Biomedical subjects

Hideyuki Câteau

Publications and source records attributed to Hideyuki Câteau.

5 recordsLinked to original sources

PubMed2006

Relation between single neuron and population spiking statistics and effects on network activity.

To simplify theoretical analyses of neural networks, individual neurons are often modeled as Poisson processes. An implicit assumption is that even if the spiking activity of each neuron is non-Poissonian, the composite activity obtained by summing many spike trains limits to a Poisson process. Here, we show analytically and through simulations that this assumption is invalid. Moreover, we show with Fokker-Planck equations that the behavior of feedforward networks is reproduced accurately only if the tendency of neurons to fire periodically is incorporated by using colored noise whose autocorrelation has a negative component.

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PubMed2003

A stochastic method to predict the consequence of arbitrary forms of spike-timing-dependent plasticity.

Synapses in various neural preparations exhibit spike-timing-dependent plasticity (STDP) with a variety of learning window functions. The window functions determine the magnitude and the polarity of synaptic change according to the time difference of pre- and postsynaptic spikes. Numerical experiments revealed that STDP learning with a single-exponential window function resulted in a bimodal distribution of synaptic conductances as a consequence of competition between synapses. A slightly modified window function, however, resulted in a unimodal distribution rather than a bimodal distribution. Since various window functions have been observed in neural preparations, we develop a rigorous mathematical method to calculate the conductance distribution for any given window function. Our method is based on the Fokker-Planck equation to determine the conductance distribution and on the Ornstein-Uhlenbeck process to characterize the membrane potential fluctuations. Demonstrating that our method reproduces the known quantitative results of STDP learning, we apply the method to the type of STDP learning found recently in the CA1 region of the rat hippocampus. We find that this learning can result in nearly optimized competition between synapses. Meanwhile, we find that the type of STDP learning found in the cerebellum-like structure of electric fish can result in all-or-none synapses: either all the synaptic conductances are maximized, or none of them becomes significantly large. Our method also determines the window function that optimizes synaptic competition.

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PubMed2002

Kinetic analysis of multisite phosphorylation using analytic solutions to Michaelis-Menten equations.

Phosphorylation-induced expression or modulation of a functional protein is a common signal in living cells. Many functional proteins are phosphorylated at multiple sites and it is frequently observed that phosphorylation at one site enhances or suppresses phosphorylation at another site. Therefore, characterizing such cooperative phosphorylation is important. In this study, we determine a temporal progress curve of multisite phosphorylation by analytically integrating the Michaelis-Menten equations in time. Using this theoretical progress curve, we derive the useful criterion that an intersection of two progress curves implies the presence of cooperativity. Experiments generally yield noisy progress curves. We fit the theoretical progress curves to noisy progress curves containing 4% Gaussian noise in order to determine the kinetics of the phosphorylation. This fitting correctly identifies the sites involved in cooperative phosphorylation.

Animals↗

PubMed2002

Two-state membrane potential transitions of striatal spiny neurons as evidenced by numerical simulations and electrophysiological recordings in awake monkeys.

Spontaneous membrane potential fluctuations of striatal spiny projection neurons play a crucial role in their spike generation. Previous intracellular recording studies in anesthetized rats have shown that the membrane potential of striatal spiny neurons shifts between the depolarized "up" state and the hyperpolarized "down" state. Here we report evidence for the occurrence of such two-state membrane potential transitions by numerical simulations and electrophysiological recordings in awake monkeys. Data from our simulations of a striatal spiny neuron model demonstrated that spike latency histograms of the model neuron displayed two separate (i.e., early and late) peaks in response to excitatory cortical input, corresponding to neuronal activity in the up or down state, respectively. Then, we addressed experimentally whether the latency distribution of cortically induced spike firing of striatal spiny neurons might show dual peaks. Striatal neuron activity was extracellularly recorded in response to electrical stimulation in the two cortical motor-related areas, the primary motor cortex and the supplementary motor area, of awake monkeys. Analysis of spike latency histograms has defined that striatal spiny neurons typically exhibit two temporally distinct peaks, as obtained by the numerical simulations. Thus, the membrane potential shifts between the up and down states appear to occur in striatal spiny neurons of the behaving animal.

Animals↗

PubMed2002

Self-organization of memory activity through spike-timing-dependent plasticity.

We studied the self-organization of memory-related activity through spike-timing-dependent plasticity (STDP). Relatively short time windows (approximately 10 ms) for the plasticity rule give rise to asynchronous persistent activity of low rates (20-30 Hz), which is typically observed in delay periods of working memory task. We demonstrate some network level effects on the activity regulation that cannot be addressed in single-neuron studies. For longer time windows (approximately 20 ms), the layered cell assemblies that propagate synchronized spikes (synfire chain) are self-organized. Synchronous spike propagation was suggested to underlie the precisely timed spikes in the monkey prefrontal cortex. The present results suggest that the two networks for sustained activity are different realizations of the same principle for synaptic wiring.

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