Abnormal salience network in normal aging and in amnestic mild cognitive impairment and Alzheimer's disease

Phasic alerting effects on visual processing speed are associated with intrinsic functional connectivity in the cingulo-opercular network

Phasic alertness refers to short-lived increases in the brain's "state of readiness", and thus to optimized performance following warning cues. Parametric modelling of whole report task performance based on the computational theory of visual attention (TVA) has demonstrated that visual processing speed is increased in such cue compared to no-cue conditions. Furthermore, with respect to the underlying neural mechanisms, individual visual processing speed has been related to intrinsic functional connectivity (iFC) within the cingulo-opercular network, suggesting that this network's iFC is relevant for the tonic maintenance of an appropriate readiness or alertness state. In the present study, we asked whether iFC in the cingulo-opercular network is also related to the individual ability to actively profit from warning cues, i.e. to the degree of phasic alerting. We obtained resting-state functional magnetic resonance imaging (rs-fMRI) data from 32 healthy young participants and combined an independent component analysis of rs-fMRI time courses and dual regression approach to determine iFC in the cingulo-opercular network. In a separate behavioural testing session, we parametrically assessed the effects of auditory phasic alerting cues on visual processing speed in a TVA-based whole report paradigm. A voxel-wise multiple regression revealed that higher individual phasic alerting effects on visual processing speed were significantly associated with lower iFC in the cingulo-opercular network, with a peak in the left superior orbital gyrus. As phasic alertness was neither related to iFC in other attention-relevant, auditory, or visual networks nor associated with any inter-network connectivity pattern, the results suggest that the individual profit in visual processing speed gained from phasic alerting is primarily associated with iFC in the cingulo-opercular network.

ASAF: altered spontaneous activity fingerprinting in Alzheimer's disease based on multisite fMRI

Several monocentric studies have noted alterations in spontaneous brain activity in Alzheimer's disease (AD), although there is no consensus on the altered amplitude of low-frequency fluctuations in AD patients. The main aim of the present study was to identify a reliable and reproducible abnormal brain activity pattern in AD. The amplitude of local brain activity (AM), which can provide fast mapping of spontaneous brain activity across the whole brain, was evaluated based on multisite rs-fMRI data for 688 subjects (215 normal controls (NCs), 221 amnestic mild cognitive impairment (aMCI) 252 AD). Two-sample t-tests were used to detect group differences between AD patients and NCs from the same site. Differences in the AM maps were statistically analyzed via the Stouffer's meta-analysis. Consistent regions of lower spontaneous brain activity in the default mode network and increased activity in the bilateral hippocampus/parahippocampus, thalamus, caudate nucleus, orbital part of the middle frontal gyrus and left fusiform were observed in the AD patients compared with those in NCs. Significant correlations (P < 0.05, Bonferroni corrected) between the normalized amplitude index and Mini-Mental State Examination scores were found in the identified brain regions, which indicates that the altered brain activity was associated with cognitive decline in the patients. Multivariate analysis and leave-one-site-out cross-validation led to a 78.49% prediction accuracy for single-patient classification. The altered activity patterns of the identified brain regions were largely correlated with the FDG-PET results from another independent study. These results emphasized the impaired brain activity to provide a robust and reproducible imaging signature of AD.

Greater Anteroposterior Default Mode Network Functional Connectivity in Long-Term Elderly Yoga Practitioners

Large-scale brain networks exhibit changes in functional connectivity during the aging process. Recent literature data suggests that Yoga and other contemplative practices may revert, at least in part, some of the aging effects in brain functional connectivity, including the Default Mode Network (DMN). The aim of this cross-sectional investigation was to compare resting-state functional connectivity of the medial prefrontal cortex (MPFC) and posterior cingulate cortex—precuneus (PCC-Precuneus) in long-term elderly Yoga practitioners and healthy paired Yoga-naïve controls. Two paired groups: yoga (Y-20 women, Hatha Yoga practitioners; practicing a minimum of twice a week with a frequency of at least 8 years) and a control group (C-20 women, Yoga-naïve, matched by age, years of formal education, and physical activity) were evaluated for: Mini Mental State Examination (MMSE), Beck Depression Inventory (BDI), Instrumental Activities of Daily Living (IADL), and open-eyes resting-state functional magnetic resonance imaging (fMRI)—seed to voxel connectivity analysis (CONN toolbox 17.f) with pre-processing—realignment and unwarping, slice-timing correction, segmentation, normalization, outlier detection, and spatial filtering. The analysis included a priori regions of interest (ROI) of DMN main nodes—MPFC and PCC-Precuneus. There was no difference between groups in terms of: age, years of formal education, MMSE, BDI and IADL. The Yoga group had a higher correlation between MPFC and the right angular gyrus (AGr), compared to the controls. Elderly women with at least 8 years of yoga practice presented greater intra-network anteroposterior brain functional connectivity of the DMN. This finding may contribute to the understanding of the influences of practicing Yoga for a healthier cognitive aging process.

Abnormal Interactions of the Salience Network, Central Executive Network, and Default-Mode Network in Patients With Different Cognitive Impairment Loads Caused by Leukoaraiosis

Leukoaraiosis (LA) is associated with cognitive impairment in the older people which can be demonstrated in functional connectivity (FC) based on resting-state functional magnetic resonance imaging (rs-fMRI). This study is to explore the FC changes in LA patients with different cognitive status by three network models. Fifty-three patients with LA were divided into three groups: the normal cognition (LA-NC; n = 14, six males), mild cognitive impairment (LA-MCI; n = 27, 13 males), and vascular dementia (LA-VD; n = 12, six males), according to the Mini Mental State Exam (MMSE) and Clinical Dementia Rating (CDR). The three groups and 30 matched healthy controls (HCs; 11 males) underwent rs-fMRI. The data of rs-fMRI were analyzed by independent components analysis (ICA) and region of interest (ROI) analysis by the REST toolbox. Then the FC was respectively analyzed by the default-mode network (DMN), salience networks (SNs) and the central executive network (CEN) with their results compared among the different groups. For inter-brain network analysis, there were negative FC between the SN and DMN in LA groups, and the FC decreased when compared with HC group. While there were enhanced inter-brain network FC between the SN and CEN as well as within the SN. The FC in patients with LA can be detected by different network models of rs-fMRI. The multi-model analysis is helpful for the further understanding of the cognitive changes in those patients.

