New resting-state fMRI related studies at PubMed

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Abnormalities of thalamus volume and resting state functional connectivity in primary insomnia patients.

Sat, 02/01/2020 - 16:40
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Abnormalities of thalamus volume and resting state functional connectivity in primary insomnia patients.

Brain Imaging Behav. 2019 Oct;13(5):1193-1201

Authors: Li M, Wang R, Zhao M, Zhai J, Liu B, Yu D, Yuan K

Abstract
Primary insomnia (PI) is associated with deteriorating attention, memory, physical and mood complaints. Based on the extensive literature demonstrating the critical roles of the thalamus in sleep regulation, we hypothesized that insomnia would be associated with functional and structural changes of the thalamus. This information is needed to better understand the neural mechanisms of insomnia, and would be useful for informing future attempts to alleviate or treat insomnia symptoms. Twenty-seven PI patients and 39 matched healthy controls were included in the present study. Subcortical volume and resting state functional connectivity (RSFC) of thalamus were compared between groups, and the relationships between neuroimaging differences and clinical features, including the Pittsburgh Sleep Quality Index (PSQI), the Insomnia Severity Index Scale (ISI), the Self-Rating Anxiety Scale (SAS) and the Self-Rating Depression Scale (SDS), also be explored. Compared with the control group, the PI group showed significantly reduced volume of thalamus. In addition, several brain regions showed reduced RSFC with thalamus in PI patients, such as anterior cingulate cortex (ACC), orbitofrontal cortex, hippocampus, caudate and putamen. Correlation analyses revealed that, several of these RSFC patterns were negatively correlated with PSQI score among PI patients, including thalamic connections with the putamen, caudate, hippocampus. Negative correlation was also observed between the RSFC strength of right thalamus-right ACC and SDS score in PI patients. This work demonstrates the structural and functional abnormalities of the thalamus in PI patients that were associated with key clinical features of insomnia. These data further highlight the important role of the thalamus in sleep and PI.

PMID: 30091019 [PubMed - indexed for MEDLINE]

Mapping correlations of psychological and structural connectome properties of the dataset of the human connectome project with the maximum spanning tree method.

Sat, 02/01/2020 - 16:40
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Mapping correlations of psychological and structural connectome properties of the dataset of the human connectome project with the maximum spanning tree method.

Brain Imaging Behav. 2019 Oct;13(5):1185-1192

Authors: Szalkai B, Varga B, Grolmusz V

Abstract
Genome-wide association studies (GWAS) opened new horizons in genomics and medicine by discovering novel genetic factors in numerous health conditions. The analogous analysis of the correlations of large quantities of psychological and brain imaging measures may yield similarly striking results in the brain science. Smith et al. (Nat Neurosci. 18(11): 1565-1567, 2015) presented a study of the associations between MRI-detected resting-state functional connectomes and behavioral data, based on the Human Connectome Project's (HCP) data release. Here we analyze the pairwise correlations between 717 psychological-, anatomical- and structural connectome-properties, based also on the Human Connectome Project's 500-subject dataset. For the connectome properties, we have focused on the structural (or anatomical) connectomes, instead of the functional connectomes. For the structural connectome analysis we have computed and publicly deposited structural braingraphs at the site http://braingraph.org . Numerous non-trivial and hard-to-compute graph-theoretical parameters (like minimum bisection width, minimum vertex cover, eigenvalue gap, maximum matching number, maximum fractional matching number) were computed for braingraphs of each subject, gained from the left- and right hemispheres and the whole brain. The correlations of these parameters, as well as other anatomical and behavioral measures were detected and analyzed. For discovering and visualizing the most interesting correlations in the 717 x 717 matrix, we have applied the maximum spanning tree method. Apart from numerous natural correlations, which describe parameters computable or approximable from one another, we have found several significant, novel correlations in the dataset, e.g., between the score of the NIH Toolbox 9-hole Pegboard Dexterity Test and the maximum weight graph theoretical matching in the left hemisphere. We also have found correlations described very recently and independently from the HCP-dataset: e.g., between gambling behavior and the number of the connections leaving the insula: these already known findings independently validate the power of our method.

PMID: 30088220 [PubMed - indexed for MEDLINE]

On the acquisition of the water signal during water suppression: High-speed MR spectroscopic imaging with water referencing and concurrent functional MRI.

Fri, 01/31/2020 - 16:00
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On the acquisition of the water signal during water suppression: High-speed MR spectroscopic imaging with water referencing and concurrent functional MRI.

