New resting-state fMRI related studies at PubMed

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Differential effects of Down's syndrome and Alzheimer's neuropathology on default mode connectivity.

Sun, 07/28/2019 - 14:40
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Differential effects of Down's syndrome and Alzheimer's neuropathology on default mode connectivity.

Hum Brain Mapp. 2019 Jul 26;:

Authors: Wilson LR, Vatansever D, Annus T, Williams GB, Hong YT, Fryer TD, Nestor PJ, Holland AJ, Zaman SH

Abstract
Down's syndrome is a chromosomal disorder that invariably results in both intellectual disability and Alzheimer's disease neuropathology. However, only a limited number of studies to date have investigated intrinsic brain network organisation in people with Down's syndrome, none of which addressed the links between functional connectivity and Alzheimer's disease. In this cross-sectional study, we employed 11 C-Pittsburgh Compound-B (PiB) positron emission tomography in order to group participants with Down's syndrome based on the presence of fibrillar beta-amyloid neuropathology. We also acquired resting state functional magnetic resonance imaging data to interrogate the connectivity of the default mode network; a large-scale system with demonstrated links to Alzheimer's disease. The results revealed widespread positive connectivity of the default mode network in people with Down's syndrome (n = 34, ages 30-55, median age = 43.5) and a stark lack of anti-correlation. However, in contrast to typically developing controls (n = 20, ages 30-55, median age = 43.5), the Down's syndrome group also showed significantly weaker connections in localised frontal and posterior brain regions. Notably, while a comparison of the PiB-negative Down's syndrome group (n = 19, ages 30-48, median age = 41.0) to controls suggested that alterations in default mode connectivity to frontal brain regions are related to atypical development, a comparison of the PiB-positive (n = 15, ages 39-55, median age = 48.0) and PiB-negative Down's syndrome groups indicated that aberrant connectivity in posterior cortices is associated with the presence of Alzheimer's disease neuropathology. Such distinct profiles of altered connectivity not only further our understanding of the brain physiology that underlies these two inherently linked conditions but may also potentially provide a biomarker for future studies of neurodegeneration in people with Down's syndrome.

PMID: 31350817 [PubMed - as supplied by publisher]

Sino Longitudinal Study on Cognitive Decline (SILCODE): protocol for a Chinese longitudinal observational study to develop risk prediction models of conversion to mild cognitive impairment in individuals with subjective cognitive decline.

Sun, 07/28/2019 - 14:40
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Sino Longitudinal Study on Cognitive Decline (SILCODE): protocol for a Chinese longitudinal observational study to develop risk prediction models of conversion to mild cognitive impairment in individuals with subjective cognitive decline.

BMJ Open. 2019 Jul 26;9(7):e028188

Authors: Li X, Wang X, Su L, Hu X, Han Y

Abstract
INTRODUCTION: Understanding the biological mechanism of subjective cognitive decline (SCD) in preclinical Alzheimer's disease (AD) and identifying those who will soon convert to mild cognitive impairment (MCI) are critical for developing appropriate strategies for early diagnosis and intervention of AD. We present the study protocol of the Sino Longitudinal Study on Cognitive Decline (SILCODE), a longitudinal observational study focusing on SCD in the context of AD.
METHODS AND ANALYSIS: Within SILCODE, approximately 800 subjects with SCD who are between 50 and 79 years old will be recruited through standardised public advertisements or memory clinics. They will undergo extensive assessment, including clinical and neuropsychological assessments, blood sample collection for plasma beta-amyloid and ApoE genotype, urine samples collection for AD7c-NTP, and multimodal MRI scans (structural MRI, diffusion tensor imaging, resting-state functional MRI and optional task-based functional MRI) as well as optional glucose metabolism and amyloid positron emission tomography. Subjects will be contacted by telephone every 3 months and interviewed, on average, every 15 months for 5 years. The study endpoint is the development of mild cognitive impairment or dementia. Jak & Bondi's actuarial neuropsychological method will be used for diagnosis of MCI. The least absolute shrinkage and selection operator logistic regression model followed by the sub-distribution hazard function model with death as a competing risk will be constructed to establish risk prediction models.
ETHICS AND DISSEMINATION: The ethics committee of the Xuanwu Hospital of Capital Medical University has approved this study protocol (ID: [2017]046). The results will be published in peer-reviewed journals and presented at national and international scientific conferences.
TRIAL REGISTRATION NUMBER: NCT03370744; Pre-results.

PMID: 31350244 [PubMed - in process]

Identifying inter-individual differences in pain threshold using brain connectome: a test-retest reproducible study.

Sun, 07/28/2019 - 14:40
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Identifying inter-individual differences in pain threshold using brain connectome: a test-retest reproducible study.

