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A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity.

Thu, 12/13/2018 - 15:01
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A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity.

Elife. 2018 Dec 10;7:

Authors: Yamashita M, Yoshihara Y, Hashimoto R, Yahata N, Ichikawa N, Sakai Y, Yamada T, Matsukawa N, Okada G, Tanaka SC, Kasai K, Kato N, Okamoto Y, Seymour B, Takahashi H, Kawato M, Imamizu H

Abstract
Working memory deficits are present in many neuropsychiatric diseases with diagnosis-related severity. However, it is unknown whether this common behavioral abnormality is a continuum explained by a neural mechanism shared across diseases or a set of discrete dysfunctions. Here, we performed predictive modeling to examine working memory ability (WMA) as a function of normative whole-brain connectivity across psychiatric diseases. We built a quantitative model for letter 3-back task performance in healthy participants, using resting state functional magnetic resonance imaging (rs-fMRI). This normative model was applied to independent participants (N = 965) including four psychiatric diagnoses. Individual's predicted WMA significantly correlated with a measured WMA in both healthy population and schizophrenia. Our predicted effect size estimates on WMA impairment were comparable to previous meta-analysis results. These results suggest a general association between brain connectivity and working memory ability applicable commonly to health and psychiatric diseases.

PMID: 30526859 [PubMed - as supplied by publisher]

Brain regional homogeneity and function connectivity in attenuated psychosis syndrome -based on a resting state fMRI study.

Thu, 12/13/2018 - 15:01
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Brain regional homogeneity and function connectivity in attenuated psychosis syndrome -based on a resting state fMRI study.

BMC Psychiatry. 2018 Dec 07;18(1):383

Authors: Long X, Liu F, Huang N, Liu N, Zhang J, Chen J, Qi A, Guan X, Lu Z

Abstract
BACKGROUND: By combining regional homogeneity (ReHo) and functional connectivity (FC) analyses, this study aimed to explore brain functional alterations in Attenuated Psychosis Syndrome (APS), which could provide complementary information for the neurophysiological indicators for schizophrenia (SZ) associated brain dysfunction.
METHODS: Twenty-one APS subjects and twenty healthy controls were enrolled in the data acquisition of demographics and clinical characteristics as well as structural and resting-state functional magnetic resonance imaging (rs-fMRI). ReHo analysis was conducted to determine the peak coordinate of the abnormal regional brain activity. Then, identified brain regions were considered as seed regions and were used to calculate FC between reginal brain voxels and whole brain voxels. Finally, potential correlations between imaging indices and clinical data were also explored.
RESULTS: Four APS and two HC subjects were excluded because the largest dynamic translation or rotation had exceeded 2 mm / 2°. Compared with healthy controls (HCs), APS subjects exhibited higher ReHo values in the right middle temporal gyrus (MTG) and lower ReHo values in the left middle frontal gyrus (MFG), left superior frontal gyrus (SFG), left postcentral gyrus (PoCG), and left superior frontal gyrus, medial (SFGmed). Considered these areas as seed regions, the APS subjects showed abnormal enhancement in functional brain connections, predominantly in the frontal and temporal lobes.
CONCLUSIONS: We concluded that the APS subjects had spatially regional dysfunction and remoted synchronous dysfunction in the frontal and temporal lobes of the brain, and changes in ReHo and FC patterns may reveal the mechanism of brain dysfunctions and may serve as an imaging biomarker for the diagnosis and evaluation of SZ.

PMID: 30526563 [PubMed - in process]

Methylphenidate Alters Functional Connectivity of Default Mode Network in Drug-Naive Male Adults With ADHD.

Thu, 12/13/2018 - 15:01
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Methylphenidate Alters Functional Connectivity of Default Mode Network in Drug-Naive Male Adults With ADHD.

J Atten Disord. 2018 Dec 10;:1087054718816822

Authors: Picon FA, Sato JR, Anés M, Vedolin LM, Mazzola AA, Valentini BB, Cupertino RB, Karam RG, Victor MM, Breda V, Silva K, da Silva N, Bau CHD, Grevet EH, Rohde LAP

Abstract
OBJECTIVE: This study evaluated the hypothesis that methylphenidate immediate release (MPH-IR) treatment would improve Default Mode Network (DMN) within-connectivity.
METHOD: Resting-state functional connectivity of the main nodes of DMN was evaluated in a highly homogeneous sample of 18 drug-naive male adult participants with ADHD.
RESULTS: Comparing resting-state functional connectivity functional magnetic resonance imaging (R-fMRI) scans before and after MPH treatment focusing exclusively on within-DMN connectivity, we evidenced the strengthening of functional connectivity between two nodes of the DMN: posterior cingulate cortex (PCC) and left lateral parietal cortex (LLP).
CONCLUSION: Our results contribute to the further understanding on how MPH affects functional connectivity within DMN of male adults with ADHD and corroborate the hypothesis of ADHD being a delayed neurodevelopmental disorder.

