Most recent paper

Examining resting-state functional connectivity in first-episode schizophrenia with 7T fMRI and MEG.

Neuroimage Clin. 2019 Jul 23;24:101959

Authors: Lottman KK, Gawne TJ, Kraguljac NV, Killen JF, Reid MA, Lahti AC

Abstract
Schizophrenia is often characterized by dysconnections in the brain, which can be estimated via functional connectivity analyses. Commonly measured using resting-state functional magnetic resonance imaging (fMRI) in order to characterize the intrinsic or baseline function of the brain, fMRI functional connectivity has significantly contributed to the understanding of schizophrenia. However, these measures may not capture the full extent of functional connectivity abnormalities in schizophrenia as fMRI is temporally limited by the hemodynamic response. In order to extend fMRI functional connectivity findings, the complementary modality of magnetoencephalography (MEG) can be utilized to capture electrophysiological functional connectivity abnormalities in schizophrenia that are not obtainable with fMRI. Therefore, we implemented a multimodal functional connectivity analysis using resting-state 7 Tesla fMRI and MEG data in a sample of first-episode patients with schizophrenia (n = 19) and healthy controls (n = 24). fMRI and MEG data were decomposed into components reflecting resting state networks using a group spatial independent component analysis. Functional connectivity between resting-state networks was computed and group differences were observed. In fMRI, patients demonstrated hyperconnectivity between subcortical and auditory networks, as well as hypoconnectivity between interhemispheric homotopic sensorimotor network components. In MEG, patients demonstrated hypoconnectivity between sensorimotor and task positive networks in the delta frequency band. Results not only support the dysconnectivity hypothesis of schizophrenia, but also suggest the importance of jointly examining multimodal neuroimaging data as critical disorder-related information may not be detectable in a single modality alone.

PMID: 31377556 [PubMed - as supplied by publisher]

Alterations in knee sensorimotor brain functional connectivity contributes to ACL injury in male high-school football players: a prospective neuroimaging analysis.

Braz J Phys Ther. 2019 Jul 17;:

Authors: Diekfuss JA, Grooms DR, Nissen KS, Schneider DK, Foss KDB, Thomas S, Bonnette S, Dudley JA, Yuan W, Reddington DL, Ellis JD, Leach J, Gordon M, Lindsey C, Rushford K, Shafer C, Myer GD

Abstract
OBJECTIVE: This study's purpose was to utilize a prospective dataset to examine differences in functional brain connectivity in male high school athletes who suffered an ACL anterior cruciate ligament injury relative to their non-injured peers.
METHODS: Sixty-two male high school football players were evaluated using functional magnetic resonance imaging prior to their competitive season to evaluate resting-state functional brain connectivity. Three athletes later experienced an ACL injury and were matched to 12 teammates who did not go on to sustain an ACL injury (controls) based on school, age, height, weight, and year in school. Twenty-five knee-motor regions of interest (ROIs) were created to identify differences in connectivity between the two groups. Between-subject F and t tests were used to identify significant ROI differences using a false discovery rate correction for multiple comparisons.
RESULTS: There was significantly less connectivity between the left secondary somatosensory cortex and the left supplementary motor area (p = 0.025), right pre-motor cortex (p = 0.026), right supplementary motor area (p = 0.026), left primary somatosensory cortex (superior division; p = 0.026), left primary somatosensory cortex (inferior division; p = 0.026), and left primary motor cortex (p = 0.048) for the ACL-injured compared to the control subjects. No other ROI-to-ROI comparisons were significantly different between the groups (all p > 0.05).
CONCLUSION: Our preliminary data indicate a potential sensorimotor disruption for male football players who go on to experience an ACL injury. Future studies with larger sample sizes and complimentary measures of neuromuscular control are needed to support these findings.

PMID: 31377125 [PubMed - as supplied by publisher]

The impact of ischemic stroke on connectivity gradients.

Neuroimage Clin. 2019 Jul 19;24:101947

Authors: Bayrak Ş, Khalil AA, Villringer K, Fiebach JB, Villringer A, Margulies DS, Ovadia-Caro S

