New resting-state fMRI related studies at PubMed

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The Effects of Useful Field of View Training on Brain Activity and Connectivity.

Tue, 05/15/2018 - 16:20

The Effects of Useful Field of View Training on Brain Activity and Connectivity.

J Gerontol B Psychol Sci Soc Sci. 2018 May 11;:

Authors: Ross LA, Webb CE, Whitaker C, Hicks JM, Schmidt EL, Samimy S, Dennis NA, Visscher KM

Abstract
Objectives: Useful Field of View training (UFOVt) is an adaptive computerized cognitive intervention that improves visual attention and transfers to maintained health and everyday functioning in older adults. Although its efficacy is well established, the neural mechanisms underlying this intervention are unknown. This pilot study used functional MRI (fMRI) to explore neural changes following UFOVt.
Method: Task-driven and resting-state fMRI were used to examine changes in brain activity and connectivity in healthy older adults randomized to 10 hr of UFOVt (n = 13), 10 hr of cognitively stimulating activities (CSA; n = 11), or a no-contact control (NC; n = 10).
Results: UFOVt resulted in reduced task-driven activity in the majority of regions of interest (ROIs) associated with task performance, CSA resulted in reduced activity in one ROI, and there were no changes within the NC group. Relative to NC, UFOVt reduced activity in ROIs involved in effortful information processing. There were no other significant between-group task-based differences. Resting-state functional connectivity between ROIs involved in executive function and visual attention was strengthened following UFOVt compared with CSA and NC.
Discussion: UFOVt enhances connections needed for visual attention. Together with prior work, this study provides evidence that improvement of the brain's visual attention efficiency is one mechanism underlying UFOVt.

PMID: 29757433 [PubMed - as supplied by publisher]

Neural Correlates of Suicidality in Adolescents with Major Depression: Resting-State Functional Connectivity of the Precuneus and Posterior Cingulate Cortex.

Tue, 05/15/2018 - 16:20
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Neural Correlates of Suicidality in Adolescents with Major Depression: Resting-State Functional Connectivity of the Precuneus and Posterior Cingulate Cortex.

Suicide Life Threat Behav. 2018 May 13;:

Authors: Schreiner MW, Klimes-Dougan B, Cullen KR

Abstract
OBJECTIVE: Major depressive disorder (MDD) is associated with suicidal thoughts and behaviors ("suicidality"). Of the three components of Joiner's interpersonal theory of suicide, two involve negatively valenced, self-related beliefs: perceived burdensomeness and thwarted belongingness. However, the neurocircuitry underlying self-processing and suicidality has not been fully explored. This study examined the association between suicidality and the neurocircuitry of regions relevant to self-referential processing in adolescents with depression.
METHOD: Fifty-eight adolescents underwent assessment and a resting-state fMRI scan. Resting-state functional connectivity (RSFC) analyses included two brain regions implicated in self-referential processing: precuneus and posterior cingulate cortex (PCC). Suicidality was measured using the Index of Depression and Anxiety Symptoms. While controlling for depression severity, we conducted whole-brain correlation analyses between suicidality and left and right precuneus and PCC connectivity maps.
RESULTS: Suicidality was positively associated with RSFC between left precuneus and left primary motor and somatosensory cortices, and middle and superior frontal gyri. Suicidality was negatively associated with RSFC between left PCC and left cerebellum, lateral occipital cortex, and temporal-occipital fusiform gyrus.
CONCLUSIONS: Findings of hyperconnectivity stemming from the precuneus and hypoconnectivity from the PCC may reflect maladaptive self-reflection and mentalization. However, additional investigation is warranted to further clarify these relationships.

PMID: 29756354 [PubMed - as supplied by publisher]

Anticorrelations between Active Brain Regions: An Agent-Based Model Simulation Study.

Tue, 05/15/2018 - 16:20
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Anticorrelations between Active Brain Regions: An Agent-Based Model Simulation Study.

Neural Plast. 2018;2018:6815040

Authors: Parente F, Colosimo A

Abstract
Anticorrelations among brain areas observed in fMRI acquisitions under resting state are not endowed with a well-defined set of characters. Some evidence points to a possible physiological role for them, and simulation models showed that it is appropriate to explore such an issue. A large-scale brain representation was considered, implementing an agent-based brain-inspired model (ABBM) incorporating the SER (susceptible-excited-refractory) cyclic mechanism of state change. The experimental data used for validation included 30 selected functional images of healthy controls from the 1000 Functional Connectomes Classic collection. To study how different fractions of positive and negative connectivities could modulate the model efficiency, the correlation coefficient was systematically used to check the goodness-of-fit of empirical data by simulations under different combinations of parameters. The results show that a small fraction of positive connectivity is necessary to match at best the empirical data. Similarly, a goodness-of-fit improvement was observed upon addition of negative links to an initial pattern of only-positive connections, indicating a significant information intrinsic to negative links. As a general conclusion, anticorrelations showed that it is crucial to improve the performance of our simulation and, since these cannot be assimilated to noise, should be always considered in order to refine any brain functional model.