Resting-State Functional Connectivity Is Associated With Cerebrospinal Fluid Levels of the Synaptic Protein NPTX2 in Non-demented Older Adults

Intrinsic functional connectivity of large-scale brain networks has been shown to change with aging and Alzheimer’s disease (AD). These alterations are thought to reflect changes in synaptic function, but the underlying biological mechanisms are poorly understood. This study examined whether Neuronal Pentraxin 2 (NPTX2), a synaptic protein that mediates homeostatic strengthening of inhibitory circuits to control cortical excitability, is associated with functional connectivity as measured by resting-state functional magnetic resonance imaging (rsfMRI) in five large-scale cognitive brain networks. In this cross-sectional study, rsfMRI scans were obtained from 130 older individuals (mean age = 69 years) with normal cognition (N = 113) and Mild Cognitive Impairment (N = 17); NPTX2 was measured in the same individuals in cerebrospinal fluid (CSF). Higher levels of NPTX2 in CSF were associated with greater functional connectivity in the salience/ventral attention network, based on linear regression analysis. Moreover, this association was stronger among individuals with lower levels of cognitive reserve, as measured by a composite score (comprised of years of education, reading, and vocabulary measures). Additionally, higher connectivity in the salience/ventral attention network was related to better performance on a composite measure of executive function. Levels of NPTX2 were not associated with connectivity in other networks (executive control, limbic, dorsal attention, and default-mode). Findings also confirmed prior reports that individuals with MCI have lower levels of NPTX2 compared to those with normal cognition. Taken together, the results suggest that NPTX2 mechanisms may play a central role among older individuals in connectivity within the salience/ventral attention network and for cognitive tasks that require modulation of attention and response selection.

The intrinsic neural architecture of inhibitory control: The role of development and emotional experience

Inhibitory control is a key determinant of goal-directed behavior. Its susceptibility to reward implies that its variations may not only reflect cognitive ability, but also sensitivity to goal-relevant information. Since cognitive ability and motivational sensitivity vary as a function of age and mood, we hypothesized that their relevance for predicting individual differences in inhibition would similarly vary. Here, we tested this prediction with respect to the brain's intrinsic functional architecture. Specifically, we reasoned that age and affective functioning would both moderate the relationship between inhibition and resting state expression of the dynamic neural organization patterns linked to engaging in cognitive effort versus those involved in manipulating motivationally salient information. First, we used task fMRI data from the Human Connectome Project (N = 359 participants) to identify the brain organization patterns unique to effortful cognitive processing versus manipulation of motivationally relevant information. We then assessed the association between inhibitory control and relative expression of these two neural patterns in an independent resting state dataset from the Nathan Kline Institute-Rockland lifespan sample (N = 247). As hypothesized, the relation between inhibition and intrinsic functional brain architecture varied as a function of age and affective functioning. Among those with superior affective functioning, better inhibitory control in adolescence and early adulthood was associated with stronger resting state expression of the brain pattern that typified processing of motivationally salient information. The opposite effect emerged beyond the age of 49. Among individuals with poorer affective functioning, a significant link between inhibition and brain architecture emerged only before the age of 28. In this group, superior inhibition was associated with stronger resting state expression of the neural pattern that typified effortful cognitive processing. Our results thus imply that motivational relevance makes a unique contribution to superior cognitive functioning during earlier life stages. However, its relevance to higher-order mentation decreases with aging and increased prevalence of mood-related problems, which raises the possibility that patterns of neurobehavioral responsiveness to motivational salience may constitute sensitive markers of successful lifespan development.

Connectome-wide network analysis of white matter connectivity in Alzheimer's disease

A multivariate analytical strategy may pinpoint the structural connectivity patterns associated with Alzheimer's disease (AD) pathology in connectome-wide association studies. Diffusion magnetic resonance imaging data from 161 participants including subjects with healthy controls, AD, stable and converting mild cognitive impairment, were selected for group-wise comparisons. A multivariate distance matrix regression (MDMR) analysis was performed to detect abnormality in brain structural network along with disease progression. Based on the seed regions returned by the MDMR analysis, supervised learning was applied to evaluate the disease predictive performance. Nine brain regions, including the left orbital part of superior and middle frontal gyrus, the bilateral supplementary motor area, the bilateral insula, the left hippocampus, the left putamen, and the left thalamus demonstrated extremely significant structural pattern changes along with the progression of AD. The disease classification was more efficient when based on the key connectivity related to these seed regions than when based on whole-brain structural connectivity. MDMR analysis reveals brain network reorganization caused by AD pathology. The key structural connectivity detected in this study exhibits promising distinguishing capability to predict prodromal AD patients.

Multiparametric graph theoretical analysis reveals altered structural and functional network topology in Alzheimer's disease

Alzheimer's disease (AD), an irreversible neurodegenerative disease, is the most common type of dementia in elderly people. This present study incorporated multiple structural and functional connectivity metrics into a graph theoretical analysis framework and investigated alterations in brain network topology in patients with mild cognitive impairment (MCI) and AD. By using this multiparametric analysis, we expected different connectivity metrics may reflect additional or complementary information regarding the topological changes in brain networks in MCI or AD. In our study, a total of 73 subjects participated in this study and underwent the magnetic resonance imaging scans. For the structural network, we compared commonly used connectivity metrics, including fractional anisotropy and normalized streamline count, with multiple diffusivity-based metrics. We compared Pearson correlation and covariance by investigating their sensitivities to functional network topology. Significant disruption of structural network topology in MCI and AD was found predominantly in regions within the limbic system, prefrontal and occipital regions, in addition to widespread alterations of local efficiency. At a global scale, our results showed that the disruption of the structural network was consistent across different edge definitions and global network metrics from the MCI to AD stages. Significant changes in connectivity and tract-specific diffusivity were also found in several limbic connections. Our findings suggest that tract-specific metrics (e.g., fractional anisotropy and diffusivity) provide more sensitive and interpretable measurements than does metrics based on streamline count. Besides, the use of inversed radial diffusivity provided additional information for understanding alterations in network topology caused by AD progression and its possible origins. Use of this proposed multiparametric network analysis framework may facilitate early MCI diagnosis and AD prevention.

