New resting-state fMRI related studies at PubMed

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Longitudinal decreases in suicidal ideation are associated with increases in salience network coherence in depressed adolescents.

Fri, 11/16/2018 - 12:20

Longitudinal decreases in suicidal ideation are associated with increases in salience network coherence in depressed adolescents.

J Affect Disord. 2018 Nov 03;245:545-552

Authors: Schwartz J, Ordaz SJ, Ho TC, Gotlib IH

Abstract
BACKGROUND: Suicidal ideation (SI) is an important predictor of suicide attempt, yet SI is difficult to predict. Given that SI begins in adolescence when brain networks are maturing, it is important to understand associations between network functioning and changes in severity of SI.
METHODS: Thirty-three depressed adolescents were administered the Columbia-Suicide Severity Rating Scale to assess SI and completed resting-state fMRI at baseline (T1) and 6 months later (T2). We computed coherence in the executive control (ECN), default mode (DMN), salience (SN), and non-relevant noise networks and then examined the association between changes in brain network coherence and changes in SI severity from T1 to T2.
RESULTS: A greater reduction in severity of SI was associated with a stronger increase in SN coherence from T1 to T2. There were no associations between the other networks and SI.
LIMITATIONS: We cannot generalize our findings to more psychiatrically diverse samples. More time-points are necessary to understand the trajectory of SI and SN coherence change.
CONCLUSIONS: Our finding that reductions in SI are associated with increases in SN coherence extends previous cross-sectional results documenting a negative association between SI severity and SN coherence. The SN is involved in coordinating activation of ECN and DMN in response to salient information. Given this regulatory role of the SN, the association between SN coherence and SI suggests that adolescents with reduced SN coherence might more easily engage in harmful thoughts. Thus, the SN may be particularly relevant as a target for treatment applications in depressed adolescents.

PMID: 30439679 [PubMed - as supplied by publisher]

Image-guided phenotyping of ovariectomized mice: altered functional connectivity, cognition, myelination, and dopaminergic functionality.

Fri, 11/16/2018 - 12:20

Image-guided phenotyping of ovariectomized mice: altered functional connectivity, cognition, myelination, and dopaminergic functionality.

Neurobiol Aging. 2018 Oct 17;74:77-89

Authors: Anckaerts C, van Gastel J, Leysen V, Hinz R, Azmi A, Simoens P, Shah D, Kara F, Langbeen A, Bols P, Laloux C, Prevot V, Verhoye M, Maudsley S, Van der Linden A

Abstract
A large proportion of the population suffers from endocrine disruption, e.g., menopausal women, which might result in accelerated aging and a higher risk for developing cognitive disorders. Therefore, it is crucial to fully understand the impact of such disruptions on the brain to identify potential therapeutic strategies. Here, we show using resting-state functional magnetic resonance imaging that ovariectomy and consequent hypothalamus-pituitary-gonadal disruption result in the selective dysconnectivity of 2 discrete brain regions in mice. This effect coincided with cognitive deficits and an underlying pathological molecular phenotype involving an imbalance of neurodevelopmental/neurodegenerative signaling. Furthermore, this quantitative mass spectrometry proteomics-based analysis of molecular signaling patterns further identified a strong involvement of altered dopaminergic functionality (e.g., DAT and predicted upstream regulators DRD3, NR4A2), reproductive signaling (e.g., Srd5a2), rotatin expression (rttn), cellular aging (e.g., Rxfp3, Git2), myelination, and axogenesis (e.g., Nefl, Mag). With this, we have provided an improved understanding of the impact of hypothalamus-pituitary-gonadal dysfunction and highlighted the potential of using a highly translational magnetic resonance imaging technique for monitoring these effects on the brain.

PMID: 30439596 [PubMed - as supplied by publisher]

Altered baseline activity and connectivity associated with cognitive impairment following acute cerebellar infarction: A resting-state fMRI study.

Fri, 11/16/2018 - 12:20

Altered baseline activity and connectivity associated with cognitive impairment following acute cerebellar infarction: A resting-state fMRI study.

Neurosci Lett. 2018 Nov 12;:

Authors: Fan L, Hu J, Ma W, Wang D, Yao Q, Shi J

Abstract
The aims of this study were to investigated the changes of brain function and cognitive function in patients with acute posterior cerebellar infarction using the functional magnetic resonance imaging (fMRI) tecniques: fractional amplitude of low-frequency fluctuation (fALFF) and functional connectivity (FC). Forty acute cerebellar infarction patients and 40 healthy controls were included. The differences of fALFF were compared. The regions showed significant differences were set as regions of interest (ROIs), and then the FC values between ROIs and the whole brain were analysed. Pearson correlation analysis was used to understand the correlation between FC values and cognitive function scores. The results showed significant group differences in fALFF values in the four brain regions, including the right frontal lobe, left hippocampus, right cingulate gyrus and cerebellum posterior lobe. Pearson correlation analysis suggested that abnormal alterations in the left hippocampus and right cingulate gyrus may play a core role in the cognitive impairment associated with cerebellar infarction. The changes of fALFF and FC values in related brain area from cerebellar stroke complement and enrich our understanding of cerebellar involvement in cognition involved in cognitive performance.