PMID: 29755515 [PubMed - in process]

Altered Amygdala Resting-State Functional Connectivity and Hemispheric Asymmetry in Patients With Social Anxiety Disorder.

Tue, 05/15/2018 - 16:20
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Altered Amygdala Resting-State Functional Connectivity and Hemispheric Asymmetry in Patients With Social Anxiety Disorder.

Front Psychiatry. 2018;9:164

Authors: Jung YH, Shin JE, Lee YI, Jang JH, Jo HJ, Choi SH

Abstract
Background: The amygdala plays a key role in emotional hyperreactivity in response to social threat in patients with social anxiety disorder (SAD). We investigated resting-state functional connectivity (rs-FCN) of the left and right amygdala with various brain regions and functional lateralization in patients with SAD. Methods: A total of 36 patients with SAD and 42 matched healthy controls underwent functional magnetic resonance imaging (fMRI) at rest. Using the left and right amygdala as seed regions, we compared the strength of the rs-FCN in the patient and control groups. Furthermore, we investigated group differences in the hemispheric asymmetry of the functional connectivity maps of the left and right amygdala. Results: Compared with healthy controls, the rs-FCN between the left amygdala and the dorsolateral prefrontal cortex was reduced in patients with SAD, whereas left amygdala connectivity with the fusiform gyrus, anterior insula, supramarginal gyrus, and precuneus was increased or positively deflected in the patient group. Additionally, the strength rs-FCN between the left amygdala and anterior insula was positively associated with the severity of the fear of negative evaluation in patients with SAD (r = 0.338, p = 0.044). The rs-FCN between the right amygdala and medial frontal gyrus was decreased in patients with SAD compared with healthy controls, whereas connectivity with the parahippocampal gyrus was greater in the patient group than in the control group. The hemispheric asymmetry patterns in the anterior insula, intraparietal sulcus (IPS), and inferior frontal gyrus of the patient group were opposite those of the control group, and functional lateralization of the connectivity between the amygdala and the IPS was associated with the severity of social anxiety symptoms (r = 0.365, p = 0.037). Conclusion: Our findings suggest that in addition to impaired fronto-amygdala communication, the functional lateralization of amygdala function plays a central role in the pathophysiology of SAD.

PMID: 29755374 [PubMed]

Bidirectional Causal Connectivity in the Cortico-Limbic-Cerebellar Circuit Related to Structural Alterations in First-Episode, Drug-Naive Somatization Disorder.

Tue, 05/15/2018 - 16:20
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Bidirectional Causal Connectivity in the Cortico-Limbic-Cerebellar Circuit Related to Structural Alterations in First-Episode, Drug-Naive Somatization Disorder.

Front Psychiatry. 2018;9:162

Authors: Li R, Liu F, Su Q, Zhang Z, Zhao J, Wang Y, Wu R, Zhao J, Guo W

Abstract
Background: Anatomical and functional deficits in the cortico-limbic-cerebellar circuit are involved in the neurobiology of somatization disorder (SD). The present study was performed to examine causal connectivity of the cortico-limbic-cerebellar circuit related to structural deficits in first-episode, drug-naive patients with SD at rest. Methods: A total of 25 first-episode, drug-naive patients with SD and 28 healthy controls underwent structural and resting-state functional magnetic resonance imaging. Voxel-based morphometry and Granger causality analysis (GCA) were used to analyze the data. Results: Results showed that patients with SD exhibited decreased gray matter volume (GMV) in the right cerebellum Crus I, and increased GMV in the left anterior cingulate cortex (ACC), right middle frontal gyrus (MFG), and left angular gyrus. Causal connectivity of the cortico-limbic-cerebellar circuit was partly affected by structural alterations in the patients. Patients with SD showed bidirectional cortico-limbic connectivity abnormalities and bidirectional cortico-cerebellar and limbic-cerebellar connectivity abnormalities. The mean GMV of the right MFG was negatively correlated with the scores of the somatization subscale of the symptom checklist-90 and persistent error response of the Wisconsin Card Sorting Test (WCST) in the patients. A negative correlation was observed between increased driving connectivity from the right MFG to the right fusiform gyrus/cerebellum IV, V and the scores of the Eysenck Personality Questionnaire extraversion subscale. The mean GMV of the left ACC was negatively correlated with the WCST number of errors and persistent error response. Negative correlation was found between the causal effect from the left ACC to the right middle temporal gyrus and the scores of WCST number of categories achieved. Conclusions: Our findings show the partial effects of structural alterations on the cortico-limbic-cerebellar circuit in first-episode, drug-naive patients with SD. Correlations are observed between anatomical alterations or causal effects and clinical variables in patients with SD, and bear clinical significance. The present study emphasizes the importance of the cortico-limbic-cerebellar circuit in the neurobiology of SD.

