The effects of age on resting state functional connectivity of the basal ganglia from young to middle adulthood.
Neuroimage. 2014 Dec 13;
Authors: Manza P, Zhang S, Hu S, Chao HH, Leung HC, Li CS
The basal ganglia nuclei are critical for a variety of cognitive and motor functions. Much work has shown age-related structural changes of the basal ganglia. Yet less is known about how the functional interactions of these regions with the cerebral cortex and the cerebellum change throughout the lifespan. Here, we took advantage of a convenient sample and examined resting state functional magnetic resonance imaging data from 250 adults 18 to 49years of age, focusing specifically on the caudate nucleus, pallidum, putamen, and ventral tegmental area/substantia nigra (VTA/SN). There are a few main findings to report. First, with age, caudate head connectivity increased with a large region of ventromedial prefrontal/medial orbitofrontal cortex. Second, across all subjects, pallidum and putamen showed negative connectivity with default mode network (DMN) regions such as the ventromedial prefrontal cortex and posterior cingulate cortex, in support of anticorrelation of the "task-positive" network (TPN) and DMN. This negative connectivity was reduced with age. Furthermore, pallidum, posterior putamen and VTA/SN connectivity to other TPN regions, such as somatomotor cortex, decreased with age. These results highlight a distinct effect of age on cerebral functional connectivity of the dorsal striatum and VTA/SN from young to middle adulthood and may help research investigating the etiologies or monitoring outcomes of neuropsychiatric conditions that implicate dopaminergic dysfunction.
PMID: 25514518 [PubMed - as supplied by publisher]
Assessing dynamic brain graphs of time-varying connectivity in fMRI data: Application to healthy controls and patients with schizophrenia.
Neuroimage. 2014 Dec 13;
Authors: Yu Q, Erhardt EB, Sui J, Du Y, He H, Hjelm D, Cetin MS, Rachakonda S, Miller RL, Pearlson G, Calhoun VD
Graph theory-based analysis has been widely employed in brain imaging studies, and altered topological properties of brain connectivity have emerged as important features of mental diseases such as schizophrenia. However, most previous studies have focused on graph metrics of stationary brain graphs, ignoring that brain connectivity exhibits fluctuations over time. Here we develop a new framework for accessing dynamic graph properties of time-varying functional brain connectivity in resting state fMRI data and apply it to healthy controls (HCs) and patients with schizophrenia (SZs). Specifically, nodes of brain graphs are defined by intrinsic connectivity networks (ICNs) identified by group independent component analysis (ICA). Dynamic graph metrics of the time-varying brain connectivity estimated by the correlation of sliding time-windowed ICA time courses of ICNs are calculated. First- and second-level connectivity states are detected based on the correlation of nodal connectivity strength between time-varying brain graphs. Our results indicate that SZs show decreased variance in the dynamic graph metrics. Consistent with prior stationary functional brain connectivity works, graph measures of identified first-level connectivity states show lower values in SZs. In addition, more first-level connectivity states are disassociated with the second-level connectivity state which resembles the stationary connectivity pattern computed by the entire scan. Collectively, the findings provide new evidence about altered dynamic brain graphs in schizophrenia which may underscore the abnormal brain performance in this mental illness.
PMID: 25514514 [PubMed - as supplied by publisher]
Abnormal spontaneous neural activity in the anterior insula and anterior cingulate cortices in anxious depression.
Behav Brain Res. 2014 Dec 13;
Authors: Liu CH, Ma X, Song LP, Fan J, Wang WD, Lv XY, Zhang Y, Li F, Wang L, Wang CY
OBJECTIVE: Anxious depression is a distinct clinical subtype of major depressive disorder (MDD) characterized by palpitations, somatic complaints, altered interoceptive awareness, high risk of suicide, and poor response to pharmacotherapy. However, the neural mechanisms of anxious depression are still not well understood. In this study we investigated changes in neural oscillation during the resting-state of patients with anxious depression by measuring differences in the amplitude of low-frequency fluctuation (ALFF).
