Most recent paper

Altered social cognition and connectivity of default mode networks in the co-occurrence of autistic spectrum disorder and attention deficit hyperactivity disorder.

Aust N Z J Psychiatry. 2019 Mar 07;:4867419836031

Authors: Wang K, Xu M, Ji Y, Zhang L, Du X, Li J, Luo Q, Li F

Abstract
OBJECTIVE:: As two common neurodevelopmental disorders, autistic spectrum disorder and attention deficit hyperactivity disorder frequently occur together. Until now, only a few studies have investigated the co-occurrence of attention deficit hyperactivity disorder and autistic spectrum disorder, this is due to restrictions associated with previous Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision. Most previous research has focused on the developmental trajectories for autistic spectrum disorder and attention deficit hyperactivity disorder separately, while the neural mechanisms underpinning the co-occurrence of autistic spectrum disorder and attention deficit hyperactivity disorder remain largely unknown.
METHODS:: We studied 162 autistic spectrum disorder individuals (including 79 co-attention deficit hyperactivity disorder and 83 non-attention deficit hyperactivity disorder patients) and 177 typical developing individuals using resting-state functional magnetic resonance imaging data from the Autism Brain Imaging Data Exchange II, an aggregated magnetic resonance imaging dataset from 19 centers. Independent component analysis was used to extract sub-networks from the classic resting-state networks. Functional connectivity values within (intra-iFC) and between (inter-iFC) these networks were then determined. Subsequently, we compared the ASD_coADHD group with the ASD_nonADHD group in relation to the abnormal intra-iFC and inter-iFC of autistic spectrum disorder group relative to the typical developing group.
RESULTS:: The ASD_coADHD group showed more severe social impairment and decreased intra-iFC in the bilateral posterior cingulate cortex of the default mode network (independent component 17) and increased inter-iFC between the default mode network (independent component 8) and the somatomotor networks (independent component 2) compared to the ASD_nonADHD group. In addition, the strength of the intra-iFC in the default mode network was associated with the severity of autistic traits across the entire autistic spectrum disorder group and particularly the ASD_coADHD group.
CONCLUSION:: Our results showed that dysfunction of the default mode network is a central feature in the co-occurrence of autistic spectrum disorder and attention deficit hyperactivity disorder, including connectivity within the default mode network as well as between the default mode network and the somatomotor networks, thus supporting the existence of a clinically combined phenotype (autistic spectrum disorder + attention deficit hyperactivity disorder).

PMID: 30843728 [PubMed - as supplied by publisher]

Altered coupling of spontaneous brain activities and brain temperature in patients with adolescent-onset, first-episode, drug-naïve schizophrenia.

Neuroradiology. 2019 Mar 06;:

Authors: Zhao Z, Xu G, Sun B, Li X, Shen Z, Li S, Xu Y, Huang M, Xu D

Abstract
PURPOSE: A recent study has reported that schizophrenia patients show an uncoupled association between intraventricular brain temperature (BT) and cerebral blood flow (CBF). CBF has been found to be closely coupled with spontaneous brain activities (SBAs) derived from resting-state BOLD fMRI metrics. Yet, it is unclear so far whether the relationship between the intraventricular BT and the SBAs may change in patients with adolescent-onset schizophrenia (AOS) compared with that in healthy controls (HCs).
METHODS: The present study recruited 28 first-episode, drug-naïve AOS patients and 22 matched HCs. We measured the temperature of the lateral ventricles (LV) using diffusion-weighted imaging thermometry and measured SBAs using both regional homogeneity and amplitude of low-frequency fluctuation methods. A nonparametric Wilcoxon rank sum test was used to detect the difference in intraventricular BT between AOS patients and HCs with LV volume, age, and sex as covariates. We also evaluated the relationship between the intraventricular BT and the SBAs using partial correlation analysis controlling for LV volume, age, and sex.
RESULTS: We found that HCs showed a significant negative correlation between the intraventricular BT and the local SBAs in the bilateral putamina and left superior temporal gyrus, while such a correlation was absent in AOS patients. Additionally, no significant difference between the two groups was found in the intraventricular BT.
CONCLUSION: These findings suggest that AOS patients may experience an uncoupling between intraventricular BT and SBAs in several schizophrenia-related brain areas, which may be associated with the altered relationships among intraventricular BT, CBF, and metabolism.

