New resting-state fMRI related studies at PubMed

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Human neural correlates of sevoflurane-induced unconsciousness.

Fri, 11/10/2017 - 15:40

Human neural correlates of sevoflurane-induced unconsciousness.

Br J Anaesth. 2017 Oct 01;119(4):573-582

Authors: Palanca BJA, Avidan MS, Mashour GA

Abstract
Sevoflurane, a volatile anaesthetic agent well-tolerated for inhalation induction, provides a useful opportunity to elucidate the processes whereby halogenated ethers disrupt consciousness and cognition. Multiple molecular targets of sevoflurane have been identified, complementing imaging and electrophysiologic markers for the mechanistically obscure progression from wakefulness to unconsciousness. Recent investigations have more precisely detailed scalp EEG activity during this transition, with practical clinical implications. The relative timing of scalp potentials in frontal and parietal EEG signals suggests that sevoflurane might perturb the propagation of neural information between underlying cortical regions. Spatially distributed brain activity during general anaesthesia has been further investigated with positron emission tomography (PET) and resting-state functional magnetic resonance imaging (fMRI). Combined EEG and PET investigations have identified changes in cerebral blood flow and metabolic activity in frontal, parietal, and thalamic regions during sevoflurane-induced loss of consciousness. More recent fMRI investigations have revealed that sevoflurane weakens the signal correlations among brain regions that share functionality and specialization during wakefulness. In particular, two such resting-state networks have shown progressive breakdown in intracortical and thalamocortical connectivity with increasing anaesthetic concentrations: the Default Mode Network (introspection and episodic memory) and the Ventral Attention Network (orienting of attention to salient feature of the external world). These data support the hypotheses that perturbations in temporally correlated activity across brain regions contribute to the transition between states of sevoflurane sedation and general anaesthesia.

PMID: 29121298 [PubMed - in process]

Brain functional connectivity differentiates dexmedetomidine from propofol and natural sleep.

Fri, 11/10/2017 - 15:40

Brain functional connectivity differentiates dexmedetomidine from propofol and natural sleep.

Br J Anaesth. 2017 Oct 01;119(4):674-684

Authors: Guldenmund P, Vanhaudenhuyse A, Sanders RD, Sleigh J, Bruno MA, Demertzi A, Bahri MA, Jaquet O, Sanfilippo J, Baquero K, Boly M, Brichant JF, Laureys S, Bonhomme V

Abstract
Background: We used functional connectivity measures from brain resting state functional magnetic resonance imaging to identify human neural correlates of sedation with dexmedetomidine or propofol and their similarities with natural sleep.
Methods: Connectivity within the resting state networks that are proposed to sustain consciousness generation was compared between deep non-rapid-eye-movement (N3) sleep, dexmedetomidine sedation, and propofol sedation in volunteers who became unresponsive to verbal command. A newly acquired dexmedetomidine dataset was compared with our previously published propofol and N3 sleep datasets.
Results: In all three unresponsive states (dexmedetomidine sedation, propofol sedation, and N3 sleep), within-network functional connectivity, including thalamic functional connectivity in the higher-order (default mode, executive control, and salience) networks, was significantly reduced as compared with the wake state. Thalamic functional connectivity was not reduced for unresponsive states within lower-order (auditory, sensorimotor, and visual) networks. Voxel-wise statistical comparisons between the different unresponsive states revealed that thalamic functional connectivity with the medial prefrontal/anterior cingulate cortex and with the mesopontine area was reduced least during dexmedetomidine-induced unresponsiveness and most during propofol-induced unresponsiveness. The reduction seen during N3 sleep was intermediate between those of dexmedetomidine and propofol.
Conclusions: Thalamic connectivity with key nodes of arousal and saliency detection networks was relatively preserved during N3 sleep and dexmedetomidine-induced unresponsiveness as compared to propofol. These network effects may explain the rapid recovery of oriented responsiveness to external stimulation seen under dexmedetomidine sedation.
Trial registry number: Committee number: 'Comité d'Ethique Hospitalo-Facultaire Universitaire de Liège' (707); EudraCT number: 2012-003562-40; internal reference: 20121/135; accepted on August 31, 2012; Chair: Prof G. Rorive. As it was considered a phase I clinical trial, this protocol does not appear on the EudraCT public website.

PMID: 29121293 [PubMed - in process]

Increased resting-state global functional connectivity density of default mode network in schizophrenia subjects treated with electroconvulsive therapy.

Fri, 11/10/2017 - 15:40
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Increased resting-state global functional connectivity density of default mode network in schizophrenia subjects treated with electroconvulsive therapy.

