Transcranial magnetic stimulation (TMS) to the left dorsal-lateral prefrontal cortex (DLPFC) is used clinically for the treatment of depression. However the antidepressant mechanism remains unknown and its therapeutic efficacy remains limited. Recent data suggests that some left DLPFC targets are more effective than others, however the reasons for this heterogeneity and how to capitalize on this information remain unclear.
Intrinsic (resting state) fMRI data from 98 normal subjects were used to compute functional connectivity with various left DLPFC TMS targets employed in the literature. Differences in functional connectivity related to differences in previously reported clinical efficacy were identified. This information was translated into a connectivity-based targeting strategy to identify optimized left DLPFC TMS coordinates. Results in normal subjects were tested for reproducibility in an independent cohort of 13 patients with depression.
Differences in functional connectivity were related to previously reported differences in clinical efficacy across a distributed set of cortical and limbic regions. DLPFC TMS sites with better clinical efficacy were more negatively correlated (anticorrelated) with the subgenual cingulate. Optimum connectivity-based stimulation coordinates were identified in BA46. Results were reproducible in patients with depression.
Reported antidepressant efficacy of different left DLPFC TMS sites is related to the anticorrelation of each site with the subgenual cingulate, potentially lending insight into the antidepressant mechanism of TMS and suggesting a role for intrinsically anticorrelated networks in depression. These results can be translated into a connectivity-based targeting strategy for focal brain stimulation that might be used to optimize clinical response.
Transcranial magnetic stimulation; TMS; intrinsic connectivity; resting state functional connectivity; MRI; subgenual; dorsolateral prefrontal cortex; depression
Anterior cingulate cortex (ACC) is known to be involved in functions such as emotion, pain, and cognitive control. While studies in humans and non-human mammals have advanced our understanding of ACC function, the subjective correlates of ACC activity have remained largely unexplored. In the current study, we show that electrical charge delivery in the anterior mid-cingulate cortex (aMCC) elicits autonomic changes and the expectation of an imminent challenge coupled with a determined attitude to overcome it. Seed-based, resting-state connectivity analysis revealed that the site of stimulation in both patients was at the core of a large-scale distributed network linking aMCC to the frontoinsular and frontopolar as well as some subcortical regions. This report provides compelling, first-person accounts of electrical stimulation of this brain network and suggests its possible involvement in psychopathological conditions that are characterized by a reduced capacity to endure psychological or physical distress.
Fragile X syndrome (FXS) is an X-linked neurogenetic disorder characterized by a cognitive and behavioral phenotype resembling features of autism spectrum disorder. Until now, research has focused largely on identifying regional differences in brain structure and function between individuals with FXS and various control groups. Very little is known about the large-scale brain networks that may underlie the cognitive and behavioral symptoms of FXS.
To identify large-scale, resting-state networks in FXS that differ from control individuals matched on age, IQ, and severity of behavioral and cognitive symptoms.
DESIGN, SETTING, AND PARTICIPANTS
Cross-sectional, in vivo neuroimaging study conducted in an academic medical center. Participants (aged 10–23 years) included 17 males and females with FXS and 16 males and females serving as controls.
MAIN OUTCOMES AND MEASURES
Univariate voxel-based morphometric analyses, fractional amplitude of low-frequency fluctuations (fALFF) analysis, and group-independent component analysis with dual regression.
Patients with FXS showed decreased functional connectivity in the salience, precuneus, left executive control, language, and visuospatial networks compared with controls. Decreased fALFF in the bilateral insular, precuneus, and anterior cingulate cortices also was found in patients with FXS compared with control participants. Furthermore, fALFF in the left insular cortex was significantly positively correlated with IQ in patients with FXS. Decreased gray matter density, resting-state connectivity, and fALFF converged in the left insular cortex in patients with FXS.
CONCLUSIONS AND RELEVANCE
Fragile X syndrome results in widespread reductions in functional connectivity across multiple cognitive and affective brain networks. Converging structural and functional abnormalities in the left insular cortex, a region also implicated in individuals diagnosed with autism spectrum disorder, suggests that insula integrity and connectivity may be compromised in FXS. This method could prove useful in establishing an imaging biomarker for FXS.
