Volume 73, Issue 4, 23 February 2012, Pages 633–637
Open Archive
Music
can be seen as a model system for understanding gene × environment
interactions and how these can influence neurocognitive development. The
concept of musicality, however, is underspecified and not well
understood. Here, I propose a framework for defining musicality to
provide a foundation for studying the contributions of biological and
environmental factors.
Main Text
Musical
ability is popularly regarded to be innate: one either is or is not
born with musical talent. Increasingly, neuroscientists are
collaborating with geneticists to understand the links between genes,
brain development, cognition, and behavior (Ebstein et al., 2010 and Posner et al., 2011).
Music can be seen as a model system for understanding what genes can
accomplish and how they relate to experience. On the practical side,
identifying genetic components that underlie musical ability can also
help us to predict who will succeed or, more interestingly, what types
of instruction will be most successful for individuals according to
their genetic-cognitive profiles. In all domains, successful genotyping
requires an accurately described phenotype. Unfortunately, the latter
has not yet been accomplished for music, creating a significant hurdle
to further progress. Part of the difficulty in describing the musical
phenotype is its heterogeneity, the wide variety of ways in which
musicality presents itself (Sloboda, 2008).
My goal in this article is to review those factors that might be
associated with the phenotype and to discuss definitions, measurement,
and accuracy, three common obstacles in understanding the genetics of
complex behavioral phenomena (Ebstein et al., 2010), with the hope that this may stimulate discussion and future work on the topic.
The Functional Neuroanatomy of Music
We
now know that music activates regions throughout the brain, not just a
single “music center.” As with vision, music is processed component by
component, with specific neural circuits handling pitch, duration,
loudness, and timbre. Higher brain centers bring this information
together, binding it into representations of contour, melody, rhythm,
tempo, meter, and, ultimately, phrases and whole compositions. The idea
that music processing can be broken down into component operations was
first proposed as a conceptual tool by cognitive theorists and has been
confirmed by neuroimaging studies (Levitin and Tirovolas, 2009).
The
early distinction that music processing is right hemisphere lateralized
and that language is left hemisphere lateralized has been modified by a
more nuanced understanding. Pitch is represented by tonotopic maps,
virtual piano keyboards stretched across the cortex that represent
pitches in a low-to-high spatial arrangement. The sounds of different
musical instruments (timbres) are processed in well-defined regions of
posterior Heschl's gyrus and superior temporal sulcus (extending into
the circular insular sulcus). Tempo and rhythm are believed to invoke
hierarchical oscillators in the cerebellum and basal ganglia. Loudness
is processed in a network of neural circuits beginning at the brain stem
and inferior colliculus and extending to the temporal lobes. The
localization of sounds and the perception of distance cues are handled
by a network that attends to (among other cues) differences in
interaural time of arrival, changes in frequency spectrum, and changes
in the temporal spectrum, such as are caused by reverberation. One can
attain world-class expertise in one of these component operations
without necessarily attaining world-class expertise in others.
Higher
cognitive functions in music, such as musical attention, musical
memory, and the tracking of temporal and harmonic structure, have been
linked to particular neural processing networks. Listening to music
activates reward and pleasure circuits in the nucleus accumbens, ventral
tegmental area, and amygdala, modulating production of dopamine (Menon and Levitin, 2005).
The generation of musical expectations is a largely automatic process
in adults, developing in childhood, and is believed to be critical to
the enjoyment of music (Huron, 2006).
Tasks that require the tracking of tonal, harmonic, and rhythmic
expectations activate prefrontal regions, in particular Brodmann areas
44, 45, and 47, and anterior and posterior cingulate gyrus as part of a
cortical network that also involves limbic structures and the
cerebellum.
Musical training
is associated with changes in gray matter volume and cortical
representation. Musicians exhibit changes in the white matter structure
of the corticospinal tract, as indicated by reduced fractional
anisotropy, which suggests increased radial diffusivity. Cerebellar
volumes in keyboard players increase as a function of practice. Learning
to name notes and intervals is accompanied by a leftward shift in
processing as musical concepts become lexicalized. Writing music
involves circuits distinct from other kinds of writing, and there are
clinical reports of individuals who have musical agraphia without
textual agraphia. Double dissociations have also been reported between
musical agraphia and musical alexia. Indeed, the patient literature is
rich with accounts of individuals who have lost one specific aspect of
musical processing while others remain intact, bolstering claims
of distinct, componential processing of music (Marin and Perry, 1999).
