Nicole Kristine Flaig
Department of Psychology, University of Connecticut
Music Dynamics Laboratory- University of Connecicut.
Current Researches and Interests:
Music is a high-level cognitive capacity, a form of communication that relies on highly structured temporal sequences comparable in complexity to language. Music is found among all human cultures, and musical ‘languages’ vary among cultures and depend upon learning. For example, European melodies use different kinds of note combinations than Indian melodies, so that Westerners find it difficult to understand Indian music, and vice versa. Unlike language, however, music rarely refers to the external world. It consists of self-contained patterns of sound, aspects of which are found universally among musical cultures. This suggests that it may be possible to discover the general principles of neural dynamics that underlie music perception and cognition.
Tonality refers to the stability and attraction relationships that are perceived among notes in a musical language. Although there are different kinds of tonality, tonality itself is a universal feature of music, found in virtually every musical language. Our hypothesis is that neural oscillation underlies tonal cognition and perception. Neural oscillation is periodic neural activity that, in the auditory system, becomes phase-locked to incoming sounds. Neural oscillations can be complex, but there are now powerful mathematical tools for analyzing them. These mathematical analyses predict a set of general constraints on what sorts of tonal relationships are possible. In other words, fundamental principles of neural oscillation combined with fundamental principles of brain plasticity should predict what musical languages can be learned.
To make these predictions, we are building build a computer model of the auditory system, based on knowledge of auditory organization and general neurodynamic principles. We are training simulations through passive exposure to European and North Indian melodies. We will ask whether our computer models can predict neurophysiological and perceptual results that have been found over the past twenty-five years or so.
Awards and Recognitions:
Provost’s Fellowship (2010)