The factors driving clinical heterogeneity in Alzheimer’s disease are not well understood. This study assessed the relationship between amyloid deposition, glucose metabolism and clinical phenotype in Alzheimer’s disease, and investigated how these relate to the involvement of functional networks. The study included 17 patients with early-onset Alzheimer’s disease (age at onset <65 years), 12 patients with logopenic variant primary progressive aphasia and 13 patients with posterior cortical atrophy [whole Alzheimer’s disease group: age = 61.5 years (standard deviation 6.5 years), 55% male]. Thirty healthy control subjects [age = 70.8 (3.3) years, 47% male] were also included. Subjects underwent positron emission tomography with 11C-labelled Pittsburgh compound B and 18F-labelled fluorodeoxyglucose. All patients met National Institute on Ageing–Alzheimer’s Association criteria for probable Alzheimer’s disease and showed evidence of amyloid deposition on 11C-labelled Pittsburgh compound B positron emission tomography. We hypothesized that hypometabolism patterns would differ across variants, reflecting involvement of specific functional networks, whereas amyloid patterns would be diffuse and similar across variants. We tested these hypotheses using three complimentary approaches: (i) mass-univariate voxel-wise group comparison of 18F-labelled fluorodeoxyglucose and 11C-labelled Pittsburgh compound B; (ii) generation of covariance maps across all subjects with Alzheimer’s disease from seed regions of interest specifically atrophied in each variant, and comparison of these maps to functional network templates; and (iii) extraction of 11C-labelled Pittsburgh compound B and 18F-labelled fluorodeoxyglucose values from functional network templates. Alzheimer’s disease clinical groups showed syndrome-specific 18F-labelled fluorodeoxyglucose patterns, with greater parieto-occipital involvement in posterior cortical atrophy, and asymmetric involvement of left temporoparietal regions in logopenic variant primary progressive aphasia. In contrast, all Alzheimer’s disease variants showed diffuse patterns of 11C-labelled Pittsburgh compound B binding, with posterior cortical atrophy additionally showing elevated uptake in occipital cortex compared with early-onset Alzheimer’s disease. The seed region of interest covariance analysis revealed distinct 18F-labelled fluorodeoxyglucose correlation patterns that greatly overlapped with the right executive-control network for the early-onset Alzheimer’s disease region of interest, the left language network for the logopenic variant primary progressive aphasia region of interest, and the higher visual network for the posterior cortical atrophy region of interest. In contrast, 11C-labelled Pittsburgh compound B covariance maps for each region of interest were diffuse. Finally, 18F-labelled fluorodeoxyglucose was similarly reduced in all Alzheimer’s disease variants in the dorsal and left ventral default mode network, whereas significant differences were found in the right ventral default mode, right executive-control (both lower in early-onset Alzheimer’s disease and posterior cortical atrophy than logopenic variant primary progressive aphasia) and higher-order visual network (lower in posterior cortical atrophy than in early-onset Alzheimer’s disease and logopenic variant primary progressive aphasia), with a trend towards lower 18F-labelled fluorodeoxyglucose also found in the left language network in logopenic variant primary progressive aphasia. There were no differences in 11C-labelled Pittsburgh compound B binding between syndromes in any of the networks. Our data suggest that Alzheimer’s disease syndromes are associated with degeneration of specific functional networks, and that fibrillar amyloid-β deposition explains at most a small amount of the clinico-anatomic heterogeneity in Alzheimer’s disease.
Alzheimer’s disease; posterior cortical atrophy; logopenic variant of PPA; positron emission tomography (PET); functional networks
We examined whether the effect of APOE genotype on functional brain connectivity is modulated by gender in healthy older human adults. Our results confirm significantly decreased connectivity in the default mode network in healthy older APOE ε4 carriers compared to ε3 homozygotes. More importantly, further testing revealed a significant interaction between APOE genotype and gender in the precuneus, a major default mode hub. Female ε4 carriers showed significantly reduced default mode connectivity compared to either female ε3 homozygotes or male ε4 carriers, whereas male ε4 carriers differed minimally from male ε3 homozygotes. An additional analysis in an independent sample of healthy elderly using an independent marker of Alzheimer’s disease, i.e. spinal fluid levels of tau, provided corresponding evidence for this gender by APOE interaction. Taken together, these results converge with previous work showing a higher prevalence of the ε4 allele among women with Alzheimer’s disease and, critically, demonstrate that this interaction between APOE genotype and gender is detectable in the preclinical period.