Schizophr Res. 2017 Nov 06;:

Authors: Huang H, Jiang Y, Xia M, Tang Y, Zhang T, Cui H, Wang J, Li Y, Xu L, Curtin A, Sheng J, Jia Y, Yao D, Li C, Luo C, Wang J

Abstract
Modified electroconvulsive therapy (MECT) has been widely applied to help treat schizophrenia patients who are treatment-resistant to pharmaceutical therapy. Although the technique is increasingly prevalent, the underlying neural mechanisms have not been well clarified. We conducted a longitudinal study to investigate the alteration of global functional connectivity density (gFCD) in schizophrenia patients undergoing MECT using resting state fMRI (functional magnetic resonance imaging). Two groups of schizophrenia inpatients were recruited. One group received a four-week MECT together with antipsychotic drugs (ECT+Drug, n=21); the other group only received antipsychotic drugs (Drug, n=21). Both groups were compared to a sample of healthy controls (HC, n=23). fMRI scans were obtained from the schizophrenia patients twice at baseline (t1) and after 4-week treatment (t2), and from healthy controls at baseline. gFCD was computed using resting state fMRI. Repeated ANCOVA showed a significant interaction effect of group×time in the schizophrenia patients in left precuneus (Pcu), ventral medial prefrontal cortex (vMPFC), and dorsal medial prefrontal cortex (dMPFC) (GRF-corrected P<0.05), which are mainly located within the default mode network (DMN). Post-hoc analysis revealed that compared with baseline (t1), an increased gFCD was found in the ECT+Drug group in the dMPFC (t=3.87, p=0.00095), vMPFC (t=3.95, p=0.00079) and left Pcu (t=3.33, p=0.0034), but no significant effect was identified in the Drug group. The results suggested that increased global functional connectivity density within the DMN might be one important neural mechanism of MECT in schizophrenia.

PMID: 29117910 [PubMed - as supplied by publisher]

Detecting Perfusion Pattern based on the Background Low-frequency Fluctuation in Resting-State Functional MRI Data and its Influence on Resting-State Networks: An Iterative Post-processing Approach.

Fri, 11/10/2017 - 15:40
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Detecting Perfusion Pattern based on the Background Low-frequency Fluctuation in Resting-State Functional MRI Data and its Influence on Resting-State Networks: An Iterative Post-processing Approach.

Brain Connect. 2017 Nov 08;:

Authors: Qian T, Zanchi D, Rodriguez C, Ackermann M, Giannakopoulos P, Haller S

Abstract
INTRODUCTION: RS-fMRI is based on the assumption that the vascular response and the blood oxygenation level dependent (BOLD) response are homogenous across the entire brain. However, this a priori hypothesis is not consistent with the well-known variability of cerebral vascular territories. In order to explore whether the RS networks are influenced by varied vascular speed in different vascular territories, we assessed the time-shift maps that give an estimate of the local timing of the vascular response and check whether local differences in this timing have an impact on the estimates of RS networks.
METHODS: 217 elderly (>=60 years), healthy participants (73.74 ± 4.41 years, 143 female, 203 right-handed) underwent one MRI examination including an RS-fMRI session. After preprocessing, statistical analyses included time-shift analyses and RS-fMRI analyses using as regressor the delay maps obtained from the time-shift analyses. The functional connectivity map of default mode network of each participant was then calculated by using the seed-to-voxel analysis in the REST toolbox.
RESULTS: Faster cerebrovascular responses were notably present in the primary motor and somatosensory and peri-insular cortex while slower responses were present in various regions including notably the posterior cingulate cortex (PCC). Moreover, significant changes notably in the default mode network (DMN), including medial pre-frontal cortex (t=11.95), posterior cingulate cortex (t=11.52), right middle temporal lobe (t=10.72) and right angular gyrus (t=10.88), were observed also taking into account the cerebrovascular delayed maps.
DISCUSSION: As the most prominent example of the RS networks, DMN activation patterns change as a function of the cerebrovascular delay. These data suggest that a group correction for vascular maps in RS-fMRI measurements is essential to correctly depict functional differences and exclude potential confounding effects, notably in the elderly with increasing prevalence of vascular co-morbidity.

PMID: 29117709 [PubMed - as supplied by publisher]

Successful group psychotherapy of depression in adolescents alters fronto-limbic resting-state connectivity.

Fri, 11/10/2017 - 15:40
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Successful group psychotherapy of depression in adolescents alters fronto-limbic resting-state connectivity.

