were increased. The amplitude of activation was significantly lower after infarct and demonstrated a pattern of temporal dispersion independent of stroke location. Differences were prominent in the fusiform gyrus and lateral temporal lobe. The pattern suggests that distributed network dysfunction may be responsible. Additionally, controls were able to modulate their cerebral activity based on task difficulty. In contrast, stroke patients exhibited the same low-amplitude response to all stimuli. Group differences remained, to a lesser degree, six months later; while MoCA scores and reaction times improved for patients. This study suggests that function is a globally distributed property beyond area-specific functionality, and illustrates the need for longer-term follow-up studies to determine whether abnormal activation patterns ultimately resolve or another mechanism underlies continued recovery.