Alzheimer's disease and the processing of uncertainty during choice task performance: Executive dysfunction within the Hick-Hyman law

The Hick-Hyman law states that choice response time (RT) increases linearly with increasing information uncertainty. Neuroimaging studies suggest that the representation of uncertainty in support of response generation is mediated by the cognitive control network (CCN), which is disrupted in Alzheimer's disease (AD). Thus, we predicted that patients with AD would be sensitive to increased uncertainty particularly under conditions that place demands on the internal representation of uncertainty, and that choice RT performance under these conditions would be associated with performance on tests of executive function. Cognitively normal older adults (CN) and patients with AD completed card-sorting tasks that separately manipulated either externally cued uncertainty (i.e., number of sorting piles with a fixed probability of each stimulus type) or more internally driven uncertainty (i.e., the probability of each stimulus type with a fixed number of sorting piles). Consistent with our predictions, AD patients were impaired relative to CN particularly on the internally driven uncertainty task, and RT in this task was associated with performance on neuropsychological measures of executive functioning but not episodic memory. We suggest that this pattern of findings is consistent with presumed disruptions to the CCN in AD and provides neuropsychological evidence in support of the role of the CCN in the representation of uncertainty.

Dissociable Effects of Aging on Salience Subnetwork Connectivity Mediate Age-Related Changes in Executive Function and Affect

Aging is associated with both changes in affective experience and attention. An intrinsic brain network subserving these functions, the salience network, has not shown clear evidence of a corresponding age-related change. We propose a solution to this discrepancy: that aging differentially affects the connectivity of two dissociated subsystems of the salience network identified in our prior research (Touroutoglou et al., 2012). We examined the age-related changes in intrinsic connectivity between a dorsal and a ventral salience subsystem in a sample of 111 participants ranging in age from 18 years to 81 years old. We predicted that connectivity within the ventral subsystem is relatively preserved with age, while connectivity in the dorsal subsystem declines. Our findings showed that the connectivity within the ventral subsystem was not only preserved but it actually increased with age, whereas the connectivity within the dorsal subsystem decreased with age. Furthermore, age-related increase in arousal experience was partially mediated by age-related increases in ventral salience subsystem, whereas age-related decline in executive function was fully mediated by age-related decreases in dorsal salience subsystem connectivity. These findings explain previously conflicting results on age-related changes in the salience network, and suggest a mechanism for relatively preserved affective function in the elderly.

Voxelwise-based Brain Function Network using Multi-Graph Model

In the research of the fMRI based brain functional network, the pairwise correlation between vertices usually means the similarity between BOLD signals. Our analysis found that the low (0:01–0:06 Hz), intermediate (0:06–0:15 Hz), and high (0:15–0:2 Hz) bands of the BOLD signal are not synchronous. Therefore, this paper presents a voxelwise based multi-frequency band brain functional network model, called Multi-graph brain functional network. First, our analysis found the low-frequency information on the BOLD signal of the brain functional network obscures the other information because of its high intensity. Then, a low-, intermediate-, and high-band brain functional networks were constructed by dividing the BOLD signals. After that, using complex network analysis, we found that different frequency bands have different properties; the modulation in low-frequency is higher than that of the intermediate and high frequency. The power distributions of different frequency bands were also significantly different, and the ‘hub’ vertices under all frequency bands are evenly distributed. Compared to a full-frequency network, the multi-graph model enhances the accuracy of the classification of Alzheimer’s disease.

Decreased cingulo-opercular network functional connectivity mediates the impact of aging on visual processing speed

The neural factors that account for the visual processing speed reduction in aging are incompletely understood. Based on previous reports of age-related decreases in the intrinsic functional connectivity (iFC) within the cingulo-opercular network and its relevance for processing speed, we hypothesized that these decreases are associated with age-related reductions in visual processing speed. We used a whole-report task and modeling based on Bundesen's "theory of visual attention" to parameterize visual processing speed in 91 healthy participants aged from 20 to 77 years. iFC was estimated using independent component analysis of resting-state functional magnetic resonance imaging data. From the clusters within the cingulo-opercular network exhibiting age-related decreased iFC, we found a cluster in the left insula to be particularly associated with visual processing speed and to mediate the age effect on visual speed. This mediation was not observed for age-related decreased iFC in other networks or for other attentional parameters. Our results point to the iFC in the cingulo-opercular network, represented by the left insula, as being a relevant marker for visual processing speed changes in aging.

BRANT: A Versatile and Extendable Resting-State fMRI Toolkit

Data processing toolboxes for resting-state functional MRI (rs-fMRI) have provided us with a variety of functions and user friendly graphic user interfaces (GUIs). However, many toolboxes only cover a certain range of functions, and use exclusively designed GUIs. To facilitate data processing and alleviate the burden of manually drawing GUIs, we have developed a versatile and extendable MATLAB-based toolbox, BRANT (BRAinNetome fmri Toolkit), with a wide range of rs-fMRI data processing functions and code-generated GUIs. During the implementation, we have also empowered the toolbox with parallel computing techniques, efficient file handling methods for compressed file format, and one-line scripting. In BRANT, users can find rs-fMRI batch processing functions for preprocessing, brain spontaneous activity analysis, functional connectivity analysis, complex network analysis, statistical analysis, and results visualization, while developers can quickly publish scripts with code-generated GUIs.

Gray Matter Abnormalities Associated With Chronic Back Pain: A Meta-Analysis of Voxel-based Morphometric Studies

BACKGROUND

Studies employing voxel-based morphometry have reported inconsistent findings on the association of gray matter (GM) abnormalities with chronic back pain (CBP). We, therefore, performed a meta-analysis of available studies to identify the most consistent GM regions associated with CBP.

METHODS

The PubMed, Embase, and Web of Science databases were searched from January 2000 to May 29, 2016. Comprehensive meta-analyses of whole-brain voxel-based morphometry studies to identify the most robust GM abnormalities in CBP were conducted using the Seed-based d Mapping software package.

RESULTS

A total of 10 studies, comprising 293 patients with CBP and 624 healthy controls, were included in the meta-analyses. The most robust findings of regional GM decreases in patients with CBP compared with healthy controls were identified in the bilateral medial prefrontal cortex extending to the anterior cingulate cortex, the right medial prefrontal cortex extending to the orbitofrontal cortex. Regional GM decreases in the left anterior insula were less robustly observed.

CONCLUSIONS

The present study demonstrates a pattern of GM alterations in CBP. These data further advance our understanding of the pathophysiology of CBP.

