Altered Network Topology Research Articles

On the sensitivity of centrality metrics

Despite the huge importance that the centrality metrics have in understanding the topology of a network, too little is known about the effects that small alterations in the topology of the input graph induce in the norm of the vector that stores the node centralities. If so, then it could be possible to avoid re-calculating the vector of centrality metrics if some minimal changes occur in the network topology, which would allow for significant computational savings. Hence, after formalising the notion of centrality, three of the most basic metrics were herein considered (i.e., Degree, Eigenvector, and Katz centrality). To perform the simulations, two probabilistic failure models were used to describe alterations in network topology: Uniform (i.e., all nodes can be independently deleted from the network with a fixed probability) and Best Connected (i.e., the probability a node is removed depends on its degree). Our analysis suggests that, in the case of degree, small variations in the topology of the input graph determine small variations in Degree centrality, independently of the topological features of the input graph; conversely, both Eigenvector and Katz centralities can be extremely sensitive to changes in the topology of the input graph. In other words, if the input graph has some specific features, even small changes in the topology of the input graph can have catastrophic effects on the Eigenvector or Katz centrality.

The neural signature of psychomotor disturbance in depression

Up to 70% of patients with major depressive disorder present with psychomotor disturbance (PmD), but at the present time understanding of its pathophysiology is limited. In this study, we capitalized on a large sample of patients to examine the neural correlates of PmD in depression. This study included 820 healthy participants and 699 patients with remitted (n = 402) or current (n = 297) depression. Patients were further categorized as having psychomotor retardation, agitation, or no PmD. We compared resting-state functional connectivity (ROI-to-ROI) between nodes of the cerebral motor network between the groups, including primary motor cortex, supplementary motor area, sensory cortex, superior parietal lobe, caudate, putamen, pallidum, thalamus, and cerebellum. Additionally, we examined network topology of the motor network using graph theory. Among the currently depressed 55% had PmD (15% agitation, 29% retardation, and 11% concurrent agitation and retardation), while 16% of the remitted patients had PmD (8% retardation and 8% agitation). When compared with controls, currently depressed patients with PmD showed higher thalamo-cortical and pallido-cortical connectivity, but no network topology alterations. Currently depressed patients with retardation only had higher thalamo-cortical connectivity, while those with agitation had predominant higher pallido-cortical connectivity. Currently depressed patients without PmD showed higher thalamo-cortical, pallido-cortical, and cortico-cortical connectivity, as well as altered network topology compared to healthy controls. Remitted patients with PmD showed no differences in single connections but altered network topology, while remitted patients without PmD did not differ from healthy controls in any measure. We found evidence for compensatory increased cortico-cortical resting-state functional connectivity that may prevent psychomotor disturbance in current depression, but may perturb network topology. Agitation and retardation show specific connectivity signatures. Motor network topology is slightly altered in remitted patients arguing for persistent changes in depression. These alterations in functional connectivity may be addressed with non-invasive brain stimulation.

Graph Theoretical Measures for Alzheimer’s, MCI, and Normal Controls: A Comparative Study Using MRI Data

Background The Graph theory provides the platform that could be used to model complex brain networks mathematically, and it could play a significant role in the diagnosis of various neurodegenerative diseases such as Alzheimer’s. Purpose The main aim of our study is to perform a comparative analysis in terms of various graph theoretic measures of structural brain networks. In particular, the paper evaluates graph theoretical measures by first forming graphs using magnetic resonance imaging (MRI) data. Method In this paper, we study and evaluate graph theoretical measures using MRI data, namely characteristic path length, global efficiency, strength, and clustering coefficient, in a cohort of normal controls ( N = 30), a cohort of mild cognitive impairment (MCI) ( N = 30), and a cohort of Alzheimer’s disease (AD) ( N = 30). In our work, MRI data is preprocessed and cortical thickness is extracted for each brain region. The connectivity matrix is obtained, and thus a graph is formed. We have also performed receiver operating characteristic (ROC) and area under the ROC analyses of all graph theoretical measures to better elucidate and validate the results. Results It is observed that these measures may be used to differentiate Alzheimer’s from normal. In our study, we observed that a very random and disrupted network is obtained in the case of Alzheimer’s in comparison with the normal and MCI cases. The other observations in terms of graph theoretic measures are an increase in characteristic path length, a decrease in global efficiency, a decrease in strength, and a reduction in values of the clustering coefficient in the case of Alzheimer’s. Conclusion The findings suggest that graph theoretical measures and alterations in network topology could be used as quantitative biomarkers of AD.