NMR Biomed. 2020 Jan 30;:e4261

Authors: Posse S, Sa De La Rocque Guimaraes B, Hutchins-Delgado T, Vakamudi K, Fotso Tagne K, Moeller S, Dager SR

Abstract
This study evaluated the utility of concurrent water signal acquisition as part of the water suppression in MR spectroscopic imaging (MRSI), to allow simultaneous water referencing for metabolite quantification, and to concurrently acquire functional MRI (fMRI) data. We integrated a spatial-spectral binomial water excitation RF pulse and a short spatial-spectral echo-planar readout into the water suppression module of 2D and 3D proton-echo-planar-spectroscopic-imaging (PEPSI) with a voxel size as small as 4 x 4 x 6 mm3 . Metabolite quantification in reference to tissue water was validated in healthy controls for different prelocalization methods (spin-echo, PRESS and semi-LASER) and the clinical feasibility of a 3-minute 3D semi-Laser PEPSI scan (TR/TE: 1250/32 ms) with water referencing in patients with brain tumors was demonstrated. Spectral quality, SNR, Cramer-Rao-lower-bounds and water suppression efficiency were comparable with conventional PEPSI. Metabolite concentration values in reference to tissue water, using custom LCModel-based spectral fitting with relaxation correction, were in the range of previous studies and independent of the prelocalization method used. Next, we added a phase-encoding undersampled echo-volumar imaging (EVI) module during water suppression to concurrently acquire metabolite maps with water referencing and fMRI data during task execution and resting state in healthy controls. Integration of multimodal signal acquisition prolongated minimum TR by less than 50 ms on average. Visual and motor activation in concurrent fMRI/MRSI (TR: 1250-1500 ms, voxel size: 4 x 4 x 6 mm3 ) was readily detectable in single-task blocks with percent signal change comparable with conventional fMRI. Resting-state connectivity in sensory and motor networks was detectable in 4 minutes. This hybrid water suppression approach for multimodal imaging has the potential to significantly reduce scan time and extend neuroscience research and clinical applications through concurrent quantitative MRSI and fMRI acquisitions.

PMID: 31999397 [PubMed - as supplied by publisher]

Predictive Pattern Classification Can Distinguish Gender Identity Subtypes from Behavior and Brain Imaging.

Fri, 01/31/2020 - 16:00
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Predictive Pattern Classification Can Distinguish Gender Identity Subtypes from Behavior and Brain Imaging.

Cereb Cortex. 2020 Jan 29;:

Authors: Clemens B, Derntl B, Smith E, Junger J, Neulen J, Mingoia G, Schneider F, Abel T, Bzdok D, Habel U

Abstract
The exact neurobiological underpinnings of gender identity (i.e., the subjective perception of oneself belonging to a certain gender) still remain unknown. Combining both resting-state functional connectivity and behavioral data, we examined gender identity in cisgender and transgender persons using a data-driven machine learning strategy. Intrinsic functional connectivity and questionnaire data were obtained from cisgender (men/women) and transgender (trans men/trans women) individuals. Machine learning algorithms reliably detected gender identity with high prediction accuracy in each of the four groups based on connectivity signatures alone. The four normative gender groups were classified with accuracies ranging from 48% to 62% (exceeding chance level at 25%). These connectivity-based classification accuracies exceeded those obtained from a widely established behavioral instrument for gender identity. Using canonical correlation analyses, functional brain measurements and questionnaire data were then integrated to delineate nine canonical vectors (i.e., brain-gender axes), providing a multilevel window into the conventional sex dichotomy. Our dimensional gender perspective captures four distinguishable brain phenotypes for gender identity, advocating a biologically grounded reconceptualization of gender dimorphism. We hope to pave the way towards objective, data-driven diagnostic markers for gender identity and transgender, taking into account neurobiological and behavioral differences in an integrative modeling approach.

PMID: 31999324 [PubMed - as supplied by publisher]

Reduced Global-Brain Functional Connectivity and Its Relationship With Symptomatic Severity in Cervical Dystonia.

Fri, 01/31/2020 - 16:00
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Reduced Global-Brain Functional Connectivity and Its Relationship With Symptomatic Severity in Cervical Dystonia.

Front Neurol. 2019;10:1358

Authors: Pan P, Wei S, Ou Y, Jiang W, Li W, Lei Y, Liu F, Guo W, Luo S

Abstract
Background: Altered functional connectivity (FC) is related to pathophysiology of patients with cervical dystonia (CD). However, inconsistent results may be obtained due to different selected regions of interest. We explored voxel-wise brain-wide FC changes in patients with CD at rest in an unbiased manner and analyzed their correlations with symptomatic severity using the Tsui scale. Method: A total of 19 patients with CD and 21 sex- and age-matched healthy controls underwent resting-state functional magnetic resonance imaging scans. Global-brain FC (GFC) was applied to analyze the images. Support vector machine was used to distinguish the patients from the controls. Results: Patients with CD exhibited decreased GFC in the right precentral gyrus and right supplementary motor area (SMA) that belonged to the M1-SMA motor network. Significantly negative correlation was observed between GFC values in the right precentral gyrus and symptomatic severity in the patients (r = -0.476, p = 0.039, uncorrected). Decreased GFC values in these two brain regions could be utilized to differentiate the patients from the controls with good accuracies, sensitivities and specificities (83.33, 85.71, and 80.95% in the right precentral gyrus; and 87.59, 89.49, and 85.71% in the right SMA). Conclusions: Our investigation suggests that patients with CD show reduced GFC in brain regions of the M1-SMA motor network and provides further insights into the pathophysiology of CD. GFC values in the right precentral gyrus and right SMA may be used as potential biomarkers to recognize the patients from the controls.

