Changes In Brain Networks Research Articles

Controlling extended criticality via modular connectivity

Criticality has been conjectured as an integral part of neuronal network dynamics. Operating at a critical threshold requires precise parameter tuning and a corresponding mechanism remains an open question. Recent studies have suggested that topological features observed in brain networks give rise to a Griffiths phase, leading to power-law scaling in brain activity dynamics and the operational benefits of criticality in an extended parameter region. Motivated by growing evidence of neural correlates of different states of consciousness, we investigate how topological changes affect the expression of a Griffiths phase. We analyze the activity decay in modular networks using a susceptible-infected-susceptible propagation model and find that we can control the extension of the Griffiths phase by altering intra- and intermodular connectivity. We find that by adjusting system parameters, we can counteract changes in critical behavior and maintain a stable critical region despite changes in network topology. Our results give insight into how structural network properties affect the emergence of a Griffiths phase and how its features are linked to established topological network metrics. We discuss how those findings could contribute to an understanding of the changes in functional brain networks.

Acquisition of Resting-State Functional Magnetic Resonance Imaging Data in the Rat.

Resting-state functional magnetic resonance imaging (rs-fMRI) has become an increasingly popular method to study brain function in a resting, non-task state. This protocol describes a preclinical survival method for obtaining rs-fMRI data. Combining low dose isoflurane with continuous infusion of the α2 adrenergic receptor agonist dexmedetomidine provides a robust option for stable, high-quality data acquisition while preserving brain network function. Furthermore, this procedure allows for spontaneous breathing and near-normal physiology in the rat. Additional imaging sequences can be combined with resting-state acquisition creating experimental protocols with anesthetic stability of up to 5 h using this method. This protocol describes the setup of equipment, monitoring of rat physiology during four distinct phases of anesthesia, acquisition of resting-state scans, quality assessment of data, recovery of the animal, and a brief discussion of post-processing data analysis. This protocol can be used across a wide variety of preclinical rodent models to help reveal the resulting brain network changes that occur at rest.

White Matter Integrity in a Rat Model of Epileptogenesis: Structural Connectomics and Fixel-Based Analysis.

Introduction: Electrophysiological and neuroimaging studies have demonstrated that large-scale brain networks are affected during the development of epilepsy. These networks can be investigated by using diffusion magnetic resonance imaging (dMRI). The most commonly used model to analyze dMRI is diffusion tensor imaging (DTI). However, DTI metrics are not specific to microstructure or pathology and the DTI model does not take into account crossing fibers, which may lead to erroneous results. To overcome these limitations, a more advanced model based on multi-shell multi-tissue constrained spherical deconvolution was used in this study to perform tractography with more precise fiber orientation estimates and to assess changes in intra-axonal volume by using fixel-based analysis. Methods: dMRI images were acquired before and at several time points after induction of status epilepticus in the intraperitoneal kainic acid (IPKA) rat model of temporal lobe epilepsy. Tractography was performed, and fixel metrics were calculated in several white matter tracts. The tractogram was analyzed by using the graph theory. Results: Global degree, global and local efficiency were decreased in IPKA animals compared with controls during epileptogenesis. Nodal degree was decreased in the limbic system and default-mode network, mainly during early epileptogenesis. Further, fiber density (FD) and fiber-density-and-cross-section (FDC) were decreased in several white matter tracts. Discussion: These results indicate a decrease in overall structural connectivity, integration, and segregation and decreased structural connectivity in the limbic system and default-mode network. Decreased FD and FDC point to a decrease in intra-axonal volume fraction during epileptogenesis, which may be related to neuronal degeneration and gliosis. Impact statement To the best of our knowledge, this is the first longitudinal multi-shell diffusion magnetic resonance imaging study that combines whole-brain tractography and fixel-based analysis to investigate changes in structural brain connectivity and white matter integrity during epileptogenesis in a rat model of temporal lobe epilepsy. Our findings present better insights into how the topology of the structural brain network changes during epileptogenesis and how these changes are related to white matter integrity. This could improve the understanding of the basic mechanisms of epilepsy and aid the rational development of imaging biomarkers and epilepsy therapies.