PMID: 30439397 [PubMed - as supplied by publisher]

Beware detrending: Optimal preprocessing pipeline for low-frequency fluctuation analysis.

Fri, 11/16/2018 - 12:20
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Beware detrending: Optimal preprocessing pipeline for low-frequency fluctuation analysis.

Hum Brain Mapp. 2018 Nov 15;:

Authors: Woletz M, Hoffmann A, Tik M, Sladky R, Lanzenberger R, Robinson S, Windischberger C

Abstract
Resting-state functional magnetic resonance imaging (rs-fMRI) offers the possibility to assess brain function independent of explicit tasks and individual performance. This absence of explicit stimuli in rs-fMRI makes analyses more susceptible to nonneural signal fluctuations than task-based fMRI. Data preprocessing is a critical procedure to minimise contamination by artefacts related to motion and physiology. We herein investigate the effects of different preprocessing strategies on the amplitude of low-frequency fluctuations (ALFFs) and its fractional counterpart, fractional ALFF (fALFF). Sixteen artefact reduction schemes based on nuisance regression are applied to data from 82 subjects acquired at 1.5 T, 30 subjects at 3 T, and 23 subjects at 7 T, respectively. In addition, we examine test-retest variance and effects of bias correction. In total, 569 data sets are included in this study. Our results show that full artefact reduction reduced test-retest variance by up to 50%. Polynomial detrending of rs-fMRI data has a positive effect on group-level t-values for ALFF but, importantly, a negative effect for fALFF. We show that the normalisation process intrinsic to fALFF calculation causes the observed reduction and introduce a novel measure for low-frequency fluctuations denoted as high-frequency ALFF (hfALFF). We demonstrate that hfALFF values are not affected by the negative detrending effects seen in fALFF data. Still, highest grey matter (GM) group-level t-values were obtained for fALFF data without detrending, even when compared to an exploratory detrending approach based on autocorrelation measures. From our results, we recommend the use of full nuisance regression including polynomial detrending in ALFF data, but to refrain from using polynomial detrending in fALFF data. Such optimised preprocessing increases GM group-level t-values by up to 60%.

PMID: 30430691 [PubMed - as supplied by publisher]

Transcranial direct current stimulation reconstructs diminished thalamocortical connectivity during prolonged resting wakefulness: a resting-state fMRI pilot study.

Fri, 11/16/2018 - 12:20
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Transcranial direct current stimulation reconstructs diminished thalamocortical connectivity during prolonged resting wakefulness: a resting-state fMRI pilot study.

Brain Imaging Behav. 2018 Nov 14;:

Authors: Dalong G, Jiyuan L, Ying Z, Lei Z, Yanhong H, Yongcong S

Abstract
Reductions in the alertness and information processing capacity of individuals due to sleep deprivation (SD) were previously thought to be related to dysfunction of the thalamocortical network. Previous studies have shown that transcranial direct current stimulation (tDCS) can restore vigilance and information processing after SD. However, the underlying neural mechanisms of this phenomenon remain unclear. The purpose of this study was to investigate the neurocognitive mechanisms of tDCS following SD, by comparing changes in the brain network, especially the thalamocortical network, after tDCS and sham stimulation following 24 h of SD. Sixteen healthy volunteers were tested in a sham-controlled, randomized crossover design experiment. Resting-state functional magnetic resonance imaging was conducted during resting wakefulness and again after either active tDCS or sham stimulation to the right dorsolateral prefrontal cortex (1.0 mA, 20 min) immediately following 24 h of SD. Seed-based correlations and graph theory analysis were used to determine functional connectivity within the brain thalamocortical network. When tDCS was used, the functional connectivity of the thalamus with the temporal lobe and left caudate was higher than that when the sham stimulation was used. Analysis using graph theory showed that compared with sham stimulation, tDCS administration was associated with a significant improvement in not only the number of connections but also the global efficiency of the thalamus itself. Our study reveals a modulation of the activity of the intrinsic thalamus networks after tDCS. The effects may help explain earlier reports of improvements in the cognitive performance after anodal-tDCS.

PMID: 30430411 [PubMed - as supplied by publisher]

Homotopic Connectivity in Early Pontine Infarction Predicts Late Motor Recovery.

Fri, 11/16/2018 - 12:20
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Homotopic Connectivity in Early Pontine Infarction Predicts Late Motor Recovery.