PMID: 30526190 [PubMed - as supplied by publisher]

Functional connection between the stereotyped behavior and the motor front area in children with autism.

Thu, 12/13/2018 - 15:01
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Functional connection between the stereotyped behavior and the motor front area in children with autism.

Br J Neurosurg. 2018 Dec 11;:1-4

Authors: Huang MX, Liu XH, Zhang ZJ, Chen C, Wang D, Hou X, Chen H, Xia K

Abstract
OBJECT: Autism spectrum disorders (ASD) is characterized by stereotyped behavior, attention deficit and/or impaired sensory perception to external stimuli. Its neurobiological mechanisms remain unclear. In this study we examined the resting-state functional connectivity of the premotor area and investigated its correlation with behavioral variables to determine whether connectivity alterations can distinguish ASD from healthy controls.
METHODS: 39 children with ASD and 42 healthy children with matched age, sex and intelligence were recruited. All the 81 subjects had behavioral index evaluation and underwent resting-state functional magnetic resonance imaging (fMRI) scans. After MRI data preprocessing, the left and right premotor areas were selected as region of interest (ROI) seeds to perform functional connectivity. Groups were compared, and the correlation between functional connectivity and behavioral indicators was analyzed.
RESULTS: Compared with healthy controls, ASD children showed significantly increased functional connectivity between the left premotor area and the posterior cingulate gyrus or anterior lobe of wedge, but functional connectivity between the left premotor area and the left insular lobe was decreased (p < 0.05, FDR correction). In addition, the connectivity between the left premotor area and the left insular lobe was negatively correlated with the behavioral scores (p < 0.05).
CONCLUSION: Imbalanced premotor functional connectivity may be one possible mechanism of stereotyped behavior in ASD.

PMID: 30526115 [PubMed - as supplied by publisher]

The Effects of Global Signal Regression on Estimates of Resting-state BOLD fMRI and EEG Vigilance Correlations.

Thu, 12/13/2018 - 15:01
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The Effects of Global Signal Regression on Estimates of Resting-state BOLD fMRI and EEG Vigilance Correlations.

Brain Connect. 2018 Dec 07;:

Authors: Falahpour M, Nalci A, Liu T

Abstract
Global signal regression (GSR) is a commonly used albeit controversial preprocessing approach in the analysis of resting-state BOLD fMRI data. While the effects of GSR on resting-state functional connectiv- ity measures have received much attention, there has been relatively little attention devoted to its effects on studies looking at the relation between resting-state BOLD measures and independent measures of brain activity. In this study we used simultaneously acquired EEG-fMRI data in humans to examine the effects of GSR on the correlation between resting-state BOLD fluctuations and EEG vigilance measures. We show that GSR leads to a positive shift in the correlation between the BOLD and vigilance measures. This shift leads to a reduction in the spatial extent of negative correlations in widespread brain areas, including the visual cortex, but leads to the appearance of positive correlations in other areas, such as the cingulate gyrus. The results obtained using GSR are consistent with those of a temporal censoring process in which the correlation is computed using a temporal subset of the data. Since the data from these retained time points are unaffected by the censoring process, this finding suggests that the positive correlations in cingulate gyrus are not simply an artifact of GSR.

PMID: 30525929 [PubMed - as supplied by publisher]

Dynamic functional connectivity during task performance and rest predicts individual differences in attention across studies.

Mon, 12/10/2018 - 21:49

Dynamic functional connectivity during task performance and rest predicts individual differences in attention across studies.

Neuroimage. 2018 Dec 03;:

Authors: Ching Fong A, Yoo K, Rosenberg M, Zhang S, Chiang-Shan RL, Scheinost D, Constable RT, Chun M

