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Large-scale brain networks undergo functional reorganization over the course of the lifespan, with concurrent implications for cognition. Characterizing network connectivity during a task may provide complementary insight into cognitive development and aging, to that provided by resting-state. We assessed network background connectivity, which refers to connectivity that remains after task effects have been regressed out, during a visual memory-encoding task in a lifespan sample. More specifically we assessed the within- and between-network background connectivity of the default mode, salience, and frontoparietal networks. Within-network background connectivity of salience and frontoparietal networks differed between age groups, with late-life adults showing lower connectivity. We did not find an effect of age group in default mode network background connectivity, contrary to previous findings using resting-state. However, default mode between-network background connectivity with salience and frontoparietal networks was greater in mid-life and late-life adults than in younger age groups. Overall, our findings in a lifespan sample are in line with previous observations of age-related network de-differentiation. However, the lack of age effect in default mode network background connectivity suggests that background connectivity indeed represents a complementary measure to resting-state connectivity, providing a differential glance of network connectivity during a particular state., Competing Interests: Declarations of interest None., (Copyright © 2022 Japan Neuroscience Society and Elsevier B.V. All rights reserved.)

Previous literature has focused on predicting a diagnostic label from structural brain imaging. Since subtle changes in the brain precede a cognitive decline in healthy and pathological aging, our study predicts future decline as a continuous trajectory instead. Here, we tested whether baseline multimodal neuroimaging data improve the prediction of future cognitive decline in healthy and pathological aging. Nonbrain data (demographics, clinical, and neuropsychological scores), structural MRI, and functional connectivity data from OASIS-3 (N = 662; age = 46-96 years) were entered into cross-validated multitarget random forest models to predict future cognitive decline (measured by CDR and MMSE), on average 5.8 years into the future. The analysis was preregistered, and all analysis code is publicly available. Combining non-brain with structural data improved the continuous prediction of future cognitive decline (best test-set performance: R2 = 0.42). Cognitive performance, daily functioning, and subcortical volume drove the performance of our model. Including functional connectivity did not improve predictive accuracy. In the future, the prognosis of age-related cognitive decline may enable earlier and more effective individualized cognitive, pharmacological, and behavioral interventions., Competing Interests: Disclosure statement The authors declare no conflict of interest., (Copyright © 2022. Published by Elsevier Inc.)

Prenatal nutrition may significantly impact brain aging. Results from the Dutch Famine Birth Cohort indicated that prenatal undernutrition is negatively associated with cognition, brain volumes, perfusion and structural brain aging in late life, predominantly in men. This study investigates the association between prenatal undernutrition and late-life functional brain network connectivity. In an exploratory resting-state functional magnetic resonance imaging study of 112 participants from the Dutch Famine Birth Cohort, we investigated whether the within- and between-network functional connectivity of the default mode network, salience network and central executive network differ at age 68 in men (N = 49) and women (N = 63) either exposed or unexposed to undernutrition in early gestation. Additionally, we explored sex-specific effects. Compared to unexposed participants, exposed participants revealed multiple clusters of different functional connectivity within and between the three networks studied. Sex-specific analyses suggested a pattern of network desegregation fitting with brain aging in men and a more diffuse pattern of group differences in women. This study demonstrates that associations between prenatal undernutrition and brain network functional connectivity extend late into life., (Copyright © 2022. Published by Elsevier Inc.)

Subjective cognitive decline is a putative precursor to dementia marked by perceived worsening of cognitive function without overt performance issues on neuropsychological assessment. Although healthy older adults with subjective cognitive decline may function normally, perceived worsening may indicate incipient dementia and predict future deterioration. Therefore, the experience of decline represents a possible entry point for clinical intervention. However, intervention requires a physical manifestation of neuroabnormality to both corroborate incipient dementia and to target clinically. While some individuals with subjective cognitive decline may harbor pathophysiology for specific neurodegenerative disorders, many do not display clear indicators. Thus, disorder-agnostic brain measures could be useful to track the trajectory of decline, and functional neuroimaging in particular may be sensitive to detect incipient dementia and have the ability to track disease-related change when the underlying disease etiology remains unclear. Therefore, in this review, we discuss functional neuroimaging studies of subjective cognitive decline and possible reconciliations to inconsistent findings. We conclude by proposing a functional model where noisy signal propagation and inefficient signal processing across whole-brain networks may lead to the subjective experience of decline and discuss future research directions guided by this model.