PMID: 30843095 [PubMed - as supplied by publisher]

Sleep-State Dependent Alterations in Brain Functional Connectivity under Urethane Anesthesia in a Rat Model of Early-Stage Parkinson's Disease.

eNeuro. 2019 Jan-Feb;6(1):

Authors: Zhurakovskaya E, Leikas J, Pirttimäki T, Casas Mon F, Gynther M, Aliev R, Rantamäki T, Tanila H, Forsberg MM, Gröhn O, Paasonen J, Jalkanen AJ

Abstract
Parkinson's disease (PD) is characterized by the gradual degeneration of dopaminergic neurons in the substantia nigra, leading to striatal dopamine depletion. A partial unilateral striatal 6-hydroxydopamine (6-OHDA) lesion causes 40-60% dopamine depletion in the lesioned rat striatum, modeling the early stage of PD. In this study, we explored the connectivity between the brain regions in partially 6-OHDA lesioned male Wistar rats under urethane anesthesia using functional magnetic resonance imaging (fMRI) at 5 weeks after the 6-OHDA infusion. Under urethane anesthesia, the brain fluctuates between the two states, resembling rapid eye movement (REM) and non-REM sleep states. We observed clear urethane-induced sleep-like states in 8/19 lesioned animals and 8/18 control animals. 6-OHDA lesioned animals exhibited significantly lower functional connectivity between the brain regions. However, we observed these differences only during the REM-like sleep state, suggesting the involvement of the nigrostriatal dopaminergic pathway in REM sleep regulation. Corticocortical and corticostriatal connections were decreased in both hemispheres, reflecting the global effect of the lesion. Overall, this study describes a promising model to study PD-related sleep disorders in rats using fMRI.

PMID: 30838323 [PubMed - in process]

Resting-state Functional MRI in Parkinsonian Syndromes.

Mov Disord Clin Pract. 2019 Feb;6(2):104-117

Authors: Filippi M, Sarasso E, Agosta F

Abstract
Background: Functional MRI (fMRI) has been widely used to study abnormal patterns of functional connectivity at rest in patients with movement disorders such as idiopathic Parkinson's disease (PD) and atypical parkinsonisms.
Methods: This manuscript provides an educational review of the current use of resting-state fMRI in the field of parkinsonian syndromes.
Results: Resting-state fMRI studies have improved the current knowledge about the mechanisms underlying motor and non-motor symptom development and progression in movement disorders. Even if its inclusion in clinical practice is still far away, resting-state fMRI has the potential to be a promising biomarker for early disease detection and prediction. It may also aid in differential diagnosis and monitoring brain responses to therapeutic agents and neurorehabilitation strategies in different movement disorders.
Conclusions: There is urgent need to identify and validate prodromal biomarkers in PD patients, to perform further studies assessing both overlapping and disease-specific fMRI abnormalities among parkinsonian syndromes, and to continue technical advances to fully realize the potential of fMRI as a tool to monitor the efficacy of chronic therapies.

PMID: 30838308 [PubMed]

Abnormal Dynamic Functional Connectivity Associated With Subcortical Networks in Parkinson's Disease: A Temporal Variability Perspective.

Front Neurosci. 2019;13:80

Authors: Zhu H, Huang J, Deng L, He N, Cheng L, Shu P, Yan F, Tong S, Sun J, Ling H

Abstract
Parkinson's disease (PD) is a neurodegenerative disease characterized by dysfunction in distributed functional brain networks. Previous studies have reported abnormal changes in static functional connectivity using resting-state functional magnetic resonance imaging (fMRI). However, the dynamic characteristics of brain networks in PD is still poorly understood. This study aimed to quantify the characteristics of dynamic functional connectivity in PD patients at nodal, intra- and inter-subnetwork levels. Resting-state fMRI data of a total of 42 PD patients and 40 normal controls (NCs) were investigated from the perspective of the temporal variability on the connectivity profiles across sliding windows. The results revealed that PD patients had greater nodal variability in precentral and postcentral area (in sensorimotor network, SMN), middle occipital gyrus (in visual network), putamen (in subcortical network) and cerebellum, compared with NCs. Furthermore, at the subnetwork level, PD patients had greater intra-network variability for the subcortical network, salience network and visual network, and distributed changes of inter-network variability across several subnetwork pairs. Specifically, the temporal variability within and between subcortical network and other cortical subnetworks involving SMN, visual, ventral and dorsal attention networks as well as cerebellum was positively associated with the severity of clinical symptoms in PD patients. Additionally, the increased inter-network variability of cerebellum-auditory pair was also correlated with clinical severity of symptoms in PD patients. These observations indicate that temporal variability can detect the distributed abnormalities of dynamic functional network of PD patients at nodal, intra- and inter-subnetwork scales, and may provide new insights into understanding PD.

