Functional Brain Network Topology Research Articles

Topological Perturbations in the Functional Connectome Support the Deficit/Non-deficit Distinction in Antipsychotic Medication-Naïve First Episode Psychosis Patients.

Heterogeneity in the etiology, pathophysiology, and clinical features of schizophrenia challenges clinicians and researchers. A helpful approach could be stratifying patients according to the presence or absence of clinical features of the deficit syndrome (DS). DS is characterized by enduring and primary negative symptoms, a clinically less heterogeneous subtype of the illness, and patients with features of DS are thought to present abnormal brain network characteristics, however, this idea has received limited attention. We investigated functional brain network topology in patients displaying deficit features and those who do not. We applied graph theory analytics to resting-state functional magnetic resonance imaging data of 61 antipsychotic medication-naïve first episode psychosis patients, 18 DS and 43 non-deficit schizophrenia (NDS), and 72 healthy controls (HC). We quantified small-worldness, global and nodal efficiency measures, shortest path length, nodal local efficiency, and synchronization and contrasted them among the 3 groups. DS presented decreased network integration and segregation compared to HC and NDS. DS showed lower global efficiency, longer global path lengths, and lower global local efficiency. Nodal efficiency was lower and the shortest path length was longer in DS in default mode, ventral attention, dorsal attention, frontoparietal, limbic, somatomotor, and visual networks compared to HC. Compared to NDS, DS showed lower efficiency and longer shortest path length in default mode, limbic, somatomotor, and visual networks. Our data supports increasing evidence, based on topological perturbations of the functional connectome, that deficit syndrome may be a distinct form of the illness.

The alterations of functional brain networks and its relationship with sport decision-making and training duration in soccer players across different skill levels

Studies have indicated that skilled soccer players possess superior decision-making abilities compared to their less-skilled counterparts. However, the underlying neural mechanism for this phenomenon remains incompletely understood. In our investigation, we explored distinctions in the topology of functional brain networks between skilled and less-skilled soccer players. Employing mediating analysis, we scrutinized the relationships among functional brain network parameters, training duration, and decision-making accuracy. Our findings revealed that skilled soccer players demonstrated significantly higher decision-making accuracy compared to their less-skilled counterparts. Skilled players also exhibited increased values in the cluster coefficient, characteristic path length and local efficiency but lower global efficiency. Moreover, we observed enhanced functional brain connectivity within the occipital and cingulo-opercular networks, as well as between the fronto-parietal and cingulo-opercular networks in skilled soccer players. Cluster coefficient and functional connectivity between fronto-parietal and cingulo-opercular networks had positive mediating effects on the association between training duration and sport decision-making accuracy. In conclusion, our study provides initial evidence for distinctions in functional brain network parameters between soccer players with varying skill levels and their relationship with sport decision-making accuracy.

Sex differences in fetal brain functional network topology.

The fetal period is a critical stage in brain development, and understanding the characteristics of the fetal brain is crucial. Although some studies have explored aspects of fetal brain functional networks, few have specifically focused on sex differences in brain network characteristics. We adopted the graph theory method to calculate brain network functional connectivity and topology properties (including global and nodal properties), and further compared the differences in these parameters between male and female fetuses. We found that male fetuses showed an increased clustering coefficient and local efficiency than female fetuses, but no significant group differences concerning other graph parameters and the functional connectivity matrix. Our study suggests the existence of sex-related distinctions in the topological properties of the brain network at the fetal stage of development and demonstrates an increase in brain network separation in male fetuses compared with female fetuses.

Disrupted properties of functional brain networks in major depressive disorder during emotional face recognition: an EEG study via graph theory analysis.

