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Alterations of Regional Homogeneity in Parkinson's Disease Patients With Freezing of Gait: A Resting-State fMRI Study.

Tue, 11/05/2019 - 21:13
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Alterations of Regional Homogeneity in Parkinson's Disease Patients With Freezing of Gait: A Resting-State fMRI Study.

Front Aging Neurosci. 2019;11:276

Authors: Liu Y, Li M, Chen H, Wei X, Hu G, Yu S, Ruan X, Zhou J, Pan X, Li Z, Luo Z, Xie Y

Abstract
Objective: The purposes of this study are to investigate the regional homogeneity (ReHo) of spontaneous brain activities in Parkinson's disease (PD) patients with freeze of gait (FOG) and to investigate the neural correlation of movement function through resting-state functional magnetic resonance imaging (RS-fMRI).
Methods: A total of 35 normal controls (NC), 33 PD patients with FOG (FOG+), and 35 PD patients without FOG (FOG-) were enrolled. ReHo was applied to evaluate the regional synchronization of spontaneous brain activities. Analysis of covariance (ANCOVA) was performed on ReHo maps of the three groups, followed by post hoc two-sample t-tests between every two groups. Moreover, the ReHo signals of FOG+ and FOG- were extracted across the whole brain and correlated with movement scores (FOGQ, FOG questionnaire; GFQ, gait and falls questionnaire).
Results: Significant ReHo differences were observed in the left cerebrum. Compared to NC subjects, the ReHo of PD subjects was increased in the left angular gyrus (AG) and decreased in the left rolandic operculum/postcentral gyrus (Rol/PostC), left inferior opercular-frontal cortex, left middle occipital gyrus, and supramarginal gyrus (SMG). Compared to that of FOG-, the ReHo of FOG+ was increased in the left caudate and decreased in the left Rol/PostC. Within the significant regions, the ReHo of FOG+ was negatively correlated with FOGQ in the left SMG/PostC (r = -0.39, p < 0.05). Negative correlations were also observed between ReHo and GFQ/FOGQ (r = -0.36/-0.38, p < 0.05) in the left superior temporal gyrus (STG) of the whole brain analysis based on AAL templates.
Conclusion: The ReHo analysis suggested that the regional signal synchronization of brain activities in FOG+ subjects was most active in the left caudate and most hypoactive in the left Rol/PostC. It also indicated that ReHo in the left caudate and left Rol/PostC was critical for discriminating the three groups. The correlation between ReHo and movement scores (GFQ/FOGQ) in the STG has the potential to differentiate FOG+ from FOG-. This study provided new insight into the understanding of PD with and without FOG.

PMID: 31680931 [PubMed]

Functional Connectivity Patterns and the Role of 5-HTTLPR Polymorphism on Network Architecture in Female Patients With Anorexia Nervosa.

Tue, 11/05/2019 - 21:13
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Functional Connectivity Patterns and the Role of 5-HTTLPR Polymorphism on Network Architecture in Female Patients With Anorexia Nervosa.

Front Neurosci. 2019;13:1056

Authors: Collantoni E, Meneguzzo P, Solmi M, Tenconi E, Manara R, Favaro A

Abstract
Introduction: Recent neuroimaging studies suggest that anorexia nervosa (AN) symptoms emerge from failures in the relationships between spatially distributed networks that support different cognitive, emotional, and somatosensory functions. The 5-HTTLPR genotype has been shown to modulate all these abilities in AN, as well as the connectivity patterns between brain regions that support their functioning. This study aims at exploring the presence of any difference in functional connectome properties between AN patients and healthy controls (HC) by means of graph theory tools. The effect of 5-HTTLPR genotype on regional and global network characteristics in AN and HC was also explored.
Methods: A sample of 74 subjects (38 HC, 36 AN) underwent a resting state functional magnetic resonance imaging and was genotyped for 5-HTTLPR polymorphism. Comparisons of network properties were made between the AN and HC groups and, within each group, between 5-HTTLPR carriers of low-functioning alleles and carriers of the long-long genotype.
Results: Patients with AN displayed lower network clustering than HC (p = 0.04 at Mann-Whitney U test). Based on both degree and betweenness, a different distribution of network hubs emerged in the two groups. In particular, the anterior part of the anterior cingulate cortex was a hub only in the patient group. A correlation emerged between differences in brain volumes between patients and HC and differences in degree values of basal ganglia, nodes in the insula, and those in the parietal cortex. Carriers of the short allele of the 5-HTTLPR polymorphism were characterized by lower small-world properties (p = 0.027) and modularity (p = 0.031) in the patient group, and a trend toward higher modularity (p = 0.033) and small-world values (p = 0.123) in the HC group.
Discussion: Patients with AN showed differences in hubs distribution, providing evidence of the presence of a different functional architectural backbone in this group. Since some correlation emerged between different degree values of nodes and differences in volumes, further longitudinal studies are warranted to better understand the role of malnutrition on brain network architecture. The opposite effects of 5-HTTLPR polymorphism on global network characteristics in the two groups suggest an interaction of the short allele and malnutrition in modulating brain network properties.