METHODS: Resting-state functional magnetic resonance imaging was acquired in 31 patients with anxious depression, 18 patients with remitted depression, as well as 68 gender- and age-matched healthy participants. We compared the differences both in the ALFF and fractional ALFF (fALFF) among the three groups. We also examined the correlation between the ALFF/fALFF and the severity of anxiety as well as depression.
RESULTS: Anxious depression patients showed increased ALFF/fALFF in the right dorsal anterior insular cortex and decreased ALFF/fALFF in the bilateral lingual gyrus relative to remitted depression patients and healthy controls. The increased ALFF in the dorsal anterior insula was also positively correlated with stronger anxiety in the anxious depression group. Anxious depression patients also displayed increased fALFF in the right ventral anterior cingulate cortex (ACC) compared to remitted depression patients and healthy controls.
CONCLUSIONS: Our results suggest that alterations of the cortico-limbic networks, including the right dorsal anterior insula and right ventral ACC, may play a critical role in the physiopathology of anxious depression.
PMID: 25513974 [PubMed - as supplied by publisher]
Evaluating structural symmetry of weighted brain networks via graph matching.
Med Image Comput Comput Assist Interv. 2014;17(Pt 2):733-40
Authors: Hu C, El Fakhri G, Li Q
We study the symmetry of weighted brain networks to understand the roles of individual brain areas and the redundancy of the brain connectivity. We quantify the structural symmetry of every node pair in the network by isomorphism of the residual graphs of those nodes. The efficacy of the symmetry measure is evaluated on both simulated networks and real data sets. In the resting state fMRI (rs-fMRI) data, we discover that subjects with inattentive type of Attention Deficit Hyperactivity Disorder (ADHD) demonstrate a higher level of network symmetry in contrast to the typically development group, consistent with former findings. Moreover, by comparing the average functional networks of normal subjects during resting state and activation, we obtain a higher symmetry level in the rs-fMRI network when applying median thresholds to the networks. But the symmetry levels of the networks are almost the same when larger thresholds are used, which may imply the invariance of the prominent network symmetry for ordinary people.
PMID: 25513577 [PubMed - in process]
Brain connectivity hyper-network for MCI classification.
Med Image Comput Comput Assist Interv. 2014;17(Pt 2):724-32
Authors: Jie B, Shen D, Zhang D
Brain connectivity network has been used for diagnosis and classification of neurodegenerative diseases, such as Alzheimer's disease (AD) as well as its early stage, i.e., mild cognitive impairment (MCI). However, conventional connectivity network is usually constructed based on the pairwise correlation among brain regions and thus ignores the higher-order relationship among them. Such information loss is unexpected because the brain itself is a complex network and the higher-order interaction may contain useful information for classification. Accordingly, in this paper, we propose a new brain connectivity hyper-network based method for MCI classification. Here, the connectivity hyper-network denotes a network where an edge can connect more than two brain regions, which can be naturally represented with a hyper-graph. Specifically, we first construct connectivity hyper-networks from the resting-state fMRI time series using sparse representation modeling. Then, we extract three sets of the brain-region specific features from the connectivity hyper-networks, and exploit a manifold regularized multi-task feature selection method to jointly select the most discriminative features. Finally, we use multi-kernel support vector machine (SVM) for classification. The experimental results demonstrate the efficacy of our proposed method for MCI classification with comparison to the conventional connectivity network based methods.
PMID: 25513576 [PubMed - in process]
Group-wise functional community detection through joint Laplacian diagonalization.