PMID: 30837825 [PubMed]

Functional connectivity of hypothalamus in chronic migraine with medication overuse.

Cephalalgia. 2019 Mar 05;:333102419833087

Authors: Lerebours F, Boulanouar K, Barège M, Denuelle M, Bonneville F, Payoux P, Larrue V, Fabre N

Abstract
OBJECTIVE: To investigate the functional connectivity of the hypothalamus in chronic migraine compared to interictal episodic migraine in order to improve our understanding of migraine chronification.
METHODS: Using task-free fMRI and ROI-to-ROI analysis, we compared anterior hypothalamus intrinsic connectivity with the spinal trigeminal nucleus in patients with chronic migraine (n = 25) to age- and sex-matched patients with episodic migraine in the interictal phase (n = 22). We also conducted a seed-to-voxel analysis with anterior hypothalamus as a seed.
RESULTS: All patients with chronic migraine had medication overuse. We found a significant connectivity (T = 2.08, p = 0.024) between anterior hypothalamus and spinal trigeminal nucleus in the chronic group, whereas these two regions were not connected in the episodic group. The strength of connectivity was not correlated with pain intensity (rho: 0.09, p = 0.655). In the seed-to-voxel analysis, three regions were more connected with the anterior hypothalamus in the chronic group: The spinal trigeminal nuclei (MNI coordinate x = 2, y = -44, z = -62), the right dorsal anterior insula (MNI coordinate x = 10, y = 10, z = 18), and the right caudate (MNI coordinate x = 12, y = 28, z = 6). However, these correlations were no longer significant after whole brain FWE correction.
CONCLUSION: An increased functional connectivity between the anterior hypothalamus and the spinal trigeminal nucleus, as previously reported in preictal episodic migraine, was demonstrated in chronic migraine with medication overuse. This finding confirms a major role of the anterior hypothalamus in migraine and suggests that chronic migraineurs are locked in the preictal phase.

PMID: 30836766 [PubMed - as supplied by publisher]

Effect of tDCS on Aberrant Functional Network Connectivity in Refractory Hallucinatory Schizophrenia: A Pilot Study.

Psychiatry Investig. 2019 Mar 07;:

Authors: Yoon YB, Kim M, Lee J, Cho KIK, Kwak S, Lee TY, Kwon JS

Abstract
We aim to investigate the effect of fronto-temporal transcranial direct current stimulation (tDCS) on the interactions among functional networks and its association with psychotic symptoms. In this pilot study, we will determine possible candidate functional networks and an adequate sample size for future research. Seven schizophrenia patients with treatment-refractory auditory hallucinations underwent tDCS twice daily for 5 days. Resting-state fMRI data and measures of the severity of psychotic symptoms were acquired at baseline and after completion of the tDCS sessions. At baseline, decreased functional network interaction was negatively correlated with increased hallucinatory behavior. After tDCS, the previously reduced functional network connectivity significantly increased. Our results showed that fronto-temporal tDCS could possibly remediate aberrant hallucination-related functional network interactions in patients with schizophrenia.

PMID: 30836741 [PubMed - as supplied by publisher]

Divergent patterns of loss of interpersonal warmth in frontotemporal dementia syndromes are predicted by altered intrinsic network connectivity.

