Regional Homogeneity: A Multimodal, Multiscale Neuroimaging Marker of the Human Connectome.
Neuroscientist. 2015 Jul 13;
Authors: Jiang L, Zuo XN
Much effort has been made to understand the organizational principles of human brain function using functional magnetic resonance imaging (fMRI) methods, among which resting-state fMRI (rfMRI) is an increasingly recognized technique for measuring the intrinsic dynamics of the human brain. Functional connectivity (FC) with rfMRI is the most widely used method to describe remote or long-distance relationships in studies of cerebral cortex parcellation, interindividual variability, and brain disorders. In contrast, local or short-distance functional interactions, especially at a scale of millimeters, have rarely been investigated or systematically reviewed like remote FC, although some local FC algorithms have been developed and applied to the discovery of brain-based changes under neuropsychiatric conditions. To fill this gap between remote and local FC studies, this review will (1) briefly survey the history of studies on organizational principles of human brain function; (2) propose local functional homogeneity as a network centrality to characterize multimodal local features of the brain connectome; (3) render a neurobiological perspective on local functional homogeneity by linking its temporal, spatial, and individual variability to information processing, anatomical morphology, and brain development; and (4) discuss its role in performing connectome-wide association studies and identify relevant challenges, and recommend its use in future brain connectomics studies.
PMID: 26170004 [PubMed - as supplied by publisher]
Task- and stimulus-related cortical networks in language production: Exploring similarity of MEG- and fMRI-derived functional connectivity.
Neuroimage. 2015 Jul 10;
Authors: Liljeström M, Stevenson C, Kujala J, Salmelin R
Large-scale networks support the dynamic integration of information across multiple functionally specialized brain regions. Network analyses of haemodynamic modulations have revealed such functional brain networks that show high consistency across subjects and different cognitive states. However, the relationship between the slowly fluctuating haemodynamic responses and the underlying neural mechanisms is not well understood. Resting state studies have revealed spatial similarities in the estimated network hub locations derived using haemodynamic and electrophysiological recordings, suggesting a direct neural basis for the widely described functional magnetic resonance imaging (fMRI) resting state networks. To truly understand the nature of the relationship between electrophysiology and haemodynamics it is important to move away from a task absent state and to establish if such networks are differentially modulated by cognitive processing. The present parallel fMRI and magnetoencephalography (MEG) experiment investigated the structural similarities between haemodynamic networks and their electrophysiological counterparts when either the stimulus or the task was varied. Connectivity patterns underlying action vs. object naming (task-driven modulations), and action vs. object images (stimulus-driven modulations) were identified in a data driven all-to-all connectivity analysis, with cross spectral coherence adopted as a metric of functional connectivity in both MEG and fMRI. We observed a striking difference in functional connectivity between conditions. The spectral profiles of the frequency-specific network similarity differed significantly for the task-driven vs. stimulus-driven connectivity modulations. While the greatest similarity between MEG and fMRI derived networks was observed at neural frequencies below 30 Hz, haemodynamic network interactions could not be attributed to a single frequency band. Instead, the entire spectral profile should be taken into account when assessing the correspondence between MEG and fMRI networks. Task-driven network hubs, evident in both MEG and fMRI, were found in cortical regions previously associated with language processing, including the posterior temporal cortex and the inferior frontal cortex. Network hubs related to stimulus-driven modulations, however, were found in regions related to object recognition and visual processing, including the lateral occipital cortex. Overall, the results depict a shift in network structure when moving from a task dependent modulation to a stimulus dependent modulation, revealing a reorganisation of large-scale functional connectivity during task performance.
PMID: 26169324 [PubMed - as supplied by publisher]
The frequency dimension of fMRI dynamic connectivity: network connectivity, functional hubs and integration in the resting brain.
Neuroimage. 2015 Jul 10;
Authors: Thompson WH, Fransson P
The large-scale functional MRI connectome of the human brain is composed of multiple resting-state networks (RSNs). However, the network dynamics, such as integration and segregation between and within RSNs is largely unknown. To address this question we created high-resolution "frequency graphlets", connectivity matrices derived across the low-frequency spectrum of the BOLD fMRI resting-state signal (0.01 - 0.1 Hz) in a cohort of 100 subjects. We then apply and compare graph theoretical measures across the frequency graphlets. Our results show that the within- and between-network connectivity and presence of functional hubs shift as a function of frequency. Furthermore, we show that the small world network property peaks at different frequencies with corresponding spatial connectivity profiles. We conclude that the frequency dependence of the network connectivity and the spatial configuration of functional hubs suggest that the dynamics of large-scale network integration and segregation operate at different time scales.
