Biology subjects

Vuust, P.

Publications and source records attributed to Vuust, P..

At least 55 records · Page 3Linked to original sources

bioRxiv2023

The major-minor mode dichotomy in music perception: A systematic review on its behavioural, physiological, and clinical correlates

Since ancient Greece, major and minor modes in Western tonal music have been identified as the primary responsible musical feature for eliciting emotional states. As such, the underlying correlates of the major-minor mode dichotomy in music perception have been extensively investigated through decades of psychological and neuroscientific research, providing plentiful yet often discordant results. Specifically, crucial questions remain about the several factors contributing to the affective perception of major and minor modes, at times very different among individuals. Moreover, major and minor mode perception has never been quantitatively compared in literature. This comprehensive systematic review and meta-analysis aimed to provide a qualitative and quantitative synthesis of musical mode perception and its behavioural and neural correlates. The qualitative synthesis resulted in 69 studies, showing great diversity in how the major-minor dichotomy has been empirically approached. Most studies reviewed were conducted on adults, considered participants expertise, employed real-life musical stimuli, performed behavioural evaluations, and were carried out among Western listeners. Behavioural, electroencephalography, and neuroimaging meta-analyses (36 studies) consistently showed that major and minor mode elicit distinct neural and emotional responses. Based on our findings, a framework to describe a Major-Minor Mode(l) of music perception and its behavioural and physiological correlates is proposed, incorporating individual factors such as age, expertise, cultural background, and emotional disorders. Limitations, implications, and suggestions for future research are discussed, including putative clinical applications of major-minor dichotomy and best practices regarding stimulation paradigms for musical mode investigation. Public Significance StatementThis study provides qualitative and quantitative evidence of the distinct behavioral and neural responses elicited by major and minor mode, while also highlighting the influence of factors such as age, culture, personality, and health. Results offers a detailed overview of the major-minor dichotomy in music, putting forward an integrated and critical discussion of methodologies, paradigms, and clinical implications of this pivotal musical feature.

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bioRxiv2023

Age-related brain mechanisms underlying short-term recognition of musical sequences: An EEG study

Recognition is the ability to correctly identify previously learned information. It is an important part of declarative episodic memory and a vital cognitive function, which declines with ageing. Several studies investigated recognition of visual elements, complex images, spatial patterns, and musical melodies, focusing especially on automatic and long-term recognition. Here, we studied the impact of ageing on the event-related potentials using electroencephalography (EEG) associated with short-term recognition of auditory sequences. To this end, we recruited 54 participants, which were divided into two groups: (i) 29 young adults (20-30 years old), (ii) 25 older adults (60-80 years old). We presented two sequences with an interval of a few seconds. Participants were asked to state how similar the second sequence was with regards to the first one. The neural results indicated a stronger negative, widespread activity associated with the recognition of the same sequence compared to the sequences that were transposed or completely different. This difference was widely distributed across the EEG sensors and involved especially temporo-parietal areas of the scalp. Notably, we reported largely reduced neural responses for the older versus young adults, even when no behavioral differences were observed. In conclusion, our study suggests that the combination of auditory sequences, music, and fast-scale neurophysiology may represent a privileged solution to better understand short-term memory and the cognitive decline associated with ageing.

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bioRxiv2023

Dopamine dysregulation in Parkinson's disease flattens the pleasurable urge to move to musical rhythms

The pleasurable urge to move to music (PLUMM) elicits activity in motor and reward areas of the brain and is thought to be driven by predictive processes. Dopamine within motor and limbic cortico-striatal networks is implicated in the predictive processes underlying beat-based timing and music-induced pleasure, respectively. This suggests a central role of cortico-striatal dopamine in PLUMM. This study tested this hypothesis by comparing PLUMM in Parkinsons disease patients, healthy age-matched, and young controls. Participants listened to musical sequences with varying rhythmic and harmonic complexity (low, medium, high), and rated their experienced pleasure and urge to move to the rhythm. In line with previous results, healthy younger participants showed an inverted U-shaped relation between rhythmic complexity and ratings, with a preference for medium complexity rhythms, while age-matched controls showed a similar, but weaker, inverted U-shaped response. Conversely, PD patients showed a significantly flattened response for both the urge to move and pleasure. Crucially, this flattened response could not be attributed to differences in rhythm discrimination and did not reflect an overall decrease in ratings. Together, these results support the role of dopamine within cortico-striatal networks in the predictive processes that form the link between the perceptual processing of rhythmic patterns, and the affective and motor responses to rhythmic music.