Noradrenergic Dysfunction in Alzheimer's and Parkinson's Diseases-An Overview of Imaging Studies

Noradrenergic dysfunction contributes to cognitive impairment in Alzheimer's Disease (AD) and Parkinson's Disease (PD). Conventional therapeutic strategies seek to enhance cholinergic and dopaminergic neurotransmission in AD and PD, respectively, and few studies have examined noradrenergic dysfunction as a target for medication development. We review the literature of noradrenergic dysfunction in AD and PD with a focus on human imaging studies that implicate the locus coeruleus (LC) circuit. The LC sends noradrenergic projections diffusely throughout the cerebral cortex and plays a critical role in attention, learning, working memory, and cognitive control. The LC undergoes considerable degeneration in both AD and PD. Advances in magnetic resonance imaging have facilitated greater understanding of how structural and functional alteration of the LC may contribute to cognitive decline in AD and PD. We discuss the potential roles of the noradrenergic system in the pathogenesis of AD and PD with an emphasis on postmortem anatomical studies, structural MRI studies, and functional MRI studies, where we highlight changes in LC connectivity with the default mode network (DMN). LC degeneration may accompany deficient capacity in suppressing DMN activity and increasing saliency and task control network activities to meet behavioral challenges. We finish by proposing potential and new directions of research to address noradrenergic dysfunction in AD and PD.

Altered Functional Connectivity of Insular Subregions in Alzheimer's Disease

Recent researches have demonstrated that the insula is the crucial hub of the human brain networks and most vulnerable region of Alzheimer’s disease (AD). However, little is known about the changes of functional connectivity of insular subregions in the AD patients. In this study, we collected resting-state functional magnetic resonance imaging (fMRI) data including 32 AD patients and 38 healthy controls (HCs). By defining three subregions of insula, we mapped whole-brain resting-state functional connectivity (RSFC) and identified several distinct RSFC patterns of the insular subregions: For positive connectivity, three cognitive-related RSFC patterns were identified within insula that suggest anterior-to-posterior functional subdivisions: (1) an dorsal anterior zone of the insula that exhibits RSFC with executive control network (ECN); (2) a ventral anterior zone of insula, exhibits functional connectivity with the salience network (SN); (3) a posterior zone along the insula exhibits functional connectivity with the sensorimotor network (SMN). In addition, we found significant negative connectivities between the each insular subregion and several special default mode network (DMN) regions. Compared with controls, the AD patients demonstrated distinct disruption of positive RSFCs in the different network (ECN and SMN), suggesting the impairment of the functional integrity. There were no differences of the positive RSFCs in the SN between the two groups. On the other hand, several DMN regions showed increased negative RSFCs to the sub-region of insula in the AD patients, indicating compensatory plasticity. Furthermore, these abnormal insular subregions RSFCs are closely correlated with cognitive performances in the AD patients. Our findings suggested that different insular subregions presented distinct RSFC patterns with various functional networks, which are differently affected in the AD patients.

Aging and Network Properties: Stability Over Time and Links with Learning during Working Memory Training

Growing evidence suggests that healthy aging affects the configuration of large-scale functional brain networks. This includes reducing network modularity and local efficiency. However, the stability of these effects over time and their potential role in learning remain poorly understood. The goal of the present study was to further clarify previously reported age effects on "resting-state" networks, to test their reliability over time, and to assess their relation to subsequent learning during training. Resting-state fMRI data from 23 young (YA) and 20 older adults (OA) were acquired in 2 sessions 2 weeks apart. Graph-theoretic analyses identified both consistencies in network structure and differences in module composition between YA and OA, suggesting topological changes and less stability of functional network configuration with aging. Brain-wide, OA showed lower modularity and local efficiency compared to YA, consistent with the idea of age-related functional dedifferentiation, and these effects were replicable over time. At the level of individual networks, OA consistently showed greater participation and lower local efficiency and within-network connectivity in the cingulo-opercular network, as well as lower intra-network connectivity in the default-mode network and greater participation of the somato-sensorimotor network, suggesting age-related differential effects at the level of specialized brain modules. Finally, brain-wide network properties showed associations, albeit limited, with learning rates, as assessed with 10 days of computerized working memory training administered after the resting-state sessions, suggesting that baseline network configuration may influence subsequent learning outcomes. Identification of neural mechanisms associated with learning-induced plasticity is important for further clarifying whether and how such changes predict the magnitude and maintenance of training gains, as well as the extent and limits of cognitive transfer in both younger and older adults.

Impact of Total Knee Arthroplasty with General Anesthesia on Brain Networks: Cognitive Efficiency and Ventricular Volume Predict Functional Connectivity Decline in Older Adults

Using resting state functional magnetic resonance imaging (RS-fMRI), we explored: 1) pre- to post-operative changes in functional connectivity in default mode, salience, and central executive networks after total knee arthroplasty (TKA) with general anesthesia, and 2) the contribution of cognitive/brain reserve metrics these resting state functional declines. Individuals age 60 and older electing unilateral total knee arthroplasty (TKA; n = 48) and non-surgery peers with osteoarthritis (n = 45) completed baseline cognitive testing and baseline and post-surgery (post-baseline, 48-h post-surgery) brain MRI. We acquired cognitive and brain estimates for premorbid (vocabulary, reading, education, intracranial volume) and current (working memory, processing speed, declarative memory, ventricular volume) reserve. Functional network analyses corrected for pain severity and pain medication. The surgery group declined in every functional network of interest (p < 0.001). Relative to non-surgery peers, 23% of surgery participants declined in at least one network and 15% of the total TKA sample declined across all networks. Larger preoperative ventricular volume and lower scores on preoperative metrics of processing speed and working memory predicted default mode network connectivity decline. Premorbid cognitive and premorbid brain reserve did not predict decline. Within 48 hours after surgery, at least one fourth of the older adult sample showed significant functional network decline. Metrics of current brain status (ventricular volume), working memory, and processing speed predicted the severity of default mode network connectivity decline. These findings demonstrate the relevance of preoperative cognition and brain integrity on acute postoperative functional network change.

Brain gray matter changes in type 2 diabetes mellitus: A meta-analysis of whole-brain voxel-based morphometry study

AIMS

We aimed to identify alterations in global gray matter volumes (GMV) and consistent regional abnormalities in T2DM patients via meta-analysis.

METHODS

A systematic search for relevant studies indexed in the PubMed and Embase databases was conducted. A quantitative meta-analysis of volumetric and whole-brain VBM data was conducted using STATA v.12.0 and AES-SDM software packages, respectively.

RESULTS

A total of 15 volumetric studies and five VBM studies of GM in T2DM patients vs. healthy controls (HCs) were identified. The volumetric meta-analysis showed that the GMV of patients with T2DM is lower than in HCs (SMD = -0.56, 95% CI = -0.81 to -0.31, P 0.01). The whole-brain VBM meta-analysis revealed GM reductions in the left superior temporal gyrus, the right middle temporal gyrus, the right rolandic operculum, and the left fusiform gyrus in T2DM patients compared with HCs. Meta-regression analysis showed that Mini-Mental State Examination (MMSE) scores have a positive relationship with GMV in the right insula.

