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Rytty R, Nikkinen J, Paavola L, et al. GroupICA dual regression analysis of resting state networks in a behavioral variant of frontotemporal dementia. Front Hum Neurosci. 2013;7:461doi: 10.3389/fnhum.2013.00461.
Rytty, R., Nikkinen, J., Paavola, L., Abou Elseoud, A., Moilanen, V., Visuri, A., Tervonen, O., Renton, A. E., Traynor, B. J., Kiviniemi, V., & Remes, A. M. (2013). GroupICA dual regression analysis of resting state networks in a behavioral variant of frontotemporal dementia. Frontiers in human neuroscience, 7461. https://doi.org/10.3389/fnhum.2013.00461
Rytty, Riikka, et al. "GroupICA dual regression analysis of resting state networks in a behavioral variant of frontotemporal dementia." Frontiers in human neuroscience vol. 7 (2013): 461. doi: https://doi.org/10.3389/fnhum.2013.00461
Rytty R, Nikkinen J, Paavola L, Abou Elseoud A, Moilanen V, Visuri A, Tervonen O, Renton AE, Traynor BJ, Kiviniemi V, Remes AM. GroupICA dual regression analysis of resting state networks in a behavioral variant of frontotemporal dementia. Front Hum Neurosci. 2013 Aug 26;7:461. doi: 10.3389/fnhum.2013.00461. eCollection 2013. PMID: 23986673; PMCID: PMC3752460.
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Front Hum Neurosci. 2013 Aug 26;7:461. doi: 10.3389/fnhum.2013.00461. eCollection 2013.

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

Frontiers in human neuroscience

Riikka Rytty, Juha Nikkinen, Liisa Paavola, Ahmed Abou Elseoud, Virpi Moilanen, Annina Visuri, Osmo Tervonen, Alan E Renton, Bryan J Traynor, Vesa Kiviniemi, Anne M Remes

Affiliations

  1. Department of Neurology, Institute of Clinical Medicine, University of Oulu Oulu, Finland ; Department of Neurology, Oulu University Hospital Oulu, Finland.

PMID: 23986673 PMCID: PMC3752460 DOI: 10.3389/fnhum.2013.00461

Abstract

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.

Keywords: default; dorsal attention network; frontotemporal dementia; functional MRI; resting state

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