Abstract
The functional organization of the brain can be represented as a low-dimensional space that reflects its macroscale hierarchy. The dimensions of this space, described as connectivity gradients, capture the similarity of areas' connections along a continuous space. Studying how pathological perturbations with known effects on functional connectivity affect these connectivity gradients provides support for their biological relevance. Previous work has shown that localized lesions cause widespread functional connectivity alterations in structurally intact areas, affecting a network of interconnected regions. By using acute stroke as a model of the effects of focal lesions on the connectome, we apply the connectivity gradient framework to depict how functional reorganization occurs throughout the brain, unrestricted by traditional definitions of functional network boundaries. We define a three-dimensional connectivity space template based on functional connectivity data from healthy controls. By projecting lesion locations into this space, we demonstrate that ischemic strokes result in dimension-specific alterations in functional connectivity over the first week after symptom onset. Specifically, changes in functional connectivity were captured along connectivity Gradients 1 and 3. The degree of functional connectivity change was associated with the distance from the lesion along these connectivity gradients (a measure of functional similarity) regardless of the anatomical distance from the lesion. Together, these results provide support for the biological validity of connectivity gradients and suggest a novel framework to characterize connectivity alterations after stroke.

PMID: 31376644 [PubMed - as supplied by publisher]

Structural and functional asymmetry of the language network emerge in early childhood.

Dev Cogn Neurosci. 2019 Jul 21;39:100682

Authors: Reynolds JE, Long X, Grohs MN, Dewey D, Lebel C

Abstract
Structural and functional neuroimaging studies show language and reading processes are left-lateralized, and associated with a dispersed group of left brain regions. However, it is unclear when and how asymmetry of these regions emerges. We characterized the development of structural and functional asymmetry of the language network in 386 datasets from 117 healthy children (58 male) across early childhood (2-7.5 years). Structural asymmetry was investigated using diffusion tensor imaging (DTI) and manual delineation of the arcuate fasciculus. Functional connectivity asymmetry was calculated from seed regions in the inferior frontal gyrus (IFG) and middle temporal gyrus (MTG). We show that macrostructural asymmetry of the arcuate fasciculus is present by age 2 years, while leftward asymmetry of microstructure and functional connectivity with the IFG increases across the age range. This emerging microstructural and functional asymmetry likely underlie the development of language and reading skills during this time.

PMID: 31376589 [PubMed - as supplied by publisher]

Functional MRI and resting state connectivity in white matter - a mini-review.

Magn Reson Imaging. 2019 Jul 31;:

Authors: Gore JC, Li M, Gao Y, Wu TL, Schilling KG, Huang Y, Mishra A, Newton AT, Rogers BP, Chen LM, Anderson AW, Ding Z

Abstract
Functional MRI (fMRI) signals are robustly detectable in white matter (WM) but they have been largely ignored in the fMRI literature. Their nature, interpretation, and relevance as potential indicators of brain function remain under explored and even controversial. Blood oxygenation level dependent (BOLD) contrast has for over 25 years been exploited for detecting localized neural activity in the cortex using fMRI. While BOLD signals have been reliably detected in grey matter (GM) in a very large number of studies, such signals have rarely been reported from WM. However, it is clear from our own and other studies that although BOLD effects are weaker in WM, using appropriate detection and analysis methods they are robustly detectable both in response to stimuli and in a resting state. BOLD fluctuations in a resting state exhibit similar temporal and spectral profiles in both GM and WM, and their relative low frequency (0.01-0.1 Hz) signal powers are comparable. They also vary with baseline neural activity e.g. as induced by different levels of anesthesia, and alter in response to a stimulus. In previous work we reported that BOLD signals in WM in a resting state exhibit anisotropic temporal correlations with neighboring voxels. On the basis of these findings, we derived functional correlation tensors that quantify the correlational anisotropy in WM BOLD signals. We found that, along many WM tracts, the directional preferences of these functional correlation tensors in a resting state are grossly consistent with those revealed by diffusion tensors, and that external stimuli tend to enhance visualization of specific and relevant fiber pathways. These findings support the proposition that variations in WM BOLD signals represent tract-specific responses to neural activity. We have more recently shown that sensory stimulations induce explicit BOLD responses along parts of the projection fiber pathways, and that task-related BOLD changes in WM occur synchronously with the temporal pattern of stimuli. WM tracts also show a transient signal response following short stimuli analogous to but different from the hemodynamic response function (HRF) characteristic of GM. Thus there is converging and compelling evidence that WM exhibits both resting state fluctuations and stimulus-evoked BOLD signals very similar (albeit weaker) to those in GM. A number of studies from other laboratories have also reported reliable observations of WM activations. Detection of BOLD signals in WM has been enhanced by using specialized tasks or modified data analysis methods. In this mini-review we report summaries of some of our recent studies that provide evidence that BOLD signals in WM are related to brain functional activity and deserve greater attention by the neuroimaging community.

PMID: 31376477 [PubMed - as supplied by publisher]

Abnormal synchronization of functional and structural networks in schizophrenia.

