Neuropsychiatric Disease Classification Using Functional Connectomics - Results of the Connectomics in NeuroImaging Transfer Learning Challenge

Large, open-source datasets, such as the Human Connectome Project and the Autism Brain Imaging Data Exchange, have spurred the development of new and increasingly powerful machine learning approaches for brain connectomics. However, one key question remains: are we capturing biologically relevant and generalizable information about the brain, or are we simply overfitting to the data? To answer this, we organized a scientific challenge, the Connectomics in NeuroImaging Transfer Learning Challenge (CNI-TLC), held in conjunction with MICCAI 2019. CNI-TLC included two classification tasks: (1) diagnosis of Attention-Deficit/Hyperactivity Disorder (ADHD) within a pre-adolescent cohort; and (2) transference of the ADHD model to a related cohort of Autism Spectrum Disorder (ASD) patients with an ADHD comorbidity. In total, 240 resting-state fMRI (rsfMRI) time series averaged according to three standard parcellation atlases, along with clinical diagnosis, were released for training and validation (120 neurotypical controls and 120 ADHD). We also provided Challenge participants with demographic information of age, sex, IQ, and handedness. The second set of 100 subjects (50 neurotypical controls, 25 ADHD, and 25 ASD with ADHD comorbidity) was used for testing. Classification methodologies were submitted in a standardized format as containerized Docker images through ChRIS, an open-source image analysis platform. Utilizing an inclusive approach, we ranked the methods based on 16 metrics: accuracy, area under the curve, F1-score, false discovery rate, false negative rate, false omission rate, false positive rate, geometric mean, informedness, markedness, Matthew’s correlation coefficient, negative predictive value, optimized precision, precision, sensitivity, and specificity. The final rank was calculated using the rank product for each participant across all measures. Furthermore, we assessed the calibration curves of each methodology. Five participants submitted their method for evaluation, with one outperforming all other methods in both ADHD and ASD classification. However, further improvements are still needed to reach the clinical translation of functional connectomics. We have kept the CNI-TLC open as a publicly available resource for developing and validating new classification methodologies in the field of connectomics

The neural basis of auditory temporal discrimination in girls with fragile X syndrome

Fragile X syndrome (FXS) is a common genetic disorder in which temporal processing may be impaired. To our knowledge however, no studies have examined the neural basis of temporal discrimination in individuals with FXS using functional magnetic resonance imaging (fMRI). Ten girls with fragile X syndrome and ten developmental age-matched typically developing controls performed an auditory temporal discrimination task in a 3T scanner. Girls with FXS showed significantly greater brain activation in a left-lateralized network, comprising left medial frontal gyrus, left superior and middle temporal gyrus, left cerebellum, and left brainstem (pons), when compared to a developmental age-matched typically developing group of subjects who had similar in-scanner task performance. There were no regions that showed significantly greater brain activation in the control group compared to individuals with FXS. These data indicate that networks of brain regions involved in auditory temporal processing may be dysfunctional in FXS. In particular, it is possible that girls with FXS employ left hemispheric resources to overcompensate for relative right hemispheric dysfunction

Medio-Frontal and Anterior Temporal abnormalities in children with attention deficit hyperactivity disorder (ADHD) during an acoustic antisaccade task as revealed by electro-cortical source reconstruction

<p>Abstract</p> <p>Background</p> <p>Attention Deficit Hyperactivity Disorder (ADHD) is one of the most prevalent disorders in children and adolescence. Impulsivity is one of three core symptoms and likely associated with inhibition difficulties. To date the neural correlate of the antisaccade task, a test of response inhibition, has not been studied in children with (or without) ADHD.</p> <p>Methods</p> <p>Antisaccade responses to visual and acoustic cues were examined in nine unmedicated boys with ADHD (mean age 122.44 ± 20.81 months) and 14 healthy control children (mean age 115.64 ± 22.87 months, three girls) while an electroencephalogram (EEG) was recorded. Brain activity before saccade onset was reconstructed using a 23-source-montage.</p> <p>Results</p> <p>When cues were acoustic, children with ADHD had a higher source activity than control children in Medio-Frontal Cortex (MFC) between -230 and -120 ms and in the left-hemispheric Temporal Anterior Cortex (TAC) between -112 and 0 ms before saccade onset, despite both groups performing similarly behaviourally (antisaccades errors and saccade latency). When visual cues were used EEG-activity preceding antisaccades did not differ between groups.</p> <p>Conclusion</p> <p>Children with ADHD exhibit altered functioning of the TAC and MFC during an antisaccade task elicited by acoustic cues. Children with ADHD need more source activation to reach the same behavioural level as control children.</p

