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Sliding window correlation analysis: Modulating window shape for dynamic brain connectivity in resting state.

Thu, 02/07/2019 - 00:02
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Sliding window correlation analysis: Modulating window shape for dynamic brain connectivity in resting state.

Neuroimage. 2019 Feb 02;:

Authors: Mokhtari F, Akhlaghi MI, Simpson SL, Wu G, Laurienti PJ

Abstract
The sliding window correlation (SWC) analysis is a straightforward and common approach for evaluating dynamic functional connectivity. Despite the fact that sliding window analyses have been long used, there are still considerable technical issues associated with the approach. A great effort has recently been dedicated to investigate the window setting effects on dynamic connectivity estimation. In this direction, tapered windows have been proposed to alleviate the effect of sudden changes associated with the edges of rectangular windows. Nevertheless, the majority of the windows exploited to estimate brain connectivity tend to suppress dynamic correlations, especially those with faster variations over time. Here, we introduced a window named modulated rectangular (mRect) to address the suppressing effect associated with the conventional windows. We provided a frequency domain analysis using simulated time series to investigate how sliding window analysis (using the regular window functions, e.g. rectangular and tapered windows) may lead to unwanted spectral modulations, and then we showed how this issue can be alleviated through the mRect window. Moreover, we created simulated dynamic network data with altering states over time using simulated fMRI time series, to examine the performance of different windows in tracking network states. We quantified the state identification rate of different window functions through the Jaccard index, and observed superior performance of the mRect window compared to the conventional window functions. Overall, the proposed window function provides an approach that improves SWC estimations, and thus the subsequent inferences and interpretations based on the connectivity network analyses.

PMID: 30721750 [PubMed - as supplied by publisher]

Resting state connectivity differences in eyes open versus eyes closed conditions.

Thu, 02/07/2019 - 00:02
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Resting state connectivity differences in eyes open versus eyes closed conditions.

Hum Brain Mapp. 2019 Feb 05;:

Authors: Agcaoglu O, Wilson T, Wang YP, Stephen J, Calhoun VD

Abstract
Functional magnetic resonance imaging data are commonly collected during the resting state. Resting state functional magnetic resonance imaging (rs-fMRI) is very practical and applicable for a wide range of study populations. Rs-fMRI is usually collected in at least one of three different conditions/tasks, eyes closed (EC), eyes open (EO), or eyes fixated on an object (EO-F). Several studies have shown that there are significant condition-related differences in the acquired data. In this study, we compared the functional network connectivity (FNC) differences assessed via group independent component analysis on a large rs-fMRI dataset collected in both EC and EO-F conditions, and also investigated the effect of covariates (e.g., age, gender, and social status score). Our results indicated that task condition significantly affected a wide range of networks; connectivity of visual networks to themselves and other networks was increased during EO-F, while EC was associated with increased connectivity of auditory and sensorimotor networks to other networks. In addition, the association of FNC with age, gender, and social status was observed to be significant only in the EO-F condition (though limited as well). However, statistical analysis did not reveal any significant effect of interaction between eyes status and covariates. These results indicate that resting-state condition is an important variable that may limit the generalizability of clinical findings using rs-fMRI.

PMID: 30720907 [PubMed - as supplied by publisher]

Different Brain Activation after Acupuncture at Combined Acupoints and Single Acupoint in Hypertension Patients: An Rs-fMRI Study Based on ReHo Analysis.

Thu, 02/07/2019 - 00:02
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Different Brain Activation after Acupuncture at Combined Acupoints and Single Acupoint in Hypertension Patients: An Rs-fMRI Study Based on ReHo Analysis.

Evid Based Complement Alternat Med. 2019;2019:5262896

Authors: Zhang J, Cai X, Wang Y, Zheng Y, Qu S, Zhang Z, Yao Z, Chen G, Tang C, Huang Y

