Subregions Of Corpus Callosum Research Articles

Obesity is associated with alterations in anatomical connectivity of frontal-corpus callosum.

Obesity has been linked to abnormal frontal function, including the white matter fibers of anterior portion of the corpus callosum, which is crucial for information exchange within frontal cortex. However, alterations in white matter anatomical connectivity between corpus callosum and cortical regions in patients with obesity have not yet been investigated. Thus, we enrolled 72 obese and 60 age-/gender-matched normal weight participants who underwent clinical measurements and diffusion tensor imaging. Probabilistic tractography with connectivity-based classification was performed to segment the corpus callosum and quantify white matter anatomical connectivity between subregions of corpus callosum and cortical regions, and associations between corpus callosum-cortex white matter anatomical connectivity and clinical behaviors were also assessed. Relative to normal weight individuals, individuals with obesity exhibited significantly greater white matter anatomical connectivity of corpus callosum-orbitofrontal cortex, which was positively correlated with body mass index and self-reported disinhibition of eating behavior, and lower white matter anatomical connectivity of corpus callosum-prefrontal cortex, which was significantly negatively correlated with craving for high-calorie food cues. The findings show that alterations in white matter anatomical connectivity between corpus callosum and frontal regions involved in reward and executive control are associated with abnormal eating behaviors.

Corpus Callosum Atrophy in Alcohol-Dependent Men with Memory Disorders and Visual Attention Difficulties.

The earlier research confirm the relationship between structural changes in the corpus callosum and difficulties in attention and memory in the group of patients with alcohol use disorder (AUD). Nevertheless, the image of auditory and visual memory disorders in men with gradual atrophy of the corpus callosum and different alcohol abuse duration, it has not been explained yet. The overriding objective of this study was: (1) to determine whether there are principal and interaction effects of visuospatial and auditory-verbal memory on alcohol consumption and cross-sectional corpus callosum area in men with alcohol use disorder, (2) to assess the impact of callosal changes on the memory and visual attention processes. 97 men with alcohol use disorder were examined. T1-weighted scans were used to carry out corpus callosum segmentation and volumetric measurements. The cognition profile included two domains: attention, memory (visuospatial and auditory-verbal). The results showed that participants with visuospatial memory disorder had inferior education background, and were characterized by a longer duration of alcohol abuse, more severe alcohol use disorder, and greater alcohol consumption per day. Second, alcohol-dependent men with auditory and visual memory disorders had a smaller frontal and posterior part of the corpus callosum areas. Additionally, among the alcohol-dependent men with memory disorders the smaller rostral body of corpus callosum was determined by the longer alcohol abuse duration. On the other hand, the smaller rostral body of corpus callosum was predicted by the older age only in alcohol-dependent men with normal memory. Among all examined individuals were observed a statistically significant relationships among visual attention, visuospatial memory and corpus callosum subregions including in particular genu and isthmus. The smaller corpus callosum cross-sectional area significantly affects visual attention and memory difficulties in alcohol use disorder, especially have differentiated the patients with normal and disordered memory. Longer alcohol abuse duration plays also a significant role in the corpus callosum atrophy in alcohol-dependent men with disordered memory (visuospatial in particular).

Distributed genetic effects of the corpus callosum subregions suggest links to neuropsychiatric disorders and related traits.

