Connectivity Profiles Research Articles

A combined DTI-fMRI approach for optimizing the delineation of posteromedial versus anterolateral entorhinal cortex.

In the entorhinal cortex (EC), attempts have been made to identify the human homologue regions of the medial (MEC) and lateral (LEC) subregions using either functional magnetic resonance imaging (fMRI) or diffusion tensor imaging (DTI). However, there are still discrepancies between entorhinal subdivisions depending on the choice of connectivity seed regions and the imaging modality used. While DTI can be used to follow the white matter tracts of the brain, fMRI can identify functionally connected brain regions. In this study, we used both DTI and resting-state fMRI in 103 healthy adults to investigate both structural and functional connectivity between the EC and associated cortical brain regions. Differential connectivity with these regions was then used to predict the locations of the human homologues of MEC and LEC. Our results from combining DTI and fMRI support a subdivision into posteromedial (pmEC) and anterolateral (alEC) EC and reveal a confined border between the pmEC and alEC. Furthermore, the EC subregions obtained by either imaging modality showed similar distinct whole-brain connectivity profiles. Optimizing the delineation of the human homologues of MEC and LEC with a combined, cross-validated DTI-fMRI approach allows to define a likely border between the two subdivisions and has implications for both cognitive and translational neuroscience research.

Harsh parenting, amygdala functional connectivity changes across childhood, and behavioral problems.

Harsh parenting in early childhood is related to offspring's adverse behavioral outcomes. Due to the scarcity of longitudinal neuroimaging data, few studies have explored the neurobiological underpinnings of this association, focusing on within-person variability. This study examined the temporal associations among harsh parenting, later behavioral problems, and the developmental trajectories of amygdala volume and amygdala resting-state functional connectivity (RSFC) profiles, using longitudinal neuroimaging data. The study was embedded in the Growing Up in Singapore Towards healthy Outcomes (GUSTO) cohort. T1-weighted (296 children, 642 scans) and resting-state functional scans (256 children, 509 scans) were collected at ages 4.5, 6, 7.5, and 10.5 years. Amygdala volume and RSFC between the amygdala and six brain regions that have leading roles in emotional regulation were extracted. Harsh parenting at 4.5 years and child behavioral problems at 10.5 years were assessed via parent-report questionnaires. Linear regression and linear mixed models were applied. Harsh parenting was associated with more severe externalizing problems in girls (β = 0.24, 95% CI 0.08-0.40) but not boys (pint = 0.07). In the overall sample, harsh parenting was associated with the developmental trajectories of amygdala-ACC, amygdala-OFC, and amygdala-DLPFC RSFC. In addition, the developmental trajectory of amygdala-ACC RSFC mediated the harsh parenting-externalizing problems association in girls (indirect effect = 0.06, 95% CI 0.01-0.14). Harsh parenting in early childhood was associated with amygdala neurocircuitry development and behavioral problems. The developmental trajectory of amygdala-ACC RSFC is a potential neural mechanism linking harsh parenting and externalizing problems in girls.

Elucidating a statistical learning brain network: Coordinate-based meta-analyses and functional connectivity profiles of artificial grammar learning in healthy adults

Abstract Language rehabilitation centers on modifying its use through experience-based neuroplasticity. Statistical learning of language is essential to its acquisition and likely its rehabilitation following brain injury, but its corresponding brain networks remain elusive. Coordinate-based meta-analyses were conducted to identify common and distinct brain activity across 25 studies coded for meta-data and experimental contrasts (Grammatical and Ungrammatical). The resultant brain regions served as seeds for profiling functional connectivity in large task-independent and task-dependent data sets. Hierarchical clustering of these profiles grouped brain regions into three subnetworks associated with statistical learning processes. Functional decoding clarified the mental operations associated with those subnetworks. Results support a left-dominant language sub-network and two cognitive control networks as scaffolds for language rule identification, maintenance, and application in healthy adults. These data suggest that cognitive control is necessary to track regularities across stimuli and imperative for rule identification and application of grammar. Future empirical investigation of these brain networks in language learning in individuals with brain injury will clarify their prognostic role in language recovery.

Lesion and lesion network localization of dysnomia after epilepsy surgery.

