Structural Connectivity Patterns Research Articles

Associations between handedness and brain functional connectivity patterns in children

Handedness develops early in life, but the structural and functional brain connectivity patterns associated with it remains unknown. Here we investigate associations between handedness and the asymmetry of brain connectivity in 9- to 10-years old children from the Adolescent Brain Cognitive Development (ABCD) study. Compared to right-handers, left-handers had increased global functional connectivity density in the left-hand motor area and decreased it in the right-hand motor area. A connectivity-based index of handedness provided a sharper differentiation between right- and left-handers. The laterality of hand-motor connectivity varied as a function of handedness in unimodal sensorimotor cortices, heteromodal areas, and cerebellum (P < 0.001) and reproduced across all regions of interest in Discovery and Replication subsamples. Here we show a strong association between handedness and the laterality of the functional connectivity patterns in the absence of differences in structural connectivity, brain morphometrics, and cortical myelin between left, right, and mixed handed children.

Structural connectivity of cytoarchitectonically distinct human left temporal pole subregions: a diffusion MRI tractography study.

The temporal pole (TP) is considered one of the major paralimbic cortical regions, and is involved in a variety of functions such as sensory perception, emotion, semantic processing, and social cognition. Based on differences in cytoarchitecture, the TP can be further subdivided into smaller regions (dorsal, ventrolateral and ventromedial), each forming key nodes of distinct functional networks. However, the brain structural connectivity profile of TP subregions is not fully clarified. Using diffusion MRI data in a set of 31 healthy subjects, we aimed to elucidate the comprehensive structural connectivity of three cytoarchitectonically distinct TP subregions. Diffusion tensor imaging (DTI) analysis suggested that major association fiber pathways such as the inferior longitudinal, middle longitudinal, arcuate, and uncinate fasciculi provide structural connectivity to the TP. Further analysis suggested partially overlapping yet still distinct structural connectivity patterns across the TP subregions. Specifically, the dorsal subregion is strongly connected with wide areas in the parietal lobe, the ventrolateral subregion with areas including constituents of the default-semantic network, and the ventromedial subregion with limbic and paralimbic areas. Our results suggest the involvement of the TP in a set of extensive but distinct networks of cortical regions, consistent with its functional roles.

White matter connectivity of subthalamic nucleus and globus pallidus interna targets for deep brain stimulation.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) and globus pallidus interna (GPi) have differential therapeutic effects for Parkinson's disease (PD) that drive patient selection. For example, GPi DBS is preferred for dystonic features and dyskinesia, whereas STN DBS has shown faster tremor control and medication reduction. Connectivity studies comparing these two targets, using patient-specific data, are still lacking. The objective was to find STN and GPi structural connectivity patterns in order to better understand differences in DBS-activated brain circuits between these two stimulation targets and to guide optimal contact selection. The authors simulated DBS activation along the main axis of both the STN and GPi by using volume of activated tissue (VAT) modeling with known average stimulation parameters (2.8 V and 60 μsec for STN; 3.3 V and 90 μsec for GPi). The authors modeled VATs in the anterior, middle, and posterior STN and the anterior, midanterior, midposterior, and posterior GPi. The authors generated maps of the connections shared by the patients for each VAT by using probabilistic tractography of diffusion-weighted imaging data obtained in 46 PD patients who underwent DBS (26 with STN and 20 with GPi targeting), and differences between VATs for whole-brain and distal regions of interest (prefrontal cortex, supplementary motor area, primary motor cortex, primary sensory cortex, caudate, motor thalamus, and cerebellum) were generated from structural atlases. Differences between maps were quantified and compared. VATs across the STN and GPi had different structural connectivity patterns. The authors found significant connectivity differences between VATs for all regions of interest. Posterior and middle STN showed stronger connectivity to the primary motor cortex and supplementary motor area (SMA) (p < 0.001). Posterior STN had the strongest connectivity to the primary sensory cortex and motor thalamus (p < 0.001). Posterior GPi showed stronger connectivity to the primary motor cortex (p < 0.001). Connectivity to the SMA was similar for the posterior and midposterior GPi (p > 0.05), which was greater than that for the anterior GPi (p < 0.001). When both nuclei were compared, posterior and middle STN had stronger connectivity to the SMA, cerebellum, and motor thalamus than GPi (all p < 0.001). Posterior GPi and STN had similar connectivity to the primary sensory cortex. On patient-specific imaging, structural connectivity differences existed between GPi and STN DBS, as measured with standardized electrical field modeling of the DBS targets. These connectivity differences may correlate with the differential clinical benefits obtained by targeting each of the two nuclei with DBS for PD. Prospective work is needed to relate these differences to clinical outcomes and to inform targeting and programming.