The corpus callosum (CC) is a brain structure with a high heritability and potential role in psychiatric disorders. However, the genetic architecture of the CC and the genetic link with psychiatric disorders remain largely unclear. We investigated the genetic architectures of the volume of the CC and its subregions and the genetic overlap with psychiatric disorders. We applied multivariate genome-wide association study (GWAS) to genetic and T1-weighted magnetic resonance imaging (MRI) data of 40,894 individuals from the UK Biobank, aiming to boost genetic discovery and to assess the pleiotropic effects across volumes of the five subregions of the CC (posterior, mid-posterior, central, mid-anterior and anterior) obtained by FreeSurfer 7.1. Multivariate GWAS was run combining all subregions, co-varying for relevant variables. Gene-set enrichment analyses were performed using MAGMA. Linkage disequilibrium score regression (LDSC) was used to determine Single nucleotide polymorphism (SNP)-based heritability of total CC volume and volumes of its subregions as well as their genetic correlations with relevant psychiatric traits. We identified 70 independent loci with distributed effects across the five subregions of the CC (p < 5 × 10-8). Additionally, we identified 33 significant loci in the anterior subregion, 23 in the mid-anterior, 29 in the central, 7 in the mid-posterior and 56 in the posterior subregion. Gene-set analysis revealed 156 significant genes contributing to volume of the CC subregions (p < 2.6 × 10-6). LDSC estimated the heritability of CC to (h2SNP = 0.38, SE = 0.03) and subregions ranging from 0.22 (SE = 0.02) to 0.37 (SE = 0.03). We found significant genetic correlations of total CC volume with bipolar disorder (BD, rg = -0.09, SE = 0.03; p = 5.9 × 10-3) and drinks consumed per week (rg = -0.09, SE = 0.02; p = 4.8 × 10-4), and volume of the mid-anterior subregion with BD (rg = -0.12, SE = 0.02; p = 2.5 × 10-4), major depressive disorder (MDD) (rg = -0.12, SE = 0.04; p = 3.6 × 10-3), drinks consumed per week (rg = -0.13, SE = 0.04; p = 1.8 × 10-3) and cannabis use (rg = -0.09, SE = 0.03; p = 8.4 × 10-3). Our results demonstrate that the CC has a polygenic architecture implicating multiple genes and show that CC subregion volumes are heritable. We found that distinct genetic factors are involved in the development of anterior and posterior subregions, consistent with their divergent functional specialisation. Significant genetic correlation between volumes of the CC and BD, drinks per week, MDD and cannabis consumption subregion volumes with psychiatric traits is noteworthy and deserving of further investigation.

Linked patterns of interhemispheric functional connectivity and microstructural characteristics of the corpus callosum in antipsychotic-naive first-episode schizophrenia.

Many magnetic resonance imaging (MRI) studies have showed significant structural abnormalities of the corpus callosum (CC) and dysregulated interhemispheric functional connectivity (FC) in schizophrenia. Although the hemispheres are mainly linked through CC, few studies directly examined the relationship between aberrant interhemispheric FC and the white matter deficits of the CC in schizophrenia. One hundred and sixty-nine antipsychotic-naive first-episode schizophrenia patients (AN-FES) and 214 healthy controls (HCs) were recruited. Diffusional and functional MRI data were obtained for each participant, and fractional anisotropy (FA) values of the five CC subregions and interhemispheric FC for each participant were acquired. Between-group differences in these metrics were compared using multivariate analysis of covariance (MANCOVA). Moreover, sparse canonical correlation analysis (sCCA) was conducted to explore correlations of fibers integrity of the CC subregions with dysregulated interhemispheric FC in patients. Compared with HCs, the patients with schizophrenia showed significantly reduced FA values of the CC subregions and dysregulated connectivity between two cerebral hemispheres. The canonical correlation coefficients identified five significant sCCA modes between FA and FC (r>0.75, p<0.001), suggesting strong relationships between FA values of the CC subregions and interhemispheric FC in patients. Our findings support a key role of CC in maintaining ongoing functional communication between two cerebral hemispheres, and suggest that microstructural changes of white matter fibers crossing different CC subregions may affect special interhemispheric FC in schizophrenia.

Prediction of subjective cognitive decline after corpus callosum infarction by an interpretable machine learning-derived early warning strategy.

