Most recent paper

Altered brain network centrality in patients with late monocular blindness: a resting-state fMRI study.

Arch Med Sci. 2019 Sep;15(5):1301-1307

Authors: Huang X, Li HJ, Peng DC, Ye L, Yang QC, Zhong YL, Zhou FQ, Shao Y

Abstract
Introduction: The aim of the study was to investigate the underlying functional network brain activity changes in patients with late monocular blindness (MB) and the relationship with their clinical features using the voxel-wise degree centrality (DC) method.
Material and methods: A total of 32 patients with MB (25 males and 7 females), and 32 healthy controls (HCs) (25 males and 7 females) closely matched in age, sex, and education, underwent resting-state functional magnetic resonance imaging scans. The DC method was used to assess local features of spontaneous brain activity. Correlation analysis was performed to explore the relationships between the observed mean DC signal values of the different areas and clinical features in these patients.
Results: Compared with HCs, MB patients had significantly lower DC values in the bilateral cuneus/V1/V2, and significantly higher DC values in the left inferior temporal gyrus and bilateral medial frontal gyrus. However, there was no relationship between the observed mean DC values of the different brain areas and the behavioral performance.
Conclusions: Late monocular blindness involves brain function network dysfunction in many regions, which might indicate impairment of the visual cortex and other vision-related brain regions in the MBs.

PMID: 31572477 [PubMed]

Brain Networks Reveal the Effects of Antipsychotic Drugs on Schizophrenia Patients and Controls.

Front Psychiatry. 2019;10:611

Authors: Towlson EK, Vértes PE, Müller-Sedgwick U, Ahnert SE

Abstract
The study of brain networks, including those derived from functional neuroimaging data, attracts a broad interest and represents a rapidly growing interdisciplinary field. Comparing networks of healthy volunteers with those of patients can potentially offer new, quantitative diagnostic methods and a framework for better understanding brain and mind disorders. We explore resting state functional Magnetic Resonance Imaging (fMRI) data through network measures. We construct networks representing 15 healthy individuals and 12 schizophrenia patients (males and females), all of whom are administered three drug treatments: i) a placebo; and two antipsychotic medications ii) aripiprazole and iii) sulpiride. We compare these resting state networks to a performance at an "N-back" working memory task. We demonstrate that not only is there a distinctive network architecture in the healthy brain that is disrupted in schizophrenia but also that both networks respond to antipsychotic medication. We first reproduce the established finding that brain networks of schizophrenia patients exhibit increased efficiency and reduced clustering compared with controls. Our data then reveal that the antipsychotic medications mitigate this effect, shifting the metrics toward those observed in healthy volunteers, with a marked difference in efficacy between the two drugs. Additionally, we find that aripiprazole considerably alters the network statistics of healthy controls. Examining the "N-back" working memory task, we establish that aripiprazole also adversely affects their performance. This suggests that changes to macroscopic brain network architecture result in measurable behavioral differences. This is one of the first studies to directly compare different medications using a whole-brain graph theoretical analysis with accompanying behavioral data. The small sample size is an inherent limitation and means a degree of caution is warranted in interpreting the findings. Our results lay the groundwork for an objective methodology with which to calculate and compare the efficacy of different treatments of mind and brain disorders.

PMID: 31572229 [PubMed]

Structural and Functional Disruptions in Subcortical Vascular Mild Cognitive Impairment With and Without Depressive Symptoms.

Front Aging Neurosci. 2019;11:241

Authors: Lyu H, Wang J, Xu J, Zheng H, Yang X, Lin S, Chen J, Zhou L, Hu Y, Guo Z

Abstract
Many previous studies have revealed structural and functional abnormalities in patients with the subcortical vascular mild cognitive impairment (svMCI). Although depression symptoms were suggested to serve as a potential marker of conversion to dementia in patients with svMCI, whether these disruptions or other new findings will be identified in the svMCI comorbid with depression symptoms has not been established. In the current study, we combined voxel-based morphometry (VBM) and the resting-state functional magnetic resonance imaging (fMRI) to investigate the structural and functional disruptions in the svMCI with and without depression symptoms using a cohort of 18 svMCI with depression symptoms (svMCI+D), 17 svMCI without depression symptoms (svMCI-D), and 23 normal controls (NC). As a result, we identified significantly decreased gray matter density in the left parahippocampus (ParaHIPP.L), the right hippocampus (HIPP.R), and the right middle cingulate cortex (MCC.R) in both svMCI+D and svMCI-D compared to NC. Most importantly, we also identified increased gray matter density in the MCC.R accompanied by increased resting-state functional connectivity (RSFC) with right parahippocampus (ParaHIPP.R) in the svMCI+D compared to svMCI-D. Moreover, the gray matter density of MCC.R and ParaHIPP.L was correlated with cognitive impairments and depression symptoms in the svMCI, respectively. In conclusion, these results extended previous studies and added weight to considerations of depression symptoms in the svMCI. Moreover, we suggested that a processing loop associated with HIPP, ParaHIPP, and MCC might underlie the mechanism of depression symptoms in the svMCI.