J Affect Disord. 2017 Feb;209:135-139

Authors: Straub J, Metzger CD, Plener PL, Koelch MG, Groen G, Abler B

Abstract
BACKGROUND: Current resting state imaging findings support suggestions that the neural signature of depression and therefore also its therapy should be conceptualized as a network disorder rather than a dysfunction of specific brain regions. In this study, we compared neural connectivity of adolescent patients with depression (PAT) and matched healthy controls (HC) and analysed pre-to-post changes of seed-based network connectivities in PAT after participation in a cognitive behavioral group psychotherapy (CBT).
METHODS: 38 adolescents (30 female; 19 patients; 13-18 years) underwent an eyes-closed resting-state scan. PAT were scanned before (pre) and after (post) five sessions of CBT. Resting-state functional connectivity was analysed in a seed-based approach for right-sided amygdala and subgenual anterior cingulate cortex (sgACC). Symptom severity was assessed using the Beck Depression Inventory Revision (BDI-II).
RESULTS: Prior to group CBT, between groups amygdala and sgACC connectivity with regions of the default mode network was stronger in the patients group relative to controls. Within the PAT group, a similar pattern significantly decreased after successful CBT. Conversely, seed-based connectivity with affective regions and regions processing cognition and salient stimuli was stronger in HC relative to PAT before CBT. Within the PAT group, a similar pattern changed with CBT. Changes in connectivity correlated with the significant pre-to-post symptom improvement, and pre-treatment amygdala connectivity predicted treatment response in depressed adolescents.
LIMITATIONS: Sample size and missing long-term follow-up limit the interpretability.
CONCLUSIONS: Successful group psychotherapy of depression in adolescents involved connectivity changes in resting state networks to that of healthy controls.

PMID: 27912160 [PubMed - indexed for MEDLINE]

Ruminative brooding is associated with salience network coherence in early pubertal youth.

Fri, 11/10/2017 - 15:40
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Ruminative brooding is associated with salience network coherence in early pubertal youth.

Soc Cogn Affect Neurosci. 2017 Feb 01;12(2):298-310

Authors: Ordaz SJ, LeMoult J, Colich NL, Prasad G, Pollak M, Popolizio M, Price A, Greicius M, Gotlib IH

Abstract
Rumination, and particularly ruminative brooding, perpetuates dysphoric mood states and contributes to the emergence of depression. Studies of adults and older adolescents have characterized the association between rumination and intrinsic functional connectivity within default mode (DMN), salience (SN) and executive control (ECN) networks; we know little, however, about the brain network basis of rumination during early puberty, a sensitive period for network reorganization. 112 early puberty boys and girls completed resting-state scans, the Ruminative Response Scale, and the Youth Self-Report questionnaire. Using independent components analysis and dual regression, we quantified coherence for each individual in networks of interest (SN, ECN, DMN) and in non-relevant networks (motor, visual) in which we predicted no correlations with behavioral measures. Boys and girls did not differ in levels of rumination or internalizing symptoms, or in coherence for any network. The relation between SN network coherence and rumination; however, and specifically ruminative brooding, was moderated by sex: greater SN coherence was associated with higher levels of brooding in girls but not in boys. Further, in girls, brooding mediated the relation between SN coherence and internalizing symptoms. These results point to coherence within the SN as a potential neurodevelopmental marker of risk for depression in early pubertal girls.

PMID: 27633394 [PubMed - indexed for MEDLINE]

Automatic Classification on Multi-Modal MRI Data for Diagnosis of the Postural Instability and Gait Difficulty Subtype of Parkinson's Disease.

Fri, 11/10/2017 - 15:40
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Automatic Classification on Multi-Modal MRI Data for Diagnosis of the Postural Instability and Gait Difficulty Subtype of Parkinson's Disease.

J Parkinsons Dis. 2016 May 11;6(3):545-56

Authors: Gu Q, Zhang H, Xuan M, Luo W, Huang P, Xia S, Zhang M

Abstract
BACKGROUND: Patients with the postural instability and gait difficulty subtype (PIGD) of Parkinson's disease (PD) are a refractory challenge in clinical practice. Despite previous attempts that have been made at studying subtype-specific brain alterations across PD population, conclusive neuroimaging biomarkers on patients with the PIGD subtype are still lacking. Machine learning-based classifications are a promising tool for differential diagnosis that effectively integrate complex and multivariate data.
OBJECTIVE: Our present study aimed to introduce the machine learning-based automatic classification for the first time to distinguish patients with the PIGD subtype from those with the non-PIGD subtype of PD at the individual level.
METHODS: Fifty-two PD patients and forty-five normal controls (NCs) were recruited and underwent multi-modal MRI scans including a set of resting-state functional, 3D T1-weighted and diffusion tensor imaging sequences. By comparing the PD patients with the NCs, features that were not conducive to the subtype-specific classification were ruled out from massive brain features. We applied a support vector machine classifier with the recursive feature elimination method to multi-modal MRI data for selecting features with the best discriminating power, and evaluated the proposed classifier with the leave-one-out cross-validation.
RESULTS: Using this classifier, we obtained satisfactory diagnostic rates (accuracy = 92.31%, specificity = 96.97%, sensitivity = 84.21% and AUCmax  = 0.9585). The diagnostic agreement evaluated by the Kappa test showed an almost perfect agreement with the existing clinical categorization (Kappa value = 0.83).
CONCLUSIONS: With these favorable results, our findings suggested the machine learning-based classification as an alternative technique to classifying clinical subtypes in PD.