PMID: 26169321 [PubMed - as supplied by publisher]
[Aberrant topological properties of whole-brain functional network in chronic right-sided sensorineural hearing loss: a resting-state functional MRI study].
Zhonghua Yi Xue Za Zhi. 2015 Feb 3;95(5):349-52
Authors: Zhang L, Liu B, Xu Y, Yang M, Feng Y, Huang Y, Huan Z, Hou Z
OBJECTIVE: To investigate the topological properties of the functional brain network in unilateral sensorineural hearing loss patients.
METHODS: In this study, we acquired resting-state BOLD- fMRI data from 19 right-sided SNHL patients and 31 healthy controls with normal hearing and constructed their whole brain functional networks. Two-sample two-tailed t-tests were performed to investigate group differences in topological parameters between the USNHL patients and the controls. Partial correlation analysis was conducted to determine the relationships between the network metrics and USNHL-related variables.
RESULTS: Both USNHL patients and controls exhibited small-word architecture in their brain functional networks within the range 0. 1 - 0. 2 of sparsity. Compared to the controls, USNHL patients showed significant increase in characteristic path length and normalized characteristic path length, but significant decrease in global efficiency. Clustering coefficient, local efficiency and normalized clustering coefficient demonstrated no significant difference. Furthermore, USNHL patients exhibited no significant association between the altered network metrics and the duration of USNHL or the severity of hearing loss.
CONCLUSION: Our results indicated the altered topological properties of whole brain functional networks in USNHL patients, which may help us to understand pathophysiologic mechanism of USNHL patients.
PMID: 26168669 [PubMed - in process]
Organization of intrinsic functional brain connectivity predicts decisions to reciprocate social behavior.
Behav Brain Res. 2015 Jul 9;
Authors: Cáceda R, James GA, Gutman DA, Kilts CD
Reciprocation of trust exchanges is central to the development of interpersonal relationships and societal well-being. Understanding how humans make pro-social and self-centered decisions in dyadic interactions and how to predict these choices has been an area of great interest in social neuroscience. A functional magnetic resonance imaging (fMRI) based technology with potential clinical application is the study of resting state brain connectivity. We tested if resting state connectivity may predict choice behavior in a social context. Twenty-nine healthy adults underwent resting state fMRI before performing the Trust Game, a two person monetary exchange game. We assessed the ability of patterns of resting-state functional brain organization, demographic characteristics and a measure of moral development, the Defining Issues Test (DIT-2), to predict individuals' decisions to reciprocate money during the Trust Game. Subjects reciprocated in 74.9% of the trials. Independent component analysis identified canonical resting-state networks. Increased functional connectivity between the salience (bilateral insula/ anterior cingulate) and central executive (dorsolateral prefrontal cortex/ posterior parietal cortex) networks significantly predicted the choice to reciprocate pro-social behavior (R(2)=0.20, p= 0.015). Stepwise linear regression analysis showed that functional connectivity between these two networks (p=0.002), age (p=0.007) and DIT-2 personal interest schema score (p=0.032) significantly predicted reciprocity behavior (R(2)=0.498, p= 0.001). Intrinsic functional connectivity between neural networks in conjunction with other individual characteristics may be a valuable tool for predicting performance during social interactions. Future replication and temporal extension of these findings may bolster the understanding of decision making in clinical, financial and marketing settings.
PMID: 26166191 [PubMed - as supplied by publisher]
Large-scale functional brain network reorganization during Taoist meditation.