PMID: 31998218 [PubMed]

Revealing Relationships Among Cognitive Functions Using Functional Connectivity and a Large-Scale Meta-Analysis Database.

Fri, 01/31/2020 - 16:00
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Revealing Relationships Among Cognitive Functions Using Functional Connectivity and a Large-Scale Meta-Analysis Database.

Front Hum Neurosci. 2019;13:457

Authors: Kurashige H, Kaneko J, Yamashita Y, Osu R, Otaka Y, Hanakawa T, Honda M, Kawabata H

Abstract
To characterize each cognitive function per se and to understand the brain as an aggregate of those functions, it is vital to relate dozens of these functions to each other. Knowledge about the relationships among cognitive functions is informative not only for basic neuroscientific research but also for clinical applications and developments of brain-inspired artificial intelligence. In the present study, we propose an exhaustive data mining approach to reveal relationships among cognitive functions based on functional brain mapping and network analysis. We began our analysis with 109 pseudo-activation maps (cognitive function maps; CFM) that were reconstructed from a functional magnetic resonance imaging meta-analysis database, each of which corresponds to one of 109 cognitive functions such as 'emotion,' 'attention,' 'episodic memory,' etc. Based on the resting-state functional connectivity between the CFMs, we mapped the cognitive functions onto a two-dimensional space where the relevant functions were located close to each other, which provided a rough picture of the brain as an aggregate of cognitive functions. Then, we conducted so-called conceptual analysis of cognitive functions using clustering of voxels in each CFM connected to the other 108 CFMs with various strengths. As a result, a CFM for each cognitive function was subdivided into several parts, each of which is strongly associated with some CFMs for a subset of the other cognitive functions, which brought in sub-concepts (i.e., sub-functions) of the cognitive function. Moreover, we conducted network analysis for the network whose nodes were parcels derived from whole-brain parcellation based on the whole-brain voxel-to-CFM resting-state functional connectivities. Since each parcel is characterized by associations with the 109 cognitive functions, network analyses using them are expected to inform about relationships between cognitive and network characteristics. Indeed, we found that informational diversities of interaction between parcels and densities of local connectivity were dependent on the kinds of associated functions. In addition, we identified the homogeneous and inhomogeneous network communities about the associated functions. Altogether, we suggested the effectiveness of our approach in which we fused the large-scale meta-analysis of functional brain mapping with the methods of network neuroscience to investigate the relationships among cognitive functions.

PMID: 31998102 [PubMed]

Corrigendum: Topological Modification of Brain Networks Organization in Children With High Intelligence Quotient: A Resting-State fMRI Study.

Fri, 01/31/2020 - 16:00
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Corrigendum: Topological Modification of Brain Networks Organization in Children With High Intelligence Quotient: A Resting-State fMRI Study.

Front Hum Neurosci. 2019;13:450

Authors: Suprano I, Delon-Martin C, Kocevar G, Stamile C, Hannoun S, Achard S, Badhwar A, Fourneret P, Revol O, Nusbaum F, Sappey-Marinier D

Abstract
[This corrects the article DOI: 10.3389/fnhum.2019.00241.].

PMID: 31998099 [PubMed - in process]

Healthy Subjects With Extreme Patterns of Performance Differ in Functional Network Topology and Benefits From Nicotine.

Fri, 01/31/2020 - 16:00
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Healthy Subjects With Extreme Patterns of Performance Differ in Functional Network Topology and Benefits From Nicotine.