Resilient functioning is associated with altered structural brain network topology in adolescents exposed to childhood adversity.

Childhood adversity is one of the strongest predictors of adolescent mental illness. Therefore, it is critical that the mechanisms that aid resilient functioning in individuals exposed to childhood adversity are better understood. Here, we examined whether resilient functioning was related to structural brain network topology. We quantified resilient functioning at the individual level as psychosocial functioning adjusted for the severity of childhood adversity in a large sample of adolescents (N = 2406, aged 14-24). Next, we examined nodal degree (the number of connections that brain regions have in a network) using brain-wide cortical thickness measures in a representative subset (N = 275) using a sliding window approach. We found that higher resilient functioning was associated with lower nodal degree of multiple regions including the dorsolateral prefrontal cortex, the medial prefrontal cortex, and the posterior superior temporal sulcus (z > 1.645). During adolescence, decreases in nodal degree are thought to reflect a normative developmental process that is part of the extensive remodeling of structural brain network topology. Prior findings in this sample showed that decreased nodal degree was associated with age, as such our findings of negative associations between nodal degree and resilient functioning may therefore potentially resemble a more mature structural network configuration in individuals with higher resilient functioning.

From nose to brain: The effect of lemon inhalation observed by whole brain voxel to voxel functional connectivity

Lemon fragrance is known for its stimulating properties, but its mechanisms of action are not well known yet. This study aimed to examine the effect of lemon essential oil inhalation on healthy participants’ alertness level and their neural correlates using magnetic resonance imaging (MRI). Twenty-one healthy men underwent functional MRI scans in different conditions: a resting state condition, a condition where they were exposed to passive lemon smelling (alternating exposure to lemon and breathing fresh air), and a control condition without lemon fragrance diffusion –the order of the last two conditions being randomized. Alertness levels were assessed immediately after each condition using the Karolinska Sleepiness Scale. Voxel-wise whole-brain global functional connectivity and graph theory analyses were computed to investigate brain functional connectivity and network topology alterations. After lemon fragrance inhalation, we observed a higher level of alertness as compared to resting state –but not compared to control condition. During lemon fragrance inhalation, we found increased global functional connectivity in the thalamus, paralleled by decreased global connectivity in several cortical regions such as precuneus, postcentral and precentral gyrus, lateral occipital cortex and paracingulate gyrus. Graph theory analysis revealed increased network integration in cortical regions typically involved in olfaction and emotion processing such as olfactory bulb, hypothalamus and thalamus, while decreased network segregation in several regions of the posterior part of the brain during olfaction as compared to resting state. The present findings suggest that lemon essential oil inhalation could increase the level of alertness.

Disrupted longitudinal restoration of brain connectivity during weight normalization in severe anorexia nervosa

Altered intrinsic brain connectivity of patients with anorexia nervosa has been observed in the acute phase of the disorder, but it remains unclear to what extent these alterations recover during weight normalization. In this study, we used functional imaging data from three time points to probe longitudinal changes in intrinsic connectivity patterns in patients with severe anorexia nervosa (BMI ≤ 15.5 kg/m2) over the course of weight normalization. At three distinct stages of inpatient treatment, we examined resting-state functional connectivity in 27 women with severe anorexia nervosa and 40 closely matched healthy controls. Using network-based statistics and graph-theoretic measures, we examined differences in global network strength, subnetworks with altered intrinsic connectivity, and global network topology. Patients with severe anorexia nervosa showed weakened intrinsic connectivity and altered network topology which did not recover during treatment. The persistent disruption of brain networks suggests sustained alterations of information processing in weight-recovered severe anorexia nervosa.

