Patanjali and neuroscientific research on meditation.
Front Psychol. 2015;6:915
Authors: Bærentsen KB
PMID: 26191024 [PubMed]
Brain activation induced by psychological stress in patients with schizophrenia.
Schizophr Res. 2015 Jul 16;
Authors: Castro MN, Villarreal MF, Bolotinsky N, Papávero E, Goldschmidt MG, Costanzo EY, Drucaroff L, Wainsztein A, de Achával D, Pahissa J, Bär KJ, Nemeroff CB, Guinjoan SM
Environmental influences are critical for the expression of genes putatively related to the behavioral and cognitive phenotypes of schizophrenia. Among such factors, psychosocial stress has been proposed to play a major role in the expression of symptoms. However, it is unsettled how stress interacts with pathophysiological pathways to produce the disease. We studied 21 patients with schizophrenia and 21 healthy controls aged 18 to 50years with 3T-fMRI, in which a period of 6min of resting state acquisition was followed by a block design, with three blocks of 1-min control-task, 1-min stress-task and 1-min rest after-task. Self-report of stress and PANSS were measured. Limbic structures were activated in schizophrenia patients by simple tasks and remained active during, and shortly after stress. In controls, stress-related brain activation was more time-focused, and restricted to the stressful task itself. Negative symptom severity was inversely related to activation of anterior cingulum and orbitofrontal cortex. Results might represent the neurobiological aspect of hyper-reactivity to normal stressful situations previously described in schizophrenia, thus providing evidence on the involvement of limbic areas in the response to stress in schizophrenia. Patients present a pattern of persistent limbic activation probably contributing to hypervigilance and subsequent psychotic thought distortions.
PMID: 26190301 [PubMed - as supplied by publisher]
Acute ketamine challenge increases resting state prefrontal-hippocampal connectivity in both humans and rats.
Psychopharmacology (Berl). 2015 Jul 18;
Authors: Grimm O, Gass N, Weber-Fahr W, Sartorius A, Schenker E, Spedding M, Risterucci C, Schweiger JI, Böhringer A, Zang Z, Tost H, Schwarz AJ, Meyer-Lindenberg A
RATIONALE: Aberrant prefrontal-hippocampal (PFC-HC) connectivity is disrupted in several psychiatric and at-risk conditions. Advances in rodent functional imaging have opened the possibility that this phenotype could serve as a translational imaging marker for psychiatric research. Recent evidence from functional magnetic resonance imaging (fMRI) studies has indicated an increase in PFC-HC coupling during working-memory tasks in both schizophrenic patients and at-risk populations, in contrast to a decrease in resting-state PFC-HC connectivity. Acute ketamine challenge is widely used in both humans and rats as a pharmacological model to study the mechanisms of N-methyl-D-aspartate (NMDA) receptor hypofunction in the context of psychiatric disorders.
OBJECTIVES: We aimed to establish whether acute ketamine challenge has consistent effects in rats and humans by investigating resting-state fMRI PFC-HC connectivity and thus to corroborate its potential utility as a translational probe.
METHODS: Twenty-four healthy human subjects (12 females, mean age 25 years) received intravenous doses of either saline (placebo) or ketamine (0.5 mg/kg body weight). Eighteen Sprague-Dawley male rats received either saline or ketamine (25 mg/kg). Resting-state fMRI measurements took place after injections, and the data were analyzed for PFC-HC functional connectivity.
RESULTS: In both species, ketamine induced a robust increase in PFC-HC coupling, in contrast to findings in chronic schizophrenia.
CONCLUSIONS: This translational comparison demonstrates a cross-species consistency in pharmacological effect and elucidates ketamine-induced alterations in PFC-HC coupling, a phenotype often disrupted in pathological conditions, which may give clue to understanding of psychiatric disorders and their onset, and help in the development of new treatments.
PMID: 26184011 [PubMed - as supplied by publisher]
Auditory resting-state functional connectivity in tinnitus and modulation with transcranial direct current stimulation.
