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

Fri, 01/31/2020 - 20:11

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 - 20:11

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]

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

Fri, 01/31/2020 - 20:11
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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 - 20:11
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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]

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

Thu, 01/30/2020 - 20:10
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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 - 20:10
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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 - 20:10
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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 - 20:10
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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]

Magnetic resonance imaging of neuroinflammation in chronic pain: a role for astrogliosis?

Wed, 01/29/2020 - 20:09

Magnetic resonance imaging of neuroinflammation in chronic pain: a role for astrogliosis?

Pain. 2020 Jan 25;:

Authors: Jung C, Ichesco E, Ratai EM, Gonzalez RG, Burdo T, Loggia ML, Harris RE, Napadow V

Abstract
Non-invasive measures of neuroinflammatory processes in humans could substantially aid diagnosis and therapeutic development for many disorders, including chronic pain. Several proton Magnetic Resonance Spectroscopy (H-MRS) metabolites have been linked with glial activity (i.e. choline and myo-inositol) and found to be altered in chronic pain patients, but their role in the neuroinflammatory cascade is not well known. Our multimodal study evaluated resting fMRI connectivity and H-MRS metabolite concentration in insula cortex in 43 patients suffering from fibromyalgia, a chronic centralized pain disorder previously demonstrated to include a neuroinflammatory component, and 16 healthy controls. Patients demonstrated elevated choline (but not myo-inositol) in anterior insula (p=0.03), with greater choline levels linked with worse pain interference (r=0.41, p=0.01). In addition, reduced resting functional connectivity between anterior insula and putamen was associated with both pain interference (whole brain analysis, pcorrected<0.01) and elevated anterior insula choline (r=-0.37, p=0.03). In fact, anterior insula/putamen connectivity statistically mediated the link between anterior insula choline and pain interference (p<0.01), highlighting the pathway by which neuroinflammation can impact clinical pain dysfunction. In order to further elucidate the molecular substrates of the effects observed, we investigated how putative neuroinflammatory H-MRS metabolites are linked with ex-vivo tissue inflammatory markers in a nonhuman primate model of neuroinflammation. Results demonstrated that cortical choline levels were correlated with glial fibrillary acidic protein, a known marker for astrogliosis (Spearman r=0.49, p=0.03). Choline, a putative neuroinflammatory H-MRS assessed metabolite elevated in fibromyalgia and associated with pain interference, may be linked with astrogliosis in these patients.

PMID: 31990749 [PubMed - as supplied by publisher]

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

Wed, 01/29/2020 - 20:09
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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 - 20:09
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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]

Topographic mapping as a basic principle of functional organization for visual and prefrontal functional connectivity.

Wed, 01/29/2020 - 20:09
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Topographic mapping as a basic principle of functional organization for visual and prefrontal functional connectivity.

eNeuro. 2020 Jan 27;:

Authors: O'Rawe JF, Leung HC

Abstract
The organization of region-to-region functional connectivity has major implications for understanding information transfer and transformation between brain regions. We extended connective field mapping methodology to 3-dimensional anatomical space to derive estimates of cortico-cortical functional organization. Using multiple publicly available human (both male and female) resting-state fMRI data samples for model testing and replication analysis, we have three main findings. First, we found that the functional connectivity between early visual regions maintained a topographic relationship along the anterior-posterior dimension, which corroborates previous research. Higher order visual regions showed a pattern of connectivity that supports convergence and biased sampling, which has implications for their receptive field properties. Second, we demonstrated that topographic organization is a fundamental aspect of functional connectivity across the entire cortex, with higher topographic connectivity between regions within a functional network than across networks. The principle gradient of topographic connectivity across the cortex resembled whole brain gradients found in previous work. Last but not least, we showed that the organization of higher order regions such as the lateral prefrontal cortex demonstrate functional gradients of topographic connectivity and convergence. These organizational features of the lateral prefrontal cortex predict task based activation patterns, particularly visual specialization and higher order rules. In sum, these findings suggest that topographic input is a fundamental motif of functional connectivity between cortical regions for information processing and transfer, with maintenance of topography potentially important for preserving the integrity of information from one region to another.Significance Statement Quantifying spatial patterns of region-to-region functional connectivity provides an avenue for testing theories of corticocortical information transformation and organization. This work demonstrates that this quantification is feasible not only in early visual cortex, but even in highly multimodal regions where spatial topography is less clear. Overall, we show that topographic relationships as a common motif functional connectivity across the cortex between regions within the same functional network and that analyzing the lateral prefrontal cortex in terms of topographic connectivity reveals organizational features that voxelwise connectivity analysis misses.