PMID: 29755373 [PubMed]

Neurofeedback and the Neural Representation of Self: Lessons From Awake State and Sleep.

Tue, 05/15/2018 - 16:20
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Neurofeedback and the Neural Representation of Self: Lessons From Awake State and Sleep.

Front Hum Neurosci. 2018;12:142

Authors: Ioannides AA

Abstract
Neurofeedback has been around for half a century, but despite some promising results it is not yet widely appreciated. Recently, some of the concerns about neurofeedback have been addressed with functional magnetic resonance imaging and magnetoencephalography adding their contributions to the long history of neurofeedback with electroencephalography. Attempts to address other concerns related to methodological issues with new experiments and meta-analysis of earlier studies, have opened up new questions about its efficacy. A key concern about neurofeedback is the missing framework to explain how improvements in very different and apparently unrelated conditions are achieved. Recent advances in neuroscience begin to address this concern. A particularly promising approach is the analysis of resting state of fMRI data, which has revealed robust covariations in brain networks that maintain their integrity in sleep and even anesthesia. Aberrant activity in three brain wide networks (i.e., the default mode, central executive and salience networks) has been associated with a number of psychiatric disorders. Recent publications have also suggested that neurofeedback guides the restoration of "normal" activity in these three networks. Using very recent results from our analysis of whole night MEG sleep data together with key concepts from developmental psychology, cloaked in modern neuroscience terms, a theoretical framework is proposed for a neural representation of the self, located at the core of a double onion-like structure of the default mode network. This framework fits a number of old and recent neuroscientific findings, and unites the way attention and memory operate in awake state and during sleep. In the process, safeguards are uncovered, put in place by evolution, before any interference with the core representation of self can proceed. Within this framework, neurofeedback is seen as set of methods for restoration of aberrant activity in large scale networks. The framework also admits quantitative measures of improvements to be made by personalized neurofeedback protocols. Finally, viewed through the framework developed, neurofeedback's safe nature is revealed while raising some concerns for interventions that attempt to alter the neural self-representation bypassing the safeguards evolution has put in place.

PMID: 29755332 [PubMed]

Individualized Functional Parcellation of the Human Amygdala Using a Semi-supervised Clustering Method: A 7T Resting State fMRI Study.

Tue, 05/15/2018 - 16:20
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Individualized Functional Parcellation of the Human Amygdala Using a Semi-supervised Clustering Method: A 7T Resting State fMRI Study.

Front Neurosci. 2018;12:270

Authors: Zhang X, Cheng H, Zuo Z, Zhou K, Cong F, Wang B, Zhuo Y, Chen L, Xue R, Fan Y

Abstract
The amygdala plays an important role in emotional functions and its dysfunction is considered to be associated with multiple psychiatric disorders in humans. Cytoarchitectonic mapping has demonstrated that the human amygdala complex comprises several subregions. However, it's difficult to delineate boundaries of these subregions in vivo even if using state of the art high resolution structural MRI. Previous attempts to parcellate this small structure using unsupervised clustering methods based on resting state fMRI data suffered from the low spatial resolution of typical fMRI data, and it remains challenging for the unsupervised methods to define subregions of the amygdala in vivo. In this study, we developed a novel brain parcellation method to segment the human amygdala into spatially contiguous subregions based on 7T high resolution fMRI data. The parcellation was implemented using a semi-supervised spectral clustering (SSC) algorithm at an individual subject level. Under guidance of prior information derived from the Julich cytoarchitectonic atlas, our method clustered voxels of the amygdala into subregions according to similarity measures of their functional signals. As a result, three distinct amygdala subregions can be obtained in each hemisphere for every individual subject. Compared with the cytoarchitectonic atlas, our method achieved better performance in terms of subregional functional homogeneity. Validation experiments have also demonstrated that the amygdala subregions obtained by our method have distinctive, lateralized functional connectivity (FC) patterns. Our study has demonstrated that the semi-supervised brain parcellation method is a powerful tool for exploring amygdala subregional functions.