Previous neuroimaging studies have revealed abnormal brain networks in patients with major depressive disorder (MDD) in emotional processing. While any cognitive task consists of a series of stages, little is yet known about the topology of functional brain networks in MDD for these stages during emotional face recognition. To address this problem, electroencephalography (EEG)-based functional brain networks of MDD patients at different stages of facial information processing were investigated in this study. First, EEG signals were collected from 16 patients with MDD and 18 age-, gender-, and education-matched normal subjects when performing an emotional face recognition task. Second, the global field power (GFP) method was employed to divide group-averaged event-related potentials into different stages. Third, using the phase transfer entropy (PTE) approach, the brain networks of MDD patients and normal individuals were constructed for each stage in negative and positive face processing, respectively. Finally, we compared the topological properties of brain networks of each stage between the two groups using graph theory approaches. The results showed that the analyzed three stages of emotional face processing corresponded to specific neurophysiological phases, namely, visual perception, face recognition, and emotional decision-making. It was also demonstrated that depressed patients showed abnormally decreased characteristic path length at the visual perception stage of negative face recognition and normalized characteristic path length in the stage of emotional decision-making during positive face processing compared to healthy subjects. Furthermore, while both the MDD and normal groups' brain networks were found to exhibit small-world network characteristics, the brain network of patients with depression tended to be randomized. Moreover, for patients with MDD, the centro-parietal region may lose its status as a hub in the process of facial expression identification. Together, our findings suggested that altered emotional function in MDD patients might be associated with disruptions in the topological organization of functional brain networks during emotional face recognition, which further deepened our understanding of the emotion processing dysfunction underlying MDD.

Mapping brain functional networks topological characteristics in new daily persistent headache: a magnetoencephalography study

BackgroundThe brain functional network topology in new daily persistent headache (NDPH) is not well understood. In this study, we aim to assess the cortical functional network topological characteristics of NDPH using non-invasive neural signal recordings.MethodsResting-state magnetoencephalography (MEG) was used to measure power fluctuations in neuronal oscillations from distributed cortical parcels in 35 patients with NDPH and 40 healthy controls (HCs). Their structural data were collected by 3T MRI. Functional connectivity (FC) of neural networks from 1 to 80 Hz frequency ranges was analyzed with topographic patterns and calculated network topological parameters with graph theory.ResultsIn the delta (1–4 Hz) and beta (13–30 Hz) bands, the lateral occipital cortex and superior frontal gyrus FC were increased in NDPH groups compared to HCs. Graph theory analysis revealed that the NDPH had significantly increased global efficiency in the delta band and decreased nodal clustering coefficient (left medial orbitofrontal cortex) in the theta (4–8 Hz) band. The clinical characteristics had a significant correlation with network topological parameters. Age at onset of patients showed a positive correlation with global efficiency in the delta band. The degree of depression of patients showed a negative correlation with the nodal clustering coefficient (left medial orbitofrontal cortex) in the theta band.ConclusionThe FC and topology of NDPH in brain networks may be altered, potentially leading to cortical hyperexcitability. Moreover, medial orbitofrontal cortex is involved in the pathophysiological mechanism of depression in patients with NDPH. Increased FC observed in the lateral occipital cortex and superior frontal gyrus during resting-state MEG could serve as one of the imaging characteristics associated with NDPH.

TCM meridian type influences the effect of functional brain network topology remodeling in healthy individuals

TCM meridian type influences the effect of functional brain network topology remodeling in healthy individuals

Association of aberrant structural-functional network coupling with cognitive decline in patients with non-dialysis-dependent stage 5 chronic kidney disease.

