Decoupling of structural and functional brain connectivity in older adults with white matter hyperintensities

Reijmer, Yaël D.; Schultz, Aaron P.; Leemans, Alexander; O’Sullivan, Michael; Gurol, M. Edip; Sperling, Reisa A.; Greenberg, Steven M.; Viswanathan, Anand; Hedden, Trey

doi:10.1016/j.neuroimage.2015.05.054

Cited by 69 publications

(79 citation statements)

References 53 publications

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“…The strength of PCC- and MIC-based FC was significant decreased with the decline of cognitive level in LA, which was consistent with the common view (12, 13, 23–26). In contrast, a part of eMIC-based FC demonstrated increased strength with the decline of cognitive level, such as the FC of left caudate and left heschl, right rectus and right sulcus.…”

Section: Discussionsupporting

confidence: 88%

“…Previous studies have shown that the FC between the posterior cingulate cortex and medial prefrontal frontal cortex of the default mode network is altered in LA [e.g., Ref. (23)]. Moreover, FC among the right cingulate motor area, left posterior insula, and left ventral premotor area has been shown to be significantly decreased in LA (13, 24).…”

Section: Introductionmentioning

confidence: 86%

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Classification of Cognitive Level of Patients with Leukoaraiosis on the Basis of Linear and Non-Linear Functional Connectivity

Lai

Zhang

et al. 2017

Front. Neurol.

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Leukoaraiosis (LA) describes diffuse white matter abnormalities apparent in computed tomography (CT) or magnetic resonance (MR) brain scans. Patients with LA generally show varying degrees of cognitive impairment, which can be classified as cognitively normal (CN), mild cognitive impairment (MCI), and dementia. However, a consistent relationship between the degree of LA and the level of cognitive impairment has not yet been established. We used functional magnetic resonance imaging (fMRI) to explore possible neuroimaging biomarkers for classification of cognitive level in LA. Functional connectivity (FC) between brain regions was calculated using Pearson’s correlation coefficient (PCC), maximal information coefficient (MIC), and extended maximal information coefficient (eMIC). Next, FCs with high discriminative power for different cognitive levels in LA were used as features for classification based on support vector machine. CN and MCI were classified with accuracies of 75.0, 61.9, and 91.1% based on features from PCC, MIC, and eMIC, respectively. MCI and dementia were classified with accuracies of 80.1, 86.2, and 87.4% based on features from PCC, MIC, and eMIC, respectively. CN and dementia were classified with accuracies of 80.1, 89.9, and 94.4% based on features from PCC, MIC, and eMIC, respectively. Our results suggest that features extracted from fMRI were efficient for classification of cognitive impairment level in LA, especially, when features were based on a non-linear method (eMIC).

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Section: Discussionsupporting

confidence: 88%

Section: Introductionmentioning

confidence: 86%

Classification of Cognitive Level of Patients with Leukoaraiosis on the Basis of Linear and Non-Linear Functional Connectivity

Lai

Zhang

et al. 2017

Front. Neurol.

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“…A decoupling of functional and structural networks has been reported in other clinical groups as well. A study by Reijmer et al () in older adults with white matter hyperintensities for example demonstrated a clear decoupling. The authors suggested this might be related to different neural abnormalities that determine the white matter hyperintensities since they might have a differential effect on the BOLD signal and the diffusion parameters.…”

Section: Discussionmentioning

confidence: 94%

Impaired rich club and increased local connectivity in children with traumatic brain injury: Local support for the rich?

Verhelst

Linden

Pauw

et al. 2018

Human Brain Mapping

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Recent evidence has shown the presence of a "rich club" in the brain, which constitutes a core network of highly interconnected and spatially distributed brain regions, important for high-order cognitive processes. This study aimed to map the rich club organization in 17 young patients with moderate to severe TBI (15.71 ± 1.75 years) in the chronic stage of recovery and 17 age- and gender-matched controls. Probabilistic tractography was performed on diffusion weighted imaging data to construct the edges of the structural connectomes using number of streamlines as edge weight. In addition, the whole-brain network was divided into a rich club network, a local network and a feeder network connecting the latter two. Functional outcome was measured with a parent questionnaire for executive functioning. Our results revealed a significantly decreased rich club organization (p values < .05) and impaired executive functioning (p < .001) in young patients with TBI compared with controls. Specifically, we observed reduced density values in all three subnetworks (p values < .005) and a reduced mean strength in the rich club network (p = .013) together with an increased mean strength in the local network (p = .002) in patients with TBI. This study provides new insights into the nature of TBI-induced brain network alterations and supports the hypothesis that the local subnetwork tries to compensate for the biologically costly subnetwork of rich club nodes after TBI.

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“…Decoupling of functional and structural connectivity by WMH has been demonstrated in recent studies (Reijmer et al. ; Wang et al. ).…”

Section: Discussionmentioning

confidence: 83%

“…One explanation for the unique contribution of dWMH to VaD diagnosis is the increased potential for the disruption of multiple functionally important networks supporting cognition (Medaglia et al 2015). Decoupling of functional and structural connectivity by WMH has been demonstrated in recent studies (Reijmer et al 2015;Wang et al 2015b). Local functional regions tend to be densely connected, with these dense sets of nodes linked by sparse long-range connections (Park and Friston 2013).…”

Section: Ad Versusmentioning

confidence: 99%

Peripheral (deep) but not periventricular MRI white matter hyperintensities are increased in clinical vascular dementia compared to Alzheimer's disease

et al. 2016

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Background and purposeVascular dementia (VAD) is a complex diagnosis at times difficult to distinguish from Alzheimer's disease (AD). MRI scans often show white matter hyperintensities (WMH) in both conditions. WMH increase with age, and both VAD and AD are associated with aging, thus presenting an attribution conundrum. In this study, we sought to show whether the amount of WMH in deep white matter (dWMH), versus periventricular white matter (PVH), would aid in the distinction between VAD and AD, independent of age.MethodsBlinded semiquantitative ratings of WMH validated by objective quantitation of WMH volume from standardized MRI image acquisitions. PVH and dWMH were rated separately and independently by two different examiners using the Scheltens scale. Receiver operator characteristic (ROC) curves were generated using logistic regression to assess classification of VAD (13 patients) versus AD (129 patients). Clinical diagnoses were made in a specialty memory disorders clinic.ResultsUsing PVH rating alone, overall classification (area under the ROC curve, AUC) was 75%, due only to the difference in age between VAD and AD patients in our study and not PVH. In contrast, dWMH rating produced 86% classification accuracy with no independent contribution from age. A global Longstreth rating that combines dWMH and PVH gave an 88% AUC.ConclusionsIncreased dWMH indicate a higher likelihood of VAD versus AD. Assessment of dWMH on MRI scans using Scheltens and Longstreth scales may aid the clinician in distinguishing the two conditions.

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Decoupling of structural and functional brain connectivity in older adults with white matter hyperintensities

Cited by 69 publications

References 53 publications

Classification of Cognitive Level of Patients with Leukoaraiosis on the Basis of Linear and Non-Linear Functional Connectivity

Classification of Cognitive Level of Patients with Leukoaraiosis on the Basis of Linear and Non-Linear Functional Connectivity

Impaired rich club and increased local connectivity in children with traumatic brain injury: Local support for the rich?

Peripheral (deep) but not periventricular MRI white matter hyperintensities are increased in clinical vascular dementia compared to Alzheimer's disease

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