Brain Connect. 2015 Jul 13;
Authors: Jao T, Li CW, Vértes PE, Wu CW, Achard S, Hsieh CH, Liou CH, Chen JH, Bullmore E
Meditation induces a distinct and reversible mental state that provides insights into brain correlates of consciousness. We explored brain network changes related to meditation by graph theoretical analysis of resting-state functional magnetic resonance imaging (rs-fMRI) data. Eighteen Taoist meditators with varying levels of expertise were scanned using a within-subjects counterbalanced design during resting and meditation states. State-related differences in network topology were measured globally and at the level of individual nodes and edges. Although measures of global network topology, such as small-worldness, were unchanged, meditation was characterized by an extensive and expertise-dependent reorganization of the hubs (highly connected nodes) and edges (functional connections). Areas of sensory cortex, especially the bilateral primary visual and auditory cortices, and the bilateral temporopolar areas, which had the highest degree (or connectivity) during the resting state, showed the biggest decrease during meditation. Conversely, bilateral thalamus and components of the default mode network (DMN), mainly the bilateral precuneus and posterior cingulate cortex, had low degree in the resting state but increased degree during meditation. Additionally, these changes in nodal degree were accompanied by reorganization of anatomical orientation of the edges. During meditation, long-distance longitudinal (antero-posterior) edges increased proportionally whereas orthogonal long-distance transverse (right-left) edges connecting bilaterally homologous cortices decreased. Our findings suggest that transient changes in consciousness associated with meditation introduce convergent changes in the topological and spatial properties of brain functional networks, and the anatomical pattern of integration might be as important as the global level of integration when considering the network basis for human consciousness.
PMID: 26165867 [PubMed - as supplied by publisher]
Thalamocortical Sensorimotor Circuit Damage Associated with Disorders of Consciousness for Diffuse Axonal Injury Patients.
J Neurol Sci. 2015 Jun 24;
Authors: Yao S, Song J, Gao L, Yan Y, Huang C, Ding H, Huang H, He Y, Sun R, Xu G
The relationship of structural and functional brain damage and disorders of consciousness (DOC) for diffuse axonal injury (DAI) is still not fully explored. We employed diffusion tensor imaging (DTI) and resting-state fMRI (RS-fMRI) to examine the changes of resting activations and white matter (WM) integrity for DAI with DOC. WM damages were observed in the body and genu of the corpus callosum, right external capsule (EC) and superior corona radiate (SCR), left superior cerebellar peduncle (SCP) and posterior thalamic radiation (PTR). The RS-fMRI revealed augmented amplitude of low-frequency fluctuation (ALFF) in the anterior cingulate cortex, hippocampus, insula, amygdala and putamen, and reduced ALFF in the precuneus, thalamus, pre-central and post-central gyri. Correlation analysis identified positive associations between the Glasgow Coma Scale (GCS) and activation of the precuneus and between GCS and DTI measurements in the left PTR and SCP, but a negative correlation was found between GCS and activation of the thalamus. Cross modality association analyses indicated that activations of the amygdala and postcentral gyrus were correlated with DTI measurements of the right EC and left PTR respectively. These results implicate that the WM damages in thalamocortical sensorimotor circuit and aberrant brain activity responding to self-awareness and sensation are critical factors to DOC, which expand the current understanding of the neural mechanisms underlying DAI.
PMID: 26165776 [PubMed - as supplied by publisher]
Longitudinal reproducibility of default-mode network connectivity in healthy elderly participants: A multicentric resting-state fMRI study.
