Spoken language is colored by fluctuations in pitch and rhythm. Rather than speaking in a flat monotone, we allow our sentences to rise and fall. We vary the length of syllables, drawing out some, and shortening others. These fluctuations, known as prosody, add emotion to speech and denote punctuation. In written language, we use a comma or a period to signal a boundary between phrases. In speech, we use changes in pitch – how deep or sharp a voice sounds – or in the length of syllables.

Having more than one type of cue that can signal emotion or transitions between sentences has a number of advantages. It means that people can understand each other even when factors such as background noise obscure one set of cues. It also means that people with impaired sound perception can still understand speech. Those with a condition called congenital amusia, for example, struggle to perceive pitch, but they can compensate for this difficulty by placing greater emphasis on other aspects of speech.

Jasmin et al. showed how the brain achieves this by comparing the brain activities of people with and without amusia. Participants were asked to read sentences on a screen where a comma indicated a boundary between two phrases. They then heard two spoken sentences, and had to choose the one that matched the written sentence. The spoken sentences used changes in pitch and/or syllable duration to signal the position of the comma. This provided listeners with the information needed to distinguish between "after John runs the race, ..." and "after John runs, the race...", for example.

When two brain regions communicate, they tend to increase their activity at around the same time. The brain regions are then said to show functional connectivity. Jasmin et al. found that compared to healthy volunteers, people with amusia showed less functional connectivity between left hemisphere brain regions that process language and right hemisphere regions that process pitch. In other words, because pitch is a less reliable source of information for people with amusia, they recruit pitch-related brain regions less when processing speech.

These results add to our understanding of how brains compensate for impaired perception. This may be useful for understanding the neural basis of compensation in other clinical conditions. It could also help us design bespoke hearing aids or other communication devices, such as computer programs that convert text into speech. Such programs could tailor the pitch and rhythm characteristics of the speech they produce to suit the perception of individual users.

Congenital amusia is a rare condition characterized by impaired perception of and memory for pitch (Peretz et al., 2002). Although congenital amusia presents as an auditory condition, auditory cortical responses are normal (Moreau et al., 2013; Norman-Haignere et al., 2016), as is subcortical encoding of pitch (Liu et al., 2015b). The dominant view of amusia’s neural basis is that connectivity between right inferior frontal cortex and right auditory cortex is impaired, resulting in impaired conscious access to pitch information for guiding behavior (Hyde et al., 2011; Albouy et al., 2013; Leveque et al., 2016; Zendel et al., 2015; see Peretz, 2016 for review). While congenital amusia is believed to be innate, there is evidence that recovery is possible through training (Whiteford and Oxenham, 2018).

Although pitch is usually associated with music, it is also important for cueing categories in spoken language (de Pijper and Sanderman, 1994; Streeter, 1978) and conveying emotion in speech (Frick, 1985). In highly controlled laboratory tasks in which speech perception judgments must be made based on pitch alone, only minor deficits have been observed in amusia (Liu et al., 2015a; Patel et al., 2008). In naturalistic speech perception contexts, people with amusia rarely report any difficulties (Liu et al., 2010). This may be because, in natural speech, pitch variation tends to co-occur with variation in other acoustic dimensions, such as duration and amplitude. Our lab has shown that in such cases where multiple redundant cues are available, English-speaking individuals with amusia tend to rely less on pitch than non-amusic controls, suggesting they may calibrate their perception by down-weighting the cues that are less reliable for them (Jasmin et al., 2020a). As for emotional prosody in speech, individuals with amusia can recognize emotions in spoken sentences, but not in short samples such as isolated vowels (Pralus et al., 2019), or when speech has been filtered to remove high-frequency non-pitch cues (Lolli et al., 2015).

