Impaired glymphatic system revealed by DTI-ALPS in cerebral palsy due to periventricular leukomalacia: relation with brain lesion burden and hand dysfunction.

PURPOSE: Preterm children with cerebral palsy (CP) often have varying hand dysfunction, while the specific brain injury with periventricular leukomalacia (PVL) cannot quite explain its mechanism. We aimed to investigate glymphatic activity using diffusion tensor image analysis along the perivascular space (DTI-ALPS) method and evaluate its association with brain lesion burden and hand dysfunction in children with CP secondary to PVL. METHODS: We retrospectively enrolled 18 children with bilateral spastic CP due to PVL and 29 age- and sex-matched typically developing controls. The Manual Ability Classification System (MACS) was used to assess severity of hand dysfunction in CP. A mediation model was performed to explore the relationship among the DTI-ALPS index, brain lesion burden, and the MACS level in children with CP. RESULTS: There were significant differences in the DTI-ALPS index between children with CP and their typically developing peers. The DTI-ALPS index of the children with CP was lower than that of the controls (1.448 vs. 1.625, P = 0.003). The mediation analysis showed that the DTI-ALPS index fully mediated the relationship between brain lesion burden and the MACS level (c' = 0.061, P = 0.665), explaining 80% of the effect. CONCLUSION: This study provides new insights into the neural basis of hand dysfunction in children with CP, demonstrating an important role of glymphatic impairment in such patients. These results suggest that PVL might affect hand function in children with CP by disrupting glymphatic drainage.

Atrophy of hippocampal subfields relates to memory decline during the pathological progression of Alzheimer's disease.

Background: It has been well documented that atrophy of hippocampus and hippocampal subfields is closely linked to cognitive decline in normal aging and patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, evidence is still sparce regarding the atrophy of hippocampus and hippocampal subfields in normal aging adults who later developed MCI or AD. Objective: To examine whether atrophy of hippocampus and hippocampal subfields has occurred in normal aging before a diagnosis of MCI or AD. Methods: We analyzed structural magnetic resonance imaging (MRI) data of cognitively normal (CN, n = 144), MCI (n = 90), and AD (n = 145) participants obtained from the Alzheimer's Disease Neuroimaging Initiative. The CN participants were categorized into early dementia converters (CN-C) and non-converters (CN-NC) based on their scores of clinical dementia rating after an average of 36.2 months (range: 6-105 months). We extracted the whole hippocampus and hippocampal subfields for each participant using FreeSurfer, and analyzed the differences in volumes of hippocampus and hippocampal subfields between groups. We then examined the associations between volume of hippocampal subfields and delayed recall scores in each group separately. Results: Hippocampus and most of the hippocampal subfields demonstrated significant atrophy during the progression of AD. The CN-C and CN-NC groups differed in the left hippocampus-amygdala transition area (HATA). Furthermore, the volume of presubiculum was significantly correlated with delayed recall scores in the CN-NC and AD groups, but not in the CN-C and MCI groups. Conclusion: Hippocampal subfield atrophy (i.e., left HATA) had occurred in cognitively normal elderly individuals before clinical symptoms were recognized. Significant associations of presubiculum with delayed recall scores in the CN-NC and AD groups highlight the essential role of the hippocampal subfields in both early dementia detection and AD progression.

Absence of associations with prefrontal cortex and cerebellum may link to early language and social deficits in preschool children with ASD.

Introduction: Autism spectrum disorder (ASD) is a complex developmental disorder, characterized by language and social deficits that begin to appear in the first years of life. Research in preschool children with ASD has consistently reported increased global brain volume and abnormal cortical patterns, and the brain structure abnormalities have also been found to be clinically and behaviorally relevant. However, little is known regarding the associations between brain structure abnormalities and early language and social deficits in preschool children with ASD. Methods: In this study, we collected magnetic resonance imaging (MRI) data from a cohort of Chinese preschool children with and without ASD (24 ASD/20 non-ASD) aged 12-52 months, explored group differences in brain gray matter (GM) volume, and examined associations between regional GM volume and early language and social abilities in these two groups, separately. Results: We observed significantly greater global GM volume in children with ASD as compared to those without ASD, but there were no regional GM volume differences between these two groups. For children without ASD, GM volume in bilateral prefrontal cortex and cerebellum was significantly correlated with language scores; GM volume in bilateral prefrontal cortex was significantly correlated with social scores. No significant correlations were found in children with ASD. Discussion: Our data demonstrate correlations of regional GM volume with early language and social abilities in preschool children without ASD, and the absence of these associations appear to underlie language and social deficits in children with ASD. These findings provide novel evidence for the neuroanatomical basis associated with language and social abilities in preschool children with and without ASD, which promotes a better understanding of early deficits in language and social functions in ASD.