Front Syst Neurosci. 2019;13:83

Authors: Gießing C, Ahrens S, Thiel CM

Abstract
Do subjects with atypical patterns in attentional and executive behaviour show different brain network topology and react differently towards nicotine administration? The efficacy of pro-cognitive drugs like nicotine considerably varies between subjects and previous theoretical and empirical evidence suggest stronger behavioural nicotine effects in subjects with low performance. One problem is, however, how to best define low performance, especially if several cognitive functions are assessed for subject characterisation. We here present a method that used a multivariate, robust outlier detection algorithm to identify subjects with suspicious patterns of performance in attentional and executive functioning. In contrast to univariate approaches, this method is sensitive towards extreme positions within the multidimensional space that do not have to be extreme values in the individual behavioural distributions. The method was applied to a dataset of healthy, non-smoking subjects (n = 34) who were behaviorally characterised by an attention and executive function test on which N = 12 volunteers were classified as outliers. All subjects then underwent a resting-state functional magnetic resonance imaging (fMRI) scan to characterise brain network topology and an experimental behavioural paradigm under placebo and nicotine (7 mg patch) that gauged aspects of attention and executive function. Our results indicate that subjects with an atypical multivariate pattern in attention and executive functioning showed significant differences in nodal brain network integration in visual association and pre-motor brain regions during resting state. These differences in brain network topology significantly predicted larger individual nicotine effects on attentional processing. In summary, the current approach successfully identified a subgroup of healthy volunteers with low behavioural performance who differ in brain network topology and attentional benefit from nicotine.

PMID: 31998085 [PubMed]

Abnormal brain activity in adolescents with Internet addiction who attempt suicide: an assessment using functional magnetic resonance imaging.

Fri, 01/31/2020 - 16:00
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Abnormal brain activity in adolescents with Internet addiction who attempt suicide: an assessment using functional magnetic resonance imaging.

Neural Regen Res. 2020 Aug;15(8):1554-1559

Authors: Huang Y, Xu L, Kuang L, Wang W, Cao J, Xiao MN

Abstract
Internet addiction is associated with an increased risk of suicidal behavior and can lead to brain dysfunction among adolescents. However, whether brain dysfunction occurs in adolescents with Internet addiction who attempt suicide remains unknown. This observational cross-sectional study enrolled 41 young Internet addicts, aged from 15 to 20 years, from the Department of Psychiatry, the First Affiliated Hospital of Chongqing Medical University, China from January to May 2018. The participants included 21 individuals who attempted suicide and 20 individuals with Internet addiction without a suicidal attempt history. Brain images in the resting state were obtained by a 3.0 T magnetic resonance imaging scanner. The results showed that activity in the gyrus frontalis inferior of the right pars triangularis and the right pars opercularis was significantly increased in the suicidal attempt group compared with the non-suicidal attempt group. In the resting state, the prefrontal lobe of adolescents who had attempted suicide because of Internet addiction exhibited functional abnormalities, which may provide a new basis for studying suicide pathogenesis in Internet addicts. The study was authorized by the Ethics Committee of Chongqing Medical University, China (approval No. 2017 Scientific Research Ethics (2017-157)) on December 11, 2017.

PMID: 31997822 [PubMed]

Multivariate Classification of Earthquake Survivors with Posttraumatic Stress Disorder Based on Large-scale Brain Networks.

Fri, 01/31/2020 - 16:00
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Multivariate Classification of Earthquake Survivors with Posttraumatic Stress Disorder Based on Large-scale Brain Networks.

Acta Psychiatr Scand. 2020 Jan 29;:

Authors: Zhu H, Yuan M, Qiu C, Ren Z, Li Y, Wang J, Huang X, Lui S, Gong Q, Zhang W, Zhang Y

Abstract
OBJECTIVE: The identification of posttraumatic stress disorder (PTSD) among natural disaster survivors is remarkably challenging, and there are no reliable objective signatures that can be used to assist clinical diagnosis and optimize treatment. The current study aimed to establish a neurobiological signature of PTSD from the connectivity of large-scale brain networks and clarify the brain network mechanisms of PTSD.
METHODS: We examined fifty-seven unmedicated survivors with chronic PTSD and 59 matched trauma-exposed healthy controls (TEHCs) using resting-state functional magnetic resonance imaging (rs-fMRI). We extracted the node-to-network connectivity and obtained a feature vector with a dimensionality of 864 (108 nodes× 8 networks) to represent each subject's functional connectivity (FC) profile. Multivariate pattern analysis with a relevance vector machine was then used to distinguish PTSD patients from TEHCs.
RESULTS: We achieved a promising diagnostic accuracy of 89.2% in distinguishing PTSD patients from TEHCs. The most heavily weighted connections for PTSD classification were among the default mode network (DMN), visual network (VIS), somatomotor network, limbic network, and dorsal attention network (DAN). The strength of the anticorrelation of FC between the ventral medial prefrontal cortex (vMPFC) in DMN and the VIS and DAN was associated with the severity of PTSD.
CONCLUSIONS: This study achieved relatively high accuracy in classifying PTSD patients versus TEHCs at the individual level. This performance demonstrates that rs-fMRI-derived multivariate classification based on large-scale brain networks can provide potential signatures both to facilitate clinical diagnosis and to clarify the underlying brain network mechanisms of PTSD caused by natural disasters.

