Diminished large-scale functional brain networks in absolute pitch during the perception of naturalistic music and audiobooks

Effects of absolute pitch on brain activation and functional connectivity during hearing-in-noise perception

Hearing-in-noise (HIN) ability is crucial in speech and music communication. Recent evidence suggests that absolute pitch (AP), the ability to identify isolated musical notes, is associated with HIN benefits. A theoretical account postulates a link between AP ability and neural network indices of segregation. However, how AP ability modulates the brain activation and functional connectivity underlying HIN perception remains unclear. Here we used functional magnetic resonance imaging to contrast brain responses among a sample (n = 45) comprising 15 AP musicians, 15 non-AP musicians, and 15 non-musicians in perceiving Mandarin speech and melody targets under varying signal-to-noise ratios (SNRs: No-Noise, 0, -9 dB). Results reveal that AP musicians exhibited increased activation in auditory and superior frontal regions across both HIN domains (music and speech), irrespective of noise levels. Notably, substantially higher sensorimotor activation was found in AP musicians when the target was music compared to speech. Furthermore, we examined AP effects on neural connectivity using psychophysiological interaction analysis with the auditory cortex as the seed region. AP musicians showed decreased functional connectivity with the sensorimotor and middle frontal gyrus compared to non-AP musicians. Crucially, AP differentially affected connectivity with parietal and frontal brain regions depending on the HIN domain being music or speech. These findings suggest that AP plays a critical role in HIN perception, manifested by increased activation and functional independence between auditory and sensorimotor regions for perceiving music and speech streams.

Increased Alpha-Band Connectivity During Tic Suppression in Children With Tourette Syndrome Revealed by Source Electroencephalography Analyses

BACKGROUND

Tourette syndrome (TS) is a neurodevelopmental disorder involving chronic motor and phonic tics. Most individuals with TS can suppress their tics for at least a short period of time. Yet, the brain correlates of tic suppression are still poorly understood.

METHODS

In the current study, high-density electroencephalography was recorded during a resting-state and a tic suppression session in 72 children with TS. Functional connectivity between cortical regions was assessed in the alpha band (8-13 Hz) using an electroencephalography source connectivity method. Graph theory and network-based statistics were used to assess the global network topology and to identify brain regions showing increased connectivity during tic suppression.

RESULTS

Graph theoretical analyses revealed distinctive global network topology during tic suppression, relative to rest. Using network-based statistics, we found a subnetwork of increased connectivity during tic suppression (p < .001). That subnetwork encompassed many cortical areas, including the right superior frontal gyrus and the left precuneus, which are involved in the default mode network. We also found a condition-by-age interaction, suggesting age-mediated increases in connectivity during tic suppression.

CONCLUSIONS

These results suggest that children with TS suppress their tics through a brain circuit involving distributed cortical regions, many of which are part of the default mode network. Brain connectivity during tic suppression also increases as youths with TS mature. These results highlight a mechanism by which children with TS may control their tics, which could be relevant for future treatment studies.

Use of explicit priming to phenotype absolute pitch ability

Musicians with absolute pitch (AP) can name the pitch of a musical note in isolation. Expression of this unusual ability is thought to be influenced by heritability, early music training and current practice. However, our understanding of factors shaping its expression is hampered by testing and scoring methods that treat AP as dichotomous. These fail to capture the observed variability in pitch-naming accuracy among reported AP possessors. The aim of this study was to trial a novel explicit priming paradigm to explore phenotypic variability of AP. Thirty-five musically experienced individuals (M_age = 29 years, range 18–68; 14 males) with varying AP ability completed a standard AP task and the explicit priming AP task. Results showed: 1) phenotypic variability of AP ability, including high-accuracy AP, heterogeneous intermediate performers, and chance-level performers; 2) intermediate performance profiles that were either reliant on or independent of relative pitch strategies, as identified by the priming task; and 3) the emergence of a bimodal distribution of AP performance when adopting scoring criteria that assign credit to semitone errors. These findings show the importance of methods in studying behavioural traits, and are a key step towards identifying AP phenotypes. Replication of our results in larger samples will further establish the usefulness of this priming paradigm in AP research.