PMID: 27176623 [PubMed - indexed for MEDLINE]

Collective sparse symmetric non-negative matrix factorization for identifying overlapping communities in resting-state brain functional networks.

Thu, 11/09/2017 - 14:20
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Collective sparse symmetric non-negative matrix factorization for identifying overlapping communities in resting-state brain functional networks.

Neuroimage. 2017 Nov 05;:

Authors: Li X, Gan JQ, Wang H

Abstract
Resting-state functional magnetic resonance imaging (rs-fMRI) provides a valuable tool to study spontaneous brain activity. Using rs-fMRI, researchers have extensively studied the organization of the brain functional network and found several consistent communities consisting of functionally connected but spatially separated brain regions across subjects. However, increasing evidence in many disciplines has shown that most realistic complex networks have overlapping community structure. Only recently has the overlapping community structure drawn increasing interest in the domain of brain network studies. Another issue is that the inter-subject variability is often not directly reflected in the process of community detection at the group level. In this paper, we propose a novel method called collective sparse symmetric non-negative matrix factorization (cssNMF) to address these issues. The cssNMF approach identifies the group-level overlapping communities across subjects and in the meantime preserves the information of individual variation in brain functional network organization. To comprehensively validate cssNMF, a simulated fMRI dataset with ground-truth, a real rs-fMRI dataset with two repeated sessions and another different real rs-fMRI dataset have been used for performance comparison in the experiment. Experimental results show that the proposed cssNMF method accurately and stably identifies group-level overlapping communities across subjects as well as individual differences in network organization with neurophysiologically meaningful interpretations. This research extends our understanding of the common underlying community structures and individual differences in community strengths in brain functional network organization.

PMID: 29117581 [PubMed - as supplied by publisher]

Dynamic Network Communication in the Human Functional Connectome Predicts Perceptual Variability in Visual Illusion.

Thu, 11/09/2017 - 14:20
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Dynamic Network Communication in the Human Functional Connectome Predicts Perceptual Variability in Visual Illusion.

Cereb Cortex. 2016 Nov 22;:1-15

Authors: Wang Z, Zeljic K, Jiang Q, Gu Y, Wang W, Wang Z

Abstract
Ubiquitous variability between individuals in visual perception is difficult to standardize and has thus essentially been ignored. Here we construct a quantitative psychophysical measure of illusory rotary motion based on the Pinna-Brelstaff figure (PBF) in 73 healthy volunteers and investigate the neural circuit mechanisms underlying perceptual variation using functional magnetic resonance imaging (fMRI). We acquired fMRI data from a subset of 42 subjects during spontaneous and 3 stimulus conditions: expanding PBF, expanding modified-PBF (illusion-free) and expanding modified-PBF with physical rotation. Brain-wide graph analysis of stimulus-evoked functional connectivity patterns yielded a functionally segregated architecture containing 3 discrete hierarchical networks, commonly shared between rest and stimulation conditions. Strikingly, communication efficiency and strength between 2 networks predominantly located in visual areas robustly predicted individual perceptual differences solely in the illusory stimulus condition. These unprecedented findings demonstrate that stimulus-dependent, not spontaneous, dynamic functional integration between distributed brain networks contributes to perceptual variability in humans.

PMID: 29117288 [PubMed - as supplied by publisher]

Altered DMN functional connectivity and regional homogeneity in partial epilepsy patients: a seventy cases study.

Thu, 11/09/2017 - 14:20
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Altered DMN functional connectivity and regional homogeneity in partial epilepsy patients: a seventy cases study.

Oncotarget. 2017 Oct 06;8(46):81475-81484

Authors: Hu CY, Gao X, Long L, Long X, Liu C, Chen Y, Xie Y, Liu C, Xiao B, Hu ZY