Med Image Comput Comput Assist Interv. 2014;17(Pt 2):708-15
Authors: Dodero L, Gozzi A, Liska A, Murino V, Sona D
There is a growing conviction that the understanding of the brain function can come through a deeper knowledge of the network connectivity between different brain areas. Resting state Functional Magnetic Resonance Imaging (rs-fMRI) is becoming one of the most important imaging modality widely used to understand network functionality. However, due to the variability at subject scale, mapping common networks across individuals is by now a real challenge. In this work we present a novel approach to group-wise community detection, i.e. identification of functional coherent sub-graphs across multiple subjects. This approach is based on a joint diagonalization of two or more graph Laplacians, aiming at finding a common eigenspace across individuals, over which clustering in fewer dimension can then be applied. This allows to identify common sub-networks across different graphs. We applied our method to rs-fMRI dataset of mouse brain finding most important sub-networks recently described in literature.
PMID: 25513574 [PubMed - in process]
[Effect of acupuncture at pericardium points of amplitude of low frequency fluctuations of healthy people in resting state functional magnetic resonance imaging].
Zhongguo Zhong Xi Yi Jie He Za Zhi. 2014 Oct;34(10):1197-201
Authors: Zhou YL, Xu HZ, Duan YL, Zhang G, Su CG, Wu YH, Xing W, Jin XY
OBJECTIVE: To observe the effect of acupuncture at the whole points of Hand Jueyin pericardium meridian on the amplitude of low frequency fluctuations (ALFF) of healthy people in resting state (R1) functional magnetic resonance imaging (fMRI).
METHODS: Totally 16 healthy subjects received structure scan of T1 and T2. Then two fMRI scans were conducted for each participant. fMRI included the resting-state scan (R1; the scanning time was 8 min 6 s), the stimulating-acupoint scan (AP; the scanning time was 8 min 6 s). fMRI data acquisition from structure scanning and function scanning were processed with format conversion and statistical analysis.
RESULTS: Under R1 state, brain regions with activated ALFF signals included bilateral superior frontal gyrus, medial frontal gyrus, middle occipital gyrus, precuneus, superior temporal gyrus, and cingulate gyrus. Under the AP state, brain regions with activated ALFF signals were bilateral superior frontal gyrus, medial frontal gyrus, middle temporal gyrus, left fusiform gyrus, precuneus, posterior cingulate, and declivis. Compared with R1 state, obvious difference of ALFF signal areas of the brain caused by acupuncture at pericardium were: bilateral cuneus, precuneus, left posterior cingulate gyrus, right middle occipital gyrus, and right occipital lingual gyrus.
CONCLUSION: Acupuncture at the whole points of Hand Jueyin pericardium meridian could significantly change inherent activity states of the cerebral cortex, especially in bilateral superior frontal gyrus, medial frontal gyrus, and precuneus.
PMID: 25509261 [PubMed - in process]
Different resting-state functional connectivity alterations in smokers and nonsmokers with internet gaming addiction.
Biomed Res Int. 2014;2014:825787
Authors: Chen X, Wang Y, Zhou Y, Sun Y, Ding W, Zhuang Z, Xu J, Du Y
This study investigated changes in resting-state functional connectivity (rsFC) of posterior cingulate cortex (PCC) in smokers and nonsmokers with Internet gaming addiction (IGA). Twenty-nine smokers with IGA, 22 nonsmokers with IGA, and 30 healthy controls (HC group) underwent a resting-state fMRI scan. PCC connectivity was determined in all subjects by investigating synchronized low-frequency fMRI signal fluctuations using a temporal correlation method. Compared with the nonsmokers with IGA, the smokers with IGA exhibited decreased rsFC with PCC in the right rectus gyrus. Left middle frontal gyrus exhibited increased rsFC. The PCC connectivity with the right rectus gyrus was found to be negatively correlated with the CIAS scores in the smokers with IGA before correction. Our results suggested that smokers with IGA had functional changes in brain areas related to motivation and executive function compared with the nonsmokers with IGA.
PMID: 25506057 [PubMed - in process]
Modality-spanning deficits in attention-deficit/hyperactivity disorder in functional networks, gray matter, and white matter.