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bioRxiv2022

Hierarchical whole-brain dynamics of auditory predictive coding at the fine-grained milliseconds level

Our brain is constantly extracting, predicting, and recognising key spatiotemporal features of the physical world in order to survive. While neural processing of visuospatial patterns has been extensively studied, the hierarchical brain mechanisms underlying conscious recognition of auditory sequences and the associated prediction errors remain elusive. Using magnetoencephalography (MEG), we studied the brain functioning of 83 participants during recognition of previously memorised musical sequences and systematic variations. The results showed feedforward connections originating from auditory cortices, and extending to the hippocampus, anterior cingulate gyrus, and medial cingulate gyrus. Simultaneously, we observed backward connections operating in the opposite direction. Throughout the sequences, the hippocampus and cingulate gyrus maintained the same hierarchical level, except for the final tone, where the cingulate gyrus assumed the top position within the hierarchy. The evoked responses of memorised sequences and variations engaged the same hierarchical brain network but systematically differed in terms of temporal dynamics, strength, and polarity. Furthermore, induced-response analysis showed that alpha and beta power was stronger for the variations, while gamma power was enhanced for the memorised sequences. This study expands on the predictive coding theory by providing quantitative evidence of hierarchical brain mechanisms during conscious memory and predictive processing of auditory sequences.

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bioRxiv2022

Age and musical training effects on auditory short-term, long-term, and working memory

Cognitive aging is characterized by a gradual decline in cognitive functioning. One of the most worrying deficits for older adults is a decreased capacity to memorize and remember new information. In this study, we assessed auditory short-term memory (STM), long-term memory (LTM), and working memory (WM) abilities of young and older adults using musical and numerical tasks. Additionally, we measured musical training and tested whether this capacity influences memory performance. Regarding STM, young adults scored higher than older adults when making same/different judgements of rhythmic sequences, but their performance was alike for melodic sequences. Higher levels of musical training were associated with enhanced STM capacity for melodic sequences. In relation to LTM, young adults outperformed older adults in identifying new musical sequences. Moreover, younger and older individuals with high musical training outperformed those with low musical training. No group differences were found in the recognition of previously memorized musical sequences. Finally, we found no group differences in WM capacity, although there was a non-significant tendency for young adults to outperform older adults. Overall, we found that aging differently affects several types of auditory memory and that, for certain musical memory tasks, a higher level of musical training provides significant advantages.

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bioRxiv2022

A potential marker for problematic mother-infant bonding revealed by magnetoencephalography study of first-time mothers listening to infant cries

Studies using magnetoencephalography (MEG) have identified the orbitofrontal cortex (OFC) to be an important early hub for a parental instinct in the brain. This complements the finding from functional magnetic resonance imaging (fMRI) studies linking reward, emotion regulation, empathy and mentalisation networks to the parental brain. Here, we used MEG in 43 first-time mothers listening to infant and adult cry vocalisations to investigate the link with mother-infant postpartum bonding scores and their level of sleep deprivation (assessed using both actigraphy and sleep logs). We found significant differences 800-1000ms after onset of infant compared to adult cries in source-reconstructed brain activity in areas previously linked to the parental brain. Importantly, mothers with weaker bonding scores showed decreased brain responses to infant cries in the auditory cortex, middle and superior temporal gyrus, OFC, hippocampal areas, supramarginal gyrus and inferior frontal gyrus at around 100-200ms after stimulus onset. In contrast, we did not find correlations with sleep deprivation scores. The significant changes in brain processing of an infants distress signals could be a novel marker of weaker infant bonding in new mothers and should be investigated in vulnerable populations.