Prediction of Epilepsy Based on Tensor Decomposition and Functional Brain Network.

Epilepsy is a chronic neurological disorder which can affect 65 million patients worldwide. Recently, network based analyses have been of great help in the investigation of seizures. Now graph theory is commonly applied to analyze functional brain networks, but functional brain networks are dynamic. Methods based on graph theory find it difficult to reflect the dynamic changes of functional brain network. In this paper, an approach to extracting features from brain functional networks is presented. Dynamic functional brain networks can be obtained by stacking multiple functional brain networks on the time axis. Then, a tensor decomposition method is used to extract features, and an ELM classifier is introduced to complete epilepsy prediction. In the prediction of epilepsy, the accuracy and F1 score of the feature extracted by tensor decomposition are higher than the degree and clustering coefficient. The features extracted from the dynamic functional brain network by tensor decomposition show better and more comprehensive performance than degree and clustering coefficient in epilepsy prediction.

Dynamic Network Analysis Demonstrates the Formation of Stable Functional Networks During Rule Learning.

Variations in the functional connectivity of large-scale cortical brain networks may explain individual differences in learning ability. We used a dynamic network analysis of fMRI data to identify changes in functional brain networks that are associated with context-dependent rule learning. During fMRI scanning, naïve subjects performed a cognitive task designed to test their ability to learn context-dependent rules. Notably, subjects were given minimal instructions about the task prior to scanning. We identified several key network characteristics associated with fast and accurate rule learning. First, consistent with the formation of stable functional networks, a dynamic community detection analysis revealed regionally specific reductions in flexible switching between different functional communities in successful learners. Second, successful rule learners showed decreased centrality of ventral attention regions and increased assortative mixing of cognitive control regions as the rules were learned. Finally, successful subjects showed greater decoupling of default and attention communities throughout the entire task, whereas ventral attention and cognitive control regions became more connected during learning. Overall, the results support a framework by which a stable ventral attention community and more flexible cognitive control community support sustained attention and the formation of rule representations in successful learners.

Low-Frequency TMS Results in Condition-Related Dynamic Activation Changes of Stimulated and Contralateral Inferior Parietal Lobule.

Non-invasive brain stimulation is a promising approach to study the causal relationship between brain function and behavior. However, it is difficult to interpret behavioral null results as dynamic brain network changes have the potential to prevent stimulation from affecting behavior, ultimately compensating for the stimulation. The present study investigated local and remote changes in brain activity via functional magnetic resonance imaging (fMRI) after offline disruption of the inferior parietal lobule (IPL) or the vertex in human participants via 1 Hz repetitive transcranial magnetic stimulation (rTMS). Since the IPL acts as a multimodal hub of several networks, we implemented two experimental conditions in order to robustly engage task-positive networks, such as the fronto-parietal control network (on-task condition) and the default mode network (off-task condition). The condition-dependent neural after-effects following rTMS applied to the IPL were dynamic in affecting post-rTMS BOLD activity depending on the exact time-window. More specifically, we found that 1 Hz rTMS applied to the right IPL led to a delayed activity increase in both, the stimulated and the contralateral IPL, as well as in other brain regions of a task-positive network. This was markedly more pronounced in the on-task condition suggesting a condition-related delayed upregulation. Thus together, our results revealed a dynamic compensatory reorganization including upregulation and intra-network compensation which may explain mixed findings after low-frequency offline TMS.

