Resumen
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.
Idioma original | English (US) |
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Título de la publicación alojada | Conference Record - 43rd Asilomar Conference on Signals, Systems and Computers |
Páginas | 1079-1082 |
Número de páginas | 4 |
DOI | |
Estado | Published - dic 1 2009 |
Evento | 43rd Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States Duración: nov 1 2009 → nov 4 2009 |
Serie de la publicación
Nombre | Conference Record - Asilomar Conference on Signals, Systems and Computers |
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ISSN (versión impresa) | 1058-6393 |
Other
Other | 43rd Asilomar Conference on Signals, Systems and Computers |
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País/Territorio | United States |
Ciudad | Pacific Grove, CA |
Período | 11/1/09 → 11/4/09 |
ASJC Scopus subject areas
- Signal Processing
- Computer Networks and Communications