Biomedical subjects

Keiji Miura

Publications and source records attributed to Keiji Miura.

4 recordsLinked to original sources

PubMed2006

Organization and structure of hox gene loci in medaka genome and comparison with those of pufferfish and zebrafish genomes.

We isolated BAC clones that cover the entire hox gene loci in the medaka fish Oryzias latipes. The BAC clones were characterized by the Southern hybridization with many hox gene probes isolated in our previous study and by PCR using primers designed for selective amplification of respective hox genes. Then, the BAC clones have been subjected to shotgun sequencing. The results revealed the organization of the entire hox gene loci. Forty-six hox genes in total are encoded in seven clusters as follows: 10 hox genes in Aa cluster; 5 in Ab; 9 in Ba; 4 in Bb; 10 in Ca; 6 in Da; and 2 in Db. Together with the information on the hox gene loci registered in the Fugu genome database and in the Danio genome database, the physical maps of three fish genomes were constructed and compared one another. Not only numbers of hox genes but also the distances between the neighboring hox genes are highly similar between medaka and fugu. As for six clusters, Aa, Ab, Ba, Bb, Ca and Da that are commonly present in the three fishes, only few or no differences were found in each cluster. Thus, the hox gene sets should have been well conserved once they had been established in respective species.

Animals↗

PubMed2006

Estimating spiking irregularities under changing environments.

We considered a gamma distribution of interspike intervals as a statistical model for neuronal spike generation. A gamma distribution is a natural extension of the Poisson process taking the effect of a refractory period into account. The model is specified by two parameters: a time-dependent firing rate and a shape parameter that characterizes spiking irregularities of individual neurons. Because the environment changes over time, observed data are generated from a model with a time-dependent firing rate, which is an unknown function. A statistical model with an unknown function is called a semiparametric model and is generally very difficult to solve. We used a novel method of estimating functions in information geometry to estimate the shape parameter without estimating the unknown function. We obtained an optimal estimating function analytically for the shape parameter independent of the functional form of the firing rate. This estimation is efficient without Fisher information loss and better than maximum likelihood estimation. We suggest a measure of spiking irregularity based on the estimating function, which may be useful for characterizing individual neurons in changing environments.

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PubMed2004

Pulse-coupled resonate-and-fire models.

We analyze two pulse-coupled resonate-and-fire neurons. Numerical simulation reveals that an antiphase state is an attractor of this model. We can analytically explain the stability of antiphase states by means of a return map of firing times, which we propose in this paper. The resultant stability condition turns out to be quite simple. The phase diagram based on our theory shows that there are two types of antiphase states. One of these cannot be seen in coupled integrate-and-fire models and is peculiar to resonate-and-fire models. The results of our theory coincide with those of numerical simulations.

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PubMedDate not supplied

A measure of local variation of inter-spike intervals.

It has been revealed in our recent study that cortical neurons are categorized into distinct types, according to a new measure of the local variation of inter-spike intervals, L(V). In this paper, we obtain values of the local variation L(V) and a conventional coefficient of variation C(V) for a variety of model point processes. While the value of C(V) undergoes large changes by rate fluctuation of the point processes, the value of L(V) does not undergo large changes by rate fluctuation, and is principally determined by the form of intrinsic interval distribution of the original model point process.

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