The neurobiology of openness as a personality trait.

Openness is a multifaceted behavioral disposition that encompasses personal, interpersonal, and cultural dimensions. It has been suggested that the interindividual variability in openness as a personality trait is influenced by various environmental and genetic factors, as well as differences in brain functional and structural connectivity patterns along with their various associated cognitive processes. Alterations in degree of openness have been linked to several aspects of health and disease, being impacted by both physical and mental health, substance use, and neurologic conditions. This review aims to explore the current state of knowledge describing the neurobiological basis of openness and how individual differences in openness can manifest in brain health and disease.

Functional and structural connectivity in the Papez circuit in different stages of Alzheimer’s disease

ObjectiveAlzheimer's disease (AD) is a progressive neurodegenerative continuum with memory impairment. We aimed to examine the detailed functional (FC) and structural connectivity (SC) pattern of the Papez circuit, known as the memory circuit, along the AD. MethodsMRI data of 15 patients diagnosed with AD dementia (ADD), 15 patients with the amnestic mild cognitive impairment (MCI), and 15 patients with subjective cognitive impairment were analyzed. The FC analyses were performed between main nodes of the Papez circuit, and the SC was quantified as fractional anisotropy (FA) of the main white matter pathways of the Papez circuit. ResultsThe FC between the retrosplenial (RSC) and parahippocampal cortices (PHC) was the earliest affected FC, while a manifest SC change in the ventral cingulum and fornix was observed in the later ADD stage. The RSC-PHC FC and the ventral cingulum FA efficiently predicted the memory performance of the non-demented participants. ConclusionsOur findings revealed the importance of the Papez circuit as target regions along the AD. SignificanceThe ventral cingulum connecting the RSC and PHC, a critical overlap area between the Papez circuit and the default mode network, seems to be a target region associated with the earliest objective memory findings in AD.

Diffusion-based structural connectivity patterns of multiple sclerosis phenotypes

BackgroundWe aimed to describe the severity of the changes in brain diffusion-based connectivity as multiple sclerosis (MS) progresses and the microstructural characteristics of these networks that are associated with distinct...

Temporal Patterns of Structural Sagebrush Connectivity from 1985 to 2020

The sagebrush biome within the western United States has been reshaped by disturbances, management, and changing environmental conditions. As a result, sagebrush cover and configuration have varied over space and time, influencing processes and species that rely on contiguous, connected sagebrush. Previous studies have documented changes in sagebrush cover, but we know little about how the connectivity of sagebrush has changed over time and across the sagebrush biome. We investigated temporal connectivity patterns for sagebrush using a time series (1985–2020) of fractional sagebrush cover and used an omnidirectional circuit algorithm to assess the density of connections among areas with abundant sagebrush. By comparing connectivity patterns over time, we found that most of the biome experienced moderate change; the amount and type of change varied spatially, indicating that areas differ in the trend direction and magnitude of change. Two different types of designated areas of conservation and management interest had relatively high proportions of stable, high-connectivity patterns over time and stable connectivity trends on average. These results provide ecological information on sagebrush connectivity persistence across spatial and temporal scales that can support targeted actions to address changing structural connectivity and to maintain functioning, connected ecosystems.