Abstract
Background: Acupuncture is proved to be effective on hypertension by numerous studies and resting-state functional magnetic resonance imaging (Rs-fMRI) is a widely used technique to study its mechanism. Along with lower blood pressure, patients with hypertension receiving acupuncture also presented improvement in function of cognition, emotion, language, sematic sensation, and so on. This study was a primary study to explore the acting path of acupuncture at combined acupoints in stimulated brain areas related to such functions.
Methods: In this research, regional homogeneity (ReHo) was applied to analyze the Rs-fMRI image data of brain activities after acupuncture at LR3, KI3, and LR3+KI3 and to compare the differences of functional brain activities between stimulating combined acupoints and single acupoint under pathological conditions. A total of thirty hypertension patients underwent Rs-fMRI scanning before acupuncture treatment and then were randomly divided into three groups following random number table, the LR3 group (3 males and 7 females), the KI3 group (3 males and 7 females), and the LR3+ KI3 group (4 males and 6 females) for needling, respectively. When the 30-min treatment finished, they received a further Rs-fMRI scanning. The Rs-fMRI data before and after the acupuncture treatment were analyzed through ReHo.
Results: Compared with preacupuncture, respectively, ReHo values increased in Brodmann areas (BAs) 3, 18, and 40 and decreased in BAs 7 and 31 in LR3+ KI3 group. However, ReHo values only decreased in BA7 of KI3 group while the results showed no significant difference of brain regions in LR3 group between pre- and postacupuncture. Compared with LR3 group, LR3+KI3 group exhibited decreased ReHo values in BAs 7, 9, and 31. Meanwhile, compared with KI3 group, LR3+KI3 group exhibited increased ReHo values in the BAs 2, 18, 30, and 40 and decreased ReHo values in BA13.
Conclusion: Combined acupoints of LR3 and KI3 could act on wider brain areas than the sum of single acupoints, whose functions include emotional processing, cognition, somatic sensation, spatial orientation, language production, and vision.

PMID: 30719061 [PubMed]

Acupuncture Enhances Communication between Cortices with Damaged White Matters in Poststroke Motor Impairment.

Thu, 02/07/2019 - 00:02
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Acupuncture Enhances Communication between Cortices with Damaged White Matters in Poststroke Motor Impairment.

Evid Based Complement Alternat Med. 2019;2019:4245753

Authors: Han X, Bai L, Sun C, Niu X, Ning Y, Chen Z, Li Y, Li K, Lyu D, Fu C, Cui F, Chen Z, Tan Z, Tang L, Zou Y

Abstract
Stroke is a leading cause of motor disability. Acupuncture is an effective therapeutic strategy for poststroke motor impairment. However, its mechanism is still elusive. Twenty-two stroke patients having a right-hemispheric subcortical infarct and 22 matched healthy controls were recruited to undergo diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) scanning. The resting-state fMRI was implemented before and after needling at GB34 (Yanglingquan). The stroke patients presented a substantially reduced fractional anisotropy value in the right superior longitudinal fasciculus (SLF), corticospinal tract, and corpus callosum. The structural integrity of the frontoparietal part of the SLF (SLF-FP) correlated with the motor scores of lower limbs in stroke patients. This corticocortical association bundle originated from the premotor cortex (PM) and the adjacent supplementary motor area (SMA), known as secondary motor areas, and terminated in the supramarginal gyrus (SMG). After acupuncture intervention, the corresponding functional connectivity between the PM/SMA and SMG was enhanced in stroke patients compared with healthy controls. These findings suggested that the integrity of the SLF is a potential neuroimaging biomarker for motor disability of lower limbs following a stroke. Acupuncture could increase the communication between the cortices connected by the impaired white matter tracts, implying the neural mechanism underlying the acupuncture intervention.

PMID: 30719060 [PubMed]

Tracking perceptual decision mechanisms through changes in interhemispheric functional connectivity in human visual cortex.

Thu, 02/07/2019 - 00:02
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Tracking perceptual decision mechanisms through changes in interhemispheric functional connectivity in human visual cortex.

Sci Rep. 2019 Feb 04;9(1):1242

Authors: Sousa T, Duarte JV, Costa GN, Kemper VG, Martins R, Goebel R, Castelo-Branco M