Exploring the Restoration of Brain Connectivity during Weight Normalization in Severe Anorexia Nervosa

Abstract Anorexia nervosa is a persistent and often difficult to treat eating disorder with significant physical and mental health consequences. While it is known that the disorder is associated with alterations in brain functional connectivity during the phase of acute underweight, the effect of weight normalization on brain connectivity remains unclear. This talk focuses on the recovery of intrinsic brain connectivity during weight normalization in severe anorexia nervosa, presenting data from a longitudinal study. Using resting-state functional magnetic resonance imaging, we assessed brain connectivity at three different stages of inpatient treatment. Our findings indicate that patients with severe anorexia nervosa have weaker intrinsic connectivity and altered network topology, which do not improve during treatment. These persistent disruptions in brain networks suggest that severe anorexia nervosa may have long-term effects on the way the brain processes information, even after weight is restored. Disclosure of Interest None Declared

Clinical factors associated with microstructural connectome related brain dysmaturation in term neonates with congenital heart disease.

Term congenital heart disease (CHD) neonates display abnormalities of brain structure and maturation, which are possibly related to underlying patient factors, abnormal physiology and perioperative insults. Our primary goal was to delineate associations between clinical factors and postnatal brain microstructure in term CHD neonates using diffusion tensor imaging (DTI) magnetic resonance (MR) acquisition combined with complementary data-driven connectome and seed-based tractography quantitative analyses. Our secondary goal was to delineate associations between mild dysplastic structural brain abnormalities and connectome and seed-base tractography quantitative analyses. These mild dysplastic structural abnormalities have been derived from prior human infant CHD MR studies and neonatal mouse models of CHD that were collectively used to calculate to calculate a brain dysplasia score (BDS) that included assessment of subcortical structures including the olfactory bulb, the cerebellum and the hippocampus. Neonates undergoing cardiac surgery for CHD were prospectively recruited from two large centers. Both pre- and postoperative MR brain scans were obtained. DTI in 42 directions was segmented into 90 regions using a neonatal brain template and three weighted methods. Clinical data collection included 18 patient-specific and 9 preoperative variables associated with preoperative scan and 6 intraoperative (e.g., cardiopulmonary bypass and deep hypothermic circulatory arrest times) and 12 postoperative variables associated with postoperative scan. We compared patient specific and preoperative clinical factors to network topology and tractography alterations on a preoperative neonatal brain MRI, and intra and postoperative clinical factors to network topology alterations on postoperative neonatal brain MRI. A composite BDS was created to score abnormal findings involving the cerebellar hemispheres and vermis, supratentorial extra-axial fluid, olfactory bulbs and sulci, hippocampus, choroid plexus, corpus callosum, and brainstem. The neuroimaging outcomes of this study included (1) connectome metrics: cost (number of connections) and global/nodal efficiency (network integration); (2) seed based tractography methods of fractional anisotropy (FA), radial diffusivity, and axial diffusivity. Statistics consisted of multiple regression with false discovery rate correction (FDR) comparing the clinical risk factors and BDS (including subcortical components) as predictors/exposures and the global connectome metrics, nodal efficiency, and seed based- tractography (FA, radial diffusivity, and axial diffusivity) as neuroimaging outcome measures. A total of 133 term neonates with complex CHD were prospectively enrolled and 110 had analyzable DTI. Multiple patient-specific factors including d-transposition of the great arteries (d-TGA) physiology and severity of impairment of fetal cerebral substrate delivery (i.e., how much the CHD lesion alters typical fetal circulation such that the highest oxygen and nutrient rich blood from the placenta are not directed toward the fetal brain) were predictive of preoperative reduced cost (p < 0.0073) and reduced global/nodal efficiency (p < 0.03). Cardiopulmonary bypass time predicted postoperative reduced cost (p < 0.04) and multiple postoperative factors [extracorporeal membrane oxygenation (ECMO), seizures and cardiopulmonary resuscitation (CPR)] were predictive of postoperative reduced cost and reduced global/nodal efficiency (p < 0.05). Anthropometric measurements (weight, length, and head size) predicted tractography outcomes. Total BDS was not predictive of brain network topology. However, key subcortical components of the BDS score did predict key global and nodal network topology: abnormalities of the cerebellum predicted reduced cost (p < 0.0417) and of the hippocampus predicted reduced global efficiency (p < 0.0126). All three subcortical structures predicted unique alterations of nodal efficiency (p < 0.05), including hippocampal abnormalities predicting widespread reduced nodal efficiency in all lobes of the brain, cerebellar abnormalities predicting increased prefrontal nodal efficiency, and olfactory bulb abnormalities predicting posterior parietal-occipital nodal efficiency. Patient-specific (d-TGA anatomy, preoperative impairment of fetal cerebral substrate delivery) and postoperative (e.g., seizures, need for ECMO, or CPR) clinical factors were most predictive of diffuse postnatal microstructural dysmaturation in term CHD neonates. Anthropometric measurements (weight, length, and head size) predicted tractography outcomes. In contrast, subcortical components (cerebellum, hippocampus, olfactory) of a structurally based BDS (derived from CHD mouse mutants), predicted more localized and regional postnatal microstructural differences. Collectively, these findings suggest that brain DTI connectome and seed-based tractography are complementary techniques which may facilitate deciphering the mechanistic relative contribution of clinical and genetic risk factors related to poor neurodevelopmental outcomes in CHD.