PMID: 31997301 [PubMed - as supplied by publisher]

Exploring the Correlation Between M/EEG Source-Space and fMRI Networks at Rest.

Fri, 01/31/2020 - 16:00
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Exploring the Correlation Between M/EEG Source-Space and fMRI Networks at Rest.

Brain Topogr. 2020 Jan 29;:

Authors: Rizkallah J, Amoud H, Fraschini M, Wendling F, Hassan M

Abstract
Magneto/electro-encephalography (M/EEG) source connectivity is an emerging approach to estimate brain networks with high temporal and spatial resolutions. Here, we aim to evaluate the effect of functional connectivity (FC) methods on the correlation between M/EEG source-space and fMRI networks at rest. Two main FC families are tested: (i) FC methods that do not remove zero-lag connectivity including Phase Locking Value (PLV) and Amplitude Envelope Correlation (AEC) and (ii) FC methods that remove zero-lag connections such as Phase Lag Index (PLI) and two orthogonalisation approaches combined with PLV (PLVCol, PLVPas) and AEC (AECCol, AECPas). Methods are evaluated on resting state M/EEG signals recorded from healthy participants at rest (N = 74). Networks obtained by each FC method are compared with fMRI networks (obtained from the Human Connectome Project). Results show low correlations for all FC methods, however PLV and AEC networks are significantly correlated with fMRI networks (ρ = 0.12, p = 1.93 × 10-8 and ρ = 0.06, p = 0.007, respectively), while other methods are not. These observations are consistent for all M/EEG frequency bands and for different FC matrices threshold. Our main message is to be careful in selecting FC methods when comparing or combining M/EEG with fMRI. We consider that more comparative studies based on simulation and real data and at different levels (node, module or sub networks) are still needed in order to improve our understanding on the relationships between M/EEG source-space networks and fMRI networks at rest.

PMID: 31997058 [PubMed - as supplied by publisher]

Influence of 4-week multi-strain probiotic administration on resting-state functional connectivity in healthy volunteers.

Fri, 01/31/2020 - 16:00
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Influence of 4-week multi-strain probiotic administration on resting-state functional connectivity in healthy volunteers.

Eur J Nutr. 2019 Aug;58(5):1821-1827

Authors: Bagga D, Aigner CS, Reichert JL, Cecchetto C, Fischmeister FPS, Holzer P, Moissl-Eichinger C, Schöpf V

Abstract
PURPOSE: Experimental investigations in rodents have contributed significantly to our current understanding of the potential importance of the gut microbiome and brain interactions for neurotransmitter expression, neurodevelopment, and behaviour. However, clinical evidence to support such interactions is still scarce. The present study used a double-blind, randomized, pre- and post-intervention assessment design to investigate the effects of a 4-week multi-strain probiotic administration on whole-brain functional and structural connectivity in healthy volunteers.
METHODS: Forty-five healthy volunteers were recruited for this study and were divided equally into three groups (PRP: probiotic, PLP: placebo, and CON: control). All the participants underwent resting-state functional MRI and diffusion MRI brain scans twice during the course of study, at the beginning (time point 1) and after 4 weeks (time point 2). MRI data were acquired using a 3T whole-body MR system (Magnetom Skyra, Siemens, Germany).
RESULTS: Functional connectivity (FC) changes were observed in the default mode network (DMN), salience network (SN), and middle and superior frontal gyrus network (MFGN) in the PRP group as compared to the PLP and CON groups. PRP group showed a significant decrease in FC in MFGN (in frontal pole and frontal medial cortex) and in DMN (in frontal lobe) as compared to CON and PLP groups, respectively. Further, significant increase in FC in SN (in cingulate gyrus and precuneus cortex) was also observed in PRP group as compared to CON group. The significance threshold was set to p < 0.05 FWE corrected. No significant structural differences were observed between the three groups.
CONCLUSIONS: This work provides new insights into the role of a multi-strain probiotic administration in modulating the behaviour, which is reflected as changes in the FC in healthy volunteers. This study motivates future investigations into the role of probiotics in context of major depression and stress disorders.

PMID: 29850990 [PubMed - indexed for MEDLINE]

Evaluating global brain connectivity as an imaging marker for depression: influence of preprocessing strategies and placebo-controlled ketamine treatment.

Thu, 01/30/2020 - 14:40
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Evaluating global brain connectivity as an imaging marker for depression: influence of preprocessing strategies and placebo-controlled ketamine treatment.

