Randomly connected neural networks displaying 1/f spectra
Hiroki Suyari, Yoshinobu Kamitani, Ikuo Matsuba · 2000
It is known that electroencephalogram (EEG) is broadly scale-invariant over several orders of frequencies. Applying the renormalization group method to the neural network model, we obtain the self-similar solution from which the scaling exponent -1 of the spectrum fall-off. This paper permits one to study the self-similar behavior and helps in understanding the basic ingredients underlying 1/f spectra of EEG.