Abstract
Dynamic functional connectivity (DFC) aims to maximize resolvable information from functional brain scans by considering temporal changes in network structure. Recent work has demonstrated that static, i.e. time-invariant resting-state and task-based FC predicts individual differences in behavior, including attention. Here, we show that DFC predicts attention performance across individuals. Sliding-window FC matrices were generated from fMRI data collected during rest and attention task performance by calculating Pearson's r between every pair of nodes of a whole-brain atlas within overlapping 10-60s time segments. Next, variance in r values across windows was taken to quantify temporal variability in the strength of each connection, resulting in a DFC connectome for each individual. In a leave-one-subject-out-cross-validation approach, partial-least-square-regression (PLSR) models were then trained to predict attention task performance from DFC matrices. Predicted and observed attention scores were significantly correlated, indicating successful out-of-sample predictions across rest and task conditions. Combining DFC and static FC features numerically improves predictions over either model alone, but the improvement was not statistically significant. Moreover, dynamic and combined models generalized to two independent data sets (participants performing the Attention Network Task and the stop-signal task). Edges with significant PLSR coefficients concentrated in visual, motor, and executive-control brain networks; moreover, most of these coefficients were negative. Thus, better attention may rely on more stable, i.e. less variable, information flow between brain regions.

PMID: 30521950 [PubMed - as supplied by publisher]

Traces of Statistical Learning in the Brain's Functional Connectivity after Artificial Language Exposure.

Mon, 12/10/2018 - 21:49

Traces of Statistical Learning in the Brain's Functional Connectivity after Artificial Language Exposure.

Neuropsychologia. 2018 Dec 03;:

Authors: Sengupta P, Burgaleta M, Zamora-López G, Basora A, Sanjuán A, Deco G, Sebastian-Galles N

Abstract
Our environment is full of statistical regularities, and we are attuned to learn about these regularities by employing Statistical Learning (SL), a domain-general ability that enables the implicit detection of probabilistic regularities in our surrounding environment. The role of brain connectivity on SL has been previously explored, highlighting the relevance of structural and functional connections between frontal, parietal, and temporal cortices. However, whether SL can induce changes in the functional connections of the resting state brain has yet to be investigated. To address this question, we applied a pre-post design where participants (n=38) were submitted to resting-state fMRI acquisition before and after in-scanner exposure to either an artificial language stream (formed by 4 concatenated words) or a random audio stream. Our results showed that exposure to an artificial language stream significantly changed (corrected p < 0.05) the functional connectivity between Right Posterior Cingulum and Left Superior Parietal Lobule. This suggests that functional connectivity between brain networks supporting attentional and working memory processes may play an important role in statistical learning.

PMID: 30521815 [PubMed - as supplied by publisher]

Exploring the Brain Lateralization in ADHD Based on Variability of Resting-State fMRI Signal.

Mon, 12/10/2018 - 21:49

Exploring the Brain Lateralization in ADHD Based on Variability of Resting-State fMRI Signal.

J Atten Disord. 2018 Dec 06;:1087054718816170

Authors: Zou H, Yang J

Abstract
OBJECTIVE: In this study, we investigate the brain lateralization in ADHD patients. Furthermore, we also explore the difference between male and female patients, and the difference among distinct ADHD subtypes, that is, ADHD-inattentive (ADHD-IA) and ADHD-combined (ADHD-C).
METHOD: We employed the standard deviation to quantify the variability of resting-state functional magnetic resonance imaging (fMRI) signal and measure the lateralization index (LI).
RESULTS: ADHD patients showed significantly increased rightward lateralization in the inferior frontal gyrus (opercular), precuneus, and paracentral lobule, and decreased rightward lateralization in the insula. Compared with male patients, female patients showed significantly rightward lateralization in the putamen and lobule VII of cerebellar hemisphere. ADHD-C patients exhibited increased rightward lateralization in the inferior frontal gyrus (opercular), and decreased rightward lateralization in the inferior temporal gyrus, as compared with ADHD-IA. The LI was also found to be related to inattentive and hyper/impulsive scores.
CONCLUSION: These key findings may aid in understanding the pathology of ADHD.

PMID: 30520697 [PubMed - as supplied by publisher]

Effect of selective serotonin reuptake inhibitor on prefrontal-striatal connectivity is dependent on the level of TNF-α in patients with major depressive disorder.

Mon, 12/10/2018 - 21:49

Effect of selective serotonin reuptake inhibitor on prefrontal-striatal connectivity is dependent on the level of TNF-α in patients with major depressive disorder.