PMID: 31988218 [PubMed - as supplied by publisher]

Portable, field-based neuroimaging using high-density diffuse optical tomography.

Wed, 01/29/2020 - 20:09
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Portable, field-based neuroimaging using high-density diffuse optical tomography.

Neuroimage. 2020 Jan 24;:116541

Authors: Fishell AK, Arbeláez AM, Valdés CP, Burns-Yocum TM, Sherafati A, Richter EJ, Torres M, Eggebrecht AT, Smyser CD, Culver JP

Abstract
Behavioral and cognitive tests in individuals who were malnourished as children have revealed malnutrition-related deficits that persist throughout the lifespan. These findings have motivated recent neuroimaging investigations that use highly portable functional near-infrared spectroscopy (fNIRS) instruments to meet the demands of brain imaging experiments in low-resource environments and enable longitudinal investigations of brain function in the context of long-term malnutrition. However, recent studies in healthy subjects have demonstrated that high-density diffuse optical tomography (HD-DOT) can significantly improve image quality over that obtained with sparse fNIRS imaging arrays. In studies of both task activations and resting state functional connectivity, HD-DOT is beginning to approach the data quality of fMRI for superficial cortical regions. In this work, we developed a customized HD-DOT system for use in malnutrition studies in Cali, Colombia. Our results evaluate the performance of the HD-DOT instrument for assessing brain function in a cohort of malnourished children. In addition to demonstrating portability and wearability, we show the HD-DOT instrument's sensitivity to distributed brain responses using a sensory processing task and measurements of homotopic functional connectivity. Task-evoked responses to the passive word listening task produce activations localized to bilateral superior temporal gyrus, replicating previously published work using this paradigm. Evaluating this localization performance across sparse and dense reconstruction schemes indicates that greater localization consistency is associated with a dense array of overlapping optical measurements. These results provide a foundation for additional avenues of investigation, including identifying and characterizing a child's individual malnutrition burden and eventually contributing to intervention development.

PMID: 31987995 [PubMed - as supplied by publisher]

Graph theory analysis of functional connectivity combined with machine learning approaches demonstrate widespread network differences and predict clinical variables in temporal lobe epilepsy.

Tue, 01/28/2020 - 20:06

Graph theory analysis of functional connectivity combined with machine learning approaches demonstrate widespread network differences and predict clinical variables in temporal lobe epilepsy.

Brain Connect. 2020 Jan 26;:

Authors: Mazrooyisedani M, Nair VA, Camille Garcia-Ramos C, Mohanty R, Meyerand ME, Hermann B, Prabhakaran V, Ahmed R

Abstract
Understanding how global brain networks are affected in epilepsy may elucidate the pathogenesis of seizures and its accompanying neurobehavioral comorbidities. We investigated functional changes within neural networks in temporal lobe epilepsy (TLE) using graph theory analysis of resting-state connectivity. 27 TLE presurgical patients (age 41.0 ± 12.3 years), and 85 age, gender and handedness equivalent healthy controls (HC) (age 39.7±16.9 years) were enrolled. Eyes-closed resting-state fMRI scans were analyzed to compare network properties and functional connectivity changes. TLE subjects showed significantly higher global efficiency, lower clustering coefficient ratio and lower shortest path lengths ratio compared to HC, as an indication of a more synchronized, yet less segregated network. A trend of functional reorganization with a shift of network hubs to the contralateral hemisphere was noted in TLE subjects. Support vector machine (SVM) with linear kernel was trained to separate between neural networks in TLE and HC subjects based on graph measurements. SVM analysis allowed separation between TLE and HC networks with 80.66% accuracy using 8 features of graph measurements. Support vector regression (SVR) was used to predict neurocognitive performance from graph metrics. A SVR linear predictor showed discriminative prediction accuracy for 4 key neurocognitive variables in TLE (absolute R-value range: 0.61 - 0.75) Despite temporal onset of epilepsy, our results showed both local and global network topology differences that reflect widespread alterations in functional connectivity in TLE. Network differences are discriminative between TLE and HCs using data driven analysis and predicted severity of neurocognitive sequelae in our cohort.

PMID: 31984759 [PubMed - as supplied by publisher]

Decreased functional connectivity of hippocampal subregions and methylation of the NR3C1 gene in Han Chinese adults who lost their only child.