Neuroimage. 2019 Jul 23;:116049

Authors: Tu Y, Zhang B, Cao J, Wilson G, Zhang Z, Kong J

Abstract
Individuals are unique in terms of brain and behavior. Some are very sensitive to pain, while others have a high tolerance. However, how inter-individual intrinsic differences in the brain are related to pain is unknown. Here, we performed longitudinal test-retest analyses to investigate pain threshold variability among individuals using a resting-state fMRI brain connectome. Twenty-four healthy subjects who received four MRI sessions separated by at least 7 days were included in the data analysis. Subjects' pain thresholds were measured using two modalities of experimental pain (heat and pressure) on two different locations (heat pain: leg and arm; pressure pain: leg and thumbnail). Behavioral results showed strong inter-individual variability and strong within-individual stability in pain threshold. Resting state fMRI data analyses showed that functional connectivity profiles can accurately identify subjects across four sessions, indicating that an individual's connectivity profile may be intrinsic and unique. By using multivariate pattern analyses, we found that connectivity profiles could be used to predict an individual's pain threshold at both within-session and between-session levels, with the most predictive contribution from medial-frontal and frontal-parietal networks. These results demonstrate the potential of using a resting-state fMRI brain connectome to build a 'neural trait' for characterizing an individual's pain-related behavior, and such a 'neural trait' may eventually be used to personalize clinical assessments.

PMID: 31349067 [PubMed - as supplied by publisher]

Dissociating individual connectome traits using low-rank learning.

Sun, 07/28/2019 - 14:40
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Dissociating individual connectome traits using low-rank learning.

Brain Res. 2019 Jul 23;:146348

Authors: Qin J, Shen H, Zeng LL, Gao K, Luo Z, Hu D

Abstract
Intrinsic functional connectivity (FC) exhibits high variability across individuals, which may account for the diversity of cognitive and behavioural ability. This variability in connectivity could be attributed to individual-specific trait and inter-session state differences (intra-subject differences), as well as a small amount of noise. However, it is still a challenge to perform accurate identification of connectivity traits from FC. Here, we introduced a novel low-rank learning model to solve this problem with a new constraint item that could reduce intra-subject differences. The model could dissociate FC into a substrate (substrate) that delineates functional characteristics common across the population and connectivity traits that are expected to account for individual behavioural differences. Subsequently, we performed a sparse dictionary learning algorithm on the extracted connectivity traits and obtained a dictionary matrix, named connectivity dictionary. We could then predict cognitive behaviours, including fluid intelligence, oral reading recognition, grip strength and anger-aggression, more accurately using the connectivity dictionary than the original FC. The results reflect that we captured individual connectivity traits that more effectively represent cognitive behaviour. Moreover, we found that the functional substrate is significantly correlated with large-scale anatomical brain architecture, and individual differences in connectivity traits are constrained by the connectivity substrate. Our findings may advance our understanding of the relationships among anatomy, function, and behaviour.

PMID: 31348912 [PubMed - as supplied by publisher]

Brachial plexus injury and resting-state fMRI: Need for consensus.

Sun, 07/28/2019 - 14:40
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Brachial plexus injury and resting-state fMRI: Need for consensus.

Neurol India. 2019 May-Jun;67(3):679-683

Authors: Thaploo D, Bhat DI, Kulkarni MV, Devi BI

Abstract
Objective: The purpose of the study is to conduct the systematic review of literature available on resting-state functional MRI (fMRI) and brachial plexus injury.
Methods: We reviewed all the literature that are available on PubMed; keywords used were resting state, brachial plexus injury, and functional imaging. The reference papers listed were also reviewed. The research items were restricted to publications in English. Some papers have also incorporated studies such as task-based fMRI and transcranial magnetic stimulation (TMS), but only resting-state studies were included for this review.
Results: A total of 13 papers were identified, and only 10 were reviewed based on the criteria. The reviewed papers were further categorized on the basis of whether or not any surgical intervention was done. Seven papers have surgical management such as contralateral cervical 7 (CC7) neurotisation or intercostal nerve (ICN) musculocutaneous nerve (MCN) neurotisation.
Conclusion: There is conclusive evidence showing that there is cortical reorganisation following brachial plexus injury in both birth and traumatic cases. The changes are restricted to some of the resting-state networks only (default mode network, sensorimotor network, in particular). However, no study till date has focused on a far more longitudinal approach at studying these changes. It will be interesting to see the exact time and effect of these changes.

PMID: 31347534 [PubMed - in process]

Synchronization and variability imbalance underlie cognitive impairment in primary-progressive multiple sclerosis.

Sun, 07/28/2019 - 14:40
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Synchronization and variability imbalance underlie cognitive impairment in primary-progressive multiple sclerosis.

