Most recent paper

Syndicate content NCBI pubmed
NCBI: db=pubmed; Term="resting"[All Fields] AND "fMRI"[All Fields]
Updated: 8 min 30 sec ago

Resting State BOLD Functional Connectivity at 3T: Spin Echo versus Gradient Echo EPI.

Wed, 03/11/2015 - 13:30
Related Articles

Resting State BOLD Functional Connectivity at 3T: Spin Echo versus Gradient Echo EPI.

PLoS One. 2015;10(3):e0120398

Authors: Chiacchiaretta P, Ferretti A

Abstract
Previous evidence showed that, due to refocusing of static dephasing effects around large vessels, spin-echo (SE) BOLD signals offer an increased linearity and promptness with respect to gradient-echo (GE) acquisition, even at low field. These characteristics suggest that, despite the reduced sensitivity, SE fMRI might also provide a potential benefit when investigating spontaneous fluctuations of brain activity. However, there are no reports on the application of spin-echo fMRI for connectivity studies at low field. In this study we compared resting state functional connectivity as measured with GE and SE EPI sequences at 3T. Main results showed that, within subject, the GE sensitivity is overall larger with respect to that of SE, but to a less extent than previously reported for activation studies. Noteworthy, the reduced sensitivity of SE was counterbalanced by a reduced inter-subject variability, resulting in comparable group statistical connectivity maps for the two sequences. Furthermore, the SE method performed better in the ventral portion of the default mode network, a region affected by signal dropout in standard GE acquisition. Future studies should clarify if these features of the SE BOLD signal can be beneficial to distinguish subtle variations of functional connectivity across different populations and/or treatments when vascular confounds or regions affected by signal dropout can be a critical issue.

PMID: 25749359 [PubMed - in process]

The selective impairment of resting-state functional connectivity of the lateral subregion of the frontal pole in schizophrenia.

Wed, 03/11/2015 - 13:30
Related Articles

The selective impairment of resting-state functional connectivity of the lateral subregion of the frontal pole in schizophrenia.

PLoS One. 2015;10(3):e0119176

Authors: Zhou Y, Ma X, Wang D, Qin W, Zhu J, Zhuo C, Yu C

Abstract
OBJECTIVE: Although extensive resting-state functional connectivity (rsFC) changes have been reported in schizophrenia, rsFC changes of the frontal pole (FP) remain unclear. The FP contains several subregions with different connection patterns; however, it is unknown whether the FP subregions are differentially affected in schizophrenia. To explore this possibility, we compared rsFC differences of the FP subregions between schizophrenia patients and healthy controls.
METHOD: One hundred healthy controls and 91 patients with schizophrenia underwent resting-state functional MRI with a sensitivity-encoded spiral-in (SENSE-SPIRAL) imaging sequence to reduced susceptibility-induced signal loss and distortion. The FP was subdivided into the orbital (FPo), medial (FPm), and lateral (FPl) subregions. Mean fMRI time series were extracted for each FP subregion and entered into a seed-based rsFC analysis.
RESULTS: The FP subregions exhibited differential rsFC patterns in both healthy controls and schizophrenia patients. Direct comparison between groups revealed reduced rsFCs between the bilateral FPl and several cognitive-related regions, including the dorsolateral prefrontal cortex, medial prefrontal cortex, anterior cingulate cortex, posterior cingulate cortex/precuneus, temporal cortex and inferior parietal lobule in schizophrenia. Although the FPl exhibited obvious atrophy, rsFC changes were unrelated to volumetric atrophy in the FPl, to duration of illness, and to antipsychotic medication dosage. No significant differences were observed in the rsFCs of other FP subregions.
CONCLUSION: These findings suggest a selective (the lateral subregion) functional disconnection of the FP subregions in schizophrenia.

PMID: 25748858 [PubMed - in process]

Combined noninvasive language mapping by navigated transcranial magnetic stimulation and functional MRI and its comparison with direct cortical stimulation.

Wed, 03/11/2015 - 13:30
Related Articles

Combined noninvasive language mapping by navigated transcranial magnetic stimulation and functional MRI and its comparison with direct cortical stimulation.