Corpus callosum (CC) infarction is an extremely rare subtype of cerebral ischemic stroke, however, the symptoms of cognitive impairment often fail to attract early attention of patients, which seriously affects the long-term prognosis, such as high mortality, personality changes, mood disorders, psychotic reactions, financial burden and so on. This study seeks to develop and validate models for early predicting the risk of subjective cognitive decline (SCD) after CC infarction by machine learning (ML) algorithms. This is a prospective study that enrolled 213 (only 3.7%) CC infarction patients from a nine-year cohort comprising 8,555 patients with acute ischemic stroke. Telephone follow-up surveys were carried out for the patients with definite diagnosis of CC infarction one-year after disease onset, and SCD was identified by Behavioral Risk Factor Surveillance System (BRFSS) questionnaire. Based on the significant features selected by the least absolute shrinkage and selection operator (LASSO), seven ML models including Extreme Gradient Boosting (XGBoost), Logistic Regression (LR), Light Gradient Boosting Machine (LightGBM), Adaptive Boosting (AdaBoost), Gaussian Naïve Bayes (GNB), Complement Naïve Bayes (CNB), and Support vector machine (SVM) were established and their predictive performances were compared by different metrics. Importantly, the SHapley Additive exPlanations (SHAP) was also utilized to examine internal behavior of the highest-performance ML classifier. The Logistic Regression (LR)-model performed better than other six ML-models in SCD predictability after the CC infarction, with the area under the receiver characteristic operator curve (AUC) of 77.1% in the validation set. Using LASSO and SHAP analysis, we found that infarction subregions of CC infarction, female, 3-month modified Rankin Scale (mRS) score, age, homocysteine, location of angiostenosis, neutrophil to lymphocyte ratio, pure CC infarction, and number of angiostenosis were the top-nine significant predictors in the order of importance for the output of LR-model. Meanwhile, we identified that infarction subregion of CC, female, 3-month mRS score and pure CC infarction were the factors which independently associated with the cognitive outcome. Our study firstly demonstrated that the LR-model with 9 common variables has the best-performance to predict the risk of post-stroke SCD due to CC infarcton. Particularly, the combination of LR-model and SHAP-explainer could aid in achieving personalized risk prediction and be served as a decision-making tool for early intervention since its poor long-term outcome.

The genetic architecture of the corpus callosum and its genetic overlap with common neuropsychiatric diseases

BackgroundThe corpus callosum (CC) is the main structure transferring information between the cerebral hemispheres. Although previous large-scale genome-wide association study (GWAS) has illustrated the genetic architecture of white matter integrity of CC, CC volume is less stressed. MethodsUsing MRI data from 33,861 individuals in UK Biobank, we conducted univariate and multivariate GWAS for CC fractional anisotropy (FA) and volume with PLINK 2.0 and MOSTest. All discovered SNPs in the multivariate framework were functionally annotated in FUMA v1.3.8. In the meanwhile, a series of gene property analyses was conducted simultaneously. In addition, we estimated genetic relationship between CC metrics and other neuropsychiatric traits and diseases. ResultsWe identified a total of 36 and 82 significant genomic loci for CC FA and volume (P < 5 × 10−8). And 53 and 27 genes were respectively mapped by four mapping strategies. For CC volume, gene-set analysis revealed pathways mainly relating to cell migration; cell-type analysis found the top enrichment in neuroglia while for CC FA in GABAergic neurons. Furthermore, we found a lot of genetic overlap and shared loci between CC FA and volume and common neuropsychiatric diseases. DiscussionCollectively, this study helps to better understand the genetic architecture of whole CC and CC subregions. However, the way to divide CC FA and volume in our study restricts the interpretations of our results. Future work will be needed to pay attention to the genetic structure of white matter volume, and an appropriate division of CC may help to better understand CC structure.

Brain Connectivity: A Journal of Clinical Neurology, Neuroscience, &amp; Neuroimaging Advancing the Field of Neurology

Brain Connectivity: A Journal of Clinical Neurology, Neuroscience, &amp; Neuroimaging Advancing the Field of Neurology

Upper-Limb Amputation Disrupts the Interhemispheric Structural Rather than Functional Connectivity.