Psychol Med. 2018 Dec 06;:1-9

Authors: Liu K, Zhao X, Lu X, Zhu X, Chen H, Wang M, Yan W, Jing L, Deng Y, Yu L, Wu H, Wen G, Sun X, Lv Z

Abstract
BACKGROUND: We hypothesize that the tumor necrosis factor-α (TNF-α) may play a role in disturbing the effect of selective serotonin reuptake inhibitor (SSRI) on the striatal connectivity in patients with major depressive disorder (MDD).
METHODS: We performed a longitudinal observation by combining resting-state functional magnetic resonance imaging (rs-fMRI) and biochemical analyses to identify the abnormal striatal connectivity in MDD patients, and to evaluate the effect of TNF-α level on these abnormal connectivities during SSRI treatment. Eighty-five rs-fMRI scans were collected from 25 MDD patients and 35 healthy controls, and the scans were repeated for all the patients before and after a 6-week SSRI treatment. Whole-brain voxel-wise functional connectivity (FC) was calculated by correlating the rs-fMRI time courses between each voxel and the striatal seeds (i.e. spherical regions placed at the striatums). The level of TNF-α in serum was evaluated by Milliplex assay. Factorial analysis was performed to assess the interaction effects of 'TNF-α × treatment' in the regions with between-group FC difference.
RESULTS: Compared with controls, MDD patients showed significantly higher striatal FC in the medial prefrontal cortex (MPFC) and bilateral middle/superior temporal cortices before SSRI treatment (p < 0.001, uncorrected). Moreover, a significant interaction effect of 'TNF-α × treatment' was found in MPFC-striatum FC in MDD patients (p = 0.002), and the significance remained after adjusted for age, gender, head motion, and episode of disease.
CONCLUSION: These findings provide evidence that treatment-related brain connectivity change is dependent on the TNF-α level in MDD patients, and the MPFC-striatum connectivities possibly serve as an important target in the brain.

PMID: 30520409 [PubMed - as supplied by publisher]

Effect of blast-related mTBI on the working memory system: a resting state fMRI study.

Mon, 12/10/2018 - 21:49
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Effect of blast-related mTBI on the working memory system: a resting state fMRI study.

Brain Imaging Behav. 2018 Dec 05;:

Authors: Pagulayan KF, Petrie EC, Cook DG, Hendrickson RC, Rau H, Reilly M, Mayer C, Meabon JS, Raskind MA, Peskind ER, Kleinhans N

Abstract
Reduced working memory is frequently reported by Veterans with a history of blast-related mild traumatic brain injury (mTBI), but can be difficult to quantify on neuropsychological measures. This study aimed to improve our understanding of the impact of blast-related mTBI on the working memory system by using resting state functional magnetic resonance imaging (fMRI) to explore differences in functional connectivity between OEF/OIF/OND Veterans with and without a history of mTBI. Participants were twenty-four Veterans with a history of blast-related mTBI and 17 Veterans who were deployed but had no lifetime history of TBI. Working memory ability was evaluated with the Auditory Consonants Trigrams (ACT) task. Resting state fMRI was used to evaluate intrinsic functional connectivity from frontal seed regions that are known components of the working memory network. No significant group differences were found on the ACT, but the imaging analyses revealed widespread hyper-connectivity from the frontal seed regions in the Veterans with a history of mTBI relative to the deployed control group. Further, within the mTBI group, but not the control group, better performance on the ACT was associated with increased functional connectivity to multiple brain regions, including cerebellar components of the working memory network. These results were present after controlling for age, PTSD symptoms, and estimated premorbid IQ, and suggest that long-term alterations in the functional connectivity of the working memory network following blast-related mTBI may reflect a compensatory change that contributes to intact performance on an objective measure of working memory.

PMID: 30519997 [PubMed - as supplied by publisher]

Opposite subgenual cingulate cortical functional connectivity and metabolic activity patterns in refractory melancholic major depression.

Mon, 12/10/2018 - 21:49
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Opposite subgenual cingulate cortical functional connectivity and metabolic activity patterns in refractory melancholic major depression.

Brain Imaging Behav. 2018 Dec 05;:

Authors: Wu GR, De Raedt R, Van Schuerbeek P, Baeken C

Abstract
Although in treatment-resistant depression (TRD) subgenual anterior cingulate cortex (sgACC) functional connectivity (FC) is frequently used to examine deregulated brain networks, neurobiological data from other sources may be required to interpret these FC findings. In 16 melancholic TRD patients with a high level of treatment resistance and 16 closely matched healthy never-depressed individuals we verified whether sgACC FC patterns were related to regional metabolic activity (CMRglc) with 18FDG PET imaging. Notwithstanding that TRD patients displayed stronger sgACC FC with the right lateral frontotemporal cortex, metabolically they exhibited the opposite pattern. Our results indicate that the sgACC seed and its functionally connected regions not automatically follow a similar metabolic pattern in TRD, possibly reflecting the refractory state of the sample. Multimodal brain imaging may help to increase our insight into the pathophysiology of TRD.

PMID: 30519995 [PubMed - as supplied by publisher]

Functional Connectivity of Paired Default Mode Network Subregions in Retinal Detachment.