Sci Rep. 2017 04 21;7:46411

Authors: Petracca M, Saiote C, Bender HA, Arias F, Farrell C, Magioncalda P, Martino M, Miller A, Northoff G, Lublin F, Inglese M

Abstract
We aimed to investigate functional connectivity and variability across multiple frequency bands in brain networks underlying cognitive deficits in primary-progressive multiple sclerosis (PP-MS) and to explore how they are affected by the presence of cortical lesions (CLs). We analyzed functional connectivity and variability (measured as the standard deviation of BOLD signal amplitude) in resting state networks (RSNs) associated with cognitive deficits in different frequency bands in 25 PP-MS patients (12 M, mean age 50.9 ± 10.5 years) and 20 healthy subjects (9 M, mean age 51.0 ± 9.8 years). We confirmed the presence of a widespread cognitive deterioration in PP-MS patients, with main involvement of visuo-spatial and executive domains. Cognitively impaired patients showed increased variability, reduced synchronicity between networks involved in the control of cognitive macro-domains and hyper-synchronicity limited to the connections between networks functionally more segregated. CL volume was higher in patients with cognitive impairment and was correlated with functional connectivity and variability. We demonstrate, for the first time, that a functional reorganization characterized by hypo-synchronicity of functionally-related/hyper-synchronicity of functionally-segregated large scale networks and an abnormal pattern of neural activity underlie cognitive dysfunction in PP-MS, and that CLs possibly play a role in variability and functional connectivity abnormalities.

PMID: 28429774 [PubMed - indexed for MEDLINE]

Novel relative relevance score for estimating Brain Connectivity from fMRI data using an explainable neural network approach.

Fri, 07/26/2019 - 10:20

Novel relative relevance score for estimating Brain Connectivity from fMRI data using an explainable neural network approach.

J Neurosci Methods. 2019 Jul 22;:108371

Authors: Dang S, Chaudhury S

Abstract
BACKGROUND: Functional integration or connectivity in brain is directional, non-linear as well as variable in time-lagged dependence. Deep neural networks (DNN) have become an indispensable tool everywhere, by learning higher levels of abstract and complex patterns from raw data. However, in neuroscientific community they generally work as black-boxes, leading to the explanation of results difficult and less intuitive. We aim to propose a brain-connectivity measure based on an explainable NN (xNN) approach.
NEW METHOD: We build a NN-based predictor for regression problem. Since we aim to determine the contribution/relevance of past data-point from one region i in the prediction of current data-point from another region j, i.e. the higher-order connectivity between two brain-regions, we employ layer-wise relevance propagation (Bach et al., 2015) (LRP, a method for explaining DNN predictions), which has not been done before to the best of our knowledge. Specifically, we propose a novel score depending on weights as a quantitative measure of connectivity, called as relative relevance score (xNN-RRS). The RRS is an intuitive and transparent score. We provide an interpretation of the trained NN weights with-respect-to the brain-connectivity.
RESULTS: Face validity of our approach is demonstrated with experiments on simulated data, over existing methods. We also demonstrate construct validity of xNN-RRS in a resting-state fMRI experiment.
COMPARISON: Our approach shows superior performance, in terms of accuracy and computational complexity, over existing state-of-the-art methods for brain-connectivity estimation.
CONCLUSION: The proposed method is promising to serve as a first post-hoc explainable NN-approach for brain-connectivity analysis in clinical applications.

PMID: 31344374 [PubMed - as supplied by publisher]

Resting-state connectivity within and across neural circuits in anorexia nervosa.

Fri, 07/26/2019 - 10:20
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Resting-state connectivity within and across neural circuits in anorexia nervosa.

Brain Behav. 2019 01;9(1):e01205

Authors: Uniacke B, Wang Y, Biezonski D, Sussman T, Lee S, Posner J, Steinglass J

Abstract
INTRODUCTION: Obsessional thoughts and ritualized eating behaviors are characteristic of Anorexia Nervosa (AN), leading to the common suggestion that the illness shares neurobiology with obsessive-compulsive disorder (OCD). Resting-state functional connectivity MRI (rs-fcMRI) is a measure of functional neural architecture. This longitudinal study examined functional connectivity in AN within the limbic cortico-striato-thalamo-cortical (CSTC) loop, as well as in the salience network, the default mode network, and the executive control network (components of the triple network model of psychopathology).
METHODS: Resting-state functional connectivity MRI scans were collected in unmedicated female inpatients with AN (n = 25) and healthy controls (HC; n = 24). Individuals with AN were scanned before and after weight restoration and followed for one month after hospital discharge. HC were scanned twice over the same timeframe.
RESULTS: Using a seed-based correlation approach, individuals with AN had increased connectivity within the limbic CSTC loop when underweight, only. There was no significant association between limbic CSTC connectivity and obsessive-compulsive symptoms or prognosis. Exploratory analyses of functional network connectivity within the triple network model showed reduced connectivity between the salience network and left executive control network among AN relative to HC. These abnormalities persisted following weight restoration.
CONCLUSIONS: The CSTC findings suggest that the neural underpinnings of obsessive-compulsive symptoms may differ from those of OCD. The inter-network abnormalities warrant examination in relation to illness-specific behaviors, namely abnormal eating behavior. This longitudinal study highlights the complexity of the neural underpinnings of AN.