Background: Recent neuroimaging studies on upper-limb amputation have revealed the reorganization of bilateral sensorimotor cortex after sensory deprivation, underpinning the assumption of changes in the interhemispheric connections. In the present study, using functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), we aim to explore the alterations in the interhemispheric functional and structural connectivity after upper-limb amputation. Methods: Twenty-two upper-limb amputees and 15 age- and sex-matched healthy controls were recruited for MRI scanning. The amputees were further divided into subgroups by amputation side and residual limb pain (RLP). DTI metrics of corpus callosum (CC) subregions and resting-state functional connectivity (FC) between the bilateral sensorimotor cortices were measured for each participant. Linear mixed models were carried out to investigate the relationship of interhemispheric connectivity with the amputation, amputation side, and RLP. Results: Compared with healthy controls, upper-limb amputees showed lower axial diffusivity (AD) in CC subregions II and III. Subgroup analyses showed that the dominant hand amputation induced significant microstructural changes in CC subregion III. In addition, only amputees with RLP showed decreased fractional anisotropy and AD in CC, which was also correlated with the intensity of RLP. No significant changes in interhemispheric FC were found after upper-limb amputation. Conclusion: The present study demonstrated that the interhemispheric structural connectivity rather than FC degenerated after upper-limb amputation, and the degeneration of interhemispheric structural connectivity was shown to be relevant to the amputation side and the intensity of RLP. Impact statement Neuroimaging studies have revealed the functional reorganization of bilateral sensorimotor cortex after amputation, with expanded activation from the intact hemisphere to the deprived hemisphere. Our findings indicated a degeneration of interhemispheric white matter connections in upper-limb amputees, unveiling the underlying structural basis for bilateral functional reorganization after amputation.

Structural Brain Network Reorganization Following Anterior Callosotomy for Colloid Cysts: Connectometry and Graph Analysis Results.

Introduction:The plasticity of the neural circuits after injuries has been extensively investigated over the last decades. Transcallosal microsurgery for lesions affecting the third ventricle offers an interesting opportunity to investigate the whole-brain white matter reorganization occurring after a selective resection of the genu of the corpus callosum (CC).MethodDiffusion MRI (dMRI) data and neuropsychological testing were collected pre- and postoperatively in six patients with colloid cysts, surgically treated with a transcallosal-transgenual approach. Longitudinal connectometry analysis on dMRI data and graph analysis on structural connectivity matrix were implemented to analyze how white matter pathways and structural network topology reorganize after surgery.ResultsAlthough a significant worsening in cognitive functions (e.g., executive and memory functioning) at early postoperative, a recovery to the preoperative status was observed at 6 months. Connectometry analysis, beyond the decrease of quantitative anisotropy (QA) near the resection cavity, showed an increase of QA in the body and forceps major CC subregions, as well as in the left intra-hemispheric corticocortical associative fibers. Accordingly, a reorganization of structural network topology was observed between centrality increasing in the left hemisphere nodes together with a rise in connectivity strength among mid and posterior CC subregions and cortical nodes.ConclusionA structural reorganization of intra- and inter-hemispheric connective fibers and structural network topology were observed following the resection of the genu of the CC. Beyond the postoperative transient cognitive impairment, it could be argued anterior CC resection does not preclude neural plasticity and may subserve the long-term postoperative cognitive recovery.

Impact of Infant Thoracic Non-cardiac Perioperative Critical Care on Homotopic-Like Corpus Callosum and Forebrain Sub-regional Volumes.

Previously, we reported quantitatively smaller total corpus callosum (CC) and total forebrain size in critically ill term-born and premature patients following complex perioperative critical care for long-gap esophageal atresia (LGEA) that included Foker process repair. We extended our cross-sectional pilot study to determine sub-regional volumes of CC and forebrain using structural brain MRI. Our objective was to evaluate region-specific CC as an in-vivo marker for decreased myelination and/or cortical neural loss of homotopic-like sub-regions of the forebrain. Term-born (n = 13) and premature (n = 13) patients, and healthy naïve controls (n = 21) <1-year corrected age underwent non-sedated MRI using a 3T Siemens scanner, as per IRB approval at Boston Children's Hospital following completion of clinical treatment for Foker process. We used ITK-SNAP (v.3.6) to manually segment six sub-regions of CC and eight sub-regions of forebrain as per previously reported methodology. Group differences were assessed using a general linear model univariate analysis with corrected age at scan as a covariate. Our analysis implicates globally smaller CC and forebrain with sub-region II (viz. rostral body of CC known to connect to pre-motor cortex) to be least affected in comparison to other CC sub-regions in LGEA patients. Our report of smaller subgenual forebrain implicates (mal)adaptation in limbic circuits development in selected group of infant patients following LGEA repair. Future studies should include diffusion tractography studies of CC in further evaluation of what appears to represent global decrease in homotopic-like CC/forebrain size following complex perioperative critical care of infants born with LGEA.