While resting state functional connectivity has been shown to decrease in patients with mild/moderate Alzheimer’s disease, it is not yet known how functional connectivity changes in patients as the disease progresses. Furthermore, it has been noted that the default mode network is not as homogenous as previously assumed and several fractionations of the network have been proposed. Here, we separately investigated the modulation of three default mode sub-networks, as identified with group ICA, by comparing Alzheimer’s disease patients to healthy controls and by assessing connectivity changes over time. Our results showed decreased connectivity at baseline in patients versus controls in the posterior default mode network, and increased connectivity in the anterior and ventral default mode networks. At follow-up, functional connectivity decreased across all default mode systems in patients. Our results suggest that earlier in the disease, regions of the posterior default mode network start to disengage whereas regions within the anterior and ventral networks enhance their connectivity. However, as the disease progresses connectivity within all systems eventually deteriorates.
Alzheimer’s disease; functional connectivity; resting state fMRI; disease progression; default mode network; fractionation
Resting-state functional connectivity magnetic resonance imaging (fcMRI) studies constitute a growing proportion of functional brain imaging publications. This approach detects temporal correlations in spontaneous blood oxygen level–dependent (BOLD) signal oscillations while subjects rest quietly in the scanner. Although distinct resting-state networks related to vision, language, executive processing, and other sensory and cognitive domains have been identified, considerable skepticism remains as to whether resting-state functional connectivity maps reflect neural connectivity or simply track BOLD signal correlations driven by nonneural artifact. Here we combine diffusion tensor imaging (DTI) tractography with resting-state fcMRI to test the hypothesis that resting-state functional connectivity reflects structural connectivity. These 2 modalities were used to investigate connectivity within the default mode network, a set of brain regions—including medial prefrontal cortex (MPFC), medial temporal lobes (MTLs), and posterior cingulate cortex (PCC)/retropslenial cortex (RSC)—implicated in episodic memory processing. Using seed regions from the functional connectivity maps, the DTI analysis revealed robust structural connections between the MTLs and the retrosplenial cortex whereas tracts from the MPFC contacted the PCC (just rostral to the RSC). The results demonstrate that resting-state functional connectivity reflects structural connectivity and that combining modalities can enrich our understanding of these canonical brain networks.
Alzheimer's disease; hippocampus; memory; posterior cingulate; retrosplenial; white matter
Although beta-amyloid (Aβ) deposition is a characteristic feature of Alzheimer's disease (AD), this pathology is commonly found in elderly normal controls (NC). The pattern of Aβ deposition as detected with Pittsburgh compound-B positron emission tomography (PIB-PET) imaging shows substantial spatial overlap with the default mode network (DMN), a group of brain regions that typically deactivates during externally driven cognitive tasks. In this study, we show that DMN functional connectivity (FC) during rest is altered with increasing levels of PIB uptake in NC. Specifically, FC decreases were identified in regions implicated in episodic memory (EM) processing (posteromedial cortex, ventral medial prefrontal cortex, and angular gyrus), whereas connectivity increases were detected in dorsal and anterior medial prefrontal and lateral temporal cortices. This pattern of decreases is consistent with previous studies that suggest heightened vulnerability of EM-related brain regions in AD, whereas the observed increases in FC may reflect a compensatory response.
aging; beta-amyloid; PIB-PET; resting state fMRI
Variations in neural circuitry, inherited or acquired, may underlie important individual differences in thought, feeling, and action patterns. Here, we used task-free connectivity analyses to isolate and characterize two distinct networks typically coactivated during functional MRI tasks. We identified a “salience network,” anchored by dorsal anterior cingulate (dACC) and orbital frontoinsular cortices with robust connectivity to subcortical and limbic structures, and an “executive-control network” that links dorsolateral frontal and parietal neocortices. These intrinsic connectivity networks showed dissociable correlations with functions measured outside the scanner. Prescan anxiety ratings correlated with intrinsic functional connectivity of the dACC node of the salience network, but with no region in the executive-control network, whereas executive task performance correlated with lateral parietal nodes of the executive-control network, but with no region in the salience network. Our findings suggest that task-free analysis of intrinsic connectivity networks may help elucidate the neural architectures that support fundamental aspects of human behavior.