Neuroimage. 2015 Jul 8;
Authors: Jovicich J, Minati L, Marizzoni M, Marchitelli R, Sala-Llonch R, Bartrés-Faz D, Arnold J, Benninghoff J, Fiedler U, Roccatagliata L, Picco A, Nobili F, Blin O, Bombois S, Lopes R, Bordet R, Sein J, Ranjeva JP, Didic M, Gros-Dagnac H, Payoux P, Zoccatelli G, Alessandrini F, Beltramello A, Bargalló N, Ferretti A, Caulo M, Aiello M, Cavaliere C, Soricelli A, Parnetti L, Tarducci R, Floridi P, Tsolaki M, Constantinidis M, Drevelegas A, Rossini PM, Marra C, Schönknecht P, Hensch T, Hoffmann KT, Kuijer JP, Visser PJ, Scheltens P, Frisoni GB, PharmaCog Consortium
To date, limited data are available regarding the inter-site consistency of test-retest reproducibility of functional connectivity measurements, in particular with regards to integrity of the default mode network (DMN) in elderly participants. We implemented a harmonized resting-state fMRI protocol on 13 clinical scanners at 3.0 Tesla using vendor-provided sequences. Each site scanned a group of 5 healthy elderly participants twice, at least a week apart. We evaluated inter-site differences and test-retest reproducibility of both temporal signal-to-noise ratio (tSNR) and functional connectivity measurements derived from: i) seed-based analysis (SBA) with seed in the posterior cingulate cortex (PCC), ii) group independent component analysis (ICA) separately for each site (site ICA), and iii) consortium ICA, with group ICA across the whole consortium. Despite protocol harmonization, significant and quantitatively important inter-site differences remained in the tSNR of resting-state fMRI data; these were plausibly driven by hardware and pulse sequence differences across scanners which could not be harmonized. Nevertheless, the tSNR test-retest reproducibility in the consortium was high (ICC=0.81). The DMN was consistently extracted across all sites and analysis methods. While significant inter-site differences in connectivity scores were found, there were no differences in the associated test-retest error. Overall, ICA measurements were more reliable than PCC-SBA, with site ICA showing higher reproducibility than consortium ICA. Across the DMN nodes, the PCC yielded the most reliable measurements (≈4% test-retest error, ICC=0.85), the medial frontal cortex the least reliable (≈12%, ICC=0.82) and the lateral parietal cortices were in between (site ICA). Altogether these findings support usage of harmonized multisite studies of resting-state functional connectivity to characterize longitudinal effects in studies that assess disease progression and treatment response.
PMID: 26163799 [PubMed - as supplied by publisher]
Improved sensitivity and specificity for resting state and task fMRI with multiband multi-echo EPI compared to multi-echo EPI at 7T.
Neuroimage. 2015 Jul 8;
Authors: Boyacioğlu R, Schulz J, Koopmans PJ, Barth M, Norris DG
A multiband multi-echo (MBME) sequence is implemented and compared to a matched standard multi-echo (ME) protocol to investigate the potential improvement in sensitivity and spatial specificity at 7T for resting state and task fMRI. ME acquisition is attractive because BOLD sensitivity is less affected by variation in T2*, and because of the potential for separating BOLD and non-BOLD signal components. MBME further reduces TR thus increasing the potential reduction in physiological noise. In this study we used FSL-FIX to clean ME and MBME resting state and task fMRI data (both 3.5mm isotropic). After noise correction, the detection of resting state networks improves with more non-artifactual independent components being observed. Additional activation clusters for task data are discovered for MBME data (increased sensitivity) whereas existing clusters become more localized for resting state (improved spatial specificity). The results obtained indicate that MBME is superior to ME at high field strengths.
PMID: 26162554 [PubMed - as supplied by publisher]
Dynamic coherence analysis of resting fMRI data to jointly capture state-based phase, frequency, and time-domain information.
Neuroimage. 2015 Jul 7;
Authors: Yaesoubi M, Allen EA, Miller RL, Calhoun VD
Many approaches for estimating functional connectivity among brain regions or networks in fMRI have been considered in the literature. More recently, studies have shown that connectivity which is usually estimated by calculating correlation between time series or by estimating coherence as a function of frequency has a dynamic nature, during both task and resting conditions. Sliding-window methods have been commonly used to study these dynamic properties although other approaches such as instantaneous phase synchronization have also been used for similar purposes. Some studies have also suggested that spectral analysis can be used to separate the distinct contributions of motion, respiration and neurophysiological activity from the observed correlation. Several recent studies have merged analysis of coherence with study of temporal dynamics of functional connectivity though these have mostly been limited to a few selected brain regions and frequency bands. Here we propose a novel data-driven framework to estimate time-varying patterns of whole-brain functional network connectivity of resting state fMRI combined with the different frequencies and phase lags at which these patterns are observed. We show that this analysis identifies both broad-band cluster centroids that summarize connectivity patterns observed in many frequency bands, as well as clusters consisting only of functional network connectivity (FNCs) from a narrow range of frequencies along with associated phase profiles. The value of this approach is demonstrated by its ability to reveal significant group differences in males versus females regarding occupancy rates of cluster that would not be separable without considering the frequencies and phase lags. The method we introduce provides a novel and informative framework for analyzing time-varying and frequency specific connectivity which can be broadly applied to the study of the healthy and diseased human brain.