Measuring Sex Differences in the Corpus Callosum by Undergraduates at a Small and a Large Institution

Neuroscience students often seem more responsive to laboratory exercises that involve human brains. Here we describe a lab that utilizes human brain MRIs to evaluate a long-standing debate over the presence of sex differences in the human brain, specifically the corpus callosum. Students at both Widener and UCLA measured corpus callosum subregions that were already marked-off as described by Witelson (1989) or by Hofer and Frahm (2006). Statistical analyses revealed sex differences using both schemes after correcting for the size of the midsagittal cortex. Widener students, however, uncovered more sex differences than the UCLA students. Lab instruction for UCLA students occurred during the COVID-19 pandemic. So, lab sessions were completely online. In contrast, Widener students had the benefit of in-person lab instruction. Nonetheless, both the data obtained from the images of the corpus callosi as well as measures of pedagogical efficacy were similar between the two institutions, suggesting that distance learning may be a valuable and viable option. Further, when in person learning is not an option, such as during a pandemic, digital databases serve as invaluable resources for online learning. When these databases are utilized in a hypothesis driven research setting, they can serve as the basis for course-based undergraduate research experiences (CUREs), which are known to benefit students—improving retention in science fields.

Connectivity-Based Topographical Changes of the Corpus Callosum During Aging.

Background: The corpus callosum (CC) is the most prominent white matter connection for interhemispheric information transfer. It is implicated in a variety of cognitive functions, which tend to decline with age. The region-specific projections of the fiber bundles with microstructural heterogeneity of the CC are associated with cognitive functions and diseases. However, how the CC is associated with the information transfer within functional networks and the connectivity changes during aging remain unclear. Studying the CC topography helps to understand the functional specialization and age-related changes of CC subregions.Methods: Diffusion tractography was used to subdivide the CC into seven subregions from 1,086 healthy volunteers within a wide age range (21–90 years), based on the connections to the cortical parcellations of the functional networks. Quantitative diffusion indices and connection probability were calculated to study the microstructure differences and age-related changes in the CC subregions.Results: According to the population-based probabilistic topography of the CC, part of the default mode network (DMN) and limbic network (LN) projected fibers through the genu and rostrum; the frontoparietal network (FPN), ventral attention network (VA) and somatomotor networks (SM) were interconnected by the CC body; callosal fibers arising from the part of the default mode network (DMN), dorsal attention network (DA) and visual network (VIS) passed through the splenium. Anterior CC subregions interconnecting DMN, LN, FPN, VA, and SM showed lower fractional anisotropy (FA) and higher mean diffusivity (MD) and radial diffusivity (RD) than posterior CC subregions interconnecting DA and VIS. All the CC subregions showed slightly increasing FA and decreasing MD, RD, and axial diffusivity (AD) at younger ages and opposite trends at older ages. Besides, the anterior CC subregions exhibited larger microstructural and connectivity changes compared with the posterior CC subregions during aging.Conclusion: This study revealed the callosal subregions related to functional networks and uncovered an overall “anterior-to-posterior” region-specific changing trend during aging, which provides a baseline to identify the presence and timing of callosal connection states.

An interpretable multiparametric radiomics model for the diagnosis of schizophrenia using magnetic resonance imaging of the corpus callosum

There is a growing need to develop novel strategies for the diagnosis of schizophrenia using neuroimaging biomarkers. We investigated the robustness of the diagnostic model for schizophrenia using radiomic features from T1-weighted and diffusion tensor images of the corpus callosum (CC). A total of 165 participants [86 schizophrenia and 79 healthy controls (HCs)] were allocated to training (N = 115) and test (N = 50) sets. Radiomic features of the CC subregions were extracted from T1-weighted, apparent diffusion coefficient (ADC), and fractional anisotropy (FA) images (N = 1605). Following feature selection, various combinations of classifiers were trained, and Bayesian optimization was adopted in the best performing classifier. Discrimination, calibration, and clinical utility of the model were assessed. An online calculator was constructed to offer the probability of having schizophrenia. SHapley Additive exPlanations (SHAP) was applied to explore the interpretability of the model. We identified 30 radiomic features to differentiate participants with schizophrenia from HCs. The Bayesian optimized model achieved the highest performance, with an area under the curve (AUC), accuracy, sensitivity, and specificity of 0.89 (95% confidence interval: 0.81–0.98), 80.0, 83.3, and 76.9%, respectively, in the test set. The final model offers clinical probability in an online calculator. The model explanation by SHAP suggested that second-order features from the posterior CC were highly associated with the risk of schizophrenia. The multiparametric radiomics model focusing on the CC shows its robustness for the diagnosis of schizophrenia. Radiomic features could be a potential source of biomarkers that support the biomarker-based diagnosis of schizophrenia and improve the understanding of its neurobiology.