fMRI; functional connectivity; anterior cingulate; insula; salience; anxiety
Resting-state functional connectivity magnetic resonance imaging (fcMRI) studies constitute a growing proportion of functional brain imaging publications. This approach detects temporal correlations in spontaneous blood oxygen level-dependent (BOLD) signal oscillations while subjects rest quietly in the scanner. Although distinct resting-state networks related to vision, language, executive processing, and other sensory and cognitive domains have been identified, considerable skepticism remains as to whether resting-state functional connectivity maps reflect neural connectivity or simply track BOLD signal correlations driven by nonneural artifact. Here we combine diffusion tensor imaging (DTI) tractography with resting-state fcMRI to test the hypothesis that resting-state functional connectivity reflects structural connectivity. These 2 modalities were used to investigate connectivity within the default mode network, a set of brain regions—including medial prefrontal cortex (MPFC), medial temporal lobes (MTLs), and posterior cingulate cortex (PCC)/retropslenial cortex (RSC)—implicated in episodic memory processing. Using seed regions from the functional connectivity maps, the DTI analysis revealed robust structural connections between the MTLs and the retrosplenial cortex whereas tracts from the MPFC contacted the PCC (just rostral to the RSC). The results demonstrate that resting-state functional connectivity reflects structural connectivity and that combining modalities can enrich our understanding of these canonical brain networks.
Alzheimer's disease; hippocampus; memory; posterior cingulate; retrosplenial; white matter
The default-mode network (DMN) is a set of specific brain regions whose activity, predominant in the resting-state, is attenuated during cognitively demanding, externally-cued tasks. The cognitive correlates of this network have proven difficult to interrogate, but one hypothesis is that regions in the network process episodic memories and semantic knowledge integral to internally-generated mental activity. Here, we compare default-mode functional connectivity in the same group of subjects during rest and conscious sedation with midazolam, a state characterized by anterograde amnesia and a reduced level of consciousness. Although the DMN showed functional connectivity during both rest and conscious sedation, a direct comparison found that there was significantly reduced functional connectivity in the posterior cingulate cortex during conscious sedation. These results confirm that low-frequency oscillations in the DMN persist and remain highly correlated even at reduced levels of consciousness. We hypothesize that focal reductions in DMN connectivity, as shown here in the posterior cingulate cortex, may represent a stable correlate of reduced consciousness.
consciousness; conscious sedation; default mode; episodic memory; posterior cingulate; resting-state
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
The inferior parietal lobule (IPL) of the human brain is a heterogeneous region involved in visuospatial attention, memory, and mathematical cognition. Detailed description of connectivity profiles of subdivisions within the IPL is critical for accurate interpretation of functional neuroimaging studies involving this region. We separately examined functional and structural connectivity of the angular gyrus (AG) and the intraparietal sulcus (IPS) using probabilistic cytoarchitectonic maps. Regions-of-interest (ROIs) included anterior and posterior AG subregions (PGa, PGp) and 3 IPS subregions (hIP2, hIP1, and hIP3). Resting-state functional connectivity analyses showed that PGa was more strongly linked to basal ganglia, ventral premotor areas, and ventrolateral prefrontal cortex, while PGp was more strongly connected with ventromedial prefrontal cortex, posterior cingulate, and hippocampus—regions comprising the default mode network. The anterior-most IPS ROIs, hIP2 and hIP1, were linked with ventral premotor and middle frontal gyrus, while the posterior-most IPS ROI, hIP3, showed connectivity with extrastriate visual areas. In addition, hIP1 was connected with the insula. Tractography using diffusion tensor imaging revealed structural connectivity between most of these functionally connected regions. Our findings provide evidence for functional heterogeneity of cytoarchitectonically defined subdivisions within IPL and offer a novel framework for synthesis and interpretation of the task-related activations and deactivations involving the IPL during cognition.