PMID: 26162552 [PubMed - as supplied by publisher]
Is First-Order Vector Autoregressive Model Optimal for fMRI Data?
Neural Comput. 2015 Jul 10;:1-15
Authors: Ting CM, Seghouane AK, Khalid MU, Salleh SH
We consider the problem of selecting the optimal orders of vector autoregressive (VAR) models for fMRI data. Many previous studies used model order of one and ignored that it may vary considerably across data sets depending on different data dimensions, subjects, tasks, and experimental designs. In addition, the classical information criteria (IC) used (e.g., the Akaike IC, AIC) are biased and inappropriate for the high-dimensional fMRI data typically with a small sample size. We examine the mixed results on the optimal VAR orders for fMRI, especially the validity of the order-one hypothesis, by a comprehensive evaluation using different model selection criteria over three typical data types-a resting state, an event-related design, and a block design data set-with varying time series dimensions obtained from distinct functional brain networks. We use a more balanced criterion, Kullback's IC (KIC) based on Kullback's symmetric divergence combining two directed divergences. We also consider the bias-corrected versions (AICc and KICc) to improve VAR model selection in small samples. Simulation results show better small-sample selection performance of the proposed criteria over the classical ones. Both bias-corrected ICs provide more accurate and consistent model order choices than their biased counterparts, which suffer from overfitting, with KICc performing the best. Results on real data show that orders greater than one were selected by all criteria across all data sets for the small to moderate dimensions, particularly from small, specific networks such as the resting-state default mode network and the task-related motor networks, whereas low orders close to one but not necessarily one were chosen for the large dimensions of full-brain networks.
PMID: 26161816 [PubMed - as supplied by publisher]
Change of Brain Functional Connectivity in Patients With Spinal Cord Injury: Graph Theory Based Approach.
Ann Rehabil Med. 2015 Jun;39(3):374-83
Authors: Min YS, Chang Y, Park JW, Lee JM, Cha J, Yang JJ, Kim CH, Hwang JM, Yoo JN, Jung TD
OBJECTIVE: To investigate the global functional reorganization of the brain following spinal cord injury with graph theory based approach by creating whole brain functional connectivity networks from resting state-functional magnetic resonance imaging (rs-fMRI), characterizing the reorganization of these networks using graph theoretical metrics and to compare these metrics between patients with spinal cord injury (SCI) and age-matched controls.
METHODS: Twenty patients with incomplete cervical SCI (14 males, 6 females; age, 55±14.1 years) and 20 healthy subjects (10 males, 10 females; age, 52.9±13.6 years) participated in this study. To analyze the characteristics of the whole brain network constructed with functional connectivity using rs-fMRI, graph theoretical measures were calculated including clustering coefficient, characteristic path length, global efficiency and small-worldness.
RESULTS: Clustering coefficient, global efficiency and small-worldness did not show any difference between controls and SCIs in all density ranges. The normalized characteristic path length to random network was higher in SCI patients than in controls and reached statistical significance at 12%-13% of density (p<0.05, uncorrected).
CONCLUSION: The graph theoretical approach in brain functional connectivity might be helpful to reveal the information processing after SCI. These findings imply that patients with SCI can build on preserved competent brain control. Further analyses, such as topological rearrangement and hub region identification, will be needed for better understanding of neuroplasticity in patients with SCI.
PMID: 26161343 [PubMed]
Brain Network Response to Acupuncture Stimuli in Experimental Acute Low Back Pain: An fMRI Study.