PMID: 30590873 [PubMed - indexed for MEDLINE]

Sex-Dependent Associations among Maternal Depressive Symptoms, Child Reward Network, and Behaviors in Early Childhood.

Thu, 07/25/2019 - 15:37
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Sex-Dependent Associations among Maternal Depressive Symptoms, Child Reward Network, and Behaviors in Early Childhood.

Cereb Cortex. 2019 Jul 24;:

Authors: Wang Q, Zhang H, Poh JS, Pecheva D, Broekman BFP, Chong YS, Shek LP, Gluckman PD, Fortier MV, Meaney MJ, Qiu A

Abstract
Maternal depression is associated with disrupted neurodevelopment in offspring. This study examined relationships among postnatal maternal depressive symptoms, the functional reward network and behavioral problems in 4.5-year-old boys (57) and girls (65). We employed canonical correlation analysis to evaluate whether the resting-state functional connectivity within a reward network, identified through an activation likelihood estimation (ALE) meta-analysis of fMRI studies, was associated with postnatal maternal depressive symptoms and child behaviors. The functional reward network consisted of three subnetworks, that is, the mesolimbic, mesocortical, and amygdala-hippocampus reward subnetworks. Postnatal maternal depressive symptoms were associated with the functional connectivity of the mesocortical subnetwork with the mesolimbic and amygdala-hippocampus complex subnetworks in girls and with the functional connectivity within the mesocortical subnetwork in boys. The functional connectivity of the amygdala-hippocampus subnetwork with the mesocortical and mesolimbic subnetworks was associated with both internalizing and externalizing problems in girls, while in boys, the functional connectivity of the mesocortical subnetwork with the amygdala-hippocampus complex and the mesolimbic subnetworks was associated with the internalizing and externalizing problems, respectively. Our findings suggest that the functional reward network might be a promising neural phenotype for effects of maternal depression and potential intervention to nurture child behavioral development.

PMID: 31339998 [PubMed - as supplied by publisher]

Tracking the Main States of Dynamic Functional Connectivity in Resting State.

Thu, 07/25/2019 - 15:37
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Tracking the Main States of Dynamic Functional Connectivity in Resting State.

Front Neurosci. 2019;13:685

Authors: Zhou Q, Zhang L, Feng J, Lo CZ

Abstract
Dynamical changes have recently been tracked in functional connectivity (FC) calculated from resting-state functional magnetic resonance imaging (R-fMRI), when a person is conscious but not carrying out a directed task during scanning. Diverse dynamical FC states (dFC) are believed to represent different internal states of the brain, in terms of brain-regional interactions. In this paper, we propose a novel protocol, the signed community clustering with the optimized modularity by two-step procedures, to track dynamical whole brain functional connectivity (dWFC) states. This protocol is assumption free without a priori threshold for the number of clusters. By applying our method on sliding window based dWFC's with automated anatomical labeling 2 (AAL2), three main dWFC states were extracted from R-fMRI datasets in Human Connectome Project, that are independent on window size. Through extracting the FC features of these states, we found the functional links in state 1 (WFC-C1) mainly involved visual, somatomotor, attention and cerebellar (posterior lobe) modules. State 2 (WFC-C2) was similar to WFC-C1, but more FC's linking limbic, default mode, and frontoparietal modules and less linking the cerebellum, sensory and attention modules. State 3 had more FC's linking default mode, limbic, and cerebellum, compared to WFC-C1 and WFC-C2. With tests of robustness and stability, our work provides a solid, hypothesis-free tool to detect dWFC states for the possibility of tracking rapid dynamical change in FCs among large data sets.

PMID: 31338016 [PubMed]

Combining multiple connectomes improves predictive modeling of phenotypic measures.

Thu, 07/25/2019 - 15:37
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Combining multiple connectomes improves predictive modeling of phenotypic measures.

