Most recent paper

Large-scale intrinsic connectivity is consistent across varying task demands.

PLoS One. 2019;14(4):e0213861

Authors: Kieliba P, Madugula S, Filippini N, Duff EP, Makin TR

Abstract
Measuring whole-brain functional connectivity patterns based on task-free ('resting-state') spontaneous fluctuations in the functional MRI (fMRI) signal is a standard approach to probing habitual brain states, independent of task-specific context. This view is supported by spatial correspondence between task- and rest-derived connectivity networks. Yet, it remains unclear whether intrinsic connectivity observed in a resting-state acquisition is persistent during task. Here, we sought to determine how changes in ongoing brain activation, elicited by task performance, impact the integrity of whole-brain functional connectivity patterns (commonly termed 'resting state networks'). We employed a 'steady-states' paradigm, in which participants continuously executed a specific task (without baseline periods). Participants underwent separate task-based (visual, motor and visuomotor) or task-free (resting) steady-state scans, each performed over a 5-minute period. This unique design allowed us to apply a set of traditional resting-state analyses to various task-states. In addition, a classical fMRI block-design was employed to identify individualized brain activation patterns for each task, allowing us to characterize how differing activation patterns across the steady-states impact whole-brain intrinsic connectivity patterns. By examining correlations across segregated brain regions (nodes) and the whole brain (using independent component analysis) using standard resting-state functional connectivity (FC) analysis, we show that the whole-brain network architecture characteristic of the resting-state is comparable across different steady-task states, despite striking inter-task changes in brain activation (signal amplitude). Changes in functional connectivity were detected locally, within the active networks. But to identify these local changes, the contributions of different FC networks to the global intrinsic connectivity pattern had to be isolated. Together, we show that intrinsic connectivity underlying the canonical resting-state networks is relatively stable even when participants are engaged in different tasks and is not limited to the resting-state.

PMID: 30970031 [PubMed - in process]

Why Is Aging a Risk Factor for Cognitive Impairment in Parkinson's Disease?-A Resting State fMRI Study.

Front Neurol. 2019;10:267

Authors: Nagano-Saito A, Bellec P, Hanganu A, Jobert S, Mejia-Constain B, Degroot C, Lafontaine AL, Lissemore JI, Smart K, Benkelfat C, Monchi O

Abstract
Using resting-state functional MRI (rsfMRI) data of younger and older healthy volunteers and patients with Parkinson's disease (PD) with and without mild cognitive impairment (MCI) and applying two different analytic approaches, we investigated the effects of age, pathology, and cognition on brain connectivity. When comparing rsfMRI connectivity strength of PD patients and older healthy volunteers, reduction between multiple brain regions in PD patients with MCI (PD-MCI) compared with PD patients without MCI (PD-non-MCI) was observed. This group difference was not affected by the number and location of clusters but was reduced when age was included as a covariate. Next, we applied a graph-theory method with a cost-threshold approach to the rsfMRI data from patients with PD with and without MCI as well as groups of younger and older healthy volunteers. We observed decreased hub function (measured by degree and betweenness centrality) mainly in the medial prefrontal cortex (mPFC) in older healthy volunteers compared with younger healthy volunteers. We also found increased hub function in the posterior medial structure (precuneus and the cingulate cortex) in PD-non-MCI patients compared with older healthy volunteers and PD-MCI patients. Hub function in these posterior medial structures was positively correlated with cognitive function in all PD patients. Together these data suggest that overlapping patterns of hub modifications could mediate the effect of age as a risk factor for cognitive decline in PD, including age-related reduction of hub function in the mPFC, and recruitment availability of the posterior medial structure, possibly to compensate for impaired basal ganglia function.

PMID: 30967835 [PubMed]

Early Stage Alterations in White Matter and Decreased Functional Interhemispheric Hippocampal Connectivity in the 3xTg Mouse Model of Alzheimer's Disease.

Front Aging Neurosci. 2019;11:39

Authors: Manno FAM, Isla AG, Manno SHC, Ahmed I, Cheng SH, Barrios FA, Lau C

Abstract
Alzheimer's disease (AD) is characterized in the late stages by amyloid-β (Aβ) plaques and neurofibrillary tangles. Nevertheless, recent evidence has indicated that early changes in cerebral connectivity could compromise cognitive functions even before the appearance of the classical neuropathological features. Diffusion tensor imaging (DTI), resting-state functional magnetic resonance imaging (rs-fMRI) and volumetry were performed in the triple transgenic mouse model of AD (3xTg-AD) at 2 months of age, prior to the development of intraneuronal plaque accumulation. We found the 3xTg-AD had significant fractional anisotropy (FA) increase and radial diffusivity (RD) decrease in the cortex compared with wild-type controls, while axial diffusivity (AD) and mean diffusivity (MD) were similar. Interhemispheric hippocampal connectivity was decreased in the 3xTg-AD while connectivity in the caudate putamen (CPu) was similar to controls. Most surprising, ventricular volume in the 3xTg-AD was four times larger than controls. The results obtained in this study characterize the early stage changes in interhemispheric hippocampal connectivity in the 3xTg-AD mouse that could represent a translational biomarker to human models in preclinical stages of the AD.