Tue, 01/28/2020 - 20:06
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Decreased functional connectivity of hippocampal subregions and methylation of the NR3C1 gene in Han Chinese adults who lost their only child.

Psychol Med. 2020 Jan 27;:1-10

Authors: Qi R, Luo Y, Zhang L, Weng Y, Surento W, Xu Q, Jahanshad N, Li L, Cao Z, Lu GM, Thompson PM

Abstract
BACKGROUND: Losing one's only child is a major traumatic life event that may lead to post-traumatic stress disorder (PTSD); however, the underlying mechanisms of its psychological consequences remain poorly understood. Here, we investigated subregional hippocampal functional connectivity (FC) networks based on resting-state functional magnetic resonance imaging and the deoxyribonucleic acid methylation of the human glucocorticoid receptor gene (NR3C1) in adults who had lost their only child.
METHODS: A total of 144 Han Chinese adults who had lost their only child (51 adults with PTSD and 93 non-PTSD adults [trauma-exposed controls]) and 50 controls without trauma exposure were included in this fMRI study (age: 40-67 years). FCs between hippocampal subdivisions (four regions in each hemisphere: cornu ammonis1 [CA1], CA2, CA3, and dentate gyrus [DG]) and methylation levels of the NR3C1 gene were compared among the three groups.
RESULTS: Trauma-exposed adults, regardless of PTSD diagnosis, had weaker positive FC between the left hippocampal CA1, left DG, and the posterior cingulate cortex, and weaker negative FC between the right CA1, right DG, and several frontal gyri, relative to healthy controls. Compared to non-PTSD adults, PTSD adults showed decreased negative FC between the right CA1 region and the right middle/inferior frontal gyri (MFG/IFG), and decreased negative FC between the right DG and the right superior frontal gyrus and left MFG. Both trauma-exposed groups showed lower methylation levels of the NR3C1 gene.
CONCLUSIONS: Adults who had lost their only child may experience disrupted hippocampal network connectivity and NR3C1 methylation status, regardless of whether they have developed PTSD.

PMID: 31983347 [PubMed - as supplied by publisher]

Targeting the centromedian thalamic nucleus for deep brain stimulation.

Sun, 01/26/2020 - 23:04
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Targeting the centromedian thalamic nucleus for deep brain stimulation.

J Neurol Neurosurg Psychiatry. 2020 Jan 24;:

Authors: Warren AEL, Dalic LJ, Thevathasan W, Roten A, Bulluss KJ, Archer J

Abstract
OBJECTIVES: Deep brain stimulation (DBS) of the centromedian thalamic nucleus (CM) is an emerging treatment for multiple brain diseases, including the drug-resistant epilepsy Lennox-Gastaut syndrome (LGS). We aimed to improve neurosurgical targeting of the CM by: (1) developing a structural MRI approach for CM visualisation, (2) identifying the CM's neurophysiological characteristics using microelectrode recordings (MERs) and (3) mapping connectivity from CM-DBS sites using functional MRI (fMRI).
METHODS: 19 patients with LGS (mean age=28 years) underwent presurgical 3T MRI using magnetisation-prepared 2 rapid acquisition gradient-echoes (MP2RAGE) and fMRI sequences; 16 patients proceeded to bilateral CM-DBS implantation and intraoperative thalamic MERs. CM visualisation was achieved by highlighting intrathalamic borders on MP2RAGE using Sobel edge detection. Mixed-effects analysis compared two MER features (spike firing rate and background noise) between ventrolateral, CM and parafasicular nuclei. Resting-state fMRI connectivity was assessed using implanted CM-DBS electrode positions as regions of interest.
RESULTS: The CM appeared as a hyperintense region bordering the comparatively hypointense pulvinar, mediodorsal and parafasicular nuclei. At the group level, reduced spike firing and background noise distinguished CM from the ventrolateral nucleus; however, these trends were not found in 20%-25% of individual MER trajectories. Areas of fMRI connectivity included basal ganglia, brainstem, cerebellum, sensorimotor/premotor and limbic cortex.
CONCLUSIONS: In the largest clinical trial of DBS undertaken in patients with LGS to date, we show that accurate targeting of the CM is achievable using 3T MP2RAGE MRI. Intraoperative MERs may provide additional localising features in some cases; however, their utility is limited by interpatient variability. Therapeutic effects of CM-DBS may be mediated via connectivity with brain networks that support diverse arousal, cognitive and sensorimotor processes.