Abstract
Purpose: Clinically diagnosed partial epilepsy is hard to be functionally diagnosed by regular electroencephalograph (EEG) and conventional magnetic resonance imaging (MRI). By collecting transient brain regional signals, blood oxygenation level-dependent (BOLD) function MRI (BOLD-fMRI) can provide brain function change information with high accuracy. By using resting state BOLD-fMRI technique, we aim to investigate the changes of brain function in partial epilepsy patients.
Methods: BOLD-fMRI scanning was performed in 70 partial epilepsy and 70 healthy people. BOLD-fMRI data was analyzed by using the Regional Homogeneity (ReHo) method and functional connectivity of Default Mode Network (DMN) methods. The abnormal brain functional connectivity in partial epilepsy patients was detected by Statistical Parametric Mapping 8 (SPM8) analysis.
Results: Compared to healthy group, epilepsy patients showed significant decreased ReHo in left inferior parietal lobule/pre- and post-central gyrus, right thalamus/paracentral lobule/Cerebellum anterior and posterior Lobe, bilateral insula. The DMN functional connectivity regions decreased significantly in right uncus, left Inferior parietal lobule, left supramarginal gyrus, left uncus, left parahippocampa gyrus, and left superior temporal gyrus, in epilepsy patients, compared to healthy controls.
Significance: This study clarified that both ReHo and functional connectivity of DMN decreased in partial epilepsy patients compared to healthy controls. While left inferior parietal lobule was detected in both ReHo and DMN, many other identified regions were different by using these two BOLD-fMRI techniques. We propose that both ReHo and DMN patterns in BOLD-fMRI may suggest networks responsible for partial epilepsy genesis or progression.

PMID: 29113406 [PubMed]

Altered putamen functional connectivity is associated with anxiety disorder in Parkinson's disease.

Thu, 11/09/2017 - 14:20
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Altered putamen functional connectivity is associated with anxiety disorder in Parkinson's disease.

Oncotarget. 2017 Oct 06;8(46):81377-81386

Authors: Wang X, Li J, Yuan Y, Wang M, Ding J, Zhang J, Zhu L, Shen Y, Zhang H, Zhang K

Abstract
In this study, we used resting state-functional magnetic resonance imaging (rs-fMRI) to explore altered putamen functional connectivity (FC) in Parkinson's disease patients with anxiety disorder. We divided 65 Parkinson's disease patients into anxiety (PD-A; n=18) and non-anxiety (PD-NA; n=45) groups based on a Hamilton Anxiety Rating Scale cutoff score of 12. The PD-A patients exhibited altered putamen FC with cortical and subcortical regions. The PD-A patients showed enhanced putamen FC with the caudatum, which correlated with increased emotional processing during anxiety. Decreased putamen FC with the orbitofrontal gyrus and cerebellum also correlated with increased anxiety in Parkinson's disease. Our findings demonstrate that anxiety disorder in Parkinson's disease is associated with abnormal putamen FC networks, especially with caudatum, orbitofrontal gyrus and cerebellum.

PMID: 29113397 [PubMed]

Chemotherapy-induced changes of cerebral activity in resting-state functional magnetic resonance imaging and cerebral white matter in diffusion tensor imaging.

Thu, 11/09/2017 - 14:20
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Chemotherapy-induced changes of cerebral activity in resting-state functional magnetic resonance imaging and cerebral white matter in diffusion tensor imaging.

Oncotarget. 2017 Oct 06;8(46):81273-81284

Authors: Mo C, Lin H, Fu F, Lin L, Zhang J, Huang M, Wang C, Xue Y, Duan Q, Lin W, Chen X

Abstract
While chemotherapy related cognitive disorder has been described in many studies, but we still lack relatively reliable and objective diagnostic tools, and there are few similar studies in Asian patients. We recruited Asian breast cancer patients to perform a cohort study to uncover chemotherapy related cognitive disorder by using resting-state functioning magnetic resonance imaging (RS-fMRI) and magnetic resonance diffusion tensor imaging (DTI) combined with neuropsychologic assessments. This is the first prospective study which combines RS-fMRI and DTI to detect chemotherapy related cognitive disorder. The neuropsychologic tests and MRI were performed before and after the chemotherapy. The healthy controls were tested at matched times. The chemotherapy-treated group performed worse on memory and we found significant changes in the cerebellum, right orbitofrontal area, right middle and superior temporal gyrus, right subcentral area, left dorsolateral prefrontal cortex, and precentral gyrus in RS-fMRI after chemotherapy. We found changes in the fornix and superior fronto-occipital fasciculus with DTI. There was a correlation between some cognitive function and MRI measurements in the correlation analysis, but it was not significant after false discovery rate (FDR) multiple testing corrections. The results indicate that RS-fMRI and DTI may be a prospective application for assessing chemotherapy related cognitive disorder.

PMID: 29113386 [PubMed]

Differential association of default mode network connectivity and rumination in healthy individuals and remitted MDD patients.

Thu, 11/09/2017 - 14:20
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Differential association of default mode network connectivity and rumination in healthy individuals and remitted MDD patients.