Cognitive decline exists in the chronic kidney disease (CKD) population and is particularly severe in patients with stage 5 CKD, but the mechanisms underlying this relationship are unclear. Structural-functional coupling, an integrated measure that combines functional and structural networks, offers the possibility of exploring changes in network relationships in patients with stage 5 CKD. This study aimed to investigate the brain network topology and structural-functional coupling characteristics in patients with non-dialysis-dependent stage 5 CKD (CKD 5ND) and the correlation between network changes and cognitive scores. We prospectively performed diffusion tensor and resting-state functional magnetic resonance (rs-fMRI) imaging on 40 patients with CKD 5ND disease and 47 healthy controls (HCs). Graph theory analysis of functional and structural connectivity (SC) was performed. Small-world properties and network efficiency properties were calculated, including characteristic path length (Lp), clustering coefficient (Cp), normalized clustering coefficient (Gamma), normalized characteristic path length (Lambda), small-worldness (Sigma), global efficiency (Eglob), and local efficiency (Eloc). The SC-functional connectivity (FC) coupling characteristics and the association between Montreal Cognitive Assessment (MoCA) scores and graph-theoretical features were analyzed. For SC, the Sigma (P=0.009), Cp (P=0.01), Eglob (P<0.001), and Eloc (P=0.01) were significantly lower in patients with CKD 5ND than in HCs, while Lp (P<0.001) and Lambda (P<0.001) were significantly higher in the patients than in the HCs. For FC, the Sigma (P=0.008), Gamma (P=0.009), Eglob (P=0.04), and Eloc (P<0.0001) were lower in patients with CKD 5ND than in HCs; however, the Lp (P=0.02) was higher in the patients than in the HCs. SC-SC coupling (P<0.001) was greater in patients with CKD 5ND than in HCs. The structural (Cp, Eloc, Eglob) and functional network parameters (Sigma, Gamma, Eglob) of the patients with CKD 5ND were positively correlated with MoCA scores; however, the Lp of both structural and functional networks was negatively correlated with MoCA scores. All patients with CKD 5ND included in the study exhibited changes in their structural and functional brain network topology closely related to mild cognitive impairment. SC-SC coupling was elevated in the patients compared with that in the controls. This may provide vital information for understanding and revealing the underlying mechanisms of cognitive impairment in patients with CKD 5ND.

Upregulation of a Small-World Brain Network Improves Inhibitory Control: An fNIRS Neurofeedback Training Study.

The aim of this study was to investigate the inner link between the small-world brain network and inhibitory control. Functional near-infrared spectroscopy (fNIRS) was used to construct a neurofeedback (NF) training system and regulate the frontal small-world brain network. The small-world network downregulation group (DOWN, n = 17) and the small-world network upregulation group (UP, n = 17) received five days of fNIRS-NF training and performed the color-word Stroop task before and after training. The behavioral and functional brain network topology results of both groups were analyzed by a repeated-measures analysis of variance (ANOVA), which showed that the upregulation training helped to improve inhibitory control. The upregulated small-world brain network exhibits an increase in the brain network regularization, links widely dispersed brain resources, and reduces the lateralization of brain functional networks between hemispheres. This suggests an inherent correlation between small-world functional brain networks and inhibitory control; moreover, dynamic optimization under cost efficiency trade-offs provides a neural basis for inhibitory control. Inhibitory control is not a simple function of a single brain region or connectivity but rather an emergent property of a broader network.

Aberrant functional brain network organization is associated with relapse during 1-year follow-up in alcohol-dependent patients.

Alcohol dependence (AD) is a debilitating disease associated with high relapse rates even after long periods of abstinence. Thus, elucidating neurobiological substrates of relapse risk is fundamental for the development of novel targeted interventions that could promote long-lasting abstinence. In the present study, we analysed resting-state functional magnetic resonance imaging (rsfMRI) data from a sample of recently detoxified patients with AD (n = 93) who were followed up for 12 months after rsfMRI assessment. Specifically, we employed graph theoretic analyses to compare functional brain network topology and functional connectivity between future relapsers (REL, n = 59), future abstainers (ABS, n = 28) and age- and gender-matched controls (CON, n = 83). Our results suggest increased whole-brain network segregation, decreased global network integration and overall blunted connectivity strength in REL compared with CON. Conversely, we found evidence for a comparable network architecture in ABS relative to CON. At the nodal level, REL exhibited decreased integration and decoupling between multiple brain systems compared with CON, encompassing regions associated with higher-order executive functions, sensory and reward processing. Among patients with AD, increased coupling between nodes implicated in reward valuation and salience attribution constitutes a particular risk factor for future relapse. Importantly, aberrant network organization in REL was consistently associated with shorter abstinence duration during follow-up, portending to a putative neural signature of relapse risk in AD. Future research should further evaluate the potential diagnostic value of the identified changes in network topology and functional connectivity for relapse prediction at the individual subject level.