Neuropsychopharmacology. 2020 Jan 29;:

Authors: Kraus C, Mkrtchian A, Kadriu B, Nugent AC, Zarate CA, Evans JW

Abstract
Major depressive disorder (MDD) is associated with altered global brain connectivity (GBC), as assessed via resting-state functional magnetic resonance imaging (rsfMRI). Previous studies found that antidepressant treatment with ketamine normalized aberrant GBC changes in the prefrontal and cingulate cortices, warranting further investigations of GBC as a putative imaging marker. These results were obtained via global signal regression (GSR). This study is an independent replication of that analysis using a separate dataset. GBC was analyzed in 28 individuals with MDD and 22 healthy controls (HCs) at baseline, post placebo, and post ketamine. To investigate the effects of preprocessing, three distinct pipelines were used: (1) regression of white matter (WM)/cerebrospinal fluid (CSF) signals only (BASE); (2) WM/CSF + GSR (GSR); and (3) WM/CSF + physiological parameter regression (PHYSIO). Reduced GBC was observed in individuals with MDD only at baseline in the anterior and medial cingulate cortices, as well as in the prefrontal cortex only after regressing the global signal. Ketamine had no effect compared to baseline or placebo in either group in any pipeline. PHYSIO did not resemble GBC preprocessed with GSR. These results concur with several studies that used GSR to study GBC. Further investigations are warranted into disease-specific components of global fMRI signals that may drive these results and of GBCr as a potential imaging marker in MDD.

PMID: 31995812 [PubMed - as supplied by publisher]

Altered Default Mode Network Dynamics in Civil Aviation Pilots.

Thu, 01/30/2020 - 14:40
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Altered Default Mode Network Dynamics in Civil Aviation Pilots.

Front Neurosci. 2019;13:1406

Authors: Chen X, Xu K, Yang Y, Wang Q, Jiang H, Guo X, Chen X, Yang J, Luo C

Abstract
Background: Airlines occupy an increasingly important place in the economy of many countries. Because air disasters may cause substantial losses, comprehensive surveys of the psychophysiological mechanism of flying are needed; however, relatively few studies have focused on pilots. The default mode network (DMN) is an important intrinsic connectivity network involved in a range of functions related to flying. This study aimed to examine functional properties of the DMN in pilots.
Method: Resting-state functional magnetic resonance imaging data from 26 pilots and 24 controls were collected. Independent component analysis, a data-driven approach, was combined with functional connectivity analysis to investigate functional properties of the DMN in pilots.
Results: The pilot group exhibited increased functional integration in the precuneus/posterior cingulate cortex (PCC) and left middle occipital gyrus. Subsequent functional connectivity analysis identified enhanced functional connection between the precuneus/PCC and medial superior frontal gyrus.
Conclusion: The pilot group exhibited increased functional connections within the DMN. These findings highlight the importance of the DMN in the neurophysiological mechanism of flying.

PMID: 31992967 [PubMed]

Rethinking Measures of Functional Connectivity via Feature Extraction.

Thu, 01/30/2020 - 14:40
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Rethinking Measures of Functional Connectivity via Feature Extraction.

Sci Rep. 2020 Jan 28;10(1):1298

Authors: Mohanty R, Sethares WA, Nair VA, Prabhakaran V

Abstract
Functional magnetic resonance imaging (fMRI)-based functional connectivity (FC) commonly characterizes the functional connections in the brain. Conventional quantification of FC by Pearson's correlation captures linear, time-domain dependencies among blood-oxygen-level-dependent (BOLD) signals. We examined measures to quantify FC by investigating: (i) Is Pearson's correlation sufficient to characterize FC? (ii) Can alternative measures better quantify FC? (iii) What are the implications of using alternative FC measures? FMRI analysis in healthy adult population suggested that: (i) Pearson's correlation cannot comprehensively capture BOLD inter-dependencies. (ii) Eight alternative FC measures were similarly consistent between task and resting-state fMRI, improved age-based classification and provided better association with behavioral outcomes. (iii) Formulated hypotheses were: first, in lieu of Pearson's correlation, an augmented, composite and multi-metric definition of FC is more appropriate; second, canonical large-scale brain networks may depend on the chosen FC measure. A thorough notion of FC promises better understanding of variations within a given population.

PMID: 31992762 [PubMed - in process]

Conservative and disruptive modes of adolescent change in human brain functional connectivity.

Thu, 01/30/2020 - 14:40
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Conservative and disruptive modes of adolescent change in human brain functional connectivity.