PMID: 31572164 [PubMed]

Structural and Functional Connectivity of the Anterior Cingulate Cortex in Patients With Borderline Personality Disorder.

Front Neurosci. 2019;13:971

Authors: Lei X, Zhong M, Zhang B, Yang H, Peng W, Liu Q, Zhang Y, Yao S, Tan C, Yi J

Abstract
Background: Emerging evidences supported the hypothesis that emotional dysregulation results from aberrant connectivity within the fronto-limbic neural networks in patients with borderline personality disorder (BPD). Considering its important role in emotional regulation, the anterior cingulate cortex (ACC) has not yet been fully explored in BPD patients. Therefore, using the seed-based resting state functional connectivity (rsFC) and probabilistic fiber tracking, we aimed to explore the alterations of functional and structural connectivity (SC) of the ACC in patients with BPD.
Methods: A cohort of 50 unmedicated, young BPD patients and 54 sex-, age-, and education-matched healthy controls (HCs) completed psychological tests and underwent rs-fMRI and diffuse tensor imaging (DTI) scanning. Rs-FC analysis and probabilistic fiber tracking were used to plot SC and FC of the ACC.
Results: With the left ACC selected as a seed, BPD patients exhibited increased rsFC and abnormal SC with the right middle frontal gyrus (MFG), and decreased rsFC with the left middle temporal gyrus (MTG), compared with HCs. Additionally, negative cognitive emotion regulation and depressive symptoms both correlated negatively with the rsFC of the left ACC in BPD patients.
Conclusion: Abnormal SC and FC of the ACC underlie the deficient emotional regulation circuitry in BPD patients. Such alterations may be important biomarkers of BPD and thus could point to potential BPD treatment targets.

PMID: 31572119 [PubMed]

Brain Functional Connectivity Through Phase Coupling of Neuronal Oscillations: A Perspective From Magnetoencephalography.

Front Neurosci. 2019;13:964

Authors: Marzetti L, Basti A, Chella F, D'Andrea A, Syrjälä J, Pizzella V

Abstract
Magnetoencephalography has gained an increasing importance in systems neuroscience thanks to the possibility it offers of unraveling brain networks at time-scales relevant to behavior, i.e., frequencies in the 1-100 Hz range, with sufficient spatial resolution. In the first part of this review, we describe, in a unified mathematical framework, a large set of metrics used to estimate MEG functional connectivity at the same or at different frequencies. The different metrics are presented according to their characteristics: same-frequency or cross-frequency, univariate or multivariate, directed or undirected. We focus on phase coupling metrics given that phase coupling of neuronal oscillations is a putative mechanism for inter-areal communication, and that MEG is an ideal tool to non-invasively detect such coupling. In the second part of this review, we present examples of the use of specific phase methods on real MEG data in the context of resting state, visuospatial attention and working memory. Overall, the results of the studies provide evidence for frequency specific and/or cross-frequency brain circuits which partially overlap with brain networks as identified by hemodynamic-based imaging techniques, such as functional Magnetic Resonance (fMRI). Additionally, the relation of these functional brain circuits to anatomy and to behavior highlights the usefulness of MEG phase coupling in systems neuroscience studies. In conclusion, we believe that the field of MEG functional connectivity has made substantial steps forward in the recent years and is now ready for bringing the study of brain networks to a more mechanistic understanding.

PMID: 31572116 [PubMed]

Dynamic Functional Connectivity Within the Fronto-Limbic Network Induced by Intermittent Theta-Burst Stimulation: A Pilot Study.

