Article | The Swedish AI Society Workshop May 20-21; 2010; Uppsala University | Using AI to interpret BI: machine learning for decoding and characterization of brain activity patterns

Title:
Using AI to interpret BI: machine learning for decoding and characterization of brain activity patterns
Author:
Malin Björnsdotter: Department of Physiology, Institute of Neuroscience and Physiology, University of Gothenburg, Sweden Simon Beckmann: Department of Physiology, Institute of Neuroscience and Physiology, University of Gothenburg, Sweden Erik Ziegler: Department of Physiology, Institute of Neuroscience and Physiology, University of Gothenburg, Sweden Johan Wessberg: Department of Physiology, Institute of Neuroscience and Physiology, University of Gothenburg, Sweden
Download:
Full text (pdf)
Year:
2010
Conference:
The Swedish AI Society Workshop May 20-21; 2010; Uppsala University
Issue:
048
Article no.:
004
Pages:
9-14
No. of pages:
6
Publication type:
Abstract and Fulltext
Published:
2010-05-19
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Publisher:
Linköping University Electronic Press; Linköpings universitet


The appealing properties of artificial intelligence (AI) methods are being increasingly acknowledged by the neuroimaging community; as evidenced by the recent surge of brain activity pattern recognition studies [19]. Supervised learning and classification; in particular; are appreciated tools for localizing and distinguishing intricate brain response patterns and making predictions about otherwise undetectable neural states. Our group refines and applies such methods in order to implement sensitive and dynamic tools for characterization of neurophysiological data. Specifically; we employ support vector machines (SVMs); particle swarm optimization (PSO); independent component analysis (ICA); as well as both genetic and memetic algorithms on functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) data. This paper provides a brief overview of our recent advances in the development and utilization of Aibased analysis; with the particular aspiration to characterize human brain activation patterns produced by touch.

The Swedish AI Society Workshop May 20-21; 2010; Uppsala University

Author:
Malin Björnsdotter, Simon Beckmann, Erik Ziegler, Johan Wessberg
Title:
Using AI to interpret BI: machine learning for decoding and characterization of brain activity patterns
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The Swedish AI Society Workshop May 20-21; 2010; Uppsala University

Author:
Malin Björnsdotter, Simon Beckmann, Erik Ziegler, Johan Wessberg
Title:
Using AI to interpret BI: machine learning for decoding and characterization of brain activity patterns
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