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Insula-Retrosplenial Cortex Overconnectivity Increases Internalizing via Reduced Insight in Autism.

Tue, 10/08/2019 - 10:20
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Insula-Retrosplenial Cortex Overconnectivity Increases Internalizing via Reduced Insight in Autism.

Biol Psychiatry. 2018 08 15;84(4):287-294

Authors: Hogeveen J, Krug MK, Elliott MV, Solomon M

Abstract
BACKGROUND: Internalizing symptoms like anxiety and depression are common and impairing in autism spectrum disorder (ASD). Here, we test the hypothesis that aberrant functional connectivity among three brain networks (salience network [SN], default mode network [DMN], and frontoparietal network [FPN]) plays a role in the pathophysiology of internalizing in ASD.
METHODS: We examined the association between resting-state functional connectivity and internalizing in 102 adolescents and young adults with ASD (n = 49) or typical development (n = 53). Seed-to-target functional connectivity was contrasted between adolescents and young adults with ASD and typically developing subjects using a recent parcellation of the human cerebral cortex, and connections that were aberrant in ASD were analyzed dimensionally as a function of parent-reported internalizing symptoms.
RESULTS: Three connections demonstrated robust overconnectivity in ASD: 1) the anterior insula to the retrosplenial cortex (i.e., SN-DMN), 2) the anterior insula to the frontal pole (i.e., SN-FPN), and 3) the dorsolateral prefrontal cortex to the retrosplenial cortex (i.e., FPN-DMN). These differences remained significant after controlling for age, and no age-related effects survived correction. The SN-DMN connection was associated with greater internalizing in ASD, mediated by a bigger difference between self- and parent-reported internalizing. Control analyses found that the other two connections were not associated with internalizing, and SN-DMN connectivity was not associated with a well-matched control measure (externalizing symptoms).
CONCLUSIONS: The present findings provide novel evidence for a specific link between SN-DMN overconnectivity and internalizing in ASD. Further, the mediation results suggest that intact anterior insula-retrosplenial connectivity may play a role in an individual's generating insight into his or her own psychopathology.

PMID: 29523413 [PubMed - indexed for MEDLINE]

Temporal stability of functional brain modules associated with human intelligence.

Mon, 10/07/2019 - 15:40
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Temporal stability of functional brain modules associated with human intelligence.

Hum Brain Mapp. 2019 Oct 06;:

Authors: Hilger K, Fukushima M, Sporns O, Fiebach CJ

Abstract
Individual differences in general cognitive ability (i.e., intelligence) have been linked to individual variations in the modular organization of functional brain networks. However, these analyses have been limited to static (time-averaged) connectivity, and have not yet addressed whether dynamic changes in the configuration of brain networks relate to general intelligence. Here, we used multiband functional MRI resting-state data (N = 281) and estimated subject-specific time-varying functional connectivity networks. Modularity optimization was applied to determine individual time-variant module partitions and to assess fluctuations in modularity across time. We show that higher intelligence, indexed by an established composite measure, the Wechsler Abbreviated Scale of Intelligence (WASI), is associated with higher temporal stability (lower temporal variability) of brain network modularity. Post-hoc analyses reveal that subjects with higher intelligence scores engage in fewer periods of extremely high modularity - which are characterized by greater disconnection of task-positive from task-negative networks. Further, we show that brain regions of the dorsal attention network contribute most to the observed effect. In sum, our study suggests that investigating the temporal dynamics of functional brain network topology contributes to our understanding of the neural bases of general cognitive abilities.

PMID: 31587450 [PubMed - as supplied by publisher]

A common variant in OXTR rs53576 impacts topological patterns of brain functional networks.

Mon, 10/07/2019 - 15:40
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A common variant in OXTR rs53576 impacts topological patterns of brain functional networks.

Eur Child Adolesc Psychiatry. 2019 Oct 05;:

Authors: Wang J, Zhang Y, Zhu D, Yang Z, Liu F, Qin W, Zhu J, Liu B, Jiang T, Yu C