Brain Imaging Behav. 2019 Aug 02;:

Authors: Zhu J, Qian Y, Zhang B, Li X, Bai Y, Li X, Yu Y

Abstract
Synchronization is believed to play an important role in information processing of the brain. Mounting evidence supports the hypothesis that schizophrenia is related to impaired neural synchrony. However, most previous studies characterize brain synchronization from the perspective of temporal coordination of distributed neural activity, rather than network properties. Our aim was to investigate the network synchronization alterations in schizophrenia using publically available data. Resting-state functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) were performed in 96 schizophrenia patients and 120 healthy controls. The whole-brain functional and structural networks were constructed and analyzed using graph theoretical approaches. Inter-group differences in network synchronization were investigated. Both the binary and weighted functional networks of schizophrenia patients exhibited decreased synchronizability (increased eigenratio) than those of healthy controls. With respect to the structural binary networks, schizophrenia patients showed a trend towards excessive synchronizability (decreased eigenratio). In addition, the excessive synchronizability of the structural binary networks was associated with more severe negative symptoms in schizophrenia patients. Our findings provide novel biological evidence that schizophrenia involves a disruption of neural synchrony from the perspective of network properties.

PMID: 31376115 [PubMed - as supplied by publisher]

Aberrant regional homogeneity in post-traumatic stress disorder after traffic accident: A resting-state functional MRI study.

Neuroimage Clin. 2019 Jul 22;24:101951

Authors: Fu S, Ma X, Li C, Wang T, Li C, Bai Z, Hua K, Yin Y, Wu Y, Yu K, Liu M, Ke Q, Tian J, Jiang G

Abstract
OBJECTIVES: The present study explored the changes in spontaneous regional activity in post-traumatic stress disorder (PTSD) patients, who experienced severe traffic accidents.
METHODS: 20 drug-naive PTSD patients and 18 healthy control subjects were imaged using resting-state functional magnetic resonance imaging (rs-fMRI) and analyzed by the algorithm of regional homogeneity (ReHo).
RESULTS: Compared to the healthy control group, the PTSD group showed decreased ReHo values in the right angular gyrus. In addition, a negative correlation was found between the activity level of the angular gyrus and the CAPS score.
CONCLUSION: The dysfunctions were found in the memory- and emotion-related areas, suggested a possible mechanism of memory dysregulation that might be related to the intrusive memory symptoms of PTSD. These results provided imaging evidence that might provide an in-depth understanding of the intrinsic functional architecture of PTSD.

PMID: 31374398 [PubMed - as supplied by publisher]

[Analysis on regional homogeneity of resting brain during balance acupuncture-induced analgesic effect in migraine patients without aura].

Zhen Ci Yan Jiu. 2019 Jun 25;44(6):446-50

Authors: Qin XL, Wang WY, Wang JZ, Xie WY, Zhang YM, Gao YQ

Abstract
OBJECTIVE: To observe the relationship between the analgesic effect of balance acupuncture and functional changes in brain in patients with migraine without aura.
METHODS: A total of 40 cases of migraine without aura were equally randomized into a headache-acupoint group and a sham-acupoint group. When acupuncture given, a filiform needle was inserted into the headache-acupoint (the midpoint of the depression region anterior to the juncture of the first and second metatarsal bones on the dorsum of the foot) or the sham point (the midpoint of the depression region anterior to the juncture site between the 3rd and 4th metatarsal joints of the dorsum of the foot) about 25-40 mm deep and manipulated for a while till the patient experienced feelings of electric shock and numbness, then withdrawn immediately. The treatment was conducted once daily for 4 weeks. The visual analogue scale (VAS) was used to evaluate the severity of pain, and the regional homogeneity (ReHo) analysis of resting state functional magnetic resonance imaging (fMRI) was used to assess changes of the spontaneous brain activity.
RESULTS: After acupuncture, the analgesic effect of headache-acupoint was better than that of the sham-acupoint in both intervention stage and the follow-up stage (P< 0.05), and was also stronger in the intervention stage than in the follow-up stage (P<0.05). There was no significant difference in the analgesic effect between the intervention stage and the follow-up stage in the sham-acupoint group (P>0.05). Compared with pre-intervention, 4-weeks' intervention at the headache-acupoint showed an increase of ReHo values in the anterior cingulate gyrus, anterior central gyrus, superior orbital frontal gyrus, insula, inferior lobule, left anterior cingulate gyrus, ventral lateral nucleus and ventral posteromedial nucleus of the thalamus, pontine nucleus, cerebellar tonsils and orbital frontal inferior gyrus of the brain (P<0.05), and a decrease of ReHo values in the right brain bridge, central posterior gyrus, posterior cingulate gyrus, left central anterior gyrus, posterolateral nucleus of thalamus, and hippocampus (P<0.05), separately. In the sham-acupoint group, the ReHo value was increased in the right tongue gyrus, the left anterior lobe, the anterior cingulate gyrus and the lower occipital gyrus of the brain (P<0.05), and reduced in the left ventral posterolateral nucleus of the thalamus, separately (P<0.05).
CONCLUSION: Balance acupuncture stimulation of headache acupoint has an analgesic effect in migraine patients without aura, which may be related to its effect in regulating resting state brain function of the limbic-system-dominated multiple brain regions.