We investigated the flexible modulation of undirected functional connectivity (uFC) of brain pathways during simple uni-manual responding. Two questions were central to our interests: (1) does response hand (dominant vs. non-dominant) differentially modulate connectivity and (2) are these effects related to responding under varying motor sets. fMRI data were acquired in twenty right-handed volunteers who responded with their right (dominant) or left (non-dominant) hand (blocked across acquisitions). Within acquisitions, the task oscillated between periodic responses (promoting the emergence of motor sets) or randomly induced responses (disrupting the emergence of motor sets). Conjunction analyses revealed eight shared nodes across response hand and condition, time series from which were analyzed. For right hand responses connectivity of the M1 ←→ Thalamus and SMA ←→ Parietal pathways was more significantly modulated during periodic responding. By comparison, for left hand responses, connectivity between five network pairs (including M1 and SMA, insula, basal ganglia, premotor cortex, parietal cortex, thalamus) was more significantly modulated during random responding. uFC analyses were complemented by directed FC based on multivariate autoregressive models of times series from the nodes. These results were complementary and highlighted significant modulation of dFC for SMA → Thalamus, SMA → M1, basal ganglia → Insula and basal ganglia → Thalamus. The results demonstrate complex effects of motor organization and task demand and response hand on different connectivity classes of fMRI data. The brain's sub-networks are flexibly modulated by factors related to motor organization and/or task demand, and our results have implications for assessment of medical conditions associated with motor dysfunction.

Background: Research in older adults with subjective cognitive decline (SCD) has mainly focused on Alzheimer's disease (AD)-related MRI markers, such as hippocampal volume. However, small vessel disease (SVD) is currently established as serious comorbidity in dementia and its preliminary stages. It is therefore important to examine SVD markers in addition to AD markers in older adults presenting with SCD., Objective: The aim of our study was to elucidate the role of SVD markers in late middle-aged to older adults with and without SCD in addition to the commonly found role of AD markers (hippocampal volume)., Methods: 67 healthy late middle-aged to older adults participated in this study (mean age 68 years); 25 participants with SCD and 42 participants without SCD. We evaluated quantitative as well as qualitative AD markers (i.e., hippocampal volume and medial temporal lobe atrophy (MTA) scale) and SVD markers (i.e., white matter hyperintensities (WMH) volume, Fazekas scale, microbleeds, and lacunar infarcts), and neuropsychological function and amount of memory complaints., Results: We found a significant effect of SCD on hippocampal atrophy, as assessed using the MTA scale, but not on hippocampal volume. In addition, we found a significant effect of SCD, and amount of memory complaints, on WMH volume and Fazekas score, suggesting larger WMH volumes in participants with SCD., Conclusion: SVD MRI markers are related to amount of memory complaints, in addition to the commonly observed AD MRI markers, as demonstrated by the greater WMHs in healthy late middle-aged to older adults with SCD.

