The cerebral resting state in schizophrenia is altered, as has been demonstrated separately by electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) resting state networks (RSNs). Previous simultaneous EEG/fMRI findings in healthy controls suggest that a consistent spatiotemporal coupling between neural oscillations (EEG frequency correlates) and RSN activity is necessary to organize cognitive processes optimally. We hypothesized that this coupling is disorganized in schizophrenia and related psychotic disorders, in particular regarding higher cognitive RSNs such as the default-mode (DMN) and left-working-memory network (LWMN).
Resting state was investigated in eleven patients with a schizophrenia spectrum disorder (n = 11) and matched healthy controls (n = 11) using simultaneous EEG/fMRI. The temporal association of each RSN to topographic spectral changes in the EEG was assessed by creating Covariance Maps. Group differences within, and group similarities across frequencies were estimated for the Covariance Maps.
The coupling of EEG frequency bands to the DMN and the LWMN respectively, displayed significant similarities that were shifted towards lower EEG frequencies in patients compared to healthy controls.
By combining EEG and fMRI, each measuring different properties of the same pathophysiology, an aberrant relationship between EEG frequencies and altered RSNs was observed in patients. RSNs of patients were related to lower EEG frequencies, indicating functional alterations of the spatiotemporal coupling.
The finding of a deviant and shifted coupling between RSNs and related EEG frequencies in patients with a schizophrenia spectrum disorder is significant, as it might indicate how failures in the processing of internal and external stimuli, as commonly seen during this symptomatology (i.e. thought disorders, hallucinations), arise.
A major impediment toward the development of novel treatment strategies for fibromyalgia (FM) is the lack of an objective marker which tracks with spontaneous clinical pain report. Resting state intrinsic brain connectivity in FM has demonstrated increased insular connectivity to the default mode network (DMN), a network whose activity is increased during rest. Moreover increased insular connectivity to the DMN was associated with increased spontaneous pain levels. However as these analyses were cross-sectional in nature, they provided no insight to dynamic changes in connectivity and their relationship with variation in clinical pain report.
17 FM patients underwent resting state fMRI at baseline and following 4 weeks of a non-pharmacological intervention to diminish pain. Intrinsic DMN connectivity was evaluated using probabilistic independent component analysis. A paired analysis evaluated longitudinal changes in intrinsic DMN connectivity and a multiple linear regression investigated correlations between longitudinal changes in clinical pain and changes in intrinsic DMN connectivity. Changes in clinical pain were assessed with the Short Form of the McGill Pain Questionnaire (SF-MPQ).
Clinical pain was reduced following therapy (SF-MPQ sensory scale: p<0.02). Intrinsic DMN connectivity to the insula was reduced, and this reduction was correlated with reductions in pain (corrected p<0.05).
Our findings suggest that intrinsic brain connectivity can be used as a candidate objective marker that tracks intra-subject with changes in spontaneous chronic pain in FM. We propose that intrinsic connectivity measures could potentially be used either in research or clinical settings as a complementary, more objective outcome.
resting state fMRI; fcMRI; default mode network; fibromyalgia; acupuncture
Interregional correlations between blood oxygen level dependent (BOLD) magnetic resonance imaging (fMRI) signals in the resting state have been interpreted as measures of connectivity across the brain. Here we investigate whether such connectivity in the working memory and default mode networks is modulated by changes in cognitive load. Functional connectivity was measured in a steady-state verbal identity N-back task for three different conditions (N = 1, 2, and 3) as well as in the resting state. We found that as cognitive load increases, the functional connectivity within both the working memory the default mode network increases. In order to test whether functional connectivity between the working memory and the default mode networks changed, we constructed maps of functional connectivity to the working memory network as a whole and found that increasingly negative correlations emerged in a dorsal region of the posterior cingulate cortex. These results provide further evidence that low frequency fluctuations in BOLD signals reflect variations in neural activity and suggests interaction between the default mode network and other cognitive networks.
fMRI; functional connectivity; working memory; default mode
Resting-state functional magnetic resonance imaging (fMRI) is emerging as an interesting biomarker for measuring connectivity of the brain in patients with Alzheimer's disease (AD). In this review, we discuss the origins of resting-state fMRI, common methodologies used to extract information from these four-dimensional fMRI scans, and important considerations for the analysis of these scans. Then we present the current state of knowledge in this area by summarizing various AD resting-state fMRI studies presented in the first section and end with a discussion of future developments and open questions in the field.