Neuroimage Clin. 2019 Feb 23;22:101729

Authors: Toller G, Yang WFZ, Brown JA, Ranasinghe KG, Shdo SM, Kramer JH, Seeley WW, Miller BL, Rankin KP

Abstract
Loss of warmth is well-documented in behavioral variant frontotemporal dementia (bvFTD) and semantic variant primary progressive aphasia (svPPA) at a group level, and has been linked to salience (SN) and semantic-appraisal (SAN) network atrophy. However, clinical observations of individual patients show much greater heterogeneity, thus measuring this clinical variability and identifying the underlying neurologic mechanisms is a critical step for understanding the symptom profile of any one patient. We used reliable change indexes with premorbid and current informant-based evaluations to characterize patterns of change on the warmth subscale of the Interpersonal Adjective Scale (IAS) questionnaire in 132 patients (21 bvFTD, 19 svPPA, 22 nonfluent variant primary progressive aphasia [nfvPPA], 37 Alzheimer's disease [AD]) and 33 healthy older adults. We investigated whether individual differences in warmth change were reflected in SN or SAN functional connectivity, or structural volume of individual brain regions in these two networks. Though one subset of patients showed significant drop in warmth to abnormally low levels (bvFTD: 38%; svPPA: 21%; nfvPPA: 5%; AD: 11%), a second subset significantly dropped but remained within the clinically normal range (bvFTD: 33%; svPPA: 21%; nfvPPA: 9%; AD: 5%), and a third subset did not drop and stayed in the clinically normal range (bvFTD: 29%; svPPA: 58%; nfvPPA: 86%; AD: 84%). Furthermore, interpersonal warmth score was strongly predicted by SN functional connectivity (p < .01), but not by SAN functional connectivity or by structural volume in these networks. Our results extend earlier group-level findings by showing wide individual variability in degree of disease-related reduction of interpersonal warmth and SN functional connectivity in bvFTD and svPPA, and highlight new approaches to revealing how brain connectivity predicts behavior on an individual patient level. Our findings suggest that measures of interpersonal warmth can provide important clinical information about changes in underlying brain networks, and help clinicians and clinical researchers better identify which bvFTD and svPPA patients are at greater risk for interpersonal disruption.

PMID: 30836325 [PubMed - as supplied by publisher]

Benchmarking functional connectome-based predictive models for resting-state fMRI.

Neuroimage. 2019 Mar 02;:

Authors: Dadi K, Rahim M, Abraham A, Chyzhyk D, Milham M, Thirion B, Varoquaux G, Alzheimer's Disease Neuroimaging Initiative

Abstract
Functional connectomes reveal biomarkers of individual psychological or clinical traits. However, there is great variability in the analytic pipelines typically used to derive them from rest-fMRI cohorts. Here, we consider a specific type of studies, using predictive models on the edge weights of functional connectomes, for which we highlight the best modeling choices. We systematically study the prediction performances of models in 6 different cohorts and a total of 2000 individuals, encompassing neuro-degenerative (Alzheimer's, Post-traumatic stress disorder), neuro-psychiatric (Schizophrenia, Autism), drug impact (Cannabis use) clinical settings and psychological trait (fluid intelligence). The typical prediction procedure from rest-fMRI consists of three main steps: defining brain regions, representing the interactions, and supervised learning. For each step we benchmark typical choices: 8 different ways of defining regions -either pre-defined or generated from the rest-fMRI data- 3 measures to build functional connectomes from the extracted time-series, and 10 classification models to compare functional interactions across subjects. Our benchmarks summarize more than 240 different pipelines and outline modeling choices that show consistent prediction performances in spite of variations in the populations and sites. We find that regions defined from functional data work best; that it is beneficial to capture between-region interactions with tangent-based parametrization of covariances, a midway between correlations and partial correlation; and that simple linear predictors such as a logistic regression give the best predictions. Our work is a step forward to establishing reproducible imaging-based biomarkers for clinical settings.

PMID: 30836146 [PubMed - as supplied by publisher]

Normalization enhances brain network features that predict individual intelligence in children with epilepsy.

