New resting-state fMRI related studies at PubMed

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Posttraumatic stress disorder symptom severity is associated with reduced default mode network connectivity in individuals with elevated genetic risk for psychopathology.

Fri, 05/12/2017 - 11:20

Posttraumatic stress disorder symptom severity is associated with reduced default mode network connectivity in individuals with elevated genetic risk for psychopathology.

Depress Anxiety. 2017 May 11;:

Authors: Miller DR, Logue MW, Wolf EJ, Maniates H, Robinson ME, Hayes JP, Stone A, Schichman S, McGlinchey RE, Milberg WP, Miller MW

Abstract
BACKGROUND: Accumulating evidence suggests that posttraumatic stress disorder (PTSD) is associated with disrupted default mode network (DMN) connectivity, but findings across studies have not been uniform. Individual differences in relevant genes may account for some of the reported variability in the relationship between DMN connectivity and PTSD. In this study, we investigated this possibility using genome-wide association study (GWAS) derived polygenic risk scores (PRSs) for relevant psychiatric traits. We hypothesized that the association between PTSD and DMN connectivity would be moderated by genetic risk for one or more psychiatric traits such that individuals with elevated polygenic risk for psychopathology and severe PTSD would exhibit disrupted DMN connectivity.
METHODS: Participants were 156 white, non-Hispanic veterans of the wars in Iraq and Afghanistan who were genotyped and underwent resting state functional magnetic resonance imaging and clinical assessment. PRSs for neuroticism, anxiety, major depressive disorder, and cross-disorder risk (based on five psychiatric disorders) were calculated using summary statistics from published large-scale consortia-based GWASs.
RESULTS: Cross-disorder polygenic risk influenced the relationship between DMN connectivity and PTSD symptom severity such that individuals at greater genetic risk showed a significant negative association between PTSD symptom severity and connectivity between the posterior cingulate cortex and right middle temporal gyrus. Polygenic risk for neuroticism, anxiety, and major depressive disorder did not influence DMN connectivity directly or through an interaction with PTSD.
CONCLUSIONS: Findings illustrate the potential power of genome-wide PRSs to advance understanding of the relationship between PTSD and DMN connectivity, a putative neural endophenotype of the disorder.

PMID: 28494120 [PubMed - as supplied by publisher]

Topological Filtering of Dynamic Functional Brain Networks Unfolds Informative Chronnectomics: A Novel Data-Driven Thresholding Scheme Based on Orthogonal Minimal Spanning Trees (OMSTs).

Fri, 05/12/2017 - 11:20
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Topological Filtering of Dynamic Functional Brain Networks Unfolds Informative Chronnectomics: A Novel Data-Driven Thresholding Scheme Based on Orthogonal Minimal Spanning Trees (OMSTs).

Front Neuroinform. 2017;11:28

Authors: Dimitriadis SI, Salis C, Tarnanas I, Linden DE

Abstract
The human brain is a large-scale system of functionally connected brain regions. This system can be modeled as a network, or graph, by dividing the brain into a set of regions, or "nodes," and quantifying the strength of the connections between nodes, or "edges," as the temporal correlation in their patterns of activity. Network analysis, a part of graph theory, provides a set of summary statistics that can be used to describe complex brain networks in a meaningful way. The large-scale organization of the brain has features of complex networks that can be quantified using network measures from graph theory. The adaptation of both bivariate (mutual information) and multivariate (Granger causality) connectivity estimators to quantify the synchronization between multichannel recordings yields a fully connected, weighted, (a)symmetric functional connectivity graph (FCG), representing the associations among all brain areas. The aforementioned procedure leads to an extremely dense network of tens up to a few hundreds of weights. Therefore, this FCG must be filtered out so that the "true" connectivity pattern can emerge. Here, we compared a large number of well-known topological thresholding techniques with the novel proposed data-driven scheme based on orthogonal minimal spanning trees (OMSTs). OMSTs filter brain connectivity networks based on the optimization between the global efficiency of the network and the cost preserving its wiring. We demonstrated the proposed method in a large EEG database (N = 101 subjects) with eyes-open (EO) and eyes-closed (EC) tasks by adopting a time-varying approach with the main goal to extract features that can totally distinguish each subject from the rest of the set. Additionally, the reliability of the proposed scheme was estimated in a second case study of fMRI resting-state activity with multiple scans. Our results demonstrated clearly that the proposed thresholding scheme outperformed a large list of thresholding schemes based on the recognition accuracy of each subject compared to the rest of the cohort (EEG). Additionally, the reliability of the network metrics based on the fMRI static networks was improved based on the proposed topological filtering scheme. Overall, the proposed algorithm could be used across neuroimaging and multimodal studies as a common computationally efficient standardized tool for a great number of neuroscientists and physicists working on numerous of projects.