Altered Spontaneous Neural Activity and Functional Connectivity in Parkinson’s Disease With Subthalamic Microlesion

BackgroundTransient improvement in motor symptoms are immediately observed in patients with Parkinson’s disease (PD) after an electrode has been implanted into the subthalamic nucleus (STN) for deep brain stimulation (DBS). This phenomenon is known as the microlesion effect (MLE). However, the underlying mechanisms of MLE is poorly understood.PurposeWe utilized resting state functional MRI (rs-fMRI) to evaluate changes in spontaneous brain activity and networks in PD patients during the microlesion period after DBS.MethodOverall, 37 PD patients and 13 gender- and age-matched healthy controls (HCs) were recruited for this study. Rs-MRI information was collected from PD patients three days before DBS and one day after DBS, whereas the HCs group was scanned once. We utilized the amplitude of low-frequency fluctuation (ALFF) method in order to analyze differences in spontaneous whole-brain activity among all subjects. Furthermore, functional connectivity (FC) was applied to investigate connections between other brain regions and brain areas with significantly different ALFF before and after surgery in PD patients.ResultRelative to the PD-Pre-DBS group, the PD-Post-DBS group had higher ALFF in the right putamen, right inferior frontal gyrus, right precentral gyrus and lower ALFF in right angular gyrus, right precuneus, right posterior cingulate gyrus (PCC), left insula, left middle temporal gyrus (MTG), bilateral middle frontal gyrus and bilateral superior frontal gyrus (dorsolateral). Functional connectivity analysis revealed that these brain regions with significantly different ALFF scores demonstrated abnormal FC, largely in the temporal, prefrontal cortices and default mode network (DMN).ConclusionThe subthalamic microlesion caused by DBS in PD was found to not only improve the activity of the basal ganglia-thalamocortical circuit, but also reduce the activity of the DMN and executive control network (ECN) related brain regions. Results from this study provide new insights into the mechanism of MLE.

Changes in the Functional Brain Network of Children Undergoing Repeated Epilepsy Surgery: An EEG Source Connectivity Study.

About 30% of children with drug-resistant epilepsy (DRE) continue to have seizures after epilepsy surgery. Since epilepsy is increasingly conceptualized as a network disorder, understanding how brain regions interact may be critical for planning re-operation in these patients. We aimed to estimate functional brain connectivity using scalp EEG and its evolution over time in patients who had repeated surgery (RS-group, n = 9) and patients who had one successful surgery (seizure-free, SF-group, n = 12). We analyzed EEGs without epileptiform activity at varying time points (before and after each surgery). We estimated functional connectivity between cortical regions and their relative centrality within the network. We compared the pre- and post-surgical centrality of all the non-resected (untouched) regions (far or adjacent to resection) for each group (using the Wilcoxon signed rank test). In alpha, theta, and beta frequency bands, the post-surgical centrality of the untouched cortical regions increased in the SF group (p < 0.001) whereas they decreased (p < 0.05) or did not change (p > 0.05) in the RS group after failed surgeries; when re-operation was successful, the post-surgical centrality of far regions increased (p < 0.05). Our data suggest that removal of the epileptogenic focus in children with DRE leads to a gain in the network centrality of the untouched areas. In contrast, unaltered or decreased connectivity is seen when seizures persist after surgery.

Metabolic Brain Network Analysis With 18F-FDG PET in a Rat Model of Neuropathic Pain.

Neuropathic pain has been found to be related to profound reorganization in the function and structure of the brain. We previously demonstrated changes in local brain activity and functional/metabolic connectivity among selected brain regions by using neuroimaging methods. The present study further investigated large-scale metabolic brain network changes in 32 Sprague–Dawley rats with right brachial plexus avulsion injury (BPAI). Graph theory was applied in the analysis of 2-deoxy-2-[18F] fluoro-D-glucose (18F-FDG) PET images. Inter-subject metabolic networks were constructed by calculating correlation coefficients. Global and nodal network properties were calculated and comparisons between pre- and post-BPAI (7 days) status were conducted. The global network properties (including global efficiency, local efficiency and small-world index) and nodal betweenness centrality did not significantly change for all selected sparsity thresholds following BPAI (p > 0.05). As for nodal network properties, both nodal degree and nodal efficiency measures significantly increased in the left caudate putamen, left medial prefrontal cortex, and right caudate putamen (p < 0.001). The right entorhinal cortex showed a different nodal degree (p < 0.05) but not nodal efficiency. These four regions were selected for seed-based metabolic connectivity analysis. Strengthened connectivity was found among these seeds and distributed brain regions including sensorimotor area, cognitive area, and limbic system, etc. (p < 0.05). Our results indicated that the brain had the resilience to compensate for BPAI-induced neuropathic pain. However, the importance of bilateral caudate putamen, left medial prefrontal cortex, and right entorhinal cortex in the network was strengthened, as well as most of their connections with distributed brain regions.