Graph Theory Analysis of the Cortical Functional Network During Sleep in Patients With Depression.

Depression, a common mental illness that seriously affects the psychological health of patients, is also thought to be associated with abnormal brain functional connectivity. This study aimed to explore the differences in the sleep-state functional network topology in depressed patients. A total of 25 healthy participants and 26 depressed patients underwent overnight 16-channel electroencephalography (EEG) examination. The cortical networks were constructed by using functional connectivity metrics of participants based on the weighted phase lag index (WPLI) between the EEG signals. The results indicated that depressed patients exhibited higher global efficiency and node strength than healthy participants. Furthermore, the depressed group indicated right-lateralization in the δ band. The top 30% of connectivity in both groups were shown in undirected connectivity graphs, revealing the distinct link patterns between the depressed and control groups. Links between the hemispheres were noted in the patient group, while the links in the control group were only observed within each hemisphere, and there were many long-range links inside the hemisphere. The altered sleep-state functional network topology in depressed patients may provide clues for a better understanding of the depression pathology. Overall, functional network topology may become a powerful tool for the diagnosis of depression.

Resting-State Functional Network Topology Alterations of the Occipital Lobe Associated With Attention Impairment in Isolated Rapid Eye Movement Behavior Disorder.

PurposeThis study investigates the topological properties of brain functional networks in patients with isolated rapid eye movement sleep behavior disorder (iRBD).Participants and MethodsA total of 21 patients with iRBD (iRBD group) and 22 healthy controls (HCs) were evaluated using resting-state functional MRI (rs-fMRI) and neuropsychological measures in cognitive and motor function. Data from rs-fMRI were analyzed using graph theory, which included small-world properties, network efficiency, network local efficiency, nodal shortest path, node efficiency, and network connectivity, as well as the relationship between behavioral characteristics and altered brain topological features.ResultsRey-Osterrieth complex figure test (ROCFT-copy), symbol digital modalities test (SDMT), auditory verbal learning test (AVLT)-N1, AVLT-N2, AVLT-N3, and AVLT-N1-3 scores were significantly lower in patients with iRBD than in HC (P < 0.05), while trail making test A (TMT-A), TMT-B, and Unified Parkinson’s Disease Rating Scale Part-III (UPDRS-III) scores were higher in patients with iRBD (P < 0.05). Compared with the HCs, patients with iRBD had no difference in the small-world attributes (P > 0.05). However, there was a significant decrease in network global efficiency (P = 0.0052) and network local efficiency (P = 0.0146), while an increase in characteristic path length (P = 0.0071). There was lower nodal efficiency in occipital gyrus and nodal shortest path in frontal, parietal, temporal lobe, and cingulate gyrus. Functional connectivities were decreased between the nodes of occipital with the regions where they had declined nodal shortest path. There was a positive correlation between TMT-A scores and the nodal efficiency of the right middle occipital gyrus (R = 0.602, P = 0.014).ConclusionThese results suggest that abnormal behaviors may be associated with disrupted brain network topology and functional connectivity in patients with iRBD and also provide novel insights to understand pathophysiological mechanisms in iRBD.

