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Predicting recovery following stroke: Deep learning, multimodal data and feature selection using explainable AI.
Neuroimage Clin
September 2024
School of Psychology, University of Birmingham, UK; School of Computer Science, University of Birmingham, UK.
Machine learning offers great potential for automated prediction of post-stroke symptoms and their response to rehabilitation. Major challenges for this endeavour include the very high dimensionality of neuroimaging data, the relatively small size of the datasets available for learning and interpreting the predictive features, as well as, how to effectively combine neuroimaging and tabular data (e.g.
View Article and Find Full Text PDFCompreTAP: Feasibility and reliability of a new language comprehension mapping task via preoperative navigated transcranial magnetic stimulation.
Cortex
February 2024
Department of Neurosurgery, Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Germany; TUM Neuroimaging Center, Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Germany; Department of Neurosurgery, Heidelberg University Hospital, Ruprecht-Karls-University Heidelberg, Germany. Electronic address:
Objective: Stimulation-based language mapping approaches that are used pre- and intraoperatively employ predominantly overt language tasks requiring sufficient language production abilities. Yet, these production-based setups are often not feasible in brain tumor patients with severe expressive aphasia. This pilot study evaluated the feasibility and reliability of a newly developed language comprehension task with preoperative navigated transcranial magnetic stimulation (nTMS).
View Article and Find Full Text PDFDynamic network properties of the superior temporal gyrus mediate the impact of brain age gap on chronic aphasia severity.
Commun Biol
July 2023
Department of Neurology, Emory University, Atlanta, GA, USA.
Brain structure deteriorates with aging and predisposes an individual to more severe language impairments (aphasia) after a stroke. However, the underlying mechanisms of this relation are not well understood. Here we use an approach to model brain network properties outside the stroke lesion, network controllability, to investigate relations among individualized structural brain connections, brain age, and aphasia severity in 93 participants with chronic post-stroke aphasia.
View Article and Find Full Text PDFConnecting Aortic Stiffness to Vascular Contraction: Does Sex Matter?
Int J Mol Sci
September 2022
Laboratory of Vascular Biology, Department of Biomedical and Chemical Engineering and Sciences, Florida Institute of Technology, Melbourne, FL 32901, USA.
This study was designed to connect aortic stiffness to vascular contraction in young male and female Wistar rats. We hypothesized that female animals display reduced intrinsic media-layer stiffness, which associates with improved vascular function. Atomic force microscopy (AFM)-based nanoindentation analysis was used to derive stiffness (Young's modulus) in biaxially (i.
View Article and Find Full Text PDFThe effect of an aphasia ID card on the processing of language produced by a speaker with nonfluent aphasia.
J Commun Disord
November 2022
Department of Communication Disorders, University of Massachusetts-Amherst, Amherst, MA, USA; Neuroscience and Behavior Graduate Program, University of Massachusetts-Amherst, Amherst, MA, USA. Electronic address:
Introduction: We tested whether aphasia self-disclosure via an aphasia ID card impacts (1) how non-aphasic listeners initially process language produced by a speaker with aphasia and (2) learning of the speaker's error patterns over time.
Methods: In this eye-tracking experiment, 27 young adults followed instructions recorded by a speaker with nonfluent aphasia while viewing a target picture and a distractor. The Card group (n = 14) was shown a simulated aphasia ID card for the speaker and the No Card group (n = 13) was not.
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