Quickest detection of state-transition in point processes: Application to neuronal activity

IFAC Proceedings Volumes (IFAC-PapersOnline)

Volumn 44, Issue 1 PART 1, 2011, Pages 10021-10026

  Sarma, Sridevi V ^a   Santaniello, Sabato ^a  

^a Johns Hopkins University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORKS; COST FUNCTIONS; DYNAMIC PROGRAMMING; NEURONS;

BAYESIAN FORMULATION; DETECTION DELAYS; GEOMETRIC DISTRIBUTION; NEURONAL ACTIVITIES; PARKINSON'S DISEASE; QUICKEST DETECTION; STATE TRANSITIONS; SUBTHALAMIC NUCLEUS;

PROBABILITY DISTRIBUTIONS;

EID: 83455225113     PISSN: 14746670     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3182/20110828-6-IT-1002.03408     Document Type: Conference Paper

References (27)

1. Andreou, E. and E. Ghysels (2004). The impact of sampling frequency and volatility estimators on change-point tests. J. Fin. Econometrics, vol. 2, pp. 290-318.
2. Basseville, M., and I.V. Nikiforov (1993). Detection of Abrupt Changes. Theory and Application. Prentice-Hall, Englewood Cliffs, NJ.
3. Bergman, H., T. Wichmann, B. Karmon and M.R. DeLong(1994). The primate sumbthalamic nucleus. II. Neuronal activity in the MPTP model of Parkinsonism. J. Neurophysiol., vol. 72, pp. 507-520.
4. Bertsekas, D.P. (2005). Dynamic Programming and Optimal Control. vol.I (3rd ed.). Athena Scientific, Belmont, MA.
5. Brodsky, B.E., and B.S. Darkhovsky (1992). Nonparametric Methods in Change-Point Problems. Kluwer, Boston, MA.
6. Brown, E.N., R. Barbieri, U.T. Eden and L.M. Frank (2003). Likelihood methods for neural data analysis. In:Computational Neuroscience: A Comprehensive Approach (J. Feng (Ed)), pp. 253-286. CRC, London, UK.
7. Crow, R.W. and S.C. Schwartz (1996). Quickest detection for sequential decentralized decision systems. IEEE Aero. Elec. Sys., vol. 32, pp. 267-283.
8. Daley, D. and D. Vere-Jones (2003). An Introduction to the Theory of Point Processes (2nd ed.). Springer-Verlag, New York, NY.
9. Elliott, R.J., L. Aggoun and J.B. Moore (1995). Hidden Markov Models. Estimation and Control. Springer, New York, NY.
10. Gale, J.T., D.C. Shields, F.A. Jain, R. Amirnovin and E.N. Eskandar (2009). Subthalamic nucleus discharge patterns during movement in the normal monkey and Parkinsonian patient. Brain Res., vol. 1260, pp. 15-23.
11. Kass, R.E. and V. Ventura (2001). A spike-train probability model. Neural Comput., vol. 13, pp. 1713-1720.
12. Lorden, G. (1971). Procedures for reacting to a change in distribution. Ann. Math. Statist., vol. 42, pp. 1897-1908.
13. McCullagh, P. and J.A. Nelder (1990). Generalized Linear Models (2nd ed.). CRC, Boca Raton, FL.
14. Mormann, F., R.G. Andrzejak, C.E. Elger and K. Lehnertz (2007). Seizure prediction: the long and winding road. Brain, vol. 130, pp. 313-333.
15. Papoulis, A. and S. Unnikrishna Pilai (2002). Probability, Random Variables, and Stochastic Processes (4th ed.). McGraw-Hill, New York, NY.
16. Pelkowitz, L. (1987). The general discrete time disorder problem. Stochastics, vol. 20, pp. 89-110.
17. Poor, H.V. (1998). Quickest detection with exponential penalty for delay. Ann. Statist., vol. 26, pp. 2179-2205.
18. Poor, H.V. and O. Hadjiliadis (2008). Quickest Detection. Cambridge University Press, Cambridge, UK.
19. Raghavan, V. and V.V. Veeravalli (2010). Quickest change detection of a Markov process across a sensor array. IEEE Trans. Inf. Theory, vol. 56, pp. 1961-1981.
20. Sarma, S.V., U.T. Eden, M.L. Cheng, Z.M. Williams, R. Hu, E. Eskandar and E.N. Brown (2010). Using point process models to compare neural spiking activity in the subthalamic nucleus of Parkinson's patients and a healthy primate. IEEE Trans. Biomed Eng., vol. 57, pp. 1297-1305.
21. Shiryayev, A.N. (1963). On optimum methods in quickest detection problems. Theory Probab. Appl., vol. 8, pp. 22-46.
22. Snyder, D.L. and M.I. Miller (1991). Random Point Processes in Time and Space. Springer, New York, NY.
23. Teneketzis, D. and P. Varaiya (1984). The decentralized quickest detection problem. IEEE Trans. Aut. Control, vol. 29, pp. 641-644.
24. Trivedi, S., and R. Chandramouli (2005). Secret key estimation in sequential steganography. IEEE Trans. Signal Process., vol. 53, pp. 746-757.
25. Wetherhill, G.B., and D.W. Brown (1991). Statistical Process Control. Chapman and Hall, London, UK.
26. Williams, Z.M., J.S. Neimat, G.R. Cosgrove and E.N. Eskandar (2005). Timing and direction selectivity of subthalamic and pallidal neurons in patients with Parkinson disease. Exp. Brain Res., vol. 162, pp. 407-416.
27. Yu, A.J. (2007). Optimal Change-Detection and Spiking Neurons. Advances in Neural Information Processing Systems, vol. 19, pp. 1545-1552.