Soc Cogn Affect Neurosci. 2016 Nov;11(11):1792-1801

Authors: Lois G, Wessa M

Abstract
Rumination is associated with increased default-mode network (DMN) activity and functional connectivity (FC) in depressed and healthy individuals. In this study, we sought to examine the relationship between self-reported rumination and resting-state FC in the DMN and cognitive control networks in 25 remitted depressed patients and 25 matched healthy controls using independent component and seed-based analyses. We also explored potential group differences in the global pattern of resting-state FC. Healthy subjects with increased levels of rumination exhibited increased anterior DMN connectivity with the posterior DMN and the dorsal attention network and low connectivity within the anterior DMN. On the other hand, remitted depressed ruminators patients were associated with the opposite FC pattern in these regions. Based on global FC patterns, a support vector machine algorithm correctly classified 92% of the subjects into their respective group by a leave-one-out cross-validation. Whole-brain FC analysis also revealed a group by rumination interaction effect within the DMN. The present findings highlight the different functional roles of the anterior and the posterior DMN, and provide novel insights into the underlying neural mechanisms leading to depression relapse.

PMID: 27405616 [PubMed - indexed for MEDLINE]

Role of spontaneous brain activity in explicit and implicit aspects of cognitive flexibility under socially conflicting situations: a resting-state fMRI study using fractional amplitude of low-frequency fluctuations.

Wed, 11/08/2017 - 13:00
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Role of spontaneous brain activity in explicit and implicit aspects of cognitive flexibility under socially conflicting situations: a resting-state fMRI study using fractional amplitude of low-frequency fluctuations.

Neuroscience. 2017 Oct 27;:

Authors: Fujino J, Tei S, Jankowski KF, Kawada R, Murai T, Takahashi H

Abstract
We are constantly exposed to socially conflicting situations in everyday life, and cognitive flexibility is essential for adaptively coping with such difficulties. Flexible goal choice and pursuit are not exclusively conscious, and therefore cognitive flexibility involves both explicit and implicit forms of processing. However, it is unclear how individual differences in explicit and implicit aspects of flexibility are associated with neural activity in a resting state. Here, we measured intrinsic fractional amplitude of low-frequency fluctuations (fALFF) by resting-state functional magnetic imaging (RS-fMRI) as an indicator of regional brain spontaneous activity, together with explicit and implicit aspects of cognitive flexibility using the Cognitive Flexibility Scale (CFS) and Implicit Association Test (IAT). Consistent with the dual processing theory, there was a strong association between explicit aspects of flexibility (CFS score) and "rationalism" thinking style and between implicit aspects (IAT effect) and "experientialism." The level of explicit flexibility was also correlated with fALFF values in the left lateral prefrontal cortex, whereas the level of implicit flexibility was correlated with fALFF values in the right cerebellum. Furthermore, the fALFF values in both regions predicted individual preference for flexible decision-making strategy in a vignettes simulation task. These results add to our understanding of the neural mechanisms underlying flexible decision-making for solving social conflicts. More generally, our findings highlight the utility of RS-fMRI combined with both explicit and implicit psychometric measures for better understanding individual differences in social cognition.

PMID: 29111359 [PubMed - as supplied by publisher]

Integrated cross-network connectivity of amygdala, insula, and subgenual cingulate associated with facial emotion perception in healthy controls and remitted major depressive disorder.

Wed, 11/08/2017 - 13:00
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Integrated cross-network connectivity of amygdala, insula, and subgenual cingulate associated with facial emotion perception in healthy controls and remitted major depressive disorder.

Cogn Affect Behav Neurosci. 2017 Nov 06;:

Authors: Jenkins LM, Stange JP, Barba A, DelDonno SR, Kling LR, Briceño EM, Weisenbach SL, Phan KL, Shankman SA, Welsh RC, Langenecker SA

Abstract
Emotion perception deficits could be due to disrupted connectivity of key nodes in the salience and emotion network (SEN), including the amygdala, subgenual anterior cingulate cortex (sgACC), and insula. We examined SEN resting-state (rs-)fMRI connectivity in rMDD in relation to Facial Emotion Perception Test (FEPT) performance. Fifty-two medication-free people ages 18 to 23 years participated. Twenty-seven had major depressive disorder (MDD) in remission (rMDD, 10 males), as MDD is associated with emotion perception deficits and alterations in rsfMRI. Twenty-five healthy controls (10 males) also participated. Participants completed the FEPT during fMRI, in addition to an 8-minute eyes-open resting-state scan. Seed regions of interest were defined in the amygdala, anterior insula and sgACC. Multiple regression analyses co-varied diagnostic group, sex and movement parameters. Emotion perception accuracy was positively associated with connectivity between amygdala seeds and regions primarily in the SEN and cognitive control network (CCN), and also the default mode network (DMN). Accuracy was also positively associated with connectivity between the sgACC seeds and other SEN regions, and the DMN, particularly for the right sgACC. Connectivity negatively associated with emotion perception was mostly with regions outside of these three networks, other than the left insula and part of the DMN. This study is the first to our knowledge to demonstrate relationships between facial emotion processing and resting-state connectivity with SEN nodes and between SEN nodes and regions located within other neural networks.