Research on Chinese Audio and Text Alignment Algorithm Based on AIC-FCM and Doc2Vec

“Audiobook” is a multimedia-based reading technology that has emerged in recent years. Realizing the alignment of e-book text and book audio is the most important part of its processing. This article describes an audio and text alignment algorithm using deep learning and neural network technology to improve the efficiency and quality of audiobook production. The algorithm first uses dual-threshold endpoint detection technology to segment long audio into short audio with sentence dimensions and recognizes it as short text. The threshold is calculated by AIC-FCM optimized based on simulated annealing genetic algorithm. Then the algorithm uses Doc2vec optimized by the threshold prediction method based on the average length of the short text to calculate the text similarity. Finally, proofread and output the text sequence and audio segment aligned in the time dimension to meet the needs of audiobook production. Experiments show that compared to traditional audio and text alignment algorithms, the proposed algorithm is closer to the ideal segmentation result in long audio segmentation, and the alignment effect is basically the same as Doc2vec and the time complexity is reduced by about 35%.

Integrating music-based interventions with Gamma-frequency stimulation: Implications for healthy ageing

In recent years, music-based interventions (MBIs) have risen in popularity as a non-invasive, sustainable form of care for treating dementia-related disorders, such as Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD). Despite their clinical potential, evidence regarding the efficacy of MBIs on patient outcomes is mixed. Recently, a line of related research has begun to investigate the clinical impact of non-invasive Gamma-frequency (e.g., 40 Hz) sensory stimulation on dementia. Current work, using non-human-animal models of AD, suggests that non-invasive Gamma-frequency stimulation can remediate multiple pathophysiologies of dementia at the molecular, cellular and neural-systems scales, and, importantly, improve cognitive functioning. These findings suggest that the efficacy of MBIs could, in theory, be enhanced by incorporating Gamma-frequency stimulation into current MBI protocols. In the current review, we propose a novel clinical framework for non-invasively treating dementia-related disorders that combines previous MBIs with current approaches employing Gamma-frequency sensory stimulation. We theorize that combining MBIs with Gamma-frequency stimulation could increase the therapeutic power of MBIs by simultaneously targeting multiple biomarkers of dementia, restoring neural activity that underlies learning and memory (e.g., Gamma-frequency neural activity, Theta-Gamma coupling), and actively engaging auditory and reward networks in the brain to promote behavioural change.

Individualized video recommendation modulates functional connectivity between large scale networks

With the emergence of AI‐powered recommender systems and their extensive use in the video streaming service, questions and concerns also arise. Why can recommended video content continuously capture users' attention? What is the impact of long‐term exposure to personalized video content on one's behaviors and brain functions? To address these questions, we designed an fMRI experiment presenting participants with personally recommended videos and generally recommended ones. To examine how large‐scale networks were modulated by personalized video content, graph theory analysis was applied to investigate the interaction between seven networks, including the ventral and dorsal attention networks (VAN, DAN), frontal–parietal network (FPN), salience network (SN), and three subnetworks of default mode network (dorsal medial prefrontal (dMPFC), Core, and medial temporal lobe (MTL)). Our results showed that viewing nonpersonalized video content mainly enhanced the connectivity in the DAN‐FPN‐Core pathway, whereas viewing personalized ones increased not only the connectivity in this pathway but also the DAN‐VAN‐dMPFC pathway. In addition, both personalized and nonpersonalized short videos decreased the couplings between SN and VAN as well as between two DMN subsystems, Core and MTL. Collectively, these findings uncovered distinct patterns of network interactions in response to short videos and provided insights into potential neural mechanisms by which human behaviors are biased by personally recommended content.

Structural connectivity predicts sequential processing differences in music perception ability