PMID: 31680805 [PubMed]

Ketamine-induced changes in plasma brain-derived neurotrophic factor (BDNF) levels are associated with the resting-state functional connectivity of the prefrontal cortex.

Tue, 11/05/2019 - 21:13
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Ketamine-induced changes in plasma brain-derived neurotrophic factor (BDNF) levels are associated with the resting-state functional connectivity of the prefrontal cortex.

World J Biol Psychiatry. 2019 Nov 04;:1-15

Authors: Woelfer M, Li M, Colic L, Liebe T, Di X, Biswal B, Murrough J, Lessmann V, Brigadski T, Walter M

Abstract
Objectives: Synaptic plasticity and brain-derived neurotrophic factor (BDNF) signalling are proposed to play key roles in antidepressant drug action. Ketamine, an N-methyl-D-aspartate receptor antagonist and putative antidepressant, may increase synaptic plasticity in prefrontal cortex through higher expression of BDNF. Furthermore, ketamine was shown to change resting-state functional connectivity (RSFC) of dorsomedial prefrontal cortex (dmPFC).Methods: In a randomised, placebo-controlled study, we investigated acutely (100 min) and at 24 h following subanesthetic ketamine infusion which dmPFC seeded RSFC changes are most strongly associated with plasma BDNF level changes in 53 healthy participants (21 females, age: 24.4 ± 2.9 years) using 7 T-fMRI.Results: We observed higher relative levels of BDNF 2 h and 24 h after ketamine compared to placebo. Whole-brain regression revealed that the change in BDNF after 24 h was associated with RSFC decreases from dmPFC to posterior cingulate cortex and ventromedial PFC at 24 h and exploratively also at the 100 min measurement point. Follow-up analyses revealed that RSFC reductions following ketamine were restricted to subjects showing increased BDNF levels at 24 h.Conclusions: Our findings indicate BDNF level dynamics following ketamine are related to acute and 24 h RSFC changes. Particularly when BDNF increases are observed after ketamine infusion, a disconnection from dmPFC after 24 h is seen and may reflect synaptic plasticity effects.

PMID: 31680600 [PubMed - as supplied by publisher]

Impact of acute sleep deprivation on dynamic functional connectivity states.

Tue, 11/05/2019 - 21:13
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Impact of acute sleep deprivation on dynamic functional connectivity states.

Hum Brain Mapp. 2019 Nov 04;:

Authors: Li C, Fronczek-Poncelet J, Lange D, Hennecke E, Kroll T, Matusch A, Aeschbach D, Bauer A, Elmenhorst EM, Elmenhorst D

Abstract
Sleep deprivation (SD) could amplify the temporal fluctuation of spontaneous brain activities that reflect different arousal levels using a dynamic functional connectivity (dFC) approach. Therefore, we intended to evaluate the test-retest reliability of dFC characteristics during rested wakefulness (RW), and to explore how the properties of these dynamic connectivity states were affected by extended durations of acute sleep loss (28/52 hr). We acquired resting-state fMRI and neuropsychological datasets in two independent studies: (a) twice during RW and once after 28 hr of SD (n = 15) and (b) after 52 hr of SD and after 14 hr of recovery sleep (RS; n = 14). Sliding-window correlations approach was applied to estimate their covariance matrices and corresponding three connectivity states were generated. The test-retest reliability of dFC properties demonstrated mean dwell time and fraction of connectivity states were reliable. After SD, the mean dwell time of a specific state, featured by strong subcortical-cortical anticorrelations, was significantly increased. Conversely, another globally hypoconnected state was significantly decreased. Subjective sleepiness and objective performances were separately positive and negative correlated with the increased and decreased state. Two brain connectivity states and their alterations might be sufficiently sensitive to reflect changes in the dynamics of brain mental activities after sleep loss.

PMID: 31680379 [PubMed - as supplied by publisher]

Static and dynamic network properties of the repetitive transcranial magnetic stimulation target predict changes in emotion regulation in obsessive-compulsive disorder.

Tue, 11/05/2019 - 21:13
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Static and dynamic network properties of the repetitive transcranial magnetic stimulation target predict changes in emotion regulation in obsessive-compulsive disorder.

Brain Stimul. 2019 Oct 24;:

Authors: Douw L, Quaak M, Fitzsimmons SMDD, de Wit SJ, van der Werf YD, van den Heuvel OA, Vriend C