Abstract
The role of long-range integration mechanisms underlying visual perceptual binding and their link to interhemispheric functional connectivity, as measured by fMRI, remains elusive. Only inferences on anatomical organization from resting state data paradigms not requiring coherent binding have been achieved. Here, we used a paradigm that allowed us to study such relation between perceptual interpretation and functional connectivity under bistable interhemispheric binding vs. non-binding of visual surfaces. Binding occurs by long-range perceptual integration of motion into a single object across hemifields and non-binding reflects opponent segregation of distinct moving surfaces into each hemifield. We hypothesized that perceptual integration vs. segregation of surface motion, which is achieved in visual area hMT+, is modulated by changes in interhemispheric connectivity in this region. Using 7T fMRI, we found that perceptual long-range integration of bistable motion can be tracked by changes in interhemispheric functional connectivity between left/right hMT+. Increased connectivity was tightly related with long-range perceptual integration. Our results indicate that hMT+ interhemispheric functional connectivity reflects perceptual decision, suggesting its pivotal role on long-range disambiguation of bistable physically constant surface motion. We reveal for the first time, at the scale of fMRI, a relation between interhemispheric functional connectivity and decision based perceptual binding.

PMID: 30718636 [PubMed - in process]

Segmented Echo Planar Imaging Improves Detection of Subcortical Functional Connectivity Networks in the Rat Brain.

Thu, 02/07/2019 - 00:02
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Segmented Echo Planar Imaging Improves Detection of Subcortical Functional Connectivity Networks in the Rat Brain.

Sci Rep. 2019 Feb 04;9(1):1397

Authors: Tambalo S, Scuppa G, Bifone A

Abstract
Susceptibility artifacts in the vicinity of aural and nasal cavities result in significant signal drop-out and image distortion in echo planar imaging of the rat brain. These effects may limit the study of resting state functional connectivity in deep brain regions. Here, we explore the use of segmented EPI for resting state fMRI studies in the rat, and assess the relative merits of this method compared to single shot EPI. Sequences were evaluated in terms of signal-to-noise ratio, geometric distortions, data driven detection of resting state networks and group level correlations of time series. Multishot imaging provided improved SNR, temporal SNR and reduced geometric distortion in deep areas, while maintaining acceptable overall image quality in cortical regions. Resting state networks identified by independent component analysis were consistent across methods, but multishot EPI provided a more robust and accurate delineation of connectivity patterns involving deep regions typically affected by susceptibility artifacts. Importantly, segmented EPI showed reduced between-subject variability and stronger statistical significance of pairwise correlations at group level over the whole brain and in particular in subcortical regions. Multishot EPI may represent a valid alternative to snapshot methods in functional connectivity studies, particularly for the investigation of subcortical regions and deep gray matter nuclei.

PMID: 30718628 [PubMed - in process]

Brain songs framework used for discovering the relevant timescale of the human brain.

Thu, 02/07/2019 - 00:02
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Brain songs framework used for discovering the relevant timescale of the human brain.

Nat Commun. 2019 Feb 04;10(1):583

Authors: Deco G, Cruzat J, Kringelbach ML

Abstract
A key unresolved problem in neuroscience is to determine the relevant timescale for understanding spatiotemporal dynamics across the whole brain. While resting state fMRI reveals networks at an ultraslow timescale (below 0.1 Hz), other neuroimaging modalities such as MEG and EEG suggest that much faster timescales may be equally or more relevant for discovering spatiotemporal structure. Here, we introduce a novel way to generate whole-brain neural dynamical activity at the millisecond scale from fMRI signals. This method allows us to study the different timescales through binning the output of the model. These timescales can then be investigated using a method (poetically named brain songs) to extract the spacetime motifs at a given timescale. Using independent measures of entropy and hierarchy to characterize the richness of the dynamical repertoire, we show that both methods find a similar optimum at a timescale of around 200 ms in resting state and in task data.

PMID: 30718478 [PubMed - in process]

Atypical intrinsic neural timescale in autism.

Thu, 02/07/2019 - 00:02
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Atypical intrinsic neural timescale in autism.

Elife. 2019 Feb 05;8:

Authors: Watanabe T, Rees G, Masuda N

Abstract
How long neural information is stored in a local brain area reflects functions of that region and is often estimated by the magnitude of the autocorrelation of intrinsic neural signals in the area. Here, we investigated such intrinsic neural timescales in high-functioning adults with autism and examined whether local brain dynamics reflected their atypical behaviours. By analysing resting-state fMRI data, we identified shorter neural timescales in the sensory/visual cortices and a longer timescale in the right caudate in autism. The shorter intrinsic timescales in the sensory/visual areas were correlated with the severity of autism, whereas the longer timescale in the caudate was associated with cognitive rigidity. These observations were confirmed from neurodevelopmental perspectives and replicated in two independent cross-sectional datasets. Moreover, the intrinsic timescale was correlated with local grey matter volume. This study shows that functional and structural atypicality in local brain areas is linked to higher-order cognitive symptoms in autism.