Susceptibility of subregions of prefrontal cortex and corpus callosum to damage by high-dose oxytocin-induced labor in male neonatal mice.

Induction and augmentation of labor is one of the most common obstetrical interventions. However, this intervention is not free of risks and could cause adverse events, such as hyperactive uterine contraction, uterine rupture, and amniotic-fluid embolism. Our previous study using a new animal model showed that labor induced with high-dose oxytocin (OXT) in pregnant mice resulted in massive cell death in selective brain regions, specifically in male offspring. The affected brain regions included the prefrontal cortex (PFC), but a detailed study in the PFC subregions has not been performed. In this study, we induced labor in mice using high-dose OXT and investigated neonatal brain damage in detail in the PFC using light and electron microscopy. We found that TUNEL-positive or pyknotic nuclei and Iba-1-positive microglial cells were detected more abundantly in infralimbic (IL) and prelimbic (PL) cortex of the ventromedial PFC (vmPFC) in male pups delivered by OXT-induced labor than in the control male pups. These Iba-1-positive microglial cells were engulfing dying cells. Additionally, we also noticed that in the forceps minor (FMI) of the corpus callosum (CC), the number of TUNEL-positive or pyknotic nuclei and Iba-1-positive microglial cells were largely increased and Iba-1-positive microglial cells phagocytosed massive dying cells in male pups delivered by high-dose OXT-induced labor. In conclusion, IL and PL of the vmPFC and FMI of the CC, were susceptible to brain damage in male neonates after high-dose OXT-induced labor.

Relationship between illness duration, corpus callosum changes, and sustained attention dysfunction in major depressive disorder.

Illness duration is the main index of cumulative illness severity during depression progression. Corpus callosum (CC) damage is among the most replicated neurobiological findings in major depressive disorder (MDD). We aimed to investigate the nature and extent of the association between illness duration and CC changes. Ninety-six MDD patients and 50 controls underwent diffusion and resting-state functional magnetic resonance imaging (fMRI). White matter micro-structure and inter-hemispheric functional connectivity were quantified by fractional anisotropy (FA) and voxel-mirrored homotopic connectivity (VMHC). The CC was reconstructed by tractography and divided into five sub-regions. The associations of illness duration with FA of each CC sub-region and voxel-wise VMHC were examined using correlation analyses. Also, we investigated the potential relationship between illness duration, CC changes, and clinical variables using mediation analyses. In MDD patients, longer illness duration was selectively associated with lower FA of CC sub-regions 2 [partial correlation coefficient (pr) =-0.269, P=0.009] and 5 (pr=-0.296, P=0.004) as well as higher VMHC in the supplementary motor areas (pr=0.378, P<0.001), precuneus (pr=0.384, P<0.001), and lingual gyrus (pr=0.373, P<0.001) connected by the affected CC sub-regions. Further subgroup analyses demonstrated pronounced FA decrease and VMHC increase in patients with illness duration over 20 years relative to healthy controls (HC) and other patient subgroups with shorter illness durations. Moreover, lower FA of CC sub-regions 2 and 5 mediated the association between longer illness duration and more severe sustained attention dysfunction. These findings provide evidence for compromised structure yet compensatory function of the CC with increasing depression illness duration, which may inform effective antidepressant treatment strategies at different disease stages.

A Deformation-Based Shape Study of the Corpus Callosum in First Episode Schizophrenia.