The regulatory mechanisms of behavioral and cognitive aging.

With the increase of life expectancy, the world's population is aging rapidly. Previous work in the field of aging greatly increases our understanding of biological mechanisms underlying longevity. Researchers have unraveled a number of longevity pathways conserved from yeast to mammals. However, recent evidence shows that mechanisms regulating the life span and those regulating age-related behavioral decline could be dissociated. The regulatory mechanisms underlying behavioral and cognitive aging is largely unknown. Previous work has described a significant age-related decline in cognitive behaviors including episodic memory, working memory, processing speed, as well as motor function deterioration and circadian dysfunction. With the advance of neuroscience and technology, more and more studies have focused on the age-related changes in structure and function of the brain. In this review, we briefly describe the deterioration of cognitive function and other behaviors in the aging process, and survey the role of age-related changes in brain structure and network, neuron morphology and function, transcriptome in brain and some conserved biological pathways on age-related cognitive and behavioral decline. Further studies on the mechanisms underpinning age-related cognitive and behavioral decline may provide clues not only for improving the quality of life for the ageing population, but also for developing intervention approaches for neurodegenerative diseases.

Functional brain network topology across the menstrual cycle is estradiol dependent and correlates with individual well-being.

The menstrual cycle (MC) is a sex hormone‐related phenomenon that repeats itself cyclically during the woman's reproductive life. In this explorative study, we hypothesized that coordinated variations of multiple sex hormones may affect the large‐scale organization of the brain functional network and that, in turn, such changes might have psychological correlates, even in the absence of overt clinical signs of anxiety and/or depression. To test our hypothesis, we investigated longitudinally, across the MC, the relationship between the sex hormones and both brain network and psychological changes. We enrolled 24 naturally cycling women and, at the early‐follicular, peri‐ovulatory, and mid‐luteal phases of the MC, we performed: (a) sex hormone dosage, (b) magnetoencephalography recording to study the brain network topology, and (c) psychological questionnaires to quantify anxiety, depression, self‐esteem, and well‐being. We showed that during the peri‐ovulatory phase, in the alpha band, the leaf fraction and the tree hierarchy of the brain network were reduced, while the betweenness centrality (BC) of the right posterior cingulate gyrus (rPCG) was increased. Furthermore, the increase in BC was predicted by estradiol levels. Moreover, during the luteal phase, the variation of estradiol correlated positively with the variations of both the topological change and environmental mastery dimension of the well‐being test, which, in turn, was related to the increase in the BC of rPCG. Our results highlight the effects of sex hormones on the large‐scale brain network organization as well as on their possible relationship with the psychological state across the MC. Moreover, the fact that physiological changes in the brain topology occur throughout the MC has widespread implications for neuroimaging studies.

Altered Resting-State Brain Activity in Schizophrenia and Obsessive-Compulsive Disorder Compared With Non-psychiatric Controls: Commonalities and Distinctions Across Disorders.