attention; Brodmann area 39; default mode network; inferior parietal lobule; mathematical cognition
Functional and structural maturation of networks comprised of discrete regions is an important aspect of brain development. The default-mode network (DMN) is a prominent network which includes the posterior cingulate cortex (PCC), medial prefrontal cortex (mPFC), medial temporal lobes (MTL), and angular gyrus (AG). Despite increasing interest in DMN function, little is known about its maturation from childhood to adulthood. Here we examine developmental changes in DMN connectivity using a multimodal imaging approach by combining resting-state fMRI, voxel-based morphometry and diffusion tensor imaging-based tractography. We found that the DMN undergoes significant developmental changes in functional and structural connectivity, but these changes are not uniform across all DMN nodes. Convergent structural and functional connectivity analyses suggest that PCC-mPFC connectivity along the cingulum bundle is the most immature link in the DMN of children. Both PCC and mPFC also showed gray matter volume differences, as well as prominent macrostructural and microstructural differences in the dorsal cingulum bundle linking these regions. Notably, structural connectivity between PCC and left MTL was either weak or non-existent in children, even though functional connectivity did not differ from that of adults. These results imply that functional connectivity in children can reach adult-like levels despite weak structural connectivity. We propose that maturation of PCC-mPFC structural connectivity plays an important role in the development of self-related and social-cognitive functions that emerge during adolescence. More generally, our study demonstrates how quantitative multimodal analysis of anatomy and connectivity allows us to better characterize the heterogeneous development and maturation of brain networks.
brain development; default mode network; DTI; functional brain connectivity; structural brain connectivity
Resting-state or intrinsic connectivity network functional magnetic resonance imaging provides a new tool for mapping large-scale neural network function and dysfunction. Recently, we showed that behavioural variant frontotemporal dementia and Alzheimer’s disease cause atrophy within two major networks, an anterior ‘Salience Network’ (atrophied in behavioural variant frontotemporal dementia) and a posterior ‘Default Mode Network’ (atrophied in Alzheimer’s disease). These networks exhibit an anti-correlated relationship with each other in the healthy brain. The two diseases also feature divergent symptom-deficit profiles, with behavioural variant frontotemporal dementia undermining social-emotional function and preserving or enhancing visuospatial skills, and Alzheimer’s disease showing the inverse pattern. We hypothesized that these disorders would exert opposing connectivity effects within the Salience Network (disrupted in behavioural variant frontotemporal dementia but enhanced in Alzheimer’s disease) and the Default Mode Network (disrupted in Alzheimer’s disease but enhanced in behavioural variant frontotemporal dementia). With task-free functional magnetic resonance imaging, we tested these ideas in behavioural variant frontotemporal dementia, Alzheimer’s disease and healthy age-matched controls (n = 12 per group), using independent component analyses to generate group-level network contrasts. As predicted, behavioural variant frontotemporal dementia attenuated Salience Network connectivity, most notably in frontoinsular, cingulate, striatal, thalamic and brainstem nodes, but enhanced connectivity within the Default Mode Network. Alzheimer’s disease, in contrast, reduced Default Mode Network connectivity to posterior hippocampus, medial cingulo-parieto-occipital regions and the dorsal raphe nucleus, but intensified Salience Network connectivity. Specific regions of connectivity disruption within each targeted network predicted intrinsic connectivity enhancement within the reciprocal network. In behavioural variant frontotemporal dementia, clinical severity correlated with loss of right frontoinsular Salience Network connectivity and with biparietal Default Mode Network connectivity enhancement. Based on these results, we explored whether a combined index of Salience Network and Default Mode Network connectivity might discriminate between the three groups. Linear discriminant analysis achieved 92% clinical classification accuracy, including 100% separation of behavioural variant frontotemporal dementia and Alzheimer’s disease. Patients whose clinical diagnoses were supported by molecular imaging, genetics, or pathology showed 100% separation using this method, including four diagnostically equivocal ‘test’ patients not used to train the algorithm. Overall, the findings suggest that behavioural variant frontotemporal dementia and Alzheimer’s disease lead to divergent network connectivity patterns, consistent with known reciprocal network interactions and the strength and deficit profiles of the two disorders. Further developed, intrinsic connectivity network signatures may provide simple, inexpensive, and non-invasive biomarkers for dementia differential diagnosis and disease monitoring.