Background: Previous first-episode schizophrenia (FES) studies have reported abnormalities in the volume and mid-sagittal size of the corpus callosum (CC), but findings have been inconsistent. Besides, the CC shape has rarely been analyzed in FES. Therefore, in this study, we investigated FES-related CC shape abnormalities using 198 participants [92 FES patients and 106 healthy controls (HCs)].Methods: We conducted statistical shape analysis of the mid-sagittal CC curve in a large deformation diffeomorphic metric mapping framework. The CC was divided into the genu, body, and splenium (gCC, bCC, and sCC) to target the key CC sub-regions affected by the FES pathology. Gender effects have been investigated.Results: There were significant area differences between FES and HC in the entire CC and gCC but not in bCC nor sCC. In terms of the localized shape morphometrics, significant region-specific shape inward-deformations were detected in the superior portion of gCC and the anterosuperior portion of bCC in FES. These global area and local shape morphometric abnormalities were restricted to female FES but not male FES.Conclusions: gCC was significantly affected in the neuropathology of FES and this finding was specific to female FES. This study suggests that gCC may be a key sub-region that is vulnerable to the neuropathology of FES, specifically in female patients. The morphometrics of gCC may serve as novel and efficient biomarkers for screening female FES patients.

Corpus callosum size and homotopic connectivity in Autism spectrum disorder

By examining how morphology of the corpus callosum (CC) in autism spectrum disorder (ASD) may affect functional communication across hemispheres, we hope to provide new insights into the structure-function relationship in the brain. We used a sample of 94 participants from the Autism Brain Imaging Data Exchange (ABIDE) database (55 typically-developing (TD) and 39 with ASD). The CC was segmented into five sub-regions (anterior, mid-anterior, central, mid-posterior, posterior) using FreeSurfer software, which were further examined for group differences. The total volume and specific sub-region volumes of the CC, and interhemispheric (homotopic) functional connectivity were calculated, along with the relationship between volume and connectivity. These measures were correlated with social ability assessed by the Social Responsiveness Scale (SRS). The central sub-region of CC was significantly smaller in ASD, although there was no group difference in total CC volume. ASD participants also showed stronger homotopic connectivity in the superior frontal gyrus. SRS scores were negatively correlated with the CC central sub-region volumes in ASD. The findings of this study add to the body of research showing morphological differences in the CC in ASD as well as connectivity differences. The absence of a significant relationship between structure and homotopic functional connectivity aligns with previous findings.

Reduced Inter-hemispheric Resting State Functional Connectivity and Its Association With Social Deficits in Autism.

Autism spectrum disorder (ASD) is an early onset developmental disorder which persists throughout life and is increasing in prevalence over the last few decades. Given its early onset and variable cognitive and emotional functional impairments, it is generally challenging to assess ASD individuals using task-based behavioral and functional MRI paradigms. Consequently, resting state functional MRI (rs-fMRI) has become a key approach for examining ASD-associated neural alterations and revealed functional alterations in large-scale brain networks relative to typically developing (TD) individuals, particularly those involved in social-cognitive and affective processes. Recent progress suggests that alterations in inter-hemispheric resting state functional connectivity (rsFC) between regions in the 2 brain hemispheres, particularly homotopic ones, may be of great importance. Here we have reviewed neuroimaging studies examining inter-hemispheric rsFC abnormities in ASD and its associations with symptom severity. As an index of inter-hemispheric functional connectivity, we have additionally reviewed previous studies on corpus callosum (CC) volumetric and fiber changes in ASD. There are converging findings on reduced inter-hemispheric (including homotopic) rsFC in large-scale brain networks particularly in posterior hubs of the default mode network, reduced volumes in the anterior and posterior CC, and on decreased FA and increased MD or RD across CC subregions. Associations between the strength of inter-hemispheric rsFC and social impairments in ASD together with their classification performance in distinguishing ASD subjects from TD controls across ages suggest that the strength of inter-hemispheric rsFC may be a more promising biomarker for assisting in ASD diagnosis than abnormalities in either brain wide rsFC or brain structure.

