We have developed a novel method to estimate the fine retinotopic map of the primary visual cortex from the intrinsic optical signal ( IOS ) induced by visual stimulation in an awake mouse. Unlike methods employing anesthesia, in order to reduce the burden on the animal, shortening the experimental time is an im-portant requirement. During the awake state, eye movement, pupil diameter fluctuations, and brain background activity are present. Occurrence of eye movement blurs the retinal image. Excluding data under such circums-tances in the synchronous average method is essential in conventional methods. In order to solve these problems, we focused on the strong correlation between the pupil diameter and the global signal ( GS ) of IOS and introduced a process to remove GS from IOS in preprocessing. This process improved the SN ratio of visual response in a single trial. We assumed that the response from the region of interest ( ROI ) of the cortex is described by the product sum of the retinal image and the receptive field function expressing the projection from the retina to the cortex. In this model, unlike the synchronous average method, the influence of eye movement can be expressed by shifting the retinal image. Therefore, all the response data can be used to estimate parameters, irrespective of the stimulation location or eye position. Additionally, in this method, the spatial resolution does not depend on the spatial resolution of the stimulation spot. The parameters of the receptive field function can be estimated using the nonlinear least squares method. By applying this method to real data, we obtained a retinotopic map with much higher spatial resolution than that obtained by conventional methods. Interestingly, structures similar to higher brain regions such as secondary visual cortex, which were previously observed only using invasive methods such as calcium imaging and electrophysiological method with electrode insertion in the mouse brain, were also visualized. These results demonstrate the usefulness of the proposed method with high spatial resolution.
Nowadays, a variety of vital sensing devices have been able to be easily and inexpensively connected to any smart phones by means of wireless technologies. Typical examples of such wireless tools are Bluetooth, Zigbee, WiFi and WiSUN, which are all based on the IEEE 802 standard families. This paper shows the current status of the IEEE 802 standardization activities related to the support of everyday healthcare and medicine, such as the working groups of the IEEE 802.15.1, 802.11, and 802.15.4g. In addition, it introduces the IEEE 802.15.6 standards for supporting highly reliable wireless communications, which is required for providing medical and healthcare services.