Temporal lobe (TL) epilepsy surgery is an effective treatment option for patients with drug-resistant epilepsy. However, neurosurgery poses a risk for cognitive deficits - up to one third of patients have a decline in naming ability following TL surgery. In this study, we aimed to better understand the neural correlates associated with reduced naming performance after TL surgery, with the goal of informing surgical planning strategies to mitigate the risk of dysnomia. We retrospectively identified 85 patients who underwent temporal lobe (TL) resective surgery (49 left TL, 36 right TL) for whom naming ability was assessed before and >3 months post-surgery using the Boston Naming Test (BNT). We used multivariate lesion-symptom mapping to identify resection sites associated with naming decline, and we used lesion-network mapping to evaluate the broader functional and structural connectivity profiles of resection sites associated with naming decline. We validated our findings in an independent cohort of 59 individuals with left temporal lobectomy, along with repeating all analyses after combining the cohorts. Lesion laterality and location were important predictors of post-surgical naming performance. Naming performance significantly improved after right temporal lobectomy (P = 0.015) while a decrement in performance was observed following left temporal lobectomy (P = 0.002). Declines in naming performance were associated with surgical resection of the left anterior middle temporal gyrus (Brodmann area 21, r =0.41, P = <.001), along with a previously implicated basal temporal language area. Resection sites linked to naming decline showed a functional connectivity profile featuring a left-lateralized network closely resembling the extended semantic \ default mode network, and a structural connectivity profile featuring major temporo-frontal association white matter tracts coursing through the temporal stem. This extends prior work by implicating the left anterior middle temporal gyrus in naming decline and provides additional support for the role of the previously identified basal temporal language area in naming decline. Importantly, the structural and functional connectivity profiles of these regions suggest they are key nodes of a broader extended semantic network. Together these regional and network findings may help in surgical planning and discussions of prognosis.

B-072 Analytical Evaluation of a Novel Fully Automated Multiplexed Microarray Immunoassay for the Simultaneous Detection of Eleven Autoantibodies Associated with Connective Tissue Diseases in a Spanish Reference Laboratory

Abstract Background Detection of different autoantibodies is key in the identification of autoimmune diseases; however, most available devices are either individual tests and/or manual/semi-automated. Development of fully-automated multiplexed devices for autoantibody testing is needed. We evaluated the analytical performance of the novel MosaiQ® AiPlex CTD (AiPlex-CTD) microarray, used with the fully-automated MosaiQ system, for simultaneous qualitative detection of eleven autoantibodies associated with connective tissue diseases (CTD), compared with selected CE-marked devices. Methods AiPlex-CTD microarrays (AliveDx, Switzerland) were prepared by printing antigens onto functionalized glass chips. Microarrays consisting of 2 separate sides (1 side was printed, leaving the other side available for future addition of antigens) were assembled into magazines (containing 250 microarrays) for processing on the MosaiQ 125 instrument. Serum samples from a Spanish refence laboratory, characterized as reactive to ≥1 autoantibodies using Quanta Flash® CTD Screen (Werfen, Spain) or as non-reactive by FIDISTM Connective Profile (Theradiag, France). All samples were tested with AiPlex-CTD. Positive percent agreement (PPA) and negative percent agreement (NPA), overall and for individual analytes were calculated. Results Compared with Quanta Flash® CTD Screen, AiPlex-CTD showed PPA ranging from 80% for Sm to 100% for SS-A 60, TRIM21, U1RNP, Jo-1 and Scl-70. No reactive samples were available for Sm/RNP and Ribosomal P. Compared with FIDIS, NPA ranged from 95% for dsDNA, Scl-70 and CENP-B and 100% for SS-A 60, TRIM21, SS-B, Sm, Sm/RNP, U1RNP, Jo-1 and Ribosomal P. Performance details for individual analytes are shown in the Table. Conclusions In this sample cohort, AiPlex-CTD demonstrated high concordance with the compared CE-marked devices for the automated qualitative detection of the autoantibodies included in the assay, which is line with previous observations in a larger cohort using FIDIS and other CE-marked devices. This high throughput multiplexed platform has the potential to help optimize CTD testing by simplifying complex testing pathways.