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bioRxiv2022

Associations between abstract working memory abilities and brain activity underlying long-term recognition of auditory sequences

Memory is a complex cognitive process comprised by several subsystems, namely short- and long-term memory and working memory (WM). Previous research has shown that adequate interaction between subsystems is crucial for successful memory processes such as encoding, storage and manipulation of information. However, few studies have investigated the relationship between different subsystems at the behavioral and neural levels. Thus, here we assessed the relationship between individual WM abilities and brain activity underlying the recognition of previously memorized auditory sequences. First, recognition of previously memorized versus novel auditory sequences was associated with a widespread network of brain areas comprising the cingulate gyrus, hippocampus, insula, inferior temporal cortex, frontal operculum, and orbitofrontal cortex. Second, we observed positive correlations between brain activity underlying auditory sequence recognition and WM. We showed a sustained positive correlation in the medial cingulate gyrus, a brain area which was widely involved in the auditory sequence recognition. Remarkably, we also observed positive correlations in the inferior temporal, temporal-fusiform, and postcentral gyri, brain areas which were not strongly associated to auditory sequence recognition. In conclusion, we discovered positive correlations between WM abilities and brain activity underlying long-term recognition of auditory sequences, providing new evidence on the relationship between memory subsystems. Furthermore, we showed that high WM performers recruited a larger brain network including areas associated to visual processing (i.e., inferior temporal, temporal-fusiform and postcentral gyri) for successful auditory memory recognition. Significance statementMemory is a complex cognitive process dependent on the successful interaction between its multiple subsystems. Here, we assessed the relationship between individual WM abilities and brain activity underlying the recognition of previously memorized auditory sequences. We observed positive correlations between brain activity underlying auditory sequence recognition and WM, especially in the medial cingulate gyrus, inferior temporal, temporal-fusiform and postcentral gyri. In this study, we provided new evidence on the relationship between two memory subsystems: WM and long-term auditory recognition. Moreover, we showed that, to successfully complete memory recognition tasks, high WM performers recruited a larger brain network which comprised brain areas mainly associated to visual processing, such as inferior temporal, temporal-fusiform and postcentral gyri.

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bioRxiv2022

Whole-brain computation of cognitive versus acoustic errors in music

Previous studies have evidenced how the local prediction of physical stimulus features may affect the neural processing of incoming stimuli. Less known are the effects of cognitive priors on predictive processes, and how the brain computes local versus cognitive predictions and their errors. Here, we determined the differential brain mechanisms underlying prediction errors related to high-level, cognitive priors for melody (rhythm, contour) versus low-level, local acoustic priors (tuning, timbre). We measured with magnetoencephalography the mismatch negativity (MMN) prediction error signal in 104 adults having varying levels of musical expertise. We discovered that the brain regions involved in predictive processes for local priors were primary and secondary auditory cortex and insula, whereas cognitive brain regions such as cingulate and orbitofrontal cortices were recruited for melodic errors in cognitive priors. The involvement of higher-level brain regions for computing cognitive errors was enhanced in musicians, especially in cingulate cortex, inferior frontal gyri, and supplementary motor area. Overall, the findings expand knowledge on whole-brain mechanisms of predictive processing and the related MMN generators, previously mainly confined to the auditory cortex, to a frontal network that strictly depends on the type of priors that are to be computed by the brain.

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bioRxiv2022

The spatiotemporal dynamics of recognition memory for complex versus simple auditory sequences

Differently from visual recognition, auditory recognition is a process relying on the organization of single elements that evolve in time. Here, we aimed to discover the spatiotemporal dynamics of this cognitive function by adopting a novel strategy for varying the complexity of musical sequences. We selected traditional tonal musical sequences and altered the distance between pitches to obtain matched atonal sequences. We then recorded the brain activity of 71 participants using magnetoencephalography (MEG) while they listened to and later recognized auditory sequences constructed according to simple (tonal) or complex (atonal) conventions. Results reveal qualitative changes in neural activity dependent on stimulus complexity: recognition of tonal sequences engaged hippocampal and cingulate areas, whereas recognition of atonal sequences mainly activated the auditory processing network. Our findings highlight the involvement of a cortico-subcortical brain network for auditory recognition and support the idea that stimulus complexity qualitatively alters the neural pathways of recognition memory.

