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Vuust, P.

Publications and source records attributed to Vuust, P..

At least 37 records · Page 2Linked to original sources

Inharmonicity enhances brain signals of attentional capture and auditory stream segregation

Harmonicity is an important feature for auditory perception. However, the neural substrates of processing inharmonic sounds remain unclear. Here, we systematically manipulated the harmonicity of sounds by introducing random jittering to their frequencies. Using electroencephalography, we studied the effect of inharmonicity on markers of auditory prediction errors -- mismatch negativity (MMN) and P3a -- in a roving oddball paradigm. Inharmonic sounds with a constant jittering pattern generated similar MMN and stronger P3a responses than harmonic sounds. In contrast, MMN responses became undetectable when the jittering pattern changed between consecutive sounds, suggesting that prediction errors are weighted by sequential but not spectral uncertainty. Interestingly, inharmonic sounds generated an object-related negativity, a response associated with the segregation of auditory objects. Our results suggest that inharmonicity induces the segregation of the auditory scene into different streams, captures attention, and gives rise to specific neural processes that are independent from the predictive mechanisms underlying sequential deviance detection.

neuroscience↗

Embodied Singing: Dual Role of Interoception in Vocal Expertise and Musical Competence

Musical expertise is often associated with heightened perceptual sensitivity to external sensory stimuli, yet its relationship with internal bodily awareness (interoception) remains elusive. This study examined whether interoceptive ability relates differentially to varying levels of singing expertise and explored if interoception could predispose individuals to musical skills. Professional singers, amateur singers, and non-singers completed a heartbeat discrimination task (interoceptive accuracy; IAcc), self-reported interoceptive sensibility assessment, and comprehensive musical competence measures. Results demonstrated a significant positive association between singing expertise and IAcc, which notably emerged only in professional singers, who significantly outperformed both amateur singers and non-singers. Regression analyses indicated a moderate predictive role of accumulated singing practice for IAcc among trained singers, though emotional awareness partially mediated the relationship between expertise and IAcc. Critically, higher IAcc in non-singers significantly correlated with superior singing accuracy, suggesting enhanced interoception may facilitate singing competence independently of formal vocal training. Altogether, these findings highlight a dual role of interoception, linking it to expert-level singing--partially mediated by emotional awareness-- and independently to musical competence in non-singers. These results reconcile prior inconsistencies by highlighting the embodied nature of singing and the distinct role of musical expertise, while underscoring inherent musically relevant mechanisms beyond practice alone.

neuroscience↗

LSD reconfigures the frequency-specific network landscape of the human brain

Lysergic acid diethylamide (LSD) and other psychedelic substances profoundly alter human consciousness. While several studies have demonstrated changes in brain function and connectivity associated with psychedelics, we still have a limited understanding of how LSD reshapes brain networks operating across different frequency bands. In this study, we applied the recently developed FREQ-NESS method to MEG data from 14 healthy participants who received LSD under four conditions: eyes-closed with or without music and eyes-open with or without a video stimulus. LSD significantly restructures canonical networks in the alpha and beta bands. Relative to broadband brain activity, it enhances the prominence of high alpha (12.1, 13.3 Hz) across all experimental conditions and high beta (25.3 Hz) in three conditions. Conversely, LSD decreases the prominence of low beta (18.1, 19.3 Hz) in both Open and Closed conditions and low alpha (8.5 Hz) in the latter. In addition, LSD substantially alters the spatial distributions or topographies of the networks. Under LSD, the low alpha (8.5 Hz) network shifts anteriorly toward the motor cortex, while high alpha (12.1, 13.3 Hz) becomes more localized to the visual cortex. Low beta (18.1, 19.3 Hz) expands over the temporal and occipital cortices, whereas high beta (25.3, 26.5 Hz) topographies remain unchanged. Our findings provide critical insights into the specific frequencies and spatial networks in which LSD modulates brain connectivity, adding nuance to prevailing theories about network disintegration under psychedelics. Significance statementPsychedelic substances such as lysergic acid diethylamide (LSD) profoundly alter perception and cognition, yet their effect on brain activity across different frequency bands remains unclear. Using FREQ-NESS applied to MEG data, we show that LSD reorganizes brain networks by enhancing high-frequency alpha and beta rhythms while suppressing lower-frequency counterparts. These changes occur across various experimental conditions and shift the spatial distribution of brain activity, particularly in motor and visual regions. Our findings suggest that LSD modulates brain connectivity in a frequency- and region-specific manner, offering new insights into how psychedelics alter consciousness. This work advances our understanding of LSDs neural effects, which may be relevant for therapeutic applications and models of brain function.

