Age-related differences in functional nodes of the brain cortex - a high model order group ICA study

Littow, Harri; Elseoud, Ahmed Abou; Haapea, Marianne; Isohanni, Matti; Moilanen, Irma; Mankinen, Katariina; Nikkinen, Juha; Rahko, Jukka; Rantala, Heikki; Remes, Jukka; Starck, Tuomo; Tervonen, Osmo; Veijola, Juha; Beckmann, Christian F.; Kiviniemi, Vesa

doi:10.3389/fnsys.2010.00032

Cited by 32 publications

(36 citation statements)

References 42 publications

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“…The analysis for the differences between groups was carried out using an FSL dual regression technique that allows for voxel-wise comparisons of resting-state fMRI (Filippini et al, 2009; Littow et al, 2010; Veer et al, 2010; Abou Elseoud et al, 2011). This involves (A) using the group-ICA spatial maps in a linear model fit against the separate fMRI data sets, resulting in matrices (time-course matrices) describing the temporal dynamics for each component and subject, and (B) using these time-course matrices to estimate subject-specific spatial maps.…”

Section: Methodsmentioning

confidence: 99%

The Effect of Gray Matter ICA and Coefficient of Variation Mapping of BOLD Data on the Detection of Functional Connectivity Changes in Alzheimer’s Disease and bvFTD

Tuovinen

Rytty

Moilanen

et al. 2017

Front. Hum. Neurosci.

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Resting-state fMRI results in neurodegenerative diseases have been somewhat conflicting. This may be due to complex partial volume effects of CSF in BOLD signal in patients with brain atrophy. To encounter this problem, we used a coefficient of variation (CV) map to highlight artifacts in the data, followed by analysis of gray matter voxels in order to minimize brain volume effects between groups. The effects of these measures were compared to whole brain ICA dual regression results in Alzheimer’s disease (AD) and behavioral variant frontotemporal dementia (bvFTD). 23 AD patients, 21 bvFTD patients and 25 healthy controls were included. The quality of the data was controlled by CV mapping. For detecting functional connectivity (FC) differences whole brain ICA (wbICA) and also segmented gray matter ICA (gmICA) followed by dual regression were conducted, both of which were performed both before and after data quality control. Decreased FC was detected in posterior DMN in the AD group and in the Salience network in the bvFTD group after combining CV quality control with gmICA. Before CV quality control, the decreased connectivity finding was not detectable in gmICA in neither of the groups. Same finding recurred when exclusion was based on randomization. The subjects excluded due to artifacts noticed in the CV maps had significantly lower temporal signal-to-noise ratio than the included subjects. Data quality measure CV is an effective tool in detecting artifacts from resting state analysis. CV reflects temporal dispersion of the BOLD signal stability and may thus be most helpful for spatial ICA, which has a blind spot in spatially correlating widespread artifacts. CV mapping in conjunction with gmICA yields results suiting previous findings both in AD and bvFTD.

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Section: Methodsmentioning

confidence: 99%

The Effect of Gray Matter ICA and Coefficient of Variation Mapping of BOLD Data on the Detection of Functional Connectivity Changes in Alzheimer’s Disease and bvFTD

Tuovinen

Rytty

Moilanen

et al. 2017

Front. Hum. Neurosci.

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Section: Methodsmentioning

confidence: 99%

GroupICA dual regression analysis of resting state networks in a behavioral variant of frontotemporal dementia

Rytty¹,

Nikkinen²,

Paavola³

et al. 2013

Front. Hum. Neurosci.