Acta Otolaryngol. 2015 Jul 16;:1-7
Authors: Minami SB, Oishi N, Watabe T, Uno K, Kaga K, Ogawa K
CONCLUSIONS: The functional connectivity (FC) between the right and left auditory cortex is weak in tinnitus patients. Transcranial direct current stimulation (tDCS) over the auditory cortex has potential as a tool to modulate auditory-based FC.
OBJECTIVE: This study investigated the effects of applying tDCS in tinnitus patients, and searched for modulation of brain networks in resting-state functional magnetic resonance imaging (rs-fMRI) through an analysis of FC with the stimulated brain region.
SUBJECTS AND METHODS: Nine male patients with chronic tinnitus and 10 male volunteers with normal hearing were enrolled. The subjects were evaluated with rs-fMRI immediately before and after tDCS. The tinnitus patients filled out the self-evaluation questionnaires designed to measure tinnitus conditions before tDCS treatment and 1 week afterwards.
RESULTS: The FC between the right and left auditory cortex was significantly weaker in tinnitus patients than in controls. After tDCS treatment, in the tinnitus group, the primary auditory cortex showed a reduction in the amount of statistically significant connectivity with the somatosensory area and motor area, but maintained strong significant connectivity (p < 0.005) with the auditory area and insular cortex. In contrast, in the control group, there remained strong significant connectivity between the primary auditory cortex and the somatosensory area, motor area, insular cortex, and auditory area.
PMID: 26181225 [PubMed - as supplied by publisher]
Assessment of Functional Characteristics of Amnestic Mild Cognitive Impairment and Alzheimer's Disease Using Various Methods of Resting-State FMRI Analysis.
Biomed Res Int. 2015;2015:907464
Authors: Cha J, Hwang JM, Jo HJ, Seo SW, Na DL, Lee JM
Resting-state functional magnetic resonance imaging (RS FMRI) has been widely used to analyze functional alterations in amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD) patients. Although many clinical studies of aMCI and AD patients using RS FMRI have been undertaken, conducting a meta-analysis has not been easy because of seed selection bias by the investigators. The purpose of our study was to investigate the functional differences in aMCI and AD patients compared with healthy subjects in a meta-analysis. Thus, a multimethod approach using regional homogeneity, amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and global brain connectivity was used to investigate differences between three groups based on previously published data. According to the choice of RS FMRI approach used, the patterns of functional alteration were slightly different. Nevertheless, patients with aMCI and AD displayed consistently decreased functional characteristics with all approaches. All approaches showed that the functional characteristics in the left parahippocampal gyrus were decreased in AD patients compared with healthy subjects. Although some regions were slightly different according to the different RS FMRI approaches, patients with aMCI and AD showed a consistent pattern of decreased functional characteristics with all approaches.
PMID: 26180816 [PubMed - as supplied by publisher]
Diagnostic Prediction for Social Anxiety Disorder via Multivariate Pattern Analysis of the Regional Homogeneity.
Biomed Res Int. 2015;2015:763965
Authors: Zhang W, Yang X, Lui S, Meng Y, Yao L, Xiao Y, Deng W, Zhang W, Gong Q
Although decades of efforts have been spent studying the pathogenesis of social anxiety disorder (SAD), there are still no objective biological markers that could be reliably used to identify individuals with SAD. Studies using multivariate pattern analysis have shown the potential value in clinically diagnosing psychiatric disorders with neuroimaging data. We therefore examined the diagnostic potential of regional homogeneity (ReHo) underlying neural correlates of SAD using support vector machine (SVM), which has never been studied. Forty SAD patients and pairwise matched healthy controls were recruited and scanned by resting-state fMRI. The ReHo was calculated as synchronization of fMRI signals of nearest neighboring 27 voxels. A linear SVM was then adopted and allowed the classification of the two groups with diagnostic accuracy of ReHo that was 76.25% (sensitivity = 70%, and specificity = 82.5%, P ≤ 0.001). Regions showing different discriminating values between diagnostic groups were mainly located in default mode network, dorsal attention network, self-referential network, and sensory networks, while the left medial prefrontal cortex was identified with the highest weight. These results implicate that ReHo has good diagnostic potential in SAD, and thus may provide an initial step towards the possible use of whole brain local connectivity to inform the clinical evaluation.