Front Neurosci. 2019;13:944

Authors: Tang Y, Jiao X, Wang J, Zhu T, Zhou J, Qian Z, Zhang T, Cui H, Li H, Tang X, Xu L, Zhang L, Wei Y, Sheng J, Liu L, Wang J

Abstract
Purpose: The utility of transcranial magnetic stimulation (TMS) has been growing rapidly in both neurocognitive studies and clinical applications in decades. However, it remains unclear how the responses of the stimulated site and the site-related functional network to the external TMS manipulation dynamically change over time.
Methods: A multi-session combining TMS-fMRI experiment was conducted to explore the spatiotemporal effects of TMS within the fronto-limbic network. Ten healthy volunteers were modulated by intermittent theta-burst stimulation (iTBS) at a precise site within the left dorsolateral prefrontal cortex (DLPFC, MNI coordinate [-44 36 20]), navigated by individual structural MRI image. Three-session resting-state fMRI images were acquired before iTBS (TP1), immediately after iTBS (TP2), and 15 min after iTBS (TP3) for each participant. Seventy-four regions of interests (ROIs) within the fronto-limbic network were chosen including the bilateral superior frontal gyrus (SFG), middle frontal gyrus (MidFG), inferior frontal gyrus (IFG), orbital gyrus (OrG), cingulate gyrus (CG), and subcortical nuclei (hippocampus and amygdala). Regional fractional amplitude of low-frequency fluctuation (fALFF) and ROI-to-ROI functional connectivity (FC) were compared among TP1, TP2, and TP3.
Results: The immediate iTBS effect was observed at the stimulated site. FC between the left dorsolateral SFG and left dorsal IFG and between the left rostral IFG and right MidFG increased at TP2 as compared to at TP1 (all FDR-p < 0.05), while FC within the left OrG decreased. The relatively long-term iTBS effect transmitted with decreased FC between the left IFG and right amygdala, increased FC between the left MidFG and left OrG, and decreased FC between bilateral IFG and OrG at TP3 than at TP1 (all FDR-p < 0.05). Meanwhile, mean fALFF values over the left SFG, MidFG, ventral CG, and IFG were significantly increased at TP3 as compared to those at TP2 (all p < 0.05 with Bonferroni correction).
Conclusion: By combining TMS and fMRI, it becomes possible to track the spatiotemporal dynamics of TMS after-effects within the fronto-limbic network. Our findings suggested that the iTBS effect dynamically changed over time from the local neural activation at the stimulated site to its connected remote regions within the fronto-limbic network.

PMID: 31572111 [PubMed]

Altered Cingulate Cortex Functional Connectivity in Normal Aging and Mild Cognitive Impairment.

Front Neurosci. 2019;13:857

Authors: Cera N, Esposito R, Cieri F, Tartaro A

Abstract
Purpose: Resting-state functional Magnetic Resonance Imaging studies revealed that the brain is organized into specialized networks constituted by regions that show a coherent fluctuation of spontaneous activity. Among these networks, the cingulate cortex appears to play a crucial role, particularly in the default mode network, the dorsal attention network and the salience network. In the present study, we mapped the functional connectivity (FC) pattern of different regions of the cingulate cortex: the anterior cingulate cortex, midcingulate cortex and posterior cingulate cortex/retro splenial cortex, which have been in turn divided into a total of 9 subregions. We compared FC patterns of the cingulate subregions in a sample of mild cognitive impairment patients and healthy elderly subjects.
Methods: We enrolled 19 healthy elders (age range: 61-72 y.o.) and 16 Mild cognitive impairment patients (age range 64-87 y.o.). All participants had comparable levels of education (8-10 years) and were neurologically examined to exclude visual and motor impairments, major medical conditions, psychiatric or neurological disorders and consumption of psychotropic drugs. The diagnosis of mild cognitive impairment was performed according to Petersen criteria. Subjects were evaluated with Mini-Mental State Examination, Frontal Assessment Battery, and prose memory (Babcock story) tests. In addition, with functional Magnetic Resonance Imaging, we investigated resting-state network activities.
Results: Healthy elderly, compared to mild cognitive impairment, showed significant increased level of FC for the ventral part of the anterior cingulate cortex in correspondence to the bilateral caudate and ventromedial prefrontal cortex. Moreover, for the midcingulate cortex the healthy elderly group showed increased levels of FC in the somatomotor region, prefrontal cortex, and superior parietal lobule. Meanwhile, the mild cognitive impairment group showed an increased level of FC for the superior frontal gyrus, frontal eye field and orbitofrontal cortex compared to the healthy elderly group.
Conclusion: Our findings indicate that cognitive decline observed in mild cognitive impairment patients damages the global FC of the cingulate cortex, supporting the idea that abnormalities in resting-state activities of the cingulate cortex could be a useful additional tool in order to better understand the brain mechanisms of MCI.