B-073 Analytical Performance of a Novel, Fully Automated Multiplexed Microarray Immunoassay Prototype for the Simultaneous Detection of Fifteen Autoantibodies Associated with Connective Tissue Diseases

Abstract Background There is currently a limited offer of automated multi-analyte tests for autoantibody testing in autoimmune connective tissue diseases (CTD). We assessed the analytical performance of a novel, single-use, multiplexed microarray immunoassay prototype (MosaiQ AiPlex CTDplus), used with the fully automated MosaiQ® system, for the simultaneous detection of fifteen autoantibodies associated with CTD, compared with selected CE-marked devices. Methods Banked human serum samples, characterized as reactive to ≥1 autoantibody or non-reactive were included. Reactive samples were characterized with FIDISTM Connective Profile (Theradiag) for CENP B, Jo-1, Ribosomal P, Scl-70, Sm, Sm/RNP, SS-A 60, TRIM21 (SS-A 52), SS-B and U1RNP; EliA CCP (Phadia) for CCP2, QUANTA Lite® Chromatin (Werfen) for Chromatin, QUANTA Flash® DFS70* (Werfen) for DFS70, Anti-dsDNA-IgG-ELISA (DRG) for dsDNA, and Immunodot (Euroimmun) for RNA polymerase III (RNAP III). For CCP2, only reactive samples were included. For the remaining analytes, non-reactive samples were characterized using immunofluorescence (ANA-Ro IgG FLUORESCENT HEp-2000®; Immuno Concepts, Germany) and ANAscreen ELISA (ORGENTEC-Diagnostika-GmbH, Germany). Each individual non-reactive sample was tested with the investigational device once; reactive samples were tested in duplicates. Positive percentage agreement (PPA) and negative percentage agreement (NPA) for individual analytes were calculated. For CCP2 only PPA is presented as no negative samples were included. Results Compared with relevant devices, the investigational prototype showed PPA ranging from 75% for chromatin to 99% for SS-A 60 and TRIM21. NPA ranged from 95% for chromatin, RNAP III, Scl-70 and Sm to 100% for DFS70, SS-A 60 and TRIM21. Performance details are shown in the Table. Conclusions The investigational prototype demonstrated substantial agreement with the compared CE-marked devices. Further studies will allow for expanded performance assessment of the investigational device. This fully-automated multiplexed platform has the potential to contribute to optimizing CTD evaluation by simplifying complex testing pathways and analyzing large number of samples per day.

Human Claustrum Connections: Robust In Vivo Detection by DWI-Based Tractography in Two Large Samples.

Despite substantial neuroscience research in the last decade revealing the claustrum's prominent role in mammalian forebrain organization, as evidenced by its extraordinarily widespread connectivity pattern, claustrum studies in humans are rare. This is particularly true for studies focusing on claustrum connections. Two primary reasons may account for this situation: First, the intricate anatomy of the human claustrum located between the external and extreme capsule hinders straightforward and reliable structural delineation. In addition, the few studies that used diffusion-weighted-imaging (DWI)-based tractography could not clarify whether in vivo tractography consistently and reliably identifies claustrum connections in humans across different subjects, cohorts, imaging methods, and connectivity metrics. To address these issues, we combined a recently developed deep-learning-based claustrum segmentation tool with DWI-based tractography in two large adult cohorts: 81 healthy young adults from the human connectome project and 81 further healthy young participants from the Bavarian longitudinal study. Tracts between the claustrum and 13 cortical and 9 subcortical regions were reconstructed in each subject using probabilistic tractography. Probabilistic group average maps and different connectivity metrics were generated to assess the claustrum's connectivity profile as well as consistency and replicability of tractography. We found, across individuals, cohorts, DWI-protocols, and measures, consistent and replicable cortical and subcortical ipsi- and contralateral claustrum connections. This result demonstrates robust in vivo tractography of claustrum connections in humans, providing a base for further examinations of claustrum connectivity in health and disease.