PMID: 26180811 [PubMed - as supplied by publisher]
Decreased Resting-State Interhemispheric Functional Connectivity in Parkinson's Disease.
Biomed Res Int. 2015;2015:692684
Authors: Luo C, Guo X, Song W, Zhao B, Cao B, Yang J, Gong Q, Shang HF
Background. Abnormalities in white matter integrity and specific functional network alterations have been increasingly reported in patients with Parkinson's disease (PD). However, little is known about the inter-hemispheric interaction in PD. Methods. Fifty-one drug naive patients with PD and 51 age- and gender-matched healthy subjects underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans. We compared the inter-hemispheric resting-state functional connectivity between patients with PD and healthy controls, using the voxel-mirrored homotopic connectivity (VMHC) approach. Then, we correlated the results from VMHC and clinical features in PD patients. Results. Relative to healthy subject, patients exhibited significantly lower VMHC in putamen and cortical regions associated with sensory processing and motor control (involving sensorimotor and supramarginal cortex), which have been verified to play a critical role in PD. In addition, there were inverse relationships between the UPDRS motor scores and VMHC in the sensorimotor, and between the illness duration and VMHC in the supramarginal gyrus in PD patients. Conclusions. Our results suggest that the functional coordination between homotopic brain regions is impaired in PD patients, extending previous notions about the disconnection of corticostriatal circuit by providing new evidence supporting a disturbance in inter-hemispheric connections in PD.
PMID: 26180807 [PubMed - as supplied by publisher]
Connectome-Scale Assessments of Functional Connectivity in Children with Primary Monosymptomatic Nocturnal Enuresis.
Biomed Res Int. 2015;2015:463708
Authors: Lei D, Ma J, Zhang J, Wang M, Zhang K, Chen F, Suo X, Gong Q, Du X
Primary monosymptomatic nocturnal enuresis (PMNE) is a common developmental disorder in children. Previous literature has suggested that PMNE not only is a micturition disorder but also is characterized by cerebral structure abnormalities and dysfunction. However, the biological mechanisms underlying the disease are not thoroughly understood. Graph theoretical analysis has provided a unique tool to reveal the intrinsic attributes of the connectivity patterns of a complex network from a global perspective. Resting-state fMRI was performed in 20 children with PMNE and 20 healthy controls. Brain networks were constructed by computing Pearson's correlations for blood oxygenation level-dependent temporal fluctuations among the 2 groups, followed by graph-based network analyses. The functional brain networks in the PMNE patients were characterized by a significantly lower clustering coefficient, global and local efficiency, and higher characteristic path length compared with controls. PMNE patients also showed a reduced nodal efficiency in the bilateral calcarine sulcus, bilateral cuneus, bilateral lingual gyri, and right superior temporal gyrus. Our findings suggest that PMNE includes brain network alterations that may affect global communication and integration.
PMID: 26180801 [PubMed - as supplied by publisher]
Altered Synchronizations among Neural Networks in Geriatric Depression.