J Neurosurg. 2015 Mar 6;:1-14

Authors: Ille S, Sollmann N, Hauck T, Maurer S, Tanigawa N, Obermueller T, Negwer C, Droese D, Zimmer C, Meyer B, Ringel F, Krieg SM

Abstract
OBJECT Repetitive navigated transcranial magnetic stimulation (rTMS) is now increasingly used for preoperative language mapping in patients with lesions in language-related areas of the brain. Yet its correlation with intraoperative direct cortical stimulation (DCS) has to be improved. To increase rTMS's specificity and positive predictive value, the authors aim to provide thresholds for rTMS's positive language areas. Moreover, they propose a protocol for combining rTMS with functional MRI (fMRI) to combine the strength of both methods. METHODS The authors performed multimodal language mapping in 35 patients with left-sided perisylvian lesions by using rTMS, fMRI, and DCS. The rTMS mappings were conducted with a picture-to-trigger interval (PTI, time between stimulus presentation and stimulation onset) of either 0 or 300 msec. The error rates (ERs; that is, the number of errors per number of stimulations) were calculated for each region of the cortical parcellation system (CPS). Subsequently, the rTMS mappings were analyzed through different error rate thresholds (ERT; that is, the ER at which a CPS region was defined as language positive in terms of rTMS), and the 2-out-of-3 rule (a stimulation site was defined as language positive in terms of rTMS if at least 2 out of 3 stimulations caused an error). As a second step, the authors combined the results of fMRI and rTMS in a predefined protocol of combined noninvasive mapping. To validate this noninvasive protocol, they correlated its results to DCS during awake surgery. RESULTS The analysis by different rTMS ERTs obtained the highest correlation regarding sensitivity and a low rate of false positives for the ERTs of 15%, 20%, 25%, and the 2-out-of-3 rule. However, when comparing the combined fMRI and rTMS results with DCS, the authors observed an overall specificity of 83%, a positive predictive value of 51%, a sensitivity of 98%, and a negative predictive value of 95%. CONCLUSIONS In comparison with fMRI, rTMS is a more sensitive but less specific tool for preoperative language mapping than DCS. Moreover, rTMS is most reliable when using ERTs of 15%, 20%, 25%, or the 2-out-of-3 rule and a PTI of 0 msec. Furthermore, the combination of fMRI and rTMS leads to a higher correlation to DCS than both techniques alone, and the presented protocols for combined noninvasive language mapping might play a supportive role in the language-mapping assessment prior to the gold-standard intraoperative DCS.

PMID: 25748306 [PubMed - as supplied by publisher]

Dissociation of anatomical and functional alterations of the default-mode network in first-episode, drug-naive schizophrenia.

Wed, 03/11/2015 - 13:30
Related Articles

Dissociation of anatomical and functional alterations of the default-mode network in first-episode, drug-naive schizophrenia.

Clin Neurophysiol. 2015 Feb 16;

Authors: Guo W, Liu F, Xiao C, Zhang Z, Yu M, Liu J, Liu G, Zhao J

Abstract
OBJECTIVE: Anatomical and functional alterations of the default-mode network (DMN) have been implicated in the pathophysiology of schizophrenia. However, no study is engaged to explore whether structural and functional abnormalities of the DMN overlap in schizophrenia. This study was undertaken to examine whether anatomical and functional abnormalities are present in similar or different brain regions of the DMN in first-episode, drug-naive schizophrenia.
METHODS: Forty-nine first-episode, drug-naive schizophrenia patients and 50 age-, sex-, and education-matched healthy controls underwent structural and resting-state functional magnetic resonance imaging (fMRI) scanning. The voxel-based morphometry (VBM) and fractional amplitude of low-frequency fluctuation (fALFF) methods were used to analyze imaging data.
RESULTS: The patients exhibited significantly decreased gray matter volume (GMV) in the left medial prefrontal cortex (orbital part) and increased fALFF in the left posterior cingulate cortex compared with the controls. No overlap of brain regions with anatomical and functional abnormalities was observed in the patient group. There was also no correlation between decreased GMV/increased fALFF and clinical variables in patients.
CONCLUSIONS: A dissociation pattern of brain regions with anatomical and functional changes within the DMN is revealed in schizophrenia patients.
SIGNIFICANCE: Our findings suggest that brain functional and anatomical abnormalities within the DMN might contribute independently to the pathophysiology of schizophrenia.

PMID: 25746945 [PubMed - as supplied by publisher]

Abnormal coactivation of the hypothalamus and salience network in patients with cluster headache.

Wed, 03/11/2015 - 13:30
Related Articles

Abnormal coactivation of the hypothalamus and salience network in patients with cluster headache.