PMID: 31368270 [PubMed - in process]

Effects of acupuncture on craving after tobacco cessation: a resting-state fMRI study based on the fractional amplitude of low-frequency fluctuation.

Quant Imaging Med Surg. 2019 Jun;9(6):1118-1125

Authors: Wang YY, Liu Z, Chen F, Sun L, Wu Y, Yang JS, Fang JL

Abstract
Background: To explore the immediate effects and mechanism of acupuncture on craving after tobacco cessation based on the fractional amplitude of low-frequency fluctuation (fALFF).
Methods: This was a functional magnetic resonance imaging (fMRI) study. Forty participants were recruited and divided into a smoking group and a non-smoking group, 20 cases in each one. The smoking participants were requested to quit smoking 24 hours before the fMRI scan. The scan process was scan - acupuncture - scan. Between the two scans, acupuncture was applied at Lieque (LU 7), Hegu (LI 4), Baihui (GV 20), Zusanli (ST 36), Sanyinjiao (SP 6) and Taichong (LR 3) in two groups.
Results: After acupuncture, self-made craving for smoking, Minnesota Nicotine Withdrawal Scale (MNWS) and Questionnaire of Smoking Urges (QSU) were all reduced (P<0.05). The fMRI results indicated the immediate effects of acupuncture on smoking craving were significant, and identified salience network (SN) consisted of anterior cingulate cortex and insula, prefrontal cortex, visual cortex and cerebellum as key brains area. Correlation analysis indicated that NWNS scores were positively correlated with the mean fALFF in the ACC (P<0.05) and negatively correlated with the mean fALFF in the insula (P<0.05) in the smoking group.
Conclusions: This was the first study in China to explore the neural mechanisms of acupuncture for smoking craving. The results indicated that the effects of acupuncture on smoking craving were significant, and the SN played a critical role in the process.

PMID: 31367566 [PubMed]

A role for the CD38 rs3796863 polymorphism in alcohol and monetary reward: evidence from CD38 knockout mice and alcohol self-administration, [11C]-raclopride binding, and functional MRI in humans.

Am J Drug Alcohol Abuse. 2019 Jul 31;:1-13

Authors: Lee MR, Shin JH, Deschaine S, Daurio AM, Stangl BL, Yan J, Ramchandani VA, Schwandt ML, Grodin EN, Momenan R, Corral-Frias NS, Hariri AR, Bogdan R, Alvarez VA, Leggio L

Abstract
Background: Cluster of differentiation 38 (CD38) is a transmembrane protein expressed in dopaminergic reward pathways in the brain, including the nucleus accumbens (NAc). The GG genotype of a common single nucleotide polymorphism (SNP) within CD38, rs3796863, is associated with increased social reward. Objective: Examine whether CD38 rs3796863 and Cd38 knockout (KO) are associated with reward-related neural and behavioral phenotypes. Methods: Data from four independent human studies were used to test whether rs3796863 genotype is associated with: (1) intravenous alcohol self-administration (n = 64, 30 females), (2) alcohol-stimulated dopamine (DA) release measured using 11C-raclopride positron emission tomography (n = 22 men), (3) ventral striatum (VS) response to positive feedback measured using a card guessing functional magnetic resonance imaging (fMRI) paradigm (n = 531, 276 females), and (4) resting state functional connectivity (rsfc) of the VS (n = 51, 26 females). In a fifth study, we used a mouse model to examine whether cd38 knockout influences stimulated DA release in the NAc core and dorsal striatum using fast-scanning cyclic voltammetry. Results: Relative to T allele carriers, G homozygotes at rs3796863 within CD38 were characterized by greater alcohol self-administration, alcohol-stimulated dopamine release, VS response to positive feedback, and rsfc between the VS and anterior cingulate cortex. High-frequency stimulation reduced DA release among Cd38 KO mice had reduced dopamine release in the NAc. Conclusion: Converging evidence suggests that CD38 rs3796863 genotype may increase DA-related reward response and alcohol consumption.