Proc Natl Acad Sci U S A. 2020 Jan 28;:

Authors: Váša F, Romero-Garcia R, Kitzbichler MG, Seidlitz J, Whitaker KJ, Vaghi MM, Kundu P, Patel AX, Fonagy P, Dolan RJ, Jones PB, Goodyer IM, NSPN Consortium, Vértes PE, Bullmore ET

Abstract
Adolescent changes in human brain function are not entirely understood. Here, we used multiecho functional MRI (fMRI) to measure developmental change in functional connectivity (FC) of resting-state oscillations between pairs of 330 cortical regions and 16 subcortical regions in 298 healthy adolescents scanned 520 times. Participants were aged 14 to 26 y and were scanned on 1 to 3 occasions at least 6 mo apart. We found 2 distinct modes of age-related change in FC: "conservative" and "disruptive." Conservative development was characteristic of primary cortex, which was strongly connected at 14 y and became even more connected in the period from 14 to 26 y. Disruptive development was characteristic of association cortex and subcortical regions, where connectivity was remodeled: connections that were weak at 14 y became stronger during adolescence, and connections that were strong at 14 y became weaker. These modes of development were quantified using the maturational index (MI), estimated as Spearman's correlation between edgewise baseline FC (at 14 y, [Formula: see text]) and adolescent change in FC ([Formula: see text]), at each region. Disruptive systems (with negative MI) were activated by social cognition and autobiographical memory tasks in prior fMRI data and significantly colocated with prior maps of aerobic glycolysis (AG), AG-related gene expression, postnatal cortical surface expansion, and adolescent shrinkage of cortical thickness. The presence of these 2 modes of development was robust to numerous sensitivity analyses. We conclude that human brain organization is disrupted during adolescence by remodeling of FC between association cortical and subcortical areas.

PMID: 31992644 [PubMed - as supplied by publisher]

Alterations of connectivity patterns in functional brain networks in patients with mild traumatic brain injury: A longitudinal resting-state functional magnetic resonance imaging study.

Thu, 01/30/2020 - 14:40
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Alterations of connectivity patterns in functional brain networks in patients with mild traumatic brain injury: A longitudinal resting-state functional magnetic resonance imaging study.

Neuroradiol J. 2020 Jan 28;:1971400920901706

Authors: D'Souza MM, Kumar M, Choudhary A, Kaur P, Kumar P, Rana P, Trivedi R, Sekhri T, Singh AK

Abstract
AIM: In the present study, we aimed to characterise changes in functional brain networks in individuals who had sustained uncomplicated mild traumatic brain injury (mTBI). We assessed the progression of these changes into the chronic phase. We also attempted to explore how these changes influenced the severity of post-concussion symptoms as well as the cognitive profile of the patients.
METHODS: A total of 65 patients were prospectively recruited for an advanced magnetic resonance imaging (MRI) scan within 7 days of sustaining mTBI. Of these, 25 were reassessed at 6 months post injury. Differences in functional brain networks were analysed between cases and age- and sex-matched healthy controls using independent component analysis of resting-state functional MRI.
RESULTS: Our study revealed reduced functional connectivity in multiple networks, including the anterior default mode network, central executive network, somato-motor and auditory network in patients who had sustained mTBI. A negative correlation between network connectivity and severity of post-concussive symptoms was observed. Follow-up studies performed 6 months after injury revealed an increase in network connectivity, along with an improvement in the severity of post-concussion symptoms. Neurocognitive tests performed at this time point revealed a positive correlation between the functional connectivity and the test scores, along with a persistence of negative correlation between network connectivity and post-concussive symptom severity.
CONCLUSION: Our results suggest that uncomplicated mTBI is associated with specific abnormalities in functional brain networks that evolve over time and may contribute to the severity of post-concussive symptoms and cognitive deficits.

PMID: 31992126 [PubMed - as supplied by publisher]

Functional Connectivity of Frontoparietal and Salience/Ventral Attention Networks Have Independent Associations With Co-occurring Attention-Deficit/Hyperactivity Disorder Symptoms in Children With Autism.

Thu, 01/30/2020 - 14:40
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Functional Connectivity of Frontoparietal and Salience/Ventral Attention Networks Have Independent Associations With Co-occurring Attention-Deficit/Hyperactivity Disorder Symptoms in Children With Autism.

Biol Psychiatry Cogn Neurosci Neuroimaging. 2019 04;4(4):343-351

Authors: Yerys BE, Tunç B, Satterthwaite TD, Antezana L, Mosner MG, Bertollo JR, Guy L, Schultz RT, Herrington JD

