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Prism adaptation enhances decoupling between the default mode network and the attentional networks.

Tue, 06/25/2019 - 21:03
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Prism adaptation enhances decoupling between the default mode network and the attentional networks.

Neuroimage. 2019 Jun 21;:

Authors: Wilf M, Serino A, Clarke S, Crottaz-Herbette S

Abstract
Prism adaptation (PA) is a procedure used for studying visuomotor plasticity in healthy individuals, as well as for alleviating spatial neglect in patients. The adaptation is achieved by performing goal-directed movements while wearing prismatic lenses that induce a lateral displacement of visual information. This results in an initial movement error that is compensated by a recalibration of sensory-motor coordinates; consequently, a lateral bias in both motor and perceptual measurements occurs after prism removal, i.e., after effects. Neuroimaging studies have shown that a brief exposure to rightward prism changes the activations in the inferior parietal lobule (IPL) and modulates interhemispheric balance during attention tasks. However, it is yet unknown how PA changes global interplay between cortical networks as evident from task-free resting state connectivity. Thus we compared resting state functional connectivity patterns before ('Pre') and after ('Post') participants performed session of pointing movements with rightward-shifting prism (N = 14) or with neutral lenses (as a control condition; N = 12). Global connectivity analysis revealed significant decreases in functional connectivity following PA in two nodes of the Default Mode Network (DMN), and the left anterior insula. Further analyses of these regions showed specific connectivity decrease between either of the DMN nodes and areas within the attentional networks, including the inferior frontal gyrus, the anterior insula and the right superior temporal sulcus. On the other hand, the anterior insula decreased its connectivity to a large set of areas, all within the boundaries of the DMN. These results demonstrate that a brief exposure to PA enhances the decoupling between the DMN and the attention networks. The change in interplay between those pre-existing networks might be the basis of the rapid and wide-ranged behavioural changes induce by PA in healthy individuals.

PMID: 31233909 [PubMed - as supplied by publisher]

New graph-theoretical-multimodal approach using temporal and structural correlations reveal disruption in the thalamo-cortical network in patients with schizophrenia.

Tue, 06/25/2019 - 21:03
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New graph-theoretical-multimodal approach using temporal and structural correlations reveal disruption in the thalamo-cortical network in patients with schizophrenia.

Brain Connect. 2019 Jun 22;:

Authors: Forlim CG, Finotelli P, Dulio P, Klock L, Pini A, Bächle J, Stoll L, Giemsa P, Fuchs M, Schoofs N, Montag C, Gallinat J, Kühn S

Abstract
Schizophrenia has been understood as a network disease with altered functional and structural connectivity in multiple brain networks compatible to the extremely broad spectrum of psychopathological, cognitive and behavioral symptoms in this disorder. When building brain networks, functional and structural networks are typically modelled independently: functional network models are based on temporal correlations among brain regions, whereas structural network models are based on anatomical characteristics. Combining both features may give rise to more realistic and reliable models of brain networks. In this study, we applied a new flexible graph-theoretical-multimodal model called FD (F, the functional connectivity matrix, and D, the structural matrix) to construct brain networks combining functional, structural and topological information of MRI measurements (structural and resting state imaging) to patients with schizophrenia(N=35) and matched healthy individuals(N=41). As a reference condition, the traditional pure functional connectivity (pFC) analysis was carried out. By using the FD model, we found disrupted connectivity in the thalamo-cortical network in schizophrenic patients, whereas the pFC model failed to extract group differences after multiple comparison correction. We interpret this observation as evidence that the FD model is superior to conventional connectivity analysis, by stressing relevant features of the whole brain connectivity including functional, structural and topological signatures. The FD model can be used in future research to model subtle alterations of functional and structural connectivity resulting in pronounced clinical syndromes and major psychiatric disorders. Lastly, FD is not limited to the analysis of resting state fMRI, and can be applied to EEG, MEG etc.

PMID: 31232080 [PubMed - as supplied by publisher]

Alterations of cerebral perfusion and functional brain connectivity in medication-naïve male adults with attention-deficit/hyperactivity disorder.

Tue, 06/25/2019 - 21:03
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Alterations of cerebral perfusion and functional brain connectivity in medication-naïve male adults with attention-deficit/hyperactivity disorder.