PMID: 29755313 [PubMed]

Hierarchical organization of functional connectivity in the mouse brain: a complex network approach.

Tue, 05/15/2018 - 16:20
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Hierarchical organization of functional connectivity in the mouse brain: a complex network approach.

Sci Rep. 2016 08 18;6:32060

Authors: Bardella G, Bifone A, Gabrielli A, Gozzi A, Squartini T

Abstract
This paper represents a contribution to the study of the brain functional connectivity from the perspective of complex networks theory. More specifically, we apply graph theoretical analyses to provide evidence of the modular structure of the mouse brain and to shed light on its hierarchical organization. We propose a novel percolation analysis and we apply our approach to the analysis of a resting-state functional MRI data set from 41 mice. This approach reveals a robust hierarchical structure of modules persistent across different subjects. Importantly, we test this approach against a statistical benchmark (or null model) which constrains only the distributions of empirical correlations. Our results unambiguously show that the hierarchical character of the mouse brain modular structure is not trivially encoded into this lower-order constraint. Finally, we investigate the modular structure of the mouse brain by computing the Minimal Spanning Forest, a technique that identifies subnetworks characterized by the strongest internal correlations. This approach represents a faster alternative to other community detection methods and provides a means to rank modules on the basis of the strength of their internal edges.

PMID: 27534708 [PubMed - indexed for MEDLINE]

Resilience and amygdala function in older healthy and depressed adults.

Mon, 05/14/2018 - 15:00
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Resilience and amygdala function in older healthy and depressed adults.

J Affect Disord. 2018 Apr 25;237:27-34

Authors: Leaver AM, Yang H, Siddarth P, Vlasova RM, Krause B, St Cyr N, Narr KL, Lavretsky H

Abstract
BACKGROUND: Previous studies suggest that low emotional resilience may correspond with increased or over-active amygdala function. Complementary studies suggest that emotional resilience increases with age; older adults tend to have decreased attentional bias to negative stimuli compared to younger adults. Amygdala nuclei and related brain circuits have been linked to negative affect, and depressed patients have been demonstrated to have abnormal amygdala function.
METHODS: In the current study, we correlated psychological resilience measures with amygdala function measured with resting-state arterial spin-labelled (ASL) and blood-oxygenation-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) in older adults with and without depression. Specifically, we targeted the basolateral, centromedial, and superficial nuclei groups of the amygdala, which have different functions and brain connections.
RESULTS: High levels of psychological resilience correlated with lower basal levels of amygdala activity measured with ASL fMRI. High resilience also correlated with decreased connectivity between amygdala nuclei and the ventral default-mode network independent of depression status. Instead, lower depression symptoms were associated with higher connectivity between the amygdalae and dorsal frontal networks.
LIMITATIONS: Future multi-site studies with larger sample size and improved neuroimaging technologies are needed. Longitudinal studies that target resilience to naturalistic stressors will also be a powerful contribution to the field.
CONCLUSIONS: Our results suggest that resilience in older adults is more closely related to function in ventral amygdala networks, while late-life depression is related to reduced connectivity between the amygdala and dorsal frontal regions.

PMID: 29754022 [PubMed - as supplied by publisher]

Using temporal ICA to selectively remove global noise while preserving global signal in functional MRI data.

Mon, 05/14/2018 - 15:00
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Using temporal ICA to selectively remove global noise while preserving global signal in functional MRI data.

Neuroimage. 2018 May 10;:

Authors: Glasser MF, Coalson TS, Bijsterbosch JD, Harrison SJ, Harms MP, Anticevic A, Van Essen DC, Smith SM