Abstract
BACKGROUND: Children with autism spectrum disorder (ASD) and co-occurring attention-deficit/hyperactivity disorder (ADHD) symptoms have worse functional outcomes and treatment response than those without ADHD symptoms. There is limited knowledge of the neurobiology of ADHD symptoms in ASD. Here, we test the hypothesis that aberrant functional connectivity of two large-scale executive brain networks implicated in ADHD-the frontoparietal and salience/ventral attention networks-also play a role in ADHD symptoms in ASD.
METHODS: We compared resting-state functional connectivity of the two executive brain networks in children with ASD (n = 77) and typically developing control children (n = 82). These two executive brain networks comprise five subnetworks (three frontoparietal, two salience/ventral attention). After identifying aberrant functional connections among subnetworks, we examined dimensional associations with parent-reported ADHD symptoms.
RESULTS: Weaker functional connectivity in ASD was present within and between the frontoparietal and salience/ventral attention subnetworks. Decreased functional connectivity within a single salience/ventral attention subnetwork, as well as between two frontoparietal subnetworks, significantly correlated with ADHD symptoms. Furthermore, follow-up linear regressions demonstrated that the salience/ventral attention and frontoparietal subnetworks explain unique variance in ADHD symptoms. These executive brain network-ADHD symptom relationships remained significant after controlling for ASD symptoms. Finally, specificity was also demonstrated through the use of a control brain network (visual) and a control co-occurring symptom domain (anxiety).
CONCLUSIONS: The present findings provide novel evidence that both frontoparietal and salience/ventral attention networks' weaker connectivities are linked to ADHD symptoms in ASD. Moreover, co-occurring ADHD in the context of ASD is a source of meaningful neural heterogeneity in ASD.

PMID: 30777604 [PubMed - indexed for MEDLINE]

Patterns of intrinsic brain activity in essential tremor with resting tremor and tremor-dominant Parkinson's disease.

Wed, 01/29/2020 - 13:20
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Patterns of intrinsic brain activity in essential tremor with resting tremor and tremor-dominant Parkinson's disease.

Brain Imaging Behav. 2020 Jan 27;:

Authors: Li JY, Lu ZJ, Suo XL, Li NN, Lei D, Wang L, Peng JX, Duan LR, Xi J, Jiang Y, Gong QY, Peng R

Abstract
The clinical pictures of essential tremor (ET) with resting tremor (rET) and tremor-dominant Parkinson's disease (tPD) are often quite mimic at the early stage, current approaches to the diagnosis and treatment therefore remain challenging. The regional homogeneity (ReHo) method under resting-state functional magnetic resonance imaging (rs-fMRI) would help exhibit the patterns in neural activity, which further contribute to differentiate these disorders and explore the relationship between symptoms and regional functional abnormalities. Sixty-eight Chinese participants were recruited, including 19 rET patients, 24 tPD patients and 25 age- and gender-matched healthy controls (HCs). All participants underwent clinical assessment and rs-fMRI with a ReHo method to investigate the alterations of neural activity, and the correlation between them. Differences were compared by two-sample t-test (corrected with AlphaSim, p < 0.05). Compared with HCs, patients' groups both displayed decreased ReHo in the default mode network (DMN), bilateral putamen and bilateral cerebellum. While tPD patients specifically exihibited decreased ReHo in the bilateral supplementary motor area (SMA) and precentral gyrus (M1). The correlation analysis revealed that ReHo in the bilateral putamen, right SMA and left cerebellum_crus I were negatively correlated with the UPDRS-III score, respectively, in tPD group. Our results indicated the rET patients may share part of the pathophysiological mechanism of tPD patients. In addition, we found disorder-specific involvement of the SMA and M1 in tPD. Such a distinction may lend itself to use as a potential biomarker for differentiating between these two diseases.

PMID: 31989422 [PubMed - as supplied by publisher]

Resting-state connectivity stratifies premanifest Huntington's disease by longitudinal cognitive decline rate.

Wed, 01/29/2020 - 13:20
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Resting-state connectivity stratifies premanifest Huntington's disease by longitudinal cognitive decline rate.

Sci Rep. 2020 Jan 27;10(1):1252

Authors: Polosecki P, Castro E, Rish I, Pustina D, Warner JH, Wood A, Sampaio C, Cecchi GA

Abstract
Patient stratification is critical for the sensitivity of clinical trials at early stages of neurodegenerative disorders. In Huntington's disease (HD), genetic tests make cognitive, motor and brain imaging measurements possible before symptom manifestation (pre-HD). We evaluated pre-HD stratification models based on single visit resting-state functional MRI (rs-fMRI) data that assess observed longitudinal motor and cognitive change rates from the multisite Track-On HD cohort (74 pre-HD, 79 control participants). We computed longitudinal performance change on 10 tasks (including visits from the preceding TRACK-HD study when available), as well as functional connectivity density (FCD) maps in single rs-fMRI visits, which showed high test-retest reliability. We assigned pre-HD subjects to subgroups of fast, intermediate, and slow change along single tasks or combinations of them, correcting for expectations based on aging; and trained FCD-based classifiers to distinguish fast- from slow-progressing individuals. For robustness, models were validated across imaging sites. Stratification models distinguished fast- from slow-changing participants and provided continuous assessments of decline applicable to the whole pre-HD population, relying on previously-neglected white matter functional signals. These results suggest novel correlates of early deterioration and a robust stratification strategy where a single MRI measurement provides an estimate of multiple ongoing longitudinal changes.

PMID: 31988371 [PubMed - in process]

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