Front Neurol. 2018;9:907

Authors: Shan Y, Wang YS, Zhang M, Rong DD, Zhao ZL, Cao YX, Wang PP, Deng ZZ, Ma QF, Li KC, Zuo XN, Lu J

Abstract
Connectivity-based methods are essential to explore brain reorganization after a stroke and to provide meaningful predictors for late motor recovery. We aim to investigate the homotopic connectivity alterations during a 180-day follow-up of patients with pontine infarction to find an early biomarker for late motor recovery prediction. In our study, resting-state functional MRI was performed in 15 patients (11 males, 4 females, age: 57.87 ± 6.50) with unilateral pontine infarction and impaired motor function during a period of 6 months (7, 14, 30, 90, and 180 days after stroke onset). Clinical neurological assessments were performed using the Fugl-Meyer scale (FM).15 matched healthy volunteers were also recruited. Whole-brain functional homotopy in each individual scan was measured by voxel-mirrored homotopic connectivity (VMHC) values. Group-level analysis was performed between stroke patients and normal controls. A Pearson correlation was performed to evaluate correlations between early VMHC and the subsequent 4 visits for behavioral measures during day 14 to day 180. We found in early stroke (within 7 days after onset), decreased VMHC was detected in the bilateral precentral and postcentral gyrus and precuneus/posterior cingulate cortex (PCC), while increased VMHC was found in the hippocampus/amygdala and frontal pole (P < 0.01). During follow-up, VMHC in the precentral and postcentral gyrus increased to the normal level from day 90, while VMHC in the precuneus/PCC presented decreased intensity during all time points (P < 0.05). The hippocampus/amygdala and frontal pole presented a higher level of VMHC during all time points (P < 0.05). Negative correlation was found between early VMHC in the hippocampus/amygdala with FM on day 14 (r = -0.59, p = 0.021), day 30 (r = -0.643, p = 0.01), day 90 (r = -0.693, p = 0.004), and day 180 (r = -0.668, p = 0.007). Furthermore, early VMHC in the frontal pole was negatively correlated with FM scores on day 30 (r = -0.662, p = 0.013), day 90 (r = -0.606, p = 0.017), and day 180 (r = -0.552, p = 0.033). Our study demonstrated the potential utility of early homotopic connectivity for prediction of late motor recovery in pontine infarction.

PMID: 30429821 [PubMed]

Primary Disruption of the Memory-Related Subsystems of the Default Mode Network in Alzheimer's Disease: Resting-State Functional Connectivity MRI Study.

Fri, 11/16/2018 - 12:20
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Primary Disruption of the Memory-Related Subsystems of the Default Mode Network in Alzheimer's Disease: Resting-State Functional Connectivity MRI Study.

Front Aging Neurosci. 2018;10:344

Authors: Qi H, Liu H, Hu H, He H, Zhao X

Abstract
Background: Recent studies have indicated that the default mode network (DMN) comprises at least three subsystems: The medial temporal lobe (MTL) and dorsal medial prefrontal cortex (DMPFC) subsystems and a core comprising the anterior MPFC (aMPFC) and posterior cingulate cortex (PCC). Additionally, the disruption of the DMN is related to Alzheimer's disease (AD). However, little is known regarding the changes in these subsystems in AD, a progressive disease characterized by memory impairment. Here, we performed a resting-state functional connectivity (FC) analysis to test our hypothesis that the memory-related MTL subsystem was predominantly disrupted in AD. Method: To reveal specific subsystem changes, we calculated the strength and number of FCS in the DMN intra- and inter-subsystems across individuals and compared the FC of the two groups. To further examine which pairs of brain regional functional connections contributed to the subsystem alterations, correlation coefficients between any two brain regions in the DMN were compared across groups. Additionally, to identify which regions made the strongest contributions to the subsystem changes, we calculated the regional FC strength (FCS), which was compared across groups. Results: For the intra-subsystem, decreased FC number and strength occurred in the MTL subsystem of AD patients but not in the DMPFC subsystem or core. For the inter-subsystems, the AD group showed decreased FCS and number between the MTL subsystem and PCC and a decreased number between the PCC and DMPFC subsystem. Decreased inter-regional FCS were found within the MTL subsystem in AD patients relative to controls: The posterior inferior parietal lobule (pIPL) showed decreased FC with the hippocampal formation (HF), parahippocampal cortex (PHC) and ventral MPFC (vMPFC). Decreased inter-regional FCS of the inter-subsystems were also found in AD patients: The HF and/or PHC showed decreased FC with dMPFC and TPJ, located in the DMPFC subsystem, and with PCC. AD patients also showed decreased FC between the PCC and TLC of the dMPFC subsystem. Furthermore, the HF and PHC in the MTL subsystem showed decreased regional FCS. Conclusion: Decreased intrinsic FC was mainly associated with the MTL subsystem of the AD group, suggesting that the MTL subsystem is predominantly disrupted.

PMID: 30429784 [PubMed]

Rehabilitation in chronic spatial neglect strengthens resting state connectivity.

