Yutaka Sakai, Shuji Yoshizawa Saitama Univ., Japan Saitama Univ., Japan Hiroshi Ohno Tamagawa Univ., Japan Tamagawa Univ., Japan Interpretation of Inter-Spike.

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Presentation transcript:

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

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

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

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

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

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

Dimensionless Parameters for Interpretaion Staying Time Scale Staying Time Balance

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

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

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

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

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