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Categories and gradience in intonation : An fMRI study

The Autosegmental-Metrical (AM) framework for intonational analysis [9] is now firmly established as the predominant theoretical framework in the field. The central insight on which the framework builds is that intonation independently carries linguistic meaning which is conveyed by abstract categorical phonological elements that are physically instantiated in a gradient way during phonetic implementation (e.g. [5,7]). However, empirical support for this distinction between phonology and phonetics in intonation has proved elusive (e.g.[8], cf.[5]). The problem is that categories and gradient variation in intonational forms are closely intertwined, since both can in fact be used to convey meaning, e.g. [1,3,11]. For instance, a gradiently wider pitch excursion can be used to signal gradiently increasing surprise (called 'paralinguistic' here), but gradient variation in form can also signal categorically distinct meanings, as when a bigger pitch excursion for an utterance-final rise signals a question instead of a continuation ('linguistic' here). In this paper, we investigate the neural substrates for the processing of phonetic as opposed to phonological information in intonation for the first time, combining perception data with direct physical evidence from functional Magnetic Resonance Imaging. The underlying assumption is that the different levels of representation of phonological and phonetic variation in intonation mirror differential activations in a distributed cortical network of hierarchically organised neural subsystems which subserve different cognitive functions in speech comprehension, cf. [2,4,6,10]. Using an event-related design, we recorded BOLD responses in the 3T Siemens Tim Trio MRI scanner at the MRC-CBU (Cambridge, UK) for 15 participants who made linguistic or paralinguistic interpretations of auditory stimuli in a forced choice speeded response task. Using Praat, fundamental frequency (F0) was resynthesised on 24 words with 5 intonation contours (Table 1). This speech condition was replicated as a hummed condition by low-pass filtering the stimuli. The images were realigned , spatially normalised, and analysed in SPM8. Two GLM designs at the subject level (one non-parametric, the other with the contours as linear parametric modulators) were carried forward in a random-effects analysis at the group level. Linguistically interpreted stimuli activated a widespread network of sites including STG bilaterally and LIFG, as we hypothesised, as well as areas that are likely to show activation due to the task (button pressing; Figure 1, left panel). Paralinguistic interpretation engaged the same fronto-temporal network to a lesser extent, but crucially, the activations that were observed for the linguistic and paralinguistic conditions differed as a function of F0 …