The Journal of Neuroscience, August 29, 2012 • 32(35):12251–12257 • 12251 Behavioral/Systems/Cognitive Navigating the Auditory Scene: An Expert Role for the Hippocampus Sundeep Teki,1* Sukhbinder Kumar,1,2* Katharina von Kriegstein,3 Lauren Stewart,4 C. Rebecca Lyness,5 Brian C. J. Moore,6 Brian Capleton,7 and Timothy D. Griffiths1,2 1Wellcome Trust Centre for Neuroimaging, University College London, London, WC1N 3BG, United Kingdom, 2Auditory Group, Institute of Neuroscience, Newcastle University Medical School, Newcastle upon Tyne, NE2 4HH, United Kingdom, 3Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany, 4Department of Psychology, Goldsmiths, University of London, London, SE14 6NW, United Kingdom, 5Institute of Cognitive Neuroscience, University College London, London, WC1N 3AR, United Kingdom, 6Department of Experimental Psychology, University of Cambridge, Cambridge, CB2 3EB, United Kingdom, and 7Royal National College, Hereford, HR1 1EB, United Kingdom Over a typical career piano tuners spend tens of thousands of hours exploring a specialized acoustic environment. Tuning requires accurate perception and adjustment of beats in two-note chords that serve as a navigational device to move between points in previously learned acoustic scenes. It is a two-stage process that depends on the following: first, selective listening to beats within frequency windows, and, second, the subsequent use of those beats to navigate through a complex soundscape. The neuroanatomical substrates underlyingbrainspecializationforsuchfundamentalorganizationofsoundscenesareunknown.Here,wedemonstratethatprofessional piano tuners are significantly better than controls matched for age and musical ability on a psychophysical task simulating active listening to beats within frequency windows that is based on amplitude modulation rate discrimination. Tuners show a categorical increase in gray matter volume in the right frontal operculum and right superior temporal lobe. Tuners also show a striking enhancement of gray matter volume in the anterior hippocampus, parahippocampal gyrus, and superior temporal gyrus, and an increase in white matter volume in the posterior hippocampus as a function of years of tuning experience. The relationship with gray matter volume is sensitive to years of tuning experience and starting age but not actual age or level of musicality. Our findings support a role for a core set of regions in the hippocampus and superior temporal cortex in skilled exploration of complex sound scenes in which precise sound “templates” are encoded and consolidated into memory over time in an experience-dependent manner. Introduction tigate neuroanatomical bases of skilled organization of sound We assessed brain specialization in a previously unstudied group scenes. of expert listeners who spend large amounts of time exploring a Piano tuning requires the practitioner to perform successive complex acoustic environment that requires accurate perception navigation between tuned and untuned notes in which the beat and adjustment. The subjects, piano tuners, perform an active rate between notes is used as a form of “signpost.” Traditionally, listening and adjustment task every time a piano is tuned where tuning starts with tuning a single note to a standard tuning fork. they explore an acoustic scene according to a specific route. Piano A two-note chord is then played, comprising the tuned note and tuning is a highly sophisticated skill: a single tuning session might another note. The two notes contain multiple frequencies at the take up to 2 h and a professional tuner may typically tune up to 20 fundamental and higher harmonics, and certain harmonics in the pianos a week, so the highest levels of expertise follow thousands two notes occur close to each other and produce beats fluctua- of hours of experience over a period of 20 to 30 years (Capleton, tions in the envelope of the combined harmonics at a rate equal to 2007). Thus, this group provides a unique opportunity to inves- their frequency difference (Fig. 1A). The piano tuner is required to detect a particular beat rate corresponding to the interval between the two notes played, and match that to a specific value. A further interval is then tuned based on the most re- Received Jan. 6, 2012; revised April 21, 2012; accepted May 19, 2012. cently tuned note and another note, and this process is re- Author contributions: S.K., K.v.K., L.S., B.C.M., B.C., and T.D.G. designed research; S.T., S.K., K.v.K., and L.S. peated iteratively (Fig. 2A). The beat rate and the frequency performed research; S.T., S.K., K.v.K., L.S., and C.R.L. analyzed data; S.T. and T.D.G. wrote the paper. region in which the beat is to be