Eigenvector Centrality Mapping Research Articles

Age-dependent effects of brain stimulation on network centrality

Functional magnetic resonance imaging (fMRI) studies have suggested that advanced age may mediate the effects of transcranial direct current stimulation (tDCS) on brain function. However, studies directly comparing neural tDCS effects between young and older adults are scarce and limited to task-related imaging paradigms. Resting-state (rs-) fMRI, that is independent of age-related differences in performance, is well suited to investigate age-associated differential neural tDCS effects. Three “online” tDCS conditions (anodal, cathodal, sham) were compared in a cross-over, within-subject design, in 30 young and 30 older adults. Active stimulation targeted the left sensorimotor network (active electrode over left sensorimotor cortex with right supraorbital reference electrode). A graph-based rs-fMRI data analysis approach (eigenvector centrality mapping) and complementary seed-based analyses characterized neural tDCS effects. An interaction between anodal tDCS and age group was observed. Specifically, centrality in bilateral paracentral and posterior regions (precuneus, superior parietal cortex) was increased in young, but decreased in older adults. Seed-based analyses revealed that these opposing patterns of tDCS-induced centrality modulation originated from differential effects of tDCS on functional coupling of the stimulated left paracentral lobule. Cathodal tDCS did not show significant effects. Our study provides first evidence for differential tDCS effects on neural network organization in young and older adults. Anodal stimulation mainly affected coupling of sensorimotor with ventromedial prefrontal areas in young and decoupling with posteromedial areas in older adults.

Disrupted Functional Connectivity of Basal Ganglia across Tremor-Dominant and Akinetic/Rigid-Dominant Parkinson's Disease.

It is well known that disruption of basal ganglia function generates the motor symptoms in PD, however, these are presented in a heterogeneous manner; patients can be divided into tremor-dominant and akinesia/rigidity-dominant subtypes. To date, it is unknown if these differences in the motor symptoms could be explained by differences on the functional connectivity of basal ganglia with specific brain regions. In this study, we aimed to explore the alterations of the network-based and global functional connectivity linking to basal ganglia between the PD-TD and PD-AR patients. One hundred and six PD patients and 52 normal controls were recruited. According to the subscales of UPDRS motor scale, PD patients were divided into the PD-TD (n = 57) and PD-AR (n = 49) subtypes. We performed independent component analysis to identify basal ganglia network (BGN) involving connected brain regions having coactivation with basal ganglia. Eigenvector centrality mapping were processed and the eigenvector centrality in the subcortical component of BGN including the bilateral caudate nuclei, putamen, thalami and pallidum were extracted to measure the global connectivity. Compared with controls, whole PD patients or PD subtypes showed decreases of functional connectivity within the subcortical component of BGN, e.g., thalamus, pallidum and putamen. Compared with controls, decreased functional connectivity of precuneus and amygdala with basal ganglia was observed in the PD-TD while that of occipital lobule and precuneus was observed in the PD-AR. Compared with the PD-TD, significantly decreased functional connectivity between occipital lobule and cerebellum posterior lobule and basal ganglia was observed in the PD-AR, and such connectivity had positive correlations with tremor and negative correlations with akinesia/rigidity. We also observed enhanced global connectivity in the caudate nucleus and thalamus in the PD subtypes compared with controls. In conclusion, PD patients independent of motor subtypes consistently express similar alterations of functional connectivity within the subcortical component of BGN including network-based connectivity and global connectivity. Functional connectivity of cerebellum posterior lobule and occipital lobule with basal ganglia play important roles in the modulation of parkinsonian motor symptoms.