Exercise accelerates place cell representational drift

Stable neural ensembles are often thought to underlie stable learned behaviors and memory. Recent longitudinal experiments, however, that tracked the activity of the same neurons over days to weeks have shown that neuronal activity patterns can change over extended timescales even if behaviors remain the same - a phenomenon termed representational drift1. We have tested whether neural circuit remodeling, defined as any change in structural connectivity, contributes to representational drift. To do this, we tracked how hippocampal CA1 spatial representations of a familiar environment change with time in conventionally housed mice relative to mice housed with a running wheel. Voluntary exercise is an environmental stimulus that promotes hippocampal circuit remodeling, primarily via promoting adult neurogenesis in the dentate gyrus. Adult neurogenesis alters structural connectivity patterns, as the integration of adult-generated granule cells (abGCs) is a competitive process where new input-output synaptic connections may co-exist and/or even replace existing synaptic connections2. Comparing the spatial activity of downstream hippocampal CA1 place cells in the same familiar environment over two weeks, we found that the activity of place cells in exercise mice exhibited accelerated representational drift compared to control mice, suggesting that hippocampal circuit remodeling may indeed drive representational drift.

Structural brain network lateralization across childhood and adolescence.

Developmental lateralization of brain function is imperative for behavioral specialization, yet few studies have investigated differences between hemispheres in structural connectivity patterns, especially over the course of development. The present study compares the lateralization of structural connectivity patterns, or topology, across children, adolescents, and young adults. We applied a graph theory approach to quantify key topological metrics in each hemisphere including efficiency of information transfer between regions (global efficiency), clustering of connections between regions (clustering coefficient [CC]), presence of hub-nodes (betweenness centrality [BC]), and connectivity between nodes of high and low complexity (hierarchical complexity [HC]) and investigated changes in these metrics during development. Further, we investigated BC and CC in seven functionally defined networks. Our cross-sectional study consisted of 211 participants between the ages of 6 and 21 years with 93% being right-handed and 51% female. Global efficiency, HC, and CC demonstrated a leftward lateralization, compared to a rightward lateralization of BC. The sensorimotor, default mode, salience, and language networks showed a leftward asymmetry of CC. BC was only lateralized in the salience (right lateralized) and dorsal attention (left lateralized) networks. Only a small number of metrics were associated with age, suggesting that topological organization may stay relatively constant throughout school-age development, despite known underlying changes in white matter properties. Unlike many other imaging biomarkers of brain development, our study suggests topological lateralization is consistent across age, highlighting potential nonlinear mechanisms underlying developmental specialization.

Repeated stress exposure leads to structural synaptic instability prior to disorganization of hippocampal coding and impairments in learning

Stress exposure impairs brain structure and function, resulting in cognitive deficits and increased risk for psychiatric disorders such as depression, schizophrenia, anxiety and post-traumatic stress disorder. In particular, stress exposure affects function and structure of hippocampal CA1 leading to impairments in episodic memory. Here, we applied longitudinal deep-brain optical imaging to investigate the link between changes in activity patterns and structural plasticity of dorsal CA1 pyramidal neurons and hippocampal-dependent learning and memory in mice exposed to stress. We found that several days of repeated stress led to a substantial increase in neuronal activity followed by disruption of the temporal structure of this activity and spatial coding. We then tracked dynamics of structural excitatory connectivity as a potential underlying cause of the changes in activity induced by repeated stress. We thus discovered that exposure to repeated stress leads to an immediate decrease in spinogenesis followed by decrease in spine stability. By comparison, acute stress led to stabilization of the spines born in temporal proximity to the stressful event. Importantly, the temporal relationship between changes in activity levels, structural connectivity and activity patterns, suggests that loss of structural connectivity mediates the transition between increased activity and impairment of temporal organization and spatial information content in dorsal CA1 upon repeated stress exposure.

Oh, What a Tangled Web Epilepsy Genes May Weave.