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Functional MRI studies have revealed changes in default-mode and salience networks in neurodegenerative dementias, especially in Alzheimer's disease (AD). The purpose of this study was to analyze the whole brain cortex resting state networks (RSNs) in patients with behavioral variant frontotemporal dementia (bvFTD) by using resting state functional MRI (rfMRI). The group specific RSNs were identified by high model order independent component analysis (ICA) and a dual regression technique was used to detect between-group differences in the RSNs with p < 0.05 threshold corrected for multiple comparisons. A y-concatenation method was used to correct for multiple comparisons for multiple independent components, gray matter differences as well as the voxel level. We found increased connectivity in several networks within patients with bvFTD compared to the control group. The most prominent enhancement was seen in the right frontotemporal area and insula. A significant increase in functional connectivity was also detected in the left dorsal attention network (DAN), in anterior paracingulate-a default mode sub-network as well as in the anterior parts of the frontal pole. Notably the increased patterns of connectivity were seen in areas around atrophic regions. The present results demonstrate abnormal increased connectivity in several important brain networks including the DAN and default-mode network (DMN) in patients with bvFTD. These changes may be associated with decline in executive functions and attention as well as apathy, which are the major cognitive and neuropsychiatric defects in patients with frontotemporal dementia.

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“…Such observations motivate consideration of whether the seeds employed by earlier studies map to distinct functional subdivisions of the DMN whose anti-correlation patterns differ substantially, given the growing evidence that the DMN is functionally heterogeneous. With independent component analysis (ICA), several groups have revealed that the DMN splits into dorsal and ventral branches (Damoiseaux et al, 2008; Shirer et al, 2012), or more subdivisions depending on the specified component numbers (Damoiseaux et al, 2008; Damoiseaux et al, 2012; Littow et al, 2010; Shirer et al, 2012; Westlye et al, 2011). (Uddin et al, 2009) also observed heterogeneous subdivisions within the DMN by placing seeds in MPFC and PCC respectively.…”

Section: Introductionmentioning

confidence: 99%

Dissociated patterns of anti‐correlations with dorsal and ventral default‐mode networks at rest

Chen

Glover

Greicius

et al. 2017

Human Brain Mapping

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Previous studies of resting state functional connectivity have demonstrated that the default-mode network (DMN) is negatively correlated with a set of brain regions commonly activated during goal-directed tasks. However, the location and extent of anti-correlations are inconsistent across different studies, which has been posited to result largely from differences in whether or not global signal regression (GSR) was applied as a pre-processing step. Notably, coordinates of seed regions-of-interest defined within the posterior cingulate cortex (PCC)/precuneus, an area often employed to study functional connectivity of the DMN, have been inconsistent across studies. Taken together with recent observations that the DMN contains functionally heterogeneous subdivisions, it is presently unclear whether these seeds map to different DMN subnetworks, whose patterns of anti-correlation may differ. If so, then seed location may be a non-negligible factor that, in addition to differences in preprocessing steps, contributes to the inconsistencies reported among published studies regarding DMN correlations/anti-correlations. In this study, we examined anti-correlations of different subnetworks within the DMN during rest using both seed-based and point process analyses, and discovered that: (1) the ventral branch of the DMN (vDMN) yielded significantly weaker anti-correlations than that associated with the dorsal branch of the DMN (dDMN); (2) vDMN anti-correlations introduced by GSR were distinct from dDMN anti-correlations; (3) PCC/precuneus seeds employed by earlier studies mapped to different DMN subnetworks, which may explain some of the inconsistency (in addition to preprocessing steps) in the reported DMN anti-correlations.

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Age-related differences in functional nodes of the brain cortex - a high model order group ICA study

Cited by 32 publications

References 42 publications

The Effect of Gray Matter ICA and Coefficient of Variation Mapping of BOLD Data on the Detection of Functional Connectivity Changes in Alzheimer’s Disease and bvFTD

The Effect of Gray Matter ICA and Coefficient of Variation Mapping of BOLD Data on the Detection of Functional Connectivity Changes in Alzheimer’s Disease and bvFTD

GroupICA dual regression analysis of resting state networks in a behavioral variant of frontotemporal dementia

Dissociated patterns of anti‐correlations with dorsal and ventral default‐mode networks at rest

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