Neuroimage. 2019 Jul 20;:116038

Authors: Gao S, Greene AS, Constable RT, Scheinost D

Abstract
Resting-state and task-based functional connectivity matrices, or connectomes, are powerful predictors of individual differences in phenotypic measures. However, most of the current state-of-the-art algorithms only build predictive models based on a single connectome for each individual. This approach neglects the complementary information contained in connectomes from different sources and reduces prediction performance. In order to combine different task connectomes into a single predictive model in a principled way, we propose a novel prediction framework, termed multidimensional connectome-based predictive modeling. Two specific algorithms are developed and implemented under this framework. Using two large open-source datasets with multiple tasks-the Human Connectome Project and the Philadelphia Neurodevelopmental Cohort, we validate and compare our framework against performing connectome-based predictive modeling (CPM) on each task connectome independently, CPM on a general functional connectivity matrix created by averaging together all task connectomes for an individual, and CPM with a naïve extension to multiple connectomes where each edge for each task is selected independently. Our framework exhibits superior performance in prediction compared with the other competing methods. We found that different tasks contribute differentially to the final predictive model, suggesting that the battery of tasks used in prediction is an important consideration. This work makes two major contributions: First, two methods for combining multiple connectomes from different task conditions in one predictive model are demonstrated; Second, we show that these models outperform a previously validated single connectome-based predictive model approach.

PMID: 31336188 [PubMed - as supplied by publisher]

Brain Dynamics: Global Pulse and Brain State Switching.

Thu, 07/25/2019 - 15:37
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Brain Dynamics: Global Pulse and Brain State Switching.

Curr Biol. 2019 Jul 22;29(14):R690-R692

Authors: Ville DV

Abstract
A major challenge in systems-level neuroscience is to understand the dynamic formation and succession of brain states. A new study has extracted reproducible brain states from mouse resting-state fMRI data, revealing interactions between occurrences of these states and the phase of global signal fluctuations and alterations of the states in a mouse model of autism.

PMID: 31336086 [PubMed - in process]

Abnormal intra-network architecture in extra-striate cortices in amblyopia: a resting state fMRI study.

Thu, 07/25/2019 - 15:37
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Abnormal intra-network architecture in extra-striate cortices in amblyopia: a resting state fMRI study.

Eye Vis (Lond). 2019;6:20

Authors: Lu Z, Huang Y, Lu Q, Feng L, Nguchu BA, Wang Y, Wang H, Li G, Zhou Y, Qiu B, Zhou J, Wang X

Abstract
Background: Amblyopia (lazy eye) is one of the most common causes of monocular visual impairment. Intensive investigation has shown that amblyopes suffer from a range of deficits not only in the primary visual cortex but also the extra-striate visual cortex. However, amblyopic brain processing deficits in large-scale information networks especially in the visual network remain unclear.
Methods: Through resting state functional magnetic resonance imaging (rs-fMRI), we studied the functional connectivity and efficiency of the brain visual processing networks in 18 anisometropic amblyopic patients and 18 healthy controls (HCs).
Results: We found a loss of functional correlation within the higher visual network (HVN) and the visuospatial network (VSN) in amblyopes. Additionally, compared with HCs, amblyopic patients exhibited disruptions in local efficiency in the V3v (third visual cortex, ventral part) and V4 (fourth visual cortex) of the HVN, as well as in the PFt, hIP3 (human intraparietal area 3), and BA7p (Brodmann area 7 posterior) of the VSN. No significant alterations were found in the primary visual network (PVN).
Conclusion: Our results indicate that amblyopia results in an intrinsic decrease of both network functional correlations and local efficiencies in the extra-striate visual networks.

PMID: 31334295 [PubMed]

Chemotherapy Potentially Facilitates the Occurrence of Radiation Encephalopathy in Patients With Nasopharyngeal Carcinoma Following Radiotherapy: A Multiparametric Magnetic Resonance Imaging Study.

Thu, 07/25/2019 - 15:37
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Chemotherapy Potentially Facilitates the Occurrence of Radiation Encephalopathy in Patients With Nasopharyngeal Carcinoma Following Radiotherapy: A Multiparametric Magnetic Resonance Imaging Study.

