Aging-related cortical reorganization of verbal fluency processing: a functional near-infrared spectroscopy study

Heinzel, Sebastian; Metzger, Florian; Ehlis, Ann‐Christine; Korell, Robert; Alboji, Ahmed; Haeußinger, Florian B.; Hagen, Katja; Maetzler, Walter; Eschweiler, Gerhard W.; Berg, Daniela; Fallgatter, Andreas J.

doi:10.1016/j.neurobiolaging.2012.05.021

Cited by 80 publications

(64 citation statements)

References 62 publications

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“…These results suggest that a similar posterior to anterior shift in functional connectivity may also occur in some older individuals with increasing age. SG2 also had significantly increased connectivity in the bilateral posterior insular cortex and supramarginal gyrus (Heinzel et al, 2013). This increase was not seen in SG1.…”

Section: Discussionmentioning

confidence: 99%

Capturing heterogeneous group differences using mixture-of-experts: Application to a study of aging

Eavani

Hsieh

et al. 2016

NeuroImage

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In MRI studies, linear multi-variate methods are often employed to identify regions or connections that are affected due to disease or normal aging. Such linear models inherently assume that there is a single, homogeneous abnormality pattern that is present in all affected individuals. While kernel-based methods can implicitly model a non-linear effect, and therefore the heterogeneity in the affected group, extracting and interpreting information about affected regions is difficult. In this paper, we present a method that explicitly models and captures heterogeneous patterns of change in the affected group relative to a reference group of controls. For this purpose, we use the Mixture-Of-Experts (MOE) framework, which combines unsupervised modeling of mixtures of distributions with supervised learning of classifiers. MOE approximates the non-linear boundary between the two groups with a piecewise linear boundary, thus allowing discovery of multiple patterns of group differences. In the case of patient/control comparisons, each such pattern aims to capture a different dimension of a disease, and hence to identify patient subgroups. We validated our model using multiple simulation scenarios and performance measures. We applied this method to resting state functional MRI data from the Baltimore Longitudinal Study of Aging, to investigate heterogeneous effects of aging on brain function in cognitively normal older adults (> 85 years) relative to a reference group of normal young to middle-aged adults (< 60 years). We found strong evidence for the presence of two subgroups of older adults, with similar age distributions in each subgroup, but different connectivity patterns associated with aging. While both older subgroups showed reduced functional connectivity in the Default Mode Network (DMN), increases in functional connectivity within the pre-frontal cortex as well as the bilateral insula were observed only for one of the two subgroups. Interestingly, the subgroup showing this increased connectivity (unlike the other subgroup) was, cognitively similar at baseline to the young and middle-aged subjects in two of seven cognitive domains, and had a faster rate of cognitive decline in one of seven domains. These results suggest that older individuals whose baseline cognitive performance is comparable to that of younger individuals recruit their “cognitive reserve” later in life, to compensate for reduced connectivity in other brain regions.

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Section: Discussionmentioning

confidence: 99%

Capturing heterogeneous group differences using mixture-of-experts: Application to a study of aging

Eavani

Hsieh

et al. 2016

NeuroImage

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“…The selection of a two-second rest period as baseline reference was based on previous block design fNIRS studies (e.g. Müller et al 2014; Heinzel et al 2013). The baseline-corrected time series were subsequently averaged over the four repetitions of each task.…”

Section: Methodsmentioning

confidence: 99%

Prefrontal activation may predict working-memory training gain in normal aging and mild cognitive impairment

Vermeij

Kessels

Heskamp

et al. 2016

Brain Imaging and Behavior

101

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Cognitive training has been shown to result in improved behavioral performance in normal aging and mild cognitive impairment (MCI), yet little is known about the neural correlates of cognitive plasticity, or about individual differences in responsiveness to cognitive training. In this study, 21 healthy older adults and 14 patients with MCI received five weeks of adaptive computerized working-memory (WM) training. Before and after training, functional Near-Infrared Spectroscopy (fNIRS) was used to assess the hemodynamic response in left and right prefrontal cortex during performance of a verbal n-back task with varying levels of WM load. After training, healthy older adults demonstrated decreased prefrontal activation at high WM load, which may indicate increased processing efficiency. Although MCI patients showed improved behavioral performance at low WM load after training, no evidence was found for training-related changes in prefrontal activation. Whole-group analyses showed that a relatively strong hemodynamic response at low WM load was related to worse behavioral performance, while a relatively strong hemodynamic response at high WM load was related to higher training gain. Therefore, a ‘youth-like’ prefrontal activation pattern at older age may be associated with better behavioral outcome and cognitive plasticity.

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“…Demented PD (PDD) patients also met dementia criteria of the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV). One hundred and ninety-four healthy controls were recruited from the TREND study (www.trend-studie.de) [31], [32]. Any clinical sign for a neurodegenerative disorder in these individuals led to exclusion from the study.…”

Section: Methodsmentioning

confidence: 99%

Comparable Autoantibody Serum Levels against Amyloid- and Inflammation-Associated Proteins in Parkinson’s Disease Patients and Controls

et al. 2014

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Naturally occurring autoantibodies (NAbs) against a number of potentially disease-associated cellular proteins, including Amyloid-beta1–42 (Abeta1–42), Alpha-synuclein (Asyn), myelin basic protein (MBP), myelin oligodendrocyte glycoprotein (MOG), and S100 calcium binding protein B (S100B) have been suggested to be associated with neurodegenerative disorders, in particular Alzheimer’s (AD) and Parkinson’s disease (PD). Whereas the (reduced) occurrence of specific NAbs in AD is widely accepted, previous literature examining the relation of these NAb titres between PD patients and controls, as well as comparing these levels with demographic and clinical parameters in PD patients have produced inconsistent findings. We therefore aimed, in a cross-sectional approach, to determine serum titres of the above NAbs in a cohort of 93 PD patients (31 of them demented) and 194 controls. Levels were correlated with demographic and clinical variables, cerebrospinal fluid Abeta1–42, total tau and phospho-tau levels, as well as with single nucleotide polymorphisms (SNPs) of genes which either have been reported to influence the immune system, the amyloid cascade or the occurrence of PD (ApoE, GSK3B, HLA-DRA, HSPA5, SNCA, and STK39). The investigated NAb titres were neither significantly associated with the occurrence of PD, nor with demographic and clinical parameters, neurodegenerative markers or genetic variables. These results argue against a major potential of blood-borne parameters of the adaptive immune system to serve as trait or state markers in PD.

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Aging-related cortical reorganization of verbal fluency processing: a functional near-infrared spectroscopy study

Cited by 80 publications

References 62 publications

Capturing heterogeneous group differences using mixture-of-experts: Application to a study of aging

Capturing heterogeneous group differences using mixture-of-experts: Application to a study of aging

Prefrontal activation may predict working-memory training gain in normal aging and mild cognitive impairment

Comparable Autoantibody Serum Levels against Amyloid- and Inflammation-Associated Proteins in Parkinson’s Disease Patients and Controls

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