PMID: 31572106 [PubMed]

Disrupted Brain Entropy And Functional Connectivity Patterns Of Thalamic Subregions In Major Depressive Disorder.

Neuropsychiatr Dis Treat. 2019;15:2629-2638

Authors: Xue SW, Wang D, Tan Z, Wang Y, Lian Z, Sun Y, Hu X, Wang X, Zhou X

Abstract
Purpose: Entropy analysis of resting-state functional magnetic resonance imaging (R-fMRI) has recently been adopted to characterize brain temporal dynamics in some neuropsychological or psychiatric diseases. Thalamus-related dysfunction might be a potential trait marker of major depressive disorder (MDD), but the abnormal changes in the thalamus based on R-fMRI are still unclear from the perspective of brain temporal dynamics. The aim of this study was to identify local entropy changes and subregional connectivity patterns of the thalamus in MDD patients.
Patients and methods: We measured the sample entropy of the R-fMRI data from 46 MDD patients and 32 matched healthy controls. We employed the Louvain method for the module detection algorithm to automatically identify a functional parcellation of the thalamus and then examined the whole-brain subregional connectivity patterns.
Results: The results indicated that the MDD patients had decreased entropy in the bilateral thalami compared with healthy controls. Increased functional connectivity between the thalamic subregions and the medial part of the superior frontal gyrus (mSFG) was found in MDD patients.
Conclusion: This study showed new evidence about sample entropy changes in MDD patients. The functional connectivity alterations that were widely distributed across almost all the thalamic subregions with the mSFG in MDD suggest a general involvement independent of the location and function of the subregions.

PMID: 31571880 [PubMed]

Functional-structural relationship in large-scale brain networks of patients with end stage renal disease after kidney transplantation: A longitudinal study.

Hum Brain Mapp. 2019 Oct 01;:

Authors: Chen HJ, Wang YF, Wen J, Xu Q, Lu GM, Zhang LJ

Abstract
It is unclear how the brain network changed after kidney transplantation (KT). We explored the patterns of large-scale complex network after KT in end-stage renal disease (ESRD) patients with resting-state functional MRI (rs-fMRI) and diffusion tensor imaging (DTI). Twenty-one ESRD patients (14 men; mean age, 31.5 ± 9.9 years) scheduled for KT and 17 age- and gender-matched healthy controls (HC) (8 men; mean age, 28.9 ± 7.2 years) were enrolled in this study. Each participant underwent rs-fMRI and DTI scans in three time points (pre-KT, 1 and 6 months after KT [for ESRD]). Graph theory analysis was used to characterize the topological properties by using functional and structural network connectivities intergroup correlation analysis was performed between functional/structural MR indexes and clinical markers. Compared with HC, pre-KT ESRD patients showed an altered topological organization in both functional and structural networks. Compared with pre-KT, increased node degree and node efficiency were observed for both functional and structural networks at 1 month after KT (all p < .05), which were further increased at 6 months after KT (p < .05). Both functional and structural networks did not recover completely at 6 months after KT (all p < .05). The patients showed an increased functional-structural connectivity coupling at 1 month after KT compared with HC (p = .041). A trend of progressive recovery of functional and structural connectivity networks was observed in ERSD patients after KT, which did not recover to the normal levels even in 6 months after KT. The study results underlie cognitive function recovery in ESRD patients following KT in the neuropathophysiological perspective.

PMID: 31571368 [PubMed - as supplied by publisher]

Aberrant patterns of default-mode network functional connectivity associated with metabolic syndrome: A resting-state study.

Brain Behav. 2019 Sep 30;:e01333

Authors: Rashid B, Dev SI, Esterman M, Schwarz NF, Ferland T, Fortenbaugh FC, Milberg WP, McGlinchey RE, Salat DH, Leritz EC