PMID: 28491032 [PubMed - in process]

Resting-State Functional Connectivity and Network Analysis of Cerebellum with Respect to Crystallized IQ and Gender.

Fri, 05/12/2017 - 11:20
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Resting-State Functional Connectivity and Network Analysis of Cerebellum with Respect to Crystallized IQ and Gender.

Front Hum Neurosci. 2017;11:189

Authors: Pezoulas VC, Zervakis M, Michelogiannis S, Klados MA

Abstract
During the last years, it has been established that the prefrontal and posterior parietal brain lobes, which are mostly related to intelligence, have many connections to cerebellum. However, there is a limited research investigating cerebellum's relationship with cognitive processes. In this study, the network of cerebellum was analyzed in order to investigate its overall organization in individuals with low and high crystallized Intelligence Quotient (IQ). Functional magnetic resonance imaging (fMRI) data were selected from 136 subjects in resting-state from the Human Connectome Project (HCP) database and were further separated into two IQ groups composed of 69 low-IQ and 67 high-IQ subjects. Cerebellum was parcellated into 28 lobules/ROIs (per subject) using a standard cerebellum anatomical atlas. Thereafter, correlation matrices were constructed by computing Pearson's correlation coefficients between the average BOLD time-series for each pair of ROIs inside the cerebellum. By computing conventional graph metrics, small-world network properties were verified using the weighted clustering coefficient and the characteristic path length for estimating the trade-off between segregation and integration. In addition, a connectivity metric was computed for extracting the average cost per network. The concept of the Minimum Spanning Tree (MST) was adopted and implemented in order to avoid methodological biases in graph comparisons and retain only the strongest connections per network. Subsequently, six global and three local metrics were calculated in order to retrieve useful features concerning the characteristics of each MST. Moreover, the local metrics of degree and betweenness centrality were used to detect hubs, i.e., nodes with high importance. The computed set of metrics gave rise to extensive statistical analysis in order to examine differences between low and high-IQ groups, as well as between all possible gender-based group combinations. Our results reveal that both male and female networks have small-world properties with differences in females (especially in higher IQ females) indicative of higher neural efficiency in cerebellum. There is a trend toward the same direction in men, but without significant differences. Finally, three lobules showed maximum correlation with the median response time in low-IQ individuals, implying that there is an increased effort dedicated locally by this population in cognitive tasks.

PMID: 28491028 [PubMed - in process]

Concordance of the Resting State Networks in Typically Developing, 6-to 7-Year-Old Children and Healthy Adults.

Thu, 05/11/2017 - 23:10
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Concordance of the Resting State Networks in Typically Developing, 6-to 7-Year-Old Children and Healthy Adults.

Front Hum Neurosci. 2017;11:199

Authors: Thornburgh CL, Narayana S, Rezaie R, Bydlinski BN, Tylavsky FA, Papanicolaou AC, Choudhri AF, Völgyi E

Abstract
Though fairly well-studied in adults, less is known about the manifestation of resting state networks (RSN) in children. We examined the validity of RSN derived in an ethnically diverse group of typically developing 6- to 7-year-old children. We hypothesized that the RSNs in young children would be robust and would reliably show significant concordance with previously published RSN in adults. Additionally, we hypothesized that a smaller sample size using this robust technique would be comparable in quality to pediatric RSNs found in a larger cohort study. Furthermore, we posited that compared to the adult RSNs, the primary sensorimotor and the default mode networks (DMNs) in this pediatric group would demonstrate the greatest correspondence, while the executive function networks would exhibit a lesser degree of spatial overlap. Resting state functional magnetic resonance images (rs-fMRI) were acquired in 18 children between 6 and 7 years recruited from an ethnically diverse population in the Mid-South region of the United States. Twenty RSNs were derived using group independent component analysis and their spatial correspondence with previously published adult RSNs was examined. We demonstrate that the rs-fMRI in this group can be deconstructed into the fundamental RSN as all the major RSNs previously described in adults and in a large sample that included older children can be observed in our sample of young children. Further, the primary visual, auditory, and somatosensory networks, as well as the default mode, and frontoparietal networks derived in this group exhibited a greater spatial concordance with those seen in adults. The motor, temporoparietal, executive control, dorsal attention, and cerebellar networks in children had less spatial overlap with the corresponding RSNs in adults. Our findings suggest that several salient RSNs can be mapped reliably in small and diverse pediatric cohort within a narrow age range and the evolution of these RSNs can be studied reliably in such groups during early childhood and adolescence.

PMID: 28487641 [PubMed - in process]

Intranasal insulin enhances brain functional connectivity mediating the relationship between adiposity and subjective feeling of hunger.

Thu, 05/11/2017 - 23:10
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Intranasal insulin enhances brain functional connectivity mediating the relationship between adiposity and subjective feeling of hunger.