PMID: 31365285 [PubMed - as supplied by publisher]

Interpretable, highly accurate brain decoding of subtly distinct brain states from functional MRI using intrinsic functional networks and long short-term memory recurrent neural networks.

Neuroimage. 2019 Jul 27;:116059

Authors: Li H, Fan Y

Abstract
Decoding brain functional states underlying cognitive processes from functional MRI (fMRI) data using multivariate pattern analysis (MVPA) techniques has achieved promising performance for characterizing brain activation patterns and providing neurofeedback signals. However, it remains challenging to decode subtly distinct brain states for individual fMRI data points due to varying temporal durations and dependency among different cognitive processes. In this study, we develop a deep learning based framework for brain decoding by leveraging recent advances in intrinsic functional network modeling and sequence modeling using long short-term memory (LSTM) recurrent neural networks (RNNs). Particularly, subject-specific intrinsic functional networks (FNs) are computed from resting state fMRI data and are used to characterize functional signals of task fMRI data with a compact representation for building brain decoding models, and LSTM RNNs are adopted to learn brain decoding mappings between functional profiles and brain states. Validation results on fMRI data from the HCP dataset have demonstrated that brain decoding models built on training data using the proposed method could learn discriminative latent feature representations and effectively distinguish subtly distinct working memory tasks of different subjects with significantly higher accuracy than conventional decoding models. Informative FNs of the brain decoding models identified as brain activation patterns of working memory tasks were largely consistent with the literature. The method also obtained promising decoding performance on motor and social cognition tasks. Our results suggest that LSTM RNNs in conjunction with FNs could build interpretable, highly accurate brain decoding models.

PMID: 31362049 [PubMed - as supplied by publisher]

Altered Functional Brain Network Integration, Segregation, and Modularity in Infants Born Very Preterm at Term-Equivalent Age.

J Pediatr. 2019 Jul 26;:

Authors: Bouyssi-Kobar M, De Asis-Cruz J, Murnick J, Chang T, Limperopoulos C

Abstract
OBJECTIVES: To determine the functional network organization of the brain in infants born very preterm at term-equivalent age and to relate network alterations to known clinical risk factors for poor neurologic outcomes in prematurity.
STUDY DESIGN: Resting-state functional magnetic resonance imaging data from 66 infants born very preterm (gestational age <32 weeks and birth weight <1500 g) and 66 healthy neonates born at full term, acquired as part of a prospective, cross-sectional study, were compared at term age using graph theory. Features of resting-state networks, including integration, segregation, and modularity, were derived from correlated hemodynamic activity arising from 93 cortical and subcortical regions of interest and compared between groups.
RESULTS: Despite preserved small-world topology and modular organization, resting-state networks of infants born very preterm at term-equivalent age were less segregated and less integrated than those of infants born full term. Chronic respiratory illness (ie, bronchopulmonary dysplasia and the length of oxygen support) was associated with decreased global efficiency and increased path lengths (P < .05). In both cohorts, 4 functional modules with similar composition were observed (parietal/temporal, frontal, subcortical/limbic, and occipital). The density of connections in 3 of the 4 modules was decreased in the very preterm network (P < .01); however, in the occipital/visual cortex module, connectivity was increased in infants born very preterm relative to control infants (P < .0001).
CONCLUSIONS: Early exposure to the ex utero environment is associated with altered resting-state network functional organization in infants born very preterm at term-equivalent age, likely reflecting disrupted brain maturational processes.

PMID: 31358292 [PubMed - as supplied by publisher]

Decreased stimulus-driven connectivity of the primary visual cortex during visual motion stimulation in amnestic mild cognitive impairment: An fMRI study.

Neurosci Lett. 2019 Jul 26;:134402

Authors: Yamasaki T, Aso T, Kaseda Y, Mimori Y, Doi H, Matsuoka N, Takamiya N, Torii T, Takahashi T, Ohshita T, Yamashita H, Doi H, Inamizu S, Chatani H, Tobimatsu S

Abstract
Motion perceptual deficits are common in Alzheimer's disease (AD). Although the posterior parietal cortex is thought to play a critical role in these deficits, it is currently unclear whether the primary visual cortex (V1) contributes to these deficits in AD. To elucidate this issue, we investigated the net activity or connectivity within V1 in 17 amnestic mild cognitive impairment (aMCI) patients, 17 AD patients and 17 normal controls (NC) using functional magnetic resonance imaging (fMRI). fMRI was recorded under two conditions: visual motion stimulation and resting-state. The net activity or connectivity within V1 extracted by independent component analysis (ICA) was significantly increased during visual motion stimuli compared with that of the resting-state condition in NC, but not in aMCI or AD patients. These findings suggest the alteration of the net activity or connectivity within V1, which may contribute to the previously reported motion perceptual deficits in aMCI and AD. Therefore, the decreased net V1 activity measured as the strength of the ICA component may provide a new disease biomarker for early detection of AD.