Resting state networks (RSNs) are spontaneous, synchronous, low-frequency oscillations observed in the brains of subjects who are awake but at rest. A particular RSN called the default mode network (DMN) has been shown to exhibit changes associated with neurological disorders such as temporal lobe epilepsy or Alzheimer’s disease. Previous studies have also found that differing experimental conditions such as eyes-open versus eyes-closed can produce measurable changes in the DMN. These condition-associated changes have the potential of confounding the measurements of changes in RSNs related to or caused by disease state(s). In this study, we use fMRI measurements of resting-state connectivity paired with EEG measurements of alpha rhythm and employ independent component analysis, undirected graphs of partial spectral coherence, and spatiotemporal regression to investigate the effect of music-listening on RSNs and the DMN in particular. We observed similar patterns of DMN connectivity in subjects who were listening to music compared with those who were not, with a trend towards a more introspective pattern of resting-state connectivity during music-listening. We conclude that music-listening is a valid condition under which the DMN can be studied.
fMRI; EEG; Default Mode Network; Functional Connectivity; Independent Component Analysis
Clinical diagnosis of disorders of consciousness (DOC) caused by brain injury poses great challenges since patients are often behaviorally unresponsive. A promising new approach towards objective DOC diagnosis may be offered by the analysis of ultra-slow (<0.1 Hz) spontaneous brain activity fluctuations measured with functional magnetic resonance imaging (fMRI) during the resting-state. Previous work has shown reduced functional connectivity within the “default network”, a subset of regions known to be deactivated during engaging tasks, which correlated with the degree of consciousness impairment. However, it remains unclear whether the breakdown of connectivity is restricted to the “default network”, and to what degree changes in functional connectivity can be observed at the single subject level. Here, we analyzed resting-state inter-hemispheric connectivity in three homotopic regions of interest, which could reliably be identified based on distinct anatomical landmarks, and were part of the “Extrinsic” (externally oriented, task positive) network (pre- and postcentral gyrus, and intraparietal sulcus). Resting-state fMRI data were acquired for a group of 11 healthy subjects and 8 DOC patients. At the group level, our results indicate decreased inter-hemispheric functional connectivity in subjects with impaired awareness as compared to subjects with intact awareness. Individual connectivity scores significantly correlated with the degree of consciousness. Furthermore, a single-case statistic indicated a significant deviation from the healthy sample in 5/8 patients. Importantly, of the three patients whose connectivity indices were comparable to the healthy sample, one was diagnosed as locked-in. Taken together, our results further highlight the clinical potential of resting-state connectivity analysis and might guide the way towards a connectivity measure complementing existing DOC diagnosis.
Amnestic mild cognitive impairment (aMCI) is a syndrome associated with faster memory decline than normal aging, and frequently represents the prodromal phase of Alzheimer’s disease. When a person is not actively engaged in a goal-directed task, spontaneous functional magnetic resonance imaging (fMRI) signals can reveal functionally connected brain networks, including the so-called default mode network (DMN). To date, only a few studies have investigated DMN functions in aMCI populations. In this study, group independent component analysis was conducted for resting-state fMRI data, with slices acquired perpendicular to the long axis of the hippocampus, from eight subjects with aMCI and eight normal control subjects. Subjects with aMCI showed increased DMN activity in middle cingulate cortex, medial prefrontal cortex, and left inferior parietal cortex compared to the normal control group. Decreased DMN activity for the aMCI group compared to the normal control group was noted in lateral prefrontal cortex, left medial temporal lobe (MTL), left medial temporal gyrus, posterior cingulate cortex/retrosplenial cortex/precuneus, and right angular gyrus. Although MTL volume difference between the two groups was not statistical significant, decreased activity in left MTL was observed for the aMCI group. Positive correlations between DMN activity and memory scores were noted for left lateral prefrontal cortex, left medial temporal gyrus, and right angular gyrus. These findings support the premise that alterations of the DMN occur in aMCI and may indicate deficiencies in functional, intrinsic brain architecture, that correlate with memory function, even before significant medial temporal lobe atrophy is detectable by structural MRI.
default mode network (DMN); amnestic mild cognitive impairment (aMCI); resting-state fMRI; medial temporal lobe (MTL)
Previous studies have revealed that functional magnetic resonance imaging (fMRI) blood oxygen level-dependent (BOLD) signal in specific brain regions correlates with cross-sectional performance on standardized clinical trial measures in Alzheimer's disease (AD); however, the relationship between longitudinal change in fMRI-BOLD signal and neuropsychological performance remains unknown. Objective: To identify changes in regional fMRI-BOLD activity that tracks change in neuropsychological performance in mild AD dementia over 6 months.