A study of brain networks associated with Freezing of gait in Parkinson’s disease using transfer entropy analysis

BackgroundParkinson's disease (PD) is a common neurodegenerative disease in the elderly. Freezing of Gait (FOG) is one of the common motor symptoms of PD, but the potential mechanism remains unclear. This study aimed to investigate the changes of brain functional network topology in PD patients with FOG. MethodsThe resting electroencephalogram (EEG) were acquired from15 PD patients with FOG (PD-FOG), 13 PD patients without FOG (PD-nFOG), and 16 healthy control (HC). Cognitive and motor functions were assessed using subjective scales. The whole-brain functional networks were constructed based on transfer entropy. Transfer entropy was used to analyse the information flow and causality in the network and the network connectivity was analyzed by graph theory. The characteristics of PD-FOG and PD-nFOG were compared by receiver operator characteristic (ROC) curve analysis. ResultsThe θ bands brain network of PD-FOG, PD-nFOG and HC group was significantly different (P < 0.05). The average characteristic path length of the θ bands brain network was positively correlated with FOG Questionnaire (FOGQ). PD-FOG and PD-nFOG get high classification accuracy according to this feature. The information inflow in the frontal and occipital lobes and information outflow in the temporal lobe of PD-FOG patients in the θ bands increased significantly. ConclusionsThe whole-brain functional network characteristics of PD-FOG in the θ bands can serve as potential biomarkers for early diagnosis of PD-FOG. Abnormal information flow of the frontal, occipital, and temporal lobes in the θ bands may be an important factor leading to FOG.

Relationship between 4-month functional brain network topology and 24-month neurodevelopmental outcome in children with congenital heart disease

Survivors of complex forms of congenital heart disease (CHD)∗ are at high risk of neurodevelopmental disabilities. Neuroimaging studies have pointed to brain anomalies and immature networks in infants with CHD, yet less is known about their functional network topology and associations with neurodevelopment. To characterize the functional network topology in 4-month-old infants with repaired CHD, we compared graph theory metrics measured using resting-state functional near-infrared spectroscopy (rs-fNIRS) between infants with CHD (n = 22) and healthy controls (n = 30). We also investigated the moderating effect of graph theory metrics on the relationship between group (CHD vs. Controls) and developmental outcomes at 24 months. At 4 months, both groups presented similar functional brain network topology. At 24 months, children with CHD had lower scores on the language scale and the expressive communication subscale of the Bayley Scales of Infant and Toddler Development, Third Edition (Bayley-III), as well as lower scores on the Grammatical Form scale of the MacArthur-Bates Communicative Development Inventory (MBCDI). The relationship between group and expressive language was moderated by the normalized characteristic path length (λ) and the degree (k). Although infants with CHD have functional brain topology similar to that of healthy controls, our findings suggest that they do not benefit from an optimal functional brain organization in comparison with healthy infants.

Differences in Brain Functional Network Topology in High and Low Working Memory Performance

Nowadays the network approach in neuroscience provides a promising way of analyzing neurophysiological mechanisms that underlie psychological functions and is widely used to study working memory. To date, data obtained in neuroimaging studies links working memory with topological features of brain networks, such as increased connectivity between frontal, parietal, and temporal regions, as well as increased integration in brain networks as a whole. The present study examines the relationship between the topological characteristics of functional brain networks with the performance in the Sternberg item recognition paradigm based on electroencephalographic data. It is shown that the higher performance in Sternberg paradigm, implying a higher efficiency of the processes of encoding, storage, and retrieval of information from working memory, is associated with an increase in the integration of functional networks, expressed in differences in the clustering coefficient, participation coefficient, Wiener index and eigenvector centrality between the groups of high and low working memory task performance (p &lt; .01). In addition, our data suggest the variability in the topological pattern of connectivity, which can be traced through changes in the magnitude of the standard deviation of the values of topological metrics during the task.

A Graph Theory Study of Resting-State Functional MRI Connectivity in Children With Carbon Monoxide Poisoning.