J Neurosci. 2014 Dec 10;34(50):16555-66
Authors: Kessler D, Angstadt M, Welsh RC, Sripada C
Previous neuroimaging investigations in attention-deficit/hyperactivity disorder (ADHD) have separately identified distributed structural and functional deficits, but interconnections between these deficits have not been explored. To unite these modalities in a common model, we used joint independent component analysis, a multivariate, multimodal method that identifies cohesive components that span modalities. Based on recent network models of ADHD, we hypothesized that altered relationships between large-scale networks, in particular, default mode network (DMN) and task-positive networks (TPNs), would co-occur with structural abnormalities in cognitive regulation regions. For 756 human participants in the ADHD-200 sample, we produced gray and white matter volume maps with voxel-based morphometry, as well as whole-brain functional connectomes. Joint independent component analysis was performed, and the resulting transmodal components were tested for differential expression in ADHD versus healthy controls. Four components showed greater expression in ADHD. Consistent with our a priori hypothesis, we observed reduced DMN-TPN segregation co-occurring with structural abnormalities in dorsolateral prefrontal cortex and anterior cingulate cortex, two important cognitive control regions. We also observed altered intranetwork connectivity in DMN, dorsal attention network, and visual network, with co-occurring distributed structural deficits. There was strong evidence of spatial correspondence across modalities: For all four components, the impact of the respective component on gray matter at a region strongly predicted the impact on functional connectivity at that region. Overall, our results demonstrate that ADHD involves multiple, cohesive modality spanning deficits, each one of which exhibits strong spatial overlap in the pattern of structural and functional alterations.
PMID: 25505309 [PubMed - in process]
Functional connectivity associated with gait velocity during walking and walking-while-talking in aging: A resting-state fMRI study.
Hum Brain Mapp. 2014 Dec 11;
Authors: Yuan J, Blumen HM, Verghese J, Holtzer R
Gait decline is common among older adults and is a risk factor for adverse outcomes. Poor gait performance in dual-task conditions, such as walking while performing a secondary cognitive interference task, is associated with increased risk of frailty, disability, and death. Yet, the functional neural substrates that support locomotion are not well established. We examined the functional connectivity associated with gait velocity in single- (normal pace walking) and dual-task (walking while talking) conditions using resting-state functional Magnetic Resonance Imaging (fMRI). We acquired 6 minutes of resting-state fMRI data in 30 cognitively healthy older adults. Independent components analyses were performed to separate resting-state fMRI data into group-level statistically independent spatial components that correlated with gait velocity in single- and dual-task conditions. Gait velocity in both task conditions was associated with similar functional connectivity in sensorimotor, visual, vestibular, and left fronto-parietal cortical areas. Compared to gait velocity in the single-task condition, the networks associated with gait velocity in the dual-task condition were associated with greater functional connectivity in supplementary motor and prefrontal regions. Our findings show that there are partially overlapping functional networks associated with single- and dual-task walking conditions. These initial findings encourage the future use of resting-state fMRI as tool in developing a comprehensive understanding of age-related mobility impairments. Hum Brain Mapp, 2014. © 2014 Wiley Periodicals, Inc.
PMID: 25504964 [PubMed - as supplied by publisher]
Altered Resting-State Connectivity in College Students with Nonclinical Depressive Symptoms.
PLoS One. 2014;9(12):e114603
Authors: Wei X, Shen H, Ren J, Li X, Xu X, Yang R, Lai L, Chen L, Hu J, Liu W, Jiang X
BACKGROUND: The underlying brain basis of nonclinical depressive symptoms (nCDSs) is largely unknown. Recently, the seed-based functional connectivity (FC) approach for analyzing resting-state fMRI (rs-fMRI) data has been increasingly used to explore the neural basis of depressive disorders. Other than common seed-based FC method using an a priori seed region, we conducted FC analysis based on regions with altered spontaneous activity revealed by the fractional amplitude of low-frequency fluctuations (fALFF) approach. The aim of the present study was to provide novel insight in the underlying mechanism of nCDSs in college students.