functional magnetic resonance imaging; frontotemporal dementia; Alzheimer’s disease; functional connectivity; biomarker
The ‘default network’ is defined as a set of areas, encompassing posterior-cingulate/precuneus, anterior cingulate/mesiofrontal cortex and temporo-parietal junctions, that show more activity at rest than during attention-demanding tasks. Recent studies have shown that it is possible to reliably identify this network in the absence of any task, by resting state functional magnetic resonance imaging connectivity analyses in healthy volunteers. However, the functional significance of these spontaneous brain activity fluctuations remains unclear. The aim of this study was to test if the integrity of this resting-state connectivity pattern in the default network would differ in different pathological alterations of consciousness. Fourteen non-communicative brain-damaged patients and 14 healthy controls participated in the study. Connectivity was investigated using probabilistic independent component analysis, and an automated template-matching component selection approach. Connectivity in all default network areas was found to be negatively correlated with the degree of clinical consciousness impairment, ranging from healthy controls and locked-in syndrome to minimally conscious, vegetative then coma patients. Furthermore, precuneus connectivity was found to be significantly stronger in minimally conscious patients as compared with unconscious patients. Locked-in syndrome patient’s default network connectivity was not significantly different from controls. Our results show that default network connectivity is decreased in severely brain-damaged patients, in proportion to their degree of consciousness impairment. Future prospective studies in a larger patient population are needed in order to evaluate the prognostic value of the presented methodology.
Default mode; fMRI; coma; vegetative state; minimally conscious state
During development, the healthy human brain constructs a host of large-scale, distributed, function-critical neural networks. Neurodegenerative diseases have been thought to target these systems, but this hypothesis has not been systematically tested in living humans. We used network-sensitive neuroimaging methods to show that five different neurodegenerative syndromes cause circumscribed atrophy within five distinct healthy human intrinsic functional connectivity networks. We further discovered a direct link between intrinsic connectivity and gray matter structure. Across healthy individuals, nodes within each functional network exhibited tightly correlated gray matter volumes. The findings suggest that human neural networks can be defined by synchronous baseline activity, a unified corticotrophic fate, and selective vulnerability to neurodegenerative illness. Future studies may clarify how these complex systems are assembled during development and undermined by disease.
Convergent data from various scientific approaches strongly implicate cerebellar systems in non-motor functions. The functional anatomy of these systems has been pieced together from disparate sources such as animal studies, lesion studies in humans, and structural and functional imaging studies in humans. To better define this distinct functional anatomy, in the current study we delineate the role of the cerebellum in several non-motor systems simultaneously and in the same subjects using resting state functional connectivity MRI. Independent component analysis (ICA) was applied to resting state data from two independent datasets to identify common cerebellar contributions to several previously identified intrinsic connectivity networks (ICNs) involved in executive control, episodic memory/self-reflection, salience detection, and sensorimotor function. We found distinct cerebellar contributions to each of these ICNs. The neocerebellum participates in: 1. the right and left executive control networks (especially crus I and II), 2. the salience network (lobule VI), and 3. the default-mode network (lobule IX). Little to no overlap was detected between these cerebellar regions and the sensorimotor cerebellum (lobules V–VI). Clusters were also located in pontine and dentate nuclei, prominent points of convergence for cerebellar input and output respectively. The results suggest that the most phylogenetically recent part of the cerebellum, particularly crus I and II make contributions to parallel cortico-cerebellar loops involved in executive control, salience detection, and episodic memory/self-reflection. The largest portions of the neocerebellum take part in the executive control network implicated in higher cognitive functions such as working memory.