Sci Rep. 2017 May 09;7(1):1627

Authors: Kullmann S, Heni M, Veit R, Scheffler K, Machann J, Häring HU, Fritsche A, Preissl H

Abstract
Brain insulin sensitivity is an important link between metabolism and cognitive dysfunction. Intranasal insulin is a promising tool to investigate central insulin action in humans. We evaluated the acute effects of 160 U intranasal insulin on resting-state brain functional connectivity in healthy young adults. Twenty-five lean and twenty-two overweight and obese participants underwent functional magnetic resonance imaging, on two separate days, before and after intranasal insulin or placebo application. Insulin compared to placebo administration resulted in increased functional connectivity between the prefrontal regions of the default-mode network and the hippocampus as well as the hypothalamus. The change in hippocampal functional connectivity significantly correlated with visceral adipose tissue and the change in subjective feeling of hunger after intranasal insulin. Mediation analysis revealed that the intranasal insulin induced hippocampal functional connectivity increase served as a mediator, suppressing the relationship between visceral adipose tissue and hunger. The insulin-induced hypothalamic functional connectivity change showed a significant interaction with peripheral insulin sensitivity. Only participants with high peripheral insulin sensitivity showed a boost in hypothalamic functional connectivity. Hence, brain insulin action may regulate eating behavior and facilitate weight loss by modifying brain functional connectivity within and between cognitive and homeostatic brain regions.

PMID: 28487570 [PubMed - in process]

Medial reward and lateral non-reward orbitofrontal cortex circuits change in opposite directions in depression.

Thu, 05/11/2017 - 23:10
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Medial reward and lateral non-reward orbitofrontal cortex circuits change in opposite directions in depression.

Brain. 2016 Dec;139(Pt 12):3296-3309

Authors: Cheng W, Rolls ET, Qiu J, Liu W, Tang Y, Huang CC, Wang X, Zhang J, Lin W, Zheng L, Pu J, Tsai SJ, Yang AC, Lin CP, Wang F, Xie P, Feng J

Abstract
The first brain-wide voxel-level resting state functional connectivity neuroimaging analysis of depression is reported, with 421 patients with major depressive disorder and 488 control subjects. Resting state functional connectivity between different voxels reflects correlations of activity between those voxels and is a fundamental tool in helping to understand the brain regions with altered connectivity and function in depression. One major circuit with altered functional connectivity involved the medial orbitofrontal cortex Brodmann area 13, which is implicated in reward, and which had reduced functional connectivity in depression with memory systems in the parahippocampal gyrus and medial temporal lobe, especially involving the perirhinal cortex Brodmann area 36 and entorhinal cortex Brodmann area 28. The Hamilton Depression Rating Scale scores were correlated with weakened functional connectivity of the medial orbitofrontal cortex Brodmann area 13. Thus in depression there is decreased reward-related and memory system functional connectivity, and this is related to the depressed symptoms. The lateral orbitofrontal cortex Brodmann area 47/12, involved in non-reward and punishing events, did not have this reduced functional connectivity with memory systems. Second, the lateral orbitofrontal cortex Brodmann area 47/12 had increased functional connectivity with the precuneus, the angular gyrus, and the temporal visual cortex Brodmann area 21. This enhanced functional connectivity of the non-reward/punishment system (Brodmann area 47/12) with the precuneus (involved in the sense of self and agency), and the angular gyrus (involved in language) is thus related to the explicit affectively negative sense of the self, and of self-esteem, in depression. A comparison of the functional connectivity in 185 depressed patients not receiving medication and 182 patients receiving medication showed that the functional connectivity of the lateral orbitofrontal cortex Brodmann area 47/12 with these three brain areas was lower in the medicated than the unmedicated patients. This is consistent with the hypothesis that the increased functional connectivity of the lateral orbitofrontal cortex Brodmann area 47/12 is related to depression. Relating the changes in cortical connectivity to our understanding of the functions of different parts of the orbitofrontal cortex in emotion helps to provide new insight into the brain changes related to depression.

PMID: 27742666 [PubMed - indexed for MEDLINE]

resting state fMRI; +18 new citations

Wed, 05/10/2017 - 10:34

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Do all roads lead to Rome? A comparison of brain networks derived from inter-subject volumetric and metabolic covariance and moment-to-moment hemodynamic correlations in old individuals.

Sun, 05/07/2017 - 21:20
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Do all roads lead to Rome? A comparison of brain networks derived from inter-subject volumetric and metabolic covariance and moment-to-moment hemodynamic correlations in old individuals.