The effect of carbon monoxide (CO) poisoning on the topology of brain functional networks is unclear, especially in children whose brains are still developing. To investigate the topological alterations of the whole-brain functional connectome in children with CO poisoning and characterize its relationship with disease severity. Cross-sectional and prospective study. A total of 26 patients with CO poisoning and 26 healthy controls. A 3.0 T MRI system/echo planar imaging (EPI) and 3D brain volume imaging (BRAVO) sequences. We used the network-based statistics (NBS) method to explore between-group differences in functional connectivity strength and a graph-theoretical-based analytic method to explore the topology of brain networks. Student's t-test, chi-square test, NBS, Pearson correlation coefficient, and false discovery rate correction. The statistical significance threshold was set at P < 0.05. The case group's brain functional network topology was impaired in comparison to the control group (reduced global efficiency and small-worldness, increased characteristic path length). According to node and edge analyses, the case group showed topologically damaged regions in the frontal lobe and basal ganglia, as well as neuronal circuits with weaker connections. Also, there was a significant correlation between the patients' coma time and the degree (r = -0.4564), efficiency (r = -0.4625), and characteristic path length (r = 0.4383) of the nodes in the left orbital inferior frontal gyrus. Carbon monoxide hemoglobin content (COHb) concentration and right rolandic operculum node characteristic path length (r = -0.3894) were significantly correlated. The node efficiency and node degree of the right middle frontal gyrus (r = 0.4447 and 0.4539) and right pallidum (r = 0.4136 and 0.4501) significantly correlated with the MMSE score. The brain network topology of CO poisoned children is damaged, which is manifested by reduced network integration and may lead to a series of clinical symptoms in patients. 2. Stage 2.

Altered whole-brain resting-state functional connectivity and brain network topology in typhoon-related post-traumatic stress disorder.

Altered resting-state functional connectivity has been found in patients with post-traumatic stress disorder (PTSD). However, the alteration of resting-state functional connectivity at whole-brain level in typhoon-traumatized individuals with PTSD remains largely unknown. To investigate changes in whole-brain resting-state functional connectivity and brain network topology in typhoon-traumatized subjects with and without PTSD. Cross-sectional study. Twenty-seven patients with typhoon-related PTSD, 33 trauma-exposed controls (TEC), and 30 healthy controls (HC) underwent resting-state functional MRI scanning. The whole brain resting-state functional connectivity network was constructed based on the automated anatomical labeling atlas. The graph theory method was used to analyze the topological properties of the large-scale resting-state functional connectivity network. Whole-brain resting-state functional connectivity and the topological network property were compared by analyzing the variance. There was no significant difference in the area under the curve of γ, λ, σ, global efficiency, and local efficiency among the three groups. The PTSD group showed increased dorsal cingulate cortex (dACC) resting-state functional connectivity with the postcentral gyrus (PoCG) and paracentral lobe and increased nodal betweenness centrality in the precuneus relative to both control groups. Compared with the PTSD and HC groups, the TEC group showed increased resting-state functional connectivity between the hippocampus and PoCG and increased connectivity strength in the putamen. In addition, compared with the HC group, both the PTSD and TEC groups showed increased connectivity strength and nodal efficiency in the insula. Aberrant resting-state functional connectivity and topology were found in all trauma-exposed individuals. These findings broaden our knowledge of the neuropathological mechanisms of PTSD.

Altered brain functional network topology in Obsessive-Compulsive Disorder: A comparison of patients with varying severity of depressive symptoms and the impact on psychosocial functioning

BackgroundObsessive-compulsive disorder (OCD) is associated with psychosocial impairment, which can be exacerbated by depressive symptoms. In this study, we employed graph theory analysis to investigate the association among neuroimaging, clinical features, and psychosocial functioning in OCD patients, with a specific focus on the differential impact of depressive symptoms. Methods216 OCD patients were divided into two subgroups based on depressive symptoms. Resting-state functional MRI data were acquired from a subset of 106 OCD patients along with 77 matched healthy controls (HCs). We analyzed the topological characteristics of the entire brain and the cognition-related subnetworks and performed Pearson correlation analyses to further explore the relationship with psychosocial functioning. ResultsOCD patients with more severe depressive symptoms exhibited greater impairment across all dimensions of psychosocial functioning. Graph theory analysis revealed more pronounced reductions in network efficiency within the entire brain, the default mode network (DMN), and the cingulo-opercular network (CON) among patients with non or mild depressive symptoms. Lower nodal efficiency and degree centrality of the right superior temporal gyrus (STG) were found in OCD patients and these variables were positively correlated with psychosocial functioning impairment. ConclusionsThis study revealed that the presence of depressive symptoms generally exacerbated psychosocial functioning impairment in OCD patients. Abnormalities in the functional integration of the entire brain, the DMN, and the CON in OCD patients may comprise the basis of cognitive deficits, while dysfunction of the right STG may affect the psychosocial functioning through its role in emotion, intention perception, and insight.