Abstract
BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive neuromodulation technique to treat psychiatric disorders, such as obsessive-compulsive disorder (OCD). However, the rTMS response varies across subjects.
OBJECTIVE/HYPOTHESIS: We hypothesize that baseline network properties of the rTMS target may help understand this variation and predict response.
METHODS: Excitatory rTMS to the dorsolateral prefrontal cortex (dlPFC) was applied in 19 unmedicated OCD patients, while inhibitory dlPFC-rTMS was applied in 17 healthy controls. The vertex was used as an active control target (19 patients, 18 controls). The rTMS response was operationalized as the individual change in state distress rating during an emotion regulation task. At baseline, subjects underwent resting-state functional MRI. The brain network was constructed by calculating wavelet coherence between regional activity of regions in the Brainnetome atlas. Local and integrative static connectivity and the dynamic network role of the target were calculated. Baseline target region network features were non-parametrically correlated to rTMS response.
RESULTS: In the dlPFC-stimulated patients, greater local connectivity (Kendall's Tau = -0.415, p = 0.013) and less promiscuous role of the target (Kendall's Tau = 0.389, p = 0.025) at baseline were related to greater distress reduction after excitatory rTMS. There were no significant associations in healthy subjects nor in the active control stimulated patients.
CONCLUSIONS: Pre-treatment network topological indices predict rTMS-induced emotional response changes in OCD, such that greater baseline resting-state local connectivity and less temporal integration of the target region imply greater stimulation effects. These results may lead the way towards personalized neuromodulation in OCD.

PMID: 31679906 [PubMed - as supplied by publisher]

A joint network optimization framework to predict clinical severity from resting state functional MRI data.

Tue, 11/05/2019 - 03:13
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A joint network optimization framework to predict clinical severity from resting state functional MRI data.

Neuroimage. 2019 Oct 31;:116314

Authors: D'Souza NS, Nebel MB, Wymbs N, Mostofsky SH, Venkataraman A

Abstract
We propose a novel optimization framework to predict clinical severity from resting state fMRI (rs-fMRI) data. Our model consists of two coupled terms. The first term decomposes the correlation matrices into a sparse set of representative subnetworks that define a network manifold. These subnetworks are modeled as rank-one outer-products which correspond to the elemental patterns of co-activation across the brain; the subnetworks are combined via patient-specific non-negative coefficients. The second term is a linear regression model that uses the patient-specific coefficients to predict a measure of clinical severity. We validate our framework on two separate datasets in a ten fold cross validation setting. The first is a cohort of fifty-eight patients diagnosed with Autism Spectrum Disorder (ASD). The second dataset consists of sixty three patients from a publicly available ASD database. Our method outperforms standard semi-supervised frameworks, which employ conventional graph theoretic and statistical representation learning techniques to relate the rs-fMRI correlations to behavior. In contrast, our joint network optimization framework exploits the structure of the rs-fMRI correlation matrices to simultaneously capture group level effects and patient heterogeneity. Finally, we demonstrate that our proposed framework robustly identifies clinically relevant networks characteristic of ASD.

PMID: 31678501 [PubMed - as supplied by publisher]

Modular organization of brain resting state networks in patients with classical trigeminal neuralgia.

Tue, 11/05/2019 - 03:13
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Modular organization of brain resting state networks in patients with classical trigeminal neuralgia.

Neuroimage Clin. 2019 Oct 21;24:102027

Authors: Tsai YH, Liang X, Yang JT, Hsu LM

Abstract
BACKGROUND: The modular organization of brain networks in trigeminal neuralgia patients has remained largely unknown. We aimed to analyze the brain modules and intermodule connectivity in patients with trigeminal neuralgia before and after percutaneous radiofrequency rhizotomy treatment to identify specific modules that may be associated with the development and brain plasticity of trigeminal neuralgia and to test the ability of modularity analysis to be a predictive imaging biomarker for the treatment effect in patients with trigeminal neuralgia.
METHODS: A total of 25 patients with right trigeminal neuralgia and 20 matched healthy subjects were included. Blood-oxygen-level dependent resting state fMRI was used to analyze the brain modular organization.
RESULTS: Whole brain modularity analysis identified seven modules. The metric of intermodule connectivity, participation coefficient, of the sensorimotor network and default mode network modules were significantly lower in patients and increased after surgery. The participation coefficient of the subcortical modules was associated with the pain duration. Higher communication between the default mode network module and other modules before surgery was associated with a better treatment response. Furthermore, the subcortical module was a significant contributor to the participation coefficient relationship of the default mode network module with the treatment response, and the bilateral midcingulate cortex and thalamus were major connectors in the subcortical module.
CONCLUSIONS: These findings have important implications regarding the global brain modular responses to chronic neuropathic pain and it may be feasible to use the modularity analysis as part of a risk stratification to predict the treatment response.

PMID: 31677586 [PubMed - as supplied by publisher]

Altered resting functional network topology assessed using graph theory in youth with attention-deficit/hyperactivity disorder.

Tue, 11/05/2019 - 03:13
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Altered resting functional network topology assessed using graph theory in youth with attention-deficit/hyperactivity disorder.