CNS Neurosci Ther. 2019 Jun 23;:

Authors: Tan YW, Liu L, Wang YF, Li HM, Pan MR, Zhao MJ, Huang F, Wang YF, He Y, Liao XH, Qian QJ

Abstract
AIMS: Functional brain abnormalities, including altered cerebral perfusion and functional connectivities, have been illustrated in adults with attention-deficit/hyperactivity disorder (aADHD). The present study attempted to explore the alterations of cerebral blood flow (CBF) and resting-state functional connectivity (RSFC) simultaneously to understand the neural mechanisms for adults with ADHD comprehensively.
METHODS: Resting-state arterial spin labeling (ASL) and blood oxygenation level-dependent (BOLD) magnetic resonance imaging (MRI) data were acquired for 69 male aADHD and 69 matched healthy controls (HCs). The altered CBFs associated with aADHD were explored based on both categorical (aADHD vs HCs) and dimensional (correlation with aADHD core symptoms) perspectives. Then, the seed-based RSFC analyses were developed for the regions showing significant alterations of CBF.
RESULTS: Significantly decreased CBF in the large-scale resting-state networks regions (eg, ventral attentional network, somatomotor network, limbic network) and subcortical regions was indicated in aADHD compared with HCs. The correlation analyses indicated that the hypoperfusion in left putamen/global pallidum and left amygdala/hippocampus was correlated with ADHD inattentive and total symptoms, respectively. Further, weaker negative functional connectivity between left amygdala and bilateral supplementary motor area, bilateral superior frontal gyrus, and left medial frontal gyrus was found in adults with ADHD.
CONCLUSION: The present findings suggested alterations of both cerebral perfusion and functional connectivity for the left amygdala in aADHD. The combination of CBF and RSFCs may help to interpret the neuropathogenesis of ADHD more comprehensively.

PMID: 31231983 [PubMed - as supplied by publisher]

Clinical Personal Connectomics Using Hybrid PET/MRI.

Tue, 06/25/2019 - 21:03
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Clinical Personal Connectomics Using Hybrid PET/MRI.

Nucl Med Mol Imaging. 2019 Jun;53(3):153-163

Authors: Lee DS

Abstract
Brain connectivity can now be studied with topological analysis using persistent homology. It overcame the arbitrariness of thresholding to make binary graphs for comparison between disease and normal control groups. Resting-state fMRI can yield personal interregional brain connectivity based on perfusion signal on MRI on individual subject bases and FDG PET produces the topography of glucose metabolism. Assuming metabolism perfusion coupling and disregarding the slight difference of representing time of metabolism (before image acquisition) and representing time of perfusion (during image acquisition), topography of brain metabolism on FDG PET and topologically analyzed brain connectivity on resting-state fMRI might be related to yield personal connectomics of individual subjects and even individual patients. The work of association of FDG PET/resting-state fMRI is yet to be warranted; however, the statistics behind the group comparison of connectivity on FDG PET or resting-state MRI was already developed. Before going further into the connectomics construction using directed weighted brain graphs of FDG PET or resting-state fMRI, I detailed in this review the plausibility of using hybrid PET/MRI to enable the interpretation of personal connectomics which can lead to the clinical use of brain connectivity in the near future.

PMID: 31231434 [PubMed]

Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri).

Tue, 06/25/2019 - 21:03
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Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri).

Front Neuroinform. 2019;13:42

Authors: Pallast N, Diedenhofen M, Blaschke S, Wieters F, Wiedermann D, Hoehn M, Fink GR, Aswendt M

Abstract
Magnetic resonance imaging (MRI) is a key technology in multimodal animal studies of brain connectivity and disease pathology. In vivo MRI provides non-invasive, whole brain macroscopic images containing structural and functional information, thereby complementing invasive in vivo high-resolution microscopy and ex vivo molecular techniques. Brain mapping, the correlation of corresponding regions between multiple brains in a standard brain atlas system, is widely used in human MRI. For small animal MRI, however, there is no scientific consensus on pre-processing strategies and atlas-based neuroinformatics. Thus, it remains difficult to compare and validate results from different pre-clinical studies which were processed using custom-made code or individual adjustments of clinical MRI software and without a standard brain reference atlas. Here, we describe AIDAmri, a novel Atlas-based Imaging Data Analysis pipeline to process structural and functional mouse brain data including anatomical MRI, fiber tracking using diffusion tensor imaging (DTI) and functional connectivity analysis using resting-state functional MRI (rs-fMRI). The AIDAmri pipeline includes automated pre-processing steps, such as raw data conversion, skull-stripping and bias-field correction as well as image registration with the Allen Mouse Brain Reference Atlas (ARA). Following a modular structure developed in Python scripting language, the pipeline integrates established and newly developed algorithms. Each processing step was optimized for efficient data processing requiring minimal user-input and user programming skills. The raw data is analyzed and results transferred to the ARA coordinate system in order to allow an efficient and highly-accurate region-based analysis. AIDAmri is intended to fill the gap of a missing open-access and cross-platform toolbox for the most relevant mouse brain MRI sequences thereby facilitating data processing in large cohorts and multi-center studies.