Coupling Between Hippocampal Parenchymal Fraction and Cortical Grey Matter Atrophy at Different Stages of Cognitive Decline.

BACKGROUND: Hippocampal atrophy is a significant brain marker of pathology in Alzheimer's disease (AD). The hippocampal parenchymal fraction (HPF) was recently developed to better assess the hippocampal volumetric integrity, and it has been shown to be a sensitive measure of hippocampal atrophy in AD. OBJECTIVE: To investigate the clinical relevance of hippocampal volumetric integrity as measured by the HPF and the coupling between the HPF and brain atrophy during AD progression. METHODS: We included data from 143 cognitively normal (CN), 101 mild cognitive impairment (MCI), and 125 AD participants. We examined group differences in the HPF, associations between HPF and cognitive ability, and coupling between the HPF and cortical grey matter volume in the CN, MCI, and AD groups. RESULTS: We observed progressive decreases in HPF from CN to MCI and from MCI to AD, and increases in the asymmetry of HPF, with the lowest asymmetry index (AI) in the CN group and the highest AI in the AD group. There was a significant association between HPF and cognitive ability across participants. The coupling between HPF and cortical regions was observed in bilateral hippocampus, parahippocampal gyrus, temporal, frontal, and occipital regions, thalamus, and amygdala in CN, MCI, and AD groups, with a greater involvement of temporal, occipital, frontal, and subcortical regions in MCI and AD patients, especially in AD patients. CONCLUSION: This study provides novel evidence for the neuroanatomical basis of cognitive decline and brain atrophy during AD progression, which may have important clinical implications for the prognosis of AD.

Posterior superior temporal cortex connectivity is related to social communication in toddlers.

The second year of life is a time when social communication skills typically develop, but this growth may be slower in toddlers with language delay. In the current study, we examined how brain functional connectivity is related to social communication abilities in a sample of 12-24 month-old toddlers including those with typical development (TD) and those with language delays (LD). We used an a-priori, seed-based approach to identify regions forming a functional network with the left posterior superior temporal cortex (LpSTC), a region associated with language and social communication in older children and adults. Social communication and language abilities were assessed using the Communication and Symbolic Behavior Scales (CSBS) and Mullen Scales of Early Learning. We found a significant association between concurrent CSBS scores and functional connectivity between the LpSTC and the right posterior superior temporal cortex (RpSTC), with greater connectivity between these regions associated with better social communication abilities. However, functional connectivity was not related to rate of change or language outcomes at 36 months of age. These data suggest an early marker of low communication abilities may be decreased connectivity between the left and right pSTC. Future longitudinal studies should test whether this neurobiological feature is predictive of later social or communication impairments.

Discrepancy between inter- and intra-subject variability in EEG-based motor imagery brain-computer interface: Evidence from multiple perspectives.

Introduction: Inter- and intra-subject variability are caused by the variability of the psychological and neurophysiological factors over time and across subjects. In the application of in Brain-Computer Interfaces (BCI), the existence of inter- and intra-subject variability reduced the generalization ability of machine learning models seriously, which further limited the use of BCI in real life. Although many transfer learning methods can compensate for the inter- and intra-subject variability to some extent, there is still a lack of clear understanding about the change of feature distribution between the cross-subject and cross-session electroencephalography (EEG) signal. Methods: To investigate this issue, an online platform for motor-imagery BCI decoding has been built in this work. The EEG signal from both the multi-subject (Exp1) and multi-session (Exp2) experiments has been analyzed from multiple perspectives. Results: Firstly we found that with the similar variability of classification results, the time-frequency response of the EEG signal within-subject in Exp2 is more consistent than cross-subject results in Exp1. Secondly, the standard deviation of the common spatial pattern (CSP) feature has a significant difference between Exp1 and Exp2. Thirdly, for model training, different strategies for the training sample selection should be applied for the cross-subject and cross-session tasks. Discussion: All these findings have deepened the understanding of inter- and intra-subject variability. They can also guide practice for the new transfer learning methods development in EEG-based BCI. In addition, these results also proved that BCI inefficiency was not caused by the subject's unable to generate the event-related desynchronization/synchronization (ERD/ERS) signal during the motor imagery.