cerebellum; cerebral cortex; intrinsically connected networks; functional connectivity; resting state; cognition
The regions that comprise the functionally connected resting-state default-mode network (DMN) in adults appear to be the same as those that are characterized by task-induced decreases in blood-oxygen-level-dependent (BOLD) signal. Independent component analysis can be used to produce a picture of the DMN as an individual rests quietly in the scanner. Contrasts across conditions in which cognitive load is parametrically modulated can delineate neural structures that have decreases in activation in response to high-demand task conditions. Examination of the degree to which these networks subsume dissociable brain substrates, and of the degree to which they overlap, provides insight concerning their purpose, function, and the nature of their associations. Few studies have examined the DMN in children, and none have tested whether the neural regions that comprise the DMN during a resting condition are the same regions that show reduced activity when children engage in cognitive tasks. In this paper we describe regions that show both task-related decreases and spontaneous intrinsic activity at rest in children, and we examine the co-localization of these networks. We describe ways in which the DMN in 7-12-year-old children is both similar to and different from the DMN in adults; moreover, we document that task-induced deactivations and default-mode resting-state activity in children share common neural substrates. It appears, therefore, that even before adolescence a core aspect of task-induced deactivation involves reallocating processing resources that are active at rest. We describe how future studies assessing the development of these systems would benefit from examining these constructs as part of one continuous system.
children; fMRI; default-mode; resting state; task-induced deactivation; functional connectivity
Recent anatomical and electrophysiological evidence in primates indicates the presence of direct connections between primary auditory and primary visual cortex that constitute cross-modal systems. We examined the intrinsic functional connectivity (fcMRI) of putative primary auditory cortex in 32 young adults during resting state scanning. We found that the medial Heschl’s gyrus was strongly coupled, in particular, to visual cortex along the anterior banks of the calcarine fissure. This observation was confirmed using novel group-level, tensor-based independent components analysis. fcMRI analysis revealed that although overall coupling between the auditory and visual cortex was significantly reduced when subjects performed a visual perception task, coupling between the anterior calcarine cortex and auditory cortex was not disrupted. These results suggest that primary auditory cortex has a functionally distinct relationship with the anterior visual cortex, which is known to represent the peripheral visual field. Our study provides novel, fcMRI-based, support for a neural system involving low-level auditory and visual cortices.
functional connectivity; cross-modal; multisensory; primary auditory cortex; primary visual cortex
Functional brain networks detected in task-free (“resting-state”) functional magnetic resonance imaging (fMRI) have a small-world architecture that reflects a robust functional organization of the brain. Here, we examined whether this functional organization is disrupted in Alzheimer's disease (AD). Task-free fMRI data from 21 AD subjects and 18 age-matched controls were obtained. Wavelet analysis was applied to the fMRI data to compute frequency-dependent correlation matrices. Correlation matrices were thresholded to create 90-node undirected-graphs of functional brain networks. Small-world metrics (characteristic path length and clustering coefficient) were computed using graph analytical methods. In the low frequency interval 0.01 to 0.05 Hz, functional brain networks in controls showed small-world organization of brain activity, characterized by a high clustering coefficient and a low characteristic path length. In contrast, functional brain networks in AD showed loss of small-world properties, characterized by a significantly lower clustering coefficient (p<0.01), indicative of disrupted local connectivity. Clustering coefficients for the left and right hippocampus were significantly lower (p<0.01) in the AD group compared to the control group. Furthermore, the clustering coefficient distinguished AD participants from the controls with a sensitivity of 72% and specificity of 78%. Our study provides new evidence that there is disrupted organization of functional brain networks in AD. Small-world metrics can characterize the functional organization of the brain in AD, and our findings further suggest that these network measures may be useful as an imaging-based biomarker to distinguish AD from healthy aging.
Alzheimer's disease (AD) is a brain disorder characterized by progressive impairment of episodic memory and other cognitive domains resulting in dementia and, ultimately, death. Functional neuroimaging studies have identified brain regions that show abnormal brain function in AD. Although there is converging evidence about the identity of these regions, it is not clear how this abnormality affects the functional organization of the whole brain. In order to characterize the functional organization of the brain, our approach uses small-world measures, which have also been used to study systems such as social networks and the internet. We use graph analytical methods to compute these measures of functional connectivity brain networks, which are derived from fMRI data obtained from healthy elderly controls and AD patients. The AD patients had significantly lower regional connectivity, and showed disrupted global functional organization, when compared to healthy controls. Moreover, our results indicate that cognitive decline in Alzheimer's disease patients is associated with disrupted functional connectivity in the entire brain. Our findings further suggest that small-world measures may be useful as an imaging-based biomarker to distinguish AD from healthy aging.