It is unknown how decreased reliance on a particular acoustic cue during speech perception (such as pitch cues in amusia) is reflected in the brain. Previous neural studies of cue integration have focused on integration of multiple modalities, for example the ‘weighted connections’ model of multisensory integration. In this model, the relative reliability of the modalities involved with perception of a stimulus is related to differential connectivity strength (Beauchamp et al., 2010; Rohe and Noppeney, 2018). For example, when participants simultaneously view and feel touches to the hand, and reliability of visual and tactile perception is manipulated experimentally via introduction of noise, connection strength (effective connectivity measured with functional MRI and structural equation modeling) between unimodal and multimodal sensory areas adjusts accordingly. More concretely, when visual information is degraded, the connection strength between lateral occipital cortex (a visual area) and intraparietal sulcus (a multimodal area) decreases, and when tactile perception is made noisier, connection strength between secondary somatosensory cortex and intraparietal sulcus becomes weaker (Beauchamp et al., 2010). Similarly, effective connectivity between the (multimodal) superior temporal sulcus (STS) and visual and auditory areas has shown similar modulations during processing of audiovisual speech: connection strength between auditory cortex and the STS is weaker when noise has been introduced to the auditory speech, and conversely connection strength between visual cortex and STS is weaker if visual noise is introduced (Nath and Beauchamp, 2011).

Just as connectivity differences have been shown to reflect the precision of different sensory modalities during multisensory integration, an analogous phenomenon may be at work within a single modality during multidimensional integration. As mentioned, the acoustic speech signal carries multiple co-occurring acoustic dimensions (e.g. roughly described as voice pitch, duration, and amplitude), which often provide redundant cues to disambiguate a linguistic category (Patel, 2014; Winter, 2014; Jasmin et al., 2020a). Individuals with typical pitch perception have learned through a lifetime of experience with speech acoustics that vocal pitch is a useful and reliable cue. By contrast, individuals with amusia, who have unreliable perception of and memory for pitch (analogous to the ‘noise’ introduced in the multisensory integration studies cited above), would have learned that, for them, pitch is not a reliable cue for processing spoken language. Thus, by analogy to the multisensory weighting results described above, we hypothesize that amusics may exhibit decreased connectivity between language regions and pitch-related areas during speech processing.

The neural foundations of perceptual weighting in speech have thus far not been investigated in atypical individuals. Indeed, only one previous functional neuroimaging study has examined the neural processing of spoken material in people with amusia. In this study, no group differences were detected in task-related activation or functional connectivity during processing of speech (whereas group differences were observed during processing of tones; Albouy et al., 2019). However, the connectivity analyses in this study focused on the silent retention interval in a task in which participants needed to maintain phonemic and not pitch-related information in memory; the analyses also used broader bilateral ROIs within networks associated with language processing. It remains an open question how functional connectivity in amusic and non-amusic participants may differ during speech encoding in pitch-related language tasks within regions of interest selected with a whole-brain data-driven approach.

To determine whether the relative reliability of auditory dimensions in speech perception is reflected in functional connectivity, we used functional magnetic resonance imaging to scan 15 individuals with amusia and 15 controls. Participants matched spoken sentences with visually presented ones on the basis of the position of intonational phrase boundaries. These intonation changes were conveyed differently, in three conditions: Pitch-Informative (where only pitch cues could be used to make the judgment), Duration-Informative (where only duration cues could be used) or Both-Informative (both pitch and duration cues could be used; Jasmin et al., 2020a; Jasmin et al., 2020b). Functional connectivity was then examined using a data-driven approach that allowed us to identify the largest group differences, without the need for regions of interest to be selected a priori. The benefit of this approach is that any set of regions could emerge, not only ones reported in previous literature. Crucially, task performance was matched between the groups (based on prior behavioural testing; Jasmin et al., 2020a), ensuring that any neural differences did not simply represent an inability to perform the task. Finally, functional connectivity between these areas was analyzed with respect to prosodic cue weights obtained outside the scanner, and also compared to functional connectivity calculated from different scanning runs with a passive listening task.

We found that individuals with amusia, who have been previously shown to rely less on pitch than controls to process spoken language (Jasmin et al., 2020a), exhibited decreased functional connectivity between left frontal areas and right hemisphere pitch-related regions. In our task, participants matched spoken sentences with visually presented sentences based on pitch, duration, or both these acoustic dimensions together. Using a data-driven approach, we identified four regions in left and right inferior frontal cortex for which the amusic group exhibited decreased functional connectivity with several other sites in frontal, temporal and occipital cortex. The most prominent of these results was decreased connectivity between left frontal regions classically implicated in language processing (left IFG and DLPFC) and right hemisphere regions —in the superior temporal gyrus and sulcus, Heschl’s gyrus, and anterior insula—that have been implicated in pitch processing (Lee et al., 2011; Garcea et al., 2017; Warren et al., 2003; Hohmann et al., 2018). We suggest that this decreased connectivity between right hemisphere pitch and left hemisphere frontal cortices may relate to the unreliability of the amusics’ perception of and memory for pitch. This is similar to the ‘weighted connections’ model of multisensory integration, where a more (or less) reliable modality is given a stronger (or weaker) weight (Beauchamp et al., 2010).