METHODOLOGY/PRINCIPAL FINDINGS: A total number of 1105 college students were recruited to participant in a survey for assessing depressive symptoms. Subsequently, 17 individuals with nCDSs and 20 healthy controls (HCs) were enrolled to perform MR studies. Alternations of fALFF were identified in the right superior parietal lobule (SPL) and left lingual gyrus, both of which were used as ROIs for further FC analysis. With right SPL, compare with HCs, subjects with nCDSs showed reduced FCs in the bilateral dorsal lateral prefrontal cortex (DLPFC), left inferior frontal gurus (IFG), left premotor cortex (PMC), DMN network [i.e., bilateral precuneus, posterior cingulate cortex (PCC), right supramarginal gyrus (SMG), right parahippocampal gyrus (PHG), bilateral inferior temporal gurus (ITG)] and left cerebellum posterior lobe (CPL). In addition, increased FCs were observed between the left lingual gyrus and right fusiform gyrus as well as in the left precuneus.
CONCLUSION/SIGNIFICANCE: Our results indicate the abnormalities of spontaneous activity in the right SPL and left lingual gyrus and their corresponding dysfunction of the brain circuits might be related to the pathophysiology of nCDSs.
PMID: 25502215 [PubMed - as supplied by publisher]
Supervised Discriminative Group Sparse Representation for Mild Cognitive Impairment Diagnosis.
Neuroinformatics. 2014 Dec 16;
Authors: Suk HI, Wee CY, Lee SW, Shen D
Research on an early detection of Mild Cognitive Impairment (MCI), a prodromal stage of Alzheimer's Disease (AD), with resting-state functional Magnetic Resonance Imaging (rs-fMRI) has been of great interest for the last decade. Witnessed by recent studies, functional connectivity is a useful concept in extracting brain network features and finding biomarkers for brain disease diagnosis. However, it still remains challenging for the estimation of functional connectivity from rs-fMRI due to the inevitable high dimensional problem. In order to tackle this problem, we utilize a group sparse representation along with a structural equation model. Unlike the conventional group sparse representation method that does not explicitly consider class-label information, which can help enhance the diagnostic performance, in this paper, we propose a novel supervised discriminative group sparse representation method by penalizing a large within-class variance and a small between-class variance of connectivity coefficients. Thanks to the newly devised penalization terms, we can learn connectivity coefficients that are similar within the same class and distinct between classes, thus helping enhance the diagnostic accuracy. The proposed method also allows the learned common network structure to preserve the network specific and label-related characteristics. In our experiments on the rs-fMRI data of 37 subjects (12 MCI; 25 healthy normal control) with a cross-validation technique, we demonstrated the validity and effectiveness of the proposed method, showing the diagnostic accuracy of 89.19 % and the sensitivity of 0.9167.
PMID: 25501275 [PubMed - as supplied by publisher]
Default Mode Network Functional Connectivity: A Promising Biomarker for Diagnosing Minimal Hepatic Encephalopathy: CONSORT-Compliant Article.