Aberrant Neuronal Connectivity in the Cortex Drives Generation of Seizures in Rat Absence Epilepsy Studer F, Jarre G, Pouyatos B, et al. Brain 2022;145(6):1978-1991. doi:10.1093/brain/awab438.Absence epilepsy belongs to genetic epilepsies and is characterized by recurrent generalized seizures that are concomitant with alterations of consciousness and associated with cognitive comorbidities. Little is known about the mechanisms leading to occurrence of epileptic seizures (i.e., epileptogenesis) and, in particular, it remains an open question whether neuronal hypersynchronization, a key feature in seizure initiation, could result from aberrant structural connectivity within neuronal networks endowing them with epileptic properties. In the present study, we addressed this question using a genetic model of absence epilepsy in the rat where seizures initiate in the whisker primary somatosensory cortex. We hypothesized that alterations in structural connectivity of neuronal networks within wS1 contribute to pathological neuronal synchronization responsible for seizures. First, we used rabies virus-mediated retrograde synaptic tracing and evidenced that cortical neurons located in both upper- and deep-layers of whisker primary somatosensory cortex displayed aberrant and significantly increased connectivity the genetic model of absence epilepsy, as highlighted by a higher number of presynaptic partners. Next, we showed at the functional level that disrupting these aberrant whisker primary somatosensory cortex neuronal networks with synchrotron X-ray-mediated cortical microtransections drastically decreased both whisker primary somatosensory cortex neuron synchronization and seizure power, as revealed by in vivo local field potential recordings with multichannel probes. Taken together, our data provide for the first time strong evidence that increased structural connectivity patterns of cortical neurons represent critical pathological substrates for increased neuronal synchronization and generation of absence seizures.

Reducing instability of inter-subject covariance of FDG uptake networks using structure-weighted sparse estimation approach.

Sparse inverse covariance estimation (SICE) is increasingly utilized to estimate inter-subject covariance of FDG uptake (FDGcov) as proxy of metabolic brain connectivity. However, this statistical method suffers from the lack of robustness in the connectivity estimation. Patterns of FDGcov were observed to be spatially similar with patterns of structural connectivity as obtained from DTI imaging. Based on this similarity, we propose to regularize the sparse estimation of FDGcov using the structural connectivity. We retrospectively analyzed the FDG-PET and DTI data of 26 healthy controls, 41 patients with Alzheimer's disease (AD), and 30 patients with frontotemporal lobar degeneration (FTLD). Structural connectivity matrix derived from DTI data was introduced as a regularization parameter to assign individual penalties to each potential metabolic connectivity. Leave-one-out cross validation experiments were performed to assess the differential diagnosis ability of structure weighted SICE approach. A few approaches of structure weighted were compared with the standard SICE. Compared to the standard SICE, structural weighting has shown more stable performance in the supervised classification, especially in the differentiation AD vs. FTLD (accuracy of 89-90%, while unweighted SICE only 85%). There was a significant positive relationship between the minimum number of metabolic connection and the robustness of the classification accuracy (r = 0.57, P < 0.001). Shuffling experiments showed significant differences between classification score derived with true structural weighting and those obtained by randomized structure (P < 0.05). The structure-weighted sparse estimation can enhance the robustness of metabolic connectivity, which may consequently improve the differentiation of pathological phenotypes.

Structural connectome-based prediction of trait anxiety.

Neurobiological research on anxiety has shown that trait-anxious individuals may be characterized by weaker structural connectivity of the amygdala-prefrontal circuitry, representing a reduced capacity for efficient communication between the two brain regions. However, comparison of available studies has been inconsistent, possibly related to factors such as aging that influences both trait anxiety and structural connectivity of the brain. To help clarify the nature of brain-anxiety relationship, we applied a connectome-based predictive modeling framework on 148 diffusion-weighted imaging data from the Leipzig Study for Mind-Body Emotion Interactions dataset and identified multivariate patterns of whole-brain structural connectivity that predicted trait anxiety. Results showed that networks predictive of trait anxiety differed across age groups. Specifically, an isolated negative network, which shared overlapping features with the amygdala-prefrontal circuitry, was found in younger adults (20-30 years of age), whereas a widespread positive network highlighted by frontotemporal and frontolimbic connectivity was identified when both younger and older adults (20-80 years of age) were examined. No predictive network was observed when only older adults (30-80 years of age) were considered. Our findings highlight an important age-dependent effect on the structural connectome-based prediction of trait anxiety, supporting ongoing efforts to develop potential neural biomarkers of anxiety.