PLoS One. 2019;14(3):e0212901

Authors: Paldino MJ, Golriz F, Zhang W, Chu ZD

Abstract
BACKGROUND AND PURPOSE: Architecture of the cerebral network has been shown to associate with IQ in children with epilepsy. However, subject-level prediction on this basis, a crucial step toward harnessing network analyses for the benefit of children with epilepsy, has yet to be achieved. We compared two network normalization strategies in terms of their ability to optimize subject-level inferences on the relationship between brain network architecture and brain function.
MATERIALS AND METHODS: Patients with epilepsy and resting state fMRI were retrospectively identified. Brain network nodes were defined by anatomic parcellation, first in patient space (nodes defined for each patient) and again in template space (same nodes for all patients). Whole-brain weighted graphs were constructed according to pair-wise correlation of BOLD-signal time courses between nodes. The following metrics were then calculated: clustering coefficient, transitivity, modularity, path length, and global efficiency. Metrics computed on graphs in patient space were normalized to the same metric computed on a random network of identical size. A machine learning algorithm was used to predict patient IQ given access to only the network metrics.
RESULTS: Twenty-seven patients (8-18 years) comprised the final study group. All brain networks demonstrated expected small world properties. Accounting for intrinsic population heterogeneity had a significant effect on prediction accuracy. Specifically, transformation of all patients into a common standard space as well as normalization of metrics to those computed on a random network both substantially outperformed the use of non-normalized metrics.
CONCLUSION: Normalization contributed significantly to accurate subject-level prediction of cognitive function in children with epilepsy. These findings support the potential for quantitative network approaches to contribute clinically meaningful information in children with neurological disorders.

PMID: 30835738 [PubMed - in process]

Altered limbic and autonomic processing supports brain-heart axis in Takotsubo syndrome.

Eur Heart J. 2019 Mar 05;:

Authors: Templin C, Hänggi J, Klein C, Topka MS, Hiestand T, Levinson RA, Jurisic S, Lüscher TF, Ghadri JR, Jäncke L

Abstract
AIMS: Takotsubo syndrome (TTS) is characterized by acute left ventricular dysfunction often triggered by emotional or physical stress. Severe activation of the sympathetic nervous system with catecholamine release caused by a dysfunctional limbic system has been proposed as a potential mechanism. We hypothesize that brain regions responsible for autonomic integration and/or limbic processing might be involved in the development of TTS. Here, we investigated alterations in resting state functional connectivity in TTS patients compared with healthy controls.
METHODS AND RESULTS: Using brain functional magnetic resonance imaging (fMRI), resting state functional connectivity has been assessed in 15 subjects with TTS and 39 healthy controls. Network-based statistical analyses were conducted to identify subnetworks with altered resting state functional connectivity. Sympathetic and parasympathetic networks have been constructed in addition to the default mode network and whole-brain network. We found parasympathetic- and sympathetic-associated subnetworks both showing reduced resting state functional connectivity in TTS patients compared with controls. Important brain regions constituting parasympathetic- and sympathetic-associated subnetworks included the amygdala, hippocampus, and insula as well as cingulate, parietal, temporal, and cerebellar regions. Additionally, the default mode network as well as limbic regions in the whole-brain analysis demonstrated reduced resting state functional connectivity in TTS, including the hippocampus, parahippocampal, and medial prefrontal regions.
CONCLUSION: For the first time, we demonstrate hypoconnectivity of central brain regions associated with autonomic functions and regulation of the limbic system in patients with TTS. These findings suggest that autonomic-limbic integration might play an important role in the pathophysiology and contribute to the understanding of TTS.

PMID: 30831580 [PubMed - as supplied by publisher]

Overlapping Brain Community Detection Using Bayesian Tensor Decomposition.

J Neurosci Methods. 2019 Mar 01;:

Authors: Mirzaei S, Soltanian-Zadeh H

Abstract
It has been found that specific regions in the brain are dedicated to specific functions. Detection and analysis of the constituent functional networks of the brain is of great importance for understanding the brain functionality and diagnosing some neuropsychiatric illnesses. In this paper, we introduce Non-negative Tensor Factorization (NTF) methods to identify the overlapping communities in brain networks using resting-state functional Magnetic Resonance Imaging (rs-fMRI) data. Instead of taking average over a group of subjects, we use individual subject connectivity matrices to build the tensor data. Decomposed factors indicate the community membership probabilities and inter-subject variability indices modeling the community strengths over subjects. In contrast to the methods based on Non-negative Matrix Factorization (NMF) which are generally applied to the average connectivity matrices, using tensor factorization modeling preserves the information conveyed by the individual subjects. The experiments are carried out on simulated data as well as real Human Connectome Project (HCP) rs-fMRI datasets. To evaluate the effectiveness of the proposed framework, we have computed reproducibility over time and groups of subjects. Test-retest reliability is also examined through computing the intra-class correlation coefficient (ICC) index. The results show that the proposed NTF-based frameworks lead to stable and accurate results.

PMID: 30831137 [PubMed - as supplied by publisher]

Resting-state fMRI effective connectivity between the bed nucleus of the stria terminalis and amygdala nuclei.