Anomalies in global network connectivity associated with early recovery from alcohol dependence: A network transcranial magnetic stimulation and electroencephalography study.

Although previous research in alcohol dependent populations identified alterations within local structures of the addiction ‘reward’ circuitry, there is limited research into global features of this network, especially in early recovery. Transcranial magnetic stimulation (TMS) is capable of non‐invasively perturbing the brain network while electroencephalography (EEG) measures the network response. The current study is the first to apply a TMS inhibitory paradigm while utilising network science (graph theory) to quantify network anomalies associated with alcohol dependence. Eleven individuals with alcohol‐dependence (ALD) in early recovery and 16 healthy controls (HC) were administered 75 single pulses and 75 paired‐pulses (inhibitory paradigm) to both the left and right prefrontal cortex (PFC). For each participant, Pearson cross‐correlation was applied to the EEG data and correlation matrices constructed. Global network measures (mean degree, clustering coefficient, local efficiency and global efficiency) were extracted for comparison between groups. Following administration of the inhibitory paired‐pulse TMS to the left PFC, the ALD group exhibited altered mean degree, clustering coefficient, local efficiency and global efficiency compared to HC. Decreases in local efficiency increased the prediction of being in the ALD group, while all network metrics (following paired‐pulse left TMS) were able to adequately discriminate between the groups. In the ALD group, reduced mean degree and global clustering was associated with increased severity of past alcohol use. Our study provides preliminary evidence of altered network topology in patients with alcohol dependence in early recovery. Network anomalies were predictive of high alcohol use and correlated with clinical features of alcohol dependence. Further research using this novel brain mapping technique may identify useful network biomarkers of alcohol dependence and recovery.

Functional network connectivity and topology during naturalistic stimulus is altered in first-episode psychosis

BackgroundPsychotic disorders have been suggested to derive from dysfunctional integration of signaling between brain regions. Earlier studies have found several changes in functional network synchronization as well as altered network topology in patients with psychotic disorders. However, studies have used mainly resting-state that makes it more difficult to link functional alterations to any specific stimulus or experience. We set out to examine functional connectivity as well as graph (topological) measures and their association to symptoms in first-episode psychosis patients during movie viewing. Our goal was to understand whole-brain functional dynamics of complex naturalistic information processing in psychosis and changes in brain functional organization related to symptoms. Methods71 first-episode psychosis patients and 57 control subjects watched scenes from the movie Alice in Wonderland during 3 T fMRI. We compared functional connectivity and graph measures indicating integration, segregation and centrality between groups, and examined the association between topology and symptom scores in the patient group. ResultsWe identified a subnetwork with predominantly decreased links of functional connectivity in first-episode psychosis patients. The subnetwork was mainly comprised of nodes of and links between the cingulo-opercular, sensorimotor and default-mode networks. In topological measures, we observed between-group differences in properties of centrality. ConclusionsFunctional brain networks are affected during naturalistic information processing already in the early stages of psychosis, concentrated in salience- and cognitive control-related hubs and subnetworks. Understanding these aberrant dynamics could add to better targeted cognitive and behavioral interventions in the early stages of psychotic disorders.

EEG based functional brain networks analysis in dyslexic children during arithmetic task.