Biomed Res Int. 2015;2015:343720
Authors: Wang L, Chou YH, Potter GG, Steffens DC
Although major depression has been considered as a manifestation of discoordinated activity between affective and cognitive neural networks, only a few studies have examined the relationships among neural networks directly. Because of the known disconnection theory, geriatric depression could be a useful model in studying the interactions among different networks. In the present study, using independent component analysis to identify intrinsically connected neural networks, we investigated the alterations in synchronizations among neural networks in geriatric depression to better understand the underlying neural mechanisms. Resting-state fMRI data was collected from thirty-two patients with geriatric depression and thirty-two age-matched never-depressed controls. We compared the resting-state activities between the two groups in the default-mode, central executive, attention, salience, and affective networks as well as correlations among these networks. The depression group showed stronger activity than the controls in an affective network, specifically within the orbitofrontal region. However, unlike the never-depressed controls, geriatric depression group lacked synchronized/antisynchronized activity between the affective network and the other networks. Those depressed patients with lower executive function has greater synchronization between the salience network with the executive and affective networks. Our results demonstrate the effectiveness of the between-network analyses in examining neural models for geriatric depression.
PMID: 26180795 [PubMed - as supplied by publisher]
An fMRI Study of Local Synchronization in Different Subfrequency Bands during the Continuous Feedback of Finger Force.
Biomed Res Int. 2015;2015:273126
Authors: Zhang H, Gao ZZ, Zang YF
Conventional functional magnetic resonance imaging (fMRI) studies on motor feedback employ periodical blocked paradigm which does not allow frequency analysis of brain activity. Here, we carried out an fMRI study by using a continuous paradigm, that is, continuous (8 min) feedback of finger force. Borrowing an analytic method widely used in resting-state fMRI studies, that is, regional homogeneity (ReHo), we compared the local synchronization in some subfrequency bands between real and sham feedback, and the subbands were defined as Slow-6 (0.0-0.01 Hz), Slow-5 (0.01-0.027 Hz), Slow-4 (0.027-0.073 Hz), Slow-3 (0.073-0.198 Hz), and Slow-2 (0.198-0.25 Hz). Our results revealed that the five subfrequency bands of brain activity contributed to the changes of ReHo between real and sham feedback differently, and, more importantly, the changes in basal ganglia were only manifested in Slow-6, implicating the fact that ReHo in ultraslow band may be associated with the functional significance of BG, that is, motor control. These findings provide novel insights into the neural substrate underlying motor feedback, and properties of the ultraslow band of local synchronization deserve more attention in future explorations.
PMID: 26180789 [PubMed - as supplied by publisher]
Cerebral Activity Changes in Different Traditional Chinese Medicine Patterns of Psychogenic Erectile Dysfunction Patients.
Evid Based Complement Alternat Med. 2015;2015:503536
Authors: Liu Q, Zhang P, Pan J, Li Z, Liu J, Li G, Qin W, You Y, Yu X, Sun J, Dong M, Gong Q, Guo J, Chang D
Background. Pattern differentiation is the foundation of traditional Chinese medicine (TCM) treatment for erectile dysfunction (ED). This study aims to investigate the differences in cerebral activity in ED patients with different TCM patterns. Methods. 27 psychogenic ED patients and 27 healthy subjects (HS) were enrolled in this study. Each participant underwent an fMRI scan in resting state. The fractional amplitude of low-frequency fluctuation (fALFF) was used to detect the brain activity changes in ED patients with different patterns. Results. Compared to HS, ED patients showed an increased cerebral activity in bilateral cerebellum, insula, globus pallidus, parahippocampal gyrus, orbitofrontal cortex (OFC), and middle cingulate cortex (MCC). Compared to the patients with liver-qi stagnation and spleen deficiency pattern (LSSDP), the patients with kidney-yang deficiency pattern (KDP) showed an increased activity in bilateral brainstem, cerebellum, hippocampus, and the right insula, thalamus, MCC, and a decreased activity in bilateral putamen, medial frontal gyrus, temporal pole, and the right caudate nucleus, OFC, anterior cingulate cortex, and posterior cingulate cortex (P < 0.005). Conclusions. The ED patients with different TCM patterns showed different brain activities. The differences in cerebral activity between LSSDP and KDP were mainly in the emotion-related regions, including prefrontal cortex and cingulated cortex.