Hum Brain Mapp. 2019 Mar 04;:

Authors: Hofmann D, Straube T

Abstract
The bed nucleus of the stria terminalis (BNST) and the laterobasal nucleus (LB), centromedial nucleus (CM), and superficial nucleus (SF) of the amygdala form an interconnected dynamical system, whose combined activity mediates a variety of behavioral and autonomic responses in reaction to homeostatic challenges. Although previous research provided deeper insight into the structural and functional connections between these nuclei, studies investigating their resting-state functional magnetic resonance imaging (fMRI) connectivity were solely based on undirected connectivity measures. Here, we used high-quality data of 391 subjects from the Human Connectome Project to estimate the effective connectivity (EC) between the BNST, the LB, CM, and SF through spectral dynamic causal modeling, the relation of the EC estimates with age and sex as well as their stability over time. Our results reveal a time-stable asymmetric EC structure with positive EC between all amygdala nuclei, which strongly inhibited the BNST while the BNST exerted positive influence onto all amygdala nuclei. Simulation of the impulse response of the estimated system showed that this EC structure shapes partially antagonistic (out of phase) activity flow between the BNST and amygdala nuclei. Moreover, the BNST-LB and BNST-CM EC parameters were less negative in males. In conclusion, our data points toward partially separated information processing between BNST and amygdala nuclei in the resting-state.

PMID: 30829454 [PubMed - as supplied by publisher]

A review of hippocampal activation in post-traumatic stress disorder.

Psychophysiology. 2019 Mar 04;:e13357

Authors: Joshi SA, Duval ER, Kubat B, Liberzon I

Abstract
Post-traumatic stress disorder (PTSD) is often characterized by deficits in memory encoding and retrieval and aberrant fear and extinction learning. The hippocampus plays a critical role in memory and contextual processing and has been implicated in intrinsic functional connectivity networks involved in self-referential thought and memory-related processes. This review focuses on hippocampal activation findings during memory and fear and extinction learning tasks, as well as resting state hippocampal connectivity in individuals with PTSD. A preponderance of functional neuroimaging studies to date, using memory, fear learning, and extinction tasks, report decreased or "controls comparable" hippocampal activation in individuals with PTSD, which is usually associated with poorer performance on the task imaged. Existing evidence thus raises the possibility that greater hippocampal recruitment in PTSD participants may be required for similar performance levels. Studies of resting state functional connectivity in PTSD predominantly report reduced within-network connectivity in the default mode network (DMN), as well as greater coupling between the DMN and salience network (SN) via the hippocampus. Together, these findings suggest that deficient hippocampal activation in PTSD may be associated with poorer performance during memory, extinction recall, and fear renewal tasks. Furthermore, studies of resting state connectivity implicate the hippocampus in decreased within-network DMN connectivity and greater coupling with SN regions characteristic of PTSD.

PMID: 30829407 [PubMed - as supplied by publisher]

Altered organization of the dorsal attention network is associated with freezing of gait in Parkinson's disease.

Parkinsonism Relat Disord. 2019 Feb 23;:

Authors: Maidan I, Jacob Y, Giladi N, Hausdorff JM, Mirelman A

Abstract
INTRODUCTION: Deficits in executive function and attention have been associated with freezing of gait (FOG) in patients with Parkinson's disease (PD). However, the exact changes in the ventral and dorsal attentional networks that may contribute to FOG are unknown. Our aim was to examine the changes in connectivity of the attentional networks in patients with PD and their role in FOG.
METHODS: Resting-state fMRI was obtained in 20 healthy controls (age: 69.7 ± 1.3yrs), 11 patients without FOG (age: 74.1 ± 1.2yrs), and 26 patients with FOG (age: 72.3 ± 1.3yrs). Graph theory analysis was used to examine differences in previously defined attention networks between groups.
RESULTS: We found differences between the groups in the dorsal attentional network (Global Efficiency: p = 0.007, Local Efficiency: p = 0.017, Between Centrality: p = 0.010). Global efficiency was lower in patients with FOG compared to healthy controls (p = 0.003) and patients without FOG (p = 0.025). Local efficiency was higher in patients with FOG compared to healthy controls (p = 0.014) but not compared to patients without FOG (p = 0.109). In contrast, no differences were found in the ventral attentional network between the groups (Global Efficiency: p = 0.258, Local Efficiency: p = 0.114, Between Centrality: p = 0.130).
CONCLUSIONS: Altered organization of the dorsal attention network in patients with FOG may explain the higher risk for FOG during complex walking situations. In contrast, the lack of changes in the ventral attention network may partially explain the effectiveness of external cues on gait in patients with PD. Our findings support the idea that attentional networks play an important role in FOG.