PMID: 29110183 [PubMed - as supplied by publisher]

Cognitive behavioral therapy increases amygdala connectivity with the cognitive control network in both MDD and PTSD.

Wed, 11/08/2017 - 13:00
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Cognitive behavioral therapy increases amygdala connectivity with the cognitive control network in both MDD and PTSD.

Neuroimage Clin. 2017;14:464-470

Authors: Shou H, Yang Z, Satterthwaite TD, Cook PA, Bruce SE, Shinohara RT, Rosenberg B, Sheline YI

Abstract
BACKGROUND: Both major depressive disorder (MDD) and post-traumatic stress disorder (PTSD) are characterized by alterations in intrinsic functional connectivity. Here we investigated changes in intrinsic functional connectivity across these disorders as a function of cognitive behavioral therapy (CBT), an effective treatment in both disorders.
METHODS: 53 unmedicated right-handed participants were included in a longitudinal study. Patients were diagnosed with PTSD (n = 18) and MDD (n = 17) with a structured diagnostic interview and treated with 12 sessions of manualized CBT over a 12-week period. Patients received an MRI scan (Siemens 3 T Trio) before and after treatment. Longitudinal functional principal components analysis (LFPCA) was performed on functional connectivity of the bilateral amygdala with the fronto-parietal network. A matched healthy control group (n = 18) was also scanned twice for comparison.
RESULTS: LFPCA identified four eigenimages or principal components (PCs) that contributed significantly to the longitudinal change in connectivity. The second PC differentiated CBT-treated patients from controls in having significantly increased connectivity of the amygdala with the fronto-parietal network following CBT.
LIMITATIONS: Analysis of CBT-induced amygdala connectivity changes was restricted to the a priori determined fronto-parietal network. Future studies are needed to determine the generalizability of these findings, given the small and predominantly female sample.
CONCLUSION: We found evidence for the hypothesis that CBT treatment is associated with changes in connectivity between the amygdala and the fronto-parietal network. CBT may work by strengthening connections between the amygdala and brain regions that are involved in cognitive control, potentially providing enhanced top-down control of affective processes that are dysregulated in both MDD and PTSD.

PMID: 28275546 [PubMed - indexed for MEDLINE]

Dynamic association between perfusion and white matter integrity across time since injury in Veterans with history of TBI.

Wed, 11/08/2017 - 13:00
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Dynamic association between perfusion and white matter integrity across time since injury in Veterans with history of TBI.

Neuroimage Clin. 2017;14:308-315

Authors: Clark AL, Bangen KJ, Sorg SF, Schiehser DM, Evangelista ND, McKenna B, Liu TT, Delano-Wood L

Abstract
OBJECTIVE: Cerebral blood flow (CBF) plays a critical role in the maintenance of neuronal integrity, and CBF alterations have been linked to deleterious white matter changes. Although both CBF and white matter microstructural alterations have been observed within the context of traumatic brain injury (TBI), the degree to which these pathological changes relate to one another and whether this association is altered by time since injury have not been examined. The current study therefore sought to clarify associations between resting CBF and white matter microstructure post-TBI.
METHODS: 37 veterans with history of mild or moderate TBI (mmTBI) underwent neuroimaging and completed health and psychiatric symptom questionnaires. Resting CBF was measured with multiphase pseudocontinuous arterial spin labeling (MPPCASL), and white matter microstructural integrity was measured with diffusion tensor imaging (DTI). The cingulate cortex and cingulum bundle were selected as a priori regions of interest for the ASL and DTI data, respectively, given the known vulnerability of these regions to TBI.
RESULTS: Regression analyses controlling for age, sex, and posttraumatic stress disorder (PTSD) symptoms revealed a significant time since injury × resting CBF interaction for the left cingulum (p < 0.005). Decreased CBF was significantly associated with reduced cingulum fractional anisotropy (FA) in the chronic phase; however, no such association was observed for participants with less remote TBI.
CONCLUSIONS: Our results showed that reduced CBF was associated with poorer white matter integrity in those who were further removed from their brain injury. Findings provide preliminary evidence of a possible dynamic association between CBF and white matter microstructure that warrants additional consideration within the context of the negative long-term clinical outcomes frequently observed in those with history of TBI. Additional cross-disciplinary studies integrating multiple imaging modalities (e.g., DTI, ASL) and refined neuropsychiatric assessment are needed to better understand the nature, temporal course, and dynamic association between brain changes and clinical outcomes post-injury.

PMID: 28210542 [PubMed - indexed for MEDLINE]

Methylphenidate alters brain connectivity after enhanced physical performance.

Tue, 11/07/2017 - 12:00

Methylphenidate alters brain connectivity after enhanced physical performance.