Congenital amusia is often described as a disorder related to structural and functional connectivity within the right hemisphere, particularly between right inferior frontal cortices and right posterior temporal cortex (see Peretz, 2016 for review). Consistent with this proposal, we found in the present study that right inferior frontal cortex exhibited strongly decreased functional connectivity in the amusia group, and follow-up seed testing revealed that right auditory areas were involved as well. However, we also found that sites in left frontal cortex also showed large decreases in connectivity in amusia, also most prominently with right hemisphere auditory areas. Our results are consistent with an account that right hemisphere auditory areas are not only abnormally connected to right frontal areas (as observed during tonal tasks) but are less integrated with frontal left hemisphere regions when processing speech and language.

Our null results for group differences in activation during speech processing are consistent with prior reports that amusics and controls do not differ in pitch representations within sensory regions. For example, the extent of pitch-responsive regions within auditory cortex has been shown to be similar in participants with amusia and controls (Norman-Haignere et al., 2016). Brainstem encoding of pitch in speech and musical stimuli is similarly unimpaired in individuals with amusia (Liu et al., 2015b). Moreover, in oddball EEG paradigms, amusics show similar pre-attentive mismatch negativity responses to small pitch deviants, but impaired attention-dependent P300 responses (Moreau et al., 2009; Peretz et al., 2009; Mignault Goulet et al., 2012; Moreau et al., 2013). These findings, along with the fact that amusics show intact non-volitional behavioral responses (unconscious pitch shifts) when presented with pitch-altered feedback of their own voice (Hutchins and Peretz, 2012), have been interpreted as evidence that amusia is a disorder of pitch awareness rather than one of low-level pitch processing (Peretz et al., 2009), with differences in structural connectivity as one possible foundation of this putative impaired pitch awareness (Hyde et al., 2006; Loui et al., 2009; but see Chen et al., 2015).

Our interpretation of differences in functional connectivity between amusics and controls diverges somewhat from these previous approaches: we argue that down-weighting of pitch information during perceptual categorization in both speech and music is adaptive, inasmuch as amusics have learned that pitch is an unreliable source of evidence relative to other perceptual dimensions. The evidence above suggesting that encoding of pitch in the brainstem and auditory cortex and pre-attentive responses to pitch changes are unaffected in amusia can be interpreted as suggesting that the fundamental deficit in amusia may not be increased perceptual noise or decreased pitch awareness but difficulties with retention of pitch information in memory (see Tillmann et al., 2016 for review). Our task arguably taxed working memory resources: in a similar paradigm performed by the same participants in quiet listening conditions (Jasmin et al., 2020a), the mean reaction time measured from the end of the second auditory stimulus was 1.64 s, indicating that participants needed some time to compare both auditory presentations and make their judgments. This interpretation is consistent with evidence suggesting that amusics have difficulty with pitch sequence processing tasks even when discrimination thresholds are accounted for (Tillmann et al., 2009), as well as the finding that delaying the time interval between standard and comparison tones exacerbates pitch discrimination impairment in individuals with amusia (Williamson et al., 2010). Moreover, the pitch awareness account of amusia cannot explain the Jasmin et al., 2020a finding that pitch cues are downweighted only during longer-scale suprasegmental speech perception, while pitch weighting is not different between amusics and controls during shorter-scale segmental speech perception, despite pitch cues being arguably more subtle in the segmental condition. However, this finding can be explained by the pitch memory account, as the suprasegmental task requires detection of and memory for pitch patterns within a complex sequence, while the segmental task does not. Furthermore, an account of amusia which suggests that the disorder primarily stems from differences in structural connectivity cannot account for the recent finding that functional connectivity patterns do not differ between amusics and controls during a verbal memory task (Albouy et al., 2019), as well as our finding that amusics and controls show similar functional connectivity patterns during passive listening to tone sequences. We suggest, therefore, that amusics neglect pitch because they have implicitly learned that their memory for pitch is unreliable, and that this down-weighting of pitch is reflected in decreased functional connectivity between right auditory areas and downstream task-relevant areas which integrate information from perceptual regions. One way to test this hypothesis would be to examine functional connectivity during perceptual categorization of consonant-vowel syllables as voiced versus unvoiced based on a pitch cue (F0 of the following vowel) and a durational cue (voice onset time). We predict, based on our previous findings (Jasmin et al., 2020a), that functional connectivity will not differ between amusics and controls on this task, a finding which would not be predicted by the pitch awareness account of amusia.

