Biomedical subjects

Tsuyoshi Horiguchi

Publications and source records attributed to Tsuyoshi Horiguchi.

4 recordsLinked to original sources

PubMed2005

Generation of complex bipartite graphs by using a preferential rewiring process.

It is important in computer science, sociology, and so on to investigate complex bipartite graphs from a viewpoint of statistical physics. We propose a model to generate complex bipartite graphs without growing; the bipartite graphs are assumed to have two sets of the fixed numbers of nodes and a fixed number of edges between nodes belonging to different sets of nodes. In this model, essential ingredients are a preferential rewiring process and a fitness distribution function. By using the preferential rewiring process, we confirm that a bipartite graph reaches a stationary state after a sufficiently long time has passed. We find that the obtained bipartite graph has a scale-free-like property when a suitable fitness distribution is used. It turns out that a condensation of edges takes place in the cases of certain fitness distributions.

Journal Article↗

PubMed2004

Neural network model of selective visual attention using Hodgkin-Huxley equation.

We propose a mathematical model of selective visual attention using a two-layered neural network with neurons described by the Hodgkin-Huxley equation in order to investigate part of the assumption proposed by Desimone and Duncan. The neural network consists of a layer of hippocampal formation and of visual cortex. A frequency of firing and a firing time for each neuron and also a correlation of the firing times between neurons are calculated numerically to clarify an attention state, a nonattention state, and an attention shift. We find that synchronous phenomena occur not only for the frequency but also for the firing time between the neurons in the hippocampal formation and those in a part of the visual cortex in our model. It also turns out that the attention shift is performed quickly in our model.

Action Potentials↗

PubMed2004

Models of MT and MST areas using wake-sleep algorithm.

We present two-layered neural network models with Q (> or =2)-states neurons for a system with middle temporal (MT) neurons and medial superior temporal (MST) neurons by using a wake-sleep algorithm proposed by Hinton et al.; we notice that the wake-sleep algorithm consists of local learning rules. We first investigate a model with binary neurons for response properties of the MST neurons to optical flows as for various types of motion. We next extend the model with binary neurons to a model with Q (> or =3)-states neurons and investigate the response properties of the MST neurons for various values of Q (> or =3). We obtain better response properties for the model with Q (> or =3)-states neurons than for the one with binary neurons.

Algorithms↗

PubMed2002

Solvable Markov random field model in color image restoration.

We propose a scheme for image restoration of full color images by means of a solvable probabilistic model in the red-green-blue space. A special case of our solvable probabilistic model is equivalent to a multicomponent Gaussian model in the statistical mechanics. Exact closed expressions of the evidence and the expectation value of intensity at each pixel in our solvable probabilistic model can be obtained by using multidimensional Gaussian integral formulas and a discrete Fourier transform. In the present paper, the degradation process is assumed to be an additive white Gaussian noise. Hyperparameters are determined so as to maximize the evidence that is expressed in terms of the partition function in our solvable probabilistic model. This work is a pioneering work for the Bayesian approach to the color image restoration by means of the statistical-mechanical technique.

Journal Article↗