Modeling Long-term Spike Frequency Adaptation in SA-I Afferent Neurons Using an Izhikevich-based Biological Neuron Model

To develop a biomimetic artificial tactile sensing system capable of detecting sustained mechanical touch, we propose a novel biological neuron model (BNM) for slowly adapting type I (SA-I) afferent neurons. The proposed BNM is designed by modifying the Izhikevich model to incorporate long-term spike frequency adaptation. Adjusting the parameters renders the Izhikevich model describing various neuronal firing patterns. We also search for optimal parameter values for the proposed BNM to describe firing patterns of biological SA-I afferent neurons in response to sustained pressure longer than 1-second. We obtain the firing data of SA-I afferent neurons for six different mechanical pressure ranging from 0.1 mN to 300 mN from the ex-vivo experiment on SA-I afferent neurons in rodents. Upon finding the optimal parameters, we generate spike trains using the proposed BNM and compare the resulting spike trains to those of biological SA-I afferent neurons using the spike distance metrics. We verify that the proposed BNM can generate spike trains showing long-term adaptation, which is not achievable by other conventional models. Our new model may offer an essential function to artificial tactile sensing technology to perceive sustained mechanical touch.

Genetic diversity of nucleocapsid genes of recent porcine epidemic diarrhea viruses isolated in Korea

Porcine epidemic diarrhea virus (PEDV), a porcine enteropathogenic coronavirus, causes lethal watery diarrhea in piglets, resulting in large economic losses because of high mortality. In November 2013, PEDV reemerged in Korea, and these outbreaks have since continuously occurred. In the present study, we determined the full-length nucleocapsid (N) gene sequences of three Korean PEDV field isolates collected in 2014-2015. Sequence and phylogenetic analysis of N genes revealed that recent prevalent Korean PEDV isolates were very closely related to the US PEDV isolates in 2013. Interestingly, the phylogenetic tree based on the nucleotide sequencing of the PEDV N gene was similar to the tree topology of the PEDV complete genomes. Therefore, our data provide a better understanding of the genetic diversity and contribute to the accurate diagnosis and development of vaccines against PEDV.