PMID: 31231202 [PubMed]

Rostral-Caudal Hippocampal Functional Convergence Is Reduced Across the Alzheimer's Disease Spectrum.

Mon, 06/24/2019 - 21:02

Rostral-Caudal Hippocampal Functional Convergence Is Reduced Across the Alzheimer's Disease Spectrum.

Mol Neurobiol. 2019 Jun 22;:

Authors: Therriault J, Wang S, Mathotaarachchi S, Pascoal TA, Parent M, Beaudry T, Shin M, Al B, Kang MS, Ng KP, Dansereau C, Park MTM, Fonov V, Carbonell F, Zimmer E, Chakravarty MM, Bellec P, Gauthier S, Rosa-Neto P, Alzheimer’s Disease Neuroimaging Initiative

Abstract
Beginning in the early stages of Alzheimer's disease (AD), the hippocampus reduces its functional connections to other cortical regions due to synaptic depletion. However, little is known regarding connectivity abnormalities within the hippocampus. Here, we describe rostral-caudal hippocampal convergence (rcHC), a metric of the overlap between the rostral and caudal hippocampal functional networks, across the clinical spectrum of AD. We predicted a decline in rostral-caudal hippocampal convergence in the early stages of the disease. Using fMRI, we generated resting-state hippocampal functional networks across 56 controls, 48 early MCI (EMCI), 35 late MCI (LMCI), and 31 AD patients from the Alzheimer's Disease Neuroimaging Initiative cohort. For each diagnostic group, we performed a conjunction analysis and compared the rostral and caudal hippocampal network changes using a mixed effects linear model to estimate the convergence and differences between these networks, respectively. The conjunction analysis showed a reduction of rostral-caudal hippocampal convergence strength from early MCI to AD, independent of hippocampal atrophy. Our results demonstrate a parallel between the functional convergence within the hippocampus and disease stage, which is independent of brain atrophy. These findings support the concept that network convergence might contribute as a biomarker for connectivity dysfunction in early stages of AD.

PMID: 31230260 [PubMed - as supplied by publisher]

The anterior insula channels prefrontal expectancy signals during affective processing.

Mon, 06/24/2019 - 21:02

The anterior insula channels prefrontal expectancy signals during affective processing.

Neuroimage. 2019 Jun 20;:

Authors: Teckentrup V, van der Meer JN, Borchardt V, Fan Y, Neuser MP, Tempelmann C, Herrmann L, Walter M, Kroemer NB

Abstract
Expectancy shapes our perception of impending events. Although such an interplay between cognitive and affective processes is often impaired in mental disorders, it is not well understood how top-down expectancy signals modulate future affect. We therefore track the information flow in the brain during cognitive and affective processing segregated in time using task-specific cross-correlations. Participants in two independent fMRI studies (N1 = 37 & N2 = 55) were instructed to imagine a situation with affective content as indicated by a cue, which was then followed by an emotional picture congruent with expectancy. To correct for intrinsic covariance of brain function, we calculate resting-state cross-correlations analogous to the task. First, using factorial modeling of delta cross-correlations (task-rest) of the first study, we find that the magnitude of expectancy signals in the anterior insula cortex (AIC) modulates the BOLD response to emotional pictures in the anterior cingulate and dorsomedial prefrontal cortex in opposite directions. Second, using hierarchical linear modeling of lagged connectivity, we demonstrate that expectancy signals in the AIC indeed foreshadow this opposing pattern in the prefrontal cortex. Third, we replicate the results in the second study using a higher temporal resolution, showing that our task-specific cross-correlation approach robustly uncovers the dynamics of information flow. We conclude that the AIC arbitrates the recruitment of distinct prefrontal networks during cued picture processing according to triggered expectations. Taken together, our study provides new insights into neuronal pathways channeling cognition and affect within well-defined brain networks. Better understanding of such dynamics could lead to new applications tracking aberrant information processing in mental disorders.

PMID: 31229657 [PubMed - as supplied by publisher]

Detecting resting-state brain activity using OEF-weighted imaging.