Neurology. 2015 Mar 6;

Authors: Qiu E, Tian L, Wang Y, Ma L, Yu S

Abstract
OBJECTIVE: The purpose of this study was to investigate whether the resting-state coactivation of the hypothalamus, both ipsilateral and contralateral to the headache side, and the salience network (SN) was altered in patients with cluster headache (CH) in the headache attack remission state in the cluster period, and to reveal possible pathogenesis of CH attacks and gain further insight into the pathophysiology of CH.
METHODS: Resting-state fMRI scans of 21 patients with CH were obtained (13 with right-sided headache and 8 with left-sided headache) and 21 age- and sex-matched normal controls. The resting-state fMRI data were analyzed using independent component analysis to identify the group differences of hypothalamic-SN coactivation between the patients with CH and healthy controls.
RESULTS: Decreased functional coactivation was detected between the hypothalamus, both ipsilateral and contralateral to the headache side, and the SN both in patients with right-sided CH and in those with left-sided CH.
CONCLUSION: Our findings suggest that the decreased hypothalamus-SN coactivation may have a role in CH attacks by the defective central pathway of pain control and autonomic nervous system dysregulation. This helps to gain additional insight into the pathophysiologic basis of CH and the nature of the brain dysfunction in CH.

PMID: 25746559 [PubMed - as supplied by publisher]

Bipolar and borderline patients display differential patterns of functional connectivity among resting state networks.

Wed, 03/11/2015 - 13:30
Related Articles

Bipolar and borderline patients display differential patterns of functional connectivity among resting state networks.

Neuroimage. 2014 Sep;98:73-81

Authors: Das P, Calhoun V, Malhi GS

Abstract
Bipolar disorder (BD) and borderline personality (BPD) disorder share clinical features such as emotional lability and poor interpersonal functioning but the course of illness and treatment differs in these groups, which suggests that the underlying neurobiology of BD and BPD is likely to be different. Understanding the neural mechanisms behind the pathophysiology of BD and BPD will facilitate accurate diagnosis and inform the administration of targeted treatment. Since deficits in social cognition or emotion regulation or in the self-referential processing system can give rise to these clinical features, and impairment in these domains have been observed in both patient groups, functional connectivity within and between networks subserving these processes during resting was investigated using functional magnetic resonance imaging. Data were acquired from 16 patients with BD, 14 patients with BPD, and 13 healthy controls (HC) and functional connectivity strength was correlated with scores using the Difficulties in Emotion Regulation Scale. Functional network connectivity (FNC) patterns differentiated BD and BPD patients from HC. In BD, FNC was increased while in BPD it was decreased. In BD impaired FNC was evident primarily among networks involved in self-referential processing while in BPD it also involved the emotion regulatory network. Impaired FNC displayed an association with impulsivity in BPD and emotional clarity and emotional awareness in BD. This study shows that BD and BPD can perhaps be differentiated using resting state FNC approach and that the neural mechanisms underpinning overlapping symptoms discernibly differ between the groups. These findings provide a potential platform for elucidating the targeted effects of psychological interventions in both disorders.

PMID: 24793833 [PubMed - indexed for MEDLINE]

Directionality of large-scale resting-state brain networks during eyes open and eyes closed conditions.

Wed, 03/11/2015 - 13:30
Related Articles

Directionality of large-scale resting-state brain networks during eyes open and eyes closed conditions.

Front Hum Neurosci. 2015;9:81

Authors: Zhang D, Liang B, Wu X, Wang Z, Xu P, Chang S, Liu B, Liu M, Huang R

Abstract
The present study examined directional connections in the brain among resting-state networks (RSNs) when the participant had their eyes open (EO) or had their eyes closed (EC). The resting-state fMRI data were collected from 20 healthy participants (9 males, 20.17 ± 2.74 years) under the EO and EC states. Independent component analysis (ICA) was applied to identify the separated RSNs (i.e., the primary/high-level visual, primary sensory-motor, ventral motor, salience/dorsal attention, and anterior/posterior default-mode networks), and the Gaussian Bayesian network (BN) learning approach was then used to explore the conditional dependencies among these RSNs. The network-to-network directional connections related to EO and EC were depicted, and a support vector machine (SVM) was further employed to identify the directional connection patterns that could effectively discriminate between the two states. The results indicated that the connections among RSNs are directionally connected within a BN during the EO and EC states. The directional connections from the salience network (SN) to the anterior/posterior default-mode networks and the high-level to primary-level visual network were the obvious characteristics of both the EO and EC resting-state BNs. Of the directional connections in BN, the directional connections of the salience and dorsal attention network (DAN) were observed to be discriminative between the EO and EC states. In particular, we noted that the properties of the salience and DANs were in opposite directions. Overall, the present study described the directional connections of RSNs using a BN learning approach during the EO and EC states, and the results suggested that the directionality of the attention systems (i.e., mainly for the salience and the DAN) in resting state might have important roles in switching between the EO and EC conditions.

PMID: 25745394 [PubMed]

Evaluating the reliability of different preprocessing steps to estimate graph theoretical measures in resting state fMRI data.

Wed, 03/11/2015 - 13:30
Related Articles

Evaluating the reliability of different preprocessing steps to estimate graph theoretical measures in resting state fMRI data.