Abstract
A common variant (rs53576, G/A) in the oxytocin receptor (OXTR) gene is associated with individual differences in social behavior and may increase the risk for neuropsychiatric disorders characterized by social impairment, especially autism. Although recent functional magnetic resonance imaging (fMRI) studies have identified functional connectivity alteration in some brain regions in risk A allele carriers, it is currently unknown whether this dysfunctional connectivity causes disruption of the topological properties of brain functional networks. We applied a graph-theoretical analysis to investigate the topological properties of brain networks derived from resting-state fMRI in relation to AA homozygotes versus G allele carriers in 290 cognitive normal young adults. We found both AA homozygotes and G allele carriers demonstrated small-world properties; however, male AA homozygotes showed lower normalized clustering coefficient, small-worldness, and local efficiency compared with male G allele carriers, no differences survived after Bonferroni correction; and the inter-group differences of all three metrics exhibited an allele-load-dependent trend (AA < AG < GG), indicating a randomization shift of their brain functional networks. No significant results were observed in any global measures in female AA homozygotes as compared to female G allele carriers. Our results suggested that the topological patterns of brain functional networks were altered in OXTR rs53576 male homozygotes for the risk A allele compared with male G allele carriers, providing evidence for the disruption of integrity in large-scale intrinsic brain networks in a sex-dimorphic manner.

PMID: 31587084 [PubMed - as supplied by publisher]

Comparison of resting-state functional connectivity in marmosets with tracer-based cellular connectivity.

Mon, 10/07/2019 - 15:40
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Comparison of resting-state functional connectivity in marmosets with tracer-based cellular connectivity.

Neuroimage. 2019 Oct 03;:116241

Authors: Hori Y, Schaeffer DJ, Gilbert KM, Hayrynen LK, Cléry JC, Gati JS, Menon RS, Everling S

Abstract
Resting-state functional MRI (RS-fMRI) is widely used to assess how strongly different brain areas are connected. However, this connection obtained by RS-fMRI, which is called functional connectivity (FC), simply refers to the correlation of blood oxygen level-dependent (BOLD) signals across time it has yet to be quantified how accurately FC reflects cellular connectivity (CC). In this study, we elucidated this relationship using RS-fMRI and quantitative tracer data in marmosets. In addition, we also elucidated the effects of distance between two brain regions on the relationship between FC and CC across seed region. To calculate FC, we used full correlation approach that is considered to reflect not only direct (monosynaptic connections) but also indirect pathways (polysynaptic connections). Our main findings are that: (1) overall FC obtained by RS-fMRI was highly correlated with tracer-based CC, but correlation coefficients varied remarkably across seed regions; (2) the strength of FC decreased with increase in the distance between two regions; (3) correlation coefficients between FC and CC after regressing out the effects of the distance between two regions still varied across seed regions, but some regions have strong correlations. These findings suggest that although FC reflects the strength of monosynaptic pathways, it is strongly affected by the distance between regions.

PMID: 31586676 [PubMed - as supplied by publisher]

Connectomics-Based Functional Network Alterations in both Depressed Patients with Suicidal Behavior and Healthy Relatives of Suicide Victims.

Sun, 10/06/2019 - 14:40
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Connectomics-Based Functional Network Alterations in both Depressed Patients with Suicidal Behavior and Healthy Relatives of Suicide Victims.

Sci Rep. 2019 Oct 04;9(1):14330

Authors: Wagner G, de la Cruz F, Köhler S, Pereira F, Richard-Devantoy S, Turecki G, Bär KJ, Jollant F

Abstract
Understanding the neural mechanisms of suicidal behavior is crucial. While regional brain alterations have previously been reported, knowledge about brain functional connectomics is currently limited. Here, we investigated differences in global topologic network properties and local network-based functional organization in both suicide attempters and suicide relatives. Two independent samples of depressed suicide attempters (N = 42), depressed patient controls (N = 43), healthy controls (N = 66) as well as one sample of healthy relatives of suicide victims (N = 16) and relatives of depressed patients (N = 16) were investigated with functional magnetic resonance imaging in the resting-state condition. Graph theory analyses were performed. Assortativity, clustering coefficients, global efficiency, and rich-club coefficients were calculated. A network-based statistic approach was finally used to examine functional connectivity matrices. In comparison to healthy controls, both patient groups showed significant reduction in assortativity, and decreased functional connectivity in largely central and posterior brain networks. Suicide attempters only differed from patient controls in terms of higher rich-club coefficients for the highest degree nodes. Compared to patient relatives and healthy controls, suicide relatives showed reduced assortativity, reduced clustering coefficients, increased global efficiency, and increased rich-club coefficients for the highest degree nodes. Suicide relatives also showed reduced functional connectivity in one anterior and one posterior sub-network in comparison to healthy controls, and in a largely anterior brain network in comparison to patient relatives. In conclusion, these results suggest that the vulnerability to suicidal behavior may be associated with heritable deficits in global brain functioning - characterized by weak resilience and poor segregation - and in functional organization with reduced connectivities affecting the ventral and dorsal prefrontal cortex, the anterior cingulate, thalamus, striatum, and possibly the insula, fusiform gyrus and the cerebellum.