Mon, 12/10/2018 - 21:49
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Functional Connectivity of Paired Default Mode Network Subregions in Retinal Detachment.

Transl Vis Sci Technol. 2018 Nov;7(6):15

Authors: Su T, Shu YQ, Liu KC, Ye L, Chen LL, Shi WQ, Min YL, Xu XW, Yuan Q, Zhu PW, Shao Y

Abstract
Purpose: To explore the difference of the default mode network (DMN) in patients with retinal detachment (RD) by the study of the resting state functional connectivity (rs-FC).
Methods: A total of 30 patients with RD (16 men, 14 women) and 30 similarly matched normal controls (NCs) were examined and recorded with rs-fMRI. The DMN was divided into eight core regions, and each rs-FC map of each subregion was obtained. The receiver operating characteristic (ROC) curve was performed to classify the mean FC values of RD patients from NCs, and the interrelationships between the FC and each region were evaluated with Pearson's correlation analysis.
Results: Compared with NCs, there were significantly increased FC in the left medial temporal lobe (MTL.L) and posterior cingulate cortex (PCC), MTL.L and left hippocampus formation (HF.L), MTL.L and HF.R, MTL.L and left inferior parietal cortices (IPC.L), MTL.L and IPC.R in the RD group (P < 0.05). Nevertheless, no correlation between the FC values of each paired region and the manifestations was found in the RD group. ROC curve analysis showed that the accuracy of the area under the curve was excellent in MTL.L-HF.R and MTL.L-IPC.R and less reliable in MTL.L-PCC, MTL.L-HF.L, and MTL.L-IPC.L.
Conclusions: The visual function impairments of RD patients were closely related to the DMN functional connections, which provided insight into the neural variation in RD patients and assisted in revealing the potential mechanisms of RD.
Translational Relevance: This study provided insight into the neural variation in RD patients and assisted in revealing the potential mechanisms of RD.

PMID: 30519500 [PubMed]

TPH-2 Gene Polymorphism in Major Depressive Disorder Patients With Early-Wakening Symptom.

Mon, 12/10/2018 - 21:49
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TPH-2 Gene Polymorphism in Major Depressive Disorder Patients With Early-Wakening Symptom.

Front Neurosci. 2018;12:827

Authors: Tao S, Chattun MR, Yan R, Geng J, Zhu R, Shao J, Lu Q, Yao Z

Abstract
Background: Sleep disturbances, such as early wakening, are frequently observed in patients with major depressive disorder (MDD). The suprachiasmatic nuclei (SCN), which controls circadian rhythm, is innervated by the raphe nucleus, a region where Tryptophan hydroxylase-2 (TPH-2) gene is primarily expressed. Although TPH-2 is often implicated in the pathophysiology of depression, few studies have applied a genetic and imaging technique to investigate the mechanism of early wakening symptom in MDD. We hypothesized that TPH-2 variants could influence the function of SCN in MDD patients with early wakening symptom. Methods: One hundred and eighty five MDD patients (62 patients without early wakening and 123 patients with early wakening) and 64 healthy controls participated in this study. Blood samples were collected and genotyping of rs4290270, rs4570625, rs11178998, rs7305115, rs41317118, and rs17110747 were performed by next-generation sequencing (NGS) technology. Logistic regression model was employed for genetic data analysis using the PLINK software. Based on the allele type, rs4290270, which was significant in the early wakening MDD group, participants were categorized into two groups (A allele and T carrier). All patients underwent whole brain resting-state functional magnetic resonance imaging (rs-fMRI) scanning and a voxel-wise functional connectivity comparison was performed between the groups. Results: rs4290270 was significantly linked to MDD patients who exhibited early wakening symptom. The functional connectivities of the right SCN with the right fusiform gyrus and right middle frontal gyrus were increased in the T carrier group compared to the A allele group. In addition, the functional connectivities of the left SCN with the right lingual gyrus and left calcarine sulcus were decreased in the T carrier group compared to the A allele group. Conclusion: These findings suggested that the TPH-2 gene variant, rs4290270, affected the circadian regulating function of SCN. The altered functional connectivities, observed between the SCN and right fusiform gyrus, right middle frontal gyrus, the right lingual gyrus and left calcarine sulcus, could highlight the neural mechanism by which SCN induces sleep-related circadian disruption in T carrier MDD patients. Hence, rs4290270 could potentially serve as a reliable biomarker to identify MDD patients with early wakening symptom.

PMID: 30519155 [PubMed]

Predictive connectome subnetwork extraction with anatomical and connectivity priors.