Twenty-four subjects (mean age 71.6) with mild AD dementia (mean Mini Mental State Examination 21.7, Global Clinical Dementia Rating 1.0) on stable donepezil dosing participated in two task-related fMRI sessions consisting of a face-name paired associative encoding memory paradigm 24 weeks apart during a randomized placebo-controlled pharmaco-fMRI drug study. Regression analysis was used to identify regions where the change in fMRI activity for Novel > Repeated stimulus contrast was associated with the change scores on postscan memory tests and the Free and Cued Selective Reminding Test (FCSRT).
Correlations between changes in postscan memory accuracy and changes in fMRI activity were observed in regions including the angular gyrus, parahippocampal gyrus, inferior frontal gyrus and cerebellum. Correlations between changes in FCSRT-free recall and changes in fMRI were observed in regions including the inferior parietal lobule, precuneus, hippocampus and parahippocampal gyrus.
Changes in encoding-related fMRI activity in regions implicated in mnemonic networks correlated with changes in psychometric measures of episodic memory retrieval performed outside the scanner. These exploratory results support the potential of fMRI activity to track cognitive change and detect signals of short-term pharmacologic effect in early-phase AD studies.
Functional MRI; Clinical trial; Episodic memory; Biomarker; Dementia
Previous studies have defined low-frequency, spatially consistent intrinsic connectivity networks (ICN) in resting functional magnetic resonance imaging (fMRI) data which reflect functional interactions among distinct brain areas. We sought to explore whether and how repeated migraine attacks influence intrinsic brain connectivity, as well as how activity in these networks correlates with clinical indicators of migraine.
Resting-state fMRI data in twenty-three patients with migraines without aura (MwoA) and 23 age- and gender-matched healthy controls (HC) were analyzed using independent component analysis (ICA), in combination with a “dual-regression” technique to identify the group differences of three important pain-related networks [default mode network (DMN), bilateral central executive network (CEN), salience network (SN)] between the MwoA patients and HC. Compared with the HC, MwoA patients showed aberrant intrinsic connectivity within the bilateral CEN and SN, and greater connectivity between both the DMN and right CEN (rCEN) and the insula cortex - a critical region involving in pain processing. Furthermore, greater connectivity between both the DMN and rCEN and the insula correlated with duration of migraine.
Our findings may provide new insights into the characterization of migraine as a condition affecting brain activity in intrinsic connectivity networks. Moreover, the abnormalities may be the consequence of a persistent central neural system dysfunction, reflecting cumulative brain insults due to frequent ongoing migraine attacks.
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.
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.
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.
Recent functional MRI (fMRI) studies have demonstrated that there is an intrinsically organized default mode network (DMN) in the resting brain, primarily made up of the posterior cingulate cortex (PCC) and the medial prefrontal cortex (MPFC). Several previous studies have found that the DMN is minimally disturbed during different resting-state conditions with limited cognitive demand. However, this conclusion was drawn from the visual inspection of the functional connectivity patterns within the DMN and no statistical comparison was performed.
Four resting-state fMRI sessions were acquired: 1) eyes-closed (EC) (used to generate the DMN mask); 2) EC; 3) eyes-open with no fixation (EO); and 4) eyes-open with a fixation (EO-F). The 2–4 sessions were counterbalanced across participants (n = 20, 10 males). We examined the statistical differences in both functional connectivity and regional amplitude of low frequency fluctuation (ALFF) within the DMN among the 2–4 resting-state conditions (i.e., EC, EO, and EO-F). Although the connectivity patterns of the DMN were visually similar across these three different conditions, we observed significantly higher functional connectivity and ALFF in both the EO and the EO-F conditions as compared to the EC condition. In addition, the first and second resting EC conditions showed significant differences within the DMN, suggesting an order effect on the DMN activity.