PMID: 31586117 [PubMed - in process]

Multi-scale dynamics of spontaneous brain activity is associated with walking speed in older adults.

Sat, 10/05/2019 - 13:40
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Multi-scale dynamics of spontaneous brain activity is associated with walking speed in older adults.

J Gerontol A Biol Sci Med Sci. 2019 Oct 05;:

Authors: Zhou J, Poole V, Wooten T, Lo OY, Iloputaife I, Manor B, Esterman M, Lipsitz LA

Abstract
BACKGROUND: In older adults, compromised white matter tract integrity within the brain has been linked to impairments in mobility. We contend that poorer integrity disrupts mobility by altering the processing of sensorimotor, cognitive and attentional resources in neural networks. The richness of information processing in a given network can be quantified by calculating the complexity of resting-state fMRI time-series. We hypothesized that: 1) older adults with lower brain complexity, specifically within sensorimotor, executive and attention networks, would exhibit slower walking speed and greater dual-task costs (i.e., DTC); and 2) such complexity would mediate the effect of white matter integrity on these metrics of mobility.
METHOD: Fifty-three older adults completed a walking assessment and a neuroimaging protocol. Brain complexity was quantified by calculating the multiscale entropy of the resting-state fMRI signal within seven previously defined functional networks. The white matter integrity across structures of the corpus callosum was quantified using fractional anisotropy (FA).
RESULTS: Participants with lower resting-state complexity within the sensorimotor, executive and attention networks walked more slowly under single- and dual-task (i.e., walking while performing a serial-subtraction task) conditions (β>0.28, p≤0.01) and had a greater DTC (β<-0.28, p<0.04). Complexity in these networks mediated the influence of the corpus callosum genu on both single- (indirect effects>0.15, 95% CIs=0.02~0.32) and dual-task walking speeds (indirect effects>0.13, 95% CIs=0.02~0.33).
CONCLUSION: These results suggest that the multi-scale dynamics of resting-state brain activity correlate with mobility and mediate the effect of the microstructural integrity in the corpus callosum genu on walking speed in older adults.

PMID: 31585008 [PubMed - as supplied by publisher]

Resting-state fMRI in disorders of consciousness to facilitate early therapeutic intervention.

Sat, 10/05/2019 - 13:40
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Resting-state fMRI in disorders of consciousness to facilitate early therapeutic intervention.

Neurol Clin Pract. 2019 Aug;9(4):e33-e35

Authors: Boerwinkle VL, Torrisi SJ, Foldes ST, Marku I, Ranjan M, Wilfong AA, Adelson PD

PMID: 31583195 [PubMed]

Abnormalities of intrinsic regional brain activity in first-episode and chronic schizophrenia: a meta-analysis of resting-state functional MRI

Fri, 10/04/2019 - 12:20
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Abnormalities of intrinsic regional brain activity in first-episode and chronic schizophrenia: a meta-analysis of resting-state functional MRI

J Psychiatry Neurosci. 2019 Oct 03;44(6):180245

Authors: Gong J, Wang J, Luo X, Chen G, Huang H, Huang R, Huang L, Wang Y

Abstract
Background: Resting-state functional MRI (fMRI) studies have provided much evidence for abnormal intrinsic brain activity in schizophrenia, but results have been inconsistent.
Methods: We conducted a meta-analysis of whole-brain, resting-state fMRI studies that explored differences in amplitude of low-frequency fluctuation (ALFF) between people with schizophrenia (including first episode and chronic) and healthy controls.
Results: A systematic literature search identified 24 studies comparing a total of 1249 people with schizophrenia and 1179 healthy controls. Overall, patients with schizophrenia displayed decreased ALFF in the bilateral postcentral gyrus, bilateral precuneus, left inferior parietal gyri and right occipital lobe, and increased ALFF in the right putamen, right inferior frontal gyrus, left inferior temporal gyrus and right anterior cingulate cortex. In the subgroup analysis, patients with first-episode schizophrenia demonstrated decreased ALFF in the bilateral inferior parietal gyri, right precuneus and left medial prefrontal cortex, and increased ALFF in the bilateral putamen and bilateral occipital gyrus. Patients with chronic schizophrenia showed decreased ALFF in the bilateral postcentral gyrus, left precuneus and right occipital gyrus, and increased ALFF in the bilateral inferior frontal gyri, bilateral superior frontal gyrus, left amygdala, left inferior temporal gyrus, right anterior cingulate cortex and left insula.
Limitations: The small sample size of our subgroup analysis, predominantly Asian samples, processing steps and publication bias could have limited the accuracy of the results.
Conclusion: Our comprehensive meta-analysis suggests that findings of aberrant regional intrinsic brain activity during the initial stages of schizophrenia, and much more widespread damage with the progression of disease, may contribute to our understanding of the progressive pathophysiology of schizophrenia.