Atypical functional connectivity of temporal cortex with precuneus and visual regions may be an early-age signature of ASD.

BACKGROUND: Social and language abilities are closely intertwined during early typical development. In autism spectrum disorder (ASD), however, deficits in social and language development are early-age core symptoms. We previously reported that superior temporal cortex, a well-established social and language region, shows reduced activation to social affective speech in ASD toddlers; however, the atypical cortical connectivity that accompanies this deviance remains unknown. METHODS: We collected clinical, eye tracking, and resting-state fMRI data from 86 ASD and non-ASD subjects (mean age 2.3 ± 0.7 years). Functional connectivity of left and right superior temporal regions with other cortical regions and correlations between this connectivity and each child's social and language abilities were examined. RESULTS: While there was no group difference in functional connectivity, the connectivity between superior temporal cortex and frontal and parietal regions was significantly correlated with language, communication, and social abilities in non-ASD subjects, but these effects were absent in ASD subjects. Instead, ASD subjects, regardless of different social or nonsocial visual preferences, showed atypical correlations between temporal-visual region connectivity and communication ability (r(49) = 0.55, p < 0.001) and between temporal-precuneus connectivity and expressive language ability (r(49) = 0.58, p < 0.001). LIMITATIONS: The distinct connectivity-behavior correlation patterns may be related to different developmental stages in ASD and non-ASD subjects. The use of a prior 2-year-old template for spatial normalization may not be optimal for a few subjects beyond this age range. CONCLUSIONS: Superior temporal cortex is known to have reduced activation to social affective speech in ASD at early ages, and here we find in ASD toddlers that it also has atypical connectivity with visual and precuneus cortices that is correlated with communication and language ability, a pattern not seen in non-ASD toddlers. This atypicality may be an early-age signature of ASD that also explains why the disorder has deviant early language and social development. Given that these atypical connectivity patterns are also present in older individuals with ASD, we conclude these atypical connectivity patterns persist across age and may explain why successful interventions targeting language and social skills at all ages in ASD are so difficult to achieve.

A predictive ensemble classifier for the gene expression diagnosis of ASD at ages 1 to 4 years.

Autism Spectrum Disorder (ASD) diagnosis remains behavior-based and the median age of diagnosis is ~52 months, nearly 5 years after its first-trimester origin. Accurate and clinically-translatable early-age diagnostics do not exist due to ASD genetic and clinical heterogeneity. Here we collected clinical, diagnostic, and leukocyte RNA data from 240 ASD and typically developing (TD) toddlers (175 toddlers for training and 65 for test). To identify gene expression ASD diagnostic classifiers, we developed 42,840 models composed of 3570 gene expression feature selection sets and 12 classification methods. We found that 742 models had AUC-ROC ≥ 0.8 on both Training and Test sets. Weighted Bayesian model averaging of these 742 models yielded an ensemble classifier model with accurate performance in Training and Test gene expression datasets with ASD diagnostic classification AUC-ROC scores of 85-89% and AUC-PR scores of 84-92%. ASD toddlers with ensemble scores above and below the overall ASD ensemble mean of 0.723 (on a scale of 0 to 1) had similar diagnostic and psychometric scores, but those below this ASD ensemble mean had more prenatal risk events than TD toddlers. Ensemble model feature genes were involved in cell cycle, inflammation/immune response, transcriptional gene regulation, cytokine response, and PI3K-AKT, RAS and Wnt signaling pathways. We additionally collected targeted DNA sequencing smMIPs data on a subset of ASD risk genes from 217 of the 240 ASD and TD toddlers. This DNA sequencing found about the same percentage of SFARI Level 1 and 2 ASD risk gene mutations in TD (12 of 105) as in ASD (13 of 112) toddlers, and classification based only on the presence of mutation in these risk genes performed at a chance level of 49%. By contrast, the leukocyte ensemble gene expression classifier correctly diagnostically classified 88% of TD and ASD toddlers with ASD risk gene mutations. Our ensemble ASD gene expression classifier is diagnostically predictive and replicable across different toddler ages, races, and ethnicities; out-performs a risk gene mutation classifier; and has potential for clinical translation.