PMID: 30717827 [PubMed - in process]

GLOBAL PDF-BASED TEMPORAL NON-LOCAL MEANS FILTERING REVEALS INDIVIDUAL DIFFERENCES IN BRAIN CONNECTIVITY.

Wed, 02/06/2019 - 09:02
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GLOBAL PDF-BASED TEMPORAL NON-LOCAL MEANS FILTERING REVEALS INDIVIDUAL DIFFERENCES IN BRAIN CONNECTIVITY.

Proc IEEE Int Symp Biomed Imaging. 2018 Apr;2018:15-19

Authors: Li J, Choi S, Joshi AA, Wisnowski JL, Leahy RM

Abstract
Characterizing functional brain connectivity using resting fMRI is challenging due to the relatively small BOLD signal contrast and low SNR. Gaussian filtering tends to undermine the individual differences detected by analysis of BOLD signal by smoothing signals across boundaries of different functional areas. Temporal non-local means (tNLM) filtering denoises fMRI data while preserving spatial structures but the kernel and parameters for tNLM filter need to be chosen carefully in order to achieve optimal results. Global PDF-based tNLM filtering (GPDF) is a new, data-dependent optimized kernel function for tNLM filtering which enables us to perform global filtering with improved noise reduction effects without blurring adjacent functional regions.

PMID: 30713593 [PubMed]

Neural markers of depression risk predict the onset of depression.

Tue, 02/05/2019 - 21:01

Neural markers of depression risk predict the onset of depression.

Psychiatry Res Neuroimaging. 2019 Jan 25;285:31-39

Authors: Shapero BG, Chai XJ, Vangel M, Biederman J, Hoover CS, Whitfield-Gabrieli S, Gabrieli JDE, Hirshfeld-Becker DR

Abstract
Although research highlights neural correlates of Major Depressive Disorder (MDD), it is unclear whether these correlates reflect the state of depression or a pre-existing risk factor. The current study examined whether baseline differences in brain activations, resting-state connectivity, and brain structural differences between non-symptomatic children at high- and low-risk for MDD based on familial depression prospectively predict the onset of a depressive episode or increases in depressive symptomatology. We re-assessed 44 participants (28 high-risk; 16 low-risk) who had undergone neuroimaging in a previous study 3-4 years earlier (Mean age at follow-up = 14.3 years, SD = 1.9 years; 45% females; 70% Caucasian). We investigated whether baseline brain imaging data (including an emotional face match task fMRI, resting-state fMRI and structural MRI) that differentiated the risk groups also predicted the onset of depression. Resting-state functional connectivity abnormalities in the default mode and cognitive control network that differentiated high-risk from low-risk youth at baseline predicted the onset of MDD during adolescence, after taking risk status into account. Increased functional activation to both happy and fearful faces was associated with greater decreases in self-reported depression symptoms at follow-up. This preliminary evidence could be used to identify youth at-risk for depression and inform early intervention strategies.

PMID: 30716688 [PubMed - as supplied by publisher]

The inner fluctuations of the brain in presymptomatic Frontotemporal Dementia: The chronnectome fingerprint.

Tue, 02/05/2019 - 21:01

The inner fluctuations of the brain in presymptomatic Frontotemporal Dementia: The chronnectome fingerprint.

Neuroimage. 2019 Feb 01;:

Authors: Premi E, Calhoun VD, Diano M, Gazzina S, Cosseddu M, Alberici A, Archetti S, Paternicò D, Gasparotti R, van Swieten J, Galimberti D, Sanchez-Valle R, Laforce R, Moreno F, Synofzik M, Graff C, Masellis M, Tartaglia MC, Rowe J, Vandenberghe R, Finger E, Tagliavini F, de Mendonça A, Santana I, Butler C, Ducharme S, Gerhard A, Danek A, Levin J, Otto M, Frisoni G, Cappa S, Sorbi S, Padovani A, Rohrer JD, Borroni B, Genetic FTD Initiative, GENFI