Enhancing studies of the connectome in autism using the autism brain imaging data exchange II

The second iteration of the Autism Brain Imaging Data Exchange (ABIDE II) aims to enhance the scope of brain connectomics research in Autism Spectrum Disorder (ASD). Consistent with the initial ABIDE effort (ABIDE I), that released 1112 datasets in 2012, this new multisite open-data resource is an aggregate of resting state functional magnetic resonance imaging (MRI) and corresponding structural MRI and phenotypic datasets. ABIDE II includes datasets from an additional 487 individuals with ASD and 557 controls previously collected across 16 international institutions. The combination of ABIDE I and ABIDE II provides investigators with 2156 unique cross-sectional datasets allowing selection of samples for discovery and/or replication. This sample size can also facilitate the identification of neurobiological subgroups, as well as preliminary examinations of sex differences in ASD. Additionally, ABIDE II includes a range of psychiatric variables to inform our understanding of the neural correlates of co-occurring psychopathology; 284 diffusion imaging datasets are also included. It is anticipated that these enhancements will contribute to unraveling key sources of ASD heterogeneity

Neurexin-1 and Frontal Lobe White Matter: An Overlapping Intermediate Phenotype for Schizophrenia and Autism Spectrum Disorders

Background: Structural variation in the neurexin-1 (NRXN1) gene increases risk for both autism spectrum disorders (ASD) and schizophrenia. However, the manner in which NRXN1 gene variation may be related to brain morphology to confer risk for ASD or schizophrenia is unknown. Method/Principal Findings: 53 healthy individuals between 18–59 years of age were genotyped at 11 single nucleotide polymorphisms of the NRXN1 gene. All subjects received structural MRI scans, which were processed to determine cortical gray and white matter lobar volumes, and volumes of striatal and thalamic structures. Each subject’s sensorimotor function was also assessed. The general linear model was used to calculate the influence of genetic variation on neural and cognitive phenotypes. Finally, in silico analysis was conducted to assess potential functional relevance of any polymorphisms associated with brain measures. A polymorphism located in the 39 untranslated region of NRXN1 significantly influenced white matter volumes in whole brain and frontal lobes after correcting for total brain volume, age and multiple comparisons. Follow-up in silico analysis revealed that this SNP is a putative microRNA binding site that may be of functional significance in regulating NRXN1 expression. This variant also influenced sensorimotor performance, a neurocognitive function impaired in both ASD and schizophrenia. Conclusions: Our findings demonstrate that the NRXN1 gene, a vulnerability gene for SCZ and ASD, influences brai

Behavioural Risk Factors in Mid-Life Associated with Successful Ageing, Disability, Dementia and Frailty in Later Life: A Rapid Systematic Review.