Brain Struct Funct. 2017 May 04;:

Authors: Di X, Gohel S, Thielcke A, Wehrl HF, Biswal BB, Alzheimer’s Disease Neuroimaging Initiative

Abstract
Relationships between spatially remote brain regions in human have typically been estimated by moment-to-moment correlations of blood-oxygen-level dependent signals in resting-state using functional MRI (fMRI). Recently, studies using subject-to-subject covariance of anatomical volumes, cortical thickness, and metabolic activity are becoming increasingly popular. However, question remains on whether these measures reflect the same inter-region connectivity and brain network organizations. In the current study, we systematically analyzed inter-subject volumetric covariance from anatomical MRI images, metabolic covariance from fluorodeoxyglucose positron emission tomography images from 193 healthy subjects, and resting-state moment-to-moment correlations from fMRI images of a subset of 44 subjects. The correlation matrices calculated from the three methods were found to be minimally correlated, with higher correlation in the range of 0.31, as well as limited proportion of overlapping connections. The volumetric network showed the highest global efficiency and lowest mean clustering coefficient, leaning toward random-like network, while the metabolic and resting-state networks conveyed properties more resembling small-world networks. Community structures of the volumetric and metabolic networks did not reflect known functional organizations, which could be observed in resting-state network. The current results suggested that inter-subject volumetric and metabolic covariance do not necessarily reflect the inter-regional relationships and network organizations as resting-state correlations, thus calling for cautions on interpreting results of inter-subject covariance networks.

PMID: 28474183 [PubMed - as supplied by publisher]

Moment-to-moment BOLD Signal Variability Reflects Regional Changes in Neural Flexibility Across the Lifespan.

Sun, 05/07/2017 - 21:20
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Moment-to-moment BOLD Signal Variability Reflects Regional Changes in Neural Flexibility Across the Lifespan.

J Neurosci. 2017 May 04;:

Authors: Nomi JS, Bolt TS, Ezie C, Uddin LQ, Heller AS

Abstract
Variability of neuronal responses is thought to underlie flexible and optimal brain function. Because previous work investigating BOLD signal variability has been conducted within task-based fMRI contexts on adults and older individuals, very little is currently known regarding regional changes in spontaneous BOLD signal variability in the human brain across the lifespan. The current study utilized resting state fMRI data from a large sample of male and female human participants covering a wide age range (6-85 years) across two different fMRI acquisition parameters (TR = 0.645 and 1.4 seconds). Variability in brain regions including a key node of the salience network (anterior insula) increased linearly across the lifespan across datasets. In contrast, variability in most other large-scale networks decreased linearly over the lifespan. These results demonstrate unique lifespan trajectories of BOLD variability related to specific regions of the brain and add to a growing literature demonstrating the importance of identifying normative trajectories of functional brain maturation.SIGNIFICANCE STATEMENTAlthough brain signal variability has traditionally been considered a source of unwanted noise, recent work demonstrates that variability in brain signals during task performance is related to brain maturation in old age as well as individual differences in behavioral performance. The current results demonstrate that intrinsic fluctuations in resting-state variability exhibit unique maturation trajectories in specific brain regions and systems, particularly those supporting salience detection. These results have implications for investigations of brain development and aging, as well as interpretations of brain function underlying behavioral changes across the lifespan.

PMID: 28473644 [PubMed - as supplied by publisher]

Mapping Domain-Selective and Counterpointed Domain-General Higher Cognitive Functions in the Lateral Parietal Cortex: Evidence from fMRI Comparisons of Difficulty-Varying Semantic Versus Visuo-Spatial Tasks, and Functional Connectivity Analyses.

Fri, 05/05/2017 - 14:05

Mapping Domain-Selective and Counterpointed Domain-General Higher Cognitive Functions in the Lateral Parietal Cortex: Evidence from fMRI Comparisons of Difficulty-Varying Semantic Versus Visuo-Spatial Tasks, and Functional Connectivity Analyses.

Cereb Cortex. 2017 May 02;:1-14

Authors: Humphreys GF, Lambon Ralph MA

Abstract
Numerous cognitive domains have been associated with the lateral parietal cortex, yet how these disparate functions are packed into this region remains unclear. Whilst areas within the dorsal and the ventral parietal cortex (DPC and VPC) show differential function, there is considerable disagreement as to what these functions might be. Studies focussed on individual domains have plotted out variations of function across the region. Direct cross-domain comparisons are rare yet, when they have been undertaken, at least some regions (particularly the intraparietal sulcus [IPS] and core angular gyrus [AG]) appear to have contrastive domain-general qualities. In order to pursue this parietal puzzle, this study utilized both functional and resting-state magnetic resonance imaging to investigate a potential unifying neurocomputational framework-in which both domain general as well as domain-selective regions arise from differential patterns of connectivity into subregions of the lateral parietal cortex. Specifically we found that, consistent with their contrastive patterns of functional connectivity, subregions of DPC (anterior IPS) and VPC (AG) exhibit counterpointed functions sensitive to task/item-difficulty irrespective of cognitive domain. We propose that these regions serve as top-down executively penetrated and automatic bottom-up domain-general buffers of active information, respectively. In contrast, other parietal and nonparietal regions are tuned toward specific domains.