A shared spatial topography links the functional connectome correlates of cocaine use disorder and dopamine D2/3 receptor densities

The biological mechanisms that contribute to cocaine and other substance use disorders involve an array of cortical and subcortical systems. Prior work on the development and maintenance of substance use has largely focused on cortico-striatal circuits, with relatively less attention on alterations within and across large-scale functional brain networks, and associated aspects of the dopamine system. Here, we characterize patterns of functional connectivity in cocaine use disorder and their spatial association with neurotransmitter receptor densities and transporter bindings assessed through PET. Profiles of functional connectivity in cocaine use disorder reliably linked with spatial densities of dopamine D2/3 receptors across independent datasets. These findings demonstrate that the topography of dopamine receptor densities may underlie patterns of functional connectivity in cocaine use disorder, as assessed through fMRI.

Fingerprints of brain disease: connectome identifiability in Alzheimer’s disease

Functional connectivity patterns in the human brain, like the friction ridges of a fingerprint, can uniquely identify individuals. Does this “brain fingerprint” remain distinct even during Alzheimer’s disease (AD)? Using fMRI data from healthy and pathologically ageing subjects, we find that individual functional connectivity profiles remain unique and highly heterogeneous during mild cognitive impairment and AD. However, the patterns that make individuals identifiable change with disease progression, revealing a reconfiguration of the brain fingerprint. Notably, connectivity shifts towards functional system connections in AD and lower-order cognitive functions in early disease stages. These findings emphasize the importance of focusing on individual variability rather than group differences in AD studies. Individual functional connectomes could be instrumental in creating personalized models of AD progression, predicting disease course, and optimizing treatments, paving the way for personalized medicine in AD management.

Contracted functional connectivity profiles in autism

ObjectiveAutism spectrum disorder (ASD) is a neurodevelopmental condition that is associated with atypical brain network organization, with prior work suggesting differential connectivity alterations with respect to functional connection length. Here, we tested whether functional connectopathy in ASD specifically relates to disruptions in long- relative to short-range functional connections. Our approach combined functional connectomics with geodesic distance mapping, and we studied associations to macroscale networks, microarchitectural patterns, as well as socio-demographic and clinical phenotypes.MethodsWe studied 211 males from three sites of the ABIDE-I dataset comprising 103 participants with an ASD diagnosis (mean ± SD age = 20.8 ± 8.1 years) and 108 neurotypical controls (NT, 19.2 ± 7.2 years). For each participant, we computed cortex-wide connectivity distance (CD) measures by combining geodesic distance mapping with resting-state functional connectivity profiling. We compared CD between ASD and NT participants using surface-based linear models, and studied associations with age, symptom severity, and intelligence scores. We contextualized CD alterations relative to canonical networks and explored spatial associations with functional and microstructural cortical gradients as well as cytoarchitectonic cortical types.ResultsCompared to NT, ASD participants presented with widespread reductions in CD, generally indicating shorter average connection length and thus suggesting reduced long-range connectivity but increased short-range connections. Peak reductions were localized in transmodal systems (i.e., heteromodal and paralimbic regions in the prefrontal, temporal, and parietal and temporo-parieto-occipital cortex), and effect sizes correlated with the sensory-transmodal gradient of brain function. ASD-related CD reductions appeared consistent across inter-individual differences in age and symptom severity, and we observed a positive correlation of CD to IQ scores.LimitationsDespite rigorous harmonization across the three different acquisition sites, heterogeneity in autism poses a potential limitation to the generalizability of our results. Additionally, we focussed male participants, warranting future studies in more balanced cohorts.ConclusionsOur study showed reductions in CD as a relatively stable imaging phenotype of ASD that preferentially impacted paralimbic and heteromodal association systems. CD reductions in ASD corroborate previous reports of ASD-related imbalance between short-range overconnectivity and long-range underconnectivity.

The degenerate coding of psychometric profiles through functional connectivity archetypes.