Our findings of the higher DMN connectivity and regional spontaneous activities in the resting state with the eyes open suggest that the participants might have more non-specific or non-goal-directed visual information gathering and evaluation, and mind wandering or daydreaming during the resting state with the eyes open as compared to that with the eyes closed, thus providing insights into the understanding of unconstrained mental activity within the DMN. Our results also suggest that it should be cautious when choosing the type of a resting condition and designating the order of the resting condition in multiple scanning sessions in experimental design.
Previous researches have explored the changes of functional connectivity caused by smoking with the aid of fMRI. This study considers not only functional connectivity but also effective connectivity regarding both brain networks and brain regions by using a novel analysis framework that combines independent component analysis (ICA) and Granger causality analysis (GCA). We conducted a resting-state fMRI experiment in which twenty-one heavy smokers were scanned in two sessions of different conditions: smoking abstinence followed by smoking satiety. In our framework, group ICA was firstly adopted to obtain the spatial patterns of the default-mode network (DMN), executive-control network (ECN), and salience network (SN). Their associated time courses were analyzed using GCA, showing that the effective connectivity from SN to DMN was reduced and that from ECN/DMN to SN was enhanced after smoking replenishment. A paired t-test on ICA spatial patterns revealed functional connectivity variation in regions such as the insula, parahippocampus, precuneus, anterior cingulate cortex, supplementary motor area, and ventromedial/dorsolateral prefrontal cortex. These regions were later selected as the regions of interest (ROIs), and their effective connectivity was investigated subsequently using GCA. In smoking abstinence, the insula showed the increased effective connectivity with the other ROIs; while in smoking satiety, the parahippocampus had the enhanced inter-area effective connectivity. These results demonstrate our hypothesis that for deprived heavy smokers, smoking replenishment takes effect on both functional and effective connectivity. Moreover, our analysis framework could be applied in a range of neuroscience studies.
Anticorrelated relationships in spontaneous signal fluctuation have been previously observed in resting-state functional magnetic resonance imaging (fMRI). In particular, it was proposed that there exists two systems in the brain that are intrinsically organized into anticorrelated networks, the default mode network, which usually exhibits task-related deactivations, and the task-positive network, which usually exhibits task-related activations during tasks that demands external attention. However, it is currently under debate whether the anticorrelations observed in resting state fMRI were valid or were instead artificially introduced by global signal regression, a common preprocessing technique to remove physiological and other noise in resting-state fMRI signal. We examined positive and negative correlations in resting-state connectivity using two different preprocessing methods: a component base noise reduction method (CompCor, Behzadi et al., 2007), in which principal components from noise regions-of-interest were removed, and the global signal regression method. Robust anticorrelations between a default mode network seed region in the medial prefrontal cortex and regions of the task-positive network were observed under both methods. Specificity of the anticorrelations was similar between the two methods. Specificity and sensitivity for positive correlations were higher under CompCor compared to the global regression method. Our results suggest that anticorrelations observed in resting-state connectivity are not an artifact introduced by global signal regression and might have biological origins, and that the CompCor method can be used to examine valid anticorrelations during rest.
fMRI; functional connectivity; physiological noise; default mode network; task-positive network; negative correlations
Despite considerable advances toward understanding the molecular pathophysiology of the neurodegenerative dementias, the mechanisms linking molecular changes to neuropathology and the latter to clinical symptoms remain largely obscure. Connectivity is a distinctive feature of the brain and the integrity of functional network dynamics is critical for normal functioning. A better understanding of network disruption in the neurodegenerative dementias may help bridge the gap between molecular changes, pathology and symptoms. Recent findings on functional network disruption as assessed with “resting-state” or intrinsic connectivity fMRI and EEG/MEG have shown distinct patterns of network disruption across the major neurodegenerative diseases. These network abnormalities are relatively specific to the clinical syndromes, and in Alzheimer's disease and frontotemporal dementia network disruption tracks the pattern of pathological changes. These findings may have a practical impact on diagnostic accuracy, allowing earlier detection of neurodegenerative diseases even at the pre-symptomatic stage, and tracking of disease progression.
Background and Purpose
Functional magnetic resonance imaging (fMRI) studies could provide crucial information on the neural mechanisms of motor recovery in stroke patients. Resting-state fMRI is applicable to stroke patients who are not capable of proper performance of the motor task. In this study, we explored neural correlates of motor recovery in stroke patients by investigating longitudinal changes in resting-state functional connectivity of the ipsilesional primary motor cortex (M1).
