Mind, Body, World- Foundations of Cognitive Science, 2013a

Interactions between perception of music and action have already been established.
For instance, when classical music is heard, the emotion associated with it
can affect perceptions of whole-body movements directed towards objects (Van den
Stock et al., 2009). The cognitive neuroscience of music has revealed a great deal of
evidence for the interaction between auditory and motor neural systems (Zatorre,
Chen, & Penhune, 2007).
Such evidence brings to mind the notion of simulation and the role of mirror
neurons, topics that were raised in Chapter 5’s discussion of embodied cognitive science.
Is it possible that direct experience of musical performances engages the mirror
system? Some researchers are considering this possibility (D’Ausilio, 2009; Lahav,
Saltzman, & Schlaug, 2007). Lahav, Saltzman, and Schlaug (2007) trained non-musicians
to play a piece of music. They then monitored their subjects’ brain activity while
they listened to this newly learned piece while not performing any movements. It was
discovered that motor-related areas of the brain were activated during the listening.
Less activity in these areas was noted if subjects heard the same notes that were
learned, but presented in a different order (i.e., as a different melody).
The mirror system has also been shown to be involved in the observation and
imitation of guitar chording (Buccino et al., 2004; Vogt et al., 2007); and musical
expertise, at least for professional piano players, is reflected in more specific mirror
neuron processing (Haslinger et al., 2005). It has even been suggested that the
mirror system is responsible for listeners misattributing anger to John Coltrane’s
style of playing saxophone (Gridley & Hoff, 2006)!
A completely hybrid approach to musical cognition that includes aspects of all
three schools of cognitive science is currently only a possibility. The closest realization
of this possibility might be an evolutionary composing system (Todd & Werner, 1991).
This system is an example of a genetic algorithm (Holland, 1992; Mitchell, 1996),
which evolves a solution to a problem by evaluating the fitness of each member of a
population, preserves the most fit, and then generates a new to-be-evaluated generation
by combining attributes of the preserved individuals. Todd and Werner (1991)
noted that such a system permits fitness to be evaluated by a number of potentially
quite different critics; their model considers contributions of human, rule-based,
and network critics.
Music is a complicated topic that has been considered at multiple levels of
investigation, including computational or mathematical (Assayag et al., 2002;
Benson, 2007; Harkleroad, 2006; Lerdahl & Jackendoff, 1983), algorithmic or behavioural
(Bailey, 1992; Deutsch, 1999; Krumhansl, 1990; Seashore, 1967; Snyder, 2000),
and implementational or biological (Jourdain, 1997; Levitin, 2006; Peretz & Zatorre,
2003). Music clearly is a domain that is perfectly suited to cognitive science. In this
chapter, the analogy between classical music and cognitive science has been developed
to highlight the very different contributions of classical, connectionist, and
312 Chapter 6