Abstract
INTRODUCTION: Metabolic syndrome (MetS) is a clustering of three or more cardiovascular risk factors (RF), including hypertension, obesity, high cholesterol, or hyperglycemia. MetS and its component RFs are more prevalent in older age, and can be accompanied by alterations in brain structure. Studies have shown altered functional connectivity (FC) in samples with individual RFs as well as in clinical populations that are at higher risk to develop MetS. These studies have indicated that the default mode network (DMN) may be particularly vulnerable, yet little is known about the overall impact of MetS on FC in this network.
METHODS: In this study, we evaluated the integrity of FC to the DMN in participants with MetS relative to non-MetS individuals. Using a seed-based connectivity analysis approach, resting-state functional MRI (fMRI) data were analyzed, and the FC measures among the DMN seed (isthmus of the cingulate) and rest of the brain voxels were estimated.
RESULTS: Participants with MetS demonstrated reduced positive connectivity between the DMN seed and left superior frontal regions, and reduced negative connectivity between the DMN seed and left superior parietal, left postcentral, right precentral, right superior temporal and right superior parietal regions, after accounting for age- and sex-effects.
CONCLUSIONS: Our results suggest that MetS is associated with alterations in FC between the DMN and other regions of the brain. Furthermore, these results indicate that the overall burden of vascular RFs associated with MetS may, in part, contribute to the pathophysiology underlying aberrant FC in the DMN.

PMID: 31568716 [PubMed - as supplied by publisher]

Resting-state functional magnetic resonance imaging versus task-based activity for language mapping and correlation with perioperative cortical mapping.

Brain Behav. 2019 Sep 30;:e01362

Authors: Lemée JM, Berro DH, Bernard F, Chinier E, Leiber LM, Menei P, Ter Minassian A

Abstract
INTRODUCTION: Preoperative language mapping using functional magnetic resonance imaging (fMRI) aims to identify eloquent areas in the vicinity of surgically resectable brain lesions. fMRI methodology relies on the blood-oxygen-level-dependent (BOLD) analysis to identify brain language areas. Task-based fMRI studies the BOLD signal increase in brain areas during a language task to identify brain language areas, which requires patients' cooperation, whereas resting-state fMRI (rsfMRI) allows identification of functional networks without performing any explicit task through the analysis of the synchronicity of spontaneous BOLD signal oscillation between brain areas. The aim of this study was to compare preoperative language mapping using rsfMRI and task fMRI to cortical mapping (CM) during awake craniotomies.
METHODS: Fifty adult patients surgically treated for a brain lesion were enrolled. All patients had a presurgical language mapping with both task fMRI and rsfMRI. Identified language networks were compared to perioperative language mapping using electric cortical stimulation.
RESULTS: Resting-state fMRI was able to detect brain language areas during CM with a sensitivity of 100% compared to 65.6% with task fMRI. However, we were not able to perform a specificity analysis and compare task-based and rest fMRI with our perioperative setting in the current study. In second-order analysis, task fMRI imaging included main nodes of the SN and main areas involved in semantics were identified in rsfMRI.
CONCLUSION: Resting-state fMRI for presurgical language mapping is easy to implement, allowing the identification of functional brain language network with a greater sensitivity than task-based fMRI, at the cost of some precautions and a lower specificity. Further study is required to compare both the sensitivity and the specificity of the two methods and to evaluate the clinical value of rsfMRI as an alternative tool for the presurgical identification of brain language areas.

PMID: 31568681 [PubMed - as supplied by publisher]

Acute effects of lysergic acid diethylamide (LSD) on resting brain function.

Swiss Med Wkly. 2019 Sep 23;149:w20124

Authors: Müller F, Borgwardt S

Abstract
Lysergic acid diethylamide (LSD) is a potent hallucinogenic substance that was extensively investigated by psychiatrists during the 1950s and 1960s. Researchers were interested in the unique effects induced by this substance, some of which resemble symptoms seen in schizophrenia. Moreover, during that period LSD was studied and used for the treatment of several mental disorders such as depression, anxiety, addiction and personality disorders. Despite this long history of research, how LSD induces its specific effects on a neuronal level has been relatively unclear. In recent years there has been a revival of research in hallucinogenic drugs and their possible clinical applications. These contemporary studies in the UK and Switzerland include neuroimaging studies using functional magnetic resonance imaging (fMRI). In this review, we collect and interpret these recent neuroimaging findings. Overall, previous results across studies indicate that LSD administration is associated with extensive alterations in functional brain connectivity, measuring the correlated activities between different brain regions. The studies mostly reported increases in connectivity between regions and, more specifically, consistently found increased connectivity within the thalamocortical system. These latter observations are in agreement with models proposing that hallucinogenic drugs exert their effects by inhibiting cerebral filtering of external and internal data. However, studies also face several limitations, including potential biases of neuroimaging measurements.

PMID: 31568558 [PubMed - in process]

TOMM40 polymorphism is associated with resting-state functional MRI results in patients with Alzheimer's disease.