Front Neurosci. 2015;9:48

Authors: Aurich NK, Alves Filho JO, Marques da Silva AM, Franco AR

Abstract
With resting-state functional MRI (rs-fMRI) there are a variety of post-processing methods that can be used to quantify the human brain connectome. However, there is also a choice of which preprocessing steps will be used prior to calculating the functional connectivity of the brain. In this manuscript, we have tested seven different preprocessing schemes and assessed the reliability between and reproducibility within the various strategies by means of graph theoretical measures. Different preprocessing schemes were tested on a publicly available dataset, which includes rs-fMRI data of healthy controls. The brain was parcellated into 190 nodes and four graph theoretical (GT) measures were calculated; global efficiency (GEFF), characteristic path length (CPL), average clustering coefficient (ACC), and average local efficiency (ALE). Our findings indicate that results can significantly differ based on which preprocessing steps are selected. We also found dependence between motion and GT measurements in most preprocessing strategies. We conclude that by using censoring based on outliers within the functional time-series as a processing, results indicate an increase in reliability of GT measurements with a reduction of the dependency of head motion.

PMID: 25745384 [PubMed]

Hubs of Anti-correlation in High-Resolution Resting State Functional Connectivity Network Architecture.

Wed, 03/11/2015 - 00:30

Hubs of Anti-correlation in High-Resolution Resting State Functional Connectivity Network Architecture.

Brain Connect. 2015 Mar 6;

Authors: Gopinath K, Krishnamurthy V, Cabanban R, Crosson B

Abstract
A major focus of the brain research recently has been to map the resting state functional connectivity (rsFC) network architecture of the normal brain and pathology through functional magnetic resonance imaging. However the phenomenon of anti-correlations in resting state signal between different brain regions has not been adequately examined. The preponderance of studies on resting state fMRI (rsFMRI) have either ignored anti-correlations in rsFC networks, or adopted methods in data analysis which have rendered anti-correlations in rsFC networks uninterpretable. The few studies that have examined anti-correlations in rsFC networks using conventional methods, have found anti-correlations to be weak in strength and not vey reproducible across subjects. Anti-correlations in rsFC network architecture could reflect mechanisms that subserve a number of important brain processes. In this preliminary study we examined the properties of anti-correlated rsFC networks by systematically focusing on negative cross-correlation coefficients (CCs) between rsFMRI voxel time-series across the brain with graph theory based network analysis. A number of innovations were implemented to enhance the neuronal specificity of resting state functional connections that yield negative CCs albeit at the cost of decreased sensitivity. Hubs of anti-correlation were seen in a number of cortical and sub-cortical brain regions. Examination of the anti-correlation maps of these hubs indicated that negative CCs in rsFC network architecture highlight a number of regulatory interactions between brain networks and regions including reciprocal modulations, suppression, inhibition and neurofeedback.

PMID: 25744222 [PubMed - as supplied by publisher]

Efficiency of weak brain connections support general cognitive functioning.

Wed, 03/11/2015 - 00:30
Related Articles

Efficiency of weak brain connections support general cognitive functioning.

Hum Brain Mapp. 2014 Sep;35(9):4566-82

Authors: Santarnecchi E, Galli G, Polizzotto NR, Rossi A, Rossi S

Abstract
Brain network topology provides valuable information on healthy and pathological brain functioning. Novel approaches for brain network analysis have shown an association between topological properties and cognitive functioning. Under the assumption that "stronger is better", the exploration of brain properties has generally focused on the connectivity patterns of the most strongly correlated regions, whereas the role of weaker brain connections has remained obscure for years. Here, we assessed whether the different strength of connections between brain regions may explain individual differences in intelligence. We analyzed-functional connectivity at rest in ninety-eight healthy individuals of different age, and correlated several connectivity measures with full scale, verbal, and performance Intelligent Quotients (IQs). Our results showed that the variance in IQ levels was mostly explained by the distributed communication efficiency of brain networks built using moderately weak, long-distance connections, with only a smaller contribution of stronger connections. The variability in individual IQs was associated with the global efficiency of a pool of regions in the prefrontal lobes, hippocampus, temporal pole, and postcentral gyrus. These findings challenge the traditional view of a prominent role of strong functional brain connections in brain topology, and highlight the importance of both strong and weak connections in determining the functional architecture responsible for human intelligence variability.

PMID: 24585433 [PubMed - indexed for MEDLINE]

Differential cerebral response to somatosensory stimulation of an acupuncture point vs. two non-acupuncture points measured with EEG and fMRI.

Sat, 03/07/2015 - 13:00

Differential cerebral response to somatosensory stimulation of an acupuncture point vs. two non-acupuncture points measured with EEG and fMRI.