Prog Neuropsychopharmacol Biol Psychiatry. 2019 Oct 29;:109796

Authors: Wang Y, Zuo C, Xu Q, Liao S, Kanji M, Wang D

Abstract
Notwithstanding an extensive literature about attention-deficit/hyperactivity disorder (ADHD) and brain structure and function, the controversy of ADHD resulting from dysfunction or developmental delay remains unclear. Graph analysis studies have reached consensus about the pattern of increased integration and decreased randomness during childhood and early adulthood. Here, we hypothesized that ADHD is a neurodevelopmental disorder resulting from developmental delay and would show a pattern of decreased integration and increased randomness during childhood and early adulthood compared with typically developing children. To test this hypothesis, publicly available resting-state fMRI data from 102 children with ADHD and 143 typically developing controls (TDC) were compared using graph theoretical analysis. Functional connectivity was estimated using Pearson correlation analysis, and network topology was characterized using small-world (SW) and minimum spanning tree (MST) properties. The mean strength of global connectivity was significantly weaker in those with ADHD and was related to ADHD diagnosis scores. Significant group differences were observed for SW(clustering coefficient, path length, global and local efficiency) and MST (leaf number, kappa and hierarchy) topology. In addition, except for global efficiency, all of these parameters showed significant correlations with ADHD-related disability. The topology of SW and MST showed less integration and more randomness, which confirmed that ADHD is a disorder associated with developmental delay. Moreover, the topology of resting-state functional networks in children with ADHD that show abnormalities was associated with the degree of disability, which can be considered neurological hallmarks of neurodevelopmental disorders and may facilitate the evaluation and monitoring of clinical status in individuals with ADHD.

PMID: 31676467 [PubMed - as supplied by publisher]

Pharmacologically informed machine learning approach for identifying pathological states of unconsciousness via resting-state fMRI.

Sat, 11/02/2019 - 21:09
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Pharmacologically informed machine learning approach for identifying pathological states of unconsciousness via resting-state fMRI.

Neuroimage. 2019 Oct 28;:116316

Authors: Campbell J, Huang Z, Zhang J, Wu X, Qin P, Northoff G, Mashour GA, Hudetz AG

Abstract
Determining the level of consciousness in patients with disorders of consciousness (DOC) remains challenging. To address this challenge, resting-state fMRI (rs-fMRI) has been widely used for detecting the local, regional, and network activity differences between DOC patients and healthy controls. Although substantial progress has been made towards this endeavor, the identification of robust rs-fMRI-based biomarkers for level of consciousness is still lacking. Recent developments in machine learning show promise as a tool to augment the discrimination between different states of consciousness in clinical practice. Here, we investigated whether machine learning models trained to make a binary distinction between conscious wakefulness and anesthetic-induced unconsciousness would then be capable of reliably identifying pathologically induced unconsciousness. We did so by extracting rs-fMRI-based features associated with local activity, regional homogeneity, and interregional functional activity in 44 subjects during wakefulness, light sedation, and unresponsiveness (deep sedation and general anesthesia), and subsequently using those features to train three distinct candidate machine learning classifiers: support vector machine, Extra Trees, artificial neural network. First, we show that all three classifiers achieve reliable performance within-dataset (via nested cross-validation), with a mean area under the receiver operating characteristic curve (AUC) of 0.95, 0.92, and 0.94, respectively. Additionally, we observed comparable cross-dataset performance (making predictions on the DOC data) as the anesthesia-trained classifiers demonstrated a consistent ability to discriminate between unresponsive wakefulness syndrome (UWS/VS) patients and healthy controls with mean AUC's of 0.99, 0.94, 0.98, respectively. Lastly, we explored the potential of applying the aforementioned classifiers towards discriminating intermediate states of consciousness, specifically, subjects under light anesthetic sedation and patients diagnosed as having a minimally conscious state (MCS). Our findings demonstrate that machine learning classifiers trained on rs-fMRI features derived from participants under anesthesia have potential to aid the discrimination between degrees of pathological unconsciousness in clinical patients.

PMID: 31672663 [PubMed - as supplied by publisher]

Intra brainstem connectivity is impaired in chronic fatigue syndrome.

Sat, 11/02/2019 - 06:09
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Intra brainstem connectivity is impaired in chronic fatigue syndrome.

Neuroimage Clin. 2019 Oct 19;24:102045

Authors: Barnden LR, Shan ZY, Staines DR, Marshall-Gradisnik S, Finegan K, Ireland T, Bhuta S

Abstract
In myalgic encephalomyelitis or chronic fatigue syndrome (ME/CFS), abnormal MRI correlations with symptom severity and autonomic measures have suggested impaired nerve signal conduction within the brainstem. Here we analyse fMRI correlations to directly test connectivity within and from the brainstem. Resting and task functional MRI (fMRI) were acquired for 45 ME/CFS (Fukuda criteria) and 27 healthy controls (HC). We selected limited brainstem reticular activation system (RAS) regions-of-interest (ROIs) based on previous structural MRI findings in a different ME/CFS cohort (bilateral rostral medulla and midbrain cuneiform nucleus), the dorsal Raphe nucleus, and two subcortical ROIs (hippocampus subiculum and thalamus intralaminar nucleus) reported to have rich brainstem connections. When HC and ME/CFS were analysed separately, significant correlations were detected for both groups during both rest and task, with stronger correlations during task than rest. In ME/CFS, connections were absent between medulla and midbrain nuclei, although hippocampal connections with these nuclei were enhanced. When corresponding correlations from HC and ME/CFS were compared, ME/CFS connectivity deficits were detected within the brainstem between the medulla and cuneiform nucleus and between the brainstem and hippocampus and intralaminar thalamus, but only during task. In CFS/ME, weaker connectivity between some RAS nuclei was associated with increased symptom severity. RAS neuron oscillatory signals facilitate coherence in thalamo-cortical oscillations. Brainstem RAS connectivity deficits can explain autonomic changes and diminish cortical oscillatory coherence which can impair attention, memory, cognitive function, sleep quality and muscle tone, all symptoms of ME/CFS.