PMID: 31580042 [PubMed - as supplied by publisher]

Weighted Graph Regularized Sparse Brain Network Construction for MCI Identification.

Fri, 10/04/2019 - 12:20
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Weighted Graph Regularized Sparse Brain Network Construction for MCI Identification.

Pattern Recognit. 2019 Jun;90:220-231

Authors: Yu R, Qiao L, Chen M, Lee SW, Fei X, Shen D

Abstract
Brain functional networks (BFNs) constructed from resting-state functional magnetic resonance imaging (rs-fMRI) have been widely applied to the analysis and diagnosis of brain diseases, such as Alzheimer's disease and its prodrome, namely mild cognitive impairment (MCI). Constructing a meaningful brain network based on, for example, sparse representation (SR) is the most essential step prior to the subsequent analysis or disease identification. However, the independent coding process of SR fails to capture the intrinsic locality and similarity characteristics in the data. To address this problem, we propose a novel weighted graph (Laplacian) regularized SR framework, based on which BFN can be optimized by considering both intrinsic correlation similarity and local manifold structure in the data, as well as sparsity prior of the brain connectivity. Additionally, the non-convergence of the graph Laplacian in the self-representation model has been solved properly. Combined with a pipeline of sparse feature selection and classification, the effectiveness of our proposed method is demonstrated by identifying MCI based on the constructed BFNs.

PMID: 31579345 [PubMed]

Strength and Similarity Guided Group-level Brain Functional Network Construction for MCI Diagnosis.

Fri, 10/04/2019 - 12:20
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Strength and Similarity Guided Group-level Brain Functional Network Construction for MCI Diagnosis.

Pattern Recognit. 2019 Apr;88:421-430

Authors: Zhang Y, Zhang H, Chen X, Liu M, Zhu X, Lee SW, Shen D

Abstract
Sparse representation-based brain functional network modeling often results in large inter-subject variability in the network structure. This could reduce the statistical power in group comparison, or even deteriorate the generalization capability of the individualized diagnosis of brain diseases. Although group sparse representation (GSR) can alleviate such a limitation by increasing network similarity across subjects, it could, in turn, fail in providing satisfactory separability between the subjects from different groups (e.g., patients vs. controls). In this study, we propose to integrate individual functional connectivity (FC) information into the GSR-based network construction framework to achieve higher between-group separability while maintaining the merit of within-group consistency. Our method was based on an observation that the subjects from the same group have generally more similar FC patterns than those from different groups. To this end, we propose our new method, namely "strength and similarity guided GSR (SSGSR)", which exploits both BOLD signal temporal correlation-based "low-order" FC (LOFC) and inter-subject LOFC-profile similarity-based "high-order" FC (HOFC) as two priors to jointly guide the GSR-based network modeling. Extensive experimental comparisons are carried out, with the rs-fMRI data from mild cognitive impairment (MCI) subjects and healthy controls, between the proposed algorithm and other state-of-the-art brain network modeling approaches. Individualized MCI identification results show that our method could achieve a balance between the individually consistent brain functional network construction and the adequately maintained inter-group brain functional network distinctions, thus leading to a more accurate classification result. Our method also provides a promising and generalized solution for the future connectome-based individualized diagnosis of brain disease.

PMID: 31579344 [PubMed]

Functional Connectivity Alterations in Neuromyelitis Optica Spectrum Disorder : Correlation with Disease Duration and Cognitive Impairment.

Fri, 10/04/2019 - 12:20
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Functional Connectivity Alterations in Neuromyelitis Optica Spectrum Disorder : Correlation with Disease Duration and Cognitive Impairment.

Clin Neuroradiol. 2019 Oct 01;:

Authors: Han Y, Liu Y, Zeng C, Luo Q, Xiong H, Zhang X, Li Y

Abstract
PURPOSE: The aim of this study was to investigate resting state functional connectivity alterations within the main brain networks in neuromyelitis optica spectrum disorder (NMOSD) and their associations with disease duration, disability and cognitive dysfunction progression.
METHODS: Resting state functional magnetic resonance imaging (rs-fMRI), clinical and neuropsychological evaluations were obtained from 41 NMOSD patients and 41 healthy controls. Seed-voxel functional connectivity was analyzed in seven major hubs, including the default mode network, dorsal attention network, visual network, sensorimotor network, cerebellar network, thalamic network and reward-emotion network. Abnormalities of functional connectivity and correlations with disease duration, scores of the expanded disability status scale (EDSS), mini-mental state examination (MMSE) and Montreal cognitive assessment (MoCA) were further explored.
RESULTS: Compared with healthy controls, NMOSD patients showed increased functional connectivity in the default mode network, dorsal attention network and thalamic network, while decreased in the visual network and cerebellum networks. At the regional level, increased functional connectivity involved the right superior temporal gyrus, left fusiform gyrus, left inferior parietal lobule, bilateral middle frontal gyrus and right precuneus, whereas functional connectivity was decreased in the right parahippocampal gyrus and left precuneus. Functional connectivity reduction in the right parahippocampal gyrus positively correlated with disease duration (r = 0.488, p = 0.001) and negatively correlated with MoCA scores (r = -0.330, p = 0.035).
CONCLUSION: The study demonstrated functional alterations in the rs-fMRI of NMOSD, which provide a novel insight into the large-scale selective functional reorganization and could be useful to reveal the characteristics of the physiological mechanism.

PMID: 31578601 [PubMed - as supplied by publisher]

Stability of dynamic functional architecture differs between brain networks and states.

Thu, 10/03/2019 - 11:20
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Stability of dynamic functional architecture differs between brain networks and states.

Neuroimage. 2019 Sep 29;:116230

Authors: Li L, Lu B, Yan CG

Abstract
Stable representation of information in distributed neural connectivity is critical to function effectively in the world. Despite the dynamic nature of the brain's functional architecture, characterizing its temporal stability within a continuous state has been largely neglected. Here we characterized stability of functional architecture at a dynamic timescale (∼1 min) for each brain voxel by measuring the concordance of dynamic functional connectivity (DFC) over time, compared between association and unimodal regions, and established its reliability using test-retest resting-state fMRI data of adults from an open dataset. After the measure of functional stability was established, we further employed another fMRI open dataset which included movie-watching and resting-state data of children and adolescents, to explore how stability was modified by natural viewing from its intrinsic form, with specific focus on the associative and primary visual cortices. The results showed that high-order association regions, especially the default mode network, demonstrated high stability during resting-state scans, while primary sensory-motor cortices revealed relatively lower stability. During movie watching, stability in the primary visual cortex was decreased, which was associated with larger DFC variation with neighboring regions. By contrast, higher-order regions in the ventral and dorsal visual stream demonstrated increased stability. The distribution of functional stability and its modification describes a profile of the brain's stability property, which may be useful reference for examining distinct mental states and disorders.

PMID: 31577959 [PubMed - as supplied by publisher]

Homotopic region connectivity during concussion recovery: A longitudinal fMRI study.

Thu, 10/03/2019 - 11:20
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Homotopic region connectivity during concussion recovery: A longitudinal fMRI study.

PLoS One. 2019;14(10):e0221892

Authors: Chong CD, Wang L, Wang K, Traub S, Li J

Abstract
OBJECTIVES: To (i) investigate alterations in homotopic functional connectivity (hfc) in concussed patients relative to healthy controls (HC) and to (ii) interrogate whether hfc in concussed patients normalized during the recovery process. The relationship between symptom recovery and change in hfc was assessed using post-hoc analyses.
METHODS: This study included 15 concussed patients (mean age = 39.1, SD = 10.1; sex: 13 females, 2 males) and 15 HC (mean age = 39.1, SD = 11.7; sex: 13 females, 2 males). Hfc patterns were interrogated using resting-state magnetic resonance imaging (rs-MRI) for 29 a priori selected pain-processing regions. Concussed patients underwent imaging at two time-points; at 1-month post-concussion (mean time following concussion: 28 days, SD = 9.5) and again at 5-months post-concussion (mean time following concussion: 121 days, SD = 13). At both time-points, symptoms associated with concussion were assessed using the Sports Concussion Assessment Tool (SCAT-3).
RESULTS: Concussed patients had significantly weaker hfc in the following six regions 1-month post-concussion compared to HC: middle cingulate, posterior insula, middle occipital, spinal trigeminal nucleus, precentral and the pulvinar. There were no regions of significantly stronger hfc in concussed patients relative to HC. Longitudinally, patients showed significant symptom recovery 5-months post-concussion and had significant strengthening of hfc patterns in seven homotopic ROIs: middle cingulate, posterior insula, middle occipital, secondary somatosensory area, spinal trigeminal nucleus, precentral, and the pulvinar. Post-hoc analyses indicated a significant negative correlation between somatosensory functional connectivity strengthening and symptom severity.
CONCLUSION: At 1-month post-concussion, patients had significantly weaker hfc in a number of pain-processing regions relative to HC. However, over a period of 5-months, region-pair connectivity showed significant recovery and normalization. Those patients with more successful symptom recovery at 5-months post-concussion had more functional somatosensory strengthening, suggesting an association between functional strengthening and post-concussion symptom recovery.