PMID: 31980515 [PubMed - as supplied by publisher]

Hippocampal plasticity underpins long-term cognitive gains from resistance exercise in MCI.

Sat, 01/25/2020 - 20:02
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Hippocampal plasticity underpins long-term cognitive gains from resistance exercise in MCI.

Neuroimage Clin. 2020 Jan 14;25:102182

Authors: Broadhouse KM, Singh MF, Suo C, Gates N, Wen W, Brodaty H, Jain N, Wilson GC, Meiklejohn J, Singh N, Baune BT, Baker M, Foroughi N, Wang Y, Kochan N, Ashton K, Brown M, Li Z, Mavros Y, Sachdev PS, J Valenzuela M

Abstract
Dementia affects 47 million individuals worldwide, and assuming the status quo is projected to rise to 150 million by 2050. Prevention of age-related cognitive impairment in older persons with lifestyle interventions continues to garner evidence but whether this can combat underlying neurodegeneration is unknown. The Study of Mental Activity and Resistance Training (SMART) trial has previously reported within-training findings; the aim of this study was to investigate the long-term neurostructural and cognitive impact of resistance exercise in Mild Cognitive Impairment (MCI). For the first time we show that hippocampal subareas particularly susceptible to volume loss in Alzheimer's disease (AD) are protected by resistance exercise for up to one year after training. One hundred MCI participants were randomised to one of four training groups: (1) Combined high intensity progressive resistance and computerised cognitive training (PRT+CCT), (2) PRT+Sham CCT, (3) CCT+Sham PRT, (4) Sham physical+sham cognitive training (SHAM+SHAM). Physical, neuropsychological and MRI assessments were carried out at baseline, 6 months (directly after training) and 18 months from baseline (12 months after intervention cessation). Here we report neuro-structural and functional changes over the 18-month trial period and the association with global cognitive and executive function measures. PRT but not CCT or PRT+CCT led to global long-term cognitive improvements above SHAM intervention at 18-month follow-up. Furthermore, hippocampal subfields susceptible to atrophy in AD were protected by PRT revealing an elimination of long-term atrophy in the left subiculum, and attenuation of atrophy in left CA1 and dentate gyrus when compared to SHAM+SHAM (p = 0.023, p = 0.020 and p = 0.027). These neuroprotective effects mediated a significant portion of long-term cognitive benefits. By contrast, within-training posterior cingulate plasticity decayed after training cessation and was unrelated to long term cognitive benefits. Neither general physical activity levels nor fitness change over the 18-month period mediated hippocampal trajectory, demonstrating that enduring hippocampal subfield plasticity is not a simple reflection of post-training changes in fitness or physical activity participation. Notably, resting-state fMRI analysis revealed that both the hippocampus and posterior cingulate participate in a functional network that continued to be upregulated following intervention cessation. Multiple structural mechanisms may contribute to the long-term global cognitive benefit of resistance exercise, developing along different time courses but functionally linked. For the first time we show that 6 months of high intensity resistance exercise is capable of not only promoting better cognition in those with MCI, but also protecting AD-vulnerable hippocampal subfields from degeneration for at least 12 months post-intervention. These findings emphasise the therapeutic potential of resistance exercise; however, future work will need to establish just how long-lived these outcomes are and whether they are sufficient to delay dementia.

PMID: 31978826 [PubMed - as supplied by publisher]

Resting-state effective connectivity in the motive circuit of methamphetamine users: a case controlled fMRI study.

Sat, 01/25/2020 - 20:02
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Resting-state effective connectivity in the motive circuit of methamphetamine users: a case controlled fMRI study.