Abstract
Temporal fluctuations in functional Magnetic Resonance Imaging (fMRI) have been profitably used to study brain activity and connectivity for over two decades. Unfortunately, fMRI data also contain structured temporal "noise" from a variety of sources, including subject motion, subject physiology, and the MRI equipment. Recently, methods have been developed to automatically and selectively remove spatially specific structured noise from fMRI data using spatial Independent Components Analysis (ICA) and machine learning classifiers. Spatial ICA is particularly effective at removing spatially specific structured noise from high temporal and spatial resolution fMRI data of the type acquired by the Human Connectome Project and similar studies. However, spatial ICA is mathematically, by design, unable to separate spatially widespread "global" structured noise from fMRI data (e.g., blood flow modulations from subject respiration). No methods currently exist to selectively and completely remove global structured noise while retaining the global signal from neural activity. This has left the field in a quandary-to do or not to do global signal regression-given that both choices have substantial downsides. Here we show that temporal ICA can selectively segregate and remove global structured noise while retaining global neural signal in both task-based and resting state fMRI data. We compare the results before and after temporal ICA cleanup to those from global signal regression and show that temporal ICA cleanup removes the global positive biases caused by global physiological noise without inducing the network-specific negative biases of global signal regression. We believe that temporal ICA cleanup provides a "best of both worlds" solution to the global signal and global noise dilemma and that temporal ICA itself unlocks interesting neurobiological insights from fMRI data.

PMID: 29753843 [PubMed - as supplied by publisher]

Extracting orthogonal subject- and condition-specific signatures from fMRI data using whole-brain effective connectivity.

Mon, 05/14/2018 - 15:00
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Extracting orthogonal subject- and condition-specific signatures from fMRI data using whole-brain effective connectivity.

Neuroimage. 2018 May 10;:

Authors: Pallarés V, Insabato A, Sanjuán A, Kühn S, Mantini D, Deco G, Gilson M

Abstract
The study of brain communication based on fMRI data is often limited because such measurements are a mixture of session-to-session variability with subject- and condition-related information. Disentangling these contributions is crucial for real-life applications, in particular when only a few recording sessions are available. The present study aims to define a reliable standard for the extraction of multiple signatures from fMRI data, while verifying that they do not mix information about the different modalities (e.g., subjects and conditions such as tasks performed by them). In particular, condition-specific signatures should not be contaminated by subject-related information, since they aim to generalize over subjects. Practically, signatures correspond to subnetworks of directed interactions between brain regions (typically 100 covering the whole brain) supporting the subject and condition identification for single fMRI sessions. The key for robust prediction is using effective connectivity instead of functional connectivity. Our method demonstrates excellent generalization capabilities for subject identification in two datasets, using only a few sessions per subject as reference. Using another dataset with resting state and movie viewing, we show that the two signatures related to subjects and tasks correspond to distinct subnetworks, which are thus topologically orthogonal. Our results set solid foundations for applications tailored to individual subjects, such as clinical diagnostic.

PMID: 29753842 [PubMed - as supplied by publisher]

A lateral-to-mesial organization of human ventral visual cortex at birth.

Sun, 05/13/2018 - 13:40
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A lateral-to-mesial organization of human ventral visual cortex at birth.

Brain Struct Funct. 2018 May 11;:

Authors: Barttfeld P, Abboud S, Lagercrantz H, Adén U, Padilla N, Edwards AD, Cohen L, Sigman M, Dehaene S, Dehaene-Lambertz G

Abstract
In human adults, ventral extra-striate visual cortex contains a mosaic of functionally specialized areas, some responding preferentially to natural visual categories such as faces (fusiform face area) or places (parahippocampal place area) and others to cultural inventions such as written words and numbers (visual word form and number form areas). It has been hypothesized that this mosaic arises from innate biases in cortico-cortical connectivity. We tested this hypothesis by examining functional resting-state correlation at birth using fMRI data from full-term human newborns. The results revealed that ventral visual regions are functionally connected with their contra-lateral homologous regions and also exhibit distinct patterns of long-distance functional correlation with anterior associative regions. A mesial-to-lateral organization was observed, with the signal of the more lateral regions, including the sites of visual word and number form areas, exhibiting higher correlations with voxels of the prefrontal, inferior parietal and temporal cortices, including language areas. Finally, we observed hemispheric asymmetries in the functional correlation of key areas of the language network that may influence later adult hemispheric lateralization. We suggest that long-distance circuits present at birth constrain the subsequent functional differentiation of the ventral visual cortex.

PMID: 29752588 [PubMed - as supplied by publisher]

Local functional connectivity alterations in schizophrenia, bipolar disorder, and major depressive disorder.

Sat, 05/12/2018 - 12:20
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Local functional connectivity alterations in schizophrenia, bipolar disorder, and major depressive disorder.