Degeneracy in the brain-behavior code refers to the brain's ability to utilize different neural configurations to support similar functions, reflecting its adaptability and robustness. This study aims to explore degeneracy by investigating the non-linear associations between psychometric profiles and resting-state functional connectivity (RSFC). The study analyzed RSFC data from 500 subjects to uncover the underlying neural configurations associated with various psychometric outcomes. Self-organized maps (SOM), a type of unsupervised machine learning algorithm, were employed to cluster the RSFC data. And identify distinct archetypal connectivity profiles characterized by unique within- and between-network connectivity patterns. The clustering analysis using SOM revealed several distinct archetypal connectivity profiles within the RSFC data. Each archetype exhibited unique connectivity patterns that correlated with various cognitive, physical, and socioemotional outcomes. Notably, the interaction between different SOM dimensions was significantly associated with specific psychometric profiles. This study underscores the complexity of brain-behavior interactions and the brain's capacity for degeneracy, where different neural configurations can lead to similar behavioral outcomes. These findings highlight the existence of multiple brain architectures capable of producing similar behavioral outcomes, illustrating the concept of neural degeneracy, and advance our understanding of neural degeneracy and its implications for cognitive and emotional health.

Functional Connectivity Profiles of Ten Sub-Regions within the Premotor and Supplementary Motor Areas: Insights into Neurophysiological Integration.

Objectives: This study aimed to comprehensively investigate the functional connectivity of ten sub-regions within the premotor and supplementary motor areas (Right and Left Premotor 6d1, 6d2, 6d3, and Right and Left pre-Supplementary Motor (presma) and SMA). Using advanced magnetic resonance imaging (MRI), the objective was to understand the neurophysiological integrative characteristics of these regions by examining their connectivity with eight distinct functional brain networks. While previous studies have largely treated these areas as homogeneous entities, there is a significant gap in our understanding of the specific roles and connectivity profiles of their distinct sub-regions. The goal was to uncover the roles of these regions beyond conventional motor functions, contributing to a more holistic understanding of brain functioning. Methods: The study involved 198 healthy volunteers, with the primary methodology being functional connectivity analysis using advanced MRI techniques. Ten sub-regions within the premotor and supplementary motor areas served as seed regions, and their connectivity with eight distinct brain regional functional networks, including the Sensorimotor, Dorsal Attention, Language, Frontoparietal, Default Mode, Cerebellar, Visual, and Salience networks, was investigated. This approach allowed for the exploration of synchronized activity between these critical brain areas, shedding light on their integrated functioning and relationships with other brain networks. Results: The study revealed a nuanced landscape of functional connectivity for the premotor and supplementary motor areas with the main functional brain networks. Despite their high functional connectedness within the motor network, these regions displayed diverse functional integrations with other networks. There was moderate connectivity with the Sensorimotor and Dorsal Attention networks, highlighting their roles in motor execution and attentional processes. However, connectivity with the Language, Frontoparietal, Default Mode, Cerebellar, Visual, and Salience networks was generally low, indicating a primary focus on motor-related tasks. Conclusions: This study emphasized the multifaceted roles of the sub-regions of the premotor and supplementary motor areas. Beyond their crucial involvement in motor functions, these regions exhibited varied functional integrations with different brain networks. The observed disparities, especially in the Sensorimotor and Dorsal Attention networks, indicated a nuanced and specialized involvement of these regions in diverse cognitive functions. By delineating the specific connectivity profiles of these sub-regions, this study addresses the existing knowledge gap and suggests unique and distinct roles for each brain area in sophisticated cognitive tasks beyond their conventional motor functions. The results suggested unique and distinct roles for each brain area in sophisticated cognitive tasks beyond their conventional motor functions. This study underscores the importance of considering the broader neurophysiological landscape to comprehend the intricate roles of these brain areas, contributing to ongoing efforts in unravelling the complexities of brain function.

Sex differences in functional cortical organization reflect differences in network topology rather than cortical morphometry

Differences in brain size between the sexes are consistently reported. However, the consequences of this anatomical difference on sex differences in intrinsic brain function remain unclear. In the current study, we investigate whether sex differences in intrinsic cortical functional organization may be associated with differences in cortical morphometry, namely different measures of brain size, microstructure, and the geodesic distance of connectivity profiles. For this, we compute a low dimensional representation of functional cortical organization, the sensory-association axis, and identify widespread sex differences. Contrary to our expectations, sex differences in functional organization do not appear to be systematically associated with differences in total surface area, microstructural organization, or geodesic distance, despite these morphometric properties being per se associated with functional organization and differing between sexes. Instead, functional sex differences in the sensory-association axis are associated with differences in functional connectivity profiles and network topology. Collectively, our findings suggest that sex differences in functional cortical organization extend beyond sex differences in cortical morphometry.