Microstructural Injury to Corpus Callosum and Intrahemispheric White Matter Tracts Correlate With Attention and Processing Speed Decline After Brain Radiation

The corpus callosum (CC) and intrahemispheric white matter tracts (IHWM) subserve critical aspects of attention and processing speed. We analyzed imaging biomarkers of microstructural injury within these regions and association with attention and processing speed performance before and after radiation therapy in primary brain tumor patients. In a prospective clinical trial, 44 primary brain tumor patients underwent cognitive testing and magnetic resonance imaging/diffusion-weighted imaging at baseline (pre-radiation therapy) and 3-, 6-, and 12-months post-radiation therapy. CC (subregions, total) and IHWM tracts (left/right without CC, total) were autosegmented; tumor, tumor bed, and edema were censored. Biomarkers included volume changes (cm3), mean diffusivity ([MD]; higher values indicate white matter injury), fractional anisotropy ([FA]; lower values indicate white matter injury). Reliable-change indices measured changes in attention (Weschler Adult Intelligence Scale [WAIS-IV] digits-forward; Delis-Kaplan Executive Function System Trail Making [D-KEFS-TM] visual-scanning), and processing speed (WAIS-IV coding; D-KEFS-TM number-sequencing, letter-sequencing), accounting for practice effects. Linear mixed-effects models evaluated associations between mean radiation dose and biomarkers (volume, MD, FA) and imaging biomarkers and neurocognitive performance. Statistics were corrected for multiple comparisons. Processing speed declined at 6 months following radiation therapy (number sequencing, letter sequencing; P < .04). Seizures and antiepileptic drug therapy were associated with lower visual-scanning attention reliable-change indices at 6 months (P = .039). Higher radiation dose correlated with smaller midanterior CC volume (P = .023); lower FA in posterior CC, anterior CC, and total CC (all P < .03); and higher MD in anterior CC (P = .012). Smaller midanterior CC and left IHWM volume correlated with worse processing speed (coding, letter-sequencing, number-sequencing; all P < .03). Higher FA in right, left, and total IHWM correlated with better coding scores (all P < .01). Lower FA in total IHWM (P = .009) was associated with worse visual-scanning attention scores. Higher FA in midposterior CC (P = .029) correlated with better digits-forward attention scores. The CC demonstrated radiation dose-dependent atrophy and WM injury. Microstructural injury within the CC and IHWM was associated with attention and processing speed decline after radiation therapy. These areas represent possible avoidance regions for preservation of attention and processing speed.

Subject-specific multiscale analysis of concussion: from macroscopic loads to molecular-level damage

Sports concussion is a form of mild traumatic brain injury (mTBI) caused by an impulsive force transmitted to the head. While concussion is recognized as a complex pathophysiological process affecting the brain at multiple scales, the causal link between external load and cellular, molecular level damage in mTBI remains elusive. The present study proposes a multiscale framework to analyze concussion and demonstrates its applicability with a real-life concussion case. The multiscale analysis starts from inputting mouth guard-recorded head kinematic into a detailed finite element (FE) head model tailored to the subject's head and white matter (WM) tract morphology. The resulting WM tract-oriented strains are then extracted and input to histology-informed micromechanical models of corpus callosum subregions with axonal detail to obtain axolemma strains at a subcellular level. By comparing axolemma strains against mechanoporation thresholds obtained via molecular dynamics (MD) simulations, axonal damage is inferred corresponding to a likelihood of concussion, in line with clinical observation. This novel multiscale framework bridges the organ-to-molecule length scales and accounts both inter- and intra-subject regional variability, providing a new way of non-invasively predicting axonal damage and real-life concussion analysis. The framework may contribute to a better understanding of the mechanistic causes behind concussion. Statement of SignificanceThis study reports a multiscale computational framework for concussion, for the first time revealing a picture of how a global impact to the head measured on the field transfers to the cellular level of axons and finally down to the molecular level. Demonstrated with a real-life concussion case using a detailed and subject-specific head model, the results show molecular level damage corresponds to a likelihood of concussion, in line with clinical observation. An insight into the multiscale mechanical consequences is critical for a better understanding of the complex pathophysiological process affecting the brain at impact, which today are still poorly understood. Analyzing the concussive injury mechanisms the whole way from brains to molecules may also have significant clinical relevance. We show that in a typical injury scenario, the axolemma sustains large enough strains to entail pore formation in the adjoining lipid bilayer. Proration is found to occur in bilayer regions lacking ganglioside lipids, which provides important implications for the treatment of brain injury and other related neurodegenerative diseases.