A longitudinal observational study using repeated fMRI experiments was conducted in 12 patients with stroke. Resting-state fMRI data were acquired four times over a period of 6 months. Patients participated in the first session of fMRI shortly after onset, and thereafter in subsequent sessions at 1, 3, and 6 months after onset. Resting-state functional connectivity of the ipsilesional M1 was assessed and compared with that of healthy subjects.
Compared with healthy subjects, patients demonstrated higher functional connectivity with the ipsilesional frontal and parietal cortices, bilateral thalamus, and cerebellum. Instead, functional connectivity with the contralesional M1 and occipital cortex were decreased in stroke patients. Functional connectivity between the ipsilesional and contralesional M1 showed the most asymmetry at 1 month after onset to the ipsilesional side. Functional connectivity of the ipsilesional M1 with the contralesional thalamus, supplementary motor area, and middle frontal gyrus at onset was positively correlated with motor recovery at 6 months after stroke.
Resting-state fMRI elicited distinctive but comparable results with previous task-based fMRI, presenting complementary and practical values for use in the study of stroke patients.
Resting-state fMRI; Stroke; Motor recovery; Functional connectivity
There has been a dramatic increase in the number of studies using resting state fMRI, a recent addition to imaging analysis techniques. The technique analyzes ongoing low frequency fluctuations in the blood oxygen level dependent (BOLD) signal. Through patterns of spatial coherence, these fluctuations can be used to identify the networks within the brain. Multiple brain networks are present simultaneously and the relationships within and between networks are in constant dynamic flux. Resting state fMRI functional connectivity (rs-fMRI) analysis is increasingly used to detect subtle brain network differences, and in the case of pathophysiology, subtle abnormalities in illnesses such as Alzheimer’s disease (AD). The sequence of events leading up to dementia has been hypothesized to begin many years or decades before any clinical symptoms occur. Here we review the findings across rs-fMRI studies in the spectrum of preclinical AD to clinical AD. In addition, we discuss evidence for underlying preclinical AD mechanisms, including an important relationship between resting state functional connectivity and brain metabolism, and how this results in a distinctive pattern of amyloid plaque deposition in default mode network regions.
fMRI; BOLD; amyloid; precuneus; default mode network (DMN); glycolysis
We hypothesize that the evolution of mild traumatic brain injury (mTBI) may be related to differential effects of a concussive blow on the functional integrity of the brain default mode network (DMN) at rest and/or in response to physical stress. Accordingly, in this resting-state functional magnetic resonance imaging (fMRI) study, we examined 14 subjects 10±2 days post-sports-related mTBI and 15 age-matched normal volunteers (NVs) to investigate the possibility that the integrity of the DMN is disrupted at the resting state and/or following the physical stress test. First, all mTBI subjects were asymptomatic based upon clinical evaluation and neuropsychological (NP) assessments prior to the MRI session. Second, the functional integrity within the DMN, a main resting-state network, remained resilient to a single concussive blow. Specifically, the major regions of interest (ROIs) constituting the DMN (e.g., the posterior cingulate cortex [PCC]/precuneus area, the medial prefrontal cortex [MPFC], and left and right lateral parietal cortices [LLP and RLP]) and the connectivity within these four ROIs was similar between NVs and mTBI subjects prior to the YMCA physical stress test. However, the YMCA physical stress test disrupted the DMN, significantly reducing the magnitude of the connection between the PCC and left lateral parietal ROI, and PCC and right lateral parietal ROI, as well as between the PCC and MPFC in mTBI subjects. Thus while the DMN remained resilient to a single mTBI without exertion at 10 days post-injury, it was altered in response to limited physical stress. This may explain some clinical features of mTBI and provide some insight into its mechanism. This important finding should be considered by clinical practitioners when making decisions regarding return-to-play and clearing mTBI athletes for sports participation.
default mode network; resting state functional magnetic resonance imaging; subacute phase of mild traumatic brain injury
Important functional connections within the “default mode network” (DMN) are disrupted in Alzheimer’s disease (AD), likely from amyloid-beta (Aβ) plaque-associated neuronal toxicity. Here we sought to determine if pathological effects of Aβ amyloid plaques could be seen even in the absence of a task by examining functional connectivity in cognitively normal participants with and without preclinical amyloid deposition.