Backgrounds: Schizophrenia (SCZ) and obsessive-compulsive disorder (OCD) are classified as two chronic psychiatric disorders with high comorbidity rate and shared clinical symptoms. Abnormal spontaneous brain activity within the cortical–striatal neural circuits has been observed in both disorders. However, it is unclear if the common or distinct neural abnormalities underlie the neurobiological substrates in the resting state.Methods: Resting-state fMRI data were collected from 88 patients with SCZ, 58 patients with OCD, and 72 healthy control subjects. First, we examined differences in amplitude of low-frequency fluctuations (ALFF) among three groups. Resting-state functional connectivity (rsFC) analysis with the brain region that showed different ALFF as the seed was then conducted to identify the changes in brain networks. Finally, we examined the correlation between the altered activities and clinical symptoms.Results: Both the patients with SCZ and OCD showed increased ALFF in the right hippocampus and decreased ALFF in the left posterior cingulate cortex (PCC). SCZ patients exhibited increased ALFF in the left caudate [voxel-level family-wise error (FWE) P < 0.05] and decreased rsFC between the left caudate and right cerebellum, which correlated with positive symptoms. The left caudate showed increased rsFC with the right thalamus and bilateral supplementary motor complex (SMC) in OCD patients (cluster-level FWE P < 0.05).Conclusions: The hippocampus and PCC are common regions presenting abnormal local spontaneous neuronal activities in both SCZ and OCD, while the abnormality of the striatum can reflect the differences. Increased ALFF in the striatum and symptom-related weakened rsFC between the caudate and cerebellum showed SCZ specificity. Enhanced rsFC between the caudate and SMC may be a key characteristic in OCD. Our research shows the similarities and differences between the two diseases from the perspective of resting-state fMRI, which provides clues to understand the disease and find methods for treatment.

Network dysfunction in cognitively normal APOE ε4 carriers is related to subclinical tau.

Apolipoprotein E (APOE) ε4 allele status is associated with amyloid and tau-related pathological changes related to Alzheimer's disease (AD). However, it is unknown whether brain network changes are related to amyloid beta (Aβ) and/or tau-related pathology in cognitively normal APOE ε4 carriers with subthreshold Aβ accumulation. Resting state functional connectivity measures of network integrity were evaluated in cognitively normal individuals (n=121, mean age 76.6 ± 7.8 years, 15% APOE ε4 carriers, 65% female) with minimal Aβ per cerebrospinal fluid (CSF) or amyloid positron emission tomography. APOE ε4 carriers had increased lateralized connections relative to callosal connections within the default-mode, memory, and salience networks (P=.02), with significant weighting on linear regression toward CSF total tau (P=.03) and CSF phosphorylated tau at codon 181 (P=.03), but not CSF Aβ42 . Cognitively normal APOE ε4 carriers with subthreshold amyloid accumulation may have network reorganization associated with tau.

Functional brain network reorganization in HIV infection.

To investigate the reorganization of the central nervous system provided by resting state-functional MRI (rs-fMRI), graph-theoretical analysis, and a newly developed functional brain network disruption index in patients with human immunodeficiency virus (HIV) infection. Forty HIV-positive patients without neurological impairment and 20 age- and sex-matched healthy controls underwent rs-fMRI at 3T; blood sampling was obtained the same day to evaluate biochemical variables (absolute, relative, and nadir CD4 T-lymphocytes value and plasmatic HIV-RNA). From fMRI data, disruption indices, as well as global and local graph theoretical measures, were estimated and examined for group differences (HIV vs. controls) as well as for associations with biochemical variables (HIV only). Finally, all data (global and local graph-theoretical measures, disruption indices, and biochemical variables) were tested for putative differences across three patient groups based on the duration of combined antiretroviral therapy (cART). Brain function of HIV patients appeared to be deeply reorganized as compared to normal controls. The disruption index showed significant negative association with relative CD4 values, and a positive significant association between plasmatic HIV-RNA and local graph-theoretical metrics in the left lingual gyrus and the right lobule IV and V of right cerebellar hemisphere was also observed. Finally, a differential distribution of HIV clinical biomarkers and several brain metrics was observed across cART duration groups. Our study demonstrates that rs-fMRI combined with advanced graph theoretical analysis and disruption indices is able to detect early and subtle functional changes of brain networks in HIV patients.

Aberrant Resting-State Cerebellar-Cerebral Functional Connectivity in Unmedicated Patients With Obsessive-Compulsive Disorder.