PMID: 31671321 [PubMed - as supplied by publisher]

Functional connectivity of the anterior cingulate cortex predicts treatment outcome for rTMS in treatment-resistant depression at 3-month follow-up.

Sat, 11/02/2019 - 06:09
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Functional connectivity of the anterior cingulate cortex predicts treatment outcome for rTMS in treatment-resistant depression at 3-month follow-up.

Brain Stimul. 2019 Oct 18;:

Authors: Ge R, Downar J, Blumberger DM, Daskalakis ZJ, Vila-Rodriguez F

Abstract
BACKGROUND AND OBJECTIVE: Repetitive transcranial magnetic stimulation (rTMS) is a first-line treatment for treatment-resistant depression (TRD). The mechanisms of action of rTMS are not fully understood, and no biomarkers are available to assist in clinical practice to predict response to rTMS. This study aimed to demonstrate that after-rTMS clinical improvement is associated with functional connectivity (FC) changes of the subgenual cingulate cortex (sgACC) and rostral anterior cingulate (rACC), and FC of sgACC and rACC might serve as potential predictors for treatment response.
METHODS: Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected within 1 week before rTMS initiation in 50 TRD patients to predict subsequent response to rTMS on the left dorsolateral prefrontal cortex (DLPFC). Follow-up rs-fMRI was obtained 12 weeks after completion of rTMS and neural correlates of rTMS in sgACC- and rACC-related FC patterns were compared to before rTMS data and with rs-fMRI from healthy participants.
RESULTS: Treatment response was associated with lower FC of sgACC to right DLPFC and higher FC of rACC to left lateral parietal cortex (IPL) measured at baseline. Using sgACC-DLPFC and rACC-IPL connectivity as features, responder-nonresponder classification accuracies of 84% and 76% (end-of-treatment), 88% and 81% (3-month follow-up), respectively were achieved. Longitudinal rs-fMRI data analyses revealed that the hyperconnectivity between sgACC and visual cortex was normalized to a level which was comparable to that of healthy participants.
CONCLUSIONS: Brain activity patterns in depression are predictive of treatment response to rTMS, and longitudinal change of brain activity in relevant brain circuits after rTMS is associated with treatment response in depression. Target engagement paradigms may offer opportunities to increase the efficacy of rTMS in TRD by optimal selection of patients for treatment.
TRIAL REGISTRATION: ClinicalTrials.gov Identifiers: NCT01887782 and NCT02800226.

PMID: 31668646 [PubMed - as supplied by publisher]

Optimizing Hippocampal-Cortical Network Modulation via Repetitive Transcranial Magnetic Stimulation: A Dose-Finding Study Using the Continual Reassessment Method.

Sat, 11/02/2019 - 06:09
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Optimizing Hippocampal-Cortical Network Modulation via Repetitive Transcranial Magnetic Stimulation: A Dose-Finding Study Using the Continual Reassessment Method.

Neuromodulation. 2019 Oct 30;:

Authors: Freedberg M, Reeves JA, Toader AC, Hermiller MS, Kim E, Haubenberger D, Cheung YK, Voss JL, Wassermann EM

Abstract
OBJECTIVE: Repetitive transcranial magnetic stimulation (rTMS) can cause potentially useful changes in brain functional connectivity (FC), but the number of treatment sessions required is unknown. We applied the continual reassessment method (CRM), a Bayesian, adaptive, dose-finding procedure to a rTMS paradigm in an attempt to answer this question.
MATERIALS AND METHODS: The sample size was predetermined at 15 subjects and the cohort size was set with three individuals (i.e., five total cohorts). In a series of consecutive daily sessions, we delivered rTMS to the left posterior parietal cortex and measured resting-state FC with fMRI in a predefined hippocampal network in the left hemisphere. The session number for each successive cohort was determined by the CRM algorithm. We set a response criterion of a 0.028 change in FC between the hippocampus and the parietal cortex, which was equal to the increase seen in 87.5% of participants in a previous study using five sessions.
RESULTS: A ≥criterion change was observed in 9 of 15 participants. The CRM indicated that greater than four sessions are required to produce the criterion change reliably in future studies.
CONCLUSIONS: The CRM can be adapted for rTMS dose finding when a reliable outcome measure, such as FC, is available. The minimum effective dose needed to produce a criterion increase in FC in our hippocampal network of interest at 87.5% efficacy was estimated to be greater than four sessions. This study is the first demonstration of a Bayesian, adaptive method to explore a rTMS parameter.