Medicine (Baltimore). 2014 Dec;93(27):e227
Authors: Qi R, Zhang LJ, Luo S, Ke J, Kong X, Xu Q, Liu C, Lu H, Lu GM
To investigate the contribution of brain default mode network (DMN) in the early diagnosis of the minimal hepatic encephalopathy (MHE), the mildest form of HE from cirrhotic patients by using resting-state functional magnetic resonance imaging (rs-fMRI).This study was approved by the local ethical committee, and a written informed consent was obtained from each participant. A total of 103 cirrhotic patients (34 MHE, 69 non-HE) and 103 matched healthy controls underwent rs-fMRI scanning. The DMN correlation map was acquired by using unbiased seed-based functional connectivity analysis and compared among MHE patients, non-HE patients, and healthy controls with analysis of variance tests. Pearson correlation analysis was performed between the abnormal DMN connectivity and neuropsychological performances. Receiver operator characteristic (ROC) analysis was used to evaluate the contribution of DMN connectivity strength in the differential diagnosis between MHE and non-HE.Compared with the healthy controls, MHE and non-HE patients showed decreased DMN connectivity in medial prefrontal cortex (MPFC), left superior frontal gyrus (SFG), left temporal lobe, and bilateral middle temporal gyri (MTG). The MHE patients showed even more decreased connectivity in MPFC, left SFG, and right MTG when compared with non-HE patients. Pearson correlation analyses revealed that the decreased connectivity strength of some DMN regions correlated with patients' neuropsychological tests scores. Connectivity strength of the MPFC, right MTG, and left SFG could differentiate MHE from non-HE, of which the MPFC had the highest effectiveness (sensitivity = 81.5%, specificity = 70.4%).Cirrhotic patients had gradually reduced DMN functional connectivty from non-HE patients to MHE patients. DMN function, especially the MPFC, might be a useful imaging marker for differentiating MHE from cirrhotic patients.
PMID: 25501083 [PubMed - in process]
Visual attention in preterm born adults: Specifically impaired attentional sub-mechanisms that link with altered intrinsic brain networks in a compensation-like mode.
Neuroimage. 2014 Dec 9;107C:95-106
Authors: Finke K, Neitzel J, Bäuml JG, Redel P, Müller HJ, Meng C, Jaekel J, Daamen M, Scheef L, Busch B, Baumann N, Boecker H, Bartmann P, Habekost T, Wolke D, Wohlschläger A, Sorg C
Although pronounced and lasting deficits in selective attention have been observed for preterm born individuals it is unknown which specific attentional sub-mechanisms are affected and how they relate to brain networks. We used the computationally specified 'Theory of Visual Attention' together with whole- and partial-report paradigms to compare attentional sub-mechanisms of pre- (n=33) and full-term (n=32) born adults. Resting-state fMRI was used to evaluate both between-group differences and inter-individual variance in changed functional connectivity of intrinsic brain networks relevant for visual attention. In preterm born adults, we found specific impairments of visual short-term memory (vSTM) storage capacity while other sub-mechanisms such as processing speed or attentional weighting were unchanged. Furthermore, changed functional connectivity was found in unimodal visual and supramodal attention-related intrinsic networks. Among preterm born adults, the individual pattern of changed connectivity in occipital and parietal cortices was systematically associated with vSTM in such a way that the more distinct the connectivity differences, the better the preterm adults' storage capacity. These findings provide first evidence for selectively changed attentional sub-mechanisms in preterm born adults and their relation to altered intrinsic brain networks. In particular, data suggest that cortical changes in intrinsic functional connectivity may compensate adverse developmental consequences of prematurity on visual short-term storage capacity.
PMID: 25498391 [PubMed - as supplied by publisher]
Abnormal regional homogeneity in young adult suicide attempters with no diagnosable psychiatric disorder: A resting state functional magnetic imaging study.
Psychiatry Res. 2014 Nov 6;
Authors: Cao J, Chen JM, Kuang L, Ai M, Fang WD, Gan Y, Wang W, Chen XR, Xu XM, Wang HG, Lv Z
Many young adults who attempt suicide have no discernible mental illness, suggesting an etiology distinct from other psychiatric disorders. Neurological anomalies associated with a history of suicidal behavior may predict future risk. In the present study, we explored changes in neural circuit organization associated with suicidal behavior by comparing local synchronization of resting-state functional magnetic resonance imaging signals in suicide attempters without a psychiatric diagnosis (SA group, 19.84±1.61 years, n=19) with those in healthy controls (HC group, 20.30±1.72 years, n=20) using regional homogeneity (ReHo) analysis. The SA group exhibited significantly lower mean ReHo in the left (L) fusiform and supraorbital inferior frontal gyri, L hippocampus, bilateral parahippocampal and middle frontal gyri, right (R) angular gyrus, and cerebellar lobules RVIII, RII, and LVI compared with the HC group. Conversely, in the SA group, ReHo was higher in the R supraorbital middle frontal gyrus, R inferior parietal lobe, and L precuneus. The SA group also had significantly higher total Barratt Impulsiveness Scale scores compared with the HC group. Local functional connectivity is altered in multiple regions of the cerebral cortex, limbic system, and cerebellum of suicidal young adults. Elucidating the functional deficits associated with these ReHo changes may clarify the pathophysiological mechanisms of suicidal behavior and assist in identifying high-risk individuals.
