Machine Learning EEG to Predict Cognitive Functioning and Processing Speed Over a 2-Year Period in Multiple Sclerosis Patients and Controls.

Autor: Kiiski H; School of Psychology and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland., Jollans L; School of Psychology and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland., Donnchadha SÓ; UCD School of Psychology, University College Dublin, Dublin, Ireland., Nolan H; School of Engineering, Trinity College Dublin, Dublin, Ireland., Lonergan R; Department of Neurology, St. Vincent's University Hospital, Dublin, Ireland., Kelly S; Department of Neurology, St. Vincent's University Hospital, Dublin, Ireland., O'Brien MC; UCD School of Psychology, University College Dublin, Dublin, Ireland., Kinsella K; Department of Neurology, St. Vincent's University Hospital, Dublin, Ireland., Bramham J; UCD School of Psychology, University College Dublin, Dublin, Ireland., Burke T; UCD School of Psychology, University College Dublin, Dublin, Ireland.; School of Nursing and Human Sciences, Dublin City University, Dublin, Ireland., Hutchinson M; Department of Neurology, St. Vincent's University Hospital, Dublin, Ireland., Tubridy N; Department of Neurology, St. Vincent's University Hospital, Dublin, Ireland., Reilly RB; School of Engineering, Trinity College Dublin, Dublin, Ireland.; Trinity Centre for Bioengineering, Trinity College Dublin, Dublin, Ireland.; School of Medicine, Trinity College Dublin, Dublin, Ireland., Whelan R; School of Psychology and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland. robert.whelan@tcd.ie.; Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland. robert.whelan@tcd.ie.
Jazyk: angličtina
Zdroj: Brain topography [Brain Topogr] 2018 May; Vol. 31 (3), pp. 346-363. Date of Electronic Publication: 2018 Jan 29.
DOI: 10.1007/s10548-018-0620-4
Abstrakt: Event-related potentials (ERPs) show promise to be objective indicators of cognitive functioning. The aim of the study was to examine if ERPs recorded during an oddball task would predict cognitive functioning and information processing speed in Multiple Sclerosis (MS) patients and controls at the individual level. Seventy-eight participants (35 MS patients, 43 healthy age-matched controls) completed visual and auditory 2- and 3-stimulus oddball tasks with 128-channel EEG, and a neuropsychological battery, at baseline (month 0) and at Months 13 and 26. ERPs from 0 to 700 ms and across the whole scalp were transformed into 1728 individual spatio-temporal datapoints per participant. A machine learning method that included penalized linear regression used the entire spatio-temporal ERP to predict composite scores of both cognitive functioning and processing speed at baseline (month 0), and months 13 and 26. The results showed ERPs during the visual oddball tasks could predict cognitive functioning and information processing speed at baseline and a year later in a sample of MS patients and healthy controls. In contrast, ERPs during auditory tasks were not predictive of cognitive performance. These objective neurophysiological indicators of cognitive functioning and processing speed, and machine learning methods that can interrogate high-dimensional data, show promise in outcome prediction.
Databáze: MEDLINE
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