PMID: 31667947 [PubMed - as supplied by publisher]

Inhibition-related modulation of salience and frontoparietal networks predicts cognitive control ability and inattention symptoms in children with ADHD.

Thu, 10/31/2019 - 18:05

Inhibition-related modulation of salience and frontoparietal networks predicts cognitive control ability and inattention symptoms in children with ADHD.

Mol Psychiatry. 2019 Oct 29;:

Authors: Cai W, Griffiths K, Korgaonkar MS, Williams LM, Menon V

Abstract
Attention-deficit hyperactivity disorder (ADHD) is associated with pervasive impairments in attention and cognitive control. Although brain circuits underlying these impairments have been extensively investigated with resting-state fMRI, little is known about task-evoked functional brain circuits and their relation to cognitive control deficits and inattention symptoms in children with ADHD. Children with ADHD and age, gender and head motion matched typically developing (TD) children completed a Go/NoGo fMRI task. We used multivariate and dimensional analyses to investigate impairments in two core cognitive control systems: (i) cingulo-opercular "salience" network (SN) anchored in the right anterior insula, dorsal anterior cingulate cortex (rdACC), and ventrolateral prefrontal cortex (rVLPFC) and (ii) dorsal frontoparietal "central executive" (FPN) network anchored in right dorsolateral prefrontal cortex (rDLPFC) and posterior parietal cortex (rPPC). We found that multivariate patterns of task-evoked effective connectivity between brain regions in SN and FPN distinguished the ADHD and TD groups, with rDLPFC-rPPC connectivity emerging as the most distinguishing link. Task-evoked rdACC-rVLPFC connectivity was positively correlated with NoGo accuracy, and negatively correlated with severity of inattention symptoms. Brain-behavior relationships were robust against potential age, gender, and head motion confounds. Our findings highlight aberrancies in task-evoked modulation of SN and FPN connectivity in children with ADHD. Crucially, cingulo-frontal connectivity was a common locus of deficits in cognitive control and clinical measures of inattention symptoms. Our study provides insights into a parsimonious systems neuroscience model of cognitive control deficits in ADHD, and suggests specific circuit biomarkers for predicting treatment outcomes in childhood ADHD.

PMID: 31664176 [PubMed - as supplied by publisher]

Functional connectivity of music-induced analgesia in fibromyalgia.

Thu, 10/31/2019 - 18:05

Functional connectivity of music-induced analgesia in fibromyalgia.

Sci Rep. 2019 Oct 29;9(1):15486

Authors: Pando-Naude V, Barrios FA, Alcauter S, Pasaye EH, Vase L, Brattico E, Vuust P, Garza-Villarreal EA

Abstract
Listening to self-chosen, pleasant and relaxing music reduces pain in fibromyalgia (FM), a chronic centralized pain condition. However, the neural correlates of this effect are fairly unknown. In our study, we wished to investigate the neural correlates of music-induced analgesia (MIA) in FM patients. To do this, we studied 20 FM patients and 20 matched healthy controls (HC) acquiring rs-fMRI with a 3T MRI scanner, and pain data before and after two 5-min auditory conditions: music and noise. We performed resting state functional connectivity (rs-FC) seed-based correlation analyses (SCA) using pain and analgesia-related ROIs to determine the effects before and after the music intervention in FM and HC, and its correlation with pain reports. We found significant differences in baseline rs-FC between FM and HC. Both groups showed changes in rs-FC after the music condition. FM patients reported MIA that was significantly correlated with rs-FC decrease between the angular gyrus, posterior cingulate cortex and precuneus, and rs-FC increase between amygdala and middle frontal gyrus. These areas are related to autobiographical and limbic processes, and auditory attention, suggesting MIA may arise as a consequence of top-down modulation, probably originated by distraction, relaxation, positive emotion, or a combination of these mechanisms.

PMID: 31664132 [PubMed - in process]

Functional connectivity in human auditory networks and the origins of variation in the transmission of musical systems.

Wed, 10/30/2019 - 18:05
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Functional connectivity in human auditory networks and the origins of variation in the transmission of musical systems.

Elife. 2019 Oct 29;8:

Authors: Lumaca M, Kleber B, Brattico E, Vuust P, Baggio G

Abstract
Music producers, whether original composers or performers, vary in their ability to acquire and faithfully transmit music. This form of variation may serve as a mechanism for the emergence of new traits in musical systems. In this study, we aim to investigate whether individual differences in the social learning and transmission of music relate to intrinsic neural dynamics of auditory processing systems. We combined auditory and resting-state functional magnetic resonance imaging (fMRI) with an interactive laboratory model of cultural transmission, the signaling game, in an experiment with a large cohort of participants (N=51). We found that the degree of interhemispheric rs-FC within fronto-temporal auditory networks predicts-weeks after scanning-learning, transmission, and structural modification of an artificial tone system. Our study introduces neuroimaging in cultural transmission research and points to specific neural auditory processing mechanisms that constrain and drive variation in the cultural transmission and regularization of musical systems.

