Kantaro Fujiwara

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Cortical neurons in vivo generate highly irregular spike sequences. Recently, it was experimentally found that the local variation of interspike intervals, LV, is nearly constant for every spike sequence for the same neurons. On the contrary, the coefficient of variation, CV, varies over different spike sequences. Here, we first show that these(More)
Irregular spike sequences of the cerebral cortex in vivo have been observed in numerous previous studies. These spike sequences generally differ from an entirely random sequence, and exhibit temporal correlations. There are at least two possible sources producing the temporal correlations: (1) temporal correlations of the incoming synaptic inputs; (2) a(More)
In the human brain, billions of neurons construct a neural network via synaptic connections. Neuronal excitation and inhibition are transmitted to other neurons through synapses via neurotransmitters. Dopamine is one of these neurotransmitters that plays a number of important roles. There are a variety of rhythms in the brain, such as alpha rhythm, beta(More)
Firing patterns of neurons are highly variable from trial to trial, even when we record a well-specified neuron exposed to identical stimuli under the same experimental conditions. The trial-to-trial variability of neuronal spike trains may represent some sort of information and provide important indications about neuronal properties. We propose a new(More)
Many stochastic systems require multiple trials to estimate their time-varying statistics. Time-varying statistics are often estimated by employing a time window of a certain length over trials. However, no standardized method exists for estimating time-varying statistics. In this paper, we propose an analysis method for measuring time-varying statistics(More)
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