To relate individual differences in music perception ability with whole brain white matter connectivity, we scanned a group of 27 individuals with varying degrees of musical training and assessed musical ability in sensory and sequential music perception domains using the Profile of Music Perception Skills-Short version (PROMS-S). Sequential processing ability was estimated by combining performance on tasks for Melody, Standard Rhythm, Embedded Rhythm, and Accent subscores while sensory processing ability was ascertained via tasks of Tempo, Pitch, Timbre, and Tuning. Controlling for musical training, gender, and years of training, network-based statistics revealed positive linear associations between total PROMS-S scores and increased interhemispheric fronto-temporal and parieto-frontal white matter connectivity, suggesting a distinct segregated structural network for music perception. Secondary analysis revealed two subnetworks for sequential processing ability, one comprising ventral fronto-temporal and subcortical regions and the other comprising dorsal fronto-temporo-parietal regions. A graph-theoretic analysis to characterize the structural network revealed a positive association of modularity of the whole brain structural connectome with the d' total score. In addition, the nodal degree of the right posterior cingulate cortex also showed a significant positive correlation with the total d' score. Our results suggest that a distinct structural network of connectivity across fronto-temporal, cerebellar, and cerebro-subcortical regions is associated with music processing abilities and the right posterior cingulate cortex mediates the connectivity of this network.

Musical Expertise Shapes Functional and Structural Brain Networks Independent of Absolute Pitch Ability

Professional musicians are a popular model for investigating experience-dependent plasticity in human large-scale brain networks. A minority of musicians possess absolute pitch, the ability to name a tone without reference. The study of absolute pitch musicians provides insights into how a very specific talent is reflected in brain networks. Previous studies of the effects of musicianship and absolute pitch on large-scale brain networks have yielded highly heterogeneous findings regarding the localization and direction of the effects. This heterogeneity was likely influenced by small samples and vastly different methodological approaches. Here, we conducted a comprehensive multimodal assessment of effects of musicianship and absolute pitch on intrinsic functional and structural connectivity using a variety of commonly used and state-of-the-art multivariate methods in the largest sample to date (n = 153 female and male human participants; 52 absolute pitch musicians, 51 non-absolute pitch musicians, and 50 non-musicians). Our results show robust effects of musicianship in interhemispheric and intrahemispheric connectivity in both structural and functional networks. Crucially, most of the effects were replicable in both musicians with and without absolute pitch compared with non-musicians. However, we did not find evidence for an effect of absolute pitch on intrinsic functional or structural connectivity in our data: The two musician groups showed strikingly similar networks across all analyses. Our results suggest that long-term musical training is associated with robust changes in large-scale brain networks. The effects of absolute pitch on neural networks might be subtle, requiring very large samples or task-based experiments to be detected.SIGNIFICANCE STATEMENT A question that has fascinated neuroscientists, psychologists, and musicologists for a long time is how musicianship and absolute pitch, the rare talent to name a tone without reference, are reflected in large-scale networks of the human brain. Much is still unknown as previous studies have reported widely inconsistent results based on small samples. Here, we investigate the largest sample of musicians and non-musicians to date (n = 153) using a multitude of established and novel analysis methods. Results provide evidence for robust effects of musicianship on functional and structural networks that were replicable in two separate groups of musicians and independent of absolute pitch ability.

Discrimination Improvement Through Undesirable Feedback in Coupling Object Manipulation Tasks

Subjective effort can significantly affect the ability of humans to act optimally in dynamic manipulation tasks. In a previous study, we designed a complex object coupling manipulation task that required tight performance and induced high cognitive workload. We hypothesize that strong-effort-related physiological reactivity during the dynamic manipulation task improves the user performance in an undesired task feedback situation. To test this hypothesis, using the motor intentions' discrimination from electroencephalogram (EEG) measurements, we evaluate the effort expended by 20 participants in a controlling task with constraints involving complex coupling objects. Specifically, the finer motor decisions are obtained from the controlling information in EEG by using two fingers from the same hand rather than two hands. The motor intention is decoded from a task-dependent EEG through a regularized discriminant analysis, and the area under the curve is [Formula: see text]. Furthermore, we compare the undesired and desired task feedback conditions along with the individual's effort dynamic adjustment, and investigate whether the undesired task feedback improved the discrimination of the motor activities. A stronger effort to attain the desired feedback state corresponds to improved motor activity discrimination from the EEG in the undesired task feedback scenario. The differences in the brain activities under the undesired and desired task feedback conditions are analyzed using brain-network-based topographical scalp maps. Our experiment provides preliminary evidence that inducing strong effort can improve discrimination performance during highly demanding tasks. This finding can advance our understanding of human attention, potentially improve the accuracy of intention recognition, and may inspire better EEG acquisition contexts.

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.