Thu, 11/15/2018 - 11:20

Rehabilitation in chronic spatial neglect strengthens resting state connectivity.

Acta Neurol Scand. 2018 Nov 14;:

Authors: Wåhlin A, Fordell H, Ekman U, Lenfeldt N, Malm J

Abstract
OBJECTIVES: Rehabilitation of patients with chronic visuospatial neglect is underexplored, and little is known about neural mechanisms that can be exploited to promote recovery. In this study, we present data on resting state functional connectivity within the dorsal attention network (DAN) in chronic neglect patients as they underwent training in a virtual reality (VR) environment that improved left-side awareness.
METHODS: The study included 13 patients with visuospatial neglect persisting more than six months after a right-sided stroke. The patients underwent resting state functional magnetic resonance imaging (fMRI). Scans were collected at baseline and after five weeks of intense training. We specifically examined resting state functional connectivity within the DAN. In addition, using spatial concordance correlation, we compared changes in the spatial topology of the DAN with that of other networks.
RESULTS: We found a longitudinal increase in interhemispheric functional connectivity between the right frontal eye field and the left intraparietal sulcus following training (pre: 0.33±0.17 [mean±SD]; post 0.45±0.13; P=0.004). The spatial concordance analyses indicated that training influenced the DAN connectivity more than any of the other networks.
CONCLUSION: Intense VR training that improved left sided awareness in chronic stroke patients also increased sporadic interhemispheric functional connectivity within the DAN. Specifically, a region responsible for saccadic eye movement to the left became more integrated with the left posterior parietal cortex. These results highlight a mechanism that should be exploited in the training of patients with chronic visuospatial neglect. This article is protected by copyright. All rights reserved.

PMID: 30427058 [PubMed - as supplied by publisher]

Altered functional connectivity strength in informant-reported subjective cognitive decline: A resting-state functional magnetic resonance imaging study.

Thu, 11/15/2018 - 11:20
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Altered functional connectivity strength in informant-reported subjective cognitive decline: A resting-state functional magnetic resonance imaging study.

Alzheimers Dement (Amst). 2018;10:688-697

Authors: Dong C, Liu T, Wen W, Kochan NA, Jiang J, Li Q, Liu H, Niu H, Zhang W, Wang Y, Brodaty H, Sachdev PS

Abstract
Introduction: Informant-reported subjective cognitive decline (iSCD) has been associated with a higher risk of conversion to dementia, but the findings of whole brain functional connectivity strength (FCS) changes in iSCD are limited.
Methods: The sample comprised 39 participants with iSCD and 39 age- and sex- matched healthy controls. The global absolute (aFCS) and relative functional connectivity strengths were estimated using weighted degree centrality and the z-scores of the weighted degree centrality respectively. FreeSurfer was used for measuring cortical thickness.
Results: The aFCS was lower in iSCD primarily in left medial superior frontal, left precuneus, left parietal, right cuneus, and bilateral calcarine; while relative functional connectivity strength was higher in posterior cingulate cortex/precuneus compared with healthy controls. No significant differences in cortical thickness were observed.
Discussion: There are detectable changes of FCS in iSCD, with the precuneus possibly playing a compensatory role. FCS could therefore have a potential role to serve as one of the earliest neuroimaging markers of neurodegenerative disease.

PMID: 30426065 [PubMed]

Functional and Structural Plasticity of Brain in Elite Karate Athletes.

Thu, 11/15/2018 - 11:20
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Functional and Structural Plasticity of Brain in Elite Karate Athletes.

J Healthc Eng. 2018;2018:8310975

Authors: Duru AD, Balcioglu TH

Abstract
The structural and functional neural differences between the elite karate athletes and control group have been investigated in the concept of this study. 13 elite karate athletes and age-gender matched 13 volunteers who have not performed regular exercises participated in the study. Magnetic resonance imaging was used to acquire the anatomical and functional maps. T1-weighted anatomical images were segmented to form gray and white matter images. Voxel-based morphometry is used to elucidate the differences between the groups. Moreover, resting state functional measurements had been done, and group independent component analysis was implemented in order to exhibit the resting state networks. Then, second-level general linear models were used to compute the statistical maps. It has been revealed that increased GM volume values of inferior/superior temporal, occipital, premotor cortex, and temporal pole superior were present for the elite athletes. Additionally, WM values were found to be increased in caudate nucleus, hypothalamus, and mammilary region for the elite karate players. Similarly, for the elite karate players, the brain regions involved in the movement planning and visual perception are found to have higher connectivity values. The differences in these findings can be thought to be originated from the advances gained through the several years of training which is required to be an elite karate athlete.

PMID: 30425820 [PubMed - in process]

Mutual Information Better Quantifies Brain Network Architecture in Children with Epilepsy.

Thu, 11/15/2018 - 11:20
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Mutual Information Better Quantifies Brain Network Architecture in Children with Epilepsy.