Front Hum Neurosci. 2015;9:74

Authors: Nierhaus T, Pach D, Huang W, Long X, Napadow V, Roll S, Liang F, Pleger B, Villringer A, Witt CM

Abstract
Acupuncture can be regarded as a complex somatosensory stimulation. Here, we evaluate whether the point locations chosen for a somatosensory stimulation with acupuncture needles differently change the brain activity in healthy volunteers. We used EEG, event-related fMRI, and resting-state functional connectivity fMRI to assess neural responses to standardized needle stimulation of the acupuncture point ST36 (lower leg) and two control point locations (CP1 same dermatome, CP2 different dermatome). Cerebral responses were expected to differ for stimulation in two different dermatomes (CP2 different from ST36 and CP1), or stimulation at the acupuncture point vs. the control points. For EEG, mu rhythm power increased for ST36 compared to CP1 or CP2, but not when comparing the two control points. The fMRI analysis found more pronounced insula and S2 (secondary somatosensory cortex) activation, as well as precuneus deactivation during ST36 stimulation. The S2 seed-based functional connectivity analysis revealed increased connectivity to right precuneus for both comparisons, ST36 vs. CP1 and ST36 vs. CP2, however in different regions. Our results suggest that stimulation at acupuncture points may modulate somatosensory and saliency processing regions more readily than stimulation at non-acupuncture point locations. Also, our findings suggest potential modulation of pain perception due to acupuncture stimulation.

PMID: 25741269 [PubMed - as supplied by publisher]

Converging Structural and Functional Connectivity of Orbitofrontal, Dorsolateral Prefrontal, and Posterior Parietal Cortex in the Human Striatum.

Sat, 03/07/2015 - 13:00

Converging Structural and Functional Connectivity of Orbitofrontal, Dorsolateral Prefrontal, and Posterior Parietal Cortex in the Human Striatum.

J Neurosci. 2015 Mar 4;35(9):3865-3878

Authors: Jarbo K, Verstynen TD

Abstract
Modification of spatial attention via reinforcement learning (Lee and Shomstein, 2013) requires the integration of reward, attention, and executive processes. Corticostriatal pathways are an ideal neural substrate for this integration because these projections exhibit a globally parallel (Alexander et al., 1986), but locally overlapping (Haber, 2003), topographical organization. Here we explore whether there are unique striatal regions that exhibit convergent anatomical connections from orbitofrontal cortex, dorsolateral prefrontal cortex, and posterior parietal cortex. Deterministic fiber tractography on diffusion spectrum imaging data from neurologically healthy adults (N = 60) was used to map frontostriatal and parietostriatal projections. In general, projections from cortex were organized according to both a medial-lateral and a rostral-caudal gradient along the striatal nuclei. Within rostral aspects of the striatum, we identified two bilateral convergence zones (one in the caudate nucleus and another in the putamen) that consisted of voxels with unique projections from orbitofrontal cortex, dorsolateral prefrontal cortex, and parietal regions. The distributed cortical connectivity of these striatal convergence zones was confirmed with follow-up functional connectivity analysis from resting state fMRI data, in which a high percentage of structurally connected voxels also showed significant functional connectivity. The specificity of this convergent architecture to these regions of the rostral striatum was validated against control analysis of connectivity within the motor putamen. These results delineate a neurologically plausible network of converging corticostriatal projections that may support the integration of reward, executive control, and spatial attention that occurs during spatial reinforcement learning.

PMID: 25740516 [PubMed - as supplied by publisher]

Decreased Prefrontal Lobe Interhemispheric Functional Connectivity in Adolescents with Internet Gaming Disorder: A Primary Study Using Resting-State fMRI.

Fri, 03/06/2015 - 18:30

Decreased Prefrontal Lobe Interhemispheric Functional Connectivity in Adolescents with Internet Gaming Disorder: A Primary Study Using Resting-State fMRI.

PLoS One. 2015;10(3):e0118733

Authors: Wang Y, Yin Y, Sun YW, Zhou Y, Chen X, Ding WN, Wang W, Li W, Xu JR, Du YS