Developmental Dyslexia is a neuro-developmental disorder that often refers to a phonological processing deficit regardless of average IQ. The present study investigated the distinct functional changes in brain networks of dyslexic children during arithmetic task performance using an electroencephalogram. Fifteen dyslexic children and fifteen normally developing children (NDC) were recruited and performed an arithmetic task. Brain functional network measures such as node strength, clustering coefficient, characteristic pathlength and small-world were calculated using graph theory methods for both groups. Task performance showed significantly less performance accuracy in dyslexics against NDC. The neural findings showed increased connectivity in the delta band and reduced connectivity in theta, alpha, and beta band at temporoparietal, and prefrontal regions in dyslexic group while performing the task. The node strengths were found to be significantly high in delta band (T3, O1, F8 regions) and low in theta (T5, P3, Pz regions), beta (Pz) and gamma band (T4 and prefrontal regions) during the task in dyslexics compared to the NDC. The clustering coefficient was found to be significantly low in the dyslexic group (theta and alpha band) and characteristic pathlength was found to be significantly high in the dyslexic group (theta and alpha band) compared to the NDC group while performing task. In conclusion, the present study shows evidence for poor fact-retrieval mechanism and altered network topology in dyslexic brain networks during arithmetic task performance.

Cognitive Training in Parkinson\u2019s Disease Induces Local, Not Global, Changes in White Matter Microstructure

Previous studies showed that cognitive training can improve cognitive performance in various neurodegenerative diseases but little is known about the effects of cognitive training on the brain. Here, we investigated the effects of our cognitive training paradigm, COGTIPS, on regional white matter microstructure and structural network topology. We previously showed that COGTIPS has small, positive effects on processing speed. A subsample of 79 PD patients (N = 40 cognitive training group, N = 39 active control group) underwent multi-shell diffusion-weighted imaging pre- and post-intervention. Our pre-registered analysis plan (osf.io/cht6g) entailed investigating white matter microstructural integrity (e.g., fractional anisotropy) in five tracts of interest, including the anterior thalamic radiation (ATR), whole-brain tract-based spatial statistics (TBSS), and the topology of the structural network. Relative to the active control condition, cognitive training had no effect on topology of the structural network or whole-brain TBSS. Cognitive training did lead to a reduction in fractional anisotropy in the ATR (B [SE]: − 0.32 [0.12], P = 0.01). This reduction was associated with faster responses on the Tower of London task (r = 0.42, P = 0.007), but this just fell short of our statistical threshold (P < 0.006). Post hoc “fixel-based” analyses showed that this was not due to changes in fiber density and cross section. This suggests that the observed effect in the ATR is due to training-induced alterations in neighboring fibers running through the same voxels, such as intra-striatal and thalamo-striatal fibers. These results indicate that 8 weeks of cognitive training does not alter network topology, but has subtle local effects on structural connectivity.

Altered Brain Functional Network Topology in Lung Cancer Patients After Chemotherapy.

Purpose: This study aimed to explore the topological features of brain functional network in lung cancer patients before and after chemotherapy using graph theory.Methods: Resting-state functional magnetic resonance imaging scans were obtained from 44 post-chemotherapy and 46 non-chemotherapy patients as well as 49 healthy controls (HCs). All groups were age- and gender-matched. Then, the topological features of brain functional network were assessed using graph theory analysis.Results: At the global level, compared with the HCs, both the non-chemotherapy group and the post-chemotherapy group showed significantly increased values in sigma (p < 0.05), gamma (p < 0.05), and local efficiency, Eloc (p < 0.05). The post-chemotherapy group and the non-chemotherapy group did not differ significantly in the above-mentioned parameters. At the nodal level, when non-chemotherapy or post-chemotherapy patients were compared with the HCs, abnormal nodal centralities were mainly observed in widespread brain regions. However, when the post-chemotherapy group was compared with the non-chemotherapy group, significantly decreased nodal centralities were observed primarily in the prefrontal–subcortical regions.Conclusions: These results indicate that lung cancer and chemotherapy can disrupt the topological features of functional networks, and chemotherapy may cause a pattern of prefrontal–subcortical brain network abnormality. As far as we know, this is the first study to report that altered functional brain networks are related to lung cancer and chemotherapy.