PMID: 26180534 [PubMed]
Resting state connectivity of the bed nucleus of the stria terminalis at ultra-high field.
Hum Brain Mapp. 2015 Jul 14;
Authors: Torrisi S, O'Connell K, Davis A, Reynolds R, Balderston N, Fudge J, Grillon C, Ernst M
The bed nucleus of the stria terminalis (BNST), a portion of the "extended amygdala," is implicated in the pathophysiology of anxiety and addiction disorders. Its small size and connection to other small regions prevents standard imaging techniques from easily capturing it and its connectivity with confidence. Seed-based resting state functional connectivity is an established method for mapping functional connections across the brain from a region of interest. We, therefore, mapped the BNST resting state network with high spatial resolution using 7 Tesla fMRI, demonstrating the in vivo reproduction of many human BNST connections previously described only in animal research. We identify strong BNST functional connectivity in amygdala, hippocampus and thalamic subregions, caudate, periaqueductal gray, hypothalamus, and cortical areas such as the medial PFC and precuneus. This work, which demonstrates the power of ultra-high field for mapping functional connections in the human, is an important step toward elucidating cortical and subcortical regions and subregions of the BNST network. Hum Brain Mapp, 2015. © 2015 Wiley Periodicals, Inc.
PMID: 26178381 [PubMed - as supplied by publisher]
Comparison of continuously acquired resting state and extracted analogues from active tasks.
Hum Brain Mapp. 2015 Jul 15;
Authors: Ganger S, Hahn A, Küblböck M, Kranz GS, Spies M, Vanicek T, Seiger R, Sladky R, Windischberger C, Kasper S, Lanzenberger R
Functional connectivity analysis of brain networks has become an important tool for investigation of human brain function. Although functional connectivity computations are usually based on resting-state data, the application to task-specific fMRI has received growing attention. Three major methods for extraction of resting-state data from task-related signal have been proposed (1) usage of unmanipulated task data for functional connectivity; (2) regression against task effects, subsequently using the residuals; and (3) concatenation of baseline blocks located in-between task blocks. Despite widespread application in current research, consensus on which method best resembles resting-state seems to be missing. We, therefore, evaluated these techniques in a sample of 26 healthy controls measured at 7 Tesla. In addition to continuous resting-state, two different task paradigms were assessed (emotion discrimination and right finger-tapping) and five well-described networks were analyzed (default mode, thalamus, cuneus, sensorimotor, and auditory). Investigating the similarity to continuous resting-state (Dice, Intraclass correlation coefficient (ICC), R(2) ) showed that regression against task effects yields functional connectivity networks most alike to resting-state. However, all methods exhibited significant differences when compared to continuous resting-state and similarity metrics were lower than test-retest of two resting-state scans. Omitting global signal regression did not change these findings. Visually, the networks are highly similar, but through further investigation marked differences can be found. Therefore, our data does not support referring to resting-state when extracting signals from task designs, although functional connectivity computed from task-specific data may indeed yield interesting information. Hum Brain Mapp, 2015. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
PMID: 26178250 [PubMed - as supplied by publisher]
Transient brain activity disentangles fMRI resting-state dynamics in terms of spatially and temporally overlapping networks.
Nat Commun. 2015;6:7751
Authors: Karahanoğlu FI, Van De Ville D
Dynamics of resting-state functional magnetic resonance imaging (fMRI) provide a new window onto the organizational principles of brain function. Using state-of-the-art signal processing techniques, we extract innovation-driven co-activation patterns (iCAPs) from resting-state fMRI. The iCAPs' maps are spatially overlapping and their sustained-activity signals temporally overlapping. Decomposing resting-state fMRI using iCAPs reveals the rich spatiotemporal structure of functional components that dynamically assemble known resting-state networks. The temporal overlap between iCAPs is substantial; typically, three to four iCAPs occur simultaneously in combinations that are consistent with their behaviour profiles. In contrast to conventional connectivity analysis, which suggests a negative correlation between fluctuations in the default-mode network (DMN) and task-positive networks, we instead find evidence for two DMN-related iCAPs consisting the posterior cingulate cortex that differentially interact with the attention network. These findings demonstrate how the fMRI resting state can be functionally decomposed into spatially and temporally overlapping building blocks using iCAPs.