Comput Math Methods Med. 2018;2018:6142898

Authors: Zhang W, Muravina V, Azencott R, Chu ZD, Paldino MJ

Abstract
Purpose: Metrics of the brain network architecture derived from resting-state fMRI have been shown to provide physiologically meaningful markers of IQ in children with epilepsy. However, traditional measures of functional connectivity (FC), specifically the Pearson correlation, assume a dominant linear relationship between BOLD time courses; this assumption may not be valid. Mutual information is an alternative measure of FC which has shown promise in the study of complex networks due to its ability to flexibly capture association of diverse forms. We aimed to compare network metrics derived from mutual information-defined FC to those derived from traditional correlation in terms of their capacity to predict patient-level IQ.
Materials and Methods: Patients were retrospectively identified with the following: (1) focal epilepsy; (2) resting-state fMRI; and (3) full-scale IQ by a neuropsychologist. Brain network nodes were defined by anatomic parcellation. Parcellation was performed at the size threshold of 350 mm2, resulting in networks containing 780 nodes. Whole-brain, weighted graphs were then constructed according to the pairwise connectivity between nodes. In the traditional condition, edges (connections) between each pair of nodes were defined as the absolute value of the Pearson correlation coefficient between their BOLD time courses. In the mutual information condition, edges were defined as the mutual information between time courses. The following metrics were then calculated for each weighted graph: clustering coefficient, modularity, characteristic path length, and global efficiency. A machine learning algorithm was used to predict the IQ of each individual based on their network metrics. Prediction accuracy was assessed as the fractional variation explained for each condition.
Results: Twenty-four patients met the inclusion criteria (age: 8-18 years). All brain networks demonstrated expected small-world properties. Network metrics derived from mutual information-defined FC significantly outperformed the use of the Pearson correlation. Specifically, fractional variation explained was 49% (95% CI: 46%, 51%) for the mutual information method; the Pearson correlation demonstrated a variation of 17% (95% CI: 13%, 19%).
Conclusion: Mutual information-defined functional connectivity captures physiologically relevant features of the brain network better than correlation.
Clinical Relevance: Optimizing the capacity to predict cognitive phenotypes at the patient level is a necessary step toward the clinical utility of network-based biomarkers.

PMID: 30425750 [PubMed - in process]

Pre-treatment Resting-State Functional MR Imaging Predicts the Long-Term Clinical Outcome After Short-Term Paroxtine Treatment in Post-traumatic Stress Disorder.

Thu, 11/15/2018 - 11:20
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Pre-treatment Resting-State Functional MR Imaging Predicts the Long-Term Clinical Outcome After Short-Term Paroxtine Treatment in Post-traumatic Stress Disorder.

Front Psychiatry. 2018;9:532

Authors: Yuan M, Qiu C, Meng Y, Ren Z, Yuan C, Li Y, Gao M, Lui S, Zhu H, Gong Q, Zhang W

Abstract
Background: The chronic phase of post-traumatic stress disorder (PTSD) and the limited effectiveness of existing treatments creates the need for the development of potential biomarkers to predict response to antidepressant medication at an early stage. However, findings at present focus on acute therapeutic effect without following-up the long-term clinical outcome of PTSD. So far, studies predicting the long-term clinical outcome of short-term treatment based on both pre-treatment and post-treatment functional MRI in PTSD remains limited. Methods: Twenty-two PTSD patients were scanned using resting-state functional MRI (rs-fMRI) before and after 12 weeks of treatment with paroxetine. Twenty patients were followed up using the same psychopathological assessments 2 years after they underwent the second MRI scan. Based on clinical outcome, the follow-up patients were divided into those with remitted PTSD or persistent PTSD. Amplitude of low-frequency fluctuations (ALFF) and degree centrality (DC) derived from pre-treatment and post-treatment rs-fMRI were used as classification features in a support vector machine (SVM) classifier. Results: Prediction of long-term clinical outcome by combined ALFF and DC features derived from pre-treatment rs-fMRI yielded an accuracy rate of 72.5% (p < 0.005). The most informative voxels for outcome prediction were mainly located in the precuneus, superior temporal area, insula, dorsal medial prefrontal cortex, frontal orbital cortex, supplementary motor area, lingual gyrus, and cerebellum. Long-term outcome could not be successfully classified by post-treatment imaging features with accuracy rates <50%. Conclusions: Combined information from ALFF and DC from rs-fMRI data before treatment could predict the long-term clinical outcome of PTSD, which is critical for defining potential biomarkers to customize PTSD treatment and improve the prognosis.

PMID: 30425661 [PubMed]

Non-invasive Assessment of Systolic and Diastolic Cardiac Function During Rest and Stress Conditions Using an Integrated Image-Modeling Approach.

Thu, 11/15/2018 - 11:20
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Non-invasive Assessment of Systolic and Diastolic Cardiac Function During Rest and Stress Conditions Using an Integrated Image-Modeling Approach.