Shared and Specific Patterns of Structural Brain Connectivity Across Affective and Psychotic Disorders

BackgroundAltered brain structural connectivity has been implicated in the pathophysiology of psychiatric disorders including schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD). However, it is unknown which part of these connectivity abnormalities are disorder specific and which are shared across the spectrum of psychotic and affective disorders. We investigated common and distinct brain connectivity alterations in a large sample (N = 1743) of patients with SZ, BD, or MDD and healthy control (HC) subjects. MethodsThis study examined diffusion-weighted imaging-based structural connectome topology in 720 patients with MDD, 112 patients with BD, 69 patients with SZ, and 842 HC subjects (mean age of all subjects: 35.7 years). Graph theory–based network analysis was used to investigate connectome organization. Machine learning algorithms were trained to classify groups based on their structural connectivity matrices. ResultsGroups differed significantly in the network metrics global efficiency, clustering, present edges, and global connectivity strength with a converging pattern of alterations between diagnoses (e.g., efficiency: HC > MDD > BD > SZ, false discovery rate–corrected p = .028). Subnetwork analysis revealed a common core of edges that were affected across all 3 disorders, but also revealed differences between disorders. Machine learning algorithms could not discriminate between disorders but could discriminate each diagnosis from HC. Furthermore, dysconnectivity patterns were found most pronounced in patients with an early disease onset irrespective of diagnosis. ConclusionsWe found shared and specific signatures of structural white matter dysconnectivity in SZ, BD, and MDD, leading to commonly reduced network efficiency. These results showed a compromised brain communication across a spectrum of major psychiatric disorders.

Brain structural connectivity sub typing in unilateral temporal lobe epilepsy.

To categorize and clinically characterize subtypes of brain structural connectivity patterns in unilateral temporal lobe epilepsy (TLE). Voxel based morphometry (VBM) and surfaced based morphometry (SBM) analysis were used to detect brain structural alterations associated with TLE from MRI data. Principal component analysis (PCA) was performed to identify subtypes of brain structural connectivity patterns. Correlation analysis was used to explore associations between PC scores and clinical characteristics. A total of 59 patients with TLE and 100 healthy adults were included in this study. Widespread cortical atrophy was shown in both left and right TLE (P < 0.05, FWE corrected). Six principal components (PCs) that explained more than 70% of the variance were extracted for left and right TLE, reflecting patterns of brain structural connectivity. PCs representing perisylvian connectivity were positively correlated with verbal IQ (left TLE: r = 0.696, P < 0.001; right TLE: r = 0.484, P = 0.012) and total IQ (left TLE r = 0.608, P < 0.001) and negatively correlated with disease duration (r = -0.448, P = 0.009). In left TLE, the PC in the ipsilateral mesial temporal region was negatively correlated with age at onset (r = -0.382, P = 0.028). In right TLE, the PC representing the default mode network was negatively correlated with number of antiepileptic drugs (r = -0.407, P = 0.039). This study categorized subtypes of unilateral TLE based on brain structural connectivity patterns. Findings may provide insight into seizure pathways, the pathophysiology of epilepsy, including comorbidities such as cognitive impairment, and help predict treatment outcomes.

Differential alterations in brain structural network organization during addiction between adolescents and adults.