neuroscience↗

Prediction of individual melodic contour processing in sensory association cortices from resting state functional connectivity

Recent studies suggest that it is possible to predict an individual brains spatial activation pattern in response to a paradigm from their functional connectivity at rest (rsFC). However, it is unclear whether this prediction works across the brain. We here aim to understand whether individual task activation can be best predicted in local regions that are highly specialised to the task at hand or whether there are domain-independent regions in the brain that carry most information about the individual. To answer this question, we used fMRI data from participants (nonmusicians, N=52) at rest and during an auditory oddball paradigm while watching a silent movie. We then predicted individual differences in brain responses to melodic deviants from their rsFC both across the whole brain (global parcellation in 22 regions) and within the auditory cortices (local parcellation in 22 regions). Predictability was consistently higher in specific brain areas. These areas are centred around sensory association cortices: In the local (auditory cortex) parcellation, the best predicted area is the right superior temporal gyrus (STG), an auditory association area. The right STG is a critical region in melodic contour processing, a capacity that is central to the paradigm at hand. Interestingly, the best predicted network in the global parcellation is the bilateral visual association cortex. Sensory association cortices may carry more information specific to an individual regardless of the particular paradigm. Our results indicate that individual differences can be predicted in paradigm-relevant areas or general areas with higher inter-individual variability.

neuroscience↗

Prior use-dependent plasticity triggers different individual corticomotor responses during persistent musculoskeletal pain

Movement repetition is crucial for pain interventions. It facilitates the rehabilitation of motor patterns, the acquisition of motor skills and the genesis of adaptive use-dependent plasticity. However, the influence of prior motor experience and pre-existing use-dependent plasticity on pain severity and progression remains poorly investigated. This study investigated the effects of pre-existing use-dependent plasticity during the development of prolonged experimental musculoskeletal pain. Using transcranial magnetic stimulation, corticospinal excitability was assessed by measuring the rest-motor thresholds (RMTs), motor-evoked potential (MEP), representational area of the motor map, volume, and center of gravity of the first dorsal interosseous (FDI) muscle in musicians (n=19), a well-known ecological model of use-dependent plasticity, and in non-musicians (n=20). All participants attended three sessions (Day1, Day3, Day8). Prolonged pain for several days was induced by intramuscular injection of nerve growth factor (NGF) into the right FDI muscle at the end of Day1. Compared to Day1, prolonged pain uniquely led to reduced motor map volume in non-musicians on Day3 (p=0.004), who also showed higher NGF-related pain intensity compared to musicians. The motor maps of musicians, which were already smaller in pain-free conditions (Day1) compared to non-musicians (p=0.021), remained non-significantly different across days. Notably, corticomotor responses (map volume, MEP amplitude, and RMTs) at Day1 were correlated to weekly and accumulated musical training. These findings demonstrate that pre-existing use-dependent plasticity associated with motor training may counteract the effects of prolonged pain in the motor system. Moreover, it confirms that prior motor experience acts as a source of individual variability to pain.

neuroscience↗

Modelling of brain dynamics reveals reduced switching between brain states in insomnia disorder - a resting state fMRI study

Insomnia disorder is the most common sleep disorder, and neuroimaging research indicates that it is related to dysfunction in large-scale brain networks. Recently developed methods have enabled the investigation of the dynamic aspects of brain activity varying over time. In the present study, we used a novel data-driven approach to evaluate time-varying brain activity in adults with insomnia disorder compared to matched controls with no sleep problems. We acquired ten minutes resting state functional magnetic resonance images and T1-weighed images in all participants. We used Hidden Markov modelling for a data-driven definition of dynamic changes in whole-brain activity. The results showed that insomnia disorder is characterised by reduced switching rates between brain states. In line with the reduced switching, the HMM analyses suggested reduced prevalence of two whole-brain states - the default mode network and a fronto-parietal network - and an increase in just one brain state - a global activation state - in insomnia patients compared to controls. The findings suggest that insomnia disorder is characterised by less flexible transitions between brain states at wakeful rest, and thus highlight the importance of evaluating the spatiotemporal dynamics of brain activity to advance the understanding of the neural underpinnings of insomnia disorder.