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bioRxiv2021

Temporal pattern recognition in the human brain: a dual simultaneous processing

Pattern recognition is a major scientific topic. Strikingly, while machine learning algorithms are constantly refined, the human brain emerges as an ancestral biological example of such complex procedure. However, how it transforms sequences of single objects into meaningful temporal patterns remains elusive. Using magnetoencephalography (MEG) and magnetic resonance imaging (MRI), we discovered and mathematically modelled an inedited dual simultaneous processing responsible for pattern recognition in the brain. Indeed, while the objects of the temporal pattern were independently elaborated by a local, rapid brain processing, their combination into a meaningful superordinate pattern depended on a concurrent global, slower processing involving a widespread network of sequentially active brain areas. Expanding the established knowledge of neural information flow from low- to high-order brain areas, we revealed a novel brain mechanism based on simultaneous activity in different frequency bands within the same brain regions, highlighting its crucial role underlying complex cognitive functions.

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bioRxiv2021

Enhanced mismatch negativity responses in harmonic compared to inharmonic sound sequences

Many natural sounds have frequency spectra composed of integer multiples of a fundamental frequency. This property, known as harmonicity, plays an important role in auditory information processing. However, the extent to which harmonicity influences the processing of sound features beyond pitch is still unclear. This is interesting because harmonic sounds have lower information entropy than inharmonic sounds. According to predictive processing accounts of perception, this property could produce more salient neural responses due to the brains weighting of sensory signals according to their uncertainty. In the present study, we used electroencephalography to investigate brain responses to harmonic and inharmonic sounds commonly occurring in music: piano tones and hi-hat cymbal sounds. In a multi-feature oddball paradigm, we measured mismatch negativity (MMN) and P3a responses to timbre, intensity, and location deviants in listeners with and without congenital amusia--an impairment of pitch processing. As hypothesized, we observed larger amplitudes and earlier latencies (for both MMN and P3a) in harmonic compared to inharmonic sounds. These harmonicity effects were modulated by sound feature. Moreover, the difference in P3a latency between harmonic and inharmonic sounds was larger for controls than amusics. We propose an explanation of these results based on predictive coding and discuss the relationship between harmonicity, information entropy, and precision weighting of prediction errors.

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bioRxiv2021

On the brain networks organization of individuals with high versus average fluid intelligence: a combined DTI and MEG study

The neural underpinning of human fluid intelligence (Gf) has gathered a large interest in the scientific community. Nonetheless, previous research did not provide a full understanding of such intriguing topic. Here, we studied the structural (from diffusion tensor imaging, DTI) and functional (from magnetoencephalography (MEG) resting state) connectivity in individuals with high versus average Gf scores. Our findings showed greater values in the brain areas degree distribution and higher proportion of long-range anatomical connections for high versus average Gfs. Further, the two groups presented different community structures, highlighting the structural and functional integration of the cingulate within frontal subnetworks of the brain in high Gfs. These results were consistently observed for structural connectivity and functional connectivity of delta, theta and alpha. Notably, gamma presented an opposite pattern, showing more segregation and lower degree distribution and connectivity in high versus average Gfs. Our study confirmed and expanded previous perspectives and knowledge on the "small-worldness" of the brain. Further, it complemented the widely investigated structural brain network of highly intelligent individuals with analyses on fast-scale functional networks in five frequency bands, highlighting key differences in the integration and segregation of information flow between slow and fast oscillations in groups with different Gf.

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bioRxiv2021

Trait empathy modulates music-related functional connectivity.

It has been well established through behavioural studies that empathy significantly influences music perception. Such individual differences typically manifest as variability in whole brain functional connectivity patterns. To date, nobody has examined the modulatory effect of empathy on functional connectivity patterns during continuous music listening. In the present study, we seek to investigate the global and local connectivity patterns of 36 participants whose fMRI scanning was done by employing the naturalistic paradigm wherein they listened to a continuous piece of music. We used graph-based measures of functional connectivity to identify how cognitive and affective components of empathy modulate functional connectivity. Partial correlation between Eigenvector centrality and measures of empathy showed that cognitive empathy is associated with higher centrality in the sensorimotor regions responsible for motor mimicry while affective empathy showed higher centrality in regions related to auditory affect processing. We furthermore identified a left-hemispheric dominance in the modulatory effect of affective empathy particularly in the Orbitofrontal cortex and the temporal pole. Results are discussed in relation to various theoretical models of empathy and music cognition.