PMID: 26178017 [PubMed - as supplied by publisher]
GRETNA: a graph theoretical network analysis toolbox for imaging connectomics.
Front Hum Neurosci. 2015;9:386
Authors: Wang J, Wang X, Xia M, Liao X, Evans A, He Y
Recent studies have suggested that the brain's structural and functional networks (i.e., connectomics) can be constructed by various imaging technologies (e.g., EEG/MEG; structural, diffusion and functional MRI) and further characterized by graph theory. Given the huge complexity of network construction, analysis and statistics, toolboxes incorporating these functions are largely lacking. Here, we developed the GRaph thEoreTical Network Analysis (GRETNA) toolbox for imaging connectomics. The GRETNA contains several key features as follows: (i) an open-source, Matlab-based, cross-platform (Windows and UNIX OS) package with a graphical user interface (GUI); (ii) allowing topological analyses of global and local network properties with parallel computing ability, independent of imaging modality and species; (iii) providing flexible manipulations in several key steps during network construction and analysis, which include network node definition, network connectivity processing, network type selection and choice of thresholding procedure; (iv) allowing statistical comparisons of global, nodal and connectional network metrics and assessments of relationship between these network metrics and clinical or behavioral variables of interest; and (v) including functionality in image preprocessing and network construction based on resting-state functional MRI (R-fMRI) data. After applying the GRETNA to a publicly released R-fMRI dataset of 54 healthy young adults, we demonstrated that human brain functional networks exhibit efficient small-world, assortative, hierarchical and modular organizations and possess highly connected hubs and that these findings are robust against different analytical strategies. With these efforts, we anticipate that GRETNA will accelerate imaging connectomics in an easy, quick and flexible manner. GRETNA is freely available on the NITRC website.
PMID: 26175682 [PubMed - as supplied by publisher]
Increased connectivity between sensorimotor and attentional areas in Parkinson's disease.
Neuroradiology. 2015 Jul 15;
Authors: Onu M, Badea L, Roceanu A, Tivarus M, Bajenaru O
INTRODUCTION: Our study is using Independent Component Analysis (ICA) to evaluate functional connectivity changes in Parkinson's disease (PD) in an unbiased manner.
METHODS: Resting-state functional magnetic resonance imaging (rs-fMRI) data was collected for 27 PD patients and 16 healthy subjects. Differences for intra- and inter-network connectivity between healthy subjects and patients were investigated using FMRIB Software Library (FSL) tools (Melodic ICA, dual regression, FSLNets).
RESULTS: Twenty-three ICA maps were identified as components of neuronal origin. For intra-network connectivity changes, eight components showed a significant connectivity increase in patients (p < 0.05); these were correlated with clinical scores and were largest for (sensori)motor networks. For inter-network connectivity changes, we found higher connectivity between the sensorimotor network and the spatial attention network (p = 0.0098) and lower connectivity between anterior and posterior default mode networks (DMN) (p = 0.024), anterior DMN and visual recognition networks (p = 0.026), as well as between visual attention and main dorsal attention networks (p = 0.03), for patients as compared to healthy subjects. The area under the Receiver Operating Characteristics (ROC) curve for the best predictor (partial correlation between sensorimotor and spatial attention networks) was 0.772. These functional alterations were not associated with any gray or white matter structural changes.
CONCLUSION: Our results show higher connectivity between sensorimotor and spatial attention areas in patients that may be related to the reduced movement automaticity in PD.
PMID: 26174425 [PubMed - as supplied by publisher]
Vascular coupling in resting-state fMRI: evidence from multiple modalities.