Front Oncol. 2019;9:567

Authors: Zhang Y, Yi X, Gao J, Li L, Liu L, Qiu T, Zhang J, Zhang Y, Liao W

Abstract
Radiation encephalopathy (RE) is deemed to be a disease induced only by radiotherapy (RT), with the effects of chemotherapeutic agents on the brains of nasopharyngeal carcinoma (NPC) patients being largely overlooked. In this study, we investigated structural and functional brain alterations in NPC patients following RT with or without chemotherapy. Fifty-six pre-RT, 37 post-RT, and 108 post-CCRT (concomitant chemo-radiotherapy) NPC patients were enrolled in this study. A surface-based local gyrification index (LGI) was obtained from high resolution MRI and was used to evaluate between-group differences in cortical folding. Seed-based functional connectivity (FC) analysis of resting-state fMRI data was also conducted to investigate the functional significance of the cortical folding alterations. Compared with the Pre-RT group, patients in the Post-CCRT group showed LGI reductions in widespread brain regions including the bilateral temporal lobes, insula, frontal lobes, and parietal lobes. Compared with the Post-RT group, patients in the Post-CCRT group showed LGI reductions in the right insula, which extended to the adjacent frontal lobe. Seed-based FC analysis showed that patients in the Post-CCRT group had lower FC between the insula and the left middle frontal gyrus than patients in the Pre-RT group. The follow-up results showed that patients in the Post-CCRT group had a much higher RE incidence rate (20.4%) than patients in the Post-RT group (2.7%; P = 0.01). These findings indicate that chemotherapy potentially facilitated the occurrence of RE in NPC patients who underwent radiotherapy.

PMID: 31334108 [PubMed]

Understanding the neural mechanisms of lisdexamfetamine dimesylate (LDX) pharmacotherapy in Binge Eating Disorder (BED): a study protocol.

Thu, 07/25/2019 - 15:37
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Understanding the neural mechanisms of lisdexamfetamine dimesylate (LDX) pharmacotherapy in Binge Eating Disorder (BED): a study protocol.

J Eat Disord. 2019;7:23

Authors: Griffiths KR, Yang J, Touyz SW, Hay PJ, Clarke SD, Korgaonkar MS, Gomes L, Anderson G, Foster S, Kohn MR

Abstract
Background: The efficacy and safety of Lisdexamfetamine dimesylate (LDX) in the treatment of moderate to severe binge eating disorder (BED) has been demonstrated in multiple randomised clinical trials. Despite this, little is known about how LDX acts to improve binge eating symptoms. This study aims to provide a comprehensive understanding of the neural mechanisms by which LDX improves symptoms of BED. We hypothesise that LDX will act by normalising connectivity within neural circuits responsible for reward and impulse control, and that this normalisation will correlate with reduced binge eating episodes.
Methods: This is an open-label Phase 4 clinical trial of LDX in adults with moderate to severe BED. Enrolment will include 40 adults with moderate to severe BED aged 18-40 years and Body Mass Index (BMI) of 20-45 kg/m2, and 22 healthy controls matched for age, gender and BMI. Clinical interview and validated scales are used to confirm diagnosis and screen for exclusion criteria, which include comorbid anorexia nervosa or bulimia nervosa, use of psychostimulants within the past 6 months, and current use of antipsychotics or noradrenaline reuptake inhibitors. Baseline assessments include clinical symptoms, multimodal neuroimaging, cognitive assessment of reward sensitivity and behavioural inhibition, and an (optional) genetic sample. A subset of these assessments are repeated after eight weeks of treatment with LDX titrated to either 50 or 70 mg. The primary outcome measures are resting-state intrinsic connectivity and the number of binge eating episodes. Analyses will be applied to resting-state fMRI data to characterise pharmacological effects across the functional connectome, and assess correlations with symptom measure changes. Comparison of neural measures between controls and those with BED post-treatment will also be performed to determine whether LDX normalises brain function.
Discussion: First enrolment was in May 2018, and is ongoing. This study is the first comprehensive investigation of the neurobiological changes that occur with LDX treatment in adults with moderate to severe BED.
Trial registration: ACTRN12618000623291, Australian and New Zealand Clinical Trials Registry URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=374913&isReview=true. Date of Registration: 20 April 2018.

PMID: 31333843 [PubMed]

A Personalized Autism Diagnosis CAD System Using a Fusion of Structural MRI and Resting-State Functional MRI Data.

Thu, 07/25/2019 - 15:37
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A Personalized Autism Diagnosis CAD System Using a Fusion of Structural MRI and Resting-State Functional MRI Data.

Front Psychiatry. 2019;10:392

Authors: Dekhil O, Ali M, El-Nakieb Y, Shalaby A, Soliman A, Switala A, Mahmoud A, Ghazal M, Hajjdiab H, Casanova MF, Elmaghraby A, Keynton R, El-Baz A, Barnes G

Abstract
Autism spectrum disorder is a neuro-developmental disorder that affects the social abilities of the patients. Yet, the gold standard of autism diagnosis is the autism diagnostic observation schedule (ADOS). In this study, we are implementing a computer-aided diagnosis system that utilizes structural MRI (sMRI) and resting-state functional MRI (fMRI) to demonstrate that both anatomical abnormalities and functional connectivity abnormalities have high prediction ability of autism. The proposed system studies how the anatomical and functional connectivity metrics provide an overall diagnosis of whether the subject is autistic or not and are correlated with ADOS scores. The system provides a personalized report per subject to show what areas are more affected by autism-related impairment. Our system achieved accuracies of 75% when using fMRI data only, 79% when using sMRI data only, and 81% when fusing both together. Such a system achieves an important next step towards delineating the neurocircuits responsible for the autism diagnosis and hence may provide better options for physicians in devising personalized treatment plans.