Abstract
PURPOSES: Recent neuroimaging studies have shown that people with Internet gaming disorder (IGD) have structural and functional abnormalities in specific brain areas and connections. However, little is known about the alterations of the interhemispheric resting-state functional connectivity (rsFC) in participants with IGD. In the present study, we used a newly developed voxel-mirrored homotopic connectivity (VMHC) method to investigate the interhemispheric rsFC of the whole brain in participants with IGD.
METHODS: We compared interhemispheric rsFC between 17 participants with IGD and 24 healthy controls, group-matched on age, gender, and education status. All participants were provided written informed consent. Resting-state functional and structural magnetic resonance images were acquired for all participants. The rsFC between bilateral homotopic voxels was calculated. Regions showing abnormal VMHC in IGD participants were adopted as regions of interest for correlation analyses.
RESULTS: Compared to healthy controls, IGD participants showed decreased VMHC between the left and right superior frontal gyrus (orbital part), inferior frontal gyrus (orbital part), middle frontal gyrus and superior frontal gyrus. Further analyses showed Chen Internet Addiction Scale (CIAS)-related VMHC in superior frontal gyrus (orbital part) and CIAS (r = -0.55, p = 0.02, uncorrected).
CONCLUSIONS: Our findings implicate the important role of altered interhemispheric rsFC in the bilateral prefrontal lobe in the neuropathological mechanism of IGD, and provide further supportive evidence for the reclassification of IGD as a behavioral addiction.

PMID: 25738502 [PubMed - as supplied by publisher]

Altered intra- and interregional synchronization in resting-state cerebral networks associated with chronic tinnitus.

Thu, 03/05/2015 - 17:00

Altered intra- and interregional synchronization in resting-state cerebral networks associated with chronic tinnitus.

Neural Plast. 2015;2015:475382

Authors: Chen YC, Zhang J, Li XW, Xia W, Feng X, Qian C, Yang XY, Lu CQ, Wang J, Salvi R, Teng GJ

Abstract
Objective. Subjective tinnitus is hypothesized to arise from aberrant neural activity; however, its neural bases are poorly understood. To identify aberrant neural networks involved in chronic tinnitus, we compared the resting-state functional magnetic resonance imaging (fMRI) patterns of tinnitus patients and healthy controls. Materials and Methods. Resting-state fMRI measurements were obtained from a group of chronic tinnitus patients (n = 29) with normal hearing and well-matched healthy controls (n = 30). Regional homogeneity (ReHo) analysis and functional connectivity analysis were used to identify abnormal brain activity; these abnormalities were compared to tinnitus distress. Results. Relative to healthy controls, tinnitus patients had significant greater ReHo values in several brain regions including the bilateral anterior insula (AI), left inferior frontal gyrus, and right supramarginal gyrus. Furthermore, the left AI showed enhanced functional connectivity with the left middle frontal gyrus (MFG), while the right AI had enhanced functional connectivity with the right MFG; these measures were positively correlated with Tinnitus Handicap Questionnaires (r = 0.459, P = 0.012 and r = 0.479, P = 0.009, resp.). Conclusions. Chronic tinnitus patients showed abnormal intra- and interregional synchronization in several resting-state cerebral networks; these abnormalities were correlated with clinical tinnitus distress. These results suggest that tinnitus distress is exacerbated by attention networks that focus on internally generated phantom sounds.

PMID: 25734018 [PubMed - in process]

Connectivity and functional profiling of abnormal brain structures in pedophilia.

Thu, 03/05/2015 - 17:00

Connectivity and functional profiling of abnormal brain structures in pedophilia.

Hum Brain Mapp. 2015 Mar 2;

Authors: Poeppl TB, Eickhoff SB, Fox PT, Laird AR, Rupprecht R, Langguth B, Bzdok D

Abstract
Despite its 0.5-1% lifetime prevalence in men and its general societal relevance, neuroimaging investigations in pedophilia are scarce. Preliminary findings indicate abnormal brain structure and function. However, no study has yet linked structural alterations in pedophiles to both connectional and functional properties of the aberrant hotspots. The relationship between morphological alterations and brain function in pedophilia as well as their contribution to its psychopathology thus remain unclear. First, we assessed bimodal connectivity of structurally altered candidate regions using meta-analytic connectivity modeling (MACM) and resting-state correlations employing openly accessible data. We compared the ensuing connectivity maps to the activation likelihood estimation (ALE) maps of a recent quantitative meta-analysis of brain activity during processing of sexual stimuli. Second, we functionally characterized the structurally altered regions employing meta-data of a large-scale neuroimaging database. Candidate regions were functionally connected to key areas for processing of sexual stimuli. Moreover, we found that the functional role of structurally altered brain regions in pedophilia relates to nonsexual emotional as well as neurocognitive and executive functions, previously reported to be impaired in pedophiles. Our results suggest that structural brain alterations affect neural networks for sexual processing by way of disrupted functional connectivity, which may entail abnormal sexual arousal patterns. The findings moreover indicate that structural alterations account for common affective and neurocognitive impairments in pedophilia. The present multimodal integration of brain structure and function analyses links sexual and nonsexual psychopathology in pedophilia. Hum Brain Mapp, 2015. © 2015 Wiley Periodicals, Inc.