Background: Although abnormality of cerebellar-cerebral functional connectivity at rest in obsessive-compulsive disorder (OCD) has been hypothesized, only a few studies have investigated the neural mechanism. To verify the findings of previous studies, a large sample of patients with OCD was studied because OCD shows possible heterogeneity.Methods: Forty-seven medication-free patients with OCD and 62 healthy controls (HCs) underwent resting-state functional magnetic imaging scans. Seed-based connectivity was examined to investigate differences in cerebellar-cerebral functional connectivity in OCD patients compared with HCs. Correlations between functional connectivity and the severity of obsessive-compulsive symptoms were analyzed.Results: In OCD, we found significantly increased functional connectivity between the right lobule VI and the left precuneus, which is a component of the default mode network (DMN), compared to HCs. However, there was no correlation between the connectivity of the right lobule VI-left precuneus and obsessive-compulsive severity.Conclusions: These findings suggest that altered functional connectivity between the cerebellum and DMN might cause changes in intrinsic large-scale brain networks related to the traits of OCD.

Association between Functional Brain Network Metrics and Surgeon Performance and Distraction in the Operating Room.

Objective: The aim of this work was to examine (electroencephalogram) EEG features that represent dynamic changes in the functional brain network of a surgical trainee and whether these features can be used to evaluate a robot assisted surgeon’s (RAS) performance and distraction level in the operating room. Materials and Methods: Electroencephalogram (EEG) data were collected from three robotic surgeons in an operating room (OR) via a 128-channel EEG headset with a frequency of 500 samples/second. Signal processing and network neuroscience algorithms were applied to the data to extract EEG features. The SURG-TLX and NASA-TLX metrics were subjectively evaluated by a surgeon and mentor at the end of each task. The scores given to performance and distraction metrics were used in the analyses here. Statistical test data were utilized to select EEG features that have a significant relationship with surgeon performance and distraction while carrying out a RAS surgical task in the OR. Results: RAS surgeon performance and distraction had a relationship with the surgeon’s functional brain network metrics as recorded throughout OR surgery. We also found a significant negative Pearson correlation between performance and the distraction level (−0.37, p-value < 0.0001). Conclusions: The method proposed in this study has potential for evaluating RAS surgeon performance and the level of distraction. This has possible applications in improving patient safety, surgical mentorship, and training.

What’s the buzz? The neuroscience and the treatment of tinnitus

Tinnitus is a pervasive public health issue that affects ∼15% of the United States population. Similar estimates have also been shown on a global scale, with similar prevalence found in Europe, Asia, and Africa. The severity of tinnitus is heterogeneous, ranging from mildly bothersome to extremely disruptive. In the United States, ∼10-20% of individuals who experience tinnitus report symptoms that severely reduce their quality of life. Due to the huge personal and societal burden, in the last 20 yr a concerted effort on basic and clinical research has significantly advanced our understanding and treatment of this disorder. Yet, neither full understanding, nor cure exists. We know that tinnitus is the persistent involuntary phantom percept of internally generated nonverbal indistinct noises and tones, which in most cases is initiated by acquired hearing loss and maintained only when this loss is coupled with distinct neuronal changes in auditory and extra-auditory brain networks. Yet, the exact mechanisms and patterns of neural activity that are necessary and sufficient for the perceptual generation and maintenance of tinnitus remain incompletely understood. Combinations of animal model and human research will be essential in filling these gaps. Nevertheless, the existing progress in investigating the neurophysiological mechanisms has improved current treatment and highlighted novel targets for drug development and clinical trials. The aim of this review is to thoroughly discuss the current state of human and animal tinnitus research, outline current challenges, and highlight new and exciting research opportunities.

The Insula Is a Hub for Functional Brain Network in Patients With Anti-N-Methyl-D-Aspartate Receptor Encephalitis.