We note that a previous fMRI study on amusia detected group differences in functional connectivity during passive listening to tones. That study used task-defined seed voxels in bilateral auditory cortex and found, in the amusia group, increased connectivity between left and right auditory cortex, but decreased connectivity between right auditory cortex and right inferior frontal gyrus (Hyde et al., 2011). The present study does not necessarily clash with these findings, as we used different seed ROIs selected with a different procedure.

We did not observe any differences in functional connectivity between conditions in our speech task. This may be because our functional imaging protocol was timed to capture the peak in the BOLD signal corresponding to the presentation of the second auditory stimulus. Participants never knew (even implicitly) which acoustic dimension might be useful on any given trial until after they had heard both spoken sentences and needed to compare them to make their response. Furthermore, pitch fluctuations in the stimuli were above participants’ thresholds , even in the Duration-Informative condition (where the standard deviation of F0 over each spoken utterance was, on average, 2.7 semitones), and so it is unsurprising that functional connectivity did not change on a trial-by-trial basis, and instead the same ‘neural strategy’ was employed to process speech regardless of the trial type.

Several other future directions are suggested by our results, particularly for examining cue weighting during auditory/speech perception. In the multimodal integration studies mentioned above (Beauchamp et al., 2010; Nath and Beauchamp, 2011), reliability of two different sensory modalities was manipulated experimentally by severely degrading input channels with noise, resulting in changes in connectivity. Similarly, aspects of speech could be selectively masked with noise in order to make them less reliable, which in turn could cause corresponding changes in functional or effective connectivity. Indeed, behavioral work has indicated that when fundamental frequency (pitch) or durational aspects of speech are manipulated to be unreliable cues, categorization behavior shifts such that participants place less relative weight on the dimension that has been made less reliable (Holt and Lotto, 2010). Certain groups, such as tone language speakers, are known to have fine-grained pitch perception abilities, and tend to place greater weight on pitch even when processing speech from a second, non-tonal language that they have learned (e.g. English; Yu and Andruski, 2010; Zhang and Francis, 2010, Zhang et al., 2008; Qin et al., 2017; Jasmin et al., 2020a). Given the increased reliability of their pitch perception, tone language speakers may exhibit correspondingly high connectivity strength between right hemisphere auditory regions and left hemisphere ‘language regions’ when pitch cues are present (more so than native non-tonal language speakers). Expert musicians also have extensive pitch-related experience and training and could also serve as a population to examine in future work.

The data that support the findings of this study are openly available in the Birkbeck repository (https://researchdata.bbk.ac.uk/65/), as are the speech stimuli (Jasmin et al., 2020b; https://researchdata.bbk.ac.uk/37/). The speech task can be demoed at the following link: (Gorilla Open Materials; https://gorilla.sc/openmaterials/102786).

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Author details

1. Kyle Jasmin

   1. Department of Psychological Sciences, Birkbeck University of London, London, United Kingdom
   2. UCL Institute of Cognitive Neuroscience, University College London, London, United Kingdom

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Methodology

   For correspondence

   kyle.jasmin.11@ucl.ac.uk

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-9723-8207

2. Frederic Dick

   1. Department of Psychological Sciences, Birkbeck University of London, London, United Kingdom
   2. Department of Experimental Psychology, University College London, London, United Kingdom

   Contribution

   Conceptualization, Supervision, Visualization, Methodology

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-2933-3912

3. Lauren Stewart

   Department of Psychology, Goldsmiths University of London, London, United Kingdom

   Contribution

   Conceptualization, Resources

   Competing interests

   No competing interests declared

4. Adam Taylor Tierney

   Department of Psychological Sciences, Birkbeck University of London, London, United Kingdom

   Contribution

   Conceptualization, Supervision, Funding acquisition

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-7624-6918

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