Evid Based Complement Alternat Med. 2015;2015:210120
Authors: Shi Y, Liu Z, Zhang S, Li Q, Guo S, Yang J, Wu W
Most neuroimaging studies have demonstrated that acupuncture can significantly modulate brain activation patterns in healthy subjects, while only a few studies have examined clinical pain. In the current study, we combined an experimental acute low back pain (ALBP) model and functional magnetic resonance imaging (fMRI) to explore the neural mechanisms of acupuncture analgesia. All ALBP subjects first underwent two resting state fMRI scans at baseline and during a painful episode and then underwent two additional fMRI scans, once during acupuncture stimulation (ACUP) and once during tactile stimulation (SHAM) pseudorandomly, at the BL40 acupoint. Our results showed that, compared with the baseline, the pain state had higher regional homogeneity (ReHo) values in the pain matrix, limbic system, and default mode network (DMN) and lower ReHo values in frontal gyrus and temporal gyrus; compared with the OFF status, ACUP yielded broad deactivation in subjects, including nearly all of the limbic system, pain status, and DMN, and also evoked numerous activations in the attentional and somatosensory systems; compared with SHAM, we found that ACUP induced more deactivations and fewer activations in the subjects. Multiple brain networks play crucial roles in acupuncture analgesia, suggesting that ACUP exceeds a somatosensory-guided mind-body therapy for ALBP.
PMID: 26161117 [PubMed]
Altered Frontal Inter-Hemispheric Resting State Functional Connectivity Is Associated With Bulimic Symptoms Among Restrained Eaters.
Neuropsychologia. 2015 Jul 6;
Authors: Chen S, Dong D, Jackson T, Su Y, Chen H
Theory and research have indicated that restrained eating (RE) increases risk for binge-eating and eating disorder symptoms. According to the goal conflict model, such risk may result from disrupted hedonic-feeding control and its interaction with reward-driven eating. However, RE-related alterations in functional interactions among associated underlying brain regions, especially between the cerebral hemispheres, have rarely been examined directly. Therefore, we investigated inter-hemispheric resting-state functional connectivity (RSFC) among female restrained eaters (REs) (n=23) and unrestrained eaters (UREs=24) following food deprivation as well as its relation to overall bulimia nervosa (BN) symptoms using voxel-mirrored homotopic connectivity (VMHC). Seed-based RSFC associated with areas exhibiting significant VMHC differences were also assessed. Compared to UREs, REs showed reduced VMHC in the dorsal-lateral prefrontal cortex (DLPFC), an area involved in inhibiting hedonic overeating. REs also displayed decreased RSFC between the right DLPFC and regions associated with reward estimation - the ventromedial prefrontal cortex (VMPFC) and posterior cingulate cortex (PCC). Finally, bulimic tendencies had a negative correlation with VMHC in the DLPFC and a positive correlation with functional connectivity (DLPFC and VMPFC) among REs but not UREs. Findings suggested that reduced inter-hemispheric functional connectivity in appetite inhibition regions and altered functional connectivity in reward related regions may help to explain why some REs fail to control hedonically-motivated feeding and experience higher associated levels of BN symptomatology.
PMID: 26160289 [PubMed - as supplied by publisher]
Abnormal degree centrality in neurologically asymptomatic patients with end-stage renal disease: A resting-state fMRI study.
Clin Neurophysiol. 2015 Jul 2;
Authors: Li S, Ma X, Huang R, Li M, Tian J, Wen H, Lin C, Wang T, Zhan W, Fang J, Jiang G
OBJECTIVE: End-stage renal disease (ESRD), characterized by multi-organ dysfunction, has been shown to co-occur with abnormal brain function. Previous resting-state fMRI studies suggested that regional brain spontaneous activity and functional connectivity within the default mode network are abnormal in ESRD patients. The current study aimed to depict intrinsic dysconnectivity pattern of whole-brain functional networks in voxel level in neurologically asymptomatic patients with ESRD.
METHODS: fMRI datasets were acquired from 22 ESRD patients (without clinical neurological disease) and 29 healthy control (HC) subjects. We investigated the degree centrality for a given element in a network to reveal the changes of functional connectivity throughout the huge human functional network. In the brain regions showing a difference between the HC and ESRD groups, we further conducted receptive operation characteristic (ROC) analyses to confirm the accuracy, sensitivity and specificity of our results.
RESULTS: ESRD patients showed decreased functional connectivity in the left inferior parietal and left precuneus within the brain network; both regions are important components of the default-mode network (DMN). In contrast, patients showed increased connectivity in depression-related regions including bilateral inferior frontal gyrus and right superior temporal gyrus. These regions showed an acceptable accuracy (0.68-0.75), sensitivity (0.64-0.70) and high specificity (0.82-0.96) in distinguishing between the two groups.
