A model of path integration and representation of spatial context in the retrosplenial cortex.

Inspired by recent biological experiments, we simulate animals moving in different environments (open space, spiral mazes and on a treadmill) to test the performances of a simple model of the retrosplenial cortex (RSC) acting as a path integration (PI) and as a categorization mechanism. The connection between the hippocampus, RSC and the entorhinal cortex is revealed through a novel perspective. We suppose that the path integration is performed by the information coming from RSC. Grid cells in the entorhinal cortex then can be built as the result of a modulo projection of RSC activity. In our model, PI is performed by a 1D field of neurons acting as a simple low-pass filter of head direction (HD) cells modulated by the linear velocity of the animal. Our paper focuses on the constraints on the HD cells shape for a good approximation of PI. Recording of neurons on our 1D PI field shows these neurons would not be intuitively interpreted as performing PI. Using inputs coming from a narrow neighbouring projection of our PI field creates place cell-like activities in the RSC when the mouse runs on the treadmill. This can be the result of local self-organizing maps representing blobs of neurons in the RSC (e.g. cortical columns). Other simulations show that accessing the whole PI field would induce place cells whatever the environment is. Since this property is not observed, we conclude that the categorization neurons in the RSC should have access to only a small fraction of the PI field.

Robust control of a silicone soft robot using neural networks.

This paper deals with the robust controller design problem to regulate the position of a soft robot with elastic behavior, driven by 4 cable actuators. In this work, we first used an artificial neural network to approximate the relation between these actuators and the controlled position of the soft robot, based on which two types of robust controllers (type of integral and sliding mode) are proposed. The effectiveness and the robustness of the proposed controllers have been analyzed both for the constant and the time-varying disturbances. The performances (precision, convergence speed and robustness) of the proposed method have been validated via different experimental tests.

miR-34b attenuates trauma-induced anxiety-like behavior by targeting CRHR1.

Exposure to trauma is a potential contributor to anxiety; however, the molecular mechanisms responsible for trauma-induced anxiety require further clarification. In this study, in an aim to explore these mechanisms, we observed the changes in the hypothalamic pituitary adrenal (HPA) axis using a radioimmunoassay and the changes in anxiety-like behavior using the open field test and elevated plus maze test in a rat model following intervention with NBI­27914, a specific corticotropin­releasing hormone receptor 1 (CRHR1) antagonist. CRHR1 was found to be involved in trauma­induced anxiety. We then applied bioinformatic analysis to screen microRNAs (miRNAs or miRs) that target CRHR1, and miR­34b was determined to negatively regulate CRHR1 mRNA in primary hypothalamic neurons. The overexpression of miR­34b in the paraventricular nucleus (PVN) by a miRNA agomir using a drug delivery system decreased the hyperactivity of the HPA axis and anxiety­like behavior. Overall, the involvement of the HPA axis in trauma­induced anxiety was demonstrated, and trauma-induced anxiety was attenuated by decreasing the hyperactivity of the HPA axis via miR­34b by targeting CRHR1.