Age-related functional brain changes in young children

Brain function and structure change significantly during the toddler and preschool years. However, most studies focus on older or younger children, so the specific nature of these changes is unclear. In the present study, we analyzed 77 functional magnetic resonance imaging datasets from 44 children aged 2–6 years. We extracted measures of both local (amplitude of low frequency fluctuation and regional homogeneity) and global (eigenvector centrality mapping) activity and connectivity, and examined their relationships with age using robust linear correlation analysis and strict control for head motion. Brain areas within the default mode network and the frontoparietal network, such as the middle frontal gyrus, the inferior parietal lobule and the posterior cingulate cortex, showed increases in local and global functional features with age. Several brain areas such as the superior parietal lobule and superior temporal gyrus presented opposite development trajectories of local and global functional features, suggesting a shifting connectivity framework in early childhood. This development of functional connectivity in early childhood likely underlies major advances in cognitive abilities, including language and development of theory of mind. These findings provide important insight into the development patterns of brain function during the preschool years, and lay the foundation for future studies of altered brain development in young children with brain disorders or injury.

Altered eigenvector centrality is related to local resting-state network functional connectivity in patients with longstanding type 1 diabetes mellitus.

Longstanding type 1 diabetes (T1DM) is associated with microangiopathy and poorer cognition. In the brain, T1DM is related to increased functional resting-state network (RSN) connectivity in patients without, which was decreased in patients with clinically evident microangiopathy. Subcortical structure seems affected in both patient groups. How these localized alterations affect the hierarchy of the functional network in T1DM is unknown. Eigenvector centrality mapping (ECM) and degree centrality are graph theoretical methods that allow determining the relative importance (ECM) and connectedness (degree centrality) of regions within the whole-brain network hierarchy. Therefore, ECM and degree centrality of resting-state functional MRI-scans were compared between 51 patients with, 53 patients without proliferative retinopathy, and 49 controls, and associated with RSN connectivity, subcortical gray matter volume, and cognition. In all patients versus controls, ECM and degree centrality were lower in the bilateral thalamus and the dorsal striatum, with lowest values in patients without proliferative retinopathy (PFWE < 0.05). Increased ECM in this group versus patients with proliferative retinopathy was seen in the bilateral lateral occipital cortex, and in the right cuneus and occipital fusiform gyrus versus controls (PFWE < 0.05). In all patients, ECM and degree centrality were related to altered visual, sensorimotor, and auditory and language RSN connectivity (PFWE < 0.05), but not to subcortical gray matter volume or cognition (PFDR > 0.05). The findings suggested reorganization of the hierarchy of the cortical connectivity network in patients without proliferative retinopathy, which is lost with disease progression. Centrality seems sensitive to capture early T1DM-related functional connectivity alterations, but not disease progression. Hum Brain Mapp 38:3623-3636, 2017. © 2017 Wiley Periodicals, Inc.

Working memory capacity and the functional connectome - insights from resting-state fMRI and voxelwise centrality mapping.

The functional connectome represents a comprehensive network map of functional connectivity throughout the human brain. To date, the relationship between the organization of functional connectivity and cognitive performance measures is still poorly understood. In the present study we use resting-state functional magnetic resonance imaging (fMRI) data to explore the link between the functional connectome and working memory capacity in an individual differences design. Working memory capacity, which refers to the maximum amount of context information that an individual can retain in the absence of external stimulation, was assessed outside the MRI scanner and estimated based on behavioral data from a change detection task. Resting-state time series were analyzed by means of voxelwise degree and eigenvector centrality mapping, which are data-driven network analytic approaches for the characterization of functional connectivity. We found working memory capacity to be inversely correlated with both centrality in the right intraparietal sulcus. Exploratory analyses revealed that this relationship was putatively driven by an increase in negative connectivity strength of the structure. This resting-state connectivity finding fits previous task based activation studies that have shown that this area responds to manipulations of working memory load.

Increased network centrality as markers of relapse risk in nicotine-dependent individuals treated with varenicline