Front Physiol. 2018;9:1515

Authors: Casas B, Viola F, Cedersund G, Bolger AF, Karlsson M, Carlhäll CJ, Ebbers T

Abstract
Background: The possibility of non-invasively assessing load-independent parameters characterizing cardiac function is of high clinical value. Typically, these parameters are assessed during resting conditions. However, for diagnostic purposes, the parameter behavior across a physiologically relevant range of heart rate and loads is more relevant than the isolated measurements performed at rest. This study sought to evaluate changes in non-invasive estimations of load-independent parameters of left-ventricular contraction and relaxation patterns at rest and during dobutamine stress. Methods: We applied a previously developed approach that combines non-invasive measurements with a physiologically-based, reduced-order model of the cardiovascular system to provide subject-specific estimates of parameters characterizing left ventricular function. In this model, the contractile state of the heart at each time point along the cardiac cycle is modeled using a time-varying elastance curve. Non-invasive data, including four-dimensional magnetic resonance imaging (4D Flow MRI) measurements, were acquired in nine subjects without a known heart disease at rest and during dobutamine stress. For each of the study subjects, we constructed two personalized models corresponding to the resting and the stress state. Results: Applying the modeling framework, we identified significant increases in the left ventricular contraction rate constant [from 1.5 ± 0.3 to 2 ± 0.5 (p = 0.038)] and relaxation constant [from 37.2 ± 6.9 to 46.1 ± 12 (p = 0.028)]. In addition, we found a significant decrease in the elastance diastolic time constant from 0.4 ± 0.04 s to 0.3 ± 0.03 s (p = 0.008). Conclusions: The integrated image-modeling approach allows the assessment of cardiovascular function given as model-based parameters. The agreement between the estimated parameter values and previously reported effects of dobutamine demonstrates the potential of the approach to assess advanced metrics of pathophysiology that are otherwise difficult to obtain non-invasively in clinical practice.

PMID: 30425650 [PubMed]

Data Driven Classification Using fMRI Network Measures: Application to Schizophrenia.

Thu, 11/15/2018 - 11:20
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Data Driven Classification Using fMRI Network Measures: Application to Schizophrenia.

Front Neuroinform. 2018;12:71

Authors: Moghimi P, Lim KO, Netoff TI

Abstract
Using classification to identify biomarkers for various brain disorders has become a common practice among the functional MR imaging community. Typical classification pipeline includes taking the time series, extracting features from them, and using them to classify a set of patients and healthy controls. The most informative features are then presented as novel biomarkers. In this paper, we compared the results of single and double cross validation schemes on a cohort of 170 subjects with schizophrenia and healthy control subjects. We used graph theoretic measures as our features, comparing the use of functional and anatomical atlases to define nodes and the effect of prewhitening to remove autocorrelation trends. We found that double cross validation resulted in a 20% decrease in classification performance compared to single cross validation. The anatomical atlas resulted in higher classification results. Prewhitening resulted in a 10% boost in classification performance. Overall, a classification performance of 80% was obtained with a double-cross validation scheme using prewhitened time series and an anatomical brain atlas. However, reproducibility of classification within subjects across scans was surprisingly low and comparable to across subject classification rates, indicating that subject state during the short scan significantly influences the estimated features and classification performance.

PMID: 30425631 [PubMed]

Abnormal intrinsic brain activities in stable patients with COPD: a resting-state functional MRI study.

Thu, 11/15/2018 - 11:20
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Abnormal intrinsic brain activities in stable patients with COPD: a resting-state functional MRI study.

Neuropsychiatr Dis Treat. 2018;14:2763-2772

Authors: Wang W, Li H, Peng D, Luo J, Xin H, Yu H, Yu J

Abstract
Objective: The majority of previous neuroimaging studies have reported both structural and functional changes in COPD, whereas the intrinsic low-frequency oscillations changes and the relationship between the abnormal brain regions and the clinical performances remain unknown. The present study was conducted with the aim of evaluating the intrinsic brain activity in COPD patients using the amplitude of low-frequency fluctuation (ALFF) method.
Methods: All participants, including 19 stable patients with COPD and 20 normal controls (NCs) matched in age, sex, and education, underwent resting-state functional MRI scans and performed cognitive function tests and respiratory functions tests. The local spontaneous brain activity was examined using the voxel-wise ALFF. Pearson's correlation analysis was used to investigate the relationships between the brain regions with altered ALFF signal values and the clinical features in COPD patients.
Results: Compared with the NCs, COPD patients showed significantly lower cognitive function scores. Also, lower ALFF areas in the cluster of the posterior cingulate cortex (PCC) and precuneus, as well as a higher ALFF area in the brainstem were also found in COPD patients. The mean ALFF values in the PCC, precuneus, and brainstem showed high sensitivity and specificity in operating characteristic curves analysis, which might have the ability to distinguish COPD from NCs. Meanwhile, the mean signal values of the lower ALFF cluster displayed significant positive correlations with FEV1/FVC proportion and significant negative correlation with PaCO2; the higher ALFF cluster showed significant positive correlation with FEV1 proportion in COPD.
Conclusion: According to the results of the present study, the COPD patients showed abnormal intrinsic brain activities in the precuneus, PCC, and brainstem, which might provide useful information to better understand the underlying pathophysiology of cognitive impairment.