Neuroreport. 2019 Nov 06;30(16):1068-1073

Authors: Xiao X, Wei J, Zhang W, Jiao B, Liao X, Pan C, Liu X, Yan X, Tang B, Zhang Y, Wang D, Xing W, Liao W, Shen L

Abstract
OBJECTIVE: Translocase of outer mitochondrial membrane 40 (TOMM40) encodes translocase of the outer mitochondrial membrane (TOM), which is associated with mitochondrial dysfunction in Alzheimer's disease (AD). TOMM40 rs157581-G has been reported to increase susceptibility to AD. However, the effect of TOMM40 rs157581-G in resting-state functional MRI (rs-fMRI) on AD has not been studied. Therefore, we aimed to investigate the role of TOMM40 rs157581-G on rs-fMRI results in AD patients.
METHODS: Twenty-four AD patients were divided into two groups based on TOMM40 rs157581-G status, and clinical and imaging data were compared between the groups.
RESULTS: TOMM40 rs157581-G carriers of AD showed decreased regional homogeneity in the left precuneus and decreased amplitude of low-frequency fluctuations in the bilateral temporal poles compared with noncarriers of AD. TOMM40 rs157581-G carriers of AD also showed increased functional connectivity between the right middle occipital gyrus and the left supramarginal gyrus and decreased connectivity between the left superior occipital gyrus and the right transverse temporal gyrus in comparison with TOMM40 rs157581-G noncarriers.
CONCLUSION: We analyzed rs-fMRI characteristics of TOMM40 rs157581-G carriers of AD for the first time, which suggest that TOMM40 rs157581-G plays a harmful role in AD patients.

PMID: 31568198 [PubMed - in process]

Fused Sparse Network Learning for Longitudinal Analysis of Mild Cognitive Impairment.

IEEE Trans Cybern. 2019 Sep 30;:

Authors: Yang P, Zhou F, Ni D, Xu Y, Chen S, Wang T, Lei B

Abstract
Alzheimer's disease (AD) is a neurodegenerative disease with an irreversible and progressive process. To understand the brain functions and identify the biomarkers of AD and early stages of the disease [also known as, mild cognitive impairment (MCI)], it is crucial to build the brain functional connectivity network (BFCN) using resting-state functional magnetic resonance imaging (rs-fMRI). Existing methods have been mainly developed using only a single time-point rs-fMRI data for classification. In fact, multiple time-point data is more effective than a single time-point data in diagnosing brain diseases by monitoring the disease progression patterns using longitudinal analysis. In this article, we utilize multiple rs-fMRI time-point to identify early MCI (EMCI) and late MCI (LMCI), by integrating the fused sparse network (FSN) model with parameter-free centralized (PFC) learning. Specifically, we first construct the FSN framework by building multiple time-point BFCNs. The multitask learning via PFC is then leveraged for longitudinal analysis of EMCI and LMCI. Accordingly, we can jointly learn the multiple time-point features constructed from the BFCN model. The proposed PFC method can automatically balance the contributions of different time-point information via learned specific and common features. Finally, the selected multiple time-point features are fused by a similarity network fusion (SNF) method. Our proposed method is evaluated on the public AD neuroimaging initiative phase-2 (ADNI-2) database. The experimental results demonstrate that our method can achieve quite promising performance and outperform the state-of-the-art methods.

PMID: 31567112 [PubMed - as supplied by publisher]

A dimensional approach to jealousy reveals enhanced fronto-striatal, insula and limbic responses to angry faces.

Brain Struct Funct. 2019 Sep 27;:

Authors: Zheng X, Luo L, Li J, Xu L, Zhou F, Gao Z, Becker B, Kendrick KM

Abstract
Jealousy is a complex social emotion combining the different primary emotions of anger, fear and sadness. Previous evidence has suggested the involvement of fronto-striatal dopaminergic circuitry in pathological jealousy, although little is known about overlaps with the neural representation of primary emotions involved in non-morbid jealousy and the utility of a dimensional neuroimaging approach. In the current study, 85 healthy subjects underwent fMRI during an emotional face recognition paradigm and resting state. A total of 150 faces (happy, angry, fearful, sad, neutral) were presented and subjects required to identify the expression and rate its intensity. Trait jealousy was assessed using the Multidimensional Jealousy Scale. Behavioral results showed that only intensity ratings of angry faces were positively associated with subjects' jealousy scores. During processing of angry versus neutral expression faces, subjects with elevated jealousy exhibited increased activation in the right thalamus, insula, fusiform gyrus and hippocampus, left dorsal striatum, superior parietal lobule and bilateral cerebellum and inferior frontal gyrus after controlling for trait aggression and sex. Functional connectivity between the inferior frontal gyrus and dorsal striatum was also increased. No associations with resting-state functional connectivity were found. Overall, the present study demonstrates an association between exaggerated jealousy and increased intensity ratings of angry faces as well as activity and functional connectivity of the dorsal striatal-inferior frontal circuitry. Thus, increased emotional responsivity to social threat and enhanced activity in limbic regions and dopaminergic fronto-striatal circuitry may be features of both non-morbid and pathological jealousy confirming the utility of a dimensional approach.