PMID: 30967770 [PubMed]

Migraine in the Young Brain: Adolescents vs. Young Adults.

Front Hum Neurosci. 2019;13:87

Authors: Colon E, Ludwick A, Wilcox SL, Youssef AM, Danehy A, Fair DA, Lebel AA, Burstein R, Becerra L, Borsook D

Abstract
Migraine is a disease that peaks in late adolescence and early adulthood. The aim of this study was to evaluate age-related brain changes in resting state functional connectivity (rs-FC) in migraineurs vs. age-sex matched healthy controls at two developmental stages: adolescence vs. young adulthood. The effect of the disease was assessed within each developmental group and age- and sex-matched healthy controls and between developmental groups (migraine-related age effects). Globally the within group comparisons indicated more widespread abnormal rs-FC in the adolescents than in the young adults and more abnormal rs-FC associated with sensory networks in the young adults. Direct comparison of the two groups showed a number of significant changes: (1) more connectivity changes in the default mode network in the adolescents than in the young adults; (2) stronger rs-FC in the cerebellum network in the adolescents in comparison to young adults; and (3) stronger rs-FC in the executive and sensorimotor network in the young adults. The duration and frequency of the disease were differently associated with baseline intrinsic connectivity in the two groups. fMRI resting state networks demonstrate significant changes in brain function at critical time point of brain development and that potentially different treatment responsivity for the disease may result.

PMID: 30967767 [PubMed]

Salience network connectivity is reduced by a meal and influenced by genetic background and hypothalamic gliosis.

Int J Obes (Lond). 2019 Apr 09;:

Authors: Sewaybricker LE, Melhorn SJ, Askren MK, Webb MF, Tyagi V, De Leon MRB, Grabowski TJ, Seeley WW, Schur EA

Abstract
BACKGROUND/OBJECTIVES: The salience network (SN) comprises brain regions that evaluate cues in the external environment in light of internal signals. We examined the SN response to meal intake and potential genetic and acquired influences on SN function.
SUBJECTS/METHODS: Monozygotic (MZ; 40 pairs) and dizygotic (15 pairs) twins had body composition and plasma metabolic profile evaluated (glucose, insulin, leptin, ghrelin, and GLP-1). Twins underwent resting-state functional magnetic resonance imaging (fMRI) scans before and after a standardized meal. The strength of SN connectivity was analyzed pre- and post-meal and the percentage change elicited by a meal was calculated. A multi-echo T2 MRI scan measured T2 relaxation time, a radiologic index of gliosis, in the mediobasal hypothalamus (MBH) and control regions. Statistical approaches included intraclass correlations (ICC) to investigate genetic influences and within-pair analyses to exclude genetic confounders.
RESULTS: SN connectivity was reduced by a meal ingestion (β = -0.20; P < 0.001). Inherited influences on both pre- and post-meal connectivity were present (ICC MZ twins 26%, P < 0.05 and 47%, P < 0.001, respectively), but not percentage change in response to the meal. SN connectivity in response to a meal did not differ between participants with obesity and of normal weight (χ2(1) = 0.93; P = 0.33). However, when participants were classified as having high or low signs of MBH gliosis, the high MBH gliosis group failed to reduce the connectivity in response to a meal (z = -1.32; P = 0.19). Excluding genetic confounders, the percentage change in SN connectivity by a meal correlated to body fat percentage (r = 0.24; P < 0.01).
CONCLUSIONS: SN connectivity was reduced by a meal, indicating potential participation of the SN in control of feeding. The strength of SN connectivity is inherited, but the degree to which SN connectivity is reduced by eating appears to be influenced by adiposity and the presence of hypothalamic gliosis.

PMID: 30967608 [PubMed - as supplied by publisher]

Effect of second-generation antipsychotics on brain network topology in first-episode schizophrenia: A longitudinal rs-fMRI study.