PMID: 30827838 [PubMed - as supplied by publisher]

Baseline effective connectivity predicts response to repetitive transcranial magnetic stimulation in patients with treatment-resistant depression.

Eur Neuropsychopharmacol. 2019 Feb 28;:

Authors: Iwabuchi SJ, Auer DP, Lankappa ST, Palaniyappan L

Abstract
Repetitive transcranial magnetic stimulation (rTMS) has become a popular treatment option for treatment-resistant depression (TRD). However, suboptimal response rates highlight the need for improved efficacy through optimisation of treatment protocol and patient selection. We investigate whether the limbic salience network and its connectivity with prefrontal stimulation sites predict immediate and longer-term responsiveness to rTMS. Twenty-seven patients with TRD were randomly allocated to receive 16 sessions of either conventional rTMS or intermittent theta-burst (iTBS) over 4 weeks; delivered using connectivity profiling and neuronavigation to target person-specific dorsolateral prefrontal cortex (DLPFC). At baseline and 3-month follow-up, patients underwent clinical assessment and scanning session, and 1-month clinical follow-up. Resting-state fMRI data were entered into seed-based functional and effective connectivity analyses between right anterior insula (rAI) and DLPFC target, and independent components analysis to extract resting-state networks. Cerebral blood flow (CBF) was also assessed in the rAI. All brain measures were compared between baseline and follow-up, and related to treatment response at 1- and 3-months. Baseline fronto-insular effective connectivity and salience network connectivity were significantly positively correlated, while baseline rAI CBF was negatively correlated, with early (1-month) response to rTMS treatment but not sustained response (3-months), suggesting persistence of therapeutic response is not associated with baseline features. Connectivity or CBF measures did not change between the two time points. We demonstrate that fronto-insular and salience-network interactions can predict early response to rTMS in TRD, suggesting that these network nodes may be key regions toward developing rTMS response biomarkers.

PMID: 30827757 [PubMed - as supplied by publisher]

Phase fMRI informs whole-brain function connectivity balance across lifespan with connection-specific aging effects during the resting state.

Brain Struct Funct. 2019 Mar 02;:

Authors: Chen Z, Zhou Q, Calhoun V

Abstract
A functional magnetic resonance imaging (fMRI) experiment produces complex-valued images consisting of pairwise magnitude and phase images. As different perspective on the same magnetic source, fMRI magnitude and phase data are complementary for brain function analysis. We collected 600-subject fMRI data during rest, decomposed via group-level independent component analysis (ICA) (mICA and pICA for magnitude and phase respectively), and calculated brain functional network connectivity matrices (mFC and pFC). The pFC matrix shows a fewer of significant connections balanced across positive and negative relationships. In comparison, the mFC matrix contains a positively-biased pattern with more significant connections. Our experiment data analyses also show that human brain maintains a whole-brain connection balance in resting state across an age span from 10 to 76 years, however, phase and magnitude data analyses reveal different connection-specific age effects on significant positive and negative subnetwork couplings.

PMID: 30826929 [PubMed - as supplied by publisher]

Exploring Brain Mechanisms Underlying Gulf War Illness with Group ICA based Analysis of fMRI Resting State Networks.

Neurosci Lett. 2019 Feb 27;:

Authors: Gopinath KS, Sakoglu U, Crosson BA, Haley RW

Abstract
Around 200,000 veterans (up to 32% of those deployed) of the 1991 Gulf War (GW) suffer from GW illness (GWI), which is characterized by multiple deficits in cognitive, affective, sensory and nociception domains. In this study we employed resting state fMRI (rsfMRI) to map impairments in brain function in GWI with advanced network analysis. RsfMRI data was obtained from 60 GWI veterans and 30 age-matched military controls. Group independent component analysis (GICA) was conducted to probe the functional connectivity networks in all 90 subjects. GICA revealed impaired functional connectivity (FC) in GWI veterans between a number of brain function networks consistent with their self-reported symptoms. GWI veterans exhibited impaired FC between language networks, and sensory input networks of all modalities as well as motor output networks. GWI veterans also exhibited impaired FC between different sensory perception and motor networks, and between different networks in the sensorimotor domain. These FC impairments provide putative mechanism of central nervous system dysfunction in GWI.