Subjective memory complaints, the perceived decline in cognitive abilities in the absence of clinical deficits, may precede Alzheimer's disease. Individuals with subjective memory complaints show differential brain activation during memory encoding; however, whether such differences contribute to successful memory formation remains unclear. Here, we investigated how subsequent memory effects, activation which is greater for hits than misses during an encoding task, differed between healthy older adults aged 50 to 85 years with (n = 23) and without (n = 41) memory complaints. Older adults with memory complaints, compared to those without, showed lower subsequent memory effects in the occipital lobe, superior parietal lobe, and posterior cingulate cortex. In addition, older adults with more memory complaints showed a more negative subsequent memory effects in areas of the default mode network, including the posterior cingulate cortex, precuneus, and ventromedial prefrontal cortex. Our findings suggest that for successful memory formation, older adults with subjective memory complaints rely on distinct neural mechanisms which may reflect an overall decreased task-directed attention., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Over the past decade there has been an enormous rise in the application of functional and structural connectivity approaches to explore the brain's intrinsic organization in healthy and clinical populations. The notion underlying the application of these approaches to study aging is that subtle age-related disruption of the brain's regional integrity and information flow across the brain, are expressed by age-related differences in functional and structural connectivity. In this review I will discus recent advances in our understanding of how age affects our brain's intrinsic organization, and I will share my perspective on potential challenges and future directions of the field., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Background: The neurobiology of Trichotillomania is poorly understood, although there is increasing evidence to suggest that TTM may involve alterations of reward processing. The current study represents the first exploration of reward processing in TTM and the first resting state fMRI study in TTM. We incorporate both event-related fMRI using a monetary incentive delay (MID) task, and resting state fMRI, using two complementary resting state analysis methodologies (functional connectivity to the nucleus accumbens and dual regression within a reward network) in a pilot study to investigate differences in reward processing between TTM and healthy controls (HC)., Methods: 21 unmedicated subjects with TTM and 14 HC subjects underwent resting state fMRI scans. A subset (13 TTM and 12 HC) also performed the MID task., Results: For the MID task, TTM subjects showed relatively decreased nucleus accumbens (NAcc) activation to reward anticipation, but relative over-activity of the NAcc to both gain and loss outcomes. Resting state functional connectivity analysis showed decreased connectivity of the dorsal anterior cingulate (dACC) to the NAcc in TTM. Dual regression analysis of a reward network identified through independent component analysis (ICA) also showed decreased dACC connectivity and more prominently decreased basolateral amygdala connectivity within the reward network in TTM., Conclusions: Disordered reward processing at the level of NAcc, also involving decreased modulatory input from the dACC and the basolateral amygdala may play a role in the pathophysiology of TTM., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Regional functional connectivity (FC) of 39 patients with Alzheimer's disease (AD), 23 patients with mild cognitive impairment (MCI), and 43 healthy elderly controls was studied using resting-state functional magnetic resonance imaging (rs-fMRI). After a mean follow-up of 2.8 ± 1.9 years, 7 MCI patients converted to AD, while 14 patients remained cognitively stable. Resting-state functional magnetic resonance imaging scans were analyzed using independent component analysis (ICA), followed by a "dual-regression" technique to create and compare subject-specific maps of each independent spatiotemporal component, correcting for age, sex, and gray matter atrophy. AD patients displayed lower FC within the default-mode network (DMN) in the precuneus and posterior cingulate cortex compared with controls, independent of cortical atrophy. Regional FC values of MCI patients were numerically in between AD patients and controls, but only the difference between AD and stable MCI patients was statistically significant. Correlation with cognitive dysfunction demonstrated the clinical relevance of FC changes within the DMN. In conclusion, clinically relevant decreased FC within the DMN was observed in AD., (Copyright © 2012 Elsevier Inc. All rights reserved.)

We examined whether the effect of the apolipoprotein E (APOE) genotype on functional brain connectivity is modulated by gender in healthy older human adults. Our results confirm significantly decreased connectivity in the default mode network in healthy older APOE ε4 carriers compared with ε3 homozygotes. More important, further testing revealed a significant interaction between APOE genotype and gender in the precuneus, a major default mode hub. Female ε4 carriers showed significantly reduced default mode connectivity compared with either female ε3 homozygotes or male ε4 carriers, whereas male ε4 carriers differed minimally from male ε3 homozygotes. An additional analysis in an independent sample of healthy elderly using an independent marker of Alzheimer's disease, i.e., spinal fluid levels of tau, provided corresponding evidence for this gender-by-APOE interaction. Together, these results converge with previous work showing a higher prevalence of the ε4 allele among women with Alzheimer's disease and, critically, demonstrate that this interaction between APOE genotype and gender is detectable in the preclinical period.

