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

Research output: Chapter in Book/Report/Conference proceedingChapter

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.
LanguageEnglish
Title of host publicationInternational Conference on Information Technology in Bio- and Medical Informatics - ITBAM 2012
Subtitle of host publicationLecture Notes in Computer Science 7451
EditorsChristian Böhm, Sami Khuri, Lenka Lhotska, M.Elena Renda
Place of PublicationHeidelberg, Berlin, New York
PublisherSpringer
Pages166-168
Volume7451
EditionLecture Notes in Computer Science LNCS 7451
ISBN (Electronic)978-3-642-32395-9
ISBN (Print)978-3-642-32394-2
DOIs
StatusPublished - 2012

Fingerprint

Brain mapping
Patient rehabilitation
Data mining
Brain
Electroencephalography
Data visualization
Independent component analysis
Tomography
Monitoring

Keywords

  • Knowledge Discovery
  • Data Mining
  • Gait analysis
  • infomax independent component analysis

ASJC Scopus subject areas

  • Artificial Intelligence

Fields of Expertise

  • Human- & Biotechnology

Treatment code (Nähere Zuordnung)

  • Basic - Fundamental (Grundlagenforschung)
  • Experimental

Cite this

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 (Eds.), 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 ed., Vol. 7451, pp. 166-168). Heidelberg, Berlin, New York: Springer. DOI: 10.1007/978-3-642-32395-9_13

Computational Sensemaking on Examples of Knowledge Discovery from Neuroscience Data: Towards Enhancing Stroke Rehabilitation. / Holzinger, Andreas; Scherer, Reinhold; Seeber, Martin; Wagner, Johanna; Müller-Putz, Gernot.

International Conference on Information Technology in Bio- and Medical Informatics - ITBAM 2012: Lecture Notes in Computer Science 7451. ed. / Christian Böhm; Sami Khuri; Lenka Lhotska; M.Elena Renda. Vol. 7451 Lecture Notes in Computer Science LNCS 7451. ed. Heidelberg, Berlin, New York : Springer, 2012. p. 166-168.

Research output: Chapter in Book/Report/Conference proceedingChapter

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 & ME Renda (eds), 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 edn, vol. 7451, Springer, Heidelberg, Berlin, New York, pp. 166-168. DOI: 10.1007/978-3-642-32395-9_13
Holzinger A, Scherer R, Seeber M, Wagner J, Müller-Putz G. Computational Sensemaking on Examples of Knowledge Discovery from Neuroscience Data: Towards Enhancing Stroke Rehabilitation. In Böhm C, Khuri S, Lhotska L, Renda ME, editors, 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 ed. Vol. 7451. Heidelberg, Berlin, New York: Springer. 2012. p. 166-168. Available from, DOI: 10.1007/978-3-642-32395-9_13
Holzinger, Andreas ; Scherer, Reinhold ; Seeber, Martin ; Wagner, Johanna ; Müller-Putz, Gernot. / Computational Sensemaking on Examples of Knowledge Discovery from Neuroscience Data: Towards Enhancing Stroke Rehabilitation. International Conference on Information Technology in Bio- and Medical Informatics - ITBAM 2012: Lecture Notes in Computer Science 7451. editor / Christian Böhm ; Sami Khuri ; Lenka Lhotska ; M.Elena Renda. Vol. 7451 Lecture Notes in Computer Science LNCS 7451. ed. Heidelberg, Berlin, New York : Springer, 2012. pp. 166-168
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