PMID: 31577811 [PubMed - in process]

Power spectrum of resting-state blood-oxygen-level-dependent signal.

Thu, 10/03/2019 - 11:20
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Power spectrum of resting-state blood-oxygen-level-dependent signal.

Phys Rev E. 2019 Aug;100(2-1):022418

Authors: Pang JC, Robinson PA

Abstract
Hemodynamic modeling is used to explore the origin, predict, and analyze the power spectrum of the resting-state blood-oxygen-level-dependent (BOLD) signal measured by functional magnetic resonance imaging (fMRI), which has been reported to have a power-law form, i.e., P(f)∝f^{-s}, where P(f) is the power, f is the frequency, and s>0 is the power-law exponent. However, current fMRI experimental paradigms have limited acquisition durations, affecting the spectral resolution of fMRI data at the low-frequency regime. Here, the claimed power-law spectrum is investigated by using a recent hemodynamic model to analytically derive the BOLD power spectrum, with parameters that are related to neurophysiology. The theoretical results show that, for all realistic parameter combinations, the BOLD power spectrum is flat at f≲0.01Hz, has a weak resonance originating from intrinsic oscillations of vasodilatory response, and becomes a power law for high frequencies, all of which is in agreement with an empirical data set that describes the spectrum of one subject and brain region. However, the results are contrary to studies reporting a pure power-law spectrum at f≲0.2Hz. The discrepancy is attributed largely to data averaging employed by current approaches that averages together important properties of the BOLD power spectrum, such as its resonance, that biases the spectrum to only show a power law. Data averaging also reduces the high-frequency power-law exponent relative to individual cases. Overall, this work demonstrates how the model can reproduce BOLD dynamics and further analyze its low-frequency behavior. Moreover, it also uses the model to explain the impact of procedures, such as data averaging, on the reported features of the BOLD power spectrum.

PMID: 31574765 [PubMed - in process]

Individualized functional networks reconfigure with cognitive state.

Wed, 10/02/2019 - 16:20

Individualized functional networks reconfigure with cognitive state.

Neuroimage. 2019 Sep 28;:116233

Authors: Salehi M, Karbasi A, Barron DS, Scheinost D, Constable RT

Abstract
There is extensive evidence that functional organization of the human brain varies dynamically as the brain switches between task demands, or cognitive states. This functional organization also varies across subjects, even when engaged in similar tasks. To date, the functional network organization of the brain has been considered static. In this work we use fMRI data obtained across multiple cognitive states (task-evoked and rest conditions) and across multiple subjects, to measure state- and subject-specific functional network parcellation (the assignment of nodes to networks). Our parcellation approach provides a measure of how node-to-network assignment (NNA) changes across states and across subjects. We demonstrate that the brain's functional networks are not spatially fixed, but that many nodes change their network membership as a function of cognitive state. Such reconfigurations are highly robust and reliable to the extent that they can be used to predict cognitive state with up to 97% accuracy. Our findings suggest that if functional networks are to be defined via functional clustering of nodes, then it is essential to consider that such definitions may be fluid and cognitive-state dependent.

PMID: 31574322 [PubMed - as supplied by publisher]

Learning to play badminton altered resting-state activity and functional connectivity of the cerebellar sub-regions in adults.

Wed, 10/02/2019 - 16:20

Learning to play badminton altered resting-state activity and functional connectivity of the cerebellar sub-regions in adults.

