Title :
Estimating inputs and an internal neuronal parameter from a single spike train
Author :
Shinomoto, Shigeru ; Kim, Heonhwan
Author_Institution :
Dept. of Phys., Kyoto Univ., Kyoto, Japan
Abstract :
Because neurons are integrating input signals and translating them into timed output spikes, examining spike timing may reveal information about inputs, such as population activities of excitatory and inhibitory presynaptic neurons. Here we construct a state-space method for estimating not only such extrinsic parameters, but also an intrinsic neuronal parameter such as the membrane time constant from a single spike train.
Keywords :
biomembranes; brain; neural nets; neurophysiology; excitatory presynaptic neuron; extrinsic parameter; inhibitory presynaptic neuron; integrating input signal; internal neuronal parameter; intrinsic neuronal parameter; membrane time constant; population activity; single spike train; spike timing; state-space method; timed output spike; Biological system modeling; Estimation; Fluctuations; Neurons; Sociology; State-space methods; Statistics;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE
Conference_Location :
Osaka
DOI :
10.1109/EMBC.2013.6611193