An ensemble with the Chinese pentatonic scale using electroencephalogram from both hemispheres

To listen to brain activity as a piece of music,we previously proposed scale-free brainwave music（SFBM）technology,which translated the scalp electroencephalogram（EEG）into musical notes according to the power law of both the EEG and music.In this study,the methodology was further extended to ensemble music on two channels from the two hemispheres.EEG data from two channels symmetrically located on the left and right hemispheres were translated into MIDI sequences by SFBM,and the EEG parameters modulated the pitch,duration and volume of each note.Then,the two sequences were filtered into an ensemble with two voices：the pentatonic scale（traditional Chinese music）or the heptatonic scale（standard Western music）.We demonstrated differences in harmony between the two scales generated at different sleep stages,with the pentatonic scale being more harmonious.The harmony intervals of this brain ensemble at various sleep stages followed the power law.Compared with the heptatonic scale,it was easier to distinguish the different stages using the pentatonic scale.These results suggested that the hemispheric ensemble can represent brain activity by variations in pitch,tempo and harmony.The ensemble with the pentatonic scale sounds more consonant,and partially reflects the relations of the two hemispheres.This can be used to distinguish the different states of brain activity and provide a new perspective on EEG analysis.

The allometric propagation of COVID-19 is explained by human travel

We analyzed the number of cumulative positive cases of COVID-19 as a function of time in countries around the World.We tracked the increase in cases from the onset of the pandemic in each region for up to 150 days.We found that in 81 out of 146 regions the trajectory was described with a power-law function for up to 30 days.We also detected scale-free properties in the majority of sub-regions in Australia,Canada,China,and the United States(US).We developed an allometric model that was capable of fitting the initial phase of the pandemic and was the best predictor for the propagation of the illness for up to 100 days.We then determined that the power-law COVID-19 exponent correlated with measurements of human mobility.The COVID-19 exponent correlated with the magnitude of air passengers per country.This correlation persisted when we analyzed the number of air passengers per US states,and even per US metropolitan areas.Furthermore,the COVID19 exponent correlated with the number of vehicle miles traveled in the US.Together,air and vehicular travel explained 70%of the variability of the COVID-19 exponent.Taken together,our results suggest that the scale-free propagation of the virus is present at multiple geographical scales and is correlated with human mobility.We conclude that models of disease transmission should integrate scale-free dynamics as part of the modeling strategy and not only as an emergent phenomenological property.