PMID: 30425494 [PubMed]

Denoising of 3D magnetic resonance images with multi-channel residual learning of convolutional neural network.

Thu, 11/15/2018 - 11:20
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Denoising of 3D magnetic resonance images with multi-channel residual learning of convolutional neural network.

Jpn J Radiol. 2018 Sep;36(9):566-574

Authors: Jiang D, Dou W, Vosters L, Xu X, Sun Y, Tan T

Abstract
PURPOSE: To test if the proposed deep learning based denoising method denoising convolutional neural networks (DnCNN) with residual learning and multi-channel strategy can denoise three dimensional MR images with Rician noise robustly.
MATERIALS AND METHODS: Multi-channel DnCNN (MCDnCNN) method with two training strategies was developed to denoise MR images with and without a specific noise level, respectively. To evaluate our method, three datasets from two public data sources of IXI dataset and Brainweb, including T1 weighted MR images acquired at 1.5 and 3 T as well as MR images simulated with a widely used MR simulator, were randomly selected and artificially added with different noise levels ranging from 1 to 15%. For comparison, four other state-of-the-art denoising methods were also tested using these datasets.
RESULTS: In terms of the highest peak-signal-to-noise-ratio and global of structure similarity index, our proposed MCDnCNN model for a specific noise level showed the most robust denoising performance in all three datasets. Next to that, our general noise-applicable model also performed better than the rest four methods in two datasets. Furthermore, our training model showed good general applicability.
CONCLUSION: Our proposed MCDnCNN model has been demonstrated to robustly denoise three dimensional MR images with Rician noise.

PMID: 29982919 [PubMed - indexed for MEDLINE]

Lithium Monotherapy Associated Longitudinal Effects on Resting State Brain Networks in Clinical Treatment of Bipolar Disorder.

Wed, 11/14/2018 - 16:40
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Lithium Monotherapy Associated Longitudinal Effects on Resting State Brain Networks in Clinical Treatment of Bipolar Disorder.

Bipolar Disord. 2018 Nov 12;:

Authors: Spielberg JM, Matyi MA, Karne H, Anand A

Abstract
OBJECTIVES: Lithium is one of the most effective and specific treatments for bipolar disorder (BP), but the neural mechanisms by which lithium impacts symptoms remain unclear. Past research has been limited by a reliance on cross-sectional designs, which does not allow for identification of within-person changes due to lithium and has not examined communication between brain regions (i.e., networks). In the present study, we prospectively investigated the lithium monotherapy associated effects in vivo on the brain connectome in medication-free BP patients. In particular, we examined the within-person impact of lithium treatment on connectome indices previously linked to mania and depression in bipolar disorder.
METHODS: Thirty-nine medication-free subjects - 26 BP (13 (hypo)manic and 13 depressed) and 13 closely matched health controls (HC) - were included. fMRI data was obtained at 3 timepoints: baseline, after 2 weeks, and after 8 weeks (total of 117 scans: 78 BP and 39 HC scans). BP subjects were clinically treated with lithium for 8 weeks while HC were scanned at the same time points but not treated. Graph theory metrics and repeated measures GLM were used to analyze lithium treatment associated effects.
RESULTS: Consistent with hypotheses, lithium treatment was associated with a normalizing effect on mania-related connectome indices. Furthermore, shifts in both mania- and depression-related connectome indices were proportional to symptom change. Finally, lithium treatment-associated impact on amygdala function differed depending on baseline mood.
CONCLUSIONS: Present findings provide deeper insight into the therapeutic neural mechanisms associated with lithium treatment. This article is protected by copyright. All rights reserved.

PMID: 30421491 [PubMed - as supplied by publisher]

Independent Component Analysis and Graph Theoretical Analysis in Patients with Narcolepsy.

Wed, 11/14/2018 - 16:40
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Independent Component Analysis and Graph Theoretical Analysis in Patients with Narcolepsy.

