Functional Contributions Derived from the Game-theoretical Analysis of Brain Damage after Stroke

Field: Neuroscience (Life Sciences)

Event Abstract Back to Event Functional Contributions Derived from the Game-theoretical Analysis of Brain Damage after Stroke Melissa Zavaglia1*, Nils D Forkert2, Bastian Cheng3, Götz Thomalla3 and Claus C Hilgetag4 1 Dept. Comput. Neurosci. Univ. Med. Ctr. Hamburg-Eppendorf; Jacobs Univ. Bremen, Germany 2 Dept. Comput. Neurosci. Univ. Med. Ctr. Hamburg-Eppendorf, Germany 3 Dept. Neurology, Univ. Med. Ctr. Hamburg-Eppendorf, Germany 4 Dept. Comput. Neurosci. Univ. Med. Ctr. Hamburg-Eppendorf; Jacobs Univ. Bremen; Boston Univ., Germany Lesion analysis reveals causal contributions of brain regions to mental functions, aiding the understanding of normal brain function and rehabilitation of brain-damaged patients. Using a game-theoretical approach, we analyzed a large stroke patient dataset to derive contributions of brain regions to essential functions. Stroke patients show a variety of deﬁcits depending on their lesion patterns. The NIH Stroke Scale (NIHSS) [1] represents a standardized assessment of neurological deficits. We used the Multi-perturbation Shapley value Analysis (MSA) [2] to analyze patients' scores together with their lesion patterns. MSA is a rigorous theoretical method to infer functional contributions from behavioral performance after multiple lesions, treating brain regions as players in a coalition game. For each coalition of regions, the system's performance (inverse of NIHSS) is measured. MSA then derives each region's contribution to behavioral function from analyzing all possible configurations of intact and lesioned regions. Using a large multi-centre dataset of stroke patients [3], we investigated 9 bilateral regions of interest (ROI), defined by the MNI152 atlas [4]: caudate, cerebellum, insula, putamen, thalamus, frontal, occipital, parietal and temporal lobes. The overlap (in %) between infarct lesions registered to the atlas and each ROI was calculated for each patient. The resulting dataset was composed of 159 cases with different patterns of lesioned ROIs and associated NIHSS. Lesion percentages were thresholded (eg, 0.16%) to obtain binary sets of lesioned and intact regions, and different clasifiers (shown here: regtree) were trained on the available set of lesion configurations to predict the performance of the remaining, unknown configurations, required for MSA. Fig. 1 shows relative, unitless contribution values in a gray-scale map. Highest contributions are found in the left frontal lobe, left thalamus, followed by bilateral caudate, while other regions make weaker positive or negative contributions. The results are in line with the known pivotal role of these regions for basic brain function as measured by the NIHSS. Further contributions can be computed based on individual NIHSS components, to obtain a specific map for each task, such as language or attention, and provide detailed insights for rehabilitation. Supported by ERA-NET NEURON (MZ, CCH) [1] Brott 1989 Stroke [2] Keinan 2004 Neur Comp [3] Thomalla 2011 Lancet Neur [4] Collins 1995 HBM Figure 1 Keywords: General neuroinformatics, Stroke, brain functions, Brain damaged patients, theoretical methods Conference: 5th INCF Congress of Neuroinformatics, Munich, Germany, 10 Sep - 12 Sep, 2012. Presentation Type: Poster Topic: Neuroinformatics Citation: Zavaglia M, Forkert N, Cheng B, Thomalla G and Hilgetag C (2014). Functional Contributions Derived from the Game-theoretical Analysis of Brain Damage after Stroke. Front. Neuroinform. Conference Abstract: 5th INCF Congress of Neuroinformatics. doi: 10.3389/conf.fninf.2014.08.00009 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 21 Mar 2013; Published Online: 27 Feb 2014. * Correspondence: Dr. Melissa Zavaglia, Dept. Comput. Neurosci. Univ. Med. Ctr. Hamburg-Eppendorf; Jacobs Univ. Bremen, Hamburg, Germany, m.zavaglia@uke.de Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Melissa Zavaglia Nils D Forkert Bastian Cheng Götz Thomalla Claus C Hilgetag Google Melissa Zavaglia Nils D Forkert Bastian Cheng Götz Thomalla Claus C Hilgetag Google Scholar Melissa Zavaglia Nils D Forkert Bastian Cheng Götz Thomalla Claus C Hilgetag PubMed Melissa Zavaglia Nils D Forkert Bastian Cheng Götz Thomalla Claus C Hilgetag Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.