PMID: 25733379 [PubMed - as supplied by publisher]

Characterizing and differentiating task-based and resting state fMRI signals via two-stage sparse representations.

Thu, 03/05/2015 - 17:00

Characterizing and differentiating task-based and resting state fMRI signals via two-stage sparse representations.

Brain Imaging Behav. 2015 Mar 3;

Authors: Zhang S, Li X, Lv J, Jiang X, Guo L, Liu T

Abstract
A relatively underexplored question in fMRI is whether there are intrinsic differences in terms of signal composition patterns that can effectively characterize and differentiate task-based or resting state fMRI (tfMRI or rsfMRI) signals. In this paper, we propose a novel two-stage sparse representation framework to examine the fundamental difference between tfMRI and rsfMRI signals. Specifically, in the first stage, the whole-brain tfMRI or rsfMRI signals of each subject were composed into a big data matrix, which was then factorized into a subject-specific dictionary matrix and a weight coefficient matrix for sparse representation. In the second stage, all of the dictionary matrices from both tfMRI/rsfMRI data across multiple subjects were composed into another big data-matrix, which was further sparsely represented by a cross-subjects common dictionary and a weight matrix. This framework has been applied on the recently publicly released Human Connectome Project (HCP) fMRI data and experimental results revealed that there are distinctive and descriptive atoms in the cross-subjects common dictionary that can effectively characterize and differentiate tfMRI and rsfMRI signals, achieving 100 % classification accuracy. Moreover, our methods and results can be meaningfully interpreted, e.g., the well-known default mode network (DMN) activities can be recovered from the very noisy and heterogeneous aggregated big-data of tfMRI and rsfMRI signals across all subjects in HCP Q1 release.

PMID: 25732072 [PubMed - as supplied by publisher]

Improving Reliability of Subject-Level Resting-State fMRI Parcellation with Shrinkage Estimators.

Thu, 03/05/2015 - 17:00

Improving Reliability of Subject-Level Resting-State fMRI Parcellation with Shrinkage Estimators.

Neuroimage. 2015 Feb 27;

Authors: Mejia AF, Nebel MB, Shou H, Crainiceanu CM, Pekar JJ, Mostofsky S, Caffo B, Lindquist MA

Abstract
A recent interest in resting state functional magnetic resonance imaging (rsfMRI) lies in subdividing the human brain into anatomically and functionally distinct regions of interest. For example, brain parcellation is often a necessary step for defining the network nodes used in connectivity studies. While inference has traditionally been performed on group-level data, there is a growing interest in parcellating single subject data. However, this is difficult due to the inherent low signal-to-noise ratio of rsfMRI data, combined with typically short scan lengths. A large number of brain parcellation approaches employ clustering, which begins with a measure of similarity or distance between voxels. The goal of this work is to improve the reproducibility of single-subject parcellation using shrinkage-based estimators of such measures, allowing the noisy subject-specific estimator to "borrow strength" in a principled manner from a larger population of subjects. We present several empirical Bayes shrinkage estimators and outline methods for shrinkage when multiple scans are not available for each subject. We perform shrinkage on raw inter-voxel correlation estimates and use both raw and shrinkage estimates to produce parcellations by performing clustering on the voxels. While we employ a standard spectral clustering approach, our proposed method is agnostic to the choice of clustering method and can be used as a pre-processing step for any clustering algorithm. Using two datasets - a simulated dataset where the true parcellation is known and is subject-specific and a test-retest dataset consisting of two 7-minute resting-state fMRI scans from 20 subjects - we show that parcellations produced from shrinkage correlation estimates have higher reliability and validity than those produced from raw correlation estimates. Application to test-retest data shows that using shrinkage estimators increases the reproducibility of subject-specific parcellations of the motor cortex by up to 30%.

PMID: 25731998 [PubMed - as supplied by publisher]

Gaussian process classification of Alzheimer's disease and mild cognitive impairment from resting-state fMRI.

Thu, 03/05/2015 - 17:00

Gaussian process classification of Alzheimer's disease and mild cognitive impairment from resting-state fMRI.

