TY - JOUR
T1 - Inter- and intra-subject variability of neuromagnetic resting state networks
AU - Wens, Vincent
AU - Bourguignon, Mathieu
AU - Goldman, Serge
AU - Marty, Brice
AU - Op De Beeck, Marc
AU - Clumeck, Catherine
AU - Mary, Alison
AU - Peigneux, Philippe
AU - Van Bogaert, Patrick
AU - Brookes, Matthew J.
AU - De Tiège, Xavier
PY - 2014/1/1
Y1 - 2014/1/1
N2 - Functional connectivity studies conducted at the group level using magnetoencephalography (MEG) suggest that resting state networks (RSNs) emerge from the large-scale envelope correlation structure within spontaneous oscillatory brain activity. However, little is known about the consistency of MEG RSNs at the individual level. This paper investigates the inter- and intra-subject variability of three MEG RSNs (sensorimotor, auditory and visual) using seed-based source space envelope correlation analysis applied to 5 min of resting state MEG data acquired from a 306-channel whole-scalp neuromagnetometer (Elekta Oy, Helsinki, Finland) and source projected with minimum norm estimation. The main finding is that these three MEG RSNs exhibit substantial variability at the single-subject level across and within individuals, which depends on the RSN type, but can be reduced after averaging over subjects or sessions. Over- and under-estimations of true RSNs variability are respectively obtained using template seeds, which are potentially mislocated due to inter-subject variations, and a seed optimization method minimizing variability. In particular, bounds on the minimal number of subjects or sessions required to obtain highly consistent between- or within-subject averages of MEG RSNs are derived. Furthermore, MEG RSN topography positively correlates with their mean connectivity at the inter-subject level. These results indicate that MEG RSNs associated with primary cortices can be robustly extracted from seed-based envelope correlation and adequate averaging. MEG thus appears to be a valid technique to compare RSNs across subjects or conditions, at least when using the current methods.
AB - Functional connectivity studies conducted at the group level using magnetoencephalography (MEG) suggest that resting state networks (RSNs) emerge from the large-scale envelope correlation structure within spontaneous oscillatory brain activity. However, little is known about the consistency of MEG RSNs at the individual level. This paper investigates the inter- and intra-subject variability of three MEG RSNs (sensorimotor, auditory and visual) using seed-based source space envelope correlation analysis applied to 5 min of resting state MEG data acquired from a 306-channel whole-scalp neuromagnetometer (Elekta Oy, Helsinki, Finland) and source projected with minimum norm estimation. The main finding is that these three MEG RSNs exhibit substantial variability at the single-subject level across and within individuals, which depends on the RSN type, but can be reduced after averaging over subjects or sessions. Over- and under-estimations of true RSNs variability are respectively obtained using template seeds, which are potentially mislocated due to inter-subject variations, and a seed optimization method minimizing variability. In particular, bounds on the minimal number of subjects or sessions required to obtain highly consistent between- or within-subject averages of MEG RSNs are derived. Furthermore, MEG RSN topography positively correlates with their mean connectivity at the inter-subject level. These results indicate that MEG RSNs associated with primary cortices can be robustly extracted from seed-based envelope correlation and adequate averaging. MEG thus appears to be a valid technique to compare RSNs across subjects or conditions, at least when using the current methods.
UR - http://www.scopus.com/inward/record.url?scp=84905904193&partnerID=8YFLogxK
U2 - 10.1007/s10548-014-0364-8
DO - 10.1007/s10548-014-0364-8
M3 - Article
C2 - 24777562
AN - SCOPUS:84905904193
SN - 0896-0267
VL - 27
SP - 620
EP - 634
JO - Brain Topography
JF - Brain Topography
IS - 5
ER -