Identifying smokers at high risk of relapse could improve the effectiveness of cessation therapies. Although altered regional brain function in smokers has been reported, whether the whole-brain functional organization differs smokers with relapse vulnerability from others remains unclear. Thus, the goal of this study is to investigate the baseline functional connectivity differences between relapsers and quitters. Using resting-state fMRI, we acquired images from 57 smokers prior to quitting attempts. After 12-week treatment with varenicline, smokers were divided into relapsers (n=36) and quitters (n=21) (quitter: continuously abstinent for weeks 9–12). The smoking cessation outcomes were cross-validated by self-reports and expired carbon monoxide. We then used eigenvector centrality (EC) mapping to identify the functional connectivity differences between relapsers and quitters. When compared to quitters, increased EC in the right dorsolateral prefrontal cortex (DLPFC), left middle temporal gyrus (MTG) and cerebellum anterior lobe was observed in relapsers. In addition, a logistic regression analysis of EC data (with DLPFC, MTG and cerebellum included) predicted relapse with 80.7% accuracy. These findings suggest that the DLPFC, MTG and cerebellum may be important substrates of smoking relapse vulnerability. The data also suggest that relapse-vulnerable smokers can be identified before quit attempts, which could enable personalized treatment and improve smoking cessation outcomes.

General and selective brain connectivity alterations in essential tremor: A resting state fMRI study.

Although essential tremor is the most common movement disorder, there is little knowledge about the pathophysiological mechanisms of this disease. Therefore, we explored brain connectivity based on slow spontaneous fluctuations of blood oxygenation level dependent (BOLD) signal in patients with essential tremor (ET). A cohort of 19 ET patients and 23 healthy individuals were scanned in resting condition using functional magnetic resonance imaging (fMRI). General connectivity was assessed by eigenvector centrality (EC) mapping. Selective connectivity was analyzed by correlations of the BOLD signal between the preselected seed regions and all the other brain areas. These measures were then correlated with the tremor severity evaluated by the Fahn-Tolosa-Marin Tremor Rating Scale (FTMTS). Compared to healthy subjects, ET patients were found to have lower EC in the cerebellar hemispheres and higher EC in the anterior cingulate and in the primary motor cortices bilaterally. In patients, the FTMTS score correlated positively with the EC in the putamen. In addition, the FTMTS score correlated positively with selective connectivity between the thalamus and other structures (putamen, pre-supplementary motor area (pre-SMA), parietal cortex), and between the pre-SMA and the putamen. We observed a selective coupling between a number of areas in the sensorimotor network including the basal ganglia and the ventral intermediate nucleus of thalamus, which is widely used as neurosurgical target for tremor treatment. Finally, ET was marked by suppression of general connectivity in the cerebellum, which is in agreement with the concept of ET as a disorder with cerebellar damage.

Sustained Effects of Acupuncture Stimulation Investigated with Centrality Mapping Analysis.

Acupuncture can have instant and sustained effects, however, its mechanisms of action are still unclear. Here, we investigated the sustained effect of acupuncture by evaluating centrality changes in resting-state functional magnetic resonance imaging after manually stimulating the acupuncture point ST36 at the lower leg or two control point locations (CP1 same dermatome, CP2 different dermatome). Data from a previously published experiment evaluating instant BOLD effects and S2-seed-based resting state connectivity was re-analyzed using eigenvector centrality mapping and degree centrality mapping. These data-driven methods might add new insights into sustained acupuncture effects on both global and local inter-region connectivity (centrality) by evaluating the summary of connections of every voxel. We found higher centrality in parahippocampal gyrus and middle temporal gyrus after ST36 stimulation in comparison to the two control points. These regions are positively correlated to major hubs of the default mode network, which might be the primary network affected by chronic pain. The stronger integration of both regions within the whole-brain connectome after stimulation of ST36 might be a potential contributor to pain modulation by acupuncture. These findings highlight centrality mapping as a valuable analysis for future imaging studies investigating clinically relevant outcomes associated with physiological response to acupuncture stimulation. Clinical trial registration: NCT01079689, ClinicalTrials.gov.

Disrupted Brain Network in Progressive Mild Cognitive Impairment Measured by Eigenvector Centrality Mapping is Linked to Cognition and Cerebrospinal Fluid Biomarkers.

