Suppression of Pitch Labeling: No Evidence for an Impact of Absolute Pitch on Behavioral and Neurophysiological Measures of Cognitive Inhibition in an Auditory Go/Nogo Task.

Pitch labeling in absolute pitch (AP), the ability to recognize the pitch class of a sound without an external reference, is effortless, fast, and presumably automatic. Previous studies have shown that pitch labeling in AP can interfere with task demands. In the current study, we used a cued auditory Go/Nogo task requiring same/different decisions to investigate both behavioral and electrophysiological correlates of increased inhibitory demands related to automatic pitch labeling. The task comprised two Nogo conditions: a Nogo condition with pitch differences larger than one semitone, and a second Nogo condition with pitch differences of only a quarter semitone. The first Nogo condition tested if auditory-related inhibition processes are generally altered in AP musicians. The second Nogo condition tested the suppressibility of the pitch labeling using a Stroop-like effect: the two tones belonged to the same pitch class but were not identical in terms of tone frequency. If pitch labeling cannot be suppressed, the conflicting information would be expected to increase the inhibitory load in AP musicians. Our data provided no evidence for an increased difficulty to inhibit a prepotent response or to suppress conflicting pitch-labeling information in AP: AP musicians showed similar commission error rates as non-AP musicians in both Nogo conditions. N2d and P3d amplitudes of AP musicians were also comparable to those of non-AP musicians. The event-related potentials (ERPs) were, however, modulated by the Nogo condition, probably indicating an effect of stimulus similarity. It is possible that, depending on the context, pitch labeling in AP musicians is not entirely automatic and can be suppressed.

Heterogeneity of EEG resting-state brain networks in absolute pitch.

The neural basis of absolute pitch (AP), the ability to effortlessly identify a musical tone without an external reference, is poorly understood. One of the key questions is whether perceptual or cognitive processes underlie the phenomenon, as both sensory and higher-order brain regions have been associated with AP. To integrate the perceptual and cognitive views on AP, here, we investigated joint contributions of sensory and higher-order brain regions to AP resting-state networks. We performed a comprehensive functional network analysis of source-level EEG in a large sample of AP musicians (n = 54) and non-AP musicians (n = 51), adopting two analysis approaches: First, we applied an ROI-based analysis to examine the connectivity between the auditory cortex and the dorsolateral prefrontal cortex (DLPFC) using several established functional connectivity measures. This analysis is a replication of a previous study which reported increased connectivity between these two regions in AP musicians. Second, we performed a whole-brain network-based analysis on the same functional connectivity measures to gain a more complete picture of the brain regions involved in a possibly large-scale network supporting AP ability. In our sample, the ROI-based analysis did not provide evidence for an AP-specific connectivity increase between the auditory cortex and the DLPFC. The whole-brain analysis revealed three networks with increased connectivity in AP musicians comprising nodes in frontal, temporal, subcortical, and occipital areas. Commonalities of the networks were found in both sensory and higher-order brain regions of the perisylvian area. Further research will be needed to confirm these exploratory results.

Neural patterns reveal single-trial information on absolute pitch and relative pitch perception.

Pitch is a fundamental attribute of sounds and yet is not perceived equally by all humans. Absolute pitch (AP) musicians perceive, recognize, and name pitches in absolute terms, whereas relative pitch (RP) musicians, representing the large majority of musicians, perceive pitches in relation to other pitches. In this study, we used electroencephalography (EEG) to investigate the neural representations underlying tone listening and tone labeling in a large sample of musicians (n = 105). Participants performed a pitch processing task with a listening and a labeling condition during EEG acquisition. Using a brain-decoding framework, we tested a prediction derived from both theoretical and empirical accounts of AP, namely that the representational similarity of listening and labeling is higher in AP musicians than in RP musicians. Consistent with the prediction, time-resolved single-trial EEG decoding revealed a higher representational similarity in AP musicians during late stages of pitch perception. Time-frequency-resolved EEG decoding further showed that the higher representational similarity was present in oscillations in the theta and beta frequency bands. Supplemental univariate analyses were less sensitive in detecting subtle group differences in the frequency domain. Taken together, the results suggest differences between AP and RP musicians in late pitch processing stages associated with cognition, rather than in early processing stages associated with perception.

Absolute and relative pitch processing in the human brain: neural and behavioral evidence.