PMID: 31356844 [PubMed - as supplied by publisher]

Predicting the Post-therapy Severity Level (UPDRS-III) of Patients With Parkinson's Disease After Drug Therapy by Using the Dynamic Connectivity Efficiency of fMRI.

Front Neurol. 2019;10:668

Authors: Li X, Xiong Y, Liu S, Zhou R, Hu Z, Tong Y, He L, Niu Z, Ma Y, Guo H

Abstract
Parkinson's disease (PD) is a multi-systemic disease in the brain arising from the dysfunction of several neural networks. The diagnosis and treatment of PD have gained more attention for clinical researchers. While there have been many fMRI studies about functional topological changes of PD patients, whether the dynamic changes of functional connectivity can predict the drug therapy effect is still unclear. The primary objective of this study was to assess whether large-scale functional efficiency changes of topological network are detectable in PD patients, and to explore whether the severity level (UPDRS-III) after drug treatment can be predicted by the pre-treatment resting-state fMRI (rs-fMRI). Here, we recruited 62 Parkinson's disease patients and calculated the dynamic nodal efficiency networks based on rs-fMRI. With connectome-based predictive models using the least absolute shrinkage and selection operator, we demonstrated that the dynamic nodal efficiency properties predict drug therapy effect well. The contributed regions for the prediction include hippocampus, post-central gyrus, cingulate gyrus, and orbital gyrus. Specifically, the connections between hippocampus and cingulate gyrus, hippocampus and insular gyrus, insular gyrus, and orbital gyrus are positively related to the recovery (post-therapy severity level) after drug therapy. The analysis of these connection features may provide important information for clinical treatment of PD patients.

PMID: 31354605 [PubMed]

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

Front Hum Neurosci. 2019;13:241

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
The idea that intelligence is embedded not only in a single brain network, but instead in a complex, well-optimized system of complementary networks, has led to the development of whole brain network analysis. Using graph theory to analyze resting-state functional MRI data, we investigated the brain graph networks (or brain networks) of high intelligence quotient (HIQ) children. To this end, we computed the "hub disruption index κ," an index sensitive to graph network modifications. We found significant topological differences in the integration and segregation properties of brain networks in HIQ compared to standard IQ children, not only for the whole brain graph, but also for each hemispheric graph, and for the homotopic connectivity. Moreover, two profiles of HIQ children, homogenous and heterogeneous, based on the differences between the two main IQ subscales [verbal comprehension index (VCI) and perceptual reasoning index (PRI)], were compared. Brain network changes were more pronounced in the heterogeneous than in the homogeneous HIQ subgroups. Finally, we found significant correlations between the graph networks' changes and the full-scale IQ (FSIQ), as well as the subscales VCI and PRI. Specifically, the higher the FSIQ the greater was the brain organization modification in the whole brain, the left hemisphere, and the homotopic connectivity. These results shed new light on the relation between functional connectivity topology and high intelligence, as well as on different intelligence profiles.

PMID: 31354458 [PubMed]

Characterizing the Dynamical Complexity Underlying Meditation.

Front Syst Neurosci. 2019;13:27

Authors: Escrichs A, Sanjuán A, Atasoy S, López-González A, Garrido C, Càmara E, Deco G

Abstract
Over the past 2,500 years, contemplative traditions have explored the nature of the mind using meditation. More recently, neuroimaging research on meditation has revealed differences in brain function and structure in meditators. Nevertheless, the underlying neural mechanisms are still unclear. In order to understand how meditation shapes global activity through the brain, we investigated the spatiotemporal dynamics across the whole-brain functional network using the Intrinsic Ignition Framework. Recent neuroimaging studies have demonstrated that different states of consciousness differ in their underlying dynamical complexity, i.e., how the broadness of communication is elicited and distributed through the brain over time and space. In this work, controls and experienced meditators were scanned using functional magnetic resonance imaging (fMRI) during resting-state and meditation (focused attention on breathing). Our results evidenced that the dynamical complexity underlying meditation shows less complexity than during resting-state in the meditator group but not in the control group. Furthermore, we report that during resting-state, the brain activity of experienced meditators showed higher metastability (i.e., a wider dynamical regime over time) than the one observed in the control group. Overall, these results indicate that the meditation state operates in a different dynamical regime compared to the resting-state.