Mon, 12/10/2018 - 21:49
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Predictive connectome subnetwork extraction with anatomical and connectivity priors.

Comput Med Imaging Graph. 2018 Aug 25;71:67-78

Authors: Brown CJ, Miller SP, Booth BG, Zwicker JG, Grunau RE, Synnes AR, Chau V, Hamarneh G

Abstract
We present a new method to identify anatomical subnetworks of the human connectome that are optimally predictive of targeted clinical variables, developmental outcomes or disease states. Given a training set of structural or functional brain networks, derived from diffusion MRI (dMRI) or functional MRI (fMRI) scans respectively, our sparse linear regression model extracts a weighted subnetwork. By enforcing novel backbone network and connectivity based priors along with a non-negativity constraint, the discovered subnetworks are simultaneously anatomically plausible, well connected, positively weighted and reasonably sparse. We apply our method to (1) predicting the cognitive and neuromotor developmental outcomes of a dataset of 168 structural connectomes of preterm neonates, and (2) predicting the autism spectrum category of a dataset of 1013 resting-state functional connectomes from the Autism Brain Imaging Data Exchange (ABIDE) database. We find that the addition of each of our novel priors improves prediction accuracy and together outperform other state-of-the-art prediction techniques. We then examine the structure of the learned subnetworks in terms of topological features and with respect to established function and physiology of different regions of the brain.

PMID: 30508806 [PubMed - as supplied by publisher]

Alternating Diffusion Map Based Fusion of Multimodal Brain Connectivity Networks for IQ Prediction.

Mon, 12/10/2018 - 21:49
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Alternating Diffusion Map Based Fusion of Multimodal Brain Connectivity Networks for IQ Prediction.

IEEE Trans Biomed Eng. 2018 Nov 29;:

Authors: Xiao L, Stephen JM, Wilson TW, Calhoun VD, Wang Y

Abstract
OBJECTIVE: To explain individual differences in development, behavior, and cognition, most previous studies focused on projecting resting-state functional MRI (fMRI) based functional connectivity (FC) data into a low-dimensional space via linear dimensionality reduction techniques, followed by executing analysis operations. However, linear dimensionality analysis techniques may fail to capture nonlinearity of brain neuroactivity. Moreover, besides resting-state FC, FC based on task fMRI can be expected to provide complementary information. Motivated by these considerations, we nonlinearly fuse resting-state and task-based FC networks (FCNs) to seek a better representation in this paper.
METHODS: We propose a framework based on alternating diffusion map (ADM), which extracts geometry-preserving low-dimensional embeddings that successfully parameterize the intrinsic variables driving the phenomenon of interest. Specifically, we first separately build resting-state and task-based FCNs by symmetric positive definite matrices using sparse inverse covariance estimation for each subject, and then utilize the ADM to fuse them in order to extract significant low-dimensional embeddings, which are used as fingerprints to identify individuals.
RESULTS: The proposed framework is validated on the Philadelphia Neurodevelopmental Cohort data, where we conduct extensive experimental study on resting-state and fractal n-back task fMRI for the classification of intelligence quotient (IQ). The fusion of resting-state and n-back task fMRI by the proposed framework achieves better classification accuracy than any single fMRI, and the proposed framework is shown to outperform several other data fusion methods.
CONCLUSION AND SIGNIFICANCE: To our knowledge, this paper is the first to demonstrate a successful extension of the ADM to fuse resting-state and task-based fMRI data for accurate prediction of IQ.

PMID: 30507492 [PubMed - as supplied by publisher]

Cerebral resting state markers of biased perception in social anxiety.

Mon, 12/10/2018 - 21:49
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Cerebral resting state markers of biased perception in social anxiety.

Brain Struct Funct. 2018 Dec 01;:

Authors: Kreifelts B, Weigel L, Ethofer T, Brück C, Erb M, Wildgruber D

Abstract
Social anxiety (SA) comprises a multitude of persistent fears around the central element of dreaded negative evaluation and exclusion. This very common anxiety is spectrally distributed among the general population and associated with social perception biases deemed causal in its maintenance. Here, we investigated cerebral resting state markers linking SA and biased social perception. To this end, resting state functional connectivity (RSFC) was assessed as the neurobiological marker in a study population with greatly varying SA using fMRI in the first step of the experiment. One month later the impact of unattended laughter-exemplifying social threat-on a face rating task was evaluated as a measure of biased social perception. Applying a dimensional approach, SA-related cognitive biases tied to the valence, dominance and arousal of the threat signal and their underlying RSFC patterns among central nodes of the cerebral emotion, voice and face processing networks were identified. In particular, the connectivity patterns between the amygdalae and the right temporal voice area met all criteria for a cerebral mediation of the association between SA and the laughter valence-related interpretation bias. Thus, beyond this identification of non-state-dependent cerebral markers of biased perception in SA, this study highlights both a starting point and targets for future research on the causal relationships between cerebral connectivity patterns, SA and biased perception, potentially via neurofeedback methods.