PMID: 28472382 [PubMed - as supplied by publisher]

Privacy preserving Evaporative Cooling feature selection and classification with Relief-F and Random Forests.

Fri, 05/05/2017 - 14:05

Privacy preserving Evaporative Cooling feature selection and classification with Relief-F and Random Forests.

Bioinformatics. 2017 May 04;:

Authors: Le TT, Kyle Simmons W, Misaki M, Bodurka J, White BC, Savitz J, McKinney BA

Abstract
Motivation: Classification of individuals into disease or clinical categories from high-dimensional biological data with low prediction error is an important challenge of statistical learning in bioinformatics. Feature selection can improve classification accuracy but must be incorporated carefully into cross-validation to avoid overfitting. Recently, feature selection methods based on differential privacy, such as differentially private random forests and reusable holdout sets, have been proposed. However, for domains such as bioinformatics, where the number of features is much larger than number of observations, these differential privacy methods are susceptible to overfitting.
Methods: We introduce private Evaporative Cooling, a stochastic privacy-preserving machine learning algorithm that uses Relief-F for feature selection and random forest for privacy preserving classification that also prevents overfitting. We relate the privacy-preserving threshold mechanism to a thermodynamic Maxwell-Boltzmann distribution, where the temperature represents the privacy threshold. We use the thermal statistical physics concept of Evaporative Cooling of atomic gases to perform backward stepwise privacy-preserving feature selection.
Results: On simulated data with main effects and statistical interactions, we compare accuracies on holdout and validation sets for three privacy-preserving methods: the reusable holdout, reusable holdout with random forest, and private Evaporative Cooling, which uses Relief-F feature selection and random forest classification. In simulations where interactions exist between attributes, private Evaporative Cooling provides higher classification accuracy without overfitting based on an independent validation set. In simulations without interactions, thresholdout with random forest and private Evaporative Cooling give comparable accuracies. We also apply these privacy methods to human brain resting-state fMRI data from a study of major depressive disorder.
Availability: Code available at http://insilico.utulsa.edu/software/privateEC .
Contact: brett- mckinney@utulsa.edu.
Supplementary information: Supplementary data are available at Bioinformatics online.

PMID: 28472232 [PubMed - as supplied by publisher]

Brain Modularity Mediates the Relation between Task Complexity and Performance.

Fri, 05/05/2017 - 14:05

Brain Modularity Mediates the Relation between Task Complexity and Performance.

J Cogn Neurosci. 2017 May 04;:1-15

Authors: Yue Q, Martin R, Fischer-Baum S, Ramos-Nuñez AI, Ye F, Deem MW

Abstract
Recent work in cognitive neuroscience has focused on analyzing the brain as a network, rather than as a collection of independent regions. Prior studies taking this approach have found that individual differences in the degree of modularity of the brain network relate to performance on cognitive tasks. However, inconsistent results concerning the direction of this relationship have been obtained, with some tasks showing better performance as modularity increases and other tasks showing worse performance. A recent theoretical model [Chen, M., & Deem, M. W. Development of modularity in the neural activity of children's brains. Physical Biology, 12, 016009, 2015] suggests that these inconsistencies may be explained on the grounds that high-modularity networks favor performance on simple tasks whereas low-modularity networks favor performance on more complex tasks. The current study tests these predictions by relating modularity from resting-state fMRI to performance on a set of simple and complex behavioral tasks. Complex and simple tasks were defined on the basis of whether they did or did not draw on executive attention. Consistent with predictions, we found a negative correlation between individuals' modularity and their performance on a composite measure combining scores from the complex tasks but a positive correlation with performance on a composite measure combining scores from the simple tasks. These results and theory presented here provide a framework for linking measures of whole-brain organization from network neuroscience to cognitive processing.

PMID: 28471728 [PubMed - as supplied by publisher]

Intrinsic functional organization of putative language networks in the brain following left cerebral hemispherectomy.

Fri, 05/05/2017 - 14:05

Intrinsic functional organization of putative language networks in the brain following left cerebral hemispherectomy.

Brain Struct Funct. 2017 May 03;:

Authors: Ivanova A, Zaidel E, Salamon N, Bookheimer S, Uddin LQ, de Bode S

Abstract
In rare cases of severe and intractable epilepsy, cerebral hemispherectomy is performed to arrest seizure activity and improve quality of life. The remaining hemisphere is often capable of supporting many cognitive functions post-surgery, although the outcome depends on the underlying etiology, hemisphere removed, and age of resection. The mechanisms underlying this massive reorganization are at present unknown. Here we examined intrinsic functional connectivity of putative language brain networks in four children after left cerebral hemispherectomy using resting-state functional magnetic resonance imaging (rsfMRI). We compared these functional systems to intrinsic language networks in 15 neurotypical controls using region-of-interest (ROI)-based functional connectivity analyses. In three out of four hemispherectomy patients, the ROI placed in the right inferior gyrus revealed a functional network that strongly resembled the right-hemisphere intrinsic language network observed in controls. This network typically comprised inferior frontal gyrus, superior temporal sulcus, and premotor regions. Quantitative ROI-to-ROI analyses revealed that functional connectivity between major nodes of the language network was significantly altered in all 4 examined patients. Overall, our data demonstrate that the pattern of functional connectivity within language networks is at least partially preserved in the intact right hemisphere of patients who underwent left hemispherectomy.