PMID: 31354439 [PubMed]

Characterizing Rapid Fluctuations of Resting State Functional Connectivity in Demyelinating, Neurodegenerative, and Psychiatric Conditions: From Static to Time-Varying Analysis.

Front Neurosci. 2019;13:618

Authors: Valsasina P, Hidalgo de la Cruz M, Filippi M, Rocca MA

Abstract
Functional magnetic resonance imaging (fMRI) at resting state (RS) has been widely used to characterize the main brain networks. Functional connectivity (FC) has been mostly assessed assuming that FC is static across the whole fMRI examination. However, FC is highly variable at a very fast time-scale, as demonstrated by neurophysiological techniques. Time-varying functional connectivity (TVC) is a novel approach that allows capturing reoccurring patterns of interaction among functional brain networks. Aim of this review is to provide a description of the methods currently used to assess TVC on RS fMRI data, and to summarize the main results of studies applying TVC in healthy controls and patients with multiple sclerosis (MS). An overview of the main results obtained in neurodegenerative and psychiatric conditions is also provided. The most popular TVC approach is based on the so-called "sliding windows," in which the RS fMRI acquisition is divided in small temporal segments (windows). A window of fixed length is shifted over RS fMRI time courses, and data within each window are used to calculate FC and its variability over time. Sliding windows can be combined with clustering techniques to identify recurring FC states or used to assess global TVC properties of large-scale functional networks or specific brain regions. TVC studies have used heterogeneous methodologies so far. Despite this, similar results have been obtained across investigations. In healthy subjects, the default-mode network (DMN) exhibited the highest degree of connectivity dynamism. In MS patients, abnormal global TVC properties and TVC strengths were found mainly in sensorimotor, DMN and salience networks, and were associated with more severe structural MRI damage and with more severe physical and cognitive disability. Conversely, abnormal TVC measures of the temporal network were correlated with better cognitive performances and less severe fatigue. In patients with neurodegenerative and psychiatric conditions, TVC abnormalities of the DMN, attention and executive networks were associated to more severe clinical manifestations. TVC helps to provide novel insights into fundamental properties of functional networks, and improves the understanding of brain reorganization mechanisms. Future technical advances might help to clarify TVC association with disease prognosis and response to treatment.

PMID: 31354402 [PubMed]

Machine learning techniques in a structural and functional MRI diagnostic approach in schizophrenia: a systematic review.

Neuropsychiatr Dis Treat. 2019;15:1605-1627

Authors: de Filippis R, Carbone EA, Gaetano R, Bruni A, Pugliese V, Segura-Garcia C, De Fazio P

Abstract
Background: Diagnosis of schizophrenia (SCZ) is made exclusively clinically, since specific biomarkers that can predict the disease accurately remain unknown. Machine learning (ML) represents a promising approach that could support clinicians in the diagnosis of mental disorders.
Objectives: A systematic review, according to the PRISMA statement, was conducted to evaluate its accuracy to distinguish SCZ patients from healthy controls.
Methods: We systematically searched PubMed, Embase, MEDLINE, PsychINFO and the Cochrane Library through December 2018 using generic terms for ML techniques and SCZ without language or time restriction. Thirty-five studies were included in this review: eight of them used structural neuroimaging, twenty-six used functional neuroimaging and one both, with a minimum accuracy >60% (most of them 75-90%). Sensitivity, Specificity and accuracy were extracted from each publication or obtained directly from authors.
Results: Support vector machine, the most frequent technique, if associated with other ML techniques achieved accuracy close to 100%. The prefrontal and temporal cortices appeared to be the most useful brain regions for the diagnosis of SCZ. ML analysis can efficiently detect significantly altered brain connectivity in patients with SCZ (eg, default mode network, visual network, sensorimotor network, frontoparietal network and salience network).
Conclusion: The greater accuracy demonstrated by these predictive models and the new models resulting from the integration of multiple ML techniques will be increasingly decisive for early diagnosis and evaluation of the treatment response and to establish the prognosis of patients with SCZ. To achieve a real benefit for patients, the future challenge is to reach an accurate diagnosis not only through clinical evaluation but also with the aid of ML algorithms.

PMID: 31354276 [PubMed]

Multi-parametric analysis reveals metabolic and vascular effects driving differences in BOLD-based cerebrovascular reactivity associated with a history of sport concussion.