Associations between disrupted functional brain network topology and cognitive impairment in patients with rectal cancer during chemotherapy.

Cognitive impairment has been identified in patients with non-central nervous system cancer received chemotherapy. Chemotherapy-induced changes in the brain are considered as the possible causes of the cognitive deficits of patients. This study aimed to explore chemotherapy-related functional brain changes and cognitive impairment in rectal cancer (RC) patients who had just finished chemotherapy treatment. In this study, RC patients after chemotherapy (on the day patients received the last dose of chemotherapy) (n=30) and matched healthy controls (HCs) (n=30) underwent cognitive assessments, structural magnetic resonance imaging (MRI) and resting-state functional MRI. The functional brain networks were constructed by thresholding the partial correlation matrices of 90 brain regions in the Anatomical Automatic Labeling template and the topologic properties were evaluated by graph theory analysis. Moreover, correlations between altered topological measures and scores of cognitive scales were explored in the patient group. Compared with HCs, RC patients had lower scores of cognitive scales. The functional brain network had preserved small-world topological features but with a tendency towards higher path length in the whole network. In addition, patients had decreased nodal global efficiency (Eglo(i)) in the left superior frontal gyrus (dorsolateral), superior frontal gyrus (orbital part), inferior frontal gyrus (opercular part), inferior frontal gyrus (triangular part) and right inferior frontal gyrus (triangular part). Moreover, values of Eglo(i) in the superior and inferior frontal gyrus were positively associated with cognitive function in the patient group. These results suggested that cognitive impairment was associated with disruptions of the topological organization in functional brain networks of RC patients who had just finished chemotherapy, which provided new insights into the pathophysiology underlying acute effects of chemotherapy on cognitive function.

Method for persistent topological features extraction of schizophrenia patients' electroencephalography signal based on persistent homology.

With the development of network science and graph theory, brain network research has unique advantages in explaining those mental diseases, the neural mechanism of which is unclear. Additionally, it can provide a new perspective in revealing the pathophysiological mechanism of brain diseases from the system level. The selection of threshold plays an important role in brain networks construction. There are no generally accepted criteria for determining the proper threshold. Therefore, based on the topological data analysis of persistent homology theory, this study developed a multi-scale brain network modeling analysis method, which enables us to quantify various persistent topological features at different scales in a coherent manner. In this method, the Vietoris–Rips filtering algorithm is used to extract dynamic persistent topological features by gradually increasing the threshold in the range of full-scale distances. Subsequently, the persistent topological features are visualized using barcodes and persistence diagrams. Finally, the stability of persistent topological features is analyzed by calculating the Bottleneck distances and Wasserstein distances between the persistence diagrams. Experimental results show that compared with the existing methods, this method can extract the topological features of brain networks more accurately and improves the accuracy of diagnostic and classification. This work not only lays a foundation for exploring the higher-order topology of brain functional networks in schizophrenia patients, but also enhances the modeling ability of complex brain systems to better understand, analyze, and predict their dynamic behaviors.

Analysis on topological alterations of functional brain networks after acute alcohol intake using resting-state functional magnetic resonance imaging and graph theory.