The unbalanced reorganization of weaker functional connections induces the altered brain network topology in schizophrenia

Network neuroscience shed some light on the functional and structural modifications occurring to the brain associated with the phenomenology of schizophrenia. In particular, resting-state functional networks have helped our understanding of the illness by highlighting the global and local alterations within the cerebral organization. We investigated the robustness of the brain functional architecture in 44 medicated schizophrenic patients and 40 healthy comparators through an advanced network analysis of resting-state functional magnetic resonance imaging data. The networks in patients showed more resistance to disconnection than in healthy controls, with an evident discrepancy between the two groups in the node degree distribution computed along a percolation process. Despite a substantial similarity of the basal functional organization between the two groups, the expected hierarchy of healthy brains' modular organization is crumbled in schizophrenia, showing a peculiar arrangement of the functional connections, characterized by several topologically equivalent backbones. Thus, the manifold nature of the functional organization’s basal scheme, together with its altered hierarchical modularity, may be crucial in the pathogenesis of schizophrenia. This result fits the disconnection hypothesis that describes schizophrenia as a brain disorder characterized by an abnormal functional integration among brain regions.

Decline of anterior cingulate functional network efficiency in first-episode, medication-naïve somatic symptom disorder and its relationship with catastrophizing

The high prevalence of somatic symptom disorder (SSD) led to cumulative burdens to the medical system. However, the pathogenesis of this disease still remains unclear. Graph theoretical analysis discovered altered network topology across various psychiatric disorders, yet alteration in the topological structure of brain functional network in SSD patients is still unexplored. Catastrophizing is a common cognitive distortion in SSD. We hypothesize that the network topological metrics of SSD should be altered, and should correlate with catastrophizing scales. 32 medication-naïve, first-episode SSD patients and 30 age, gender matched HCs were recruited. The 17-item Hamilton Depression Rating Scale (HAMD-17), Hamilton Anxiety Rating Scale (HAMA) and Cognitive Emotion Regulation Questionnaire (CERQ) were accessed. Functional MRI were scanned and brain functional networks were constructed based on 166 anatomically cerebrum regions from the automated anatomical labeling 3 (AAL3) template. Network topological metrics were calculated and compared between the two groups. Correlation between these metrics and clinical scales were also calculated. Network global efficiency of SSD was significantly lower than that of HC. Nodal global efficiency of the left subgenual anterior cingulate cortex (sgACC) of SSD was significantly lower than that of HC. FCs between the left sgACC and other 21 seed nodes were significantly declined in SSD in comparison with HC. In SSD group, HAMD total score was significantly negatively correlated with the connection between the left medial superior frontal gyrus and the left sgACC. CERQ catastrophizing score was significantly negatively correlated with nodal global efficiency of left sgACC and with the FCs between the left sgACC and other 13 seed nodes. Catastrophizing could reflect the specific sgACC-centered dysfunction of brain network global efficiency of SSD. The left sgACC may be a future treatment target of dealing with catastrophizing, which is a core cognitive distortion of SSD.

Source-level EEG and graph theory reveal widespread functional network alterations in focal epilepsy

ObjectiveThe hypersynchronous neuronal activity associated with epilepsy causes widespread functional network disruptions extending beyond the epileptogenic zone. This altered network topology is considered a mediator for non-seizure symptoms, such as cognitive impairment. The aim of this study was to investigate functional network alterations in focal epilepsy patients with good seizure control and high quality of life. MethodsWe compared twenty-two focal epilepsy patients and sixteen healthy controls on graph metrics derived from functional connectivity of source-level resting-state EEG. Graph metrics were calculated over a range of network densities in five frequency bands. ResultsWe observed a significantly increased small world index in patients relative to controls. On the local level, two left-hemisphere regions displayed a shift towards greater alpha band “hubness”. The findings were not mediated by age, sex or education, nor by age of epilepsy onset, duration or focus lateralisation. ConclusionsWidespread functional network alterations are evident in focal epilepsy, even in a cohort characterised by successful anti-seizure medication therapy and high quality of life. These findings might support the position that functional network analysis could hold clinical relevance for epilepsy. SignificanceFocal epilepsy is accompanied by global and local functional network aberrancies which might be implied in the sustenance of non-seizure symptoms.