Abstract
Frontotemporal Dementia (FTD) is preceded by a long period of subtle brain changes, occurring in the absence of overt cognitive symptoms, that need to be still fully characterized. Dynamic network analysis based on resting-state magnetic resonance imaging (rs-fMRI) is a potentially powerful tool for the study of preclinical FTD. In the present study, we employed a "chronnectome" approach (recurring, time-varying patterns of connectivity) to evaluate measures of dynamic connectivity in 472 at-risk FTD subjects from the Genetic Frontotemporal dementia research Initiative (GENFI) cohort. We considered 249 subjects with FTD-related pathogenetic mutations and 223 mutation non-carriers (HC). Dynamic connectivity was evaluated using independent component analysis and sliding-time window correlation to rs-fMRI data, and meta-state measures of global brain flexibility were extracted. Results show that presymptomatic FTD exhibits diminished dynamic fluidity, visiting less meta-states, shifting less often across them, and travelling through a narrowed meta-state distance, as compared to HC. Dynamic connectivity changes characterize preclinical FTD, arguing for the desynchronization of the inner fluctuations of the brain. These changes antedate clinical symptoms, and might represent an early signature of FTD to be used as a biomarker in clinical trials.

PMID: 30716457 [PubMed - as supplied by publisher]

Reproducibility of functional brain alterations in major depressive disorder: Evidence from a multisite resting-state functional MRI study with 1,434 individuals.

Tue, 02/05/2019 - 21:01

Reproducibility of functional brain alterations in major depressive disorder: Evidence from a multisite resting-state functional MRI study with 1,434 individuals.

Neuroimage. 2019 Feb 01;:

Authors: Xia M, Si T, Sun X, Ma Q, Liu B, Wang L, Meng J, Chang M, Huang X, Chen Z, Tang Y, Xu K, Gong Q, Wang F, Qiu J, Xie P, Li L, He Y, DIDA-Major Depressive Disorder Working Group

Abstract
Resting-state functional MRI (R-fMRI) studies have demonstrated widespread alterations in brain function in patients with major depressive disorder (MDD). However, a clear and consistent conclusion regarding a repeatable pattern of MDD-relevant alterations is still limited due to the scarcity of large-sample, multisite datasets. Here, we address this issue by including a large R-fMRI dataset with 1434 participants (709 patients with MDD and 725 healthy controls) from five centers in China. Individual functional activity maps that represent very local to long-range connections are computed using the amplitude of low-frequency fluctuations, regional homogeneity and distance-related functional connectivity strength. The reproducibility analyses involve different statistical strategies, global signal regression, across-center consistency, clinical variables, and sample size. We observed significant hypoactivity in the orbitofrontal, sensorimotor, and visual cortices and hyperactivity in the frontoparietal cortices in MDD patients compared to the controls. These alterations are not affected by different statistical analysis strategies, global signal regression and medication status and are generally reproducible across centers. However, these between-group differences are partially influenced by the episode status and the age of disease onset in patients, and the brain-clinical variable relationship exhibits poor cross-center reproducibility. Bootstrap analyses reveal that at least 400 subjects in each group are required to replicate significant alterations (an extent threshold of P < .05 and a height threshold of P < .001) at 50% reproducibility. Together, these results highlight reproducible patterns of functional alterations in MDD and relevant influencing factors, which provides crucial guidance for future neuroimaging studies of this disorder.

PMID: 30716456 [PubMed - as supplied by publisher]

Distinctive Interaction Between Cognitive Networks and the Visual Cortex in Early Blind Individuals.

Tue, 02/05/2019 - 21:01

Distinctive Interaction Between Cognitive Networks and the Visual Cortex in Early Blind Individuals.

Cereb Cortex. 2019 Jan 31;:

Authors: Abboud S, Cohen L

Abstract
In early blind individuals, brain activation by a variety of nonperceptual cognitive tasks extends to the visual cortex, while in the sighted it is restricted to supramodal association areas. We hypothesized that such activation results from the integration of different sectors of the visual cortex into typical task-dependent networks. We tested this hypothesis with fMRI in blind and sighted subjects using tasks assessing speech comprehension, incidental long-term memory and both verbal and nonverbal executive control, in addition to collecting resting-state data. All tasks activated the visual cortex in blind relative to sighted subjects, which enabled its segmentation according to task sensitivity. We then assessed the unique brain-scale functional connectivity of the segmented areas during resting state. Language-related seeds were preferentially connected to frontal and temporal language areas; the seed derived from the executive task was connected to the right dorsal frontoparietal executive network; and the memory-related seed was uniquely connected to mesial frontoparietal areas involved in episodic memory retrieval. Thus, using a broad set of language, executive, and memory tasks in the same subjects, combined with resting state connectivity, we demonstrate the selective integration of different patches of the visual cortex into brain-scale networks with distinct localization, lateralization, and functional roles.