PMID: 28470553 [PubMed - as supplied by publisher]

Diminished Posterior Precuneus Connectivity with the Default Mode Network Differentiates Normal Aging from Alzheimer's Disease.

Fri, 05/05/2017 - 14:05
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Diminished Posterior Precuneus Connectivity with the Default Mode Network Differentiates Normal Aging from Alzheimer's Disease.

Front Aging Neurosci. 2017;9:97

Authors: Klaassens BL, van Gerven JMA, van der Grond J, de Vos F, Möller C, Rombouts SARB

Abstract
Both normal aging and Alzheimer's disease (AD) have been associated with a reduction in functional brain connectivity. It is unknown how connectivity patterns due to aging and AD compare. Here, we investigate functional brain connectivity in 12 young adults (mean age 22.8 ± 2.8), 12 older adults (mean age 73.1 ± 5.2) and 12 AD patients (mean age 74.0 ± 5.2; mean MMSE 22.3 ± 2.5). Participants were scanned during 6 different sessions with resting state functional magnetic resonance imaging (RS-fMRI), resulting in 72 scans per group. Voxelwise connectivity with 10 functional networks was compared between groups (p < 0.05, corrected). Normal aging was characterized by widespread decreases in connectivity with multiple brain networks, whereas AD only affected connectivity between the default mode network (DMN) and precuneus. The preponderance of effects was associated with regional gray matter volume. Our findings indicate that aging has a major effect on functional brain interactions throughout the entire brain, whereas AD is distinguished by additional diminished posterior DMN-precuneus coherence.

PMID: 28469571 [PubMed - in process]

Disrupted Topology of Frontostriatal Circuits Is Linked to the Severity of Insomnia.

Fri, 05/05/2017 - 14:05
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Disrupted Topology of Frontostriatal Circuits Is Linked to the Severity of Insomnia.

Front Neurosci. 2017;11:214

Authors: Lu FM, Liu CH, Lu SL, Tang LR, Tie CL, Zhang J, Yuan Z

Abstract
Insomnia is one of the most common health complaints, with a high prevalence of 30~50% in the general population. In particular, neuroimaging research has revealed that widespread dysfunctions in brain regions involved in hyperarousal are strongly correlated with insomnia. However, whether the topology of the intrinsic connectivity is aberrant in insomnia remains largely unknown. In this study, resting-state functional magnetic resonance imaging (rsfMRI) in conjunction with graph theoretical analysis, was used to construct functional connectivity matrices and to extract the attribute features of the small-world networks in insomnia. We examined the alterations in global and local small-world network properties of the distributed brain regions that are predominantly implicated in the frontostriatal network between 30 healthy subjects with insomnia symptoms (IS) and 62 healthy subjects without insomnia symptoms (NIS). Correlations between the small-world properties and clinical measurements were also generated to identify the differences between the two groups. Both the IS group and the NIS group exhibited a small-worldness topology. Meanwhile, the global topological properties didn't show significant difference between the two groups. By contrast, participants in the IS group showed decreased regional degree and efficiency in the left inferior frontal gyrus (IFG) compared with subjects in the NIS group. More specifically, significantly decreased nodal efficiency in the IFG was found to be negatively associated with insomnia scores, whereas the abnormal changes in nodal betweenness centrality of the right putamen were positively correlated with insomnia scores. Our findings suggested that the aberrant topology of the salience network and frontostriatal connectivity is linked to insomnia, which can serve as an important biomarker for insomnia.

PMID: 28469552 [PubMed - in process]

Neural plasticity in amplitude of low frequency fluctuation, cortical hub construction, regional homogeneity resulting from working memory training.

Fri, 05/05/2017 - 14:05
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Neural plasticity in amplitude of low frequency fluctuation, cortical hub construction, regional homogeneity resulting from working memory training.