Mild cognitive impairment (MCI) is a heterogeneous condition associated with a high risk of progressing to Alzheimer's disease (AD). Although functional brain network alterations have been observed in progressive MCI (pMCI), the underlying pathological mechanisms of network alterations remain unclear. In the present study, we evaluated neuropsychological, imaging, and cerebrospinal fluid (CSF) data at baseline across a cohort of: 21 pMCI patients, 33 stable MCI (sMCI) patients, and 29 normal controls. Fast eigenvector centrality mapping (fECM) based on resting-state functional MRI (rsfMRI) was used to investigate brain network organization differences among these groups, and we further assessed its relation to cognition and AD-related pathology. Our results demonstrated that pMCI had decreased eigenvector centrality (EC) in left temporal pole and parahippocampal gyrus, and increased EC in left middle frontal gyrus compared to sMCI. In addition, compared to normal controls, patients with pMCI showed decreased EC in right hippocampus and bilateral parahippocampal gyrus, and sMCI had decreased EC in right middle frontal gyrus and superior parietal lobule. Correlation analysis showed that EC in the left temporal pole was related to Wechsler Memory Scale-Revised Logical Memory (WMS-LM) delay score (r = 0.467, p = 0.044) and total tau (t-tau) level in CSF (r = -0.509, p = 0.026) in pMCI. Our findings implicate EC changes of different brain network nodes in the prognosis of pMCI and sMCI. Importantly, the association between decreased EC of brain network node and pathological changes may provide a deeper understanding of the underlying pathophysiology of pMCI.

Intrinsic functional connectivity alterations in cognitively intact elderly APOE ε4 carriers measured by eigenvector centrality mapping are related to cognition and CSF biomarkers: a preliminary study.

Apolipoprotein E (APOE) ε4 allele is the best established genetic risk factor for sporadic Alzheimer's disease (AD). However, there is a need to understand the effects of this genotype on the brain by simultaneously assessing intrinsic brain network and cerebral spinal fluid (CSF) biomarkers changes in healthy older ε4 carriers. Thirteen cognitively intact, elderly APOE ε4 carriers and 22 ε3 homozygotes were included in the present study. Eigenvector centrality mapping (ECM) was used to identify brain network hub organization based on resting-state functional MRI (rsfMRI). We evaluated comprehensive cognitive ability and tested levels of Aβ1-42, total-tau (t-tau) and phosphorylated-tau (p-tau181) in CSF. Comparisons of ECM between two groups were conducted, followed by correlations analyses between EC values with significant group differences and cognitive ability/CSF biomarkers. APOE ε4 carriers showed significantly decreased EC values in left medial temporal lobe (MTL), left lingual gyrus (LG) and increased EC values in left middle frontal gyrus (MFG) as compared to non-carriers. Correlation analysis demonstrated that left LG EC value correlated with Rey Auditory Verbal Learning Test total learning (RAVLT, r=0.57, p<0.05) and t-tau level (r=-0.57, p<0.05), while left MFG EC values correlated with log-transformed Trail-Making Test B (TMT-B, r=-0.67, p<0.05) in APOE ε4 carriers. This study suggests the APOE ε4 allele contributes to disruption of brain connectedness in certain functional nodes, which may result from neuronal death caused by toxicity of neurofibrillary tangles.

Changes of Cerebral Perfusion andFunctional Brain Network Organization inPatients with Mild Cognitive Impairment.

Disruptions of the functional brain network and cerebral blood flow (CBF) have been revealed in patients with mild cognitive impairment (MCI). However, the neurophysiological mechanism of hypoperfusion as well as the reorganization of the intrinsic whole brain network due to the neuropathology of MCI are still unclear. In this study, we aimed to investigate the changes of CBF and the whole brain network organization in MCI by using a multimodal MRI approach. Resting state ASL MRI and BOLD MRI were used to evaluate disruptions of CBF and underlying functional connectivity in 27 patients with MCI and 35 cognitive normal controls (NC). The eigenvector centrality mapping (ECM) was used to assess the whole brain network reorganization in MCI, and a seed-based ECM approach was proposed to reveal the contributions of the whole brain network on the ECM alterations. Significantly decreased perfusion in the posterior parietal cortex as well as its connectivity within the default mode network and occipital cortex were found in the MCI group compared to the NC group. The ECM analysis revealed decreased EC in the middle cingulate cortex, parahippocampal gyrus, medial frontal gyrus, and increased EC in the right calcarine sulcus, superior temporal gyrus, and supplementary motor area in the MCI group. The results of this study indicate that there are deficits in cerebral blood flow and functional connectivity in the default mode network, and that sensory-processing networks might play a compensatory role to make up for the decreased connections in MCI.