PMID: 30715236 [PubMed - as supplied by publisher]

rfDemons: Resting fMRI-based Cortical Surface Registration using the BrainSync Transform.

Tue, 02/05/2019 - 21:01
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rfDemons: Resting fMRI-based Cortical Surface Registration using the BrainSync Transform.

Med Image Comput Comput Assist Interv. 2018 Sep;11072:198-205

Authors: Joshi AA, Li J, Chong M, Akrami H, Leahy RM

Abstract
Cross subject functional studies of cerebral cortex require cortical registration that aligns functional brain regions. While cortical folding patterns are approximate indicators of the underlying cytoarchitecture, coregistration based on these features alone does not accurately align functional regions in cerebral cortex. This paper presents a method for cortical surface registration (rfDemons) based on resting fMRI (rfMRI) data that uses curvature-based anatomical registration as an initialization. In contrast to existing techniques that use connectivity-based features derived from rfMRI, the proposed method uses 'synchronized' resting rfMRI time series directly. The synchronization of rfMRI data is performed using the BrainSync transform which applies an orthogonal transform to the rfMRI time series to temporally align them across subjects. The rfDemons method was applied to rfMRI from the Human Connectome Project and evaluated using task fMRI data to explore the impact of cortical registration performed using resting fMRI data on functional alignment of the cerebral cortex.

PMID: 30714047 [PubMed - in process]

Editorial for the special issue "Resting-state fMRI and cognition" in Brain and Cognition.

Tue, 02/05/2019 - 21:01
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Editorial for the special issue "Resting-state fMRI and cognition" in Brain and Cognition.

Brain Cogn. 2019 Jan 31;:

Authors: Lotze M, Langner R

PMID: 30712965 [PubMed - as supplied by publisher]

Interactive effect of 5-HTTLPR and BDNF polymorphisms on amygdala intrinsic functional connectivity and anxiety.

Tue, 02/05/2019 - 03:00

Interactive effect of 5-HTTLPR and BDNF polymorphisms on amygdala intrinsic functional connectivity and anxiety.

Psychiatry Res Neuroimaging. 2019 Jan 29;285:1-8

Authors: Loewenstern J, You X, Merchant J, Gordon EM, Stollstorff M, Devaney J, Vaidya CJ

Abstract
The serotonin transporter (5-HTTLPR) and brain-derived neurotrophic factor (BDNF) gene polymorphisms have been associated with risk for affective disorders and functional variability of the amygdala. We examined whether the two genotypes interactively influence intrinsic functional connectivity (FC) of the amygdala and whether FC mediates the genetic association with anxiety. Eighty genotyped healthy adults underwent resting state fMRI and completed the self-reported State-Trait Anxiety Inventory. Interactive genetic association with anxiety was observed such that effects of 5-HTTLPR depended on the BDNF Val66Met polymorphism (rs6265 variant), with higher anxiety scores in short and Met carriers compared to the other allelic groups. Voxel-wise FC with left and right amygdala seeds identified regions that were sensitive to variability in anxiety scores. A significant moderated mediation model demonstrated that the effect of 5-HTTLPR genotype on anxiety, moderated by BDNF Val66Met genotype, was fully mediated by FC between the left amygdala and the right dorsolateral prefrontal cortex, a cognitive control-related region, during a task-free state. FC was highest in carriers of the 5-HTTLPR short allele and BDNF Met allele. These findings establish intrinsic amygdala-prefrontal functional connectivity as a potential intermediate phenotype for anxiety, an important step toward identification of causal pathways for vulnerability to affective disorders.

PMID: 30711709 [PubMed - as supplied by publisher]

Altered Connectivity Between Cerebellum, Visual, and Sensory-Motor Networks in Autism Spectrum Disorder: Results from the EU-AIMS Longitudinal European Autism Project.

