  Principal Investigator: Apostolos P. Georgopoulos
Co-Investigator: Roger Dumas
Sonification: musical analysis of brain signals:
Multi-channel to multi-dimensional
The study involves the production and presentation of multi-channel audio displays (sonifications) which present MEG time-stream data in a variety of intuitive formats. Sound is a multi-dimensional array and an ideal medium for the portrayal of many data-streams in time. Using many different sound parameters, we hope to design an optimum sonification of datastreams that will convey the most information when played back.
Data parameters examined: amplitude, slope, frequency, lag, pattern, means, correlation, auto-regression, coherency,
Sound parameters examined: pitch, loudness, timbre, tone color, panorama, presence, accent, phase, silence, signal-to-noise ratio and reverberation.
Temporal parameters examined: tempo, mean offset, time-stretch, retrograde, re-mapping, duration, modulation, pitch-bend, and attack time.
Musical parameters examined: rhythm, dynamics, melody, harmony, polyphony, instrumentation, transposition, range, scale/mode, inversion,musical form and genre.
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