Neurosci Bull. 2018 Nov 13;:

Authors: Xiao F, Lu C, Zhao D, Zou Q, Xu L, Li J, Zhang J, Han F

Abstract
The present study was aimed to evaluate resting-state functional connectivity and topological properties of brain networks in narcolepsy patients compared with healthy controls. Resting-state fMRI was performed in 26 adult narcolepsy patients and 30 matched healthy controls. MRI data were first analyzed by group independent component analysis, then a graph theoretical method was applied to evaluate the topological properties in the whole brain. Small-world network parameters and nodal topological properties were measured. Altered topological properties in brain areas between groups were selected as region-of-interest seeds, then the functional connectivity among these seeds was compared between groups. Partial correlation analysis was performed to evaluate the relationship between the severity of sleepiness and functional connectivity or topological properties in the narcolepsy patients. Twenty-one independent components out of 48 were obtained. Compared with healthy controls, the narcolepsy patients exhibited significantly decreased functional connectivity within the executive and salience networks, along with increased functional connectivity in the bilateral frontal lobes within the executive network. There were no differences in small-world network properties between patients and controls. The altered brain areas in nodal topological properties between groups were mainly in the inferior frontal cortex, basal ganglia, anterior cingulate, sensory cortex, supplementary motor cortex, and visual cortex. In the partial correlation analysis, nodal topological properties in the putamen, anterior cingulate, and sensory cortex as well as functional connectivity between these regions were correlated with the severity of sleepiness (sleep latency, REM sleep latency, and Epworth sleepiness score) among narcolepsy patients. Altered connectivity within the executive and salience networks was found in narcolepsy patients. Functional connection changes between the left frontal cortex and left caudate nucleus may be one of the parameters describing the severity of narcolepsy. Changes in the nodal topological properties in the left putamen and left posterior cingulate, changes in functional connectivity between the left supplementary motor area and right occipital as well as in functional connectivity between the left anterior cingulate gyrus and bilateral postcentral gyrus can be considered as a specific indicator for evaluating the severity of narcolepsy.

PMID: 30421271 [PubMed - as supplied by publisher]

Functional hierarchy of oculomotor and visual motion subnetworks within the human cortical optokinetic system.

Wed, 11/14/2018 - 16:40
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Functional hierarchy of oculomotor and visual motion subnetworks within the human cortical optokinetic system.

Brain Struct Funct. 2018 Nov 13;:

Authors: Ruehl RM, Hoffstaedter F, Reid A, Eickhoff S, Zu Eulenburg P

Abstract
Optokinetic look nystagmus (look OKN) is known to engage cortical visual motion and oculomotor hubs. Their functional network hierarchy, however, and the role of the cingulate eye field (CEF) and the dorsolateral prefrontal cortex (DLPFC) in particular have not been investigated. We used look OKN in fMRI to identify all cortical visual motion and oculomotor hubs involved. Using these activations as seed regions, we employed hierarchical clustering in two differing resting state conditions from a separate public data set. Robust activations in the CEF highlight its functional role in OKN and involvement in higher order oculomotor control. Deactivation patterns indicate a decreased modulatory involvement of the DLPFC. The hierarchical clustering revealed a changeable organization of the eye fields, hMT, V3A, and V6 depending on the resting state condition, segregating executive from higher order visual subnetworks. Overall, hierarchical clustering seems to allow for a robust delineation of physiological cortical networks.

PMID: 30421037 [PubMed - as supplied by publisher]

Aberrances of Cortex Excitability and Connectivity Underlying Motor Deficit in Acute Stroke.

Wed, 11/14/2018 - 16:40
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Aberrances of Cortex Excitability and Connectivity Underlying Motor Deficit in Acute Stroke.

Neural Plast. 2018;2018:1318093

Authors: Du J, Hu J, Hu J, Xu Q, Zhang Q, Liu L, Ma M, Xu G, Zhang Y, Liu X, Lu G, Zhang Z, Yang F

Abstract
Purpose: This study was aimed at evaluating the motor cortical excitability and connectivity underlying the neural mechanism of motor deficit in acute stroke by the combination of functional magnetic resonance imaging (fMRI) and electrophysiological measures.
Methods: Twenty-five patients with motor deficit after acute ischemic stroke were involved. General linear model and dynamic causal model analyses were applied to fMRI data for detecting motor-related activation and effective connectivity of the motor cortices. Motor cortical excitability was determined as a resting motor threshold (RMT) of motor evoked potential detected by transcranial magnetic stimulation (TMS). fMRI results were correlated with cortical excitability and upper extremity Fugl-Meyer assessment scores, respectively.
Results: Greater fMRI activation likelihood and motor cortical excitability in the ipsilesional primary motor area (M1) region were associated with better motor performance. During hand movements, the inhibitory connectivity from the contralesional to the ipsilesional M1 was correlated with the degree of motor impairment. Furthermore, ipsilesional motor cortex excitability was correlated with an enhancement of promoting connectivity in ipsilesional M1 or a reduction of interhemispheric inhibition in contralesional M1.
Conclusions: The study suggested that a dysfunction of the ipsilesional M1 and abnormal interhemispheric interactions might underlie the motor disability in acute ischemic stroke. Modifying the excitability of the motor cortex and correcting the abnormal motor network connectivity associated with the motor deficit might be the therapeutic target in early neurorehabilitation for stroke patients.

PMID: 30420876 [PubMed - in process]

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