J Affect Disord. 2018 Apr 10;236:266-273

Authors: Wei Y, Chang M, Womer FY, Zhou Q, Yin Z, Wei S, Zhou Y, Jiang X, Yao X, Duan J, Xu K, Zuo XN, Tang Y, Wang F

Abstract
BACKGROUND: Local functional connectivity (FC) indicates local or short-distance functional interactions and may serve as a neuroimaging marker to investigate the human brain connectome. Local FC alterations suggest a disrupted balance in the local functionality of the whole brain network and are increasingly implicated in schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD).
METHODS: We aim to examine the similarities and differences in the local FC across SZ, BD, and MDD. In total, 537 participants (SZ, 126; BD, 97; MDD, 126; and healthy controls, 188) completed resting-state functional magnetic resonance imaging at a single site. The local FC at resting state was calculated and compared across SZ, BD, and MDD.
RESULTS: The local FC increased across SZ, BD, and MDD within the bilateral orbital frontal cortex (OFC) and additional region in the left OFC extending to putamen and decreased in the primary visual, auditory, and motor cortices, right supplemental motor area, and bilateral thalami. There was a gradient in the extent of alterations such that SZ > BD > MDD.
LIMITATIONS: This cross-sectional study cannot consider medications and other clinical variables.
CONCLUSIONS: These findings indicate a disrupted balance between network integration and segregation in SZ, BD, and MDD, including over-integration via increased local FC in the OFC and diminished segregation of neural processing with the weakening of the local FC in the primary sensory cortices and thalamus. The shared local FC abnormalities across SZ, BD, and MDD may shed new light on the potential biological mechanisms underlying these disorders.

PMID: 29751242 [PubMed - as supplied by publisher]

Associations of functional connectivity and walking performance in multiple sclerosis.

Sat, 05/12/2018 - 12:20
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Associations of functional connectivity and walking performance in multiple sclerosis.

Neuropsychologia. 2018 May 08;:

Authors: Bollaert RE, Poe K, Hubbard EA, Motl RW, Pilutti LA, Johnson CL, Sutton BP

Abstract
BACKGROUND: Persons with multiple sclerosis (MS) often demonstrate impaired walking performance, and neuroimaging methods such as resting state functional connectivity (RSFC) may support a link between central nervous system damage and disruptions in walking.
OBJECTIVES: This study examined associations between RSFC in cortical networks and walking performance in persons with MS.
METHODS: 29 persons with MS underwent 3-T brain magnetic resonance imaging (MRI) and we computed RSFC among 68 Gy matter regions of interest in the brain. Participants completed the Timed 25-foot Walk as a measure of walking performance. We examined associations using partial Pearson product-moment correlation analyses (r), controlling for age.
RESULTS: There were eight cortical brain regions that were significantly associated with the T25FW, including the left parahippocampal gyrus and transverse temporal gyrus, and the right fusiform gyrus, inferior temporal gyrus, lingual gyrus, pericalcarine cortex, superior temporal gyrus, and transverse temporal gyrus.
CONCLUSIONS: We provide novel evidence that RSFC can be a valuable tool to monitor the motor and non-motor networks impacted in MS that relate to declines in motor impairment. RSFC may identify critical nodes involved in a range of motor tasks such as walking that can be more sensitive to disruption by MS.

PMID: 29750986 [PubMed - as supplied by publisher]

High definition-transcranial direct current stimulation changes older adults' subjective sleep and corresponding resting-state functional connectivity.

Sat, 05/12/2018 - 12:20
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High definition-transcranial direct current stimulation changes older adults' subjective sleep and corresponding resting-state functional connectivity.

Int J Psychophysiol. 2018 May 08;:

Authors: Sheng J, Xie C, Fan DQ, Lei X, Yu J

Abstract
With advanced age, older adults show functional deterioration in sleep. Transcranial direct current stimulation (tDCS), a noninvasive brain stimulation, modulates individuals' behavioral performance in various cognitive domains. However, the modulation effect and neural mechanisms of tDCS on sleep, especially for the elderly population are not clear. Here, we aimed to investigate whether high-definition transcranial direct current stimulation (HD-tDCS) could modulate community-dwelling older adults' subjective sleep and whether these potential improvements are associated with the large-scale brain activity alterations recorded by functional magnetic resonance imaging. Thirty-one older adults were randomly allocated to the HD-tDCS group and the control group. HD-tDCS was applied for 25 min at 1.5 mA per day for two weeks. The anode electrode was placed over the left dorsolateral prefrontal cortex, surrounded by 4 cathodes at 7 cm radius. All participants completed sleep neuropsychological assessments and fMRI scans individually before and after intervention. Behaviorally, we observed a HD-tDCS-induced enhancement of older adults' sleep duration. On the aspect of the corresponding neural alterations, we observed that HD-tDCS decreased the functional connectivity between the default mode network (DMN) and subcortical network. More importantly, the decoupling connectivity of the DMN-subcortical network was correlated with the improvements of subjective sleep in the HD-tDCS group. Our findings add novel behavioral and neural evidences about tDCS-induced sleep improvement in community-dwelling older adults. With further development, tDCS may be used as an alternative treatment for sleep disorders and alleviate the dysfunction of brain networks induced by aging.