Identifying developmental changes in functional brain connectivity associated with cognitive functioning in children and adolescents with ADHD

Youth diagnosed with Attention-Deficit/Hyperactivity Disorder (ADHD) often show deficits in various measures of higher-level cognition, such as, executive functioning. Poorer cognitive functioning in children with ADHD has been associated with differences in functional connectivity across the brain. However, little is known about the developmental changes to the brain’s functional properties linked to different cognitive abilities in this cohort. To characterize these changes, we analyzed fMRI data (ADHD = 373, NT = 106) collected while youth between the ages of 6 and 16 watched a short movie-clip. We applied machine learning models to identify patterns of network connectivity in response to movie-watching that differentially predict cognitive abilities in our cohort. Using out-of-sample cross validation, our models successfully predicted IQ, visual spatial, verbal comprehension, and fluid reasoning in children (ages 6 – 11), but not in adolescents with ADHD (ages 12–16). Connections with the default mode, memory retrieval, and dorsal attention were driving prediction during early and middle childhood, but connections with the somatomotor, cingulo-opercular, and frontoparietal networks were more important in middle childhood. This work demonstrated that machine learning approaches can identify distinct functional connectivity profiles associated with cognitive abilities at different developmental stages in children and adolescents with ADHD.

Cerebro-spinal somatotopic organization uncovered through functional connectivity mapping

Abstract Somatotopy, the topographical arrangement of sensorimotor pathways corresponding to distinct body parts, is a fundamental feature of the human central nervous system (CNS). Traditionally, investigations into brain and spinal cord somatotopy have been conducted independently, primarily utilizing body stimulations or movements. To date, however, no study has probed the somatotopic arrangement of cerebro-spinal functional connections in vivo in humans. In this study, we used simultaneous brain and cervical spinal cord functional magnetic resonance imaging (fMRI) to demonstrate how the coordinated activities of these two CNS levels at rest can reveal their shared somatotopy. Using functional connectivity analyses, we mapped preferential correlation patterns between each spinal cord segment and distinct brain regions, revealing a somatotopic gradient within the cortical sensorimotor network. We then validated this large-scale somatotopic organization through a complementary data-driven analysis, where we effectively identified spinal cord segments through the connectivity profiles of their voxels with the sensorimotor cortex. These findings underscore the potential of resting-state cerebro-spinal cord fMRI to probe the large-scale organization of the human sensorimotor system with minimal experimental burden, holding promise for gaining a more comprehensive understanding of normal and impaired somatosensory-motor functions.

Language and the Cerebellum: Structural Connectivity to the Eloquent Brain.

Neurobiological models of receptive language have focused on the left-hemisphere perisylvian cortex with the assumption that the cerebellum supports peri-linguistic cognitive processes such as verbal working memory. The goal of this study was to identify language-sensitive regions of the cerebellum then map the structural connectivity profile of these regions. Functional imaging data and diffusion-weighted imaging data from the Human Connectome Project (HCP) were analyzed. We found that (a) working memory, motor activity, and language comprehension activated partially overlapping but mostly unique subregions of the cerebellum; (b) the linguistic portion of the cerebello-thalamo-cortical circuit was more extensive than the linguistic portion of the cortico-ponto-cerebellar tract; (c) there was a frontal-lobe bias in the connectivity from the cerebellum to the cerebrum; (d) there was some degree of specificity; and (e) for some cerebellar tracts, individual differences in picture identification ability covaried with fractional anisotropy metrics. These findings yield insights into the structural connectivity of the cerebellum as relates to the uniquely human process of language comprehension.

Upper bounds for integrated information.

Originally developed as a theory of consciousness, integrated information theory provides a mathematical framework to quantify the causal irreducibility of systems and subsets of units in the system. Specifically, mechanism integrated information quantifies how much of the causal powers of a subset of units in a state, also referred to as a mechanism, cannot be accounted for by its parts. If the causal powers of the mechanism can be fully explained by its parts, it is reducible and its integrated information is zero. Here, we study the upper bound of this measure and how it is achieved. We study mechanisms in isolation, groups of mechanisms, and groups of causal relations among mechanisms. We put forward new theoretical results that show mechanisms that share parts with each other cannot all achieve their maximum. We also introduce techniques to design systems that can maximize the integrated information of a subset of their mechanisms or relations. Our results can potentially be used to exploit the symmetries and constraints to reduce the computations significantly and to compare different connectivity profiles in terms of their maximal achievable integrated information.