AimsAlcohol consumption could lead to a series of health problems and social issues. In the current study, we investigated the resting-state functional brain networks of healthy volunteers before and after drinking through graph-theory analysis, aiming to ascertain the effects of acute alcohol intake on topology and information processing mode of the functional brain networks.Materials and methodsThirty-three healthy volunteers were enrolled in this experiment. Each volunteer accepted alcohol breathalyzer tests followed by resting-state magnetic resonance imaging at three time points: before drinking, 0.5 h after drinking, and 1 h after drinking. The data obtained were grouped based on scanning time into control group, 0.5-h group and 1-h group, and post-drinking data were regrouped according to breath alcohol concentration (BrAC) into relative low BrAC group (A group; 0.5-h data, n = 17; 1-h data, n = 16) and relative high BrAC group (B group; 0.5-h data, n = 16; 1-h data, n = 17). The graph-theory approach was adopted to construct whole-brain functional networks and identify the differences of network topological properties among all the groups.ResultsThe network topology of most groups was altered after drinking, with the B group presenting the most alterations. For global network measures, B group exhibited increased global efficiency, Synchronization, and decreased local efficiency, clustering coefficient, normalized clustering coefficient, characteristic path length, normalized characteristic path length, as compared to control group. Regarding nodal network measures, nodal clustering coefficient and nodal local efficiency of some nodes were lower in B group than control group. These changes suggested that the network integration ability and synchrony improved, while the segregation ability diminished.ConclusionThis study revealed the effects of acute alcohol intake on the topology and information processing mode of resting-state functional brain networks, providing new perceptions and insights into the effects of alcohol on the brain.

The trend of disruption in the functional brain network topology of Alzheimer’s disease

Alzheimer’s disease (AD) is a progressive disorder associated with cognitive dysfunction that alters the brain’s functional connectivity. Assessing these alterations has become a topic of increasing interest. However, a few studies have examined different stages of AD from a complex network perspective that cover different topological scales. This study used resting state fMRI data to analyze the trend of functional connectivity alterations from a cognitively normal (CN) state through early and late mild cognitive impairment (EMCI and LMCI) and to Alzheimer’s disease. The analyses had been done at the local (hubs and activated links and areas), meso (clustering, assortativity, and rich-club), and global (small-world, small-worldness, and efficiency) topological scales. The results showed that the trends of changes in the topological architecture of the functional brain network were not entirely proportional to the AD progression. There were network characteristics that have changed non-linearly regarding the disease progression, especially at the earliest stage of the disease, i.e., EMCI. Further, it has been indicated that the diseased groups engaged somatomotor, frontoparietal, and default mode modules compared to the CN group. The diseased groups also shifted the functional network towards more random architecture. In the end, the methods introduced in this paper enable us to gain an extensive understanding of the pathological changes of the AD process.

Reorganized Brain Functional Network Topology in Presbycusis.

PurposePresbycusis is characterized by bilateral sensorineural hearing loss at high frequencies and is often accompanied by cognitive decline. This study aimed to identify the topological reorganization of brain functional network in presbycusis with/without cognitive decline by using graph theory analysis approaches based on resting-state functional magnetic resonance imaging (rs-fMRI).MethodsResting-state fMRI scans were obtained from 30 presbycusis patients with cognitive decline, 30 presbycusis patients without cognitive decline, and 50 age-, sex-, and education-matched healthy controls. Graph theory was applied to analyze the topological properties of brain functional networks including global and nodal metrics, modularity, and rich-club organization.ResultsAt the global level, the brain functional networks of all participants were found to possess small-world properties. Also, significant group differences in global network metrics were observed among the three groups such as clustering coefficient, characteristic path length, normalized characteristic path length, and small-worldness. At the nodal level, several nodes with abnormal betweenness centrality, degree centrality, nodal efficiency, and nodal local efficiency were detected in presbycusis patients with/without cognitive decline. Changes in intra-modular connections in frontal lobe module and inter-modular connections in prefrontal subcortical lobe module were found in presbycusis patients exposed to modularity analysis. Rich-club nodes were reorganized in presbycusis patients, while the connections among them had no significant group differences.ConclusionPresbycusis patients exhibited topological reorganization of the whole-brain functional network, and presbycusis patients with cognitive decline showed more obvious changes in these topological properties than those without cognitive decline. Abnormal changes of these properties in presbycusis patients may compensate for cognitive impairment by mobilizing additional neural resources.