Sci Rep. 2017 May 03;7(1):1470

Authors: Takeuchi H, Taki Y, Nouchi R, Sekiguchi A, Kotozaki Y, Nakagawa S, Makoto Miyauchi C, Sassa Y, Kawashima R

Abstract
Working memory training (WMT) induces changes in cognitive function and various neurological systems. Here, we investigated changes in recently developed resting state functional magnetic resonance imaging measures of global information processing [degree of the cortical hub, which may have a central role in information integration in the brain, degree centrality (DC)], the magnitude of intrinsic brain activity [fractional amplitude of low frequency fluctuation (fALFF)], and local connectivity (regional homogeneity) in young adults, who either underwent WMT or received no intervention for 4 weeks. Compared with no intervention, WMT increased DC in the anatomical cluster, including anterior cingulate cortex (ACC), to the medial prefrontal cortex (mPFC). Furthermore, WMT increased fALFF in the anatomical cluster including the right dorsolateral prefrontal cortex (DLPFC), frontopolar area and mPFC. WMT increased regional homogeneity in the anatomical cluster that spread from the precuneus to posterior cingulate cortex and posterior parietal cortex. These results suggest WMT-induced plasticity in spontaneous brain activity and global and local information processing in areas of the major networks of the brain during rest.

PMID: 28469197 [PubMed - in process]

Increased connectivity of hub networks and cognitive impairment in multiple sclerosis.

Fri, 05/05/2017 - 14:05
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Increased connectivity of hub networks and cognitive impairment in multiple sclerosis.

Neurology. 2017 May 03;:

Authors: Meijer KA, Eijlers AJC, Douw L, Uitdehaag BMJ, Barkhof F, Geurts JJG, Schoonheim MM

Abstract
OBJECTIVE: To investigate default-mode network (DMN) and frontoparietal network (FPN) dysfunction in cognitively impaired (CI) patients with multiple sclerosis (MS) because these networks strongly relate to cognition and contain most of the hubs of the brain.
METHODS: Resting-state fMRI and neuropsychological assessments were performed in 322 patients with MS and 96 healthy controls (HCs). Patients with MS were classified as CI (z score < -2.0 on at least 2 tests; n = 87), mildly cognitively impaired (z score < -1.5 on at least 2 tests and not CI; n = 65), and cognitively preserved (CP; n = 180). Within-network connectivity, connectivity with the rest of the brain, and between-network connectivity were calculated and compared between groups. Connectivity values were normalized for individual means and SDs.
RESULTS: Only in CI, both the DMN and FPN showed increased connectivity with the rest of the brain compared to HCs and CP, with no change in within- or between-network connectivity. Regionally, this increased connectivity was driven by the inferior parietal, posterior cingulate, and angular gyri. Increased connectivity with the rest of the brain correlated with worse cognitive performance, namely attention for the FPN as well as information processing speed and working memory for both networks.
CONCLUSIONS: In CI patients with MS, the DMN and FPN showed increased connectivity with the rest of the brain, while normal within- and between-network connectivity levels were maintained. These findings indicate that cognitive impairment in MS features disturbed communication of hub-rich networks, but only with the more peripheral (i.e., nonhub) regions of the brain.

PMID: 28468841 [PubMed - as supplied by publisher]

A Pilot Study on Brain Plasticity of Functional Connectivity Modulated by Cognitive Training in Mild Alzheimer's Disease and Mild Cognitive Impairment.

Fri, 05/05/2017 - 14:05
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A Pilot Study on Brain Plasticity of Functional Connectivity Modulated by Cognitive Training in Mild Alzheimer's Disease and Mild Cognitive Impairment.

Brain Sci. 2017 Apr 29;7(5):

Authors: Barban F, Mancini M, Cercignani M, Adriano F, Perri R, Annicchiarico R, Carlesimo GA, Ricci C, Lombardi MG, Teodonno V, Serra L, Giulietti G, Fadda L, Federici A, Caltagirone C, Bozzali M

Abstract
Alzheimer's disease (AD) alters the functional connectivity of the default mode network (DMN) but also the topological properties of the functional connectome. Cognitive training (CT) is a tool to slow down AD progression and is likely to impact on functional connectivity. In this pilot study, we aimed at investigating brain functional changes after a period of CT and active control (AC) in a group of 26 subjects with mild AD (mAD), 26 with amnestic mild cognitive impairment (aMCI), and a control group of 29 healthy elderly (HE) people. They all underwent a CT and AC in a counterbalanced order following a crossover design. Resting-state functional MRI and neuropsychological testing were acquired before and after each period. We tested post-CT and post-AC changes of cognitive abilities, of the functional connectivity of the DMN, and of topological network properties derived from graph theory and network-based statistics. Only CT produced functional changes, increasing the functional connectivity of the posterior DMN in all three groups. mAD also showed functional changes in the medial temporal lobe and topological changes in the anterior cingulum, whereas aMCI showed more widespread topological changes involving the frontal lobes, the cerebellum and the thalamus. Our results suggest specific functional connectivity changes after CT for aMCI and mAD.

PMID: 28468232 [PubMed]

Resting-state functional reorganization in Parkinson's disease: An activation likelihood estimation meta-analysis.

Thu, 05/04/2017 - 13:25

Resting-state functional reorganization in Parkinson's disease: An activation likelihood estimation meta-analysis.

