Brain, music, and non-Poisson renewal processes.
In this paper we show that both music composition and brain function, as revealed by the electroencephalogram (EEG) analysis, are renewal non-Poisson processes living in the nonergodic dominion. To reach this important conclusion we process the data with the minimum spanning tree method, so as to detect significant events, thereby building a sequence of times, which is the time series to analyze. Then we show that in both cases, EEG and music composition, these significant events are the signature of a non-Poisson renewal process. This conclusion is reached using a technique of statistical analysis recently developed by our group, the aging experiment (AE). First, we find that in both cases the distances between two consecutive events are described by nonexponential histograms, thereby proving the non-Poisson nature of these processes. The corresponding survival probabilities Psi(t) are well fitted by stretched exponentials [Psi(t) proportional, variant exp (-(gammat){alpha}) , with 0.5<alpha<1 .] The second step rests on the adoption of AE, which shows that these are renewal processes. We show that the stretched exponential, due to its renewal character, is the emerging tip of an iceberg, whose underwater part has slow tails with an inverse power law structure with power index mu=1+alpha. Adopting the AE procedure we find that both EEG and music composition yield mu<2. On the basis of the recently discovered complexity matching effect, according to which a complex system S with mu{S}<2 responds only to a complex driving signal P with mu{P}< or =mu{S}, we conclude that the results of our analysis may explain the influence of music on the human brain.
Bianco
Simone
S
Center for Nonlinear Science, University of North Texas, P.O. Box 311427, Denton, Texas 76203-1427, USA.
Ignaccolo
Massimiliano
M
Rider
Mark S
MS
Ross
Mary J
MJ
Winsor
Phil
P
Grigolini
Paolo
P
D001154:Art; D001307:Auditory Perception; D001921:Brain / Q000502:physiology*; D004569:Electroencephalography; D006801:Humans; D008959:Models, Neurological; D009146:Music; D013269:Stochastic Processes