Risk Factors of Prolonged Mechanical Ventilation in Patients Undergoing Redo Valve Surgery.

BACKGROUND: Prolonged mechanical ventilation (PMV) after cardiac surgery is associated with high morbidity and mortality. Patients following redo valve surgery possess many attributes that place them at risk for PMV, yet few studies particularly focused on them. The purpose of this study was to identify perioperative variables associated with PMV in redo valve surgery. METHODS: A retrospective study, including 117 patients who underwent redo valve surgery from November 2017 to September 2021, was performed. The potential perioperative risk factors for PMV were collected. PMV was defined as the need for intubation and mechanical ventilation for >24 h, after completion of the operation. The clinical data were analyzed with univariate and multivariate analyses to identify risk factors for PMV following redo valve surgery. RESULTS: The incidence of PMV was 38.5% (N = 45). Multiple logistic regression analysis showed perioperative risk factors for PMV included advanced age (age>57 years) [odds ratio (OR) 3.043, 95% confidence interval (CI) 1.172-7.905, P = 0.022], low weight (weight ≤58 kg) (OR 2.798, 95% CI: 1.088-7.199, P = 0.033), EuroSCORE II ≥6.8% (OR 3.467, 95% CI: 1.364-8.817, P = 0.009), and VIS at 12 hours post ICU admission (VIS12) >10 (OR 5.613, 95% CI: 2.211-14.249, P < 0.001). CONCLUSIONS: In adult patients undergoing redo valve surgery, advanced age, low weight, high EuroSCORE II and a high VIS at 12 hours post-ICU admission were associated with PMV. Hemodynamic status after operation were more important than preoperative and intraoperative variables in predicting PMV.

Risk Factors for Postoperative Acute Kidney Injury in Patients Undergoing Redo Cardiac Surgery Using Cardiopulmonary Bypass.

Objective: This paper aimed to investigate the incidence and risk factors of postoperative acute kidney injury (AKI) in adult patients undergoing redo cardiac surgery with cardiopulmonary bypass (CPB), and explore the impact of AKI on early outcomes. Methods: A total of 116 patients undergoing redo cardiac surgery with CPB between November 2017 and May 2021 were included. Patients were divided into two groups, AKI group and non-AKI group, according to the Kidney Disease Improving Global Outcomes criteria. Perioperative variables were retrospectively collected and analyzed. Risk factors for the development of AKI were investigated by univariate and multiple logistic regression models. Clinical outcomes were also compared between the groups. Results: Postoperative AKI occurred in 63 patients (54.3%), among whom renal replacement therapy was required in 12 patients (19.0%). The mechanical ventilation time (AKI: 43.00 (19.00, 72.00) hours; non-AKI: 18.00 (15.00, 20.00) hours; p < 0.001), ICU length of stay (AKI: 4.00 (2.00, 6.00) days; non-AKI: 3.00 (2.00, 4.00) days; p = 0.010), hospital length of stay since operation (AKI: 12.00 (8.00, 18.00) days; non-AKI: 9.00 (7.00, 12.50) days; p = 0.024), dialysis (AKI: 12.00 (19.05%); non-AKI: 0 (0%); p = 0.001), reintubation (AKI: 7.00 (11.11%); non-AKI: 0 (0%); p = 0.035), and hospital mortality (AKI: 8.00 (12.70%); non-AKI: 0 (0%); p = 0.020) were all higher in the AKI group than in the non-AKI group. Multivariate analysis revealed that high aspartate aminotransferase (OR, 1.028, 95% CI, 1.003 to 1.053, p = 0.025), coronary angiogram within 2 weeks before surgery (OR, 3.209, 95% CI, 1.307 to 7.878, p = 0.011) and CPB time (OR, 1.012, 95% CI, 1.005 to 1.019, p = 0.001) were independent risk factors for postoperative AKI. Conclusions: High aspartate aminotransferase, coronary angiogram within 2 weeks before surgery and CPB time seem to be associated with an increased incidence of postoperative AKI in patients with redo cardiac surgery.

Large scale validation of an early-age eye-tracking biomarker of an autism spectrum disorder subtype.