While resting state functional connectivity has been shown to decrease in patients with mild and/or moderate Alzheimer's disease, it is not yet known how functional connectivity changes in patients as the disease progresses. Furthermore, it has been noted that the default mode network is not as homogenous as previously assumed and several fractionations of the network have been proposed. Here, we separately investigated the modulation of 3 default mode subnetworks, as identified with group independent component analysis, by comparing Alzheimer's disease patients to healthy controls and by assessing connectivity changes over time. Our results showed decreased connectivity at baseline in patients versus controls in the posterior default mode network, and increased connectivity in the anterior and ventral default mode networks. At follow-up, functional connectivity decreased across all default mode systems in patients. Our results suggest that earlier in the disease, regions of the posterior default mode network start to disengage whereas regions within the anterior and ventral networks enhance their connectivity. However, as the disease progresses, connectivity within all systems eventually deteriorates., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Background: Local network connectivity disruptions in Alzheimer's disease patients have been found using graph analysis in BOLD fMRI. Other studies using MEG and cortical thickness measures, however, show more global long distance connectivity changes, both in functional and structural imaging data. The form and role of functional connectivity changes thus remains ambiguous. The current study shows more conclusive data on connectivity changes in early AD using graph analysis on resting-state condition fMRI data., Methodology/principal Findings: 18 mild AD patients and 21 healthy age-matched control subjects without memory complaints were investigated in resting-state condition with MRI at 1.5 Tesla. Functional coupling between brain regions was calculated on the basis of pair-wise synchronizations between regional time-series. Local (cluster coefficient) and global (path length) network measures were quantitatively defined. Compared to controls, the characteristic path length of AD functional networks is closer to the theoretical values of random networks, while no significant differences were found in cluster coefficient. The whole-brain average synchronization does not differ between Alzheimer and healthy control groups. Post-hoc analysis of the regional synchronization reveals increased AD synchronization involving the frontal cortices and generalized decreases located at the parietal and occipital regions. This effectively translates in a global reduction of functional long-distance links between frontal and caudal brain regions., Conclusions/significance: We present evidence of AD-induced changes in global brain functional connectivity specifically affecting long-distance connectivity. This finding is highly relevant for it supports the anterior-posterior disconnection theory and its role in AD. Our results can be interpreted as reflecting the randomization of the brain functional networks in AD, further suggesting a loss of global information integration in disease.

It is commonly assumed that functional brain connectivity reflects structural brain connectivity. The exact relationship between structure and function, however, might not be straightforward. In this review we aim to examine how our understanding of the relationship between structure and function in the 'resting' brain has advanced over the last several years. We discuss eight articles that directly compare resting-state functional connectivity with structural connectivity and three clinical case studies of patients with limited white matter connections between the cerebral hemispheres. All studies examined show largely convergent results: the strength of resting-state functional connectivity is positively correlated with structural connectivity strength. However, functional connectivity is also observed between regions where there is little or no structural connectivity, which most likely indicates functional correlations mediated by indirect structural connections (i.e. via a third region). As the methodologies for measuring structural and functional connectivity continue to improve and their complementary strengths are applied in parallel, we can expect important advances in our diagnostic and prognostic capacities in diseases like Alzheimer's, multiple sclerosis, and stroke.

The pattern of degenerative changes in the brain white matter (WM) in aging, mild cognitive impairment (MCI), and Alzheimer's disease (AD) has been under debate. Methods of image analysis are an important factor affecting the outcomes of various studies. Here we used diffusion tensor imaging (DTI) to obtain fractional anisotropy (FA) measures of the WM in healthy young (n = 8), healthy elderly (n = 22), MCI (n = 8), and AD patients (n = 16). We then applied "tract-based spatial statistics" (TBSS) to study the effects of aging, MCI, and AD on WM integrity. Our results show that changes in WM integrity (that is, decreases in FA) are different between healthy aging and AD: in healthy older subjects compared with healthy young subjects decreased FA was primarily observed in frontal, parietal, and subcortical areas whereas in AD, compared with healthy older subjects, decreased FA was only observed in the left anterior temporal lobe. This different pattern of decreased anatomical connectivity in normal aging and AD suggests that AD is not merely accelerated aging., (2008 Wiley-Liss, Inc.)

Background and Purpose: Considerable clinical and radiological overlap between vascular dementia (VaD) and Alzheimer disease (AD) often makes the diagnosis difficult. Diffusion-tensor imaging studies showed that fractional anisotropy (FA) could be a useful marker for white matter changes. This study aimed to identify regional FA changes to identify a biomarker that could be used to differentiate VaD from AD., Methods: T1-weighted and diffusion-tensor imaging scans were obtained in 13 VaD patients, 16 AD patients, and 22 healthy elderly controls. We used tract-based spatial statistics to study regional changes in fractional anisotropy in AD, VaD, and elderly controls. We then used probabilistic tractography to parcel the corpus callosum in 7 regions according to its connectivity with major cerebral cortices using diffusion-tensor imaging data set. We compared the volume and mean FA in each set of transcallosal fibers between groups using ANOVA and then applied a discriminant analysis based on FA and T2-weighted imaging measures., Results: FA reduction in forceps minor was the most significant area of difference between AD and VaD. Segmentation of the corpus callosum using tractography and comparison of FA changes of each segment confirmed the FA changes in transcallosal prefrontal tracts of patients with VaD when compared to AD. The best discriminant model was the combination of transcallosal prefrontal FA and Fazekas score with 87.5% accuracy, 100% specificity, and 93% sensitivity (P<0.0001)., Conclusions: Integrating mean FA in the forceps minor to the Fazekas score provides a useful quantitative marker for differentiating AD from VaD.