detected vary for different This work was funded by the Wellcome Trust, UK. We are grateful to the Radiology and IT staff at the Wellcome Trust Centre for Neuroimaging for their excellent technical support. We thank Simon Baumann, Adrian Rees, and intervals but are fixed for any given interval with beat rates Eleanor Maguire for comments on this manuscript and John Ashburner for help with the volumetric analysis. that are typically less than 20 Hz (Table 1). *S.T. and S.K. contributed equally to this work. The acoustic processes underlying tuning include: (1) selec- This article is freely available online through the J Neurosci Open Choice option. tive listening and detection of beats within particular frequency Correspondence should be addressed to Sundeep Teki, Wellcome Trust Centre for Neuroimaging, University College London, 12 Queen Square, London, WC1N 3BG, UK. E-mail: [email protected]. regions, and (2) adjustment of the beat rate and comparison with DOI:10.1523/JNEUROSCI.0082–12.2012 a predefined rate that is dependent on the interval being tuned Copyright © 2012 the authors 0270-6474/12/3212251-07$15.00/0 (which is learned and remembered by trained tuners). Impor- 12252 • J. Neurosci., August 29, 2012 • 32(35):12251–12257 Teki, Kumar et al. • Neural Bases of Acoustic Skill Underlying Piano Tuning Table 1. Beat rate relationships for different piano note pairs (Capleton, 2007) Major third (4 st) Beats (Hz) Perfect fourth (5 st) Beats (Hz) Perfect fifth (7 st) Beats (Hz) Major sixth (9 st) Beats (Hz) Minor third (3 st) Beats (Hz) Minor sixth (8 st) Beats (Hz) F–A 6.9 F–Bb 0.8 F–C 0.6 F–D 7.9 F–Ab 9.4 F–Db 11.0 F#–A# 7.3 F#–B 0.8 F#–C# 0.6 F#–D# 8.4 F#–A 10.0 F#–D 11.7 G–B 7.8 G–C 0.9 G–D 0.7 G–E 8.9 G–Bb 10.6 G–Eb 12.3 Ab–C 8.2 G#–C# 0.9 G#–D# 0.7 Ab–F 9.4 G#–B 11.2 G#–E 13.1 A–C# 8.7 A–D 1.0 A–E 0.7 A–F# 10.0 A–C 11.9 A–F 13.9 Bb–D# 9.2 A#–D# 1.1 Bb–F 0.8 Bb–G 10.6 A#–C# 12.6 A#–F# 14.7 B–D# 9.8 B–E 1.1 B–F# 0.8 B–D 13.3 B–G 15.6 C–E 10.4 C–F 1.2 C–G 0.9 C–Eb 14.1 C#–F 11.0 C#–F# 1.3 D–F# 11.7 D–G 1.3 Eb–G 12.3 Wesimulatedtheprocessoflisteningtobeatsinafrequencywindowthroughtheuseofafive-elementharmoniccomplexwhereonlythemiddlecomponentismodulatedataraterelevanttothetuningprocedure.Table1showstherange of beat rates for different note pairs for the scale area F3–G4 (difference in semitones indicated at the top) corresponding to the intervals used in tuning. The major thirds, perfect fourths, perfect fifths, and major sixths are the most useful for tuning, but the minor thirds and sixths that are also useful are included as well. In the experiment we used rates of 2 Hz and 16 Hz that are both within this range. st, Semitones. tantly, the first stage of active listening and beat detection repre- difference limen for modulation rate was defined for modulation rates of sents an essential entry-level skill following which the second skill 2 and 16 Hz, both of which fall within the range of beat rates used by of beat rate adjustment and navigation in pitch space via different tuners. A control task used a similar procedure to establish a difference tuning algorithms may develop further. Interestingly, neither limen for the frequency of an unmodulated 1000 Hz tone. musical expertise nor absolute pitch is required for proficient The task was designed to assess selective listening to envelope fluctu- piano tuning (Capleton, 2007). ation of a single component within a harmonic complex as used by piano Here, we measured thresholds of tuners and controls on an tuners. Such a skill is essential for piano tuning and was hypothesized to be enhanced in the tuners. The task does not simulate the process of amplitude modulation rate discrimination task that simulated navigating between notes that tuners must also carry out based on ad- beat detection and investigated structural brain changes in tuners justment of the beats for a particular two-note intervals to a learned that are related to their tuning experience. Based on the require- value. The AM discrimination data were analyzed to test the hypothesis ments of tuning, we predicted structural changes in the auditory that the piano tuners have a greater sensitivity to changes in envelope cortex of all tuners that correspond to their specific expertise in a fluctuation at rates of 2 and 16 Hz. We hypothesized that there would be specialized type of active listening. We also predicted structural no differences between the two groups for the tone frequency discrimi- changes in hippocampus that evolve over several years of practice nation task. during which tuners repeatedly encode beat-rate templates into All stimuli were created digitally using MATLAB (The MathWorks) at particular spectral and pitch contexts.