Few clinically validated biomarkers of ASD exist which can rapidly, accurately, and objectively identify autism during the first years of life and be used to support optimized treatment outcomes and advances in precision medicine. As such, the goal of the present study was to leverage both simple and computationally-advanced approaches to validate an eye-tracking measure of social attention preference, the GeoPref Test, among 1,863 ASD, delayed, or typical toddlers (12-48 months) referred from the community or general population via a primary care universal screening program. Toddlers participated in diagnostic and psychometric evaluations and the GeoPref Test: a 1-min movie containing side-by-side dynamic social and geometric images. Following testing, diagnosis was denoted as ASD, ASD features, LD, GDD, Other, typical sibling of ASD proband, or typical. Relative to other diagnostic groups, ASD toddlers exhibited the highest levels of visual attention towards geometric images and those with especially high fixation levels exhibited poor clinical profiles. Using the 69% fixation threshold, the GeoPref Test had 98% specificity, 17% sensitivity, 81% PPV, and 65% NPV. Sensitivity increased to 33% when saccades were included, with comparable validity across sex, ethnicity, or race. The GeoPref Test was also highly reliable up to 24 months following the initial test. Finally, fixation levels among twins concordant for ASD were significantly correlated, indicating that GeoPref Test performance may be genetically driven. As the GeoPref Test yields few false positives (~ 2%) and is equally valid across demographic categories, the current findings highlight the ability of the GeoPref Test to rapidly and accurately detect autism before the 2nd birthday in a subset of children and serve as a biomarker for a unique ASD subtype in clinical trials.

Developmental differences in brain functional connectivity during social interaction in middle childhood.

The transition from childhood to adolescence is marked by significant changes in peer interactions. However, limited research has examined the brain systems (e.g., mentalizing and reward networks) involved in direct peer interaction, particularly during childhood and early adolescence. Here, we analyzed fMRI data from 50 children aged 8-12 years while they participated in a task in which they chatted with a peer (Peer) or answered questions about a story character (Character). Using a beta-series correlation analysis, we investigated how social interaction modulates functional connectivity within and between mentalizing and reward networks and whether this modulation changes with age. We observed effects of social interaction on functional connectivity were modulated by age within the mentalizing and reward networks. Further, greater connectivity within and between these networks during social interaction was related to faster reaction time to the Peer versus Character condition. Similar effects were found in the salience and mirror neuron networks. These findings provide insights into age-related differences in how the brain supports social interaction, and thus have the potential to advance our understanding of core social difficulties in social-communicative disorders, such as autism spectrum disorder.

Neural responses to affective speech, including motherese, map onto clinical and social eye tracking profiles in toddlers with ASD.

Affective speech, including motherese, captures an infant's attention and enhances social, language and emotional development. Decreased behavioural response to affective speech and reduced caregiver-child interactions are early signs of autism in infants. To understand this, we measured neural responses to mild affect speech, moderate affect speech and motherese using natural sleep functional magnetic resonance imaging and behavioural preference for motherese using eye tracking in typically developing toddlers and those with autism. By combining diverse neural-clinical data using similarity network fusion, we discovered four distinct clusters of toddlers. The autism cluster with the weakest superior temporal responses to affective speech and very poor social and language abilities had reduced behavioural preference for motherese, while the typically developing cluster with the strongest superior temporal response to affective speech showed the opposite effect. We conclude that significantly reduced behavioural preference for motherese in autism is related to impaired development of temporal cortical systems that normally respond to parental affective speech.

Progressive structural and covariance connectivity abnormalities in patients with Alzheimer's disease.

