Koji Kurata | PubMed Health

PubMed2002

Acceleration effect of coupled oscillator systems.

We have developed a curved isochron clock (CIC) by modifying the radial isochron clock to provide a clean example of the acceleration (deceleration) effect. By analyzing a two-body system of coupled CICs, we determined that an unbalanced mutual interaction caused by curved isochron sets is the minimum mechanism needed for generating the acceleration (deceleration) effect in coupled oscillator systems. From this we can see that the Sakaguchi and Kuramoto (SK) model, which is a class of nonfrustrated mean field model, has an acceleration (deceleration) effect mechanism. To study frustrated coupled oscillator systems, we extended the SK model to two oscillator associative memory models, one with symmetric and the other with asymmetric dilution of coupling, which also have the minimum mechanism of the acceleration (deceleration) effect. We theoretically found that the Onsager reaction term (ORT), which is unique to frustrated systems, plays an important role in the acceleration (deceleration) effect. These two models are ideal for evaluating the effect of the ORT because, with the exception of the ORT, they have the same order parameter equations. We found that the two models have identical macroscopic properties, except for the acceleration effect caused by the ORT. By comparing the results of the two models, we can extract the effect of the ORT from only the rotation speeds of the oscillators.

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Self-organization of globally continuous and locally distributed information representation.

A number of findings suggest that the preferences of neighboring neurons in the inferior temporal (IT) cortex of macaque monkeys tend to be similar. However, a recent study reports convincingly that the preferences of neighboring neurons actually differ. These findings seem contradictory. To explain this conflict, we propose a new view of information representation in the IT cortex. This view takes into account sparse and local neuronal excitation. Since the excitation is sparse, information regarding visual objects seems to be encoded in a distributed manner. The local excitation of neurons coincides with the classical notion of a column structure. Our model consists of input layer and output layer. The main difference from conventional models is that the output layer has local and random intra-layer connections. In this paper, we adopt two rings embedded in three-dimensional space as an input signal space, and examine how resultant information representation depends on the distance between two rings that is denoted as D. We show that there exists critical value for the distance Dc. When D > Dc the output layer becomes able to form the column structure, this model can obtain the distributed representation within the column. While the output layer acquires the conventional information representation observed in the V1 cortex when D < Dc. Moreover, we consider the origin of the difference between information representation of the V1 cortex and that of the IT cortex. Our finding suggests that the difference in the information representations between the V1 and the IT cortices could be caused by difference between the input space structures.

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