Information Technology Reference
In-Depth Information
Chapter 12
Parametric Modeling Analysis of Optical
Imaging Data on Neuronal Activities
in the Brain
Shigeharu Kawai, Yositaka Oku, Yasumasa Okada, Fumikazu Miwakeichi,
Makio Ishiguro, and Yoshiyasu Tamura
Abstract
An optical imaging technique using a voltage-sensitive dye (voltage imag-
ing) has been widely applied to the analyses of various brain functions. Because
optical signals in voltage imaging are small and require several kinds of preprocess-
ing, researchers who use voltage imaging often conduct signal averaging of multiple
trials and correction of signals by cutting the noise near the baseline in order to im-
prove the apparent signal-noise ratio. However, a noise cutting threshold level that
is usually set arbitrarily largely affects the analyzed results. Therefore, we aimed to
develop a new method to objectively evaluate optical imaging data on neuronal ac-
tivities. We constructed a parametric model to analyze optical time series data. We
have chosen the respiratory neuronal network in the brainstem as a representative
system to test our method. In our parametric model we assumed an optical signal of
each pixel as the input and the inspiratory motor nerve activity of the spinal cord as
the output. The model consisted of a threshold function and a delay transfer func-
tion. Although it was a simple nonlinear dynamic model, it could provide precise
