Intact Bilateral Resting-State Networks in the Absence of the Corpus Callosum

Temporal correlations between different brain regions in the resting-state BOLD signal are thought to reflect intrinsic functional brain connectivity (Biswal et al., 1995; Greicius et al., 2003; Fox et al., 2007). The functional networks identified are typically bilaterally distributed across the cerebral hemispheres, show similarity to known white matter connections (Greicius et al., 2009), and are seen even in anesthetized monkeys (Vincent et al., 2007). Yet it remains unclear how they arise. Here we tested two distinct possibilities: (1) functional networks arise largely from structural connectivity constraints, and generally require direct interactions between functionally coupled regions mediated by white-matter tracts; and (2) functional networks emerge flexibly with the development of normal cognition and behavior and can be realized in multiple structural architectures. We conducted resting-state fMRI in eight adult humans with complete agenesis of the corpus callosum (AgCC) and normal intelligence, and compared their data to those from eight healthy matched controls. We performed three main analyses: anatomical region-of-interest-based correlations to test homotopic functional connectivity, independent component analysis (ICA) to reveal functional networks with a data-driven approach, and ICA-based interhemispheric correlation analysis. Both groups showed equivalently strong homotopic BOLD correlation. Surprisingly, almost all of the group-level independent components identified in controls were observed in AgCC and were predominantly bilaterally symmetric. The results argue that a normal complement of resting-state networks and intact functional coupling between the hemispheres can emerge in the absence of the corpus callosum, favoring the second over the first possibility listed above

Relational Autoencoder for Feature Extraction

Feature extraction becomes increasingly important as data grows high dimensional. Autoencoder as a neural network based feature extraction method achieves great success in generating abstract features of high dimensional data. However, it fails to consider the relationships of data samples which may affect experimental results of using original and new features. In this paper, we propose a Relation Autoencoder model considering both data features and their relationships. We also extend it to work with other major autoencoder models including Sparse Autoencoder, Denoising Autoencoder and Variational Autoencoder. The proposed relational autoencoder models are evaluated on a set of benchmark datasets and the experimental results show that considering data relationships can generate more robust features which achieve lower construction loss and then lower error rate in further classification compared to the other variants of autoencoders.Comment: IJCNN-201

Personal space regulation by the human amygdala

The amygdala plays key roles in emotion and social cognition, but how this translates to face-to-face interactions involving real people remains unknown. We found that an individual with complete amygdala lesions lacked any sense of personal space. Furthermore, healthy individuals showed amygdala activation upon close personal proximity. The amygdala may be required to trigger the strong emotional reactions normally following personal space violations, thus regulating interpersonal distance in humans

Phase separation due to quantum mechanical correlations

Can phase separation be induced by strong electron correlations? We present a theorem that affirmatively answers this question in the Falicov-Kimball model away from half-filling, for any dimension. In the ground state the itinerant electrons are spatially separated from the classical particles.Comment: 4 pages, 1 figure. Note: text and figure unchanged, title was misspelle

Idiosyncratic Brain Activation Patterns Are Associated with Poor Social Comprehension in Autism

Autism spectrum disorder (ASD) features profound social deficits but neuroimaging studies have failed to find any consistent neural signature. Here we connect these two facts by showing that idiosyncratic patterns of brain activation are associated with social comprehension deficits. Human participants with ASD (N = 17) and controls (N = 20) freely watched a television situation comedy (sitcom) depicting seminaturalistic social interactions (“The Office”, NBC Universal) in the scanner. Intersubject correlations in the pattern of evoked brain activation were reduced in the ASD group—but this effect was driven entirely by five ASD subjects whose idiosyncratic responses were also internally unreliable. The idiosyncrasy of these five ASD subjects was not explained by detailed neuropsychological profile, eye movements, or data quality; however, they were specifically impaired in understanding the social motivations of characters in the sitcom. Brain activation patterns in the remaining ASD subjects were indistinguishable from those of control subjects using multiple multivariate approaches. Our findings link neurofunctional abnormalities evoked by seminaturalistic stimuli with a specific impairment in social comprehension, and highlight the need to conceive of ASD as a heterogeneous classification