PMID: 29750977 [PubMed - as supplied by publisher]

Altered resting-state hippocampal and caudate functional networks in patients with obstructive sleep apnea.

Sat, 05/12/2018 - 12:20
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Altered resting-state hippocampal and caudate functional networks in patients with obstructive sleep apnea.

Brain Behav. 2018 May 10;:e00994

Authors: Song X, Roy B, Kang DW, Aysola RS, Macey PM, Woo MA, Yan-Go FL, Harper RM, Kumar R

Abstract
INTRODUCTION: Brain structural injury and metabolic deficits in the hippocampus and caudate nuclei may contribute to cognitive and emotional deficits found in obstructive sleep apnea (OSA) patients. If such contributions exist, resting-state interactions of these subcortical sites with cortical areas mediating affective symptoms and cognition should be disturbed. Our aim was to examine resting-state functional connectivity (FC) of the hippocampus and caudate to other brain areas in OSA relative to control subjects, and to relate these changes to mood and neuropsychological scores.
METHODS: We acquired resting-state functional magnetic resonance imaging (fMRI) data from 70 OSA and 89 healthy controls using a 3.0-Tesla magnetic resonance imaging scanner, and assessed psychological and behavioral functions, as well as sleep issues. After standard fMRI data preprocessing, FC maps were generated for bilateral hippocampi and caudate nuclei, and compared between groups (ANCOVA; covariates, age and gender).
RESULTS: Obstructive sleep apnea subjects showed significantly higher levels of anxiety and depressive symptoms over healthy controls. In OSA subjects, the hippocampus showed disrupted FC with the thalamus, para-hippocampal gyrus, medial and superior temporal gyrus, insula, and posterior cingulate cortex. Left and right caudate nuclei showed impaired FC with the bilateral inferior frontal gyrus and right angular gyrus. In addition, altered limbic-striatal-cortical FC in OSA showed relationships with behavioral and neuropsychological variables.
CONCLUSIONS: The compromised hippocampal-cortical FC in OSA may underlie depression and anxious mood levels in OSA, while impaired caudate-cortical FC may indicate deficits in reward processing and cognition. These findings provide insights into the neural mechanisms underlying the comorbidity of mood and cognitive deficits in OSA.

PMID: 29749715 [PubMed - as supplied by publisher]

Spatio-temporal dynamics of resting-state brain networks improve single-subject prediction of schizophrenia diagnosis.

Sat, 05/12/2018 - 12:20
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Spatio-temporal dynamics of resting-state brain networks improve single-subject prediction of schizophrenia diagnosis.

Hum Brain Mapp. 2018 May 10;:

Authors: Kottaram A, Johnston L, Ganella E, Pantelis C, Kotagiri R, Zalesky A

Abstract
Correlation in functional MRI activity between spatially separated brain regions can fluctuate dynamically when an individual is at rest. These dynamics are typically characterized temporally by measuring fluctuations in functional connectivity between brain regions that remain fixed in space over time. Here, dynamics in functional connectivity were characterized in both time and space. Temporal dynamics were mapped with sliding-window correlation, while spatial dynamics were characterized by enabling network regions to vary in size (shrink/grow) over time according to the functional connectivity profile of their constituent voxels. These temporal and spatial dynamics were evaluated as biomarkers to distinguish schizophrenia patients from controls, and compared to current biomarkers based on static measures of resting-state functional connectivity. Support vector machine classifiers were trained using: (a) static, (b) dynamic in time, (c) dynamic in space, and (d) dynamic in time and space characterizations of functional connectivity within canonical resting-state brain networks. Classifiers trained on functional connectivity dynamics mapped over both space and time predicted diagnostic status with accuracy exceeding 91%, whereas utilizing only spatial or temporal dynamics alone yielded lower classification accuracies. Static measures of functional connectivity yielded the lowest accuracy (79.5%). Compared to healthy comparison individuals, schizophrenia patients generally exhibited functional connectivity that was reduced in strength and more variable. Robustness was established with replication in an independent dataset. The utility of biomarkers based on temporal and spatial functional connectivity dynamics suggests that resting-state dynamics are not trivially attributable to sampling variability and head motion.