Abnormal resting-state functional connectivity in subregions of amygdala in adults and adolescents with major depressive disorder

BackgroundThe different symptoms of major depressive disorder (MDD) in adolescents compared to adults suggested there may be differences in the pathophysiology between adolescents and adults with MDD. However, despite the amygdala being considered critical in the pathophysiology, there was limited knowledge about the commonalities and differences in the resting-state functional connectivity (rsFC) of amygdala subregions in MDD patients of different age groups.MethodsIn the current study, 65 adolescents (46 with MDD and 19 controls) and 91 adults (35 with MDD and 56 controls) were included. A seed-based functional connectivity analysis was performed for each of the amygdala subregions. A 2 × 2 ANOVA was used to analyze the main effect of age, diagnosis, and their interaction on the rsFC of each subregion.ResultsA significant main effect of age was revealed in the rsFC of bilateral centromedial (CM) subregions and right laterobasal (LB) subregion with several brain regions in the limbic system and frontoparietal network. The significant main effect of diagnosis showed MDD patients of different ages showed higher connectivity than controls between the right LB and left middle frontal gyrus (MFG).ConclusionsThe rsFC of specific amygdala subregions with brain regions in the limbic system and frontoparietal network is affected by age, indicating a distinct amygdala connectivity profile in adolescents. The decreased rsFC between the right LB and the left MFG in adolescents and adults with MDD could serve as a diagnostic biomarker and a target of nonpharmacological treatment for MDD.

White matter connections of human ventral temporal cortex are organized by cytoarchitecture, eccentricity, and category-selectivity from birth.

Category-selective regions in ventral temporal cortex (VTC) have a consistent anatomical organization, which is hypothesized to be scaffolded by white matter connections. However, it is unknown how white matter connections are organized from birth. Here, we scanned newborn to 6-month-old infants and adults and used a data-driven approach to determine the organization of the white matter connections of VTC. We find that white matter connections are organized by cytoarchitecture, eccentricity, and category from birth. Connectivity profiles of functional regions in the same cytoarchitectonic area are similar from birth and develop in parallel, with decreases in endpoint connectivity to lateral occipital, and parietal, and somatosensory cortex, and increases to lateral prefrontal cortex. Additionally, connections between VTC and early visual cortex are organized topographically by eccentricity bands and predict eccentricity biases in VTC. These data have important implications for theories of cortical functional development and open new possibilities for understanding typical and atypical white matter development.

Electrophysiological functional connectivity and complexity reflecting cognitive processing speed heterogeneity in young children with ADHD

Early intervention is imperative for young children with attention-deficit/hyperactivity disorder (ADHD) who manifest heterogeneous neurocognitive deficits. The study investigated the functional connectivity and complexity of brain activity among young children with ADHD exhibiting a fast cognitive processing speed (ADHD-F, n = 26), with ADHD exhibiting a slow cognitive processing speed (ADHD-S, n = 17), and typically developing children (n = 35) using wireless electroencephalography (EEG) during rest and task conditions. During rest, compared with the typically developing group, the ADHD-F group displayed lower long-range intra-hemispheric connectivity, while the ADHD-S group had lower frontal beta inter-hemispheric connectivity. During task performance, the ADHD-S group displayed lower frontal beta inter-hemispheric connectivity than the typically developing group. The ADHD-S group had lower frontal inter-hemispheric connectivity in broader frequency bands than the ADHD-F group, indicating ADHD heterogeneity in mental processing speed. Regarding complexity, the ADHD-S group tended to show lower frontal entropy estimators than the typically developing group during the task condition. These findings suggest that the EEG profile of brain connectivity and complexity can aid the early clinical diagnosis of ADHD, support subgrouping young children with ADHD based on cognitive processing speed heterogeneity, and may contain specific novel neural biomarkers for early intervention planning.