TY - GEN
T1 - Improved estimation of human cortical activity and connectivity with the multimodal integration of neuroelectric and hemodynamic data
AU - Babiloni, F.
AU - Mattia, D.
AU - Basilisco, A.
AU - Astolfi, L.
AU - Cincotti, F.
AU - Ding, L.
AU - Christine, K.
AU - Sweeney, J.
AU - Edgar, J. C.
AU - Miller, G. A.
AU - He, B.
PY - 2005/1/1
Y1 - 2005/1/1
N2 - In the last decade, the possibility to noninvasively estimate cortical activity and connectivity has been highlighted by the application of the techniques known as high resolution EEG. These techniques include a subject's multi-compartment head model (scalp, skull, dura mater, cortex) constructed from individual magnetic resonance images, multi-dipole source model, and regularized linear inverse source estimates of cortical current density. More recently, it has proved as the use of information from the hemodynamic responses of the cortical areas as revealed by block-designed (strength of activated voxels) fMRI improves dramatically the estimates of cortical activity and connectivity. Here, we present some applications of such estimation in two set of high resolution EEG and fMRI data, related to the motor (finger tapping) and cognitive (Stroop) tasks. We observed that the proposed technology was able to unveil the direction of the information flow between the cortical regions of interest.
AB - In the last decade, the possibility to noninvasively estimate cortical activity and connectivity has been highlighted by the application of the techniques known as high resolution EEG. These techniques include a subject's multi-compartment head model (scalp, skull, dura mater, cortex) constructed from individual magnetic resonance images, multi-dipole source model, and regularized linear inverse source estimates of cortical current density. More recently, it has proved as the use of information from the hemodynamic responses of the cortical areas as revealed by block-designed (strength of activated voxels) fMRI improves dramatically the estimates of cortical activity and connectivity. Here, we present some applications of such estimation in two set of high resolution EEG and fMRI data, related to the motor (finger tapping) and cognitive (Stroop) tasks. We observed that the proposed technology was able to unveil the direction of the information flow between the cortical regions of interest.
KW - EEG and fMRI integration
KW - Finger tapping
KW - Linear inverse source estimate
KW - Stroop
UR - http://www.scopus.com/inward/record.url?scp=33846922628&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33846922628&partnerID=8YFLogxK
U2 - 10.1109/iembs.2005.1615830
DO - 10.1109/iembs.2005.1615830
M3 - Conference contribution
AN - SCOPUS:33846922628
SN - 0780387406
SN - 9780780387409
T3 - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
SP - 5888
EP - 5891
BT - Proceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
Y2 - 1 September 2005 through 4 September 2005
ER -