TY - GEN
T1 - Testing and Understanding Second-Order Statistics of Spike Patterns Using Spike Shuffling Methods
AU - Bi, Zedong
AU - ZHOU, Changsong
N1 - Funding Information:
Acknowledgments. CZ is partially supported by Hong Kong Baptist University (HKBU) Strategic Development Fund, NSFC-RGC Joint Research Scheme (Grant No. HKUST/NSFC/12-13/01) and NSFC (Grant No. 11275027). ZB is supported by HKBU Faculty of Science.
PY - 2017
Y1 - 2017
N2 - We introduce a framework of spike shuffling methods to test the significance and understand the biological meanings of the second-order statistics of spike patterns recorded in experiments or simulations. In this framework, each method is to evidently alter a specific pattern statistics, leaving the other statistics unchanged. We then use this method to understand the contribution of different second-order statistics to the variance of synaptic changes induced by the spike patterns self-organized by an integrate-and-fire (LIF) neuronal network under STDP and synaptic homeostasis. We find that burstiness/regularity and heterogeneity of cross-correlations are important to determine the variance of synaptic changes under asynchronous states, while heterogeneity of cross-correlations is the main factor to cause the variance of synaptic changes when the network moves into strong synchronous states.
AB - We introduce a framework of spike shuffling methods to test the significance and understand the biological meanings of the second-order statistics of spike patterns recorded in experiments or simulations. In this framework, each method is to evidently alter a specific pattern statistics, leaving the other statistics unchanged. We then use this method to understand the contribution of different second-order statistics to the variance of synaptic changes induced by the spike patterns self-organized by an integrate-and-fire (LIF) neuronal network under STDP and synaptic homeostasis. We find that burstiness/regularity and heterogeneity of cross-correlations are important to determine the variance of synaptic changes under asynchronous states, while heterogeneity of cross-correlations is the main factor to cause the variance of synaptic changes when the network moves into strong synchronous states.
KW - Spike pattern statistics
KW - Spike shuffling methods
UR - http://www.scopus.com/inward/record.url?scp=85035085933&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-70093-9_64
DO - 10.1007/978-3-319-70093-9_64
M3 - Conference proceeding
AN - SCOPUS:85035085933
SN - 9783319700922
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 602
EP - 612
BT - Neural Information Processing - 24th International Conference, ICONIP 2017, Proceedings
A2 - Liu, Derong
A2 - Xie, Shengli
A2 - Li, Yuanqing
A2 - El-Alfy, El-Sayed M.
A2 - Zhao, Dongbin
PB - Springer Verlag
T2 - 24th International Conference on Neural Information Processing, ICONIP 2017
Y2 - 14 November 2017 through 18 November 2017
ER -