Computational Sensemaking on Examples of Knowledge Discovery from Neuroscience Data: Towards Enhancing Stroke Rehabilitation

Andreas Holzinger, Reinhold Scherer, Martin Seeber, Johanna Wagner, Gernot Müller-Putz

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in Buch/BerichtForschungBegutachtung

Abstract

Strokes are often associated with persistent impairment of a lower limb. Functional brain mapping is a set of techniques from neuroscience for mapping biological quantities (computational maps) into spatial representations of the human brain as functional cortical tomography, generating massive data. Our goal is to understand cortical reorganization after a stroke and to develop models for optimizing rehabilitation with non-invasive electroencephalography. The challenge is to obtain insight into brain functioning, in order to develop predictive computational models to increase patient outcome. There are many EEG features that still need to be explored with respect to cortical reorganization. In the present work we use independent component analysis, and data visualization mapping as tools for sensemaking. Our results show activity patterns over the sensorimotor cortex, involved in the execution and association of movements; our results further supports the usefulness of inverse mapping methods and generative models for functional brain mapping in the context of non-invasive monitoring of brain activitity.
Originalspracheenglisch
TitelInternational Conference on Information Technology in Bio- and Medical Informatics - ITBAM 2012
UntertitelLecture Notes in Computer Science 7451
Redakteure/-innenChristian Böhm, Sami Khuri, Lenka Lhotska, M.Elena Renda
ErscheinungsortHeidelberg, Berlin, New York
Herausgeber (Verlag)Springer
Seiten166-168
Band7451
AuflageLecture Notes in Computer Science LNCS 7451
ISBN (elektronisch)978-3-642-32395-9
ISBN (Print)978-3-642-32394-2
DOIs
PublikationsstatusVeröffentlicht - 2012

Schlagwörter

    ASJC Scopus subject areas

    • Artificial intelligence

    Fields of Expertise

    • Human- & Biotechnology

    Treatment code (Nähere Zuordnung)

    • Basic - Fundamental (Grundlagenforschung)
    • Experimental

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    Holzinger, A., Scherer, R., Seeber, M., Wagner, J., & Müller-Putz, G. (2012). Computational Sensemaking on Examples of Knowledge Discovery from Neuroscience Data: Towards Enhancing Stroke Rehabilitation. in C. Böhm, S. Khuri, L. Lhotska, & M. E. Renda (Hrsg.), International Conference on Information Technology in Bio- and Medical Informatics - ITBAM 2012: Lecture Notes in Computer Science 7451 (Lecture Notes in Computer Science LNCS 7451 Aufl., Band 7451, S. 166-168). Heidelberg, Berlin, New York: Springer. https://doi.org/10.1007/978-3-642-32395-9_13