CONCLUSIONS

The results showed a reduced volume of whole and regional GM in T2DM patients, which may indicate a risk for dementia. Further longitudinal research is needed to confirm GM changes, cognitive dysfunction, and their relationship in T2DM.

Intranetwork and internetwork connectivity in patients with Alzheimer disease and the association with cerebrospinal fluid biomarker levels

BACKGROUND

In the last decade, many studies have reported abnormal connectivity within the default mode network (DMN) in patients with Alzheimer disease. Few studies, however, have investigated other networks and their association with pathophysiological proteins obtained from cerebrospinal fluid (CSF).

METHODS

We performed 3 T imaging in patients with mild Alzheimer disease, patients with amnestic mild cognitive impairment (aMCI) and healthy controls, and we collected CSF samples from the patients with aMCI and mild Alzheimer disease. We analyzed 57 regions from 8 networks. Additionally, we performed correlation tests to investigate possible associations between the networks' functional connectivity and the protein levels obtained from the CSF of patients with aMCI and Alzheimer disease.

RESULTS

Our sample included 41 patients with Alzheimer disease, 35 with aMCI and 48 controls. We found that the main connectivity abnormalities in those with Alzheimer disease occurred between the DMN and task-positive networks: these patients presented not only a decreased anticorrelation between some regions, but also an inversion of the correlation signal (positive correlation instead of anticorrelation). Those with aMCI did not present statistically different connectivity from patients with Alzheimer disease or controls. Abnormal levels of CSF proteins were associated with functional disconnectivity between several regions in both the aMCI and mild Alzheimer disease groups, extending well beyond the DMN or temporal areas.

LIMITATIONS

The presented data are cross-sectional in nature, and our findings are dependent on the choice of seed regions used.

CONCLUSION

We found that the main functional connectivity abnormalities occur between the DMN and task-positive networks and that the pathological levels of CSF biomarkers correlate with functional connectivity disruption in patients with Alzheimer disease.

White Matter Hyperintensity Load Modulates Brain Morphometry and Brain Connectivity in Healthy Adults: A Neuroplastic Mechanism?

White matter hyperintensities (WMHs) are acquired lesions that accumulate and disrupt neuron-to-neuron connectivity. We tested the associations between WMH load and (1) regional grey matter volumes and (2) functional connectivity of resting-state networks, in a sample of 51 healthy adults. Specifically, we focused on the positive associations (more damage, more volume/connectivity) to investigate a potential route of adaptive plasticity. WMHs were quantified with an automated procedure. Voxel-based morphometry was carried out to model grey matter. An independent component analysis was run to extract the anterior and posterior default-mode network, the salience network, the left and right frontoparietal networks, and the visual network. Each model was corrected for age, global levels of atrophy, and indices of brain and cognitive reserve. Positive associations were found with morphometry and functional connectivity of the anterior default-mode network and salience network. Within the anterior default-mode network, an association was found in the left mediotemporal-limbic complex. Within the salience network, an association was found in the right parietal cortex. The findings support the suggestion that, even in the absence of overt disease, the brain actuates a compensatory (neuroplastic) response to the accumulation of WMH, leading to increases in regional grey matter and modified functional connectivity.

Aberrant spontaneous low-frequency brain activity in amnestic mild cognitive impairment: A meta-analysis of resting-state fMRI studies

Recent resting-state functional magnetic resonance imaging (rs-fMRI) studies have provided strong evidence of abnormal spontaneous brain activity in amnestic mild cognitive impairment (aMCI). However, the conclusions have been inconsistent. A meta-analysis of whole-brain rs-fMRI studies that measured differences in the amplitude of low-frequency fluctuations (ALFF) between aMCI patients and healthy controls was conducted using the Seed-based d Mapping software package. Twelve studies reporting 14 datasets were included in the meta-analysis. Compared to healthy controls, patients with aMCI showed decreased ALFFs in the bilateral precuneus/posterior cingulate cortices, bilateral frontoinsular cortices, left occipitotemporal cortex, and right supramarginal gyrus and increased ALFFs in the right lingual gyrus, left middle occipital gyrus, left hippocampus, and left inferior temporal gyrus. A meta-regression analysis demonstrated that the increased severity of cognitive impairment in aMCI patients was associated with greater decreases in ALFFs in the cuneus/precuneus cortices. Our comprehensive meta-analysis suggests that aMCI is associated with widespread aberrant regional spontaneous brain activity, predominantly involving the default mode, salience, and visual networks, which contributes to understanding its pathophysiology.

Resting-state network dysfunction in Alzheimer's disease: A systematic review and meta-analysis

Introduction

We performed a systematic review and meta-analysis of the Alzheimer's disease (AD) literature to examine consistency of functional connectivity alterations in AD dementia and mild cognitive impairment, using resting-state functional magnetic resonance imaging.

Methods

Studies were screened using a standardized procedure. Multiresolution statistics were performed to assess the spatial consistency of findings across studies.

Results

Thirty-four studies were included (1363 participants, average 40 per study). Consistent alterations in connectivity were found in the default mode, salience, and limbic networks in patients with AD dementia, mild cognitive impairment, or in both groups. We also identified a strong tendency in the literature toward specific examination of the default mode network.

Discussion

Convergent evidence across the literature supports the use of resting-state connectivity as a biomarker of AD. The locations of consistent alterations suggest that highly connected hub regions in the brain might be an early target of AD.

Visual deprivation selectively reshapes the intrinsic functional architecture of the anterior insula subregions

The anterior insula (AI) is the core hub of salience network that serves to identify the most relevant stimuli among vast sensory inputs and forward them to higher cognitive regions to guide behaviour. As blind subjects were usually reported with changed perceptive abilities for salient non-visual stimuli, we hypothesized that the resting-state functional network of the AI is selectively reorganized after visual deprivation. The resting-state functional connectivity (FC) of the bilateral dorsal and ventral AI was calculated for twenty congenitally blind (CB), 27 early blind (EB), 44 late blind (LB) individuals and 50 sighted controls (SCs). The FCs of the dorsal AI were strengthened with the dorsal visual stream, while weakened with the ventral visual stream in the blind than the SCs; in contrast, the FCs of the ventral AI of the blind was strengthened with the ventral visual stream. Furthermore, these strengthened FCs of both the dorsal and ventral AI were partially negatively associated with the onset age of blindness. Our result indicates two parallel pathways that selectively transfer non-visual salient information between the deprived “visual” cortex and salience network in blind subjects.