Brain Inj. 2019 Jul 27;:1-11

Authors: Champagne AA, Coverdale NS, Germuska M, Cook DJ

Abstract
Objective: Identify alterations in cerebrovascular reactivity (CVR) based on the history of sport-related concussion (SRC). Further explore possible mechanisms underlying differences in vascular physiology using hemodynamic parameters modeled using calibrated magnetic resonance imaging (MRI). Method: End-tidal targeting and dual-echo MRI were combined to probe hypercapnic and hyperoxic challenges in athletes with (n = 32) and without (n = 31) a history of SRC. Concurrent blood oxygenation level dependent (BOLD) and arterial spin labeling (ASL) data were used to compute BOLD-CVR, ASL-CVR, and other physiological parameters including resting oxygen extraction fraction (OEF0) and cerebral blood volume (CBV0). Multiple linear and logistic regressions were then used to identify dominant parameters driving group-differences in BOLD-CVR. Results: Robust evidence for elevated BOLD-CVR were found in athletes with SRC history spreading over parts of the cortical hemispheres. Follow-up analyses showed co-localized differences in ASL-CVR (representing modulation of cerebral blood flow) and hemodynamic factors representing static vascular (i.e., CBV0) and metabolic (i.e., OEF0) effects suggesting that group-based differences in BOLD-CVR may be driven by a mixed effect from factors with vascular and metabolic origins. Conclusion: These results emphasize that while BOLD-CVR offers promises as a surrogate non-specific biomarker for cerebrovascular health following SRC, multiple hemodynamic parameters can affect its relative measurements. Abbreviations: [dHb]: concentration of deoxyhemoglobin; AFNI: Analysis of Functional NeuroImages ( https://afni.nimh.nih.gov ); ASL: arterial spin labeling; BIG: position group: defensive and offensive linemen; BIG-SKILL: position group: full backs, linebackers, running backs, tight-ends; BOLD: blood oxygen level dependent; CBF: cerebral blood flow; CMRO2: cerebral metabolic rate of oxygen consumption; CTL: group of control subjects; CVR: cerebrovascular reactivity; fMRI: functional magnetic resonance imaging; FSL: FMRIB software library ( https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/ ); HC: hypercapnia; HO: hyperoxia; HX: group with history of concussion; M: maximal theoretical BOLD signal upon complete removal of venous dHb; pCASL: pseudo-continuous arterial spin labeling; PETCO2: end-tidal carbon dioxide; PETO2: end-tidal oxygen; SCAT: sport-concussion assessment tool; SKILL: position group: defensive backs, kickers, quarterbacks, safeties, wide-receivers; SRC: sport-related concussion.

PMID: 31354054 [PubMed - as supplied by publisher]

Early second-line therapy is associated with improved episodic memory in anti-NMDA receptor encephalitis.

Ann Clin Transl Neurol. 2019 Jul;6(7):1202-1213

Authors: Wang K, Chen Z, Wu D, Ding Q, Zheng X, Wang J, Ji C, Luo B

Abstract
OBJECTIVE: To investigate whether the early administration of intravenous second-line immunotherapy correlates with improved long-term cognition and the potential mechanisms via imaging in adult patients with moderate-to-severe anti-N-methyl-D-aspartate (NMDA) receptor encephalitis.
METHODS: Sixteen adult patients with moderate-to-severe anti-NMDA receptor encephalitis past the acute stage and 15 healthy controls (HCs) performed a set of comprehensive neuropsychological tests, and underwent a resting-state fMRI study to analyze resting state functional connectivity (FC). In addition, correlation analyses were performed between hippocampal FC and cognitive performance. All patients were received intravenous first-line immunotherapy, and nine of them were also given intravenous second-line immunotherapy within 3 months of disease onset.
RESULTS: The patients who only received first-line immunotherapy showed significant verbal episodic memory impairments compared with HCs and those who received second-line immunotherapy, while no significant differences were noted between the patients with second-line immunotherapy and the HCs. In line with the results of neuropsychological tests, significant changes in bilateral hippocampal FC were observed in the patients who only received first-line immunotherapy compared with both HCs and those who received second-line immunotherapy. However, no significant differences in hippocampal FC were observed in the patients with second-line immunotherapy compared with the HCs. Importantly, hippocampal-medial prefrontal cortex (mPFC) connectivity positively correlated with memory performance.
INTERPRETATION: In the long term, early administration of intravenous second-line immunotherapy may be associated with more favorable verbal episodic memory outcomes in patients with moderate-to-severe anti-NMDA receptor encephalitis. These results may provide some evidence and guidance for the use of immunotherapy in this population.

PMID: 31353868 [PubMed - in process]