PMID: 31658945 [PubMed - in process]

Resting-State Functional Magnetic Resonance Imaging for Brain Tumor Surgical Planning: Feasibility in Clinical Setting.

Wed, 10/30/2019 - 18:05
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Resting-State Functional Magnetic Resonance Imaging for Brain Tumor Surgical Planning: Feasibility in Clinical Setting.

World Neurosurg. 2019 Nov;131:356-363

Authors: Sparacia G, Parla G, Cannella R, Perri A, Lo Re V, Mamone G, Miraglia R, Torregrossa F, Grasso G

Abstract
The aim of this study was to introduce resting-state functional magnetic resonance imaging (rest-fMRI) capability for brain tumor surgical planning. rest-fMRI is an emerging functional neuroimaging technique potentially able to provide new insights into brain physiology and to provide useful information regarding brain tumors in preoperative and postoperative settings. rest-fMRI evaluates low-frequency fluctuations in the blood oxygen level-dependent signal while the subject is at rest during magnetic resonance imaging examination. Multiple resting-state networks have been identified, including the somatosensory, language, and visual networks, which are of primary importance for surgical planning. We discuss the feasibility of rest-fMRI examination before and after surgical resection of brain tumors in routine clinical practice and the usefulness of the information obtained for surgical planning in brain tumor resection. rest-fMRI is particularly useful for patients who are unable to cooperate with the task-based paradigm, such as children or patients who are sedated, paretic, or aphasic. Although standardization and validation of rest-fMRI are still ongoing, this technique is feasible and valuable and can be implemented for routine clinical surgical planning.

PMID: 31658578 [PubMed - in process]

Altered resting-state functional connectivity of the insula in individuals with clinical high-risk and patients with first-episode schizophrenia.

Tue, 10/29/2019 - 06:03
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Altered resting-state functional connectivity of the insula in individuals with clinical high-risk and patients with first-episode schizophrenia.

Psychiatry Res. 2019 Oct 11;282:112608

Authors: Li XB, Wang LB, Xiong YB, Bo QJ, He F, Li F, Hou WP, Wen YJ, Wang XQ, Yang NB, Mao Z, Dong QH, Zhang FF, Yang R, Wang D, Xiang YT, Zhu YY, Tang YL, Yang Z, Wang CY

Abstract
OBJECTIVES: Abnormalities in insular functional connectivity have been implicated in many clinical features of schizophrenia. The aim of this study was to determine to what degree such abnormalities occur in individuals with clinical high risk for psychosis (CHR), and whether which is associated with symptom severity.
METHODS: Resting-state fMRI data were collected from 47 healthy controls, 24 CHR individuals and 19 patients with first-episode schizophrenia. Using the posterior, dorsal and ventral insular subregions as separate seeds, we examined resting-state functional connectivity differences between different groups and the association between concurrent symptom severity and dysconnectivity.
RESULTS: Compared with healthy controls, both CHR individuals and schizophrenia patients showed hypoconnectivity between posterior insula (PI) and somatosensory areas, and between dorsal anterior insula (dAI) and putamen. Schizophrenia patients also showed dAI and ventral anterior insula(vAI) hyperconnectivity with visual areas relative to controls and CHR individuals. Correlation analysis revealed that dAI functional connectivity with superior temporal gyrus was positively correlated with positive symptoms of CHR, and vAI connectivity with dorsolateral prefrontal cortex was negatively correlated with the severity of the symptoms of first-episode schizophrenia.
CONCLUSIONS: Our findings suggest that insular functional dysconnectivity with the sensory cortex may be a system-level neural substrate preceding the onset of psychosis.

PMID: 31655405 [PubMed - as supplied by publisher]

Spectral partitioning identifies individual heterogeneity in the functional network topography of ventral and anterior medial prefrontal cortex.

Tue, 10/29/2019 - 06:03
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Spectral partitioning identifies individual heterogeneity in the functional network topography of ventral and anterior medial prefrontal cortex.

Neuroimage. 2019 Oct 22;:116305

Authors: Toro-Serey C, Tobyne SM, McGuire JT

Abstract
Regions of human medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC) are part of the default network (DN), and additionally are implicated in diverse cognitive functions ranging from autobiographical memory to subjective valuation. Our ability to interpret the apparent co-localization of task-related effects with DN-regions is constrained by a limited understanding of the individual-level heterogeneity in mPFC/PCC functional organization. Here we used cortical surface-based meta-analysis to identify a parcel in human PCC that was more strongly associated with the DN than with valuation effects. We then used resting-state fMRI data and a data-driven network analysis algorithm, spectral partitioning, to partition mPFC and PCC into "DN" and "non-DN" subdivisions in individual participants (n = 100 from the Human Connectome Project). The spectral partitioning algorithm identified individual-level cortical subdivisions that varied markedly across individuals, especially in mPFC, and were reliable across test/retest datasets. Our results point toward new strategies for assessing whether distinct cognitive functions engage common or distinct mPFC subregions at the individual level.