Participants with Alzheimer’s disease (AD) (n= 35) were compared with 68 cognitively normal participants who were further subdivided by PET PIB imaging into those without evidence of brain amyloid (PIB−) and those with brain amyloid (PIB+) deposition.
Resting state fMRI demonstrated that, compared with the PIB− group, the PIB+ group differed significantly in functional connectivity of the precuneus to hippocampus, parahippocampus, anterior cingulate, dorsal cingulate, gyrus rectus, superior precuneus and visual cortex. These differences were in the same regions, and in the same direction, as differences found in the AD group.
Thus, prior to any manifestations of cognitive or behavioral changes there were differences in resting state connectivity in cognitively normal subjects with brain amyloid deposition, suggesting that early manifestation of Aβ toxicity can be detected using resting state fMRI.
PIB; fMRI; amyloid; Alzheimers Disease; resting state; precuneus; hippocampus
BACKGROUND AND PURPOSE
Connectivity mapping based on resting-state fMRI is rapidly developing and this methodology has great potential for clinical applications. However, before resting-state fMRI can be applied for diagnosis, prognosis, and monitoring treatment for an individual patient with neurologic or psychiatric diseases, it is essential to assess its long-term reproducibility and between-subject variations among healthy individuals. The purpose of the study is to (1) quantify the long-term test-retest reproducibility of intrinsic connectivity network (ICN) measures derived from resting-state fMRI, and (2) assess the between-subject variation of ICN measures across the whole brain.
MATERIALS AND METHODS
Longitudinal resting-state fMRI data of six healthy volunteers were acquired from nine scan sessions over a period of more than one year. The within-subject reproducibility and between-subject variation of ICN measures, across 1) the whole brain and 2) major nodes of the default mode network, were quantified with intraclass correlation coefficient (ICC) and coefficient of variance (COV).
Our data show that the long-term test-retest reproducibility of ICN measures is outstanding, with over 70% of the connectivity networks showing an ICC greater than 0.60. COV across six healthy volunteers in this sample was greater than 0.2, suggesting significant between-subject variation.
Our data indicate that resting-state ICN measures (e.g., the correlation coefficients between fMRI signal profiles from two different brain regions) are potentially suitable as biomarkers for monitoring disease progression and treatment effects in clinical trials and individual patients. Because between-subject variation is significant, it may be difficult to use quantitative ICN measures, in their current state, as a diagnostic tool.
Participants with mild cognitive impairment (MCI) have a higher likelihood of developing Alzheimer's disease (AD) compared to those without MCI, and functional magnetic resonance neuroimaging (fMRI) used with MCI participants may prove to be an important tool in identifying early biomarkers for AD. We tested the hypothesis that functional connectivity differences exist between older adults with and without MCI using resting-state fMRI. Data were collected on over 200 participants of the Rush Memory and Aging Project, a community-based, clinical-pathological cohort study of aging. From the cohort, 40 participants were identified as having MCI, and were compared to 40 demographically matched participants without cognitive impairment. MCI participants showed lesser functional connectivity between the posterior cingulate cortex and right and left orbital frontal, right middle frontal, left putamen, right caudate, left superior temporal, and right posterior cingulate regions; and greater connectivity with right inferior frontal, left fusiform, left rectal, and left precentral regions. Furthermore, in an alternate sample of 113, connectivity values in regions of difference correlated with episodic memory and processing speed. Results suggest functional connectivity values in regions of difference are associated with cognitive function and may reflect the presence of AD pathology and increased risk of developing clinical AD.
Mild cognitive impairment (MCI); Resting-state fMRI; Functional connectivity; Posterior cingulate cortex; Memory; Basal ganglia; Striatum
Deficits of the default mode network (DMN) have been demonstrated in subjects with amnestic type mild cognitive impairment (aMCI) who have a high risk of developing Alzheimer’s disease (AD). However, no longitudinal study of this network has been reported in aMCI. Identifying links between development of DMN and aMCI progression would be of considerable value in understanding brain changes underpinning aMCI and determining risk of conversion to AD.