The adolescent brain may be susceptible to the influences of illicit drug use. While compensatory network reorganization is a unique developmental characteristic that may restore several brain disorders, its association with methamphetamine (MA) use-induced damage during adolescence is unclear. Using independent component (IC) analysis on structural magnetic resonance imaging data, spatially ICs described as morphometric networks were extracted to examine the effects of MA use on gray matter (GM) volumes and network module connectivity in adolescents (51 MA users v. 60 controls) and adults (54 MA users v. 60 controls). MA use was related to significant GM volume reductions in the default mode, cognitive control, salience, limbic, sensory and visual network modules in adolescents. GM volumes were also reduced in the limbic and visual network modules of the adult MA group as compared to the adult control group. Differential patterns of structural connectivity between the basal ganglia (BG) and network modules were found between the adolescent and adult MA groups. Specifically, adult MA users exhibited significantly reduced connectivity of the BG with the default network modules compared to control adults, while adolescent MA users, despite the greater extent of network GM volume reductions, did not show alterations in network connectivity relative to control adolescents. Our findings suggest the potential of compensatory network reorganization in adolescent brains in response to MA use. The developmental characteristic to compensate for MA-induced brain damage can be considered as an age-specific therapeutic target for adolescent MA users.

White matter abnormalities in the amputation variant of body integrity dysphoria

“Body integrity dysphoria” (BID) is a severe condition affecting nonpsychotic individuals. In the amputation variant of BID, a limb may be experienced as not being part of the body, despite normal anatomical development and intact sensorimotor functions. We previously demonstrated altered brain structural (gray matter) and functional connectivity in 16 men with BID with a long-lasting and exclusive desire for left leg amputation. Here, we aimed to identify, in the same sample, altered patterns of white matter structural connectivity. Fractional anisotropy (FA), derived from diffusion tensor imaging data, was considered as a measure of structural connectivity. Results showed reduced structural connectivity of: (i) the right superior parietal lobule (rSPL) with the right cuneus, with the superior occipital and with the posterior cingulate gyri, (ii) the pars orbitalis of the right middle frontal gyrus (rMFGOrb) with the putamen, and (iii) the left middle temporal gyrus (lMTG) with the pars triangularis of the left inferior frontal gyrus. Increased connectivity was found between the right paracentral lobule (rPLC) and the right caudate nucleus. By using a complementary method of investigation, we confirmed and extended previous results from the same sample of individuals with BID, showing structural alterations between areas tuned to the processing of the sensorimotor representations of the affected leg (rPCL), and to higher-order components of bodily representation such as the body image (rSPL) and visual processing. Alongside this network for bodily awareness, other networks such as the limbic (rMFGOrb) and the mirror (lMTG) systems showed alterations in structural connectivity. These findings consolidate current understanding of the neural correlates of the amputation variant of BID, which might in turn guide diagnostics and rehabilitative treatments.

Subregions of DLPFC Display Graded yet Distinct Structural and Functional Connectivity.

The human dorsolateral prefrontal cortex (DLPFC; approximately corresponding to Brodmann areas 9 and 46) has demonstrable roles in diverse executive functions such as working memory, cognitive flexibility, planning, inhibition, and abstract reasoning. However, it remains unclear whether this is the result of one functionally homogeneous region or whether there are functional subdivisions within the DLPFC. Here, we divided the DLPFC into seven areas along rostral-caudal and dorsal-ventral axes anatomically and explored their respective patterns of structural and functional connectivity. In vivo probabilistic tractography (11 females and 13 males) and resting-state functional magnetic resonance imaging (fMRI; 57 females and 21 males) were employed to map out the patterns of connectivity from each DLPFC subregion. Structural connectivity demonstrated graded intraregional connectivity within the DLPFC. The patterns of structural connectivity between the DLPFC subregions and other cortical areas revealed that the dorsal-rostral subregions connections were restricted to other frontal and limbic areas, whereas the ventral-caudal region was widely connected to frontal, parietal, and limbic cortex. Functional connectivity analyses demonstrated that subregions of DLPFC were strongly interconnected to each other. The dorsal subregions were associated with the default mode network (DMN), while middle dorsal-rostral subregions were linked with the multiple demand network (MDN). The ventral-caudal subregion showed increased functional coupling with both DMN and MDN. Our results suggest that the connectivity of the DLPFC may be subdivided along a dorsorostral-ventrocaudal axis with differing (albeit graded) patterns of connectivity reflecting the integrative executive function of the DLPFC.SIGNIFICANCE STATEMENT Research has shown that the dorsolateral prefrontal cortex (DLPFC) plays a role in various executive functions. By dividing the DLPFC into seven areas along rostral-caudal and dorsal-ventral axes anatomically, we explored their patterns of structural and functional connectivity. The patterns of connectivity within DLPFC subregions demonstrated graded intraregional connectivity. There were distinctive patterns of connectivity with other cortical areas in dorsal-rostral and ventral-caudal DLPFC subregions. Divisions across DLPFC subregions seem to align with their structural and functional connectivity. Our results suggest that DLPFC may be subdivided by the diagonal axis of the dorsal-ventral axis and rostral-caudal axis, supporting the framework of a functional organization along the anterior-posterior axis in the lateral PFC.