PMID: 30825590 [PubMed - as supplied by publisher]

The Intrinsic Neural Architecture of Inhibitory Control: The Role of Development and Emotional Experience.

Neuropsychologia. 2019 Feb 26;:

Authors: Petrican R, Grady CL

Abstract
Inhibitory control is a key determinant of goal-directed behavior. Its susceptibility to reward implies that its variations may not only reflect cognitive ability, but also sensitivity to goal-relevant information. Since cognitive ability and motivational sensitivity vary as a function of age and mood, we hypothesized that their relevance for predicting individual differences in inhibition would similarly vary. Here, we tested this prediction with respect to the brain's intrinsic functional architecture. Specifically, we reasoned that age and affective functioning would both moderate the relationship between inhibition and resting state expression of the dynamic neural organization patterns linked to engaging in cognitive effort versus those involved in manipulating motivationally salient information. First, we used task fMRI data from the Human Connectome Project (N=359 participants) to identify the brain organization patterns unique to effortful cognitive processing versus manipulation of motivationally relevant information. We then assessed the association between inhibitory control and relative expression of these two neural patterns in an independent resting state dataset from the Nathan Kline Institute-Rockland lifespan sample (N=247). As hypothesized, the relation between inhibition and intrinsic functional brain architecture varied as a function of age and affective functioning. Among those with superior affective functioning, better inhibitory control in adolescence and early adulthood was associated with stronger resting state expression of the brain pattern that typified processing of motivationally salient information. The opposite effect emerged beyond the age of 49. Among individuals with poorer affective functioning, a significant link between inhibition and brain architecture emerged only before the age of 28. In this group, superior inhibition was associated with stronger resting state expression of the neural pattern that typified effortful cognitive processing. Our results thus imply that motivational relevance makes a unique contribution to superior cognitive functioning during earlier life stages. However, its relevance to higher-order mentation decreases with aging and increased prevalence of mood-related problems, which raises the possibility that patterns of neurobehavioral responsiveness to motivational salience may constitute sensitive markers of successful lifespan development.

PMID: 30822448 [PubMed - as supplied by publisher]

Resting-state networks and neurometabolites in children with ADHD after 10 weeks of treatment with micronutrients: results of a randomised placebo-controlled trial.

Nutr Neurosci. 2019 Mar 01;:1-11

Authors: Borlase N, Melzer TR, Eggleston MJF, Darling KA, Rucklidge JJ

Abstract
Children with attention-deficit/hyperactivity disorder (ADHD) show significant abnormalities on MR imaging in network communication and connectivity. The prefrontal-striatal-cerebella circuitry, involved in attention is particularly disrupted. Neurometabolites, the biochemical structures that support neurological structural integrity, particularly in the prefrontal cortex and striatum are associated with symptoms. This study aimed to explore changes in neurometabolite levels through treatment with vitamins and minerals (micronutrients), hypothesising that treatment would impact neural circuitry and correspond to a reduction in symptoms. Twenty-seven non-medicated children (M = 10.75 years) with DSM5 diagnosed ADHD were randomised to receive daily micronutrients or placebo for 10 weeks. Main outcome measures included the Clinical Global Impression-Improvement Scale and ADHD-RS-IV Clinician Ratings of ADHD symptoms. Magnetic resonance spectroscopy of the bilateral pre-frontal cortex and bilateral striatum, resting state fMRI and structural images were acquired 1 week pre-treatment, and in the last week of intervention. Results did not show any significant differences in the measured brain metrics and the levels of neurometabolites between treatment and placebo groups after ten weeks of treatment with micronutrients. In the treatment group there was a trend for: decreased choline in the striatum; decreased glutamate in the prefrontal cortex; increased grey matter in the anterior thalamus; increased white matter in the fornix and improved network integrity of the default mode network, dorsal attention network and frontal executive network. The small sample size of the current study limits results, future studies with higher power are warranted to explore any association between micronutrient treatment and neurological changes.

PMID: 30821654 [PubMed - as supplied by publisher]