Brain Res. 2017 Oct 28;:

Authors: King M, Breda KV, Rauch LH, Brooks SJ, Stein DJ, Ipser J

Abstract
Muscle fatigue is a disturbed homeostatic state characterized by a temporary inability to maintain force output and has lasting effects on the brain in the period immediately after exercise, such as decreased interhemispheric functional connectivity (FC). Stimulants that increase dopamine and norepinephrine neurotransmission can enhance performance during muscle fatiguing exercise (i.e. are ergogenic). We recently demonstrated that methylphenidate (MPH) increased force output and increased FC between the insular (IC) and hand motor cortex during a fatiguing handgrip task. However, whether resting FC is altered in the recovery period after enhanced force is unknown. The objective of these follow-up analyses was to examine the effects of performing a fatiguing handgrip task with MPH on subsequent resting state FC. In a double-blind counter-balanced design, participants ingested placebo or MPH and in a magnetic resonance imaging scanner performed: a six-minute pre-task resting scan, a fatiguing handgrip task during scanning, and then a sixminute post-task resting scan. We investigated task-related force and resting state FC pre and post task between: (1) interhemispheric motor cortex (M1) FC and (2) the right IC and left hand motor area. We found reduced interhemispheric M1 FC post task and that this decrease was negatively associated with percent increase in mean trial force in MPH conditions. Further, MPH but not placebo increased right IC - left hand motor area FC post task. This study demonstrates that using MPH during a muscle fatiguing task has lasting effects on the brain that are markedly different from drug naïve conditions.

PMID: 29107662 [PubMed - as supplied by publisher]

Distance-dependent alterations in local functional connectivity in drug-naive major depressive disorder.

Tue, 11/07/2017 - 12:00

Distance-dependent alterations in local functional connectivity in drug-naive major depressive disorder.

Psychiatry Res. 2017 Oct 25;270:80-85

Authors: Zhu J, Lin X, Lin C, Zhuo C

Abstract
Previous studies using resting-state functional magnetic resonance imaging (fMRI) have found abnormal functional connectivity in patients with major depressive disorder (MDD). Yet, effect of distance thresholds on local functional connectivity changes in MDD is largely unknown. Here, we used resting-state fMRI data and functional connectivity strength (FCS) method to test local functional connectivity differences at different distance thresholds between 47 drug-naive patients with MDD and 47 healthy controls. For the distribution of functional brain hubs with high local FCS, the overall changing trend from distance thresholds of 10mm to 100mm was from lateral to medial. Compared to controls, MDD patients exhibited decreased local FCS independent of distance threshold in the sensorimotor system (postcentral gyrus, paracentral lobule, and supplementary motor area). MDD Patients exhibited increased local FCS in the inferior temporal gyrus at two lower distance thresholds (20mm and 30mm) and a higher distance threshold (100mm). In addition, MDD patients showed increased local FCS in the putamen at higher distance thresholds (80-100mm). These findings suggest that local functional connectivity abnormalities in MDD are dependent on distance thresholds and that future studies should take the distance thresholds into account when measuring local functional connectivity in MDD.

PMID: 29107212 [PubMed - as supplied by publisher]

Intrinsic Frequency Specific Brain Networks for Identification of MCI individuals using resting-state fMRI.

Tue, 11/07/2017 - 12:00

Intrinsic Frequency Specific Brain Networks for Identification of MCI individuals using resting-state fMRI.

Neurosci Lett. 2017 Oct 26;:

Authors: Qian L, Zheng L, Shang Y, Zhang Y, Zhang Y, Alzheimer’s disease Neuroimaging Initiative

Abstract
Numerous brain oscillations are well organized into several brain rhythms to support complex brain activities within distinct frequency bands. These rhythms temporally coexist in the same or different brain areas and may interact with each other with specific properties and physiological functions. However, the identification and evaluation of these various brain rhythms derived from BOLD-fMRI signals are obscure. To address this issue, we introduced a data-driven method named Complementary Ensemble Empirical Mode Decomposition (CEEMD) to automatically decompose the BOLD oscillations into several brain rhythms within distinct frequency bands. Thereafter, in order to evaluate the performance of CEEMD in the detection of subtle BOLD signals, a novel CEEMD-based high-dimensional pattern classification framework was proposed to accurately identify mild cognitive impairment individuals from the healthy controls. Our results showed CEEMD is a stable frequency decomposition method. Furthermore, CEEMD-based frequency specific topological profiles provided a classification accuracy of 93.33%, which was saliently higher than that of the conventional frequency separation based scheme. Importantly, our findings demonstrated that CEEMD could provide an effective means for brain oscillation separation, by which a more meaningful frequency bins could be used to detect the subtle changes embedded in the BOLD signals.

PMID: 29107088 [PubMed - as supplied by publisher]

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