DECREASED INTRINSIC FUNCTIONAL NETWORK IN COGNITIVELY INTACT ELDERLY APOE-E4 CARRIERS MEASURED BY EIGENVECTOR CENTRALITY MAPPING

DECREASED INTRINSIC FUNCTIONAL NETWORK IN COGNITIVELY INTACT ELDERLY APOE-E4 CARRIERS MEASURED BY EIGENVECTOR CENTRALITY MAPPING

Aberrant emotion networks in early major depressive disorder patients: an eigenvector centrality mapping study.

Major depressive disorder (MDD) is a serious mental disorder that negatively affects the quality of life of many individuals, and is a heavy economic burden to society. In recent years it was thought that depression is a ‘disconnection syndrome'. Disorganized brain activity and un-modulated emotion responses were considered the key neuropathologies underlying depression. In the present study, we investigated the alteration of whole brain network connectivity in 28 first-episode, drug-naive patients, using resting-state functional magnetic resonance imaging and a new analytical method called voxel-based eigenvector centrality mapping. We found that compared with normal controls, MDD patients had lower functional connectivity in the bilateral middle frontal gyrus, insula, hippocampus, amygdala and cerebellum, and higher functional connectivity in the medial prefrontal cortex. The functional connectivity strength at the right hippocampus (r=−0.413, P=0.032) and the right insula (r=−0.372, P=0.041) negatively correlated with the severity of the disease. We further examined coordination among these regions, and found that frontal–subcortical connection was reduced and insula–mPFC connection was increased. These results are consistent with previous hypotheses on the neural mechanism of MDD, and provide further evidence that emotion networks are already interrupted in early stages of depression.

Serum BDNF correlates with connectivity in the (pre)motor hub in the aging human brain—a resting-state fMRI pilot study

Brain-derived neurotrophic factor (BDNF) has been discussed to be involved in plasticity processes in the human brain, in particular during aging. Recently, aging and its (neurodegenerative) diseases have increasingly been conceptualized as disconnection syndromes. Here, connectivity changes in neural networks (the connectome) are suggested to be the most relevant and characteristic features for such processes or diseases. To further elucidate the impact of aging on neural networks, we investigated the interaction between plasticity processes, brain connectivity, and healthy aging by measuring levels of serum BDNF and resting-state fMRI data in 25 young (mean age 24.8 ± 2.7 (SD) years) and 23 old healthy participants (mean age, 68.6 ± 4.1 years). To identify neural hubs most essentially related to serum BDNF, we applied graph theory approaches, namely the new data-driven and parameter-free approach eigenvector centrality (EC) mapping. The analysis revealed a positive correlation between serum BDNF and EC in the premotor and motor cortex in older participants in contrast to young volunteers, where we did not detect any association. This positive relationship between serum BDNF and EC appears to be specific for older adults. Our results might indicate that the amount of physical activity and learning capacities, leading to higher BDNF levels, increases brain connectivity in (pre)motor areas in healthy aging in agreement with rodent animal studies. Pilot results have to be replicated in a larger sample including behavioral data to disentangle the cause for the relationship between BDNF levels and connectivity.

The Association of Glucose Metabolism and Eigenvector Centrality in Alzheimer's Disease.

