Conference proceeding
Modeling motor learning connectivity using coordinate-based meta-analysis and TMS/PET
2009 Conference Record of the Forty-Third Asilomar Conference on Signals, Systems and Computers, pp.1079-1082
11/2009
DOI: 10.1109/ACSSC.2009.5470062
Abstract
BrainMap is a database of peak activation locations and metadata reported in functional neuroimaging studies, which was designed to develop and promote coordinate-based meta-analysis techniques. Here, we demonstrate the activation likelihood estimation (ALE) method in a meta-analysis of published TMS/PET studies. Using the results of this meta-analysis, we constructed a data-driven model of motor connectivity in TMS/PET data in which stimulation was delivered to RM1 before and after motor skill acquisition. A hybrid motor connectivity model of pre- and post-learning was generated to identify specific pathways most affected by the mechanisms involved in the motor learning process.
Details
- Title: Subtitle
- Modeling motor learning connectivity using coordinate-based meta-analysis and TMS/PET
- Creators
- A R Laird - The University of Texas Health Science Center at San AntonioK Li - The University of Texas Health Science Center at San AntonioS Narayana - The University of Texas Health Science Center at San AntonioL R Price - Texas State UniversityR W Laird - St. Mary's University, TexasJ Xiong - University of IowaP T Fox - Res. Imaging Inst., Univ. of Texas Health Sci. Cente, San Antonio, TX, USA
- Resource Type
- Conference proceeding
- Publication Details
- 2009 Conference Record of the Forty-Third Asilomar Conference on Signals, Systems and Computers, pp.1079-1082
- Publisher
- IEEE
- DOI
- 10.1109/ACSSC.2009.5470062
- ISSN
- 1058-6393
- eISSN
- 2576-2303
- Language
- English
- Date published
- 11/2009
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering
- Record Identifier
- 9984383308002771
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