Behav Brain Res. 2020 Jan 21;:112498

Authors: Siyah Mansoory M, Farnia V

Abstract
Methamphetamine (MA) and other psychostimulants target the motive circuit of the brain, which is involved in reward, behavioral sensitization, and relapse to drug-seeking/taking behavior. In spite of this fact, the data regarding the effective connectivity (EC) in this circuit among MA users is scarce. The present study aimed to assess resting-state EC in the motive circuit of MA users during abstinence using the fMRI technique. Seventeen MA users after abstinence and 18 normal controls were examined using a 3 T Siemens fMRI scanner. After extracting time series of the motive circuit, EC differences in the motive circuit were analyzed using dynamic causal modeling (DCM). The findings revealed that abstinent MA users had an enhanced EC from the prefrontal cortex (PFC) to the ventral palladium (VP) (PFC→VP) and on the mediodorsal thalamus (MD) self-loop (MD→MD), but they showed a decreased connectivity on the VP self-loop (VP→VP) compared to healthy controls. The findings suggest that abstinent MA users may suffer from a limited pathology in connectivity within the motive circuit involved in reward, behavioral sensitization, and relapse. The enhanced PFC→VP seems to be a compensatory mechanism to control or regulate the subcortical regions involved in reward and behavioral sensitization. Furthermore, the enhanced connectivity on the MD self-loop and the decreased connectivity on the VP self-loop in abstinent MA users may, at least partially, affect the output of the limbic system, which can be seen in the behavioral sensitization and relapse processes. Nonetheless, further investigation in this area is strongly recommended to elucidate the exact mechanisms involved.

PMID: 31978492 [PubMed - as supplied by publisher]

Weighted average of shared trajectory: a new estimator for dynamic functional connectivity efficiently estimates both rapid and slow changes over time.

Sat, 01/25/2020 - 20:02
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Weighted average of shared trajectory: a new estimator for dynamic functional connectivity efficiently estimates both rapid and slow changes over time.

J Neurosci Methods. 2020 Jan 21;:108600

Authors: Faghiri A, Iraji A, Damaraju E, Belger A, Ford J, Mathalon D, Mcewen S, Mueller B, Pearlson G, Preda A, Turner J, Vaidya JG, Van Erp T, Calhoun VD

Abstract
BACKGROUND: Dynamic functional network connectivity (dFNC) of the brain has attracted considerable attention recently. Many approaches have been suggested to study dFNC with sliding window Pearson correlation (SWPC) being the most well-known. SWPC needs a relatively large sample size to reach a robust estimation but using large window sizes prevents us to detect rapid changes in dFNC.
NEW METHOD: Here we first calculate the gradients of each time series pair and use the magnitude of these gradients to calculate weighted average of shared trajectory (WAST) as a new estimator for dFNC.
RESULTS: Using WAST to compare healthy control and schizophrenia patients using a large dataset, we show disconnectivity between different regions associated with schizophrenia. In addition, WAST results reveals patients with schizophrenia stay longer in a connectivity state with negative connectivity between motor and sensory regions than do healthy controls.
COMPARISON WITH EXISTING METHODS: We compare WAST with SWPC and multiplication of temporal derivatives (MTD) using different simulation scenarios. We show that WAST enables us to detect very rapid changes in dFNC (undetected by SWPC) while MTD performance is generally lower.
CONCLUSIONS: As large window sizes are unable to detect short states, using shorter window size is desirable if the estimator is robust enough. We provide evidence that WAST requires fewer samples (compared to SWPC) to reach a robust estimation. As a result, we were able to identify rapidly varying dFNC patterns undetected by SWPC while still being able to robustly estimate slower dFNC patterns.

PMID: 31978489 [PubMed - as supplied by publisher]

Human hippocampal CA3 damage disrupts both recent and remote episodic memories.

Sat, 01/25/2020 - 20:02
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Human hippocampal CA3 damage disrupts both recent and remote episodic memories.

Elife. 2020 Jan 24;9:

Authors: Miller TD, Chong TT, Aimola Davies AM, Johnson MR, Irani SR, Husain M, Ng TW, Jacob S, Maddison P, Kennard C, Gowland PA, Rosenthal CR

Abstract
Neocortical-hippocampal interactions support new episodic (event) memories, but there is conflicting evidence about the dependence of remote episodic memories on the hippocampus. In line with systems consolidation and computational theories of episodic memory, evidence from model organisms suggests that the cornu ammonis 3 (CA3) hippocampal subfield supports recent, but not remote, episodic retrieval. In this study, we demonstrated that recent and remote memories were susceptible to a loss of episodic detail in human participants with focal bilateral damage to CA3. Graph theoretic analyses of 7.0-Tesla resting-state fMRI data revealed that CA3 damage disrupted functional integration across the medial temporal lobe (MTL) subsystem of the default network. The loss of functional integration in MTL subsystem regions was predictive of autobiographical episodic retrieval performance. We conclude that human CA3 is necessary for the retrieval of episodic memories long after their initial acquisition and functional integration of the default network is important for autobiographical episodic memory performance.

PMID: 31976861 [PubMed - in process]