Both fluorine-18-labeled fluorodeoxyglucose ([(18)F]FDG) positron emission tomography, examining glucose metabolism, and resting-state functional magnetic resonance imaging (rs-fMRI), using covarying blood oxygen levels, can be used to explore neuronal dysfunction in Alzheimer's disease (AD). Both measures are reported to identify similar brain regions affected in AD patients. The spatial overlap and association of [(18)F]FDG with rs-fMRI in AD patients and controls were examined to investigate whether these two measures are associated, and if so, to what extent. For 24 AD patients and 18 controls, [(18)F]FDG and rs-fMRI data were available. [(18)F]FDG standardized uptake value ratios (SUVr), with cerebellar gray matter (GM) as reference tissue, were calculated. Eigenvector centrality (EC) mapping was used to spatially analyze the functional brain network. Group differences were calculated for [(18)F]FDG and eigenvector centrality mapping (ECM) values in four cortical regions (occipital, parietal, frontal, and temporal) and across voxels, with age, gender, and GM as covariates. Correlation of [(18)F]FDG with ECM was calculated within groups. Both lowered [(18)F]FDG SUVr and EC values were seen in the parietal and occipital cortex of AD patients. However, [(18)F]FDG yielded more robust and widespread brain areas affected in AD patients; hypometabolism was also observed in the temporal cortex and regions within frontal brain areas. Poor spatial overlap of both measures was observed. No associations were found between local [(18)F]FDG SUVr and ECM. In conclusion, agreement of [(18)F]FDG and ECM in AD patients seems moderate at best. [(18)F]FDG was most accurate in distinguishing AD patients from controls.

Functional connectivity indicates differential roles for the intraparietal sulcus and the superior parietal lobule in multiple object tracking

Attentive tracking requires sustained object-based attention, rather than passive vigilance or rapid attentional shifts to brief events. Several theories of tracking suggest a mechanism of indexing objects that allows for attentional resources to be directed toward the moving targets. Imaging studies have shown that cortical areas belonging to the dorsal frontoparietal attention network increase BOLD-signal during multiple object tracking (MOT). Among these areas, some studies have assigned IPS a particular role in object indexing, but the neuroimaging evidence has been sparse. In the present study, we tested participants on a continuous version of the MOT task in order to investigate how cortical areas engage in functional networks during attentional tracking. Specifically, we analyzed the data using eigenvector centrality mapping (ECM) analysis, which provides estimates of individual voxels' connectedness with hub-like parts of the functional network. The results obtained using permutation based voxel-wise statistics support the proposed role for the IPS in object indexing as this region displayed increased centrality during tracking as well as increased functional connectivity with both prefrontal and visual perceptual cortices. In contrast, the opposite pattern was observed for the SPL, with decreasing centrality, as well as reduced functional connectivity with the visual and frontal cortices, in agreement with a hypothesized role for SPL in attentional shifts. These findings provide novel evidence that IPS and SPL serve different functional roles during MOT, while at the same time being highly engaged during tracking as measured by BOLD-signal changes.

Altered brain network centrality in depressed Parkinson's disease patients.

Depression is a relatively common and serious nonmotor symptom of Parkinson's disease (PD), which reduces the quality of patients' life. Although disturbances in some related brain networks have been reported, the pathophysiology of depression in PD is still unclear. Here, we aim to investigate whole-brain functional connectivity patterns in depressed PD patients. We recruited 17 PD patients diagnosed with major depressive disorder, 17 PD patients without depression, and 17 healthy control subjects. Resting-state functional MRI and eigenvector centrality mapping were used to identify functional connectivity alterations among these groups. Results showed that depressed PD patients had decreased functional connectivity in the left dorsolateral prefrontal cortex and right superior temporal gyrus and increased functional connectivity in the right posterior cingulate cortex, compared to nondepressed patients. In addition, there was a significant negative correlation between functional connectivity and depression scores in the posterior cingulate cortex. This study suggests that functional connectivity changes in certain nodes of brain networks might contribute to depression in patients with PD.

Voxelwise eigenvector centrality mapping of the human functional connectome reveals an influence of the catechol-O-methyltransferase val158met polymorphism on the default mode and somatomotor network.

