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Research has documented the influence of ALS patients families’ attitudes on patients’ decision to accept or reject TIV, a treatment that in many cases will allow them to live long enough to experience locked-in syndrome ; under Japanese law the use of a ventilator cannot be terminated once it is essential to a patient’s survival, so to choose TIV means to choose the possibility of entering a locked-in state. Previous studies have not, however, elucidated the changes in family members’ attitudes (...) that take place after they receive pertinent information about the social systems and services available to them. This study aims to fill this gap by collecting and analyzing patients’ and family members’ narratives. In Japan, about 30% of ALS patients utilize TIV. This rate is much higher than in most other developed countries. Patients’ narratives illuminate the psychological and especially the contextual factors of their decision-making. Many Japanese patients who currently use a ventilator say that their family members encouraged them to prolong their lives through ventilation. These family members have done so because patients are able to use long-term ventilation for only ¥1000 per month, and can also access the latest communication devices and round the clock caregiver services in their homes at very low cost. Japanese caregivers who are supported by social systems and services including communication assistance, empowering factors such as patients’ associations, care provided by people outside the patient’s family, and a public nursing care system are able to encourage patients to decide to use longterm ventilation. (shrink)

In recent years, neural networks have attracted much attention in the machine learning and the deep learning technologies. Bio-inspired functions and intelligence are also expected to process efficiently and improve existing technologies. In the visual pathway, the prominent features consist of nonlinear characteristics of squaring and rectification functions observed in the retinal and visual cortex networks, respectively. Further, adaptation is an important feature to activate the biological systems, efficiently. Recently, to overcome short-comings of the deep learning techniques, orthogonality for the (...) weights in the networks has been developed for the signal propagation and the efficient optimization of the learning. In this paper, bio-inspired asymmetric networks with nonlinear characteristics are proposed, which are derived from the retinal networks in the biological visual pathway. The asymmetric network proposed here was verified to detect the movement of the object, efficiently in our previous studies. This paper shows a new characteristic of the adaptive orthogonality in the asymmetric networks. First, it is shown that the asymmetric network with nonlinear characteristics is effective for generating orthogonality. Second, the proposed asymmetric network with Gabor filters is compared with the conventional energy model from the point of the orthogonality characteristics. Finally, the asymmetric networks with nonlinear characteristics can generate the extended orthogonal bases in independent subspaces, which are useful for classification and efficient learning. (shrink)

Humans can pronounce a nonword. Some researchers have interpreted this behavior as requiring a sequential mechanism by which a grapheme-phoneme correspondence rule is applied to each grapheme in turn. However, several parallel-distributed processing models in English have simulated human nonword reading accuracy without a sequential mechanism. Interestingly, the Japanese psycholinguistic literature went partly in the same direction, but it has since concluded that a sequential parsing mechanism is required to reproduce human nonword reading accuracy. In this study, by manipulating the (...) list composition, we demonstrated that past psycholinguistic studies in Japanese have overestimated human nonword reading accuracy. When the more fairly reevaluated human performance was targeted, a newly implemented Japanese PDP model simulated the target accuracy as well as the error patterns. These findings suggest that PDP models are a more parsimonious way of explaining reading across various languages. (shrink)