Neuroimage. 2015 Feb 27;

Authors: Challis E, Hurley P, Serra L, Bozzali M, Oliver S, Cercignani M

Abstract
Multivariate pattern analysis and statistical machine learning techniques are attracting increasing interest from the neuroimaging community. Researchers and clinicians are also increasingly interested in the study of functional-connectivity patterns of brains at rest and how these relations might change in conditions like Alzheimer's disease or clinical depression. In this study we investigate the efficacy of a specific multivariate statistical machine learning technique to perform patient stratification from functional-connectivity patterns of brains at rest. Whilst the majority of previous approaches to this problem have employed support vector machines (SVMs) we investigate the performance of Bayesian Gaussian process logistic regression (GP-LR) models with linear and non-linear covariance functions. GP-LR models can be interpreted as a Bayesian probabilistic analogue to kernel SVM classifiers. However, GP-LR methods confer a number of benefits over kernel SVMs. Whilst SVMs only return a binary class label prediction; GP-LR, being a probabilistic model, provides a principled estimate of the probability of class membership. Class probability estimates are a measure of the confidence the model has in its predictions, such a confidence score may be extremely useful in the clinical setting. Additionally, if miss-classification costs are not symmetric, thresholds can be set to achieve either strong specificity or sensitivity scores. Since GP-LR models are Bayesian, computationally expensive cross-validation hyper-parameter grid-search methods can be avoided. We apply these methods to a sample of 77 subjects; 27 with a diagnosis of probable AD, 50 with a diagnosis of a-MCI and a control sample of 39. All subjects underwent a MRI examination at 3T to obtain a 7 minute and 20 second resting state image. Our results support the hypothesis that GP-LR models can be effective at performing patient stratification: the implemented model achieves 75% accuracy disambiguating healthy subjects from subjects with amnesic mild cognitive impairment and 97% accuracy disambiguating amnesic mild cognitive impairment subjects from those with Alzheimer's disease, accuracies are estimated using a held-out test set. Both results are significant at the 1% level.

PMID: 25731993 [PubMed - as supplied by publisher]

Disrupted Functional Connectivity Related to Differential Degeneration of the Cingulum Bundle in Mild Cognitive Impairment Patients.

Thu, 03/05/2015 - 17:00

Disrupted Functional Connectivity Related to Differential Degeneration of the Cingulum Bundle in Mild Cognitive Impairment Patients.

Curr Alzheimer Res. 2015 Mar 2;

Authors: Liang Y, Chen Y, Li H, Zhao T, Sun X, Shu N, Peng D, Zhang Z

Abstract
Previous studies have demonstrated that Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI) exhibited anatomical and functional abnormalities in the anterior cingulate cortex (ACC) and accumulating evidence supported the hypothesis that changes in the ACC predict the progression from aMCI to AD. In this study, we aimed to explore how the two functional and structural heterogeneous sub-regions of ACC, namely the dorsal ACC (dACC) and the ventral ACC (vACC), changed in aMCI and whether the structural connectivity affects the functional connectivity between the two ACC subregions. To investigate this hypothesis, we studied resting-state fMRI and DTI images in a group of 24 aMCI and 29 healthy controls. The dACC exhibited a significantly increased functional connectivity in the Salience Network (SN) and a decreased functional connectivity with the vACC in aMCI. The DTI results showed that the bilateral cingulum fibers were the most damaged tracts in aMCI and that the fractional anisotrophy of the left anterior cingulum was significantly correlated with the functional connectivity between the two ACC sub-regions. In conclusion, this study revealed the pathological changes in the intrinsic functional connectivity of the ACC within SN, as well as the connectivity between the dACC and vACC in aMCI. Our study also revealed that disrupted white matter integrity of the anterior regions of the cingulum was associated with the alterations in subregional connectivity in the ACC.

PMID: 25731624 [PubMed - as supplied by publisher]

Natural Grouping of Neural Responses Reveals Spatially Segregated Clusters in Prearcuate Cortex.

Wed, 03/04/2015 - 15:30

Natural Grouping of Neural Responses Reveals Spatially Segregated Clusters in Prearcuate Cortex.

Neuron. 2015 Feb 25;

Authors: Kiani R, Cueva CJ, Reppas JB, Peixoto D, Ryu SI, Newsome WT

Abstract
A fundamental challenge in studying the frontal lobe is to parcellate this cortex into "natural" functional modules despite the absence of topographic maps, which are so helpful in primary sensory areas. Here we show that unsupervised clustering algorithms, applied to 96-channel array recordings from prearcuate gyrus, reveal spatially segregated subnetworks that remain stable across behavioral contexts. Looking for natural groupings of neurons based on response similarities, we discovered that the recorded area includes at least two spatially segregated subnetworks that differentially represent behavioral choice and reaction time. Importantly, these subnetworks are detectable during different behavioral states and, surprisingly, are defined better by "common noise" than task-evoked responses. Our parcellation process works well on "spontaneous" neural activity, and thus bears strong resemblance to the identification of "resting-state" networks in fMRI data sets. Our results demonstrate a powerful new tool for identifying cortical subnetworks by objective classification of simultaneously recorded electrophysiological activity.

PMID: 25728571 [PubMed - as supplied by publisher]