Neural activation while perceiving biological motion in dynamic facial expressions and point-light body action animations

BACKGROUND： The interpretation of non-verbal social signals relies heavily on the ability to perceive biological motion. The posterior superior temporal sulcus is an important part of a network involved in biological motion processing. However, the underlying functional organization remains poorly understood. Several studies have suggested topographical representation of motion from different body parts within this region. However, other studies have shown that the posterior superior temporal sulcus responds equally to any body part. OBJECTIVE： Through the use of functional magnetic resonance imaging, the effects of socially relevant biological motion stimuli to activate a specific cortical area within posterior superior temporal sulcus, even if different body parts are involved in motion, will be analyzed. DESIGN, TIME AND SETTING： A functional magnetic resonance imaging, block-design was performed at the Magnetic Resonance Imaging, Surgical Medical Investigation Center, Havana, Cuba between 2004 and 2005. PARTICIPANTS： Thirteen healthy volunteers, from 19 to 55 years of age and compris!ng eight males and five females, were included in the study. METHODS： A conjunction analysis of responses to natural, dynamic, fearful, facial expressions and point-light, body-motion animations. MAIN OUTCOME MEASURES： The corresponding functionally specialized areas, as well as neural areas significant for both types of stimuli, were identified. RESULTS： One region within the posterior superior temporal sulcus of the right hemisphere was equally activated by facial and body complex motion. CONCLUSION： A site of common neural activity existed within the posterior superior temporal sulcus, which was not specific to a biological motion type. In addition, the activity was not related to a topographically organized body-part map, which suggested high-level visual representation of biological motion in this region.

BGMM： A Body Gauss-Markov Based Mobility Model for Body Area Networks

Existing mobility models have limitations in their ability to simulate the movement of Wireless Body Area Network（WBAN） since body nodes do not exactly follow either classic mobility models or human contact distributions. In this paper, we propose a new mobility model called Body Gauss–Markov Mobility（BGMM） model,which is oriented specially to WBAN. First, we present the random Gauss-Markov mobility model as the most suitable theoretical basis for developing our new model, as its movement pattern can reveal real human body movements. Next, we examine the transfer of human movement states and derive a simplified mathematical Human Mobility Model（HMM）. We then construct the BGMM model by combining the RGMM and HMM models. Finally,we simulate the traces of the new mobility model. We use four direct metrics in our proposed mobility model to evaluate its performance. The simulation results show that the proposed BGMM model performs with respect to the direct mobility metrics and can effectively represent a general WBAN-nodes movement pattern.

A graphene rheostat for highly durable and stretchable strain sensor

Strain sensors for human health monitoring are of paramount importance in wearable medical diagnostics and personal health monitoring.Despite extensive studies,strain sensors with both high durability and stretchability are still desired,particularly with the stability for different environmental conditions.Here,we report a series of strain sensors possessing the graphene network with a high density of intermittent physical interconnections,which produces the relative resistance change by varying the overlap area between the neighboring graphene sheets under stretching and releasing,analogous to the slide rheostat working in electronics.Our in-situ transmission electron microscope observation reveals the full recoverability of the structure from large deformation upon unloading for ensuring the exceptional cycle stability of our material on monitoring full-range body movements.The stable response is also demonstrated over wide temperature range and frequency range,because the peculiar dynamic structure can be maintained through the self-adjustment to the thermal expansion of the bulk material.Based on the working mechanism of graphene“slide rheostat,”the sensing properties of the strain sensor are tailored by tuning the graphene network structure with different mass densities using different concentrations of graphene oxide dispersion,while the stretchability and sensitivity can be separately optimized for different application requirements.