PMID: 31560099 [PubMed - as supplied by publisher]

Large scale networks for human hand-object interaction: Functionally distinct roles for two premotor regions identified intraoperatively.

Neuroimage. 2019 Sep 23;:116215

Authors: Simone L, Fornia L, Viganò L, Sambataro F, Rossi M, Leonetti A, Puglisi G, Howells H, Bellacicca A, Bello L, Cerri G

Abstract
The development of awake intraoperative brain-mapping procedures for resection of brain tumors is of growing interest in neuroscience, because it enables direct testing of brain tissue, previously only possible in non-human primates. In a recent study performed in this setting specific effects can be induced by direct electrical stimulation on different sectors of premotor cortex during the execution of a hand manipulation task. Specifically, direct electrical stimulation applied on a dorsal sector of precentral cortex led to an increase in motor unit recruitment in hand muscles during execution of a hand manipulation task (Recruitment sector). The opposite effect was elicited when electrical stimulation was delivered more ventrally on the precentral cortex (Suppression sector). We studied whether the different effects on motor behavior induced by direct electrical stimulation applied on the two sites of the precentral cortex underlie differences in their functional connectivity with other brain areas, measured using resting state fMRI. Using healthy adults scanned as part of the Human Connectome Project, we computed the functional connectivity of each sector used as seeds. The functional connectivity patterns of the two intraoperative seeds was similar but cross-comparison revealed that the left and right Recruitment sectors had stronger functional connections with the hand region of the sensorimotor cortex, while the right Suppression region displayed stronger functional connectivity with a bilateral set of parieto-frontal areas crucial for the integration of perceptual and cognitive hand-related sensorimotor processes required for goal-related hand actions. Our results suggest that analyzing data obtained in the intraoperative setting with resting state functional magnetic resonance imaging in healthy brains can yield useful insight into the roles of different premotor sectors directly involved in hand-object interaction.

PMID: 31557544 [PubMed - as supplied by publisher]

Resting-state functional magnetic resonance study of primary open-angle glaucoma based on voxelwise brain network degree centrality.

Neurosci Lett. 2019 Sep 23;:134500

Authors: Zhang Q, Shu Y, Li X, Xiong C, Li P, Pang Y, Ye W, Yang L, Zeng X, Zhang X

Abstract
OBJECTIVE: To investigate alterations in the functional brain networks of patients with primary open-angle glaucoma (POAG) by using the resting-state functional magnetic resonance imaging (fMRI) voxelwise degree centrality (DC) method.
MATERIALS AND METHODS: Thirteen patients with POAG and thirteen healthy subjects were recruited for this study, and each participant underwent a rs-fMRI scan. The voxelwise DC method was used to assess the features of spontaneous brain activity. The differences in the mean DC across brain regions between the POAG group and the healthy control group were analyzed, and the correlations between the DC values of altered brain regions and various clinical ophthalmic parameters were analyzed in the POAG group.
RESULTS: Compared with healthy controls, patients with POAG exhibited significantly decreased DC values of the left superior frontal gyrus and the left postcentral gyrus as well as significantly increased DC values of the left superior occipital gyrus. In POAG patients, the DC value of the left superior occipital gyrus was significantly positively correlated with age (r = 0.571, P = 0.042) and negatively correlated with the intraocular pressure of the right eye (r=-0.625, P = 0.022). The DC value of the left superior frontal gyrus was significantly positively correlated with the right eye average cup-to-disc ratio (r = 0.683, P = 0.010), vertical cup-to-disc ratio (r = 0.779, P = 0.002), and pattern standard deviation (r = 0.567, P = 0.043).
CONCLUSION: The results showed that altered DC values in three brain regions may reflect the underlying pathological mechanisms of POAG. Decreased DC values of the left superior occipital gyrus could be useful imaging markers for determining the extent of brain damage in POAG patients compared to healthy subjects.