PMID: 29749660 [PubMed - as supplied by publisher]

Individualized prediction of trait narcissism from whole-brain resting-state functional connectivity.

Sat, 05/12/2018 - 12:20
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Individualized prediction of trait narcissism from whole-brain resting-state functional connectivity.

Hum Brain Mapp. 2018 May 10;:

Authors: Feng C, Yuan J, Geng H, Gu R, Zhou H, Wu X, Luo Y

Abstract
Narcissism is one of the most fundamental personality traits in which individuals in general population exhibit a large heterogeneity. Despite a surge of interest in examining behavioral characteristics of narcissism in the past decades, the neurobiological substrates underlying narcissism remain poorly understood. Here, we addressed this issue by applying a machine learning approach to decode trait narcissism from whole-brain resting-state functional connectivity (RSFC). Resting-state functional MRI (fMRI) data were acquired for a large sample comprising 155 healthy adults, each of whom was assessed for trait narcissism. Using a linear prediction model, we examined the relationship between whole-brain RSFC and trait narcissism. We demonstrated that the machine-learning model was able to decode individual trait narcissism from RSFC across multiple neural systems, including functional connectivity between and within limbic and prefrontal systems as well as their connectivity with other networks. Key nodes that contributed to the prediction model included the amygdala, prefrontal and anterior cingulate regions that have been linked to trait narcissism. These findings remained robust using different validation procedures. Our findings thus demonstrate that RSFC among multiple neural systems predicts trait narcissism at the individual level.

PMID: 29749072 [PubMed - as supplied by publisher]

Multi-subject hierarchical inverse covariance modelling improves estimation of functional brain networks.

Fri, 05/11/2018 - 11:00

Multi-subject hierarchical inverse covariance modelling improves estimation of functional brain networks.

Neuroimage. 2018 May 07;:

Authors: Colclough GL, Woolrich MW, Harrison SJ, Rojas López PA, Valdes-Sosa PA, Smith SM

Abstract
A Bayesian model for sparse, hierarchical inverse covariance estimation is presented, and applied to multi-subject functional connectivity estimation in the human brain. It enables simultaneous inference of the strength of connectivity between brain regions at both subject and population level, and is applicable to fmri, meg and eeg data. Two versions of the model can encourage sparse connectivity, either using continuous priors to suppress irrelevant connections, or using an explicit description of the network structure to estimate the connection probability between each pair of regions. A large evaluation of this model, and thirteen methods that represent the state of the art of inverse covariance modelling, is conducted using both simulated and resting-state functional imaging datasets. Our novel Bayesian approach has similar performance to the best extant alternative, Ng et al.'s Sparse Group Gaussian Graphical Model algorithm, which also is based on a hierarchical structure. Using data from the Human Connectome Project, we show that these hierarchical models are able to reduce the measurement error in meg beta-band functional networks by 10%, producing concomitant increases in estimates of the genetic influence on functional connectivity.

PMID: 29746906 [PubMed - as supplied by publisher]

[Research on the rest functional magnetic resonance imaging before and after smoking cessation].

Fri, 05/11/2018 - 11:00

[Research on the rest functional magnetic resonance imaging before and after smoking cessation].

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2018 Feb 01;35(1):87-91

Authors: Mo S, Feng S, Chen H

Abstract
The aim of this paper is to reveal the change of the brain function for nicotine addicts after smoking cessation, and explore the basis of neural physiology for the nicotine addicts in the process of smoking cessation. Fourteen subjects, who have a strong dependence on nicotine, have agreed to give up smoking and insist on completing the test, and 11 volunteers were recruited as the controls. The resting state functional magnetic resonance imaging and the regional homogeneity (ReHo) algorithm have been used to study the neural activity before and after smoking cessation. A two factors mixed design was used to investigate within-group effects and between-group effects. After 2 weeks' smoking cessation, the increased ReHo value were exhibited in the brain area of supplementary motor area, paracentral lobule, calcarine, cuneus and lingual gyrus. It suggested that the synchronization of neural activity was enhanced in these brain areas. And between-group interaction effects were appeared in supplementary motor area, paracentral lobule, precentral gyrus, postcentral gyrus, and superior frontal gyrus. The results indicate that the brain function in supplementary motor area of smoking addicts would be enhanced significantly after 2 weeks' smoking cessation.

PMID: 29745606 [PubMed]

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