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bioRxiv2021

Prediction Under Uncertainty: Dissociating Sensory from Cognitive Expectations in Highly Uncertain Musical Contexts

Predictive models in the brain rely on the continuous extraction of regularities from the environment. These models are thought to be updated by novel information, as reflected in prediction error responses such as the mismatch negativity (MMN). However, although in real life individuals often face situations in which uncertainty prevails, it remains unclear whether and how predictive models emerge in high-uncertainty contexts. Recent research suggests that uncertainty affects the magnitude of MMN responses in the context of music listening. However, musical predictions are typically studied with MMN stimulation paradigms based on Western tonal music, which are characterized by relatively high predictability. Hence, we developed an MMN paradigm to investigate how the high uncertainty of atonal music modulates predictive processes as indexed by the MMN and behavior. Using MEG in a group of 20 subjects without musical training, we demonstrate that the magnetic MMN in response to pitch, intensity, timbre, and location deviants is evoked in both tonal and atonal melodies, with no significant differences between conditions. In contrast, in a separate behavioral experiment involving 39 non-musicians, participants detected pitch deviants more accurately and rated confidence higher in the tonal than in the atonal musical context. These results indicate that contextual tonal uncertainty modulates processing stages in which conscious awareness is involved, although deviants robustly elicit low-level pre-attentive responses such as the MMN. The achievement of robust MMN responses, despite high tonal uncertainty, is relevant for future studies comparing groups of listeners MMN responses to increasingly ecological music stimuli.

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bioRxiv2021

Data and model considerations for estimating time-varying functional connectivity in fMRI

Functional connectivity (FC) in the brain has been shown to exhibit subtle but reliable modulations within a session. One way of estimating time-varying FC is by using state-based models that describe fMRI time series as temporal sequences of states, each with an associated, characteristic pattern of FC. However, the estimation of these models from data sometimes fails to capture changes in a meaningful way, such that the model estimation assigns entire sessions (or the largest part of them) to a single state, therefore failing to capture within-session state modulations effectively; we refer to this phenomenon as the model becoming static, or model stasis. Here, we aim to quantify how the nature of the data and the choice of model parameters affect the models ability to detect temporal changes in FC using both simulated fMRI time courses and resting state fMRI data. We show that large between-subject FC differences can overwhelm subtler within-session modulations, causing the model to become static. Further, the choice of parcellation can also affect the models ability to detect temporal changes. We finally show that the model often becomes static when the number of free parameters that need to be estimated is high and the number of observations available for this estimation is low in comparison. Based on these findings, we derive a set of practical recommendations for time-varying FC studies, in terms of preprocessing, parcellation and complexity of the model. HighlightsO_LITime-varying FC models sometimes fail to detect temporal changes in fMRI data C_LIO_LIBetween- and within-subject FC variability affect model stasis C_LIO_LIThe choice of parcellation affects model stasis in real fMRI data C_LIO_LIThe number of observations and free parameters critically affect model stasis Keywords: fMRI; time-varying FC; Hidden Markov Model (HMM); resting state C_LI

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bioRxiv2021

Beat Perception in Polyrhythms: Time is Structured in Binary Units

In everyday life, we group and subdivide time to understand the sensory environment surrounding us. Our perceptual system establishes hierarchical structures by nesting different groups of time intervals. Organizing time in units such as diurnal rhythms, phrases, and beat patterns, is fundamental to everyday behavior, speech, and music. When listening to music, we extract rhythmic regularities to create a hierarchical metrical structure that enables us to predict the timing of the next events. Foot tapping and head bobbing to musical rhythms are observable evidence of this process. In the special case of polyrhythms, at least two metrical structures compete to become the reference for these temporal regularities, rendering several possible beats with which we can synchronize our movements. While there is general agreement that tempo, pitch, and loudness influence beat perception in polyrhythms, we focused on the yet neglected influence of beat subdivisions. In three online experiments, 300 participants listened to a range of polyrhythms and tapped their index fingers in time with the perceived beat. The polyrhythms consisted of two simultaneously presented isochronous pulse trains with different ratios (2:3, 2:5, 3:4, 3:5, 4:5, 5:6) and different tempi. For ratios 2:3 and 3:4, we additionally manipulated the pitch of the pulse trains. Results showed a highly robust influence of subdivision grouping on beat perception manifested as a propensity towards beats that are subdivided into two or four equally spaced units, as opposed to beats with three or more complex groupings of subdivisions. Additionally, lower pitched pulse trains were more likely to be perceived as the beat. Our findings suggest that subdivisions, not beats, are the basic unit of beat perception, and that the principle underlying the binary grouping of subdivisions reflects a propensity towards simplicity. This preference for simple grouping is widely applicable to human perception and cognition of time.