Mon, 06/24/2019 - 00:01
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Detecting resting-state brain activity using OEF-weighted imaging.

Neuroimage. 2019 Jun 19;:

Authors: Yang Y, Yin Y, Lu J, Zou Q, Gao JH

Abstract
Traditional resting-state functional magnetic resonance imaging (fMRI) is mainly based on the blood oxygenation level-dependent (BOLD) contrast. The oxygen extraction fraction (OEF) represents an important parameter of brain metabolism and is a key biomarker of tissue viability, detecting the ratio of oxygen utilization to oxygen delivery. Investigating spontaneous fluctuations in the OEF-weighted signal is crucial for understanding the underlying mechanism of brain activity because of the immense energy budget during the resting state. However, due to the poor temporal resolution of OEF mapping, no studies have reported using OEF contrast to assess resting-state brain activity. In this fMRI study, we recorded brain OEF-weighted fluctuations for 10 min in healthy volunteers across two scanning visits, using our recently developed pulse sequence that can acquire whole-brain voxel-wise OEF-weighted signals with a temporal resolution of 3 s. Using both group-independent component analysis and seed-based functional connectivity analysis, we robustly identified intrinsic brain networks, including the medial visual, lateral visual, auditory, default mode and bilateral executive control networks, using OEF contrast. Furthermore, we investigated the resting-state local characteristics of brain activity based on OEF-weighted signals using regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuations (fALFF). We demonstrated that the gray matter regions of the brain, especially those in the default mode network, showed higher ReHo and fALFF values with the OEF contrast. Moreover, voxel-wise test-retest reliability comparisons across the whole brain demonstrated that the reliability of resting-state brain activity based on the OEF contrast was moderate for the network indices and high for the local activity indices, especially for ReHo. Although the reliabilities of the OEF-based indices were generally lower than those based on BOLD, the reliability of OEF-ReHo was slightly higher than that of BOLD-ReHo, with a small effect size, which indicated that OEF-ReHo could be used as a reliable index for characterizing resting-state local brain activity as a complement to BOLD. In conclusion, OEF can be used as an effective contrast to study resting-state brain activity with a medium to high test-retest reliability.

PMID: 31228637 [PubMed - as supplied by publisher]

A machine learning investigation of volumetric and functional MRI abnormalities in adults born preterm.

Mon, 06/24/2019 - 00:01
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A machine learning investigation of volumetric and functional MRI abnormalities in adults born preterm.

Hum Brain Mapp. 2019 Jun 22;:

Authors: Shang J, Fisher P, Bäuml JG, Daamen M, Baumann N, Zimmer C, Bartmann P, Boecker H, Wolke D, Sorg C, Koutsouleris N, Dwyer DB

Abstract
Imaging studies have characterized functional and structural brain abnormalities in adults after premature birth, but these investigations have mostly used univariate methods that do not account for hypothesized interdependencies between brain regions or quantify accuracy in identifying individuals. To overcome these limitations, we used multivariate machine learning to identify gray matter volume (GMV) and amplitude of low frequency fluctuations (ALFF) brain patterns that best classify young adults born very preterm/very low birth weight (VP/VLBW; n = 94) from those born full-term (FT; n = 92). We then compared the spatial maps of the structural and functional brain signatures and validated them by assessing associations with clinical birth history and basic cognitive variables. Premature birth could be predicted with a balanced accuracy of 80.7% using GMV and 77.4% using ALFF. GMV predictions were mediated by a pattern of subcortical and middle temporal reductions and volumetric increases of the lateral prefrontal, medial prefrontal, and superior temporal gyrus regions. ALFF predictions were characterized by a pattern including increases in the thalamus, pre- and post-central gyri, and parietal lobes, in addition to decreases in the superior temporal gyri bilaterally. Decision scores from each classification, assessing the degree to which an individual was classified as a VP/VLBW case, were predicted by the number of days in neonatal hospitalization and birth weight. ALFF decision scores also contributed to the prediction of general IQ, which highlighted their potential clinical significance. Combined, the results clarified previous research and suggested that primary subcortical and temporal damage may be accompanied by disrupted neurodevelopment of the cortex.

PMID: 31228329 [PubMed - as supplied by publisher]

The effect of cognitive training on the brain's local connectivity organization in healthy older adults.

Mon, 06/24/2019 - 00:01
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The effect of cognitive training on the brain's local connectivity organization in healthy older adults.