neuroscience↗

Individual differences in the effects of musical familiarity and musical features on brain activity during relaxation

Finding a way to relax is increasingly difficult in our overstimulating modern society and chronic stress can have severe psychological and physiological consequences. Music is a promising tool to promote relaxation by lowering heart rate, modulating mood and thoughts, and providing a sense of safety. Here, we used functional magnetic resonance imaging (fMRI) to investigate how music influence brain activity during relaxation with a particular focus on the participants experience of different types of music. In a 2x2 design, 57 participants were scanned while rating how relaxed they felt after listening to 28-second excerpts of either familiar or unfamiliar relaxation music with calm or energetic features. Behaviourally, calm music was the strongest predictor of relaxation, followed by familiar music. fMRI results revealed activations of auditory, motor, emotion, and memory areas, for listening to familiar compared to unfamiliar music. This suggests increased audio-motor synchronization and participant engagement of known music. Listening to unfamiliar music was correlated with attention-related brain activity, suggesting increased attentional load for this music. Behaviourally, we identified four clusters of participants based on their relaxation response to the different types of music. These groups also displayed distinct auditory and motor activity patterns, suggesting that the behavioural responses are linked to changes in music processing. Interestingly, some individuals found energetic music to be relaxing if it is familiar, whereas others only found calm music to be relaxing. Such individual behavioural and neurological differences in relaxation responses to music emphasise the importance of developing personalised music-based interventions. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=123 SRC="FIGDIR/small/625650v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@34ccc0org.highwire.dtl.DTLVardef@6e7f84org.highwire.dtl.DTLVardef@75d428org.highwire.dtl.DTLVardef@1bb999d_HPS_FORMAT_FIGEXP M_FIG C_FIG Highlights- Participants listen to relaxation tracks varying in familiarity and energy levels - Sedative music followed by familiar music increased relaxation ratings the most - Auditory, motor, memory and attention activations depending on the music type - 4 distinct clusters of behavioural responses to familiar or sedative music - These groups are also present in brain activity

neuroscience↗

The neural mechanisms of concept formation over time in music

The interplay between abstraction, learning and memory is crucial for humans to interact with the environment. Abstraction in relation to concept formation is typically studied with Gestalt stimuli varying in their physical properties while maintaining abstract internal relations. The role of temporal integration in recognising abstract concepts has been, however, overlooked even in a sensory domain relying on temporal item succession such as audition. Here, we investigated the neural mechanisms underlying abstract concept generalisation over time using a musical adaptation of the old/new recognition paradigm. During magnetoencephalography (MEG) recordings, 108 participants categorised five-tone sequences as previously learned or novel or as musical or not. The sequences varied in pace, ranging from very fast (125 ms per sound) to very slow (5000 ms per sound). On the behavioural level, sequence duration exerted a substantial impact on the recognition and musicality judgments of the novel sequences. The differences in neural responses between memorised and novel sequences especially involved regions in the auditory cortex, medial cingulate gyrus and medial temporal lobe and were most pronounced at the highest musical pace, diminishing proportionally as the pace decreased. These findings contribute to our understanding of how the brain generalises and derives meaning from abstract concepts that unfold over time learned through the auditory system.

neuroscience↗

BROADband brain Network Estimation via Source Separation (BROAD-NESS)

Auditory memory enables the recognition of sound sequences by integrating sensory input with memory traces and predictive mechanisms. While predictive coding has been proposed as a key framework for this process, the large-scale brain networks supporting it remain poorly understood. Using BROADband brain Network Estimation via Source Separation (BROAD-NESS), we provide three fundamental insights into the neural organisation of auditory memory and predictive coding. First, auditory cortices participate in two distinct, orthogonal whole-brain networks, expanding on the conventional view focused on forward and backward information flow between single brain regions. One network involves the medial cingulate gyrus, while the other integrates prefrontal and hippocampal regions, inferior temporal cortex, and insula. Second, we present evidence for a dual-stream mechanism in auditory memory recognition, which both parallels and diverges from the well-established dual-stream hypothesis in vision. Third, predictive coding in conscious auditory memory is supported by large-scale networks generating confirmed predictions and prediction errors. While previous studies examined predictive coding in isolated regions or pairwise connections, our findings reveal how whole-brain networks coordinate these processes, highlighting fine-grained spatial gradients and distinct temporal dynamics. These findings enhance our understanding of auditory perception, memory, and prediction, as well as their underlying basis in whole-brain dynamical networks.