Pitch is a primary perceptual dimension of sounds and is crucial in music and speech perception. When listening to melodies, most humans encode the relations between pitches into memory using an ability called relative pitch (RP). A small subpopulation, almost exclusively musicians, preferentially encode pitches using absolute pitch (AP): the ability to identify the pitch of a sound without an external reference. In this study, we recruited a large sample of musicians with AP (AP musicians) and without AP (RP musicians). The participants performed a pitch-processing task with a Listening and a Labeling condition during functional magnetic resonance imaging. General linear model analysis revealed that while labeling tones, AP musicians showed lower blood oxygenation level-dependent (BOLD) signal in the inferior frontal gyrus and the presupplementary motor area-brain regions associated with working memory, language functions, and auditory imagery. At the same time, AP musicians labeled tones more accurately suggesting that AP might be an example of neural efficiency. In addition, using multivariate pattern analysis, we found that BOLD signal patterns in the inferior frontal gyrus and the presupplementary motor area differentiated between the groups. These clusters were similar, but not identical compared to the general linear model-based clusters. Therefore, information about AP and RP might be present on different spatial scales. While listening to tones, AP musicians showed increased BOLD signal in the right planum temporale which may reflect the matching of pitch information with internal templates and corroborates the importance of the planum temporale in AP processing. Taken together, AP and RP musicians show diverging frontal activations during Labeling and, more subtly, differences in right auditory activation during Listening. The results of this study do not support the previously reported importance of the dorsolateral prefrontal cortex in associating a pitch with its label.

A reevaluation of the electrophysiological correlates of absolute pitch and relative pitch: No evidence for an absolute pitch-specific negativity.

Musicians with absolute pitch effortlessly identify the pitch of a sound without an external reference. Previous neuroscientific studies on absolute pitch have typically had small samples sizes and low statistical power, making them susceptible for false positive findings. In a seminal study, Itoh et al. (2005) reported the elicitation of an absolute pitch-specific event-related potential component during tone listening - the AP negativity. Additionally, they identified several components as correlates of relative pitch, the ability to identify relations between pitches. Here, we attempted to replicate the main findings of Itoh et al.'s study in a large sample of musicians (n = 104) using both frequentist and Bayesian inference. We were not able to replicate the presence of an AP negativity during tone listening in individuals with high levels of absolute pitch, but we partially replicated the findings concerning the correlates of relative pitch. Our results are consistent with several previous studies reporting an absence of differences between musicians with and without absolute pitch in early auditory evoked potential components. We conclude that replication studies form a crucial part in assessing extraordinary findings, even more so in small fields where a single finding can have a large impact on further research.

Electrophysiological Correlates of Absolute Pitch in a Passive Auditory Oddball Paradigm: a Direct Replication Attempt.

Humans with absolute pitch (AP) are able to effortlessly name the pitch class of a sound without an external reference. The association of labels with pitches cannot be entirely suppressed even if it interferes with task demands. This suggests a high level of automaticity of pitch labeling in AP. The automatic nature of AP was further investigated in a study by Rogenmoser et al. (2015). Using a passive auditory oddball paradigm in combination with electroencephalography, they observed electrophysiological differences between musicians with and without AP in response to piano tones. Specifically, the AP musicians showed a smaller P3a, an event-related potential (ERP) component presumably reflecting early attentional processes. In contrast, they did not find group differences in the mismatch negativity (MMN), an ERP component associated with auditory memory processes. They concluded that early cognitive processes are facilitated in AP during passive listening and are more important for AP than the preceding sensory processes. In our direct replication study on a larger sample of musicians with (n = 54, 27 females, 27 males) and without (n = 50, 24 females, 26 males) AP, we successfully replicated the non-significant effects of AP on the MMN. However, we could not replicate the significant effects for the P3a. Additional Bayes factor analyses revealed moderate to strong evidence (Bayes factor > 3) for the null hypothesis for both MMN and P3a. Therefore, the results of this replication study do not support the postulated importance of cognitive facilitation in AP during passive tone listening.

Faster native vowel discrimination learning in musicians is mediated by an optimization of mnemonic functions.

The ability to discriminate phonemes varying in spectral and temporal attributes constitutes one of the most basic intrinsic elements underlying language learning mechanisms. Since previous work has consistently shown that professional musicians are characterized by perceptual and cognitive advantages in a variety of language-related tasks, and since vowels can be considered musical sounds within the domain of speech, here we investigated the behavioral and electrophysiological correlates of native vowel discrimination learning in a sample of professional musicians and non-musicians. We evaluated the contribution of both the neurophysiological underpinnings of perceptual (i.e., N1/P2 complex) and mnemonic functions (i.e., N400 and P600 responses) while the participants were instructed to judge whether pairs of native consonant-vowel (CV) syllables manipulated in the first formant transition of the vowel (i.e., from /tu/ to /to/) were identical or not. Results clearly demonstrated faster learning in musicians, compared to non-musicians, as reflected by shorter reaction times and higher accuracy. Most notably, in terms of morphology, time course, and voltage strength, this steeper learning curve was accompanied by distinctive N400 and P600 manifestations between the two groups. In contrast, we did not reveal any group differences during the early stages of auditory processing (i.e., N1/P2 complex), suggesting that faster learning was mediated by an optimization of mnemonic but not perceptual functions. Based on a clear taxonomy of the mnemonic functions involved in the task, results are interpreted as pointing to a relationship between faster learning mechanisms in musicians and an optimization of echoic (i.e., N400 component) and working memory (i.e., P600 component) functions.