Sci Rep. 2019 Jun 21;9(1):9033

Authors: Deng L, Cheng Y, Cao X, Feng W, Zhu H, Jiang L, Wu W, Tong S, Sun J, Li C

Abstract
Cognitive training has been shown effective in improving the cognitive function of older adults. While training related plasticity of the brain has been observed at different levels, it is still open to exploration whether local functional connectivity (FC) may be affected by training. Here, we examined the neuroimaging data from a previous randomized-controlled double-blinded behavioural study, in which healthy older adults participated in a 3-month cognitive training program. Resting-state fMRI was acquired at baseline and one year after training. The local FC in the brain was estimated using the regional homogeneity (ReHo), and the high ReHo clusters (HRCs) were extracted to quantify the level of local FC integration. Results showed that: (i) HRCs exhibited a power-law size distribution; (ii) local FC were less integrated in older participants than in younger participants; (iii) local FC in older participants of the training group became more integrated after training than the control group; (iv) the baseline local FC integration was positively correlated with educational level. These results indicated a training-related alteration in local FC.

PMID: 31227777 [PubMed - in process]

Rapid Reconfiguration of the Functional Connectome after Chemogenetic Locus Coeruleus Activation.

Mon, 06/24/2019 - 00:01
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Rapid Reconfiguration of the Functional Connectome after Chemogenetic Locus Coeruleus Activation.

Neuron. 2019 Jun 07;:

Authors: Zerbi V, Floriou-Servou A, Markicevic M, Vermeiren Y, Sturman O, Privitera M, von Ziegler L, Ferrari KD, Weber B, De Deyn PP, Wenderoth N, Bohacek J

Abstract
The locus coeruleus (LC) supplies norepinephrine (NE) to the entire forebrain and regulates many fundamental brain functions. Studies in humans have suggested that strong LC activation might shift network connectivity to favor salience processing. To causally test this hypothesis, we use a mouse model to study the effect of LC stimulation on large-scale functional connectivity by combining chemogenetic activation of the LC with resting-state fMRI, an approach we term "chemo-connectomics." We show that LC activation rapidly interrupts ongoing behavior and strongly increases brain-wide connectivity, with the most profound effects in the salience and amygdala networks. Functional connectivity changes strongly correlate with transcript levels of alpha-1 and beta-1 adrenergic receptors across the brain, and functional network connectivity correlates with NE turnover within select brain regions. We propose that these changes in large-scale network connectivity are critical for optimizing neural processing in the context of increased vigilance and threat detection.

PMID: 31227310 [PubMed - as supplied by publisher]

On the Relationship between MRI and Local Field Potential Measurements of Spatial and Temporal Variations in Functional Connectivity.

Sun, 06/23/2019 - 00:00
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On the Relationship between MRI and Local Field Potential Measurements of Spatial and Temporal Variations in Functional Connectivity.

Sci Rep. 2019 Jun 20;9(1):8871

Authors: Shi Z, Wilkes DM, Yang PF, Wang F, Wu R, Wu TL, Chen LM, Gore JC

Abstract
Correlations between fluctuations in resting state BOLD fMRI signals are interpreted as measures of functional connectivity (FC), but the neural basis of their origins and their relationships to specific features of underlying electrophysiologic activity, have not been fully established. In particular, the dependence of FC metrics on different frequency bands of local field potentials (LFPs), and the relationship of dynamic changes in BOLD FC to underlying temporal variations of LFP correlations, are not known. We compared the spatial profiles of resting state coherences of different frequency bands of LFP signals, with high resolution resting state BOLD FC measurements. We also compared the probability distributions of temporal variations of connectivity in both modalities using a Markov chain model-based approach. We analyzed data obtained from the primary somatosensory (S1) cortex of monkeys. We found that in areas 3b and 1 of S1 cortex, low frequency LFP signal fluctuations were the main contributions to resting state LFP coherence. Additionally, the dynamic changes of BOLD FC behaved most similarly to the LFP low frequency signal coherence. These results indicate that, within the S1 cortex meso-scale circuit studied, resting state FC measures from BOLD fMRI mainly reflect contributions from low frequency LFP signals and their dynamic changes.

PMID: 31222020 [PubMed - in process]

Functional Connectivity Associated with Health-Related Quality of Life in Children with Focal Epilepsy.

Sun, 06/23/2019 - 00:00
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Functional Connectivity Associated with Health-Related Quality of Life in Children with Focal Epilepsy.