Resting-state fMRI was acquired in aMCI subjects (n = 26) and controls (n = 18) at baseline and after approximately 20 months follow up. Independent component analysis was used to isolate the DMN in each participant. Differences in DMN between aMCI and controls were examined at baseline, and subsequent changes between baseline and follow-up were also assessed in the groups. Posterior cingulate cortex/precuneus (PCC/PCu) hyper-functional connectivity was observed at baseline in aMCI subjects, while a substantial decrement of these connections was evident at follow-up in aMCI subjects, compared to matched controls. Specifically, PCC/PCu dysfunction was positively related to the impairments of episodic memory from baseline to follow up in aMCI group.
The patterns of longitudinal deficits of DMN may assist investigators to identify and monitor the development of aMCI.
Positron emission tomography (PET) studies of major depression have revealed resting-state abnormalities in the prefrontal and cingulate cortices. Recently, fMRI has been adapted to examine connectivity within a specific resting-state neural network—the default-mode network—that includes the medial prefrontal and anterior cingulate cortices. The goal of this study was to examine resting-state, default-mode network functional connectivity in subjects with major depression and in healthy comparison subjects.
28 subjects with major depression and 20 healthy control subjects underwent 5-minute fMRI scans while resting quietly. Independent component analysis was used to isolate the default-mode network in each subject. Group maps of the default-mode network were generated and compared between the two groups. A within-group analysis was performed in the depressed group to explore effects of depression refractoriness on network functional connectivity.
Resting-state subgenual cingulate and thalamic functional connectivity with the default-mode network was significantly greater in the depressed subjects compared to the control group. Within the depressed group, the length of the current depressive episode (a surrogate for refractoriness) was positively correlated with functional connectivity in the subgenual cingulate.
This is the first study to explore default-mode functional connectivity in subjects with major depression. The findings provide cross-modality confirmation of PET studies demonstrating abnormally increased thalamic and subgenual cingulate activity in major depression. Further, the within-subject connectivity analysis employed here brings these previously isolated regions of hypermetabolism into the context of a disordered neural network. The correlation between refractoriness and subgenual cingulate functional connectivity within the network suggests that a quantitative, resting-state fMRI measure could be used to guide therapy on an individual subject basis.
functional connectivity; depression; subgenual cingulate; resting-state; independent component analysis
Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step.
Alzheimer’s disease (AD) is the most common cause of dementia. Much is known concerning AD pathophysiology but our understanding of the disease at the systems level remains incomplete. Previous AD research has used resting state functional connectivity magnetic resonance imaging (rs-fcMRI) to assess the integrity of functional networks within the brain. Most studies have focused on the default-mode network (DMN), a primary locus of AD pathology. However, other brain regions are inevitably affected with disease progression. We studied rs-fcMRI in five functionally defined brain networks within a large cohort of human participants of either gender (n=510) that ranged in AD severity from unaffected (clinical dementia rating, CDR 0) to very mild (CDR 0.5) to mild AD (CDR 1). We observed loss of correlations within not only the DMN but other networks at CDR 0.5. Within the salience network (SAL), increases were seen between CDR 0 and CDR 0.5. However, at CDR 1, all networks, including SAL, exhibited reduced correlations. Specific networks were preferentially affected at certain CDR stages. In addition, cross-network relations were consistently lost with increasing AD severity. Our results demonstrate that AD is associated with widespread loss of both intra- and inter-network correlations. These results provide insight into AD pathophysiology and reinforce an integrative view of the brain’s functional organization.
Alzheimer’s disease; fMRI; resting state functional connectivity; BOLD; default mode network; salience network
Task evoked functional MRI (fMRI) has been used successfully in the study of brain function and clinically for pre-surgical localization of eloquent brain regions prior to the performance of brain surgery. This method requires patient cooperation and is not useful in patients with cognitive dysfunction or physical impairment.
An alternative method that can overcome some of these disadvantages measures the intrinsic function of the brain using resting state fMRI. This method does not require any task performance and measures the spontaneous low frequency (<0.1 Hz) fluctuations of the fMRI signal over time. Resting state fMRI data can provide valuable pre-surgical information in many patients who cannot benefit from traditional task based fMRI. Our objective in the current review is to provide preliminary information, including advantages and remaining challenges, on the clinical utility of this technique for improving pre-surgical planning and individualized patient centered care.
Functional MRI; Brain Mapping; CNS Tumors; Neurosurgery; Neuroradiology