TY - GEN
T1 - A study on MEG for algorithmic head shape extraction using statistical analysis
AU - Chowdhury, Srinjoy Nag
AU - Anitha, H.
AU - Kuhikar, Kshitij Manohar
AU - Dhawan, Saniya
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/1/5
Y1 - 2017/1/5
N2 - Man's tryst with mapping neural activity of the brain has been around since the last couple of decades. From MRI, fMRI to EEGs and then finally to MEG, it has been quite a long road. In our study we have used the last most rapidly advancing neural imaging technique (Magnetoencephalography) and have applied its result onto computational geometry for generating an anatomically and physiologically feasible head shape of the subject under consideration. We have used 340 channel MEG data set to generate a mesh based head shape. On the basis of this head shape, we have gone to access the recordings on the subject, simulate trigger delays, detect and remove artefacts such as spectral line contaminations using notch filters, averaging responses to estimating the source and finally, testing the result using statistical operations. The statistical operation that has been used is the t test and it gives a measure of the suitability of the head shape used for the particular subject which in turn throws light on the effectivity of the surface reconstruction algorithm used for this study. All the simulations have been done using the Brainstorm tool box of MATLAB software bundle.
AB - Man's tryst with mapping neural activity of the brain has been around since the last couple of decades. From MRI, fMRI to EEGs and then finally to MEG, it has been quite a long road. In our study we have used the last most rapidly advancing neural imaging technique (Magnetoencephalography) and have applied its result onto computational geometry for generating an anatomically and physiologically feasible head shape of the subject under consideration. We have used 340 channel MEG data set to generate a mesh based head shape. On the basis of this head shape, we have gone to access the recordings on the subject, simulate trigger delays, detect and remove artefacts such as spectral line contaminations using notch filters, averaging responses to estimating the source and finally, testing the result using statistical operations. The statistical operation that has been used is the t test and it gives a measure of the suitability of the head shape used for the particular subject which in turn throws light on the effectivity of the surface reconstruction algorithm used for this study. All the simulations have been done using the Brainstorm tool box of MATLAB software bundle.
UR - https://www.scopus.com/pages/publications/85015016790
UR - https://www.scopus.com/pages/publications/85015016790#tab=citedBy
U2 - 10.1109/RTEICT.2016.7808115
DO - 10.1109/RTEICT.2016.7808115
M3 - Conference contribution
AN - SCOPUS:85015016790
T3 - 2016 IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Proceedings
SP - 1661
EP - 1665
BT - 2016 IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 1st IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016
Y2 - 20 May 2016 through 21 May 2016
ER -