PMID: 30506458 [PubMed - as supplied by publisher]

A Single-Blinded Trial Using Resting-State Functional Magnetic Resonance Imaging of Brain Activity in Patients with Type 2 Diabetes and Painful Neuropathy.

Mon, 12/10/2018 - 21:49
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A Single-Blinded Trial Using Resting-State Functional Magnetic Resonance Imaging of Brain Activity in Patients with Type 2 Diabetes and Painful Neuropathy.

Diabetes Ther. 2018 Nov 30;:

Authors: Zhang Q, Zhang P, Yan R, Xu X, Mao C, Liu X, Li F, Ma J, Ye L, Yao Z, Wu J

Abstract
About two-thirds of patients with painful diabetic neuropathy (PDN) suffer from anxiety and/or depression disorders. However, the pathogenesis of PDN is unclear, in particular with respect to the mechanism associated with the central nervous system. We used the neuroimaging techniques of fraction amplitude of low-frequency fluctuation (fALFF) and regional homogeneity of resting-state functional magnetic resonance imaging (fMRI) to explore the brain activity in patients with PDN. The symptoms, signs and mental conditions of 19 patients with PDN and of 18 patients with non-pain neuropathy were assessed separately and compared. Blood oxygenation level-dependent resting-state fMRI scans of the brain were performed in all 37 patients with neuropathy and in 15 gender- and age-matched healthy controls. Our data showed that patients with PDN had increased insulin resistance (p  = 0.03), increased depression (p  = 0.02) and increased anxiety (p  < 0.001) compared with the controls and that all of these conditions were associated with abnormal spontaneous activities in several regions of the brain, including the somatosensory, cognitive and emotional regions. The duration of diabetes, level of glycated hemoglobin, homeostasis model assessment of insulin resistance and estimated glomerular filtration rate were significantly correlated to abnormal spontaneous activity in patients' brains. These results lead to the conclusion that patients with PDN have abnormal brain activity, indicating that the central nervous system may contribute to painful diabetic neuropathy. TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT03700502.

PMID: 30506341 [PubMed - as supplied by publisher]

Regional cerebral metabolism alterations affect resting-state functional connectivity in major depressive disorder.

Mon, 12/10/2018 - 21:49
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Regional cerebral metabolism alterations affect resting-state functional connectivity in major depressive disorder.

Quant Imaging Med Surg. 2018 Oct;8(9):910-924

Authors: Su H, Zuo C, Zhang H, Jiao F, Zhang B, Tang W, Geng D, Guan Y, Shi S

Abstract
Background: 18F-FDG positron emission tomography (PET) is a reliable technique to quantify regional neural glucose metabolism even with major depressive disorder (MDD) heterogeneous features. Previous study proposed that in the resting-state (RS), pairs of brain regions whose regional glucose metabolic rates were significantly correlated were functionally associated. This synchronicity indicates a neuronal metabolic and functional interaction in high energy efficient brain regions. In this study, a multimode method was used to identify the RS-FC patterns based on regional metabolism changes, and to observe its relationship with the severity of depressive symptoms in MDD patients.
Methods: The study enrolled 11 medication-naive MDD patients and 14 healthy subjects. All participants received a static 18F-FDG PET brain scan and a resting-state functional magnetic resonance imaging (RS-fMRI) scan. SPM5 software was used to compare brain metabolism in MDD patients with that in healthy controls, and designated regions with a change in metabolism as regions of interest (ROIs). The glucose metabolism-based regional RS-FC Z values were compared between groups. Then group independent component analysis (ICA) was used to identify the abnormal connectivity nodes in the intrinsic function networks. Finally, the correlation between abnormal RS-FC Z values and the severity of depressive symptoms was evaluated.
Results: Patients with MDD had reduced glucose metabolism in the putamen, claustrum, insular, inferior frontal gyrus, and supramarginal gyrus. The metabolic reduction regions impaired functional connectivity (FC) to key hubs, such as the Inferior frontal gyrus (pars triangular), angular gyrus, calcarine sulcus, middle frontal gyrus (MFG), located in dorsolateral prefrontal cortex (DLPFC)/parietal lobe, salience network (SN), primary visual cortex (V1), and language network respectively. There was no correlation between aberrant connectivity and the severity of clinical symptoms.
Conclusions: This research puts forward a possibility that focal neural activity alteration may share RS-FC dysfunction and be susceptible to hubs in the functional network in MDD. In particular, the metabolism and function profiles of the Inferior frontal gyrus (pars triangularis) should be emphasized in future MDD studies.