Inferring Actual Treatment Pathways from Patient Records

Treatment pathways are step-by-step plans outlining the recommended medical care for specific diseases; they get revised when different treatments are found to improve patient outcomes. Examining health records is an important part of this revision process, but inferring patients' actual treatments from health data is challenging due to complex event-coding schemes and the absence of pathway-related annotations. This study aims to infer the actual treatment steps for a particular patient group from administrative health records (AHR) - a common form of tabular healthcare data - and address several technique- and methodology-based gaps in treatment pathway-inference research. We introduce Defrag, a method for examining AHRs to infer the real-world treatment steps for a particular patient group. Defrag learns the semantic and temporal meaning of healthcare event sequences, allowing it to reliably infer treatment steps from complex healthcare data. To our knowledge, Defrag is the first pathway-inference method to utilise a neural network (NN), an approach made possible by a novel, self-supervised learning objective. We also developed a testing and validation framework for pathway inference, which we use to characterise and evaluate Defrag's pathway inference ability and compare against baselines. We demonstrate Defrag's effectiveness by identifying best-practice pathway fragments for breast cancer, lung cancer, and melanoma in public healthcare records. Additionally, we use synthetic data experiments to demonstrate the characteristics of the Defrag method, and to compare Defrag to several baselines where it significantly outperforms non-NN-based methods. Defrag significantly outperforms several existing pathway-inference methods and offers an innovative and effective approach for inferring treatment pathways from AHRs. Open-source code is provided to encourage further research in this area

Recent Decisions

Comments on recent decisions by Daniel W. Hammer, John E. Kennedy, William J. Harte, Patrick F. McCartan, William D. Bailey, Jr., Donald L. Very, William C. Rindone, Jr., and Eugene F. Waye

Duration of Periconceptual Folic Acid Supplementation in Women Booking for Antenatal Care

Objective: To provide accurate estimates of the commencement time, duration and dosage of folic acid (FA) supplementation taken by Irish women in the periconceptional period. The study also aimed to establish the factors associated with optimal FA supplementation practices. Design: Cross-sectional observational study. Women’s clinical and sociodemographic details were computerised. Maternal weight and height were measured before calculating BMI. Detailed FA supplementation questionnaires were completed under the supervision of a trained researcher. Setting: A large university maternity hospital, Republic of Ireland, January 2014–April 2016. Subjects: Women (n 856) recruited at their convenience in the first trimester. Results: While almost all of the women (97 %) were taking FA at enrolment, only one in four women took FA for at least 12 weeks preconceptionally (n 208). Among the 44% of women who were supplementing with FA preconceptionally, 44% (162/370) reported taking FA for less than the 12 weeks required to achieve optimal red-blood-cell folate levels for prevention of neural tube defects. On multivariate analysis, only planned pregnancy and nulliparity were associated with taking FA for at least 12 weeks preconceptionally. Among women who only took FA postconceptionally, almost two-thirds commenced it after day 28 of their pregnancy when the neural tube had already closed. Conclusions: As the timing of FA was suboptimal both before and after conception, we recommend that current national FA guidelines need to be reviewed

A gap in the mass distribution for warm Neptune and terrestrial planets

Structure in the planet distribution provides an insight into the processes that shape the formation and evolution of planets. The Kepler mission has led to an abundance of statistical discoveries in regards to planetary radius, but the number of observed planets with measured masses is much smaller. By incorporating results from recent mass determination programs, we have discovered a new gap emerging in the planet population for sub-Neptune-mass planets with orbital periods less than 20 days. The gap follows a slope of decreasing mass with increasing orbital period, has a width of a few M ⊕, and is potentially completely devoid of planets. Fitting Gaussian mixture models to the planet population in this region favors a bimodel distribution over a unimodel one with a reduction in Bayesian information criterion of 19.9, highlighting the gap significance. We discuss several processes that could generate such a feature in the planet distribution, including a pileup of planets above the gap region, tidal interactions with the host star, dynamical interactions with the disk, with other planets, or with accreting material during the formation process