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bioRxiv2021

Revisiting top-down and bottom-up multi-modal brain processes: a systematic review and ALE meta-analysis of musical studies

A remarkable feature of the human brain is its ability to integrate information from the environment with internally generated content. The integration of top-down and bottom-up processes during complex multi-modal human activities, however, is yet to be fully understood. Music provides an excellent model for understanding this since music listening leads to the urge to move, and music making entails both playing and listening at the same time (i.e. audio-motor coupling). Here, we conducted activation likelihood estimation (ALE) meta-analyses of 130 neuroimaging studies of music perception, production and imagery, with 2660 foci, 139 experiments, and 2516 participants. We found that music perception and production rely on auditory cortices and sensorimotor cortices, while music imagery recruits distinct parietal regions. This indicates that the brain requires different structures to process similar information which is made available either by an interaction with the environment (i.e. bottom-up) or by internally generated content (i.e. top-down).

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bioRxiv2021

Fourier SPoC: A costumised machine-learning analysis pipeline for auditory beat-based entrainment in the MEG

We propose here (the informed use) of a customised, data-driven machine-learning pipeline to analyse magnetoencephalography (MEG) in a theoretical source space, with respect to the processing of a regular beat. This hypothesis- and data-driven analysis pipeline allows us to extract the maximally relevant components in MEG source-space, with respect to the oscillatory power in the frequency band of interest and, most importantly, the beat-related modulation of that power. Our pipeline combines Spatio-Spectral Decomposition as a first step to seek activity in the frequency band of interest (SSD, [1]) with a Source Power Co-modulation analysis (SPoC; [2]), which extracts those components that maximally entrain their activity with the given target function, that is here with the periodicity of the beat in the frequency domain (hence, f-SPoC). MEG data (102 magnetometers) from 28 participants passively listening to a 5-min long regular tone sequence with a 400 ms beat period (the "target function" for SPoC) were segmented into epochs of two beat periods each to guarantee a sufficiently long time window. As a comparison pipeline to SSD and f-SpoC, we carried out a state-of-the-art cluster-based permutation analysis (CBPA, [3]). The time-frequency analysis (TFA) of the extracted activity showed clear regular patterns of periodically occurring peaks and troughs across the alpha and beta band (8-20 Hz) in the f-SPoC but not in the CBPA results, and both the depth and the specificity of modulation to the beat frequency yielded a significant advantage. Future applications of this pipeline will address target the relevance to behaviour and inform analogous analyses in the EEG, in order to finally work toward addressing dysfunctions in beat-based timing and their consequences. Author summaryWhen listening to a regular beat, oscillations in the brain have been shown to synchronise with the frequency of that given beat. This phenomenon is called entrainment and has in previous brain-imaging studies been shown in the form of one peak and trough per beat cycle in a range of frequency bands within 15-25 Hz (beta band). Using machine-learning techniques, we designed an analysis pipeline based on Source-Power Co-Modulation (SPoC) that enables us to extract spatial components in MEG recordings that show these synchronisation effects very clearly especially across 8-20 Hz. This approach requires no anatomical knowledge of the individual or even the average brain, it is purely data driven and can be applied in a hypothesis-driven fashion with respect to the "function" that we expect the brain to entrain with and the frequency band within which we expect to see this entrainment. We here apply our customised pipeline using "f-SPoC" to MEG recordings from 28 participants passively listening to a 5-min long tone sequence with a regular 2.5 Hz beat. In comparison to a cluster-based permutation analysis (CBPA) which finds sensors that show statistically significant power modulations across participants, our individually extracted f-SPoC components find a much stronger and clearer pattern of peaks and troughs within one beat cycle. In future work, this pipeline can be implemented to tackle more complex "target functions" like speech and music, and might pave the way toward rhythm-based rehabilitation strategies.

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