PMID: 30505720 [PubMed]

Identification and functional characterization of HIV-associated neurocognitive disorders with large-scale Granger causality analysis on resting-state functional MRI.

Mon, 12/10/2018 - 21:49
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Identification and functional characterization of HIV-associated neurocognitive disorders with large-scale Granger causality analysis on resting-state functional MRI.

Proc SPIE Int Soc Opt Eng. 2018 Feb;10575:

Authors: Chockanathan U, DSouza AM, Abidin AZ, Schifitto G, Wismüller A

Abstract
Resting-state functional MRI (rs-fMRI), coupled with advanced multivariate time-series analysis methods such as Granger causality, is a promising tool for the development of novel functional connectivity biomarkers of neurologic and psychiatric disease. Recently large-scale Granger causality (lsGC) has been proposed as an alternative to conventional Granger causality (cGC) that extends the scope of robust Granger causal analyses to high-dimensional systems such as the human brain. In this study, lsGC and cGC were comparatively evaluated on their ability to capture neurologic damage associated with HIV-associated neurocognitive disorders (HAND). Functional brain network models were constructed from rs-fMRI data collected from a cohort of HIV+ and HIV - subjects. Graph theoretic properties of the resulting networks were then used to train a support vector machine (SVM) model to predict clinically relevant parameters, such as HIV status and neuropsychometric (NP) scores. For the HIV+ /- classification task, lsGC, which yielded a peak area under the receiver operating characteristic curve (AUC) of 0.83, significantly outperformed cGC, which yielded a peak AUC of 0.61, at all parameter settings tested. For the NP score regression task, lsGC, with a minimum mean squared error (MSE) of 0.75, significantly outperformed cGC, with a minimum MSE of 0.84 (p < 0.001, one-tailed paired t-test). These results show that, at optimal parameter settings, lsGC is better able to capture functional brain connectivity correlates of HAND than cGC. However, given the substantial variation in the performance of the two methods at different parameter settings, particularly for the regression task, improved parameter selection criteria are necessary and constitute an area for future research.

PMID: 30505063 [PubMed]

Methylphenidate's effects on thalamic metabolism and functional connectivity in cannabis abusers and healthy controls.

Mon, 12/10/2018 - 21:49
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Methylphenidate's effects on thalamic metabolism and functional connectivity in cannabis abusers and healthy controls.

Neuropsychopharmacology. 2018 Dec 01;:

Authors: Demiral ŞB, Tomasi D, Wiers CE, Manza P, Shokri-Kojori E, Studentsova Y, Wang GJ, Volkow ND

Abstract
Methylphenidate (MPH) is a first line treatment for ADHD and is also misused as a purported cognitive enhancer, yet its effects on brain function are still poorly understood. Recent functional magnetic resonance imaging (fMRI) studies showed that MPH altered cortico-striatal resting functional connectivity (RFC). Here we investigated the effects of MPH in thalamic connectivity since the thalamus modulates striato-cortical signaling. We hypothesized that MPH would increase thalamic connectivity and metabolism, and that this response would be blunted in cannabis abusers. For this purpose, we measured RFC in seven thalamic nuclei using fMRI and brain glucose metabolism using positron emission tomography (PET) and 18F-fluorodeoxyglucose (FDG) in sixteen healthy controls and thirteen participants with cannabis use disorder (CUD) twice after placebo and after MPH (0.5 mg/kg, iv). MPH significantly increased thalamo-cerebellar connectivity and cerebellar metabolism to the same extent in both groups. Group comparisons revealed that in CUD compared to controls, metabolism in nucleus accumbens was lower for the placebo and MPH measures, that MPH-induced increases in thalamic metabolism were blunted, and that enhanced negative connectivity between thalamus and accumbens in CUD was normalized by MPH (reducing negative connectivity). Our findings identify the thalamus as a target of MPH, which increased its metabolism and connectivity. The reduced metabolism in nucleus accumbens and the disrupted thalamo-accumbens connectivity (enhanced negative connectivity) in CUD is consistent with impaired reactivity of the brain reward's circuit. MPH's normalization of thalamo-accumbens connectivity (reduced negative connectivity) brings forth its potential therapeutic value in CUD, which merits investigation.

PMID: 30504928 [PubMed - as supplied by publisher]