J Cereb Blood Flow Metab. 2015 Jul 15;
Authors: Zhu DC, Tarumi T, Khan MA, Zhang R
Resting-state functional magnetic resonance imaging (rs-fMRI) provides a potential to understand intrinsic brain functional connectivity. However, vascular effects in rs-fMRI are still not fully understood. Through multiple modalities, we showed marked vascular signal fluctuations and high-level coupling among arterial pressure, cerebral blood flow (CBF) velocity and brain tissue oxygenation at <0.08 Hz. These similar spectral power distributions were also observed in blood oxygen level-dependent (BOLD) signals obtained from six representative regions of interest (ROIs). After applying brain global, white-matter, cerebrospinal fluid (CSF) mean signal regressions and low-pass filtering (<0.08 Hz), the spectral power of BOLD signal was reduced by 55.6% to 64.9% in all ROIs (P=0.011 to 0.001). The coherence of BOLD signal fluctuations between an ROI pair within a same brain network was reduced by 9.9% to 20.0% (P=0.004 to <0.001), but a larger reduction of 22.5% to 37.3% (P=0.032 to <0.001) for one not in a same network. Global signal regression overall had the largest impact in reducing spectral power (by 52.2% to 61.7%) and coherence, relative to the other three preprocessing steps. Collectively, these findings raise a critical question of whether a large portion of rs-fMRI signals can be attributed to the vascular effects produced from upstream changes in cerebral hemodynamics.Journal of Cerebral Blood Flow & Metabolism advance online publication, 15 July 2015; doi:10.1038/jcbfm.2015.166.
PMID: 26174326 [PubMed - as supplied by publisher]
Intrinsic brain activity as a diagnostic biomarker in children with benign epilepsy with centrotemporal spikes.
Hum Brain Mapp. 2015 Jul 14;
Authors: Zhu Y, Yu Y, Shinkareva SV, Ji GJ, Wang J, Wang ZJ, Zang YF, Liao W, Tang YL
Benign epilepsy with centrotemporal spikes (BECTS) is often associated with neural circuit dysfunction, particularly during the transient active state characterized by interictal epileptiform discharges (IEDs). Little is known, however, about the functional neural circuit abnormalities in BECTS without IEDs, or if such abnormalities could be used to differentiate BECTS patients without IEDs from healthy controls (HCs) for early diagnosis. To this end, we conducted resting-state functional magnetic resonance imaging (RS-fMRI) and simultaneous Electroencephalogram (EEG) in children with BECTS (n = 43) and age-matched HC (n = 28). The simultaneous EEG recordings distinguished BECTS with IEDs (n = 20) from without IEDs (n = 23). Intrinsic brain activity was measured in all three groups using the amplitude of low frequency fluctuation at rest. Compared to HC, BECTS patients with IEDs exhibited an intrinsic activity abnormality in the thalamus, suggesting that thalamic dysfunction could contribute to IED emergence while patients without IEDs exhibited intrinsic activity abnormalities in middle frontal gyrus and superior parietal gyrus. Using multivariate pattern classification analysis, we were able to differentiate BECTS without IEDs from HCs with 88.23% accuracy. BECTS without epileptic transients can be distinguished from HC and BECTS with IEDs by unique regional abnormalities in resting brain activity. Both transient abnormalities as reflected by IEDs and chronic abnormalities as reflected by RS-fMRI may contribute to BECTS development and expression. Intrinsic brain activity and multivariate pattern classification techniques are promising tools to diagnose and differentiate BECTS syndromes. Hum Brain Mapp, 2015. © 2015 Wiley Periodicals, Inc.
PMID: 26173095 [PubMed - as supplied by publisher]
Toward a Meta-Analytic Synthesis of the Resting-State fMRI Literature for Clinical Populations.
Biomed Res Int. 2015;2015:435265
Authors: Zang YF, Zuo XN, Milham M, Hallett M
PMID: 26171391 [PubMed - in process]
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]