Deep neural networks capture texture sensitivity in V2.

Deep convolutional neural networks (CNNs) trained on visual objects have shown intriguing ability to predict some response properties of visual cortical neurons. However, the factors (e.g., if the model is trained or not, receptive field size) and computations (e.g., convolution, rectification, pooling, normalization) that give rise to such ability, at what level, and the role of intermediate processing stages in explaining changes that develop across areas of the cortical hierarchy are poorly understood. We focused on the sensitivity to textures as a paradigmatic example, since recent neurophysiology experiments provide rich data pointing to texture sensitivity in secondary (but not primary) visual cortex (V2). We initially explored the CNN without any fitting to the neural data and found that the first two layers of the CNN showed qualitative correspondence to the first two cortical areas in terms of texture sensitivity. We therefore developed a quantitative approach to select a population of CNN model neurons that best fits the brain neural recordings. We found that the CNN could develop compatibility to secondary cortex in the second layer following rectification and that this was improved following pooling but only mildly influenced by the local normalization operation. Higher layers of the CNN could further, though modestly, improve the compatibility with the V2 data. The compatibility was reduced when incorporating random rather than learned weights. Our results show that the CNN class of model is effective for capturing changes that develop across early areas of cortex, and has the potential to help identify the computations that give rise to hierarchical processing in the brain (code is available in GitHub).

Posterior reversible encephalopathy syndrome associated with dengue fever induced intrauterine death: A case report.

In recent years dengue fever has become a major health concern specifically due to its diverse presentation and adverse outcome. Progression from mild febrile illness to a severe systemic illness may occur in dengue fever including neurological disorder. Here, we report an unusual and rare case of a 20-year-old mother who developed posterior reversible encephalopathy syndrome (PRES) following dengue fever induced intrauterine death and septic shock.

The Aging Imageomics Study: rationale, design and baseline characteristics of the study population.

Biomarkers of aging are urgently needed to identify individuals at high risk of developing age-associated disease or disability. Growing evidence from population-based studies points to whole-body magnetic resonance imaging's (MRI) enormous potential for quantifying subclinical disease burden and for assessing changes that occur with aging in all organ systems. The Aging Imageomics Study aims to identify biomarkers of human aging by analyzing imaging, biopsychosocial, cardiovascular, metabolomic, lipidomic, and microbiome variables. This study recruited 1030 participants aged ≥50 years (mean 67, range 50-96 years) that underwent structural and functional MRI to evaluate the brain, large blood vessels, heart, abdominal organs, fat, spine, musculoskeletal system and ultrasonography to assess carotid intima-media thickness and plaques. Patients were notified of incidental findings detected by a certified radiologist when necessary. Extensive data were also collected on anthropometrics, demographics, health history, neuropsychology, employment, income, family status, exposure to air pollution and cardiovascular status. In addition, several types of samples were gathered to allow for microbiome, metabolomic and lipidomic profiling. Using big data techniques to analyze all the data points from biological phenotyping together with health records and lifestyle measures, we aim to cultivate a deeper understanding about various biological factors (and combinations thereof) that underlie healthy and unhealthy aging.

Normalization and pooling in hierarchical models of natural images.

Divisive normalization and subunit pooling are two canonical classes of computation that have become widely used in descriptive (what) models of visual cortical processing. Normative (why) models from natural image statistics can help constrain the form and parameters of such classes of models. We focus on recent advances in two particular directions, namely deriving richer forms of divisive normalization, and advances in learning pooling from image statistics. We discuss the incorporation of such components into hierarchical models. We consider both hierarchical unsupervised learning from image statistics, and discriminative supervised learning in deep convolutional neural networks (CNNs). We further discuss studies on the utility and extensions of the convolutional architecture, which has also been adopted by recent descriptive models. We review the recent literature and discuss the current promises and gaps of using such approaches to gain a better understanding of how cortical neurons represent and process complex visual stimuli.

Detection of cancer antigens (CA-125) using gold nano particles on interdigitated electrode-based microfluidic biosensor.

Integrating microfluidics with biosensors is of great research interest with the increasing trend of lab-on-the chip and point-of-care devices. Though there have been numerous studies performed relating microfluidics to the biosensing mechanisms, the study of the sensitivity variation due to microfluidic flow is very much limited. In this paper, the sensitivity of interdigitated electrodes was evaluated at the static drop condition and the microfluidic flow condition. In addition, this study demonstrates the use of gold nanoparticles to enhance the sensor signal response and provides experimental results of the capacitance difference during cancer antigen-125 (CA-125) antigen-antibody conjugation at multiple concentrations of CA-125 antigens. The experimental results also provide evidence of disease-specific detection of CA-125 antigen at multiple concentrations with the increase in capacitive signal response proportional to the concentration of the CA-125 antigens. The capacitive signal response of antigen-antibody conjugation on interdigitate electrodes has been enhanced by approximately 2.8 times (from 260.80 to 736.33 pF at 20 kHz frequency) in static drop condition and approximately 2.5 times (from 205.85 to 518.48 pF at 20 kHz frequency) in microfluidic flow condition with gold nanoparticle-coating. The capacitive signal response is observed to decrease at microfluidic flow condition at both plain interdigitated electrodes (from 260.80 to 205.85 pF at 20 kHz frequency) and gold nano particle coated interdigitated electrodes (from 736.33 to 518.48 pF at 20 kHz frequency), due to the strong shear effect compared to static drop condition. However, the microfluidic channel in the biosensor has the potential to increase the signal to noise ratio due to plasma separation from the whole blood and lead to the increase concentration of the biomarkers in the blood volume for sensing.

Managing Severe Tetanus without Ventilation Support in a Resource-limited Setting in Bangladesh.

Tetanus, a vaccine-preventable and potentially fatal disease, continues to remain prevalent in low- and middle-income countries. Furthermore, physicians are often unfamiliar with management of severe tetanus without ventilator support. Therefore, we proposed a modified treatment protocol that provides a low-cost and effective solution for the management of severe tetanus in resource-constrained settings. This is an observational study of 42 patients with severe tetanus treated during 2015-2016 at Surya Kanta Hospital, Bangladesh. This facility does not have an intensive care unit (ICU), and patients admitted here were provided treatment with the modified protocol. A total number of 42 patients with severe tetanus were treated with the modified protocol. Among them, 24 (57.1%) recovered completely, six (14.3%) recovered with the sequela, and 12 (28.6%) died. Among those who recovered with the sequela, four needed mechanical support during walking and two had a visual impairment. No significant adverse event was recorded during the treatment period. The results gathered during this case series provide a sustainable, low-cost, and effective solution to management of severe tetanus in resource-constrained settings where ICUs are unavailable.