Berberine alters gut microbial function through modulation of bile acids

BackgroundBerberine (BBR) is a plant-based nutraceutical that has been used for millennia to treat diarrheal infections and in contemporary medicine to improve patient lipid profiles. Reduction in lipids, particularly cholesterol, is achieved partly through up-regulation of bile acid synthesis and excretion into the gastrointestinal tract (GI). The efficacy of BBR is also thought to be dependent on structural and functional alterations of the gut microbiome. However, knowledge of the effects of BBR on gut microbiome communities is currently lacking. Distinguishing indirect effects of BBR on bacteria through altered bile acid profiles is particularly important in understanding how dietary nutraceuticals alter the microbiome.ResultsGermfree mice were colonized with a defined minimal gut bacterial consortium capable of functional bile acid metabolism (Bacteroides vulgatus, Bacteroides uniformis, Parabacteroides distasonis, Bilophila wadsworthia, Clostridium hylemonae, Clostridium hiranonis, Blautia producta; B4PC2). Multi-omics (bile acid metabolomics, 16S rDNA sequencing, cecal metatranscriptomics) were performed in order to provide a simple in vivo model from which to identify network-based correlations between bile acids and bacterial transcripts in the presence and absence of dietary BBR. Significant alterations in network topology and connectivity in function were observed, despite similarity in gut microbial alpha diversity (P = 0.30) and beta-diversity (P = 0.123) between control and BBR treatment. BBR increased cecal bile acid concentrations, (P < 0.05), most notably deoxycholic acid (DCA) (P < 0.001). Overall, analysis of transcriptomes and correlation networks indicates both bacterial species-specific responses to BBR, as well as functional commonalities among species, such as up-regulation of Na+/H+ antiporter, cell wall synthesis/repair, carbohydrate metabolism and amino acid metabolism. Bile acid concentrations in the GI tract increased significantly during BBR treatment and developed extensive correlation networks with expressed genes in the B4PC2 community.ConclusionsThis work has important implications for interpreting the effects of BBR on structure and function of the complex gut microbiome, which may lead to targeted pharmaceutical interventions aimed to achieve the positive physiological effects previously observed with BBR supplementation.

Structural network topology in limbic encephalitis is associated with amygdala enlargement, memory performance and serostatus.

Limbic encephalitis (LE) forms a spectrum of autoimmune diseases involving temporal lobe epilepsy and memory impairment. Imaging features of LE are known to depend on the associated antibody and to occur on the brain network level. However, first studies investigating brain networks in LE have either focused on one distinct antibody subgroup or on distinct anatomical regions. In this study, brain graphs of 17 LE patients with autoantibodies against glutamic acid decarboxylase 65 (GAD-LE), four LE patients with autoantibodies against leucine-rich glioma-inactivated 1, five LE patients with autoantibodies against contactin-associated protein-like 2, 26 age- and gender-matched healthy control subjects, and 20 epilepsy control patients with hippocampal sclerosis were constructed based on T1-weighted structural magnetic resonance imaging scans and diffusion tensor imaging. GAD-LE showed significantly altered global network topology in terms of integration and segregation as compared to healthy controls and patients with hippocampal sclerosis (P<.01, analysis of variance with Tukey-Kramer post hoc tests). Linear regression linked global network measures with amygdala volume and verbal memory performance (P<.05). Alterations of local network topology show serotype dependence in hippocampus, amygdala, insula, and various cortical regions. Our findings reveal serotype-dependent patterns of structural connectivity and prove the relevance of in silico network measures on clinical grounds.