Background: Alzheimer's disease (AD) is one of most prevalent neurodegenerative diseases worldwide and characterized by cognitive decline and brain structure atrophy. While studies have reported substantial grey matter atrophy related to progression of AD, it remains unclear about brain regions with progressive grey matter atrophy, covariance connectivity, and the associations with cognitive decline in AD patients. Objective: This study aims to investigate the grey matter atrophy, structural covariance connectivity abnormalities, and the correlations between grey matter atrophy and cognitive decline during AD progression. Materials: We analyzed neuroimaging data of healthy controls (HC, n = 45) and AD patients (n = 40) at baseline (AD-T1) and one-year follow-up (AD-T2) obtained from the Alzheimer's Disease Neuroimaging Initiative. We investigated AD-related progressive changes of grey matter volume, covariance connectivity, and the clinical relevance to further understand the pathological progression of AD. Results: The results showed clear patterns of grey matter atrophy in inferior frontal gyrus, prefrontal cortex, lateral temporal gyrus, posterior cingulate cortex, insula, hippocampus, caudate, and thalamus in AD patients. There was significant atrophy in bilateral superior temporal gyrus (STG) and left caudate in AD patients over a one-year period, and the grey matter volume decrease in right STG and left caudate was correlated with cognitive decline. Additionally, we found reduced structural covariance connectivity between right STG and left caudate in AD patients. Using AD-related grey matter atrophy as features, there was high discrimination accuracy of AD patients from HC, and AD patients at different time points.

Asymptomatic carotid stenosis is associated with both edge and network reconfigurations identified by single-subject cortical thickness networks.

Background and purpose: Patients with asymptomatic carotid stenosis, even without stroke, are at high risk for cognitive impairment, and the neuroanatomical basis remains unclear. Using a novel edge-centric structural connectivity (eSC) analysis from individualized single-subject cortical thickness networks, we aimed to examine eSC and network measures in severe (> 70%) asymptomatic carotid stenosis (SACS). Methods: Twenty-four SACS patients and 24 demographically- and comorbidities-matched controls were included, and structural MRI and multidomain cognitive data were acquired. Individual eSC was estimated via the Manhattan distances of pairwise cortical thickness histograms. Results: In the eSC analysis, SACS patients showed longer interhemispheric but shorter intrahemispheric Manhattan distances seeding from left lateral temporal regions; in network analysis the SACS patients had a decreased system segregation paralleling with white matter hyperintensity burden and recall memory. Further network-based statistic analysis identified several eSC and subgraph features centred around the Perisylvian regions that predicted silent lesion load and cognitive tests. Conclusion: We conclude that SACS exhibits abnormal eSC and a less-optimized trade-off between physical cost and network segregation, providing a reference and perspective for identifying high-risk individuals.

Gray matter asymmetry in asymptomatic carotid stenosis.

Even clinically "asymptomatic" carotid stenosis is associated with multidomain cognitive impairment, gray matter (GM) atrophy, and silent lesion. However, the links between them remain unclear. Using structural MRI data, we examined GM asymmetry index (AI) and white matter hyperintensity (WMH) in 24 patients with severe asymptomatic carotid stenosis (SACS), 24 comorbidity-matched controls, and independent samples of 84 elderly controls and 22 young adults. As compared to controls, SACS patients showed worse verbal memories, higher WMH burden, and right-lateralized GM in posterior middle temporal and mouth-somatomotor regions. These clusters extended to pars triangularis, lateral temporal, and cerebellar regions, when compared with young adults. Further, a full-path of WMH burden (X), GM volume (atrophy, M1), AI (asymmetry, M2), and neuropsychological variables (Y) through a serial mediation model was analyzed. This analysis identified that left-dominated GM atrophy and right-lateralized asymmetry in the posterior middle temporal cortex mediated the relationship between WMH burden and recall memory in SACS patients. These results suggest that the unbalanced hemispheric atrophy in the posterior middle temporal cortex is crucial to mediating relationship between WMH burden and verbal recall memories, which may underlie accelerated aging and cognitive deterioration in patients with SACS and other vascular cognitive impairment.

Surface-based Cortical Morphometry, White Matter Hyperintensity, and Multidomain Cognitive Performance in Asymptomatic Carotid Stenosis.

Carotid stenosis is a major contributor to vascular dementia. Recent studies suggest that even clinically "asymptomatic" carotid stenosis is linked with cognitive decline and neuroimaging changes. Here we examined surface-based cortical morphometry, white matter hyperintensity (WMH), and multidomain cognitive performance in unilateral severe (>70% narrowing) asymptomatic carotid stenosis (SACS). We included 24 SACS patients (19 males/5 females; 64.25 ± 7.18 years) and 24 comorbidities-matched controls (19 males/5 females; 67.16 ± 6.10 years), and measured cortical thickness, sulcal depth, gyrification, cortical complexity, and WMH loads with structural MRI images. The SACS patients exhibited: (1) thinner cortex in bilateral somatosensory/motor, bilateral inferior frontal, bilateral fusiform, and left lateral temporal areas; (2) shallower sulci in left lateral temporal, parietal, insular and somatosensory/motor areas; (3) both hyper- and hypo-gyrification in lateral temporal and frontal cortices; (4) lower complexity (fractal dimension) in left insular and right superior temporal areas. Further association analyses showed that the cortical alterations were significantly correlated with verbal memory and WMH burden in SACS. These results suggest that SACS patients present a left-dominated damage tendency, especially in the Perisylvian cortices that span across several large-scale systems of somatosensory/motor and language. Our findings also provide cortical anatomy evidence for cognitive impairment in SACS, suggesting a neuroanatomical predisposition to dementia and cerebrovascular events.