Cortex. 2017 Apr 08;92:119-138

Authors: Tahmasian M, Eickhoff SB, Giehl K, Schwartz F, Herz DM, Drzezga A, van Eimeren T, Laird AR, Fox PT, Khazaie H, Zarei M, Eggers C, Eickhoff CR

Abstract
Parkinson's disease (PD) is a common progressive neurodegenerative disorder. Studies using resting-state functional magnetic resonance imaging (fMRI) to investigate underlying pathophysiology of motor and non-motor symptoms in PD yielded largely inconsistent results. This quantitative neuroimaging meta-analysis aims to identify consistent abnormal intrinsic functional patterns in PD across studies. We used PubMed to retrieve suitable resting-state studies and stereotactic data were extracted from 28 individual between-group comparisons. Convergence across their findings was tested using the activation likelihood estimation (ALE) approach. We found convergent evidence for intrinsic functional disturbances in bilateral inferior parietal lobule (IPL) and the supramarginal gyrus in PD patients compared to healthy subjects. In follow-up task-based and task-independent functional connectivity (FC) analyses using two independent healthy subject data sets, we found that the regions showing convergent aberrations in PD formed an interconnected network mainly with the default mode network (DMN). Behavioral characterization of these regions using the BrainMap database suggested associated dysfunction of perception and executive processes. Taken together, our findings highlight the role of parietal cortex in the pathophysiology of PD.

PMID: 28467917 [PubMed - as supplied by publisher]

Transdiagnostic Associations Between Functional Brain Network Integrity and Cognition.

Thu, 05/04/2017 - 13:25

Transdiagnostic Associations Between Functional Brain Network Integrity and Cognition.

JAMA Psychiatry. 2017 May 03;:

Authors: Sheffield JM, Kandala S, Tamminga CA, Pearlson GD, Keshavan MS, Sweeney JA, Clementz BA, Lerman-Sinkoff DB, Hill SK, Barch DM

Abstract
Importance: Cognitive impairment occurs across the psychosis spectrum and is associated with functional outcome. However, it is unknown whether these shared manifestations of cognitive dysfunction across diagnostic categories also reflect shared neurobiological mechanisms or whether the source of impairment differs.
Objective: To examine whether the general cognitive deficit observed across psychotic disorders is similarly associated with functional integrity of 2 brain networks widely implicated in supporting many cognitive domains.
Design, Setting, and Participants: A total of 201 healthy control participants and 375 patients with psychotic disorders from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) consortium were studied from September 29, 2007, to May 31, 2011. The B-SNIP recruited healthy controls and stable outpatients from 6 sites: Baltimore, Maryland; Boston, Massachusetts; Chicago, Illinois; Dallas, Texas; Detroit, Michigan; and Hartford, Connecticut. All participants underwent cognitive testing and resting-state functional magnetic resonance imaging. Data analysis was performed from April 28, 2015, to February 21, 2017.
Main Outcomes and Measures: The Brief Assessment of Cognition in Schizophrenia was used to measure cognitive ability. A principal axis factor analysis on the Brief Assessment of Cognition in Schizophrenia battery yielded a single factor (54% variance explained) that served as the measure of general cognitive ability. Functional network integrity measures included global and local efficiency of the whole brain, cingulo-opercular network (CON), frontoparietal network, and auditory network and exploratory analyses of all networks from the Power atlas. Group differences in network measures, associations between cognition and network measures, and mediation models were tested.
Results: The final sample for the current study included 201 healthy controls, 143 patients with schizophrenia, 103 patients with schizoaffective disorder, and 129 patients with psychotic bipolar disorder (mean [SD] age, 35.1 [12.0] years; 281 male [48.8%] and 295 female [51.2%]; 181 white [31.4%], 348 black [60.4%], and 47 other [8.2%]). Patients with schizophrenia (Cohen d = 0.36, P < .001) and psychotic bipolar disorder (Cohen d = 0.33, P = .002) had significantly reduced CON global efficiency compared with healthy controls. All patients with psychotic disorders had significantly reduced CON local efficiency, but the clinical groups did not differ from one another. The CON global efficiency was significantly associated with general cognitive ability across all groups (β = 0.099, P = .009) and significantly mediated the association between psychotic disorder status and general cognition (β = -0.037; 95% CI, -0.076 to -0.014). Subcortical network global efficiency was also significantly reduced in psychotic disorders (F3,587 = 4.01, P = .008) and positively predicted cognitive ability (β = 0.094, P = .009).
Conclusions and Relevance: These findings provide evidence that reduced CON and subcortical network efficiency play a role in the general cognitive deficit observed across the psychosis spectrum. They provide new support for the dimensional hypothesis that a shared neurobiological mechanism underlies cognitive impairment in psychotic disorders.

PMID: 28467520 [PubMed - as supplied by publisher]

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