Functional connections between brain regions constitute the substrate of the human functional connectome, whose topography has been discussed as an endophenotype for psychiatric disorders. Genetic influences on the entire connectome, however, have been rarely investigated so far. We tested for connectome-wide influences of the val158met (rs4860) polymorphism on the catechol-O-methyltransferase (COMT) gene by applying formal network analysis and eigenvector centrality mapping on the voxel level to resting-state functional magnetic imaging data. This approach finds brain regions that are central in the network by aggregating local and global connectivity patterns, most importantly without the requirement to select regions or networks of interest. The COMT variant linked to high enzyme activity increased network centrality in distributed brain areas that are known to constitute the brain's default mode network. Further results also indicated a COMT influence on areas implicated in the somatomotor network. These findings are in line with the polymorphism's alleged role in cognitive processing and its role in psychotic disorders. The study is the first to demonstrate the influence of a functional and behaviorally relevant genetic variant on connectome-wide functional connectivity and is an important step toward establishing the functional connectome as an endophenotype for psychiatric and behavioral phenotypes.

Progesterone mediates brain functional connectivity changes during the menstrual cycle—a pilot resting state MRI study

The growing interest in intrinsic brain organization has sparked various innovative approaches to generating comprehensive connectivity-based maps of the human brain. Prior reports point to a sexual dimorphism of the structural and functional human connectome. However, it is uncertain whether subtle changes in sex hormones, as occur during the monthly menstrual cycle, substantially impact the functional architecture of the female brain. Here, we performed eigenvector centrality (EC) mapping in 32 longitudinal resting state fMRI scans of a single healthy subject without oral contraceptive use, across four menstrual cycles, and assessed estrogen and progesterone levels. To investigate associations between cycle-dependent hormones and brain connectivity, we performed correlation analyses between the EC maps and the respective hormone levels. On the whole brain level, we found a significant positive correlation between progesterone and EC in the bilateral dorsolateral prefrontal cortex (DLPFC) and bilateral sensorimotor cortex. In a secondary region-of-interest analysis, we detected a progesterone-modulated increase in functional connectivity of both bilateral DLPFC and bilateral sensorimotor cortex with the hippocampus. Our results suggest that the menstrual cycle substantially impacts intrinsic functional connectivity, particularly in brain areas associated with contextual memory-regulation, such as the hippocampus. These findings are the first to link the subtle hormonal fluctuations that occur during the menstrual cycle, to significant changes in regional functional connectivity in the hippocampus in a longitudinal design, given the limitation of data acquisition in a single subject. Our study demonstrates the feasibility of such a longitudinal Resting-state functional Magnetic Resonance Imaging (rs-fMRI) design and illustrates a means of creating a personalized map of the human brain by integrating potential mediators of brain states, such as menstrual cycle phase.

Serum Neuron-Specific Enolase Is Related to Cerebellar Connectivity: A Resting-State Functional Magnetic Resonance Imaging Pilot Study.

Neuron-specific enolase (NSE) has been suggested as a prognostic biomarker for neuronal alterations resulting from conditions such as traumatic brain injury (TBI), neurodegenerative disease, or cardiac arrest. To validate serum NSE (sNSE) as a brain-specific biomarker, we related it to functional brain imaging data in 38 healthy adults to create a physiological framework for future studies in neuropsychiatric diseases. sNSE was measured by monoclonal two-site immunoluminometric assays, and functional connectivity was investigated with resting-state functional magnetic resonance imaging (rfMRI). To identify neural hubs most essentially related to sNSE, we applied graph theory approaches, namely, the new data-driven and parameter-free approach, eigenvector centrality mapping. sNSE and eigenvector centrality were negatively correlated in the female cerebellum, without any effects in male subjects. In cerebellar cortex, NSE expression was significantly higher than whole-brain expression as investigated in the whole brain and whole genome-wide atlas of the Allen Institute for Brain Sciences (Seattle, WA). Our study shows a specific linkage between the neuronal marker protein, sNSE, and cerebellar connectivity as measured with rfMRI in the female human brain, although this finding shall be proven in future studies including more subjects. Results suggest that the inclusion of sNSE in the analysis of imaging data is a useful approach to obtain more-specific information on the neuronal mechanisms that underlie functional connectivity at rest. Establishing such a baseline resting-state pattern that is tied to a neuronal serum marker opens new perspectives in the characterization of neuropsychiatric disorders as disconnective syndromes or nexopathies, in particular, resulting from TBI, neurodegenerative disease, or cardiac arrest, in the future.