Tue, 02/05/2019 - 03:00

Altered Connectivity Between Cerebellum, Visual, and Sensory-Motor Networks in Autism Spectrum Disorder: Results from the EU-AIMS Longitudinal European Autism Project.

Biol Psychiatry Cogn Neurosci Neuroimaging. 2018 Dec 05;:

Authors: Oldehinkel M, Mennes M, Marquand A, Charman T, Tillmann J, Ecker C, Dell'Acqua F, Brandeis D, Banaschewski T, Baumeister S, Moessnang C, Baron-Cohen S, Holt R, Bölte S, Durston S, Kundu P, Lombardo MV, Spooren W, Loth E, Murphy DGM, Beckmann CF, Buitelaar JK, EU-AIMS LEAP group

Abstract
BACKGROUND: Resting-state functional magnetic resonance imaging-based studies on functional connectivity in autism spectrum disorder (ASD) have generated inconsistent results. Interpretation of findings is further hampered by small samples and a focus on a limited number of networks, with networks underlying sensory processing being largely underexamined. We aimed to comprehensively characterize ASD-related alterations within and between 20 well-characterized resting-state networks using baseline data from the EU-AIMS (European Autism Interventions-A Multicentre Study for Developing New Medications) Longitudinal European Autism Project.
METHODS: Resting-state functional magnetic resonance imaging data was available for 265 individuals with ASD (7.5-30.3 years; 73.2% male) and 218 typically developing individuals (6.9-29.8 years; 64.2% male), all with IQ > 70. We compared functional connectivity within 20 networks-obtained using independent component analysis-between the ASD and typically developing groups, and related functional connectivity within these networks to continuous (overall) autism trait severity scores derived from the Social Responsiveness Scale Second Edition across all participants. Furthermore, we investigated case-control differences and autism trait-related alterations in between-network connectivity.
RESULTS: Higher autism traits were associated with increased connectivity within salience, medial motor, and orbitofrontal networks. However, we did not replicate previously reported case-control differences within these networks. The between-network analysis did reveal case-control differences showing on average 1) decreased connectivity of the visual association network with somatosensory, medial, and lateral motor networks, and 2) increased connectivity of the cerebellum with these sensory and motor networks in ASD compared with typically developing subjects.
CONCLUSIONS: We demonstrate ASD-related alterations in within- and between-network connectivity. The between-network alterations broadly affect connectivity between cerebellum, visual, and sensory-motor networks, potentially underlying impairments in multisensory and visual-motor integration frequently observed in ASD.

PMID: 30711508 [PubMed - as supplied by publisher]

Individual-specific fMRI-Subspaces improve functional connectivity prediction of behavior.

Tue, 02/05/2019 - 03:00

Individual-specific fMRI-Subspaces improve functional connectivity prediction of behavior.

Neuroimage. 2019 Jan 31;:

Authors: Kashyap R, Kong R, Bhattacharjee S, Li J, Zhou J, Yeo T

Abstract
There is significant interest in using resting-state functional connectivity (RSFC) to predict human behavior. Good behavioral prediction should in theory require RSFC to be sufficiently distinct across participants; if RSFC were the same across participants, then behavioral prediction would obviously be poor. Therefore, we hypothesize that removing common resting-state functional magnetic resonance imaging (rs-fMRI) signals that are shared across participants would improve behavioral prediction. Here, we considered 803 participants from the human connectome project (HCP) with four rs-fMRI runs. We applied the common and orthogonal basis extraction (COBE) technique to decompose each HCP run into two subspaces: a common (group-level) subspace shared across all participants and a subject-specific subspace. We found that the first common COBE component of the first HCP run was localized to the visual cortex and was unique to the run. On the other hand, the second common COBE component of the first HCP run and the first common COBE component of the remaining HCP runs were highly similar and localized to regions within the default network, including the posterior cingulate cortex and precuneus. Overall, this suggests the presence of run-specific (state-specific) effects that were shared across participants. By removing the first and second common COBE components from the first HCP run, and the first common COBE component from the remaining HCP runs, the resulting RSFC improves behavioral prediction by an average of 11.7% across 58 behavioral measures spanning cognition, emotion and personality.