AJNR Am J Neuroradiol. 2019 Jun 20;:

Authors: Nawani H, Smith ML, Wheeler AL, Widjaja E

Abstract
BACKGROUND AND PURPOSE: Although functional connectivity has been linked to cognitive function in epilepsy, its relationship with physical, psychological, or social dysfunction is unknown. This study aimed to assess the relationship between network architecture from resting-state fMRI and health-related quality of life in children with medically intractable focal epilepsy.
MATERIALS AND METHODS: Forty-seven children with nonlesional focal epilepsy were included; 22 had frontal lobe epilepsy and 15 had temporal lobe epilepsy. We computed graph metrics of functional connectivity, including network segregation (clustering coefficient and modularity) and integration (characteristic path length and participation coefficient). Health-related quality of life was measured using the Quality of Life in Childhood Epilepsy questionnaire. We examined the associations between graph metrics and the Quality of Life in Childhood Epilepsy total and domains scores, with age, sex, age at seizure onset, fMRI motion, and network density as covariates.
RESULTS: There was a negative relationship between the clustering coefficient and total Quality of Life in Childhood Epilepsy score [t(40) = -2.0; P = .04] and social function [t(40) = -2.9; P = .005]. There was a positive association between the mean participation coefficient and total Quality of Life in Childhood Epilepsy score [t(40) = 2.2; P = .03] and cognition [t(40) = 3.8; P = .0004]. In temporal lobe epilepsy, there was a negative relationship between the clustering coefficient and total Quality of Life in Childhood Epilepsy score [t(8) = -2.8; P = .02] and social function [t(8) = -3.6; P = .0075] and between modularity and total Quality of Life in Childhood Epilepsy score [t(8) = -2.5; P = .04] and social function [t(8) = -4.4; P = .0021]. In frontal lobe epilepsy, there was no association between network segregation and integration and Quality of Life in Childhood Epilepsy total or domain scores.
CONCLUSIONS: Our findings indicate that there are other higher order brain functions beyond cognition, which may be linked with functional connectivity of the brain.

PMID: 31221633 [PubMed - as supplied by publisher]

Surface-based regional homogeneity in bipolar disorder: A resting-state fMRI study.

Fri, 06/21/2019 - 23:59
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Surface-based regional homogeneity in bipolar disorder: A resting-state fMRI study.

Psychiatry Res. 2019 May 31;278:199-204

Authors: Zhang B, Wang F, Dong HM, Jiang XW, Wei SN, Chang M, Yin ZY, Yang N, Zuo XN, Tang YQ, Xu K

Abstract
Surface-based, two-dimensional regional homogeneity (2dReHo) was used in the current study to compare local functional synchronization of spontaneous neuronal activity between patients with bipolar disorder (BD) and healthy controls (HC), rather than volume-based, three-dimensional regional homogeneity (3dReHo) methods that have been previously described. Seventy-one BD patients and 113 HC participated in structural and resting-state fMRI scans. Participants ranged in age from 12 to 54 years. All subjects were rated with the Young Mania Rating Scale and the Hamilton Depression Rating Scale. BD patients showed reduced surface-based ReHo across the cortical surface, both at the global level and in the left ventral visual stream (VVS). Additionally, ReHo value across the cortical surface showed a significant negative correlation with age in both groups at the global level. Abnormal activity in the left VVS cortex may contribute to the pathogenesis of BD. Therefore, surface-based ReHo may be a useful index to explore the pathophysiology of BD.

PMID: 31220786 [PubMed - as supplied by publisher]

Abnormal spontaneous neural activity of brain regions in patients with primary blepharospasm at rest.

Fri, 06/21/2019 - 23:59
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Abnormal spontaneous neural activity of brain regions in patients with primary blepharospasm at rest.

J Neurol Sci. 2019 Jun 05;403:44-49

Authors: Jiang W, Lan Y, Cen C, Liu Y, Feng C, Lei Y, Guo W, Luo S

Abstract
BACKGROUND: Primary blepharospasm (BSP) is characterized by excessive involuntary eyelid spasms without significant morphological brain abnormalities. Its neural bases remain unclear. Resting-state functional magnetic resonance imaging (rs-fMRI) is a powerful tool for exploring cerebral function mechanisms in BSP.
METHODS: Two subject groups (24 patients with BSP and 24 healthy controls) underwent rs-fMRI scans. The rs-fMRI images were analyzed using the regional homogeneity (ReHo) method to assess the local features of spontaneous brain activity. Correlation analysis was carried out to explore the relationship between the ReHo values of abnormal brain areas and clinical variables including illness duration, symptom severity, and depression/anxiety symptoms.
RESULTS: Relative to healthy controls, patients with BSP showed significantly decreased ReHo in the left superior temporal pole/left insula, left calcarine cortex, and bilateral superior medial frontal gyrus (mSFG), and increased ReHo in the bilateral supplementary motor area (SMA). There were no significant correlations between ReHo values in these brain regions and clinical variables in the patients.
CONCLUSIONS: Our results suggest that abnormal spontaneous brain activity in multiple brain regions not limited to the basal ganglia may be trait alterations in the patients, which provides more insights into the pathogenesis of BSP.