neuroscience↗

Working memory predicts long-term recognition of auditory sequences: Dissociation between confirmed predictions and prediction errors

Memory is a crucial cognitive process involving several subsystems: sensory memory (SM), short-term memory (STM), working memory (WM), and long-term memory (LTM). While each has been extensively studied, the interaction between WM and LTM, particularly in relation to predicting temporal sequences, remains largely unexplored. This study investigates the relationship between WM and LTM, and how these relate to aging and musical training. Using three datasets with a total of 244 healthy volunteers across various age groups, we examined the impact of WM on LTM recognition of novel and previously memorized musical sequences. Our results show that WM abilities are significantly related to recognition of novel sequences, with a more pronounced effect in older compared to younger adults. In contrast, WM did not similarly impact the recognition of memorized sequences, which implies that different cognitive processes are involved in handling prediction errors compared to confirmatory predictions, and that WM contributes to these processes differently. Additionally, our findings confirm that musical training enhances memory performance. Future research should extend our investigation to populations with cognitive impairments and explore the underlying neural substrates.

neuroscience↗

FREQuency-resolved brain Network Estimation via Source Separation (FREQ-NESS)

The brain is a dynamic system whose network organization is often studied by focusing on specific frequency bands or anatomical regions, leading to fragmented insights, or by employing complex and elaborate methods that hinder straightforward interpretations. To address this issue, a new analytical pipeline named FREQuency-resolved Network Estimation via Source Separation (FREQ-NESS) is introduced. This is designed to estimate the activation and spatial configuration of simultaneous brain networks across frequencies by analyzing the frequency-resolved multivariate covariance between whole-brain voxel time series. FREQ-NESS is applied to source-reconstructed magnetoencephalography (MEG) data during resting state and isochronous auditory stimulation. Results reveal simultaneous, frequency-specific brain networks during resting state, such as the default mode, alpha-band, and motor-beta networks. During auditory stimulation, FREQ-NESS detects: (1) emergence of networks attuned to the stimulation frequency, (2) spatial reorganization of existing networks, such as alpha-band networks shifting from occipital to sensorimotor areas, (3) stability of networks unaffected by auditory stimuli. Furthermore, auditory stimulation significantly enhances cross-frequency coupling, with the phase of attuned auditory networks modulating the gamma band amplitude of medial temporal lobe networks. In conclusion, FREQ-NESS effectively maps the brains spatiotemporal dynamics, providing a comprehensive view of brain function by revealing simultaneous, frequency-resolved networks and their interaction.

neuroscience↗

The neurophysiology of healthy and pathological aging: A comprehensive systematic review

As the population of older adults grows, so does the prevalence of neurocognitive disorders such as mild cognitive impairment (MCI) and dementia. While biochemical, genetic, and neuroimaging biomarkers have accelerated early detection and diagnosis, neurophysiological measures are absent from daily medical use. Electroencephalography (EEG) and magnetoencephalography (MEG) are two non-invasive techniques that measure neurophysiological signals in the brain and convey information about signal strength at different frequency bands, event-related activity, signal complexity, and temporal correlation between spatially remote brain regions. Here we conducted a pre-registered, comprehensive systematic review of 942 studies using EEG, MEG, and combined MEG and EEG to characterise the neurophysiology of healthy aging, MCI, and dementia under resting-state and task conditions. To complement our search, we also reviewed 51 past reviews in the field. Relevant features of these papers were extracted to present a detailed overview of the current state of evidence. Overall, neurophysiological measures show great promise as diagnostic tools and could prove invaluable in predicting healthy and pathological aging trajectories. However, to reach this potential in clinical practice, it is crucial to adopt longitudinal designs, standardise methodologies, and identify biomarkers at the individual rather than group level.

neuroscience↗

Multilevel irreversibility reveals higher-order organisation of non-equilibrium interactions in human brain