Convergent and Divergent Structural Connectivity of Brain White Matter Network Between Patients With Erectile Dysfunction and Premature Ejaculation: A Graph Theory Analysis Study.

BackgroundSexual dysfunction, namely, erectile dysfunction (ED) and premature ejaculation (PE), has been found to be associated with abnormal structural connectivity in the brain. Previous studies have mainly focused on a single disorder, however, convergent and divergent structural connectivity patterns of the brain network between ED and PE remain poorly understood.MethodsT1-weighted structural data and diffusion tensor imaging data of 28 patients with psychological ED, 28 patients with lifelong PE (LPE), and 28 healthy controls (HCs) were obtained to map the white matter (WM) brain networks. Then, the graph-theoretical method was applied to investigate the differences of network properties (small-world measures) of the WM network between patients with ED and LPE. Furthermore, nodal segregative and integrative parameters (nodal clustering coefficient and characteristic path length) were also explored between these patients.ResultsSmall-world architecture of the brain networks were identified for both psychological ED and LPE groups. However, patients with ED exhibited increased average characteristic path length of the brain network when compared with patients with LPE and HCs. No significant difference was found in the average characteristic path length between patients with LPE and HCs. Moreover, increased nodal characteristic path length was found in the right middle frontal gyrus (orbital part) of patients with ED and LPE when compared with HCs. In addition, patients with ED had increased nodal characteristic path length in the right middle frontal gyrus (orbital part) when compared with patients with LPE.ConclusionTogether, our results demonstrated that decreased integration of the right middle frontal gyrus (orbital part) might be a convergent neuropathological basis for both psychological ED and LPE. In addition, patients with ED also exhibited decreased integration in the whole WM brain network, which was not found in patients with LPE. Therefore, altered integration of the whole brain network might be the divergent structural connectivity patterns for psychological ED and LPE.

Aberrant neuronal connectivity in the cortex drives generation of seizures in rat absence epilepsy.

Absence epilepsy belongs to genetic epilepsies and is characterized by recurrent generalized seizures that are concomitant with alterations of consciousness and associated with cognitive comorbidities. Little is known about the mechanisms leading to occurrence of epileptic seizures (i.e. epileptogenesis) and, in particular, it remains an open question as to whether neuronal hypersynchronization, a key feature in seizure initiation, could result from aberrant structural connectivity within neuronal networks endowing them with epileptic properties. In the present study, we addressed this question using a genetic model of absence epilepsy in the rat where seizures initiate in the whisker primary somatosensory cortex (wS1). We hypothesized that alterations in structural connectivity of neuronal networks within wS1 contribute to pathological neuronal synchronization responsible for seizures. First, we used rabies virus-mediated retrograde synaptic tracing and showed that cortical neurons located in both upper- and deep-layers of wS1 displayed aberrant and significantly increased connectivity in the genetic model of absence epilepsy, as highlighted by a higher number of presynaptic partners. Next, we showed at the functional level that disrupting these aberrant wS1 neuronal networks with synchrotron X-ray-mediated cortical microtransections drastically decreased both the synchronization and seizure power of wS1 neurons, as revealed by in vivo local field potential recordings with multichannel probes. Taken together, our data provide for the first time strong evidence that increased structural connectivity patterns of cortical neurons represent critical pathological substrates for increased neuronal synchronization and generation of absence seizures.