PMID: 31220741 [PubMed - as supplied by publisher]

EEG-correlated fMRI of human alpha (de-)synchronization.

Fri, 06/21/2019 - 23:59
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EEG-correlated fMRI of human alpha (de-)synchronization.

Clin Neurophysiol. 2019 May 24;130(8):1375-1386

Authors: Knaut P, von Wegner F, Morzelewski A, Laufs H

Abstract
OBJECTIVES: We investigated blood oxygenation level-dependent (BOLD) brain activity changes in wakefulness and light sleep and in relation to those associated with the posterior alpha rhythm, the most prominent feature of the clinical EEG. Studies have reported different sets of brain regions changing their oxygen consumption with waxing and waning alpha oscillations. Here, we hypothesize that these dissimilar activity patterns reflect different wakefulness-dependent brain states.
METHODS: We recorded BOLD signal changes and electroencephalography (EEG) simultaneously in 149 subjects at rest. Based on American Academy of Sleep Medicine criteria, we selected subjects exhibiting wakefulness or light sleep (N1). We identified brain regions in which BOLD signal changes correlated with (i) clinical sleep stages, (ii) alpha band power and (iii) a multispectral EEG index, respectively.
RESULTS: During light sleep, we found increased BOLD activity in parieto-occipital regions. In wakefulness compared to light sleep, we revealed BOLD signal increases in the thalamus. The multispectral EEG-index revealed hippocampal activity changes in light sleep not reported before.
CONCLUSION: Changes in alpha oscillations reflect different brain states associated with different levels of wakefulness and thalamic activity. We can link the previously described parieto-occipital pattern to drowsiness. Additionally, in that stage, we identify hippocampal activity fluctuations.
SIGNIFICANCE: Thalamic activity varies with early changes of wakefulness, which is important to consider in resting state experiments. The EEG-indexed activation of the hippocampus during light sleep suggests that memory encoding might already take place during this early stage of sleep.

PMID: 31220698 [PubMed - as supplied by publisher]

Ensemble learning with 3D convolutional neural networks for functional connectome-based prediction.

Fri, 06/21/2019 - 23:59
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Ensemble learning with 3D convolutional neural networks for functional connectome-based prediction.

Neuroimage. 2019 Jun 17;:

Authors: Khosla M, Jamison K, Kuceyeski A, Sabuncu MR

Abstract
The specificity and sensitivity of resting state functional MRI (rs-fMRI) measurements depend on preprocessing choices, such as the parcellation scheme used to define regions of interest (ROIs). In this study, we critically evaluate the effect of brain parcellations on machine learning models applied to rs-fMRI data. Our experiments reveal an intriguing trend: On average, models with stochastic parcellations consistently perform as well as models with widely used atlases at the same spatial scale. We thus propose an ensemble learning strategy to combine the predictions from models trained on connectivity data extracted using different (e.g., stochastic) parcellations. We further present an implementation of our ensemble learning strategy with a novel 3D Convolutional Neural Network (CNN) approach. The proposed CNN approach takes advantage of the full-resolution 3D spatial structure of rs-fMRI data and fits non-linear predictive models. Our ensemble CNN framework overcomes the limitations of traditional machine learning models for connectomes that often rely on region-based summary statistics and/or linear models. We showcase our approach on a classification (autism patients versus healthy controls) and a regression problem (prediction of subject's age), and report promising results.

PMID: 31220576 [PubMed - as supplied by publisher]

From Synchrony to Asynchrony: Cerebellar-Basal Ganglia Functional Circuits in Young and Older Adults.

Fri, 06/21/2019 - 23:59
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From Synchrony to Asynchrony: Cerebellar-Basal Ganglia Functional Circuits in Young and Older Adults.