PLoS One. 2019;14(10):e0223234

Authors: Shao M, Lin H, Yin D, Li Y, Wang Y, Ma J, Yin J, Jin H

Abstract
Previous studies have shown that sport experts are different from novices in functions and structures of the cerebellar sub-regions and the functional connectivity (FC) associated with the cerebellum, suggesting the role of the cerebellum on motor skill learning (MSL). However, the manipulation of individuals with different motor skills fails to exclude the effects of innate talents. In addition, individuals with higher motor skills often start with the MSL in their young ages. It is still unclear whether the effects regarding the cerebellum would be shown at one's adult age. The present study was to directly alter individuals' motor skills to investigate whether MSL (taking learning to play badminton as an example) in adulthood influences resting-state activity in the cerebellum. To this end, young adults without ball training experience were recruited as participants and were assigned randomly into the experimental group and the control group. Participants in the experimental group were asked to attend a badminton training course for 12 weeks, while the control group did not regularly attend any ball sports during this period. Resting-state functional magnetic resonance imaging (fMRI) was recorded before and after the training. Results showed that compared to the control group, the experimental group had smaller amplitude of low-frequency fluctuation (ALFF) in right cerebellar hemispheric VI and left VIII after training. For the experimental group, right hemispheric VIII had a stronger FC with left hemispheric IV-V, cerebellar vermal IX, left middle cingulate gyrus and right hippocampus after training. Taken together, these findings suggested that MSL, at least learning to play badminton in adulthood, reduces resting-state activity in different sub-regions in the cerebellum but increases FC between sub-regions of the cerebellum as well as between sub-regions of the cerebellum and cerebral cortices (e.g., middle cingulate cortex and hippocampus).

PMID: 31574108 [PubMed - in process]

Altered brain network centrality in patients with late monocular blindness: a resting-state fMRI study.

Wed, 10/02/2019 - 16:20

Altered brain network centrality in patients with late monocular blindness: a resting-state fMRI study.

Arch Med Sci. 2019 Sep;15(5):1301-1307

Authors: Huang X, Li HJ, Peng DC, Ye L, Yang QC, Zhong YL, Zhou FQ, Shao Y

Abstract
Introduction: The aim of the study was to investigate the underlying functional network brain activity changes in patients with late monocular blindness (MB) and the relationship with their clinical features using the voxel-wise degree centrality (DC) method.
Material and methods: A total of 32 patients with MB (25 males and 7 females), and 32 healthy controls (HCs) (25 males and 7 females) closely matched in age, sex, and education, underwent resting-state functional magnetic resonance imaging scans. The DC method was used to assess local features of spontaneous brain activity. Correlation analysis was performed to explore the relationships between the observed mean DC signal values of the different areas and clinical features in these patients.
Results: Compared with HCs, MB patients had significantly lower DC values in the bilateral cuneus/V1/V2, and significantly higher DC values in the left inferior temporal gyrus and bilateral medial frontal gyrus. However, there was no relationship between the observed mean DC values of the different brain areas and the behavioral performance.
Conclusions: Late monocular blindness involves brain function network dysfunction in many regions, which might indicate impairment of the visual cortex and other vision-related brain regions in the MBs.

PMID: 31572477 [PubMed]

Altered Patterns of the Fractional Amplitude of Low-Frequency Fluctuation and Functional Connectivity Between Deficit and Non-Deficit Schizophrenia.

Wed, 10/02/2019 - 16:20

Altered Patterns of the Fractional Amplitude of Low-Frequency Fluctuation and Functional Connectivity Between Deficit and Non-Deficit Schizophrenia.

Front Psychiatry. 2019;10:680

Authors: Zhou C, Tang X, You W, Wang X, Zhang X, Zhang X, Yu M

Abstract
Objective: A limited number of studies have previously reported on the regional activity [amplitude of low-frequency fluctuation (ALFF)] and functional integration [functional connectivity (FC)] of the whole brain in deficit schizophrenia (DS). The present study investigates the resting-state characteristics of the fractional ALFF (fALFF) and the FC in both DS and non-deficit schizophrenia (NDS) patients, and further explores their correlations with neurocognitive features. Methods: Demographic, resting-state functional magnetic resonance imaging (MRI), and neurocognitive data were collected from 33 DS and 41 NDS male patients, as well as in 40 male healthy controls (HCs). The voxel-wise fALFF was measured to evaluate regional cerebral function. Regions with differences in fALFF between DS and NDS patients were used as seed points in whole-brain FC analysis. Partial correlation analysis was conducted to examine associations between the fALFF or the FC of altered regions and neurocognitive assessments. Results: Both patient groups showed decreased fALFF in the sensorimotor area, visual cortex, and frontoparietal pathway, but increased fALFF in the precuneus and middle cingulate gyrus when compared with the HCs. Moreover, the NDS group demonstrated higher fALFF than HCs in the left thalamus, caudate, and hippocampus. Compared with the NDS group, the fALFF of the visual cortex was specifically increased, but that of the bilateral insula, the anterior cingulate gyrus (ACG), and the regions extended to the frontotemporal cortex was decreased in the DS group. Numerous abnormal FCs of nerve pathways were found between the two patient groups, mainly concentrated in the frontooccipital, frontotemporal, insula-visual cortex, as well as the temporooccipital pathway. Correlation analysis indicated that, in the DS group, the FC value between the left insula and the visual cortex was positively correlated with cognitive flexibility. In the NDS group, the fALFF of the right insula was negatively correlated with speech fluency, and the FC value between the ACG and the visual cortex was positively correlated with visual spatial memory. Conclusion: The present study demonstrates different altered patterns of fALFF and FC between male patients with DS and NDS. The specific altered regions of the salience network (SN) associated with impaired neurocognition in male DS patients suggest novel insights into the pathogenesis of cognitive impairment in schizophrenia.