Resting State Functional Connectivity Associated With Sahaja Yoga Meditation.

Neuroscience research has shown that meditation practices have effects on brain structure and function. However, few studies have combined information on the effects on structure and function in the same sample. Long-term daily meditation practice produces repeated activity of specific brain networks over years of practice, which may induce lasting structural and functional connectivity (FC) changes within relevant circuits. The aim of our study was therefore to identify differences in FC during the resting state between 23 Sahaja Yoga Meditation experts and 23 healthy participants without meditation experience. Seed-based FC analysis was performed departing from voxels that had shown structural differences between these same participants. The contrast of connectivity maps yielded that meditators showed increased FC between the left ventrolateral prefrontal cortex and the right dorsolateral prefrontal cortex but reduced FC between the left insula and the bilateral mid-cingulate as well as between the right angular gyrus and the bilateral precuneus/cuneus cortices. It thus appears that long-term meditation practice increases direct FC between ventral and dorsal frontal regions within brain networks related to attention and cognitive control and decreases FC between regions of these networks and areas of the default mode network.

Handling Multiplicity in Neuroimaging Through Bayesian Lenses with Multilevel Modeling.

Here we address the current issues of inefficiency and over-penalization in the massively univariate approach followed by the correction for multiple testing, and propose a more efficient model that pools and shares information among brain regions. Using Bayesian multilevel (BML) modeling, we control two types of error that are more relevant than the conventional false positive rate (FPR): incorrect sign (type S) and incorrect magnitude (type M). BML also aims to achieve two goals: 1) improving modeling efficiency by having one integrative model and thereby dissolving the multiple testing issue, and 2) turning the focus of conventional null hypothesis significant testing (NHST) on FPR into quality control by calibrating type S errors while maintaining a reasonable level of inference efficiency. The performance and validity of this approach are demonstrated through an application at the region of interest (ROI) level, with all the regions on an equal footing: unlike the current approaches under NHST, small regions are not disadvantaged simply because of their physical size. In addition, compared to the massively univariate approach, BML may simultaneously achieve increased spatial specificity and inference efficiency, and promote results reporting in totality and transparency. The benefits of BML are illustrated in performance and quality checking using an experimental dataset. The methodology also avoids the current practice of sharp and arbitrary thresholding in the p-value funnel to which the multidimensional data are reduced. The BML approach with its auxiliary tools is available as part of the AFNI suite for general use.

Neural correlates of developing theory of mind competence in early childhood.

Theory of mind (ToM) encompasses a range of abilities that show different developmental time courses. However, relatively little work has examined the neural correlates of ToM during early childhood. In this study, we investigated the neural correlates of ToM in typically developing children aged 4-8 years using resting-state functional magnetic resonance imaging. We calculated whole-brain functional connectivity with the right temporo-parietal junction (RTPJ), a core region involved in ToM, and examined its relation to children's early, basic, and advanced components of ToM competence assessed by a parent-report measure. Total ToM and both basic and advanced ToM components, but not early, consistently showed a positive correlation with connectivity between RTPJ and posterior cingulate cortex/precuneus; advanced ToM was also correlated with RTPJ to left TPJ connectivity. However, early and advanced ToM components showed negative correlation with the right inferior/superior parietal lobe, suggesting that RTPJ network differentiation is also related to ToM abilities. We confirmed and extended these results using a Bayesian modeling approach demonstrating significant relations between multiple nodes of the mentalizing network and ToM abilities, with no evidence for differences in relations between ToM components. Our data provide new insights into the neural correlates of multiple aspects of ToM in early childhood and may have implications for both typical and atypical development of ToM.