Cereb Cortex. 2019 Jun 20;:

Authors: Hausman HK, Jackson TB, Goen JRM, Bernard JA

Abstract
Resting state functional magnetic resonance imaging (rs-fMRI) has indicated disruptions in functional connectivity in older adults (OA) relative to young adults (YA). While age differences in cortical networks are well studied, differences in subcortical networks are poorly understood. Both the cerebellum and the basal ganglia are of particular interest given their role in cognitive and motor functions, and work in nonhuman primates has demonstrated direct reciprocal connections between these regions. Here, our goal was twofold. First, we were interested in delineating connectivity patterns between distinct regions of the cerebellum and basal ganglia, known to have topologically distinct connectivity patterns with cortex. Our second goal was to quantify age differences in these cerebellar-striatal circuits. We performed a targeted rs-fMRI analysis of the cerebellum and basal ganglia in 33 YA and 31 OA individuals. In the YA, we found significant connectivity both within and between the cerebellum and basal ganglia, in patterns supporting semi-discrete circuits that may differentially subserve motor and cognitive performance. We found a shift in connectivity, from one of synchrony in YA, to asynchrony in OA, resulting in substantial age differences. Connectivity was also associated with behavior. These findings significantly advance our understanding of cerebellar-basal ganglia interactions in the human brain.

PMID: 31219563 [PubMed - as supplied by publisher]

[POTENTIAL CLINICAL APPLICATIONS OF RESTING-STATE-FMRI IN NEUROLOGY].

Fri, 06/21/2019 - 02:58
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[POTENTIAL CLINICAL APPLICATIONS OF RESTING-STATE-FMRI IN NEUROLOGY].

Harefuah. 2019 Jun;158(6):378-382

Authors: Paz R

Abstract
INTRODUCTION: Resting-state functional Magnetic Resonance Imaging (rs-fMRI) is a non-invasive technique allowing to characterize brain functional connectivity. Blood oxygenation, the basis of the fMRI signal, fluctuates in the resting brain. These fluctuations have been shown to correlate between anatomically connected regions, thus allowing to examine functional connectivity between local and distal brain regions. The ability to identify functional networks, and to characterize their inter- and intra-connectivity is the basis for the development of useful clinical applications, which are especially relevant for neurological and neuropsychiatric diseases and disorders, in which network organization is altered. In this article, I will describe this method, review results obtained with it and demonstrate its potential through the consideration of findings from Alzheimer's disease research.

PMID: 31215190 [PubMed - in process]

Ischemic Stroke in Pontine and Corona Radiata: Location Specific Impairment of Neural Network Investigated With Resting State fMRI.

Fri, 06/21/2019 - 02:58
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Ischemic Stroke in Pontine and Corona Radiata: Location Specific Impairment of Neural Network Investigated With Resting State fMRI.

Front Neurol. 2019;10:575

Authors: Jiang C, Yi L, Cai S, Zhang L

Abstract
Objective: This study aims to investigate location-specific functional remodeling following ischemic stroke in pons and corona radiata. Methods: This study was approved by the local Institutional Review Board. Written consent was obtained from each of the participants prior to the MRI examination. Thirty six subjects with first ever acute ischemic stroke in pons (PS, n = 15, aged 62.8 ± 11.01 years) or corona radiata (CRS, n = 21, aged 59.33 ± 13.84 years) as well as 30 age and sex matched healthy controls (HC, n = 30, aged 60 ± 6.43 years) were examined with resting state functional magnetic resonance imaging (rs-fMRI). Regional homogeneity (ReHo) and degree centrality (DC) were calculated using a voxel-based approach. Intergroup differences in ReHo and DC were explored using a permutation test with a threshold-free cluster enhancement (PT TFCE, number of permutations = 1,000, family-wise error rate (FWER) < 0.05). Results: ReHo and DC alterations were identified in distributed anatomies for both PS and CRS groups. DC mainly increased in the bilateral anterior and posterior cingulate cortex, the inferior frontal-orbital gyrus, and decreased in the bilateral cuneus, calcarine, and the precuneus, while ReHo mainly decreased in the precentral and the postcentral gyri, inferior parietal lobules, precuneus, posterior cingulate cortex, and the superior occipital gyrus. PS and CRS groups were not significantly different in ReHo or DC (FWER > 0.05). Conclusions: Focal ischemic stroke in pons or corona radiata leads to extensive alterations in the functional network centrality. IS-induced network remodeling is more anatomy-specific than pathway-specific, which may underpin the clinicotopographical profiles during the disease dynamic. Approaches targeting neural pathway and functional connectivity may shed light on a better characterization and management innovation of ischemic stroke.

PMID: 31214111 [PubMed]