Characterization of functional brain activity and connectivity using EEG and fMRI in patients with sickle cell disease

Sickle cell disease (SCD) is a red blood cell disorder that causes many complications including life-long pain. Treatment of pain remains challenging due to a poor understanding of the mechanisms and limitations to characterize and quantify pain. In the present study, we examined simultaneously recording functional MRI (fMRI) and electroencephalogram (EEG) to better understand neural connectivity as a consequence of chronic pain in SCD patients. We performed independent component analysis and seed-based connectivity on fMRI data. Spontaneous power and microstate analysis was performed on EEG-fMRI data. ICA analysis showed that patients lacked activity in the default mode network (DMN) and executive control network compared to controls. EEG-fMRI data revealed that the insula cortex's role in salience increases with age in patients. EEG microstate analysis showed patients had increased activity in pain processing regions. The cerebellum in patients showed a stronger connection to the periaqueductal gray matter (involved in pain inhibition), and negative connections to pain processing areas. These results suggest that patients have reduced activity of DMN and increased activity in pain processing regions during rest. The present findings suggest resting state connectivity differences between patients and controls can be used as novel biomarkers of SCD pain.

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Simultaneous EEG-fMRI recordings revealed altered connectivity in sickle cell patients.

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Reduced activity observed in default mode network and executive control network.

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Patients' salience network strength increases with age; opposite seen in controls.

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EEG-fMRI parameters reflect disease severity in sickle cell patients.

A Triple Network Connectivity Study of Large-Scale Brain Systems in Cognitively Normal APOE4 Carriers

The triple network model, consisting of the central executive network (CEN), salience network (SN) and default mode network (DMN), has been recently employed to understand dysfunction in core networks across various disorders. Here we used the triple network model to investigate the large-scale brain networks in cognitively normal apolipoprotein e4 (APOE4) carriers who are at risk of Alzheimer’s disease (AD). To explore the functional connectivity for each of the three networks and the effective connectivity among them, we evaluated 17 cognitively normal individuals with a family history of AD and at least one copy of the APOE4 allele and compared the findings to those of 12 individuals who did not carry the APOE4 gene or have a family history of AD, using independent component analysis (ICA) and Bayesian network (BN) approach. Our findings indicated altered within-network connectivity that suggests future cognitive decline risk, and preserved between-network connectivity that may support their current preserved cognition in the cognitively normal APOE4 allele carriers. The study provides novel sights into our understanding of the risk factors for AD and their influence on the triple network model of major psychopathology.

Altered Intranetwork and Internetwork Functional Connectivity in Type 2 Diabetes Mellitus With and Without Cognitive Impairment

Type 2 diabetes mellitus (T2DM) is associated with cognitive impairment. We investigated whether alterations of intranetwork and internetwork functional connectivity with T2DM progression exist, by using resting-state functional MRI. MRI data were analysed from 19 T2DM patients with normal cognition (DMCN) and 19 T2DM patients with cognitive impairment (DMCI), 19 healthy controls (HC). Functional connectivity among 36 previously well-defined brain regions which consisted of 5 resting-state network (RSN) systems [default mode network (DMN), dorsal attention network (DAN), control network (CON), salience network (SAL) and sensorimotor network (SMN)] was investigated at 3 levels (integrity, network and connectivity). Impaired intranetwork and internetwork connectivity were found in T2DM, especially in DMCI, on the basis of the three levels of analysis. The bilateral posterior cerebellum, the right insula, the DMN and the CON were mainly involved in these changes. The functional connectivity strength of specific brain architectures in T2DM was found to be associated with haemoglobin A1c (HbA1c), cognitive score and illness duration. These network alterations in intergroup differences, which were associated with brain functional impairment due to T2DM, indicate that network organizations might be potential biomarkers for predicting the clinical progression, evaluating the cognitive impairment, and further understanding the pathophysiology of T2DM.

Distinct Aging Effects on Functional Networks in Good and Poor Cognitive Performers

Brain network hubs are susceptible to normal aging processes and disruptions of their functional connectivity are detrimental to decline in cognitive functions in older adults. However, it remains unclear how the functional connectivity of network hubs cope with cognitive heterogeneity in an aging population. This study utilized cognitive and resting-state functional magnetic resonance imaging data, cluster analysis, and graph network analysis to examine age-related alterations in the network hubs’ functional connectivity of good and poor cognitive performers. Our results revealed that poor cognitive performers showed age-dependent disruptions in the functional connectivity of the right insula and posterior cingulate cortex (PCC), while good cognitive performers showed age-related disruptions in the functional connectivity of the left insula and PCC. Additionally, the left PCC had age-related declines in the functional connectivity with the left medial prefrontal cortex (mPFC) and anterior cingulate cortex (ACC). Most interestingly, good cognitive performers showed age-related declines in the functional connectivity of the left insula and PCC with their right homotopic structures. These results may provide insights of neuronal correlates for understanding individual differences in aging. In particular, our study suggests prominent protection roles of the left insula and PCC and bilateral ACC in good performers.

Cognitive Decline and Reorganization of Functional Connectivity in Healthy Aging: The Pivotal Role of the Salience Network in the Prediction of Age and Cognitive Performances

Normal aging is related to a decline in specific cognitive processes, in particular in executive functions and memory. In recent years a growing number of studies have focused on changes in brain functional connectivity related to cognitive aging. A common finding is the decreased connectivity within multiple resting state networks, including the default mode network (DMN) and the salience network. In this study, we measured resting state activity using fMRI and explored whether cognitive decline is related to altered functional connectivity. To this end we used a machine learning approach to classify young and old participants from functional connectivity data. The originality of the approach consists in the prediction of the performance and age of the subjects based on functional connectivity by using a machine learning approach. Our findings showed that the connectivity profile between specific networks predicts both the age of the subjects and their cognitive abilities. In particular, we report that the connectivity profiles between the salience and visual networks, and the salience and the anterior part of the DMN, were the features that best predicted the age. Moreover, independently of the age of the subject, connectivity between the salience network and various specific networks (i.e., visual, frontal) predicted episodic memory skills either based on a standard assessment or on an autobiographical memory task, and short-term memory binding. Finally, the connectivity between the salience and the frontal networks predicted inhibition and updating performance, but this link was no longer significant after removing the effect of age. Our findings confirm the crucial role of episodic memory and executive functions in cognitive aging and suggest a pivotal role of the salience network in neural reorganization in aging.