PMID: 31333507 [PubMed]

Alterations of Functional Brain Connectivity After Long-Duration Spaceflight as Revealed by fMRI.

Thu, 07/25/2019 - 15:37
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Alterations of Functional Brain Connectivity After Long-Duration Spaceflight as Revealed by fMRI.

Front Physiol. 2019;10:761

Authors: Pechenkova E, Nosikova I, Rumshiskaya A, Litvinova L, Rukavishnikov I, Mershina E, Sinitsyn V, Van Ombergen A, Jeurissen B, Jillings S, Laureys S, Sijbers J, Grishin A, Chernikova L, Naumov I, Kornilova L, Wuyts FL, Tomilovskaya E, Kozlovskaya I

Abstract
The present study reports alterations of task-based functional brain connectivity in a group of 11 cosmonauts after a long-duration spaceflight, compared to a healthy control group not involved in the space program. To elicit the postural and locomotor sensorimotor mechanisms that are usually most significantly impaired when space travelers return to Earth, a plantar stimulation paradigm was used in a block design fMRI study. The motor control system activated by the plantar stimulation involved the pre-central and post-central gyri, SMA, SII/operculum, and, to a lesser degree, the insular cortex and cerebellum. While no post-flight alterations were observed in terms of activation, the network-based statistics approach revealed task-specific functional connectivity modifications within a broader set of regions involving the activation sites along with other parts of the sensorimotor neural network and the visual, proprioceptive, and vestibular systems. The most notable findings included a post-flight increase in the stimulation-specific connectivity of the right posterior supramarginal gyrus with the rest of the brain; a strengthening of connections between the left and right insulae; decreased connectivity of the vestibular nuclei, right inferior parietal cortex (BA40) and cerebellum with areas associated with motor, visual, vestibular, and proprioception functions; and decreased coupling of the cerebellum with the visual cortex and the right inferior parietal cortex. The severity of space motion sickness symptoms was found to correlate with a post- to pre-flight difference in connectivity between the right supramarginal gyrus and the left anterior insula. Due to the complex nature and rapid dynamics of adaptation to gravity alterations, the post-flight findings might be attributed to both the long-term microgravity exposure and to the readaptation to Earth's gravity that took place between the landing and post-flight MRI session. Nevertheless, the results have implications for the multisensory reweighting and gravitational motor system theories, generating hypotheses to be tested in future research.

PMID: 31333476 [PubMed]

Baseline Functional Connectivity Features of Neural Network Nodes Can Predict Improvement After Sound Therapy Through Adjusted Narrow Band Noise in Tinnitus Patients.

Thu, 07/25/2019 - 15:37
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Baseline Functional Connectivity Features of Neural Network Nodes Can Predict Improvement After Sound Therapy Through Adjusted Narrow Band Noise in Tinnitus Patients.

Front Neurosci. 2019;13:614

Authors: Han L, Na Z, Chunli L, Yuchen C, Pengfei Z, Hao W, Xu C, Peng Z, Zheng W, Zhenghan Y, Shusheng G, Zhenchang W

Abstract
Previous resting-state functional magnetic resonance imaging (fMRI) studies have shown neural connectivity alterations after the treatment of tinnitus. We aim to study the value of the baseline functional connectivity features of neural network nodes to predict outcomes of sound therapy through adjusted narrow band noise. The fMRI data of 27 untreated tinnitus patients and 27 matched healthy controls were analyzed. We calculated the graph-theoretical metric degree centrality (DC) to characterize the functional connectivity of the neural network nodes. Therapeutic outcomes are determined by the changes in the Tinnitus Handicap Inventory (THI) score after a 12-week intervention. The connectivity of 10 brain nodes in tinnitus patients was significantly increased at baseline. The functional connectivity of right insula, inferior parietal lobule (IPL), bilateral thalami, and left middle temporal gyrus was significantly modified with the sound therapy, and such changes correlated with THI changes in tinnitus patients. Receiver operating characteristic curve analyses revealed that the measurements from the five brain regions were effective at classifying improvement after therapy. After age, gender, and education correction, the adjusted area under the curve (AUC) values for the bilateral thalami were the highest (left, 0.745; right, 0.708). Our study further supported the involvement of the fronto-parietal-cingulate network in tinnitus and found that the connectivity of the thalamus at baseline is an object neuroimaging-based indicator to predict clinical outcome of sound therapy through adjusted narrow band noise.