PMID: 30711467 [PubMed - as supplied by publisher]

Computerized cognitive training for Chinese mild cognitive impairment patients: A neuropsychological and fMRI study.

Sun, 02/03/2019 - 08:59

Computerized cognitive training for Chinese mild cognitive impairment patients: A neuropsychological and fMRI study.

Neuroimage Clin. 2019 Jan 26;22:101691

Authors: Li BY, He NY, Qiao Y, Xu HM, Lu YZ, Cui PJ, Ling HW, Yan FH, Tang HD, Chen SD

Abstract
BACKGROUND: Computerized multi-model training has been widely studied for its effect on delaying cognitive decline. In this study, we designed the first Chinese-version computer-based multi-model cognitive training for mild cognitive impairment (MCI) patients. Neuropsychological effects and neural activity changes assessed by functional MRI were both evaluated.
METHOD: MCI patients in the training group were asked to take training 3-4 times per week for 6 months. Neuropsychological and resting-state fMRI assessment were performed at baseline and at 6 months. Patients in both groups were continuously followed up for another 12 months and assessed by neuropsychological tests again.
RESULTS: 78 patients in the training group and 63 patients in the control group accomplished 6-month follow-up. Training group improved 0.23 standard deviation (SD) of mini-mental state examination, while control group had 0.5 SD decline. Addenbrooke's cognitive examination-revised scores in attention (p = 0.002) and memory (p = 0.006), as well as stroop color-word test interference index (p = 0.038) and complex figure test-copy score (p = 0.035) were also in favor of the training effect. Difference between the changes of two groups after training was not statistically significant. The fMRI showed increased regional activity at bilateral temporal poles, insular cortices and hippocampus. However, difference between the changes of two groups after another 12 months was not statistically significant.
CONCLUSIONS: Multi-model cognitive training help MCI patients to gained cognition benefit, especially in memory, attention and executive function. Functional neuroimaging provided consistent neural activation evidence. Nevertheless, after one-year follow up after last training, training effects were not significant. The study provided new evidence of beneficial effect of multi-model cognitive training.

PMID: 30708349 [PubMed - as supplied by publisher]

Investigating functional brain network integrity using a traditional and novel categorical scheme for neurodevelopmental disorders.

Sun, 02/03/2019 - 08:59

Investigating functional brain network integrity using a traditional and novel categorical scheme for neurodevelopmental disorders.

Neuroimage Clin. 2019 Jan 17;21:101678

Authors: Dajani DR, Burrows CA, Odriozola P, Baez A, Nebel MB, Mostofsky SH, Uddin LQ

Abstract
BACKGROUND: Current diagnostic systems for neurodevelopmental disorders do not have clear links to underlying neurobiology, limiting their utility in identifying targeted treatments for individuals. Here, we aimed to investigate differences in functional brain network integrity between traditional diagnostic categories (autism spectrum disorder [ASD], attention-deficit/hyperactivity disorder [ADHD], typically developing [TD]) and carefully consider the impact of comorbid ASD and ADHD on functional brain network integrity in a sample adequately powered to detect large effects. We also assess the neurobiological separability of a novel, potential alternative categorical scheme based on behavioral measures of executive function.
METHOD: Five-minute resting-state fMRI data were obtained from 168 children (128 boys, 40 girls) with ASD, ADHD, comorbid ASD and ADHD, and TD children. Independent component analysis and dual regression were used to compute within- and between-network functional connectivity metrics at the individual level.
RESULTS: No significant group differences in within- or between-network functional connectivity were observed between traditional diagnostic categories (ASD, ADHD, TD) even when stratified by comorbidity (ASD + ADHD, ASD, ADHD, TD). Similarly, subgroups classified by executive functioning levels showed no group differences.
CONCLUSIONS: Using clinical diagnosis and behavioral measures of executive function, no differences in functional connectivity were observed among the categories examined. Despite our limited ability to detect small- to medium-sized differences between groups, this work contributes to a growing literature suggesting that traditional diagnostic categories do not define neurobiologically separable groups. Future work is necessary to ascertain the validity of the executive function-based nosology, but current results suggest that nosologies reliant on behavioral data alone may not lead to discovery of neurobiologically distinct categories.

PMID: 30708240 [PubMed - as supplied by publisher]