Effects of Body Mass Index and Body Fat Percent on Default Mode, Executive Control, and Salience Network Structure and Function

It is well established that obesity decreases overall life expectancy and increases the risk of several adverse health conditions. Mounting evidence indicates that body fat is likely also associated with structural and functional brain changes, reduced cognitive function, and greater impulsivity. However, previously reported differences in brain structure and function have been variable across studies and difficult to reconcile due to sample population and methodological differences. To clarify these issues, we correlated two independent measures of body composition—i.e., body mass index (BMI) and body fat percent (BFP)—with structural and functional neuroimaging data obtained from a cohort of 32 neurologically healthy adults. Whole-brain voxel-wise analyses indicated that higher BMI and BFP were associated with widespread decreases in gray matter volume, white matter volume, and white matter microstructure (including several regions, such as the striatum and orbitofrontal cortex, which may influence value assessment, habit formation, and decision-making). Moreover, closer examination of resting state functional connectivity, white matter volume, and white matter microstructure throughout the default mode network (DMN), executive control network (ECN), and salience network (SN) revealed that higher BMI and BFP were associated with increased SN functional connectivity and decreased white matter volumes throughout all three networks (i.e., the DMN, ECN, and SN). Taken together, these findings: (1) offer a biologically plausible explanation for reduced cognitive performance, greater impulsivity, and altered reward processing among overweight individuals, and (2) suggest neurobiological mechanisms (i.e., altered functional and structural brain connectivity) that may affect overweight individuals' ability to establish and maintain healthy lifestyle choices.

Aberrant salience network and its functional coupling with default and executive networks in minimal hepatic encephalopathy: a resting-state fMRI study

The purposes of this study are to explore functional alterations in salience network (SN) and its functional coupling with default mode (DMN) and central executive (CEN) networks in minimal hepatic encephalopathy (MHE). Twenty cirrhotic patients with MHE, 23 cirrhotic patients without MHE (NHE), and 18 controls underwent resting-state fMRI and psychometric hepatic encephalopathy score (PHES) test. Independent component analysis was performed to obtain DMN (including three subsystems: anterior, inferior-posterior, and superior-posterior DMN [a/ip/spDMN]), SN, and CEN (including three subsystems: left-ventral, right-ventral, and dorsal CEN [lv/rv/dCEN]). The intrinsic functional connectivity (iFC) within (intra-iFC) and between (inter-iFC and time-lagged inter-iFC) networks was measured. MHE patients showed decreased intra-iFC within aDMN, SN, lvCEN, and rvCEN; and decreased inter-iFC and time-lagged inter-iFC between SN and ipDMN/spDMN/lvCEN and increased inter-iFC and time-lagged inter-iFC between SN and aDMN, compared with controls. A progressive trend in connectivity alterations was found as the disease developed from NHE to MHE. The inter-iFC between ipDMN/spDMN and SN was significantly correlated with PHES score. In conclusion, an aberrant SN and its functional interaction with the DMN/CEN are core features of MHE that are associated with disease progression and may play an important role in neurocognitive dysfunction in MHE.

Effects of Cognitive Training on Resting-State Functional Connectivity of Default Mode, Salience, and Central Executive Networks

Neuroimaging studies have documented that aging can disrupt certain higher cognitive systems such as the default mode network (DMN), the salience network and the central executive network (CEN). The effect of cognitive training on higher cognitive systems remains unclear. This study used a 1-year longitudinal design to explore the cognitive training effect on three higher cognitive networks in healthy older adults. The community-living healthy older adults were divided into two groups: the multi-domain cognitive training group (24 sessions of cognitive training over a 3-months period) and the wait-list control group. All subjects underwent cognitive measurements and resting-state functional magnetic resonance imaging scanning at baseline and at 1 year after the training ended. We examined training-related changes in functional connectivity (FC) within and between three networks. Compared with the baseline, we observed maintained or increased FC within all three networks after training. The scans after training also showed maintained anti-correlation of FC between the DMN and CEN compared to the baseline. These findings demonstrated that cognitive training maintained or improved the functional integration within networks and the coupling between the DMN and CEN in older adults. Our findings suggested that multi-domain cognitive training can mitigate the aging-related dysfunction of higher cognitive networks.

Distinct Changes in Functional Connectivity in Posteromedial Cortex Subregions during the Progress of Alzheimer's Disease

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder which causes dementia, especially in the elderly. The posteromedial cortex (PMC), which consists of several subregions involved in distinct functions, is one of the critical regions associated with the progression and severity of AD. However, previous studies always ignored the heterogeneity of the PMC and focused on one stage of AD. Using resting-state functional magnetic resonance imaging, we studied the respective alterations of each subregion within the PMC along the progression of AD. Our data set consisted of 21 healthy controls, 18 patients with mild cognitive impairment (MCI), 17 patients with mild AD (mAD), and 18 patients with severe AD (sAD). We investigated the functional alterations of each subregion within the PMC in different stages of AD. We found that subregions within the PMC have differential vulnerability in AD. Disruptions in functional connectivity began in the transition area between the precuneus and the posterior cingulate cortex (PCC) and then extended to other subregions of the PMC. In addition, each of these subregions was associated with distinct alterations in the functional networks that we were able to relate to AD. Our research demonstrated functional changes within the PMC in the progression of AD and may elucidate potential biomarkers for clinical applications.

Enhanced spontaneous functional connectivity of the superior temporal gyrus in early deafness

Early auditory deprivation may drive the auditory cortex into cross-modal processing of non-auditory sensory information. In a recent study, we had shown that early deaf subjects exhibited increased activation in the superior temporal gyrus (STG) bilaterally during visual spatial working memory; however, the changes in the organization of the STG related spontaneous functional network, and their cognitive relevance are still unknown. To clarify this issue, we applied resting state functional magnetic resonance imaging on 42 early deafness (ED) and 40 hearing controls (HC). We also acquired the visual spatial and numerical n-back working memory (WM) information in these subjects. Compared with hearing subjects, the ED exhibited faster reaction time of visual WM tasks in both spatial and numerical domains. Furthermore, ED subjects exhibited significantly increased functional connectivity between the STG (especially of the right hemisphere) and bilateral anterior insula and dorsal anterior cingulated cortex. Finally, the functional connectivity of STG could predict visual spatial WM performance, even after controlling for numerical WM performance. Our findings suggest that early auditory deprivation can strengthen the spontaneous functional connectivity of STG, which may contribute to the cross-modal involvement of this region in visual working memory.