PMID: 25496980 [PubMed - as supplied by publisher]
Altered intrinsic regional activity and corresponding brain pathways reflect the symptom severity of functional dyspepsia.
Neurogastroenterol Motil. 2014 May;26(5):660-9
Authors: Nan J, Liu J, Zhang D, Yang Y, Yan X, Yin Q, Xiong S, von Deneen KM, Liang F, Gong Q, Qin W, Tian J, Zeng F
BACKGROUND: Increasing evidence shows central abnormalities in functional dyspepsia (FD) patients, but whether the symptom severity is directly reflected in altered brain patterns remains unclear. The purpose of this study was to explore how FD affected the resting functional brain patterns for different degrees of symptom severity.
METHODS: Functional magnetic resonance imaging was carried out in 40 FD patients and 20 healthy controls. The resting-state brain changes in regional homogeneity (ReHo) and seed correlation analysis were investigated in patients relative to controls. To what degree the brain changes reflected the severity of the disease was assessed by a pattern classification technique.
KEY RESULTS: Altered ReHo values (p < 0.05, FDR corrected) were discovered in multiple brain areas in FD patients, and only the anterior cingulate cortex (ACC) and thalamus exhibited significant correlation with the severity of dyspepsia symptoms. Compared with controls, the neural signal changes of the thalamus were not found in the less severe FD patient group but in the relatively more severe group, while the ACC showed aberrations in both groups. Seed-based correlation analysis revealed ACC- and thalamus-related functional connectivity differences between FD patients and controls at a voxel-wise level, and the altered thalamic circuits provided the best performance in distinguishing FD patients with different levels of symptom severity.
CONCLUSIONS & INFERENCES: Our results indicated that the functional abnormalities of the ACC and thalamus may occur at different clinical courses in FD. This may help us better understand the progression of FD.
PMID: 24467632 [PubMed - indexed for MEDLINE]
The value of resting-state functional magnetic resonance imaging in stroke.
Stroke. 2014 Sep;45(9):2818-24
Authors: Ovadia-Caro S, Margulies DS, Villringer A
PMID: 25013022 [PubMed - indexed for MEDLINE]
Common intrinsic connectivity states among posteromedial cortex subdivisions: Insights from analysis of temporal dynamics.
Neuroimage. 2014 Jun;93 Pt 1:124-37
Authors: Yang Z, Craddock RC, Margulies DS, Yan CG, Milham MP
Perspectives of human brain functional connectivity continue to evolve. Static representations of functional interactions between brain regions are rapidly giving way to dynamic perspectives, which emphasize non-random temporal variations in intrinsic functional connectivity (iFC) patterns. Here, we bring this dynamic perspective to our understanding of iFC patterns for posteromedial cortex (PMC), a cortical hub known for its functional diversity. Previous work has consistently differentiated iFC patterns among PMC subregions, though assumed static iFC over time. Here, we assessed iFC as a function of time utilizing a sliding-window correlation approach, and applied hierarchical clustering to detect representative iFC states from the windowed iFC. Across subregions, five iFC states were detected over time. Although with differing frequencies, each subregion was associated with each of the states, suggesting that these iFC states are "common" to PMC subregions. Importantly, each subregion possessed a unique preferred state(s) and distinct transition patterns, explaining previously observed iFC differentiations. These results resonate with task-based fMRI studies suggesting that large-scale functional networks can be flexibly reconfigured in response to changing task-demands. Additionally, we used retest scans (~1week later) to demonstrate the reproducibility of the iFC states identified, and establish moderate to high test-retest reliability for various metrics used to quantify switching behaviors. We also demonstrate the ability of dynamic properties in the visual PMC subregion to index inter-individual differences in a measure of concept formation and mental flexibility. These findings suggest functional relevance of dynamic iFC and its potential utility in biomarker identification over time, as d-iFC methodologies are refined and mature.