PMID: 31557522 [PubMed - as supplied by publisher]

Psychological Resilience Enhances the Orbitofrontal Network in the Elderly With Mild Cognitive Impairment.

Front Psychiatry. 2019;10:615

Authors: Son SJ, Park B, Choi JW, Roh HW, Kim NR, Sin JE, Kim H, Lim HK, Hong CH

Abstract
Background: It has been suggested that maintaining the efficient organization of the brain's functional connectivity (FC) supports neuroflexibility under neurogenerative stress. This study examined psychological resilience-related FC in 112 older adults with mild cognitive impairment (MCI). Methods: Using a resting-state functional magnetic resonance imaging (fMRI) approach, we investigated reorganization of the orbitofrontal gyrus (OFG)/amygdala (AMG)/hippocampus (HP)/parahippocampal gyrus (PHG) FC according to the different levels of resilience scale. Results: Compared with the low resilient group, the high resilient group had greater connectivity strengths between the left inferior OFG and right superior OFG (P < 0.05, Bonferroni corrected), between the right inferior OFG and left PHG (P < 0.05, Bonferroni corrected), and between the right middle OFG and left PHG (false discovery rate < 0.05). Conclusion: Psychological resilience may be associated with enhancement of the orbitofrontal network in the elderly with MCI.

PMID: 31555158 [PubMed]

Classification of Early and Late Mild Cognitive Impairment Using Functional Brain Network of Resting-State fMRI.

Front Psychiatry. 2019;10:572

Authors: Zhang T, Zhao Z, Zhang C, Zhang J, Jin Z, Li L

Abstract
Using the Pearson correlation coefficient to constructing functional brain network has been evidenced to be an effective means to diagnose different stages of mild cognitive impairment (MCI) disease. In this study, we investigated the efficacy of a classification framework to distinguish early mild cognitive impairment (EMCI) from late mild cognitive impairment (LMCI) by using the effective features derived from functional brain network of three frequency bands (full-band: 0.01-0.08 Hz; slow-4: 0.027-0.08 Hz; slow-5: 0.01-0.027 Hz) at Rest. Graphic theory was performed to calculate and analyze the relationship between changes in network connectivity. Subsequently, three different algorithms [minimal redundancy maximal relevance (mRMR), sparse linear regression feature selection algorithm based on stationary selection (SS-LR), and Fisher Score (FS)] were applied to select the features of network attributes, respectively. Finally, we used the support vector machine (SVM) with nested cross validation to classify the samples into two categories to obtain unbiased results. Our results showed that the global efficiency, the local efficiency, and the average clustering coefficient were significantly higher in the slow-5 band for the LMCI-EMCI comparison, while the characteristic path length was significantly longer under most threshold values. The classification results showed that the features selected by the mRMR algorithm have higher classification performance than those selected by the SS-LR and FS algorithms. The classification results obtained by using mRMR algorithm in slow-5 band are the best, with 83.87% accuracy (ACC), 86.21% sensitivity (SEN), 81.21% specificity (SPE), and the area under receiver operating characteristic curve (AUC) of 0.905. The present results suggest that the method we proposed could effectively help diagnose MCI disease in clinic and predict its conversion to Alzheimer's disease at an early stage.

PMID: 31555157 [PubMed]

The Effect of Aging on Resting State Connectivity of Predefined Networks in the Brain.

Front Aging Neurosci. 2019;11:234

Authors: Varangis E, Habeck CG, Razlighi QR, Stern Y

Abstract
Recent studies have found a deleterious effect of age on a wide variety of measures of functional connectivity, and some hints at a relationship between connectivity at rest and cognitive functioning. However, few studies have combined multiple functional connectivity methods, or examined them over a wide range of adult ages, to try to uncover which metrics and networks seem to be particularly sensitive to age-related decline across the adult lifespan. The present study utilized multiple resting state functional connectivity methods in a sample of adults from 20-80 years old to gain a more complete understanding of the effect of aging on network function and integrity. Whole-brain results showed that aging results in weakening average within-network connectivity, lower system segregation and local efficiency, and higher participation coefficient. Network-level results suggested that nearly every primary sensory and cognitive network faces some degree of age-related decline, including reduced within-network connectivity, higher network-based participation coefficient, and reduced network-level local efficiency. Further, some of these connectivity metrics showed relationships with cognitive performance. Thus, these results suggest that a multi-method analysis of functional connectivity data may be critical to capture the full effect of aging on the health of brain networks.

PMID: 31555124 [PubMed]