Schizophr Res. 2019 Apr 07;:

Authors: Wang LX, Guo F, Zhu YQ, Wang HN, Liu WM, Li C, Wang XR, Cui LB, Xi YB, Yin H

Abstract
OBJECTIVE: We aimed to evaluate the functional network properties in first-episode schizophrenia (SZ) patients at baseline and after 4-months treatment with second-generation antipsychotic drugs.
METHODS: Resting-state functional magnetic resonance imaging and graph theory approaches were utilized to evaluate the functional integration and segregation of brain networks in 36 first-episode patients (20 male/16 female) with SZ and 36 age and sex matched healthy controls (20 male/16 female).
RESULTS: Compared with healthy controls, SZ at baseline showed lower clustering coefficient (Cp) and local network efficiency (Eloc), and this abnormal pattern was modulated with treatment of antipsychotic drugs at follow-up. Longitudinally, the increase of Cp was associated with the improvement of negative symptom. We found that the strength of functional connectivity between brain regions were significantly increased in three connections after treatment, mainly involving the frontal, parietal and occipital lobes.
CONCLUSION: The current study suggested that antipsychotic drugs could modulate the faulty local clustering of the functional connectome in SZ. Furthermore, Cp, the parameter that reflects local clustering of topological organization, demonstrated the potential to be a connectome-based biomarker of treatment response to second-generation antipsychotics in patients with SZ.

PMID: 30967317 [PubMed - as supplied by publisher]

Psilocybin-assisted mindfulness training modulates self-consciousness and brain default mode network connectivity with lasting effects.

Neuroimage. 2019 Apr 06;:

Authors: Smigielski L, Scheidegger M, Kometer M, Vollenweider FX

Abstract
Both psychedelics and meditation exert profound modulatory effects on consciousness, perception and cognition, but their combined, possibly synergistic effects on neurobiology are unknown. Accordingly, we conducted a randomized, double-blind, placebo-controlled study with 38 participants following a single administration of the psychedelic psilocybin (315 μg/kg p.o.) during a 5-day mindfulness retreat. Brain dynamics were quantified directly pre- and post-intervention by functional magnetic resonance imaging during the resting state and two meditation forms. The analysis of functional connectivity identified psilocybin-related and mental-state-dependent alterations in self-referential processing regions of the default mode network (DMN). Notably, decoupling of medial prefrontal and posterior cingulate cortices, which is thought to mediate sense of self, was associated with the subjective ego dissolution effect during the psilocybin-assisted mindfulness session. The extent of ego dissolution and brain connectivity predicted positive changes in psycho-social functioning of participants 4 months later. Psilocybin, combined with meditation, facilitated neurodynamic modulations in self-referential networks, subserving the process of meditation by acting along the anterior-posterior DMN connection. The study highlights the link between altered self-experience and subsequent behavioral changes. Understanding how interventions facilitate transformative experiences may open novel therapeutic perspectives. Insights into the biology of discrete mental states foster our understanding of non-ordinary forms of human self-consciousness, and their concomitant brain substrate.

PMID: 30965131 [PubMed - as supplied by publisher]

Changes in white-matter functional network efficiency across the adult lifespan.

Neuroreport. 2019 Apr 05;:

Authors: Niu H, Zhu J, Wang C, Zhu L, Wu J

Abstract
Previous studies have used resting-state functional MRI (rs-fMRI) and graph-theory approaches to investigate the lifespan trajectory of the topological organization of the gray-matter functional networks. Recent evidences have suggested that rs-fMRI data can also be used to estimate white-matter function, challenging the conventional practice of taking white-matter signals as noise or artifacts. Here, we examined the correlation between age and white-matter functional network efficiency by applying graph-theory to a large sample of rs-fMRI data of 435 participants. We found that age was correlated negatively with both global and local efficiency of the white-matter functional networks. These findings suggest decreasing white-matter functional network efficiency during the aging process, which provides a complement to conventional gray-matter functional network studies.

PMID: 30964767 [PubMed - as supplied by publisher]

Diagnosis of Autism Spectrum Disorders in Young Children Based on Resting-State Functional Magnetic Resonance Imaging Data Using Convolutional Neural Networks.

J Digit Imaging. 2019 Apr 08;:

Authors: Aghdam MA, Sharifi A, Pedram MM

Abstract
Statistics show that the risk of autism spectrum disorder (ASD) is increasing in the world. Early diagnosis is most important factor in treatment of ASD. Thus far, the childhood diagnosis of ASD has been done based on clinical interviews and behavioral observations. There is a significant need to reduce the use of traditional diagnostic techniques and to diagnose this disorder in the right time and before the manifestation of behavioral symptoms. The purpose of this study is to present the intelligent model to diagnose ASD in young children based on resting-state functional magnetic resonance imaging (rs-fMRI) data using convolutional neural networks (CNNs). CNNs, which are by far one of the most powerful deep learning algorithms, are mainly trained using datasets with large numbers of samples. However, obtaining comprehensive datasets such as ImageNet and achieving acceptable results in medical imaging domain have become challenges. In order to overcome these two challenges, the two methods of "combining classifiers," both dynamic (mixture of experts) and static (simple ‌Bayes) approaches, and "transfer learning" were used in this analysis. In addition, since diagnosis of ASD will be much more effective at an early age, samples ranging in age from 5 to 10 years from global Autism Brain Imaging Data Exchange I and II (ABIDE I and ABIDE II) datasets were used in this research. The accuracy, sensitivity, and specificity of presented model outperform the results of previous studies conducted on ABIDE I dataset (the best results obtained from Adamax optimization technique: accuracy = 0.7273, sensitivity = 0.712, specificity = 0.7348). Furthermore, acceptable classification results were obtained from ABIDE II dataset (the best results obtained from Adamax optimization technique: accuracy = 0.7, sensitivity = 0.582, specificity = 0.804) and the combination of ABIDE I and ABIDE II datasets (the best results obtained from Adam optimization technique: accuracy = 0.7045, sensitivity = 0.679, specificity = 0.7421). We can conclude that the proposed architecture can be considered as an efficient tool for diagnosis of ASD in young children. From another perspective, this proposed method can be applied to analyzing rs-fMRI data related to brain dysfunctions.

PMID: 30963340 [PubMed - as supplied by publisher]

Childhood trauma history is linked to abnormal brain connectivity in major depression.

Proc Natl Acad Sci U S A. 2019 Apr 08;:

Authors: Yu M, Linn KA, Shinohara RT, Oathes DJ, Cook PA, Duprat R, Moore TM, Oquendo MA, Phillips ML, McInnis M, Fava M, Trivedi MH, McGrath P, Parsey R, Weissman MM, Sheline YI

Abstract
Patients with major depressive disorder (MDD) present with heterogeneous symptom profiles, while neurobiological mechanisms are still largely unknown. Brain network studies consistently report disruptions of resting-state networks (RSNs) in patients with MDD, including hypoconnectivity in the frontoparietal network (FPN), hyperconnectivity in the default mode network (DMN), and increased connection between the DMN and FPN. Using a large, multisite fMRI dataset (n = 189 patients with MDD, n = 39 controls), we investigated network connectivity differences within and between RSNs in patients with MDD and healthy controls. We found that MDD could be characterized by a network model with the following abnormalities relative to controls: (i) lower within-network connectivity in three task-positive RSNs [FPN, dorsal attention network (DAN), and cingulo-opercular network (CON)], (ii) higher within-network connectivity in two intrinsic networks [DMN and salience network (SAN)], and (iii) higher within-network connectivity in two sensory networks [sensorimotor network (SMN) and visual network (VIS)]. Furthermore, we found significant alterations in connectivity between a number of these networks. Among patients with MDD, a history of childhood trauma and current symptoms quantified by clinical assessments were associated with a multivariate pattern of seven different within- and between-network connectivities involving the DAN, FPN, CON, subcortical regions, ventral attention network (VAN), auditory network (AUD), VIS, and SMN. Overall, our study showed that traumatic childhood experiences and dimensional symptoms are linked to abnormal network architecture in MDD. Our results suggest that RSN connectivity may explain underlying neurobiological mechanisms of MDD symptoms and has the potential to serve as an effective diagnostic biomarker.

PMID: 30962366 [PubMed - as supplied by publisher]

Exploring common changes after acute mental stress and acute tryptophan depletion: Resting-state fMRI studies.

J Psychiatr Res. 2019 Apr 01;113:172-180

Authors: Zhang X, Huettel SA, Mullette-Gillman OA, Guo H, Wang L

Abstract
Stress and low serotonin levels are important biological factors in depression and anxiety etiologies. Although studies indicate that low serotonin levels, stress, and other factors may interact in depression/anxiety psychopathology, few studies have investigated the potentially shared neural substrates. We conducted resting-state fMRI scans pre- and post-stress task, and under control and tryptophan depletion condition, to explore the common changes induced by acute mental stress (AMS) and acute tryptophan depletion (ATD). The present study targeted regions within core brain networks - default mode network, salience network, executive control network, and emotion network - reported altered in AMS and ATD, and used regional homogeneity (ReHo) and functional connectivity (FC) analyses to explore their overlapped effects. We additionally examined the relationships among core neural networks - operationalized as an index of resource allocation bias that quantifies the shift from internal to external modes of processing. We found both manipulations induced increased ReHo of the amygdala and decreased ReHo of the posterior cingulate cortex (PCC). The PCC-amygdala FC was negatively correlated with the change of negative affect, whereas the right dorsolateral prefrontal cortex and right anterior insula FC was positively associated with anxiety level. In addition, we found that a greater shift to an external mode was correlated with higher anxiety level under both conditions. Common changes induced by acute mental stress and acute tryptophan depletion confirmed our hypothesis that AMS and ATD induce changes in common neural pathways, which in turn might mark vulnerability to depression and anxiety.