PMID: 31572248 [PubMed]

Brain Networks Reveal the Effects of Antipsychotic Drugs on Schizophrenia Patients and Controls.

Wed, 10/02/2019 - 16:20

Brain Networks Reveal the Effects of Antipsychotic Drugs on Schizophrenia Patients and Controls.

Front Psychiatry. 2019;10:611

Authors: Towlson EK, Vértes PE, Müller-Sedgwick U, Ahnert SE

Abstract
The study of brain networks, including those derived from functional neuroimaging data, attracts a broad interest and represents a rapidly growing interdisciplinary field. Comparing networks of healthy volunteers with those of patients can potentially offer new, quantitative diagnostic methods and a framework for better understanding brain and mind disorders. We explore resting state functional Magnetic Resonance Imaging (fMRI) data through network measures. We construct networks representing 15 healthy individuals and 12 schizophrenia patients (males and females), all of whom are administered three drug treatments: i) a placebo; and two antipsychotic medications ii) aripiprazole and iii) sulpiride. We compare these resting state networks to a performance at an "N-back" working memory task. We demonstrate that not only is there a distinctive network architecture in the healthy brain that is disrupted in schizophrenia but also that both networks respond to antipsychotic medication. We first reproduce the established finding that brain networks of schizophrenia patients exhibit increased efficiency and reduced clustering compared with controls. Our data then reveal that the antipsychotic medications mitigate this effect, shifting the metrics toward those observed in healthy volunteers, with a marked difference in efficacy between the two drugs. Additionally, we find that aripiprazole considerably alters the network statistics of healthy controls. Examining the "N-back" working memory task, we establish that aripiprazole also adversely affects their performance. This suggests that changes to macroscopic brain network architecture result in measurable behavioral differences. This is one of the first studies to directly compare different medications using a whole-brain graph theoretical analysis with accompanying behavioral data. The small sample size is an inherent limitation and means a degree of caution is warranted in interpreting the findings. Our results lay the groundwork for an objective methodology with which to calculate and compare the efficacy of different treatments of mind and brain disorders.

PMID: 31572229 [PubMed]

Structural and Functional Disruptions in Subcortical Vascular Mild Cognitive Impairment With and Without Depressive Symptoms.

Wed, 10/02/2019 - 16:20

Structural and Functional Disruptions in Subcortical Vascular Mild Cognitive Impairment With and Without Depressive Symptoms.

Front Aging Neurosci. 2019;11:241

Authors: Lyu H, Wang J, Xu J, Zheng H, Yang X, Lin S, Chen J, Zhou L, Hu Y, Guo Z

Abstract
Many previous studies have revealed structural and functional abnormalities in patients with the subcortical vascular mild cognitive impairment (svMCI). Although depression symptoms were suggested to serve as a potential marker of conversion to dementia in patients with svMCI, whether these disruptions or other new findings will be identified in the svMCI comorbid with depression symptoms has not been established. In the current study, we combined voxel-based morphometry (VBM) and the resting-state functional magnetic resonance imaging (fMRI) to investigate the structural and functional disruptions in the svMCI with and without depression symptoms using a cohort of 18 svMCI with depression symptoms (svMCI+D), 17 svMCI without depression symptoms (svMCI-D), and 23 normal controls (NC). As a result, we identified significantly decreased gray matter density in the left parahippocampus (ParaHIPP.L), the right hippocampus (HIPP.R), and the right middle cingulate cortex (MCC.R) in both svMCI+D and svMCI-D compared to NC. Most importantly, we also identified increased gray matter density in the MCC.R accompanied by increased resting-state functional connectivity (RSFC) with right parahippocampus (ParaHIPP.R) in the svMCI+D compared to svMCI-D. Moreover, the gray matter density of MCC.R and ParaHIPP.L was correlated with cognitive impairments and depression symptoms in the svMCI, respectively. In conclusion, these results extended previous studies and added weight to considerations of depression symptoms in the svMCI. Moreover, we suggested that a processing loop associated with HIPP, ParaHIPP, and MCC might underlie the mechanism of depression symptoms in the svMCI.

PMID: 31572164 [PubMed]

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