TY - GEN
T1 - Neuroactivation imaging using a monogenic framework
AU - Scinches, J. Miguel
AU - Branco, M. P.
AU - Da Silva, F. Lopes
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/6/15
Y1 - 2016/6/15
N2 - Intentions of specific motor movements are known to generate event-related (de)synchronization (ERD/ERS) patterns which may be interpreted as changes in the degree of synchronization of underlying neuronal networks. When activated, the neural populations in a certain region of the brain de-synchronize, leading to a decrease in the EEG power signal. Notably, this phenomena happens not only in time but also in space. Here, we propose a novel method to detect brain activity based on this spatial desynchronization effect. The electrical activity at the scalp is described by a finite dimension continuous 2D field estimated from the EEG data acquired at the discrete locations of the electrodes and analyzed using the monogenic framework. The method was tested with synthetic data and the results are compared with other methods, namely, the traditional power-based ERD/ERS estimation method. It is shown that the proposed approach yields more space-specific and less blurred results than traditional approaches.
AB - Intentions of specific motor movements are known to generate event-related (de)synchronization (ERD/ERS) patterns which may be interpreted as changes in the degree of synchronization of underlying neuronal networks. When activated, the neural populations in a certain region of the brain de-synchronize, leading to a decrease in the EEG power signal. Notably, this phenomena happens not only in time but also in space. Here, we propose a novel method to detect brain activity based on this spatial desynchronization effect. The electrical activity at the scalp is described by a finite dimension continuous 2D field estimated from the EEG data acquired at the discrete locations of the electrodes and analyzed using the monogenic framework. The method was tested with synthetic data and the results are compared with other methods, namely, the traditional power-based ERD/ERS estimation method. It is shown that the proposed approach yields more space-specific and less blurred results than traditional approaches.
KW - ERD/ERS
KW - Monogenic decomposition
KW - monogenic-based Phase-Locking Value field
KW - Neural populations
UR - https://www.scopus.com/pages/publications/84978374815
U2 - 10.1109/ISBI.2016.7493377
DO - 10.1109/ISBI.2016.7493377
M3 - Conference contribution
AN - SCOPUS:84978374815
T3 - Proceedings - International Symposium on Biomedical Imaging
SP - 759
EP - 762
BT - 2016 IEEE International Symposium on Biomedical Imaging
PB - IEEE Computer Society Press
T2 - 2016 IEEE 13th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016
Y2 - 13 April 2016 through 16 April 2016
ER -