PMID: 24560717 [PubMed - indexed for MEDLINE]
Borders, map clusters, and supra-areal organization in visual cortex.
Neuroimage. 2014 Jun;93 Pt 2:292-7
Authors: Buckner RL, Yeo BT
V1 is a canonical cortical area with clearly delineated architectonic boundaries and a continuous topographic representation of the visual hemifield. It thus serves as a touchstone for understanding what new mapping methods can tell us about cortical organization. By parcellating human cortex using local gradients in functional connectivity, Wig et al. (2014--in this issue) detected the V1 border with V2. By contrast, previously-published clustering methods that focus on global similarity in connectivity reveal a supra-areal organization that emphasizes eccentricity bands spanning V1 and its neighboring extrastriate areas; i.e. in the latter analysis, the V1 border is not evident. Thus the focus on local connectivity gradients emphasizes qualitatively different features of cortical organization than are captured by global similarity measures. What is intriguing to consider is that each kind of information might be telling us something unique about cortical organization. Global similarity measures may be detecting map clusters and other supra-areal arrangements that reflect a fundamental level of organization.
PMID: 24374078 [PubMed - indexed for MEDLINE]
Global resting-state functional magnetic resonance imaging analysis identifies frontal cortex, striatal, and cerebellar dysconnectivity in obsessive-compulsive disorder.
Biol Psychiatry. 2014 Apr 15;75(8):595-605
Authors: Anticevic A, Hu S, Zhang S, Savic A, Billingslea E, Wasylink S, Repovs G, Cole MW, Bednarski S, Krystal JH, Bloch MH, Li CS, Pittenger C
BACKGROUND: Obsessive-compulsive disorder (OCD) is associated with regional hyperactivity in cortico-striatal circuits. However, the large-scale patterns of abnormal neural connectivity remain uncharacterized. Resting-state functional connectivity studies have shown altered connectivity within the implicated circuitry, but they have used seed-driven approaches wherein a circuit of interest is defined a priori. This limits their ability to identify network abnormalities beyond the prevailing framework. This limitation is particularly problematic within the prefrontal cortex (PFC), which is large and heterogeneous and where a priori specification of seeds is therefore difficult. A hypothesis-neutral, data-driven approach to the analysis of connectivity is vital.
METHODS: We analyzed resting-state functional connectivity data collected at 3T in 27 OCD patients and 66 matched control subjects with a recently developed data-driven global brain connectivity (GBC) method, both within the PFC and across the whole brain.
RESULTS: We found clusters of decreased connectivity in the left lateral PFC in both whole-brain and PFC-restricted analyses. Increased GBC was found in the right putamen and left cerebellar cortex. Within regions of interest in the basal ganglia and thalamus, we identified increased GBC in dorsal striatum and anterior thalamus, which was reduced in patients on medication. The ventral striatum/nucleus accumbens exhibited decreased global connectivity but increased connectivity specifically with the ventral anterior cingulate cortex in subjects with OCD.
CONCLUSIONS: These findings identify previously uncharacterized PFC and basal ganglia dysconnectivity in OCD and reveal differentially altered GBC in dorsal and ventral striatum. Results highlight complex disturbances in PFC networks, which could contribute to disrupted cortical-striatal-cerebellar circuits in OCD.
PMID: 24314349 [PubMed - indexed for MEDLINE]