Three Large-Scale Functional Brain Networks from Resting-State Functional MRI in Subjects with Different Levels of Cognitive Impairment

Normal aging and to a greater degree degenerative brain diseases such as Alzheimer's disease (AD), cause changes in the brain's structure and function. Degenerative changes in brain structure and decline in its function are associated with declines in cognitive ability. Early detection of AD is a key priority in dementia services and research. However, depending on the disease progression, neurodegenerative manifestations, such as cerebral atrophy, are detected late in course of AD. Functional changes in the brain may be an indirect indicator of trans-synaptic activity and they usually appear prior to structural changes in AD. Resting-state functional magnetic resonance imaging (RS-fMRI) has recently been highlighted as a new technique for interrogating intrinsic functional connectivity networks. Among the majority of RS-fMRI studies, the default mode network (DMN), salience network (SN), and central executive network (CEN) gained particular focus because alterations to their functional connectivity were observed in subjects who had AD, who had mild cognitive impairment (MCI), or who were at high risk for AD. Herein, we present a review of the current research on changes in functional connectivity, as measured by RS-fMRI. We focus on the DMN, SN, and CEN to describe RS-fMRI results from three groups: normal healthy aging, MCI and AD.

Fitness, but not physical activity, is related to functional integrity of brain networks associated with aging

Greater physical activity and cardiorespiratory fitness are associated with reduced age-related cognitive decline and lower risk for dementia. However, significant gaps remain in the understanding of how physical activity and fitness protect the brain from adverse effects of brain aging. The primary goal of the current study was to empirically evaluate the independent relationships between physical activity and fitness with functional brain health among healthy older adults, as measured by the functional connectivity of cognitively and clinically relevant resting state networks. To build context for fitness and physical activity associations in older adults, we first demonstrate that young adults have greater within-network functional connectivity across a broad range of cortical association networks. Based on these results and previous research, we predicted that individual differences in fitness and physical activity would be most strongly associated with functional integrity of the networks most sensitive to aging. Consistent with this prediction, and extending on previous research, we showed that cardiorespiratory fitness has a positive relationship with functional connectivity of several cortical networks associated with age-related decline, and effects were strongest in the default mode network (DMN). Furthermore, our results suggest that the positive association of fitness with brain function can occur independent of habitual physical activity. Overall, our findings provide further support that cardiorespiratory fitness is an important factor in moderating the adverse effects of aging on cognitively and clinically relevant functional brain networks.

Aberrant intra- and inter-network connectivity architectures in Alzheimer's disease and mild cognitive impairment

Alzheimer’s disease (AD) patients and those with high-risk mild cognitive impairment are increasingly considered to have dysfunction syndromes. Large-scale network studies based on neuroimaging techniques may provide additional insight into AD pathophysiology. The aim of the present study is to evaluate the impaired network functional connectivity with the disease progression. For this purpose, we explored altered functional connectivities based on previously well-defined brain areas that comprise the five key functional systems [the default mode network (DMN), dorsal attention network (DAN), control network (CON), salience network (SAL), sensorimotor network (SMN)] in 35 with AD and 27 with mild cognitive impairment (MCI) subjects, compared with 27 normal cognitive subjects. Based on three levels of analysis, we found that intra- and inter-network connectivity were impaired in AD. Importantly, the interaction between the sensorimotor and attention functions was first attacked at the MCI stage and then extended to the key functional systems in the AD individuals. Lower cognitive ability (lower MMSE scores) was significantly associated with greater reductions in intra- and inter-network connectivity across all patient groups. These profiles indicate that aberrant intra- and inter-network dysfunctions might be potential biomarkers or predictors of AD progression and provide new insight into AD pathophysiology.

The Affective Neuroscience of Aging

Although aging is associated with clear declines in physical and cognitive processes, emotional functioning fares relatively well. Consistent with this behavioral profile, two core emotional brain regions, the amygdala and ventromedial prefrontal cortex, show little structural and functional decline in aging, compared with other regions. However, emotional processes depend on interacting systems of neurotransmitters and brain regions that go beyond these structures. This review examines how age-related brain changes influence processes such as attending to and remembering emotional stimuli, regulating emotion, and recognizing emotional expressions, as well as empathy, risk taking, impulsivity, behavior change, and attentional focus.

Resting state functional connectivity differences between behavioral variant frontotemporal dementia and Alzheimer's disease

INTRODUCTION

Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) are the most common types of early-onset dementia. Early differentiation between both types of dementia may be challenging due to heterogeneity and overlap of symptoms. Here, we apply resting state functional magnetic resonance imaging (fMRI) to study functional brain connectivity differences between AD and bvFTD.

METHODS

We used resting state fMRI data of 31 AD patients, 25 bvFTD patients, and 29 controls from two centers specialized in dementia. We studied functional connectivity throughout the entire brain, applying two different analysis techniques, studying network-to-region and region-to-region connectivity. A general linear model approach was used to study group differences, while controlling for physiological noise, age, gender, study center, and regional gray matter volume.

RESULTS

Given gray matter differences, we observed decreased network-to-region connectivity in bvFTD between (a) lateral visual cortical network and lateral occipital and cuneal cortex, and (b) auditory system network and angular gyrus. In AD, we found decreased network-to-region connectivity between the dorsal visual stream network and lateral occipital and parietal opercular cortex. Region-to-region connectivity was decreased in bvFTD between superior temporal gyrus and cuneal, supracalcarine, intracalcarine cortex, and lingual gyrus.

CONCLUSION

We showed that the pathophysiology of functional brain connectivity is different between AD and bvFTD. Our findings support the hypothesis that resting state fMRI shows disease-specific functional connectivity differences and is useful to elucidate the pathophysiology of AD and bvFTD. However, the group differences in functional connectivity are less abundant than has been shown in previous studies.

Multimodal neuroimaging computing: a review of the applications in neuropsychiatric disorders

Multimodal neuroimaging is increasingly used in neuroscience research, as it overcomes the limitations of individual modalities. One of the most important applications of multimodal neuroimaging is the provision of vital diagnostic data for neuropsychiatric disorders. Multimodal neuroimaging computing enables the visualization and quantitative analysis of the alterations in brain structure and function, and has reshaped how neuroscience research is carried out. Research in this area is growing exponentially, and so it is an appropriate time to review the current and future development of this emerging area. Hence, in this paper, we review the recent advances in multimodal neuroimaging (MRI, PET) and electrophysiological (EEG, MEG) technologies, and their applications to the neuropsychiatric disorders. We also outline some future directions for multimodal neuroimaging where researchers will design more advanced methods and models for neuropsychiatric research.