CONCLUSIONS: Our findings reveal abnormal intrinsic dysconnectivity pattern of whole-brain functional networks in ESRD patients.
SIGNIFICANCE: Our results could lead to a better understanding of the intrinsic dysconnectivity patterns of default-mode network-related regions in ESRD patients from the whole brain network perspective.
PMID: 26160274 [PubMed - as supplied by publisher]
Functional connectivity hubs could serve as a potential biomarker in Alzheimer's disease: a reproducible study.
Curr Alzheimer Res. 2015 Jul 10;
Authors: Sui X, Zhu M, Cui Y, Yu C, Sui J, Zhang X, Liu J, Duan Y, Zhang Z, Wang L, Zhang X, Jiang T
Cortical hubs that link functionally specialized neural systems are crucial for cognition. Evidence suggests that the location and organization of hubs are related to Alzheimer's disease (AD). However, two issues remain unclear: (i) where and how hubs change in AD, and (ii) whether hubs could be a potential pre-diagnosis biomarker for mild cognitive impairment (MCI) - a prodromal phase of AD. Accordingly, we examined the functional connectivity density (FCD) in two cohorts of resting-state functional magnetic resonance imaging (fMRI) scans (26 AD, 27 controls; 33 AD, 21 controls) and revealed consistently vulnerable FCD hub regions in AD compared with controls: within the default mode network, short-range FCD decreases in the posterior cingulate cortex and increases in the medial prefrontal cortex; within the frontal lobe, long-range FCD increases in the medial prefrontal cortex, superior frontal gyrus and middle frontal gyrus. Furthermore, FCD correlates with cognitive score and could distinguish MCI from controls with high accuracy (71.08% in dataset 1, 81% in dataset 2). By reflecting a robust and reproducible global shift in brain functions, FCD provides an fMRI biomarker for the underlying mechanism in AD. .
PMID: 26159198 [PubMed - as supplied by publisher]
Increased Amplitude of Low Frequency Fluctuations but Normal Hippocampal-Default Mode Network Connectivity in Schizophrenia.
Front Psychiatry. 2015;6:92
Authors: McHugo M, Rogers BP, Talati P, Woodward ND, Heckers S
BACKGROUND: Clinical and preclinical studies have established that the hippocampus is hyperactive in schizophrenia, making it a possible biomarker for drug development. Increased hippocampal connectivity, which can be studied conveniently with resting state imaging, has been proposed as a readily accessible corollary of hippocampal hyperactivity. Here, we tested the hypothesis that hippocampal activity and connectivity are increased in patients with schizophrenia.
METHODS: Sixty-three schizophrenia patients and 71 healthy control subjects completed a resting state functional magnetic resonance imaging scan. We assessed hippocampal activity with the amplitude of low frequency fluctuations. We analyzed hippocampal functional connectivity with the default mode network using three common methods: group and single subject level independent component analysis, and seed-based functional connectivity.
RESULTS: In patients with schizophrenia, we observed increased amplitude of low frequency fluctuations but normal hippocampal connectivity using independent component and seed-based analyses.
CONCLUSION: Our results indicate that although intrinsic hippocampal activity may be increased in schizophrenia, this finding does not extend to functional connectivity. Neuroimaging methods that directly assess hippocampal activity may be more promising for the identification of a biomarker for schizophrenia.
PMID: 26157396 [PubMed]
Visual Learning Induces Changes in Resting-State fMRI Multivariate Pattern of Information.
J Neurosci. 2015 Jul 8;35(27):9786-98
Authors: Guidotti R, Del Gratta C, Baldassarre A, Romani GL, Corbetta M
When measured with functional magnetic resonance imaging (fMRI) in the resting state (R-fMRI), spontaneous activity is correlated between brain regions that are anatomically and functionally related. Learning and/or task performance can induce modulation of the resting synchronization between brain regions. Moreover, at the neuronal level spontaneous brain activity can replay patterns evoked by a previously presented stimulus. Here we test whether visual learning/task performance can induce a change in the patterns of coded information in R-fMRI signals consistent with a role of spontaneous activity in representing task-relevant information. Human subjects underwent R-fMRI before and after perceptual learning on a novel visual shape orientation discrimination task. Task-evoked fMRI patterns to trained versus novel stimuli were recorded after learning was completed, and before the second R-fMRI session. Using multivariate pattern analysis on task-evoked signals, we found patterns in several cortical regions, as follows: visual cortex, V3/V3A/V7; within the default mode network, precuneus, and inferior parietal lobule; and, within the dorsal attention network, intraparietal sulcus, which discriminated between trained and novel visual stimuli. The accuracy of classification was strongly correlated with behavioral performance. Next, we measured multivariate patterns in R-fMRI signals before and after learning. The frequency and similarity of resting states representing the task/visual stimuli states increased post-learning in the same cortical regions recruited by the task. These findings support a representational role of spontaneous brain activity.
