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Yutaka Sakai, Shuji Yoshizawa Saitama Univ., Japan Saitama Univ., Japan Hiroshi Ohno Tamagawa Univ., Japan Tamagawa Univ., Japan Interpretation of Inter-Spike Interval statistics through the Markov Switching Poisson Process

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Inter-Spike Interval (ISI: T) statistics (CV, SK, COR) ~ dimensionless Coefficient of Variation Skewness coefficient (asymmetry) Correlation coefficient of consecutive ISIs ~ Irregularity ~ long silence ~ serial correlation

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PS area & MT area （ Funahashi, 1996 ） （ Ohno, 1999 ） Random Sequence : Poisson Process (1, 2, 0) What do the combinations mean?

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What does a combination (CV,SK,COR) tell us? Simple spike event process (CV,SK,COR) reproduce model parameters projection

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Active state Random spiking at Markov Switching Poisson Process Switch state at each spike event Inactive state Random spiking at

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Markov Switching Poisson Process Active state Active state Inactive state Inactive state Mean Interval (ISI) Staying time scale Parameters (4 time scales) Interval (ISI) statistics 1 to 1

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Dimensionless Parameters for Interpretaion Staying Time Scale Staying Time Balance

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section COR=-0.1section COR=0 Projection to the Markov Switching section COR=0.1section COR=0.2 Model ParametersISI statistics

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Sample data PS area of awake monkey Delay response task (Funahashi 1996) MT area of anesthetized monkey Random dots flowing (Ohno 1999)

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Sample Data (CV,SK,COR)s … for Interpretation PS typical (SK: Large) PS typical (COR: Large) MT all

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Sequence Properties … trough the Markov Switching Staying Time Scale inactiveactive Staying Time Balance Large COR : balance ~ inactiveLarge SK/CV: balance ~ activeMT data

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Summary SK/CV large or COR large long staying time SK/CV large stay longer in active SK/CV large stay longer in active SK/CV small stay longer in inactive SK/CV small stay longer in inactive

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