BackgroundIn recent years, imaging technologies have been rapidly evolving, with an emphasis on the characterization of brain structure changes and functional imaging in patients with autoimmune encephalitis. However, the neural basis of anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis and its linked cognitive decline is unclear. Our research aimed to assess changes in the functional brain network in patients with anti-NMDAR encephalitis and whether these changes lead to cognitive impairment.MethodsTwenty-one anti-NMDAR encephalitis patients and 22 age-, gender-, and education status-matched healthy controls were assessed using resting functional magnetic resonance imaging (fMRI) scanning and neuropsychological tests, including the Hamilton Depression Scale (HAMD24), the Montreal Cognitive Assessment (MoCA), and the Hamilton Anxiety Scale (HAMA). A functional brain network was constructed using fMRI, and the topology of the network parameters was analyzed using graph theory. Next, we extracted the aberrant topological parameters of the functional network as seeds and compared causal connectivity with the whole brain. Lastly, we explored the correlation of aberrant topological structures with deficits in cognitive performance.ResultsRelative to healthy controls, anti-NMDAR encephalitis patients exhibited decreased MoCA scores and increased HAMA and HAMD24 scores (p < 0.05). The nodal clustering coefficient and nodal local efficiency of the left insula (Insula_L) were significantly decreased in anti-NMDAR encephalitis patients (p < 0.05 following Bonferroni correction). Moreover, anti-NMDAR encephalitis patients showed a weakened causal connectivity from the left insula to the left inferior parietal lobe (Parietal_Inf_L) compared to healthy controls. Conversely, the left superior parietal lobe (Parietal_sup_L) exhibited an enhanced causal connectivity to the left insula in anti-NMDAR encephalitis patients compared to controls. Unexpectedly, these alterations were not correlated with any neuropsychological test scores.ConclusionThis research describes topological abnormalities in the functional brain network in anti-NMDAR encephalitis. These results will be conducive to understand the structure and function of the brain network of patients with anti-NMDAR encephalitis and further explore the neuropathophysiological mechanisms.

Gray-Matter Expansion of Social Brain Networks in Individuals High in Public Self-Consciousness.

Self-consciousness is a personality trait associated with an individual’s concern regarding observable (public) and unobservable (private) aspects of self. Prompted by previous functional magnetic resonance imaging (MRI) studies, we examined possible gray-matter expansions in emotion-related and default mode networks in individuals with higher public or private self-consciousness. One hundred healthy young adults answered the Japanese version of the Self-Consciousness Scale (SCS) questionnaire and underwent structural MRI. A voxel-based morphometry analysis revealed that individuals scoring higher on the public SCS showed expansions of gray matter in the emotion-related regions of the cingulate and insular cortices and in the default mode network of the precuneus and medial prefrontal cortex. In addition, these gray-matter expansions were particularly related to the trait of “concern about being evaluated by others”, which was one of the subfactors constituting public self-consciousness. Conversely, no relationship was observed between gray-matter volume in any brain regions and the private SCS scores. This is the first study showing that the personal trait of concern regarding public aspects of the self may cause long-term substantial structural changes in social brain networks.

Prefrontal network dysfunctions in rapid eye movement sleep behavior disorder

IntroductionResting-state functional connectivity magnetic resonance imaging (rsfcMRI) of rapid eye movement (REM) sleep behavior disorder (RBD) may provide an early biomarker of α-synucleinopathy. However, few rsfcMRI studies have examined cognitive networks. To elucidate brain network changes in RBD, we performed rsfcMRI in patients with polysomnography-confirmed RBD and healthy controls (HCs), with a sufficiently large sample size in each group. MethodsWe analyzed rsfcMRI data from 50 RBD patients and 70 age-matched HCs. Although RBD patients showed no motor signs, some exhibited autonomic and cognitive problems. Several resting-state functional networks were extracted by group independent component analysis from HCs, including the executive-control (ECN), default-mode (DMN), basal ganglia (BGN), and sensory-motor (SMN) networks. Functional connectivity (FC) was compared between groups using dual regression analysis. In the RBD group, correlation analysis was performed between FC and clinical/cognitive scales. ResultsPatients with RBD showed reduced striatal-prefrontal FC in ECN, consistent with executive dysfunctions. No abnormalities were found in DMN. In the motor networks, we identified reduced midbrain-pallidum FC in BGN and reduced motor and somatosensory cortex FC in SMN. ConclusionWe found abnormal ECN and normal DMN as a possible hallmark of cognitive dysfunctions in early α-synucleinopathies. We replicated abnormalities in BGN and SMN corresponding to subclinical movement disorder of RBD. RsfcMRI may provide an early biomarker of both cognitive and motor network dysfunctions of α-synucleinopathies.