PMID: 31654759 [PubMed - as supplied by publisher]

Abnormal brain activity in rats with sustained hypobaric hypoxia exposure: a resting-state functional magnetic resonance imaging study.

Tue, 10/29/2019 - 06:03
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Abnormal brain activity in rats with sustained hypobaric hypoxia exposure: a resting-state functional magnetic resonance imaging study.

Chin Med J (Engl). 2019 Oct 22;:

Authors: Yuan H, Wang Y, Liu PF, Yue YL, Guo JS, Wang ZC

Abstract
BACKGROUND: Hypobaric hypoxia (HH) exposure at high altitudes can result in a decline in cognitive function, which may have a serious impact on the daily life of people who migrate to high altitudes. However, the specific HH-induced changes in brain function remain unclear. This study explored changes in brain activity in rats exposed to a sustained HH environment using functional magnetic resonance imaging (fMRI).
METHODS: Healthy male rats (8 weeks old) were randomly divided into a model group and a control group. A rat model of cognitive impairment induced by sustained HH exposure was established. The control and model groups completed training and testing in the Morris water maze (MWM). A two-sample t-test for between-group difference comparisons was performed. Repeated measures analyses of variance for within-group comparisons were performed and post-hoc comparisons were made using the Tukey test. Between-group differences in spontaneous brain activity were assessed using a voxel-wise analysis of resting-state fMRI (rs-fMRI), combined with analyses of the fractional amplitude of low frequency fluctuations (fALFF) in statistical parametric mapping.
RESULTS: In the MWM test, the escape latencies of the model group were significantly longer compared with those of the control group (control group vs. model group, day 1: 21.6 ± 3.3 s vs. 40.5 ± 3.4 s, t = -11.282; day 2: 13.5 ± 2.2 s vs. 28.7 ± 5.3 s, t = -7.492; day 3: 10.5 ± 2.8 s vs. 22.6 ± 6.1 s, t = -5.099; day 4: 9.7 ± 2.5 s vs. 18.6 ± 5.2 s, t = -4.363; day 5: 8.8 ± 2.7 s vs. 16.7 ± 5.0 s, t = -3.932; all P < 0.001). Within both groups, the escape latency at day 5 was significantly shorter than those at other time points (control group: F = 57.317, P < 0.001; model group: F = 50.718, P < 0.001). There was no within-group difference in average swimming speed (control group, F = 1.162, P = 0.956; model group, F = 0.091, P = 0.880). Within the model group, the time spent within the original platform quadrant was significantly shorter (control group vs. model group: 36.1 ± 5.7 s vs. 17.8 ± 4.3 s, t = 7.249, P < 0.001) and the frequency of crossing the original platform quadrant was significantly reduced (control group vs. model group: 6.4 ± 1.9 s vs. 2.0 ± 0.8 s, t = 6.037, P < 0.001) compared with the control group. In the rs-fMRI study, compared with the control group, rats in the model group showed widespread reductions in fALFF values throughout the brain.
CONCLUSIONS: The abnormalities in spontaneous brain activity indicated by the fALFF measurements may reflect changes in brain function after HH exposure. This widespread abnormal brain activity may help to explain and to provide new insights into the mechanism underlying the impairment of brain function under sustained exposure to high altitudes.

PMID: 31651519 [PubMed - as supplied by publisher]

Dynamic changes in thalamic connectivity following stress and its association with future depression severity.

Tue, 10/29/2019 - 06:03
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Dynamic changes in thalamic connectivity following stress and its association with future depression severity.

Brain Behav. 2019 Oct 25;:e01445

Authors: Zhang X, Li X, Steffens DC, Guo H, Wang L

Abstract
INTRODUCTION: Tracking stress-induced brain activity and connectivity dynamically and examining activity/connectivity-associated recovery ability after stress might be an effective way of detecting stress vulnerability.
METHODS: Using two widely used stress paradigms, a speech task (social stress) and a mathematical calculation task (mental loading stress), we examined common changes in regional homogeneity (ReHo) and functional connectivity (FC) before, during, and after the two stressful tasks in thirty-nine college students. A counting breath relaxation task was employed as a contrast task. ReHo and FC were compared between subjects with higher versus lower depression symptoms (assessed by the Beck Depression Inventory, BDI). We developed a recovery index (RI) based on dynamic changes of ReHo/FC to evaluate individuals' ability to recover from a stressful state. To assess RI's usefulness in predicting future depression severity, BDI was also measured at one-year follow-up.
RESULTS: Our results revealed a ReHo decrease after both stressful tasks and a ReHo increase after the relaxation task in bilateral thalamus. The ReHo decrease after both stressful tasks was more significant in the higher BDI than the lower BDI group. Higher ReHo RI of the right thalamus in the higher BDI groups was significantly correlated with lower BDI severity at one-year follow-up. Bilateral thalamus also showed increased FC with the default mode network and decreased FC with the executive control network after the stressful tasks.
CONCLUSION: These findings highlight the importance of tracking resting activity and connectivity of thalamus dynamically for detecting stress vulnerability.

PMID: 31651099 [PubMed - as supplied by publisher]