PMID: 31333394 [PubMed]

Graph theory analysis of resting-state functional magnetic resonance imaging in essential tremor.

Thu, 07/25/2019 - 15:37
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Graph theory analysis of resting-state functional magnetic resonance imaging in essential tremor.

Hum Brain Mapp. 2019 Jul 22;:

Authors: Benito-León J, Sanz-Morales E, Melero H, Louis ED, Romero JP, Rocon E, Malpica N

Abstract
Essential tremor (ET) is a neurological disease with both motor and nonmotor manifestations; however, little is known about its underlying brain basis. Furthermore, the overall organization of the brain network in ET remains largely unexplored. We investigated the topological properties of brain functional network, derived from resting-state functional magnetic resonance imaging (MRI) data, in 23 ET patients versus 23 healthy controls. Graph theory analysis was used to assess the functional network organization. At the global level, the functional network of ET patients was characterized by lower small-worldness values than healthy controls-less clustered functionality of the brain. At the regional level, compared with the healthy controls, ET patients showed significantly higher values of global efficiency, cost and degree, and a shorter average path length in the left inferior frontal gyrus (pars opercularis), right inferior temporal gyrus (posterior division and temporo-occipital part), right inferior lateral occipital cortex, left paracingulate, bilateral precuneus bilaterally, left lingual gyrus, right hippocampus, left amygdala, nucleus accumbens bilaterally, and left middle temporal gyrus (posterior part). In addition, ET patients showed significant higher local efficiency and clustering coefficient values in frontal medial cortex bilaterally, subcallosal cortex, posterior cingulate cortex, parahippocampal gyri bilaterally (posterior division), right lingual gyrus, right cerebellar flocculus, right postcentral gyrus, right inferior semilunar lobule of cerebellum and culmen of vermis. Finally, the right intracalcarine cortex and the left orbitofrontal cortex showed a shorter average path length in ET patients, while the left frontal operculum and the right planum polare showed a higher betweenness centrality in ET patients. In conclusion, the efficiency of the overall brain functional network in ET is disrupted. Further, our results support the concept that ET is a disorder that disrupts widespread brain regions, including those outside of the brain regions responsible for tremor.

PMID: 31332912 [PubMed - as supplied by publisher]

A multivariate neuroimaging biomarker of individual outcome to transcranial magnetic stimulation in depression.

Thu, 07/25/2019 - 15:37
Related Articles

A multivariate neuroimaging biomarker of individual outcome to transcranial magnetic stimulation in depression.

Hum Brain Mapp. 2019 Jul 22;:

Authors: Cash RFH, Cocchi L, Anderson R, Rogachov A, Kucyi A, Barnett AJ, Zalesky A, Fitzgerald PB

Abstract
The neurobiology of major depressive disorder (MDD) remains incompletely understood, and many individuals fail to respond to standard treatments. Repetitive transcranial magnetic stimulation (rTMS) of the dorsolateral prefrontal cortex (DLPFC) has emerged as a promising antidepressant therapy. However, the heterogeneity of response underscores a pressing need for biomarkers of treatment outcome. We acquired resting state functional magnetic resonance imaging (rsfMRI) data in 47 MDD individuals prior to 5-8 weeks of rTMS treatment targeted using the F3 beam approach and in 29 healthy comparison subjects. The caudate, prefrontal cortex, and thalamus showed significantly lower blood oxygenation level-dependent (BOLD) signal power in MDD individuals at baseline. Critically, individuals who responded best to treatment were associated with lower pre-treatment BOLD power in these regions. Additionally, functional connectivity (FC) in the default mode and affective networks was associated with treatment response. We leveraged these findings to train support vector machines (SVMs) to predict individual treatment responses, based on learned patterns of baseline FC, BOLD signal power and clinical features. Treatment response (responder vs. nonresponder) was predicted with 85-95% accuracy. Reduction in symptoms was predicted to within a mean error of ±16% (r = .68, p < .001). These preliminary findings suggest that therapeutic outcome to DLPFC-rTMS could be predicted at a clinically meaningful level using only a small number of core neurobiological features of MDD, warranting prospective testing to ascertain generalizability. This provides a novel, transparent and physiologically plausible multivariate approach for classification of individual response to what has become the most commonly employed rTMS treatment worldwide. This study utilizes data from a larger clinical study (Australian New Zealand Clinical Trials Registry: Investigating Predictors of Response to Transcranial Magnetic Stimulation for the Treatment of Depression; ACTRN12610001071011; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=336262).

PMID: 31332903 [PubMed - as supplied by publisher]

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