PMID: 26156982 [PubMed - in process]
Hyper-connectivity of the thalamus during early stages following mild traumatic brain injury.
Brain Imaging Behav. 2015 Jul 8;
Authors: Sours C, George EO, Zhuo J, Roys S, Gullapalli RP
The thalamo-cortical resting state functional connectivity of seven sub-thalamic regions were examined in a prospectively recruited population of 77 acute mild TBI (mTBI) patients within the first 10 days (mean 6 ± 3 days) of injury and 35 neurologically intact control subjects using the Oxford thalamic connectivity atlas. Neuropsychological assessments were conducted using the Automated Neuropsychological Assessment Metrics (ANAM). A subset of participants received a magentic resonance spectroscopy (MRS) exam to determine metabolite concentrations in the thalamus and the posterior cingulate cortex. Results show that patients performed worse than the control group on various subtests of ANAM and the weighted throughput score, suggesting reduced cognitive performance at this early stage of injury. Both voxel and region of interest based analysis of the resting state fMRI data demonstrated that acute mTBI patients have increased functional connectivity between the various sub-thalamic regions and cortical regions associated with sensory processing and the default mode network (DMN). In addition, a significant reduction in NAA/Cr was observed in the thalamus in the mTBI patients. Furthermore, an increase in Cho/Cr ratio specific to mTBI patients with self-reported sensory symptoms was observed compared to those without self-reported sensory symptoms. These results provide novel insights into the neural mechanisms of the brain state related to internal rumination and arousal, which have implications for new interventions for mTBI patients with persistent symptoms. Furthermore, an understanding of heightened sensitivity to sensory related inputs during early stages of injury may facilitate enhanced prediction of safe return to work.
PMID: 26153468 [PubMed - as supplied by publisher]
Randomization and resilience of brain functional networks as systems-level endophenotypes of schizophrenia.
Proc Natl Acad Sci U S A. 2015 Jul 6;
Authors: Lo CZ, Su TW, Huang CC, Hung CC, Chen WL, Lan TH, Lin CP, Bullmore ET
Schizophrenia is increasingly conceived as a disorder of brain network organization or dysconnectivity syndrome. Functional MRI (fMRI) networks in schizophrenia have been characterized by abnormally random topology. We tested the hypothesis that network randomization is an endophenotype of schizophrenia and therefore evident also in nonpsychotic relatives of patients. Head movement-corrected, resting-state fMRI data were acquired from 25 patients with schizophrenia, 25 first-degree relatives of patients, and 29 healthy volunteers. Graphs were used to model functional connectivity as a set of edges between regional nodes. We estimated the topological efficiency, clustering, degree distribution, resilience, and connection distance (in millimeters) of each functional network. The schizophrenic group demonstrated significant randomization of global network metrics (reduced clustering, greater efficiency), a shift in the degree distribution to a more homogeneous form (fewer hubs), a shift in the distance distribution (proportionally more long-distance edges), and greater resilience to targeted attack on network hubs. The networks of the relatives also demonstrated abnormal randomization and resilience compared with healthy volunteers, but they were typically less topologically abnormal than the patients' networks and did not have abnormal connection distances. We conclude that schizophrenia is associated with replicable and convergent evidence for functional network randomization, and a similar topological profile was evident also in nonpsychotic relatives, suggesting that this is a systems-level endophenotype or marker of familial risk. We speculate that the greater resilience of brain networks may confer some fitness advantages on nonpsychotic relatives that could explain persistence of this endophenotype in the population.
PMID: 26150519 [PubMed - as supplied by publisher]