FMRI research in Alzheimer's disease (AD) and mild cognitive impairment (MCI) typically is aimed at determining regional changes in brain function, most commonly by creating a model of the expected BOLD-response and estimating its magnitude using a general linear model (GLM) analysis. This crucially depends on the suitability of the temporal assumptions of the model and on assumptions about normality of group distributions. Exploratory data analysis techniques such as independent component analysis (ICA) do not depend on these assumptions and are able to detect unknown, yet structured spatiotemporal processes in neuroimaging data. Tensorial probabilistic ICA (T-PICA) is a model free technique that can be used for analyzing multiple subjects and groups, extracting signals of interest (components) in the spatial, temporal, and also subject domain of FMRI data. We applied T-PICA and model-based GLM to study FMRI signal during face encoding in 18 AD, 28 MCI patients, and 41 healthy elderly controls. T-PICA showed activation in regions associated with motor, visual, and cognitive processing, and deactivation in the default mode network. Six networks showed a significantly decreased response in patients. For two networks the T-PICA technique was significantly more sensitive to detect group differences than the standard model-based technique. We conclude that T-PICA is a promising tool to identify and detect differences in (de)activated brain networks in elderly controls and dementia patients. The technique is more sensitive than the commonly applied model-based method. Consistent with other research, we show that networks of activation and deactivation show decreased reactivity in dementia., ((c) 2007 Wiley-Liss, Inc.)

Normal aging is associated with cognitive decline. Functions such as attention, information processing, and working memory are compromised. It has been hypothesized that not only regional changes, but also alterations in the integration of regional brain activity (functional brain connectivity) underlie the observed age-related deficits. Here, we examined the functional properties of brain networks based on spontaneous fluctuations within brain systems using functional magnetic resonance imaging. We hypothesized that functional connectivity of intrinsic brain activity in the "default-mode" network (DMN) is affected by normal aging and that this relates to cognitive function. Ten younger and 22 older subjects were scanned at "rest," that is, lying awake with eyes closed. Our results show decreased activity in older versus younger subjects in 2 resting-state networks (RSNs) resembling the previously described DMN, containing the superior and middle frontal gyrus, posterior cingulate, middle temporal gyrus, and the superior parietal region. These results remain significant after correction for RSN-specific gray matter volume. The relevance of these findings is illustrated by the correlation between reduced activity of one of these RSNs and less effective executive functioning/processing speed in the older group.

Functional MRI (fMRI) can be applied to study the functional connectivity of the human brain. It has been suggested that fluctuations in the blood oxygenation level-dependent (BOLD) signal during rest reflect the neuronal baseline activity of the brain, representing the state of the human brain in the absence of goal-directed neuronal action and external input, and that these slow fluctuations correspond to functionally relevant resting-state networks. Several studies on resting fMRI have been conducted, reporting an apparent similarity between the identified patterns. The spatial consistency of these resting patterns, however, has not yet been evaluated and quantified. In this study, we apply a data analysis approach called tensor probabilistic independent component analysis to resting-state fMRI data to find coherencies that are consistent across subjects and sessions. We characterize and quantify the consistency of these effects by using a bootstrapping approach, and we estimate the BOLD amplitude modulation as well as the voxel-wise cross-subject variation. The analysis found 10 patterns with potential functional relevance, consisting of regions known to be involved in motor function, visual processing, executive functioning, auditory processing, memory, and the so-called default-mode network, each with BOLD signal changes up to 3%. In general, areas with a high mean percentage BOLD signal are consistent and show the least variation around the mean. These findings show that the baseline activity of the brain is consistent across subjects exhibiting significant temporal dynamics, with percentage BOLD signal change comparable with the signal changes found in task-related experiments.