Administration of selective brain hypothermia using a simple cooling device in neonatal rats.

BACKGROUND: The interruption of oxygen and blood supply to the newborn brain around the time of birth is a risk factor for hypoxic-ischemic encephalopathy and may lead to infant mortality or lifelong neurological impairments. Currently, therapeutic hypothermia, the cooling of the infant's head or entire body, is the only treatment to curb the extent of brain damage. NEW METHOD: In this study, we designed a focal brain cooling device that circulates cooled water at a steady state temperature of 19 ± 1 °C through a coil of tubing fitted onto the neonatal rat's head. We tested its ability to selectively decrease brain temperature and offer neuroprotection in a neonatal rat model of hypoxic-ischemic brain injury. RESULTS: Our method cooled the brain to 30-33 °C in conscious pups, while keeping the core body temperature approximately 3.2 °C warmer. Furthermore, the application of the cooling device to the neonatal rat model demonstrated a reduction in brain volume loss compared to pups maintained at normothermia and achieved a level of brain tissue protection the same as that of whole-body cooling. COMPARISON WITH EXISTING METHODS: Prevailing methods of selective brain hypothermia are designed for adult animal models rather than for immature animals such as the rat as a conventional model of developmental brain pathology. Contrary to existing methods, our method of cooling does not require surgical manipulation or anaesthesia. CONCLUSION: Our simple, economical, and effective method of selective brain cooling is a useful tool for rodent studies in neonatal brain injury and adaptive therapeutic interventions.

Drug delivery platforms for neonatal brain injury.

Hypoxic-ischemic encephalopathy (HIE), initiated by the interruption of oxygenated blood supply to the brain, is a leading cause of death and lifelong disability in newborns. The pathogenesis of HIE involves a complex interplay of excitotoxicity, inflammation, and oxidative stress that results in acute to long term brain damage and functional impairments. Therapeutic hypothermia is the only approved treatment for HIE but has limited effectiveness for moderate to severe brain damage; thus, pharmacological intervention is explored as an adjunct therapy to hypothermia to further promote recovery. However, the limited bioavailability and the side-effects of systemic administration are factors that hinder the use of the candidate pharmacological agents. To overcome these barriers, therapeutic molecules may be packaged into nanoscale constructs to enable their delivery. Yet, the application of nanotechnology in infants is not well examined, and the neonatal brain presents unique challenges. Novel drug delivery platforms have the potential to magnify therapeutic effects in the damaged brain, mitigate side-effects associated with high systemic doses, and evade mechanisms that remove the drugs from circulation. Encouraging pre-clinical data demonstrates an attenuation of brain damage and increased structural and functional recovery. This review surveys the current progress in drug delivery for treating neonatal brain injury.

A Cortico- Basal Ganglia Model for choosing an optimal rehabilitation strategy in Hemiparetic Stroke.

To facilitate the selection of an optimal therapy for a stroke patient with upper extremity hemiparesis, we propose a cortico-basal ganglia model capable of performing reaching tasks under normal and stroke conditions. The model contains two hemispherical systems, each organized into an outer sensory-motor cortical loop and an inner basal ganglia (BG) loop, controlling their respective hands. The model is trained to simulate two therapeutic approaches: the constraint induced movement therapy (CIMT) in which the intact is arrested, and Bimanual Reaching in which the movements of the intact arm are found to aid the affected arm. Which of these apparently mutually conflicting approaches is right for a given patient? Based on our study on the effect of lesion size on arm performance, we hypothesize that the choice of the therapy depends on the lesion size. Whereas bimanual reaching is more suitable for smaller lesion size, CIMT is preferred in case of larger lesion sizes. By virtue of the model's ability to capture the experimental results effectively, we believe that it can serve as a benchmark for the development and testing of various rehabilitation strategies for stroke.

Modeling the Effect of Environmental Geometries on Grid Cell Representations.

Grid cells are a special class of spatial cells found in the medial entorhinal cortex (MEC) characterized by their strikingly regular hexagonal firing fields. This spatially periodic firing pattern is originally considered to be independent of the geometric properties of the environment. However, this notion was contested by examining the grid cell periodicity in environments with different polarity (Krupic et al., 2015) and in connected environments (Carpenter et al., 2015). Aforementioned experimental results demonstrated the dependence of grid cell activity on environmental geometry. Analysis of grid cell periodicity on practically infinite variations of environmental geometry imposes a limitation on the experimental study. Hence we analyze the dependence of grid cell periodicity on the environmental geometry purely from a computational point of view. We use a hierarchical oscillatory network model where velocity inputs are presented to a layer of Head Direction cells, outputs of which are projected to a Path Integration layer. The Lateral Anti-Hebbian Network (LAHN) is used to perform feature extraction from the Path Integration neurons thereby producing a spectrum of spatial cell responses. We simulated the model in five types of environmental geometries such as: (1) connected environments, (2) convex shapes, (3) concave shapes, (4) regular polygons with varying number of sides, and (5) transforming environment. Simulation results point to a greater function for grid cells than what was believed hitherto. Grid cells in the model encode not just the local position but also more global information like the shape of the environment. Furthermore, the model is able to capture the invariant attributes of the physical space ingrained in its LAHN layer, thereby revealing its ability to classify an environment using this information. The proposed model is interesting not only because it is able to capture the experimental results but, more importantly, it is able to make many important predictions on the effect of the environmental geometry on the grid cell periodicity and suggesting the possibility of grid cells encoding the invariant properties of an environment.