BACKGROUND: Smoking, alcohol consumption, poor diet and low levels of physical activity significantly contribute to the burden of illness in developed countries. Whilst the links between specific and multiple risk behaviours and individual chronic conditions are well documented, the impact of these behaviours in mid-life across a range of later life outcomes has yet to be comprehensively assessed. This review aimed to provide an overview of behavioural risk factors in mid-life that are associated with successful ageing and the primary prevention or delay of disability, dementia, frailty and non-communicable chronic conditions. METHODS: A literature search was conducted to identify cohort studies published in English since 2000 up to Dec 2014. Multivariate analyses and a minimum follow-up of five years were required for inclusion. Two reviewers screened titles, abstracts and papers independently. Studies were assessed for quality. Evidence was synthesised by mid-life behavioural risk for a range of late life outcomes. FINDINGS: This search located 10,338 individual references, of which 164 are included in this review. Follow-up data ranged from five years to 36 years. Outcomes include dementia, frailty, disability and cardiovascular disease. There is consistent evidence of beneficial associations between mid-life physical activity, healthy ageing and disease outcomes. Across all populations studied there is consistent evidence that mid-life smoking has a detrimental effect on health. Evidence specific to alcohol consumption was mixed. Limited, but supportive, evidence was available relating specifically to mid-life diet, leisure and social activities or health inequalities. CONCLUSIONS: There is consistent evidence of associations between mid-life behaviours and a range of late life outcomes. The promotion of physical activity, healthy diet and smoking cessation in all mid-life populations should be encouraged for successful ageing and the prevention of disability and chronic disease.This work was funded by the National Institute for Health and Care Excellence (NICE), invitation to tender reference DDER 42013, and supported by the National Institute for Health Research School for Public Health Research. The scope of the work was defined by NICE and the protocol was agreed with NICE prior to the start of work. The funders had no role in data analysis, preparation of the manuscript or decision to publish.This is the final version of the article. It first appeared from PLOS via http://dx.doi.org/10.1371/journal.pone.014440

Examining the Latent Structure and Correlates of Sensory Reactivity in Autism: A Multi-Site Integrative Data Analysis by the Autism Sensory Research Consortium

BACKGROUND: Differences in responding to sensory stimuli, including sensory hyperreactivity (HYPER), hyporeactivity (HYPO), and sensory seeking (SEEK) have been observed in autistic individuals across sensory modalities, but few studies have examined the structure of these supra-modal traits in the autistic population. METHODS: Leveraging a combined sample of 3868 autistic youth drawn from 12 distinct data sources (ages 3-18 years and representing the full range of cognitive ability), the current study used modern psychometric and meta-analytic techniques to interrogate the latent structure and correlates of caregiver-reported HYPER, HYPO, and SEEK within and across sensory modalities. Bifactor statistical indices were used to both evaluate the strength of a general response pattern factor for each supra-modal construct and determine the added value of modality-specific response pattern scores (e.g., Visual HYPER). Bayesian random-effects integrative data analysis models were used to examine the clinical and demographic correlates of all interpretable HYPER, HYPO, and SEEK (sub)constructs. RESULTS: All modality-specific HYPER subconstructs could be reliably and validly measured, whereas certain modality-specific HYPO and SEEK subconstructs were psychometrically inadequate when measured using existing items. Bifactor analyses supported the validity of a supra-modal HYPER construct (ω LIMITATIONS: Conclusions may not be generalizable beyond the specific pool of items used in the current study, which was limited to caregiver report of observable behaviors and excluded multisensory items that reflect many real-world sensory experiences. CONCLUSION: Of the three sensory response patterns, only HYPER demonstrated sufficient evidence for valid interpretation at the supra-modal level, whereas supra-modal HYPO/SEEK constructs demonstrated substantial psychometric limitations. For clinicians and researchers seeking to characterize sensory reactivity in autism, modality-specific response pattern scores may represent viable alternatives that overcome many of these limitations

Developmental malformation of the corpus callosum: a review of typical callosal development and examples of developmental disorders with callosal involvement

This review provides an overview of the involvement of the corpus callosum (CC) in a variety of developmental disorders that are currently defined exclusively by genetics, developmental insult, and/or behavior. I begin with a general review of CC development, connectivity, and function, followed by discussion of the research methods typically utilized to study the callosum. The bulk of the review concentrates on specific developmental disorders, beginning with agenesis of the corpus callosum (AgCC)—the only condition diagnosed exclusively by callosal anatomy. This is followed by a review of several genetic disorders that commonly result in social impairments and/or psychopathology similar to AgCC (neurofibromatosis-1, Turner syndrome, 22q11.2 deletion syndrome, Williams yndrome, and fragile X) and two forms of prenatal injury (premature birth, fetal alcohol syndrome) known to impact callosal development. Finally, I examine callosal involvement in several common developmental disorders defined exclusively by behavioral patterns (developmental language delay, dyslexia, attention-deficit hyperactive disorder, autism spectrum disorders, and Tourette syndrome)