PMID: 30959228 [PubMed - as supplied by publisher]

Abnormal Brain Network Connectivity in a Triple-Network Model of Alzheimer's Disease.

J Alzheimers Dis. 2019 Apr 01;:

Authors: Li C, Li Y, Zheng L, Zhu X, Shao B, Fan G, Liu T, Wang J, and Alzheimer’s Disease Neuroimaging Initiative

Abstract
Resting-state fMRI studies have demonstrated that Alzheimer's disease (AD) is associated with aberrant organization and function of large-scale brain networks. However, the nature of the disruption of cross-network interactions in the key neurocognitive networks in the brain remains unclear. In this paper, we examined the 'triple-network model', including the default mode network (DMN), salience network (SN), and central executive network (CEN), to identify the cross-network interactions in late mild cognitive impairment (LMCI) and AD. With resting-state fMRI, we tested cross-network functional connectivity among the DMN, SN, and CEN in 33 AD patients, 24 LMCI, and 25 well-matched normal control subjects. Then, we identified the most influential brain regions affected by AD and LMCI. Finally, we investigated the relationship between aberrant functional connectivity and clinical cognitive dysfunction. We found the cross-network functional connectivity of the SN-centered 'triple-network model' was significantly impaired in the AD group and the alterations were negatively correlated with the Mini-Mental State Examination (MMSE) scores. For the LMCI group, the functional connectivity of the SN-centered 'triple-network model' also changed compared to AD; however, we found no correlation with MMSE score. As predicted, the abnormal connections among the three networks mainly overlap with the key nodes of the three networks. Overall, our findings suggested that the interactions of the SN-centered 'triple-network model' are impaired in AD patients and that these alterations contribute to the decline in cognitive function. This 'triple-network model' provides new insights into AD and provides more information about the dysregulation of brain networks in AD.

PMID: 30958354 [PubMed - as supplied by publisher]

Early-Stage Identification and Pathological Development of Alzheimer's Disease Using Multimodal MRI.

J Alzheimers Dis. 2019 Apr 01;:

Authors: Yan T, Wang Y, Weng Z, Du W, Liu T, Chen D, Li X, Wu J, Han Y

Abstract
Alzheimer's disease (AD) is one of the most common progressive and irreversible neurodegenerative diseases. The study of the pathological mechanism of AD and early-stage diagnosis is essential and important. Subjective cognitive decline (SCD), the first at-risk stage of AD occurring prior to amnestic mild cognitive impairment (aMCI), is of great research value and has gained our interest. To investigate the entire pathological development of AD pathology efficiently, we proposed a machine learning classification method based on a multimodal support vector machine (SVM) to investigate the structural and functional connectivity patterns of the three stages of AD (SCD, aMCI, and AD). Our experiments achieved an accuracy of 98.58% in the AD group, 97.76% in the aMCI group, and 80.24% in the SCD group. Moreover, in our experiments, we identified the most discriminating brain regions, which were mainly located in the default mode network and subcortical structures (SCS). Notably, with the development of AD pathology, SCS regions have become increasingly important, and structural connectivity has shown more discriminative power than functional connectivity. The current study may shed new light on the pathological mechanism of AD and suggests that whole-brain connectivity may provide potential effective biomarkers for the early-stage diagnosis of AD.

PMID: 30958352 [PubMed - as supplied by publisher]

Effect of Sex Hormones on Brain Connectivity Related to Sexual Function in Perimenopausal Women: A Resting-State fMRI Functional Connectivity Study.

J Sex Med. 2019 Apr 04;:

Authors: Lu W, Guo W, Cui D, Dong K, Qiu J

Abstract
BACKGROUND: Perimenopause is associated with increased risk of depression, vasomotor symptoms, and sexual dysfunction.
AIMS: To explore the effect of sex hormones on the functional connectivity (FC) of different brain regions related to sexual function in perimenopausal women.
METHODS: 32 premenopausal women (mean age, 47.75 ± 1.55 years) and 25 perimenopausal women (mean age, 51.60 ± 1.63 years) underwent sex hormone level measurements and resting-state fMRI.
MAIN OUTCOME MEASURES: Serum levels of sex hormones, including prolactin (PRL), follicle-stimulating hormone (FSH), luteotropic hormone (LH), estradiol (E2), free testosterone (free-T), and progesterone (P), were measured. 10 brain regions related to sexual function were selected according to a meta-analysis, and FCs of the selected regions of interest were calculated as Pearson's correlation coefficient.
RESULTS: Compared with premenopausal women, perimenopausal women showed increased FC between the right area 13 (A13_r) and the right medial superior frontal gyrus (mSFG), between the left dorsal granular insula (dIg_L) and the right superior frontal gyrus (SFG) (Gaussian random field-corrected at the voxel level, P < .001, and cluster level, P < .025). Furthermore, the PRL level was negatively correlated with the FC of A13_R with the right mSFG and the FC of dIg_L with the right SFG.
CLINICAL TRANSLATION: These findings may be applicable to assessing brain dysfunction with FC changes in women approaching menopause.
STRENGTHS & LIMITATIONS: This study is the first to evaluate a direct relationship between sex hormone levels and brain FC changes in women approaching menopause. Sexual function was not assessed, which may weaken the conclusions related to sexual function.
CONCLUSIONS: The results show that women approaching menopause suffered from aberrant intrinsic FC in regions related to sexual function, and reveal a direct relationship between serum sex hormone levels and FC changes related to sexual function. Lu W, Guo W, Cui D, et al. Effect of Sex Hormones on Brain Connectivity Related to Sexual Function in Perimenopausal Women: A Resting-State fMRI Functional Connectivity Study. J Sex Med 2019;XX:XXX-XXX.

PMID: 30956108 [PubMed - as supplied by publisher]

Resting-state functional connectivity networks associated with fatigue in multiple sclerosis with early age onset.

Mult Scler Relat Disord. 2019 Mar 30;31:101-105

Authors: Stefancin P, Govindarajan ST, Krupp L, Charvet L, Duong TQ

Abstract
BACKGROUND: Fatigue is one of the most commonly experienced symptoms in multiple sclerosis (MS). The neural correlates of fatigue in MS, in general and specifically in early onset, remain poorly understood. This study employed resting-state fMRI (rsfMRI) to investigate the functional connectivity of fatigue in MS patients with early age onset.
METHODS: Twenty-seven relapsing-remitting MS patients (20 ± 7yo at the age of diagnosis and 26.0 ± 5.5yo at the time of study) were recruited and 22 patients were studied. Structural and rsfMRI sequences were performed on a 3-Tesla Seimens MRI scanner. Seed-based analysis was performed using CONN Functional Connectivity Toolbox for Statistic Parametric Mapping. The Fatigue Severity Scale (FSS) and the Modified Fatigue Impact scale (MFIS) as well as EDSS, Beck Depression Inventory, and symptomatology were measured. Non-fatigued (N = 12) and fatigued patients (N = 10) were separated based on FSS scores, with a score of 5 or greater being classified as fatigued. Group differences in rsfMRI between non-fatigued and fatigued patients were analyzed. Correlations between these functional connectivity differences and behavioral fatigue scores were also analyzed.
RESULTS: Ages, disease duration, lesion load, lesion volume, and neurologic disability were not significantly different between non-fatigued and fatigued patients (p > 0.05). Fatigued patients showed significantly stronger connectivity between the right thalamus and right precentral gyrus (T = 4.58, p = 0.015), and a trending increase in connectivity between the left hippocampus and left precentral gyrus (T = 7.55, p = 0.051). Patients with fatigue showed significantly reduced connectivity between the right thalamus and left parietal operculum (T= -4.28, p = 0.0002), left thalamus and right superior frontal gyrus (T=-5.54, p = 0.046), and between the left insula and posterior cingulate (T=-9.4, p = 0.003). The connectivity between the left insula and posterior cingulate was significantly correlated with the cognitive score of MFIS (R2 = -0.471, p = 0.027) and FSS (R2 = -0.719, p = 0.0001). The connectivity between the right thalamus and left parietal operculum was significantly correlated with MFIS cognitive scores (R2 = -0.431, p = 0.045) and with FSS scores (R2 = 0.402, p = 0.006). Correlations remained significant after accounting for depression scores.
CONCLUSIONS: rsfMRI identified Alterations in two distinct connections (the connectivity between insula and posterior cingulate gyrus and between the right thalamus and right precentral gyrus) that differed between fatigued and non-fatigued patients, as well as correlated with cognitive fatigue severity. These findings suggest that disruption of sensorimotor, high-order motor, and non-motor executive function likely contributes to the neural mechanism of fatigue in MS. Knowledge of the neural mechanisms of underlying MS fatigue could inform more effective treatment strategies.

PMID: 30954931 [PubMed - as supplied by publisher]

Resting state functional connectivity and cognitive task-related activation of the human claustrum.

Neuroimage. 2019 Apr 04;:

Authors: Krimmel SR, White MG, Panicker MH, Barrett FS, Mathur BN, Seminowicz DA

Abstract
Structural and functional analyses of the human claustrum, a poorly understood telencephalic gray matter structure, are hampered by its sheet-like anatomical arrangement. Here, we first describe a functional magnetic resonance imaging (fMRI) method to reveal claustrum signal with no linear relationship with adjacent regions in human subjects. We applied this approach to resting state functional connectivity (RSFC) analysis of the claustrum at high resolution (1.5 mm isotropic voxels) using a 7T dataset (n = 20) and a separate 3T dataset for replication (n = 35). We then assessed claustrum activation during performance of a cognitive task, the multi-source interference task, at 3T (n = 33). Extensive functional connectivity was observed between claustrum and cortical regions associated with cognitive control, including anterior cingulate, prefrontal and parietal cortices. Cognitive task performance was associated with widespread activation and deactivation that overlapped with the cortical areas showing functional connectivity to the claustrum. Furthermore, during high cognitive conflict conditions of the task, the claustrum was significantly activated at the onset of the task, but not during the remainder of the difficult condition. Both of these findings suggest that the human claustrum can be functionally isolated with fMRI, and that it may play a role in cognitive control, and specifically task switching, independent of sensorimotor processing.

PMID: 30954711 [PubMed - as supplied by publisher]

Self-directed down-regulation of auditory cortex activity mediated by real-time fMRI neurofeedback augments attentional processes, resting cerebral perfusion, and auditory activation.

Neuroimage. 2019 Apr 04;:

Authors: Sherwood MS, Parker JG, Diller EE, Ganapathy S, Bennett KB, Esquivel CR, Nelson JT

Abstract
In this work, we investigated the use of real-time functional magnetic resonance imaging (fMRI) with neurofeedback training (NFT) to teach volitional down-regulation of the auditory cortex (AC) using directed attention strategies as there is a growing interest in the application of fMRI-NFT to treat neurologic disorders. Healthy participants were separated into two groups: the experimental group received real feedback regarding activity in the AC; the control group was supplied sham feedback yoked from a random participant in the experimental group and matched for fMRI-NFT experience. Each participant underwent five fMRI-NFT sessions. Each session contained 2 neurofeedback runs where participants completed alternating blocks of "rest" and "lower" conditions while viewing a continuously-updated bar representing AC activation and listening to continuous noise. Average AC deactivation was extracted from each closed-loop neuromodulation run and used to quantify the control over AC (AC control), which was found to significantly increase across training in the experimental group. Additionally, behavioral testing was completed outside of the MRI on sessions 1 and 5 consisting of a subjective questionnaire to assess attentional control and two quantitative tests of attention. No significant changes in behavior were observed; however, there was a significant correlation between changes in AC control and attentional control. Also, in a neural assessment before and after fMRI-NFT, AC activity in response to continuous noise stimulation was found to significantly decrease across training while changes in AC resting perfusion were found to be significantly greater in the experimental group. These results may be useful in formulating effective therapies outside of the MRI, specifically for chronic tinnitus which is often characterized by hyperactivity of the primary auditory cortex and altered attentional processes. Furthermore, the modulation of attention may be useful in developing therapies for other disorders such as chronic pain.

PMID: 30954710 [PubMed - as supplied by publisher]

Receptor-Enriched Analysis of functional connectivity by targets (REACT): A novel, multimodal analytical approach informed by PET to study the pharmacodynamic response of the brain under MDMA.

Neuroimage. 2019 Apr 03;:

Authors: Dipasquale O, Selvaggi P, Veronese M, Gabay AS, Turkheimer F, Mehta MA

Abstract
One of the main limitations of pharmacological fMRI is its inability to provide a molecular insight into the main effect of compounds, leaving an open question about the relationship between drug effects and haemodynamic response. The aim of this study is to investigate the acute effects of 3,4-methylenedioxymethamphetamine (MDMA) on functional connectivity (FC) using a novel multimodal method (Receptor-Enriched Analysis of functional Connectivity by Targets - REACT). This approach enriches the resting state (rs-)fMRI analysis with the molecular information about the distribution density of serotonin receptors in the brain, given the serotonergic action of MDMA. Twenty healthy subjects participated in this double-blind, placebo-controlled, crossover study. A high-resolution in vivo atlas of four serotonin receptors (5-HT1A, 5-HT1B, 5-HT2A, and 5-HT4) and its transporter (5-HTT) was used as a template in a two-step multivariate regression analysis to estimate the spatial maps reflecting the whole-brain connectivity behaviour related to each target under placebo and MDMA. Results showed that the networks exhibiting significant changes after MDMA administration are the ones informed by the 5-HTT and 5-HT1A distribution density maps, which are the main targets of this compound. Changes in the 5-HT1A-enriched functional maps were also associated with the pharmacokinetic levels of MDMA and MDMA-induced FC changes in the 5-HT2A-enriched maps correlated with the spiritual experience subscale of the Altered States of Consciousness Questionnaire. By enriching the rs-fMRI analysis with molecular data of voxel-wise distribution of the serotonin receptors across the brain, we showed that MDMA effects on FC can be understood through the distribution of its main targets. This result supports the ability of this method to characterise the specificity of the functional response of the brain to MDMA binding to serotonergic receptors, paving the way to the definition of a new fingerprint in the characterization of new compounds and potentially to a further understanding to the response to treatment.

PMID: 30953835 [PubMed - as supplied by publisher]

Recent Insights in Migraine With Aura: A Narrative Review of Advanced Neuroimaging.

Headache. 2019 Apr 06;:

Authors: Russo A, Silvestro M, Tessitore A, Tedeschi G

Abstract
INTRODUCTION: Migraine is a complex neurological disorder characterized by severe headaches associated with a plethora of sensory hypersensitivity and neurovegetative symptoms. In about one-third of the cases, a set of fully reversible focal neurological symptoms, the aura, accompanies the headache. In the last decades, advanced neuroimaging investigations allowed identification of structural, microstructural, and functional abnormalities characterizing the brain of patients with migraine with aura (MwA). However, mechanisms underlying the aura phenomena are still a matter of debate.
AIMS: This article reviews the most significant findings from advanced neuroimaging studies in patients with MwA both to provide a unifying physiopathological model of the aura phenomena and to clarify the potential impact of advanced neuroimaging investigation in the clinical field.
METHODS: A comprehensive review of PubMed citations was conducted by entering the key words "magnetic resonance imaging" combined with "migraine" AND "aura." Other key words included "grey matter" OR "white matter," "structural" OR "functional." The only restriction was to English-language publications. The abstracts of all articles published between 1997 and 2018 meeting these criteria were reviewed, and the full texts were examined for relevance to the topic.
CONCLUSION: Although several advanced neuroimaging studies have been conducted to investigate the neural correlates of aura phenomena, they have failed in identifying underlying pathophysiological mechanisms in their entirety. Nevertheless, functional and structural neuroimaging findings concerning the extrastriate visual cortex are characterized by a high level of reproducibility, so much so that they could be applied, in a not so far future, as diagnostic, prognostic, or therapeutic biomarkers for MwA.

PMID: 30953581 [PubMed - as supplied by publisher]

Association between NRGN gene polymorphism and resting-state hippocampal functional connectivity in schizophrenia.

BMC Psychiatry. 2019 Apr 05;19(1):108

Authors: Zhang Y, Gong X, Yin Z, Cui L, Yang J, Wang P, Zhou Y, Jiang X, Wei S, Wang F, Tang Y

Abstract
BACKGROUND: Based on genome-wide association studies, a single-nucleotide polymorphism in the NRGN gene (rs12807809) is considered associated with schizophrenia (SZ). Moreover, hippocampal dysfunction is associated with rs12807809. In addition, converging evidence suggests that hippocampal dysfunction is involved in SZ pathophysiology. However, the association among rs12807809, hippocampal dysfunction and SZ pathophysiology is unknown. Therefore, this study investigated the association between rs12807809 and hippocampal functional connectivity at rest in SZ.
METHODS: In total, 158 participants were studied, including a C-carrier group carrying the non-risk C allele (29 SZ patients and 46 healthy controls) and a TT homozygous group carrying the risk T allele (30 SZ patients and 53 healthy controls). All participants were scanned using resting-state functional magnetic resonance imaging. Hippocampal functional connectivity was computed and compared among the 4 groups.
RESULTS: Significant main effects of diagnosis were observed in the functional connectivity between the hippocampus and bilateral fusiform gyrus, bilateral lingual gyrus, left inferior temporal gyrus, left caudate nucleus, bilateral thalamus and bilateral anterior cingulate gyri. In contrast, no significant main effect of genotype was found. In addition, a significant genotype by diagnosis interaction in the functional connectivity between the hippocampus and left anterior cingulate gyrus, as well as bilateral middle cingulate gyri, was observed, with TT homozygotes with SZ showing less functional connectivity than C-carriers with SZ and healthy control TT homozygotes.
CONCLUSIONS: These findings are the first to suggest an association between rs12807809 and abnormal Papez circuit function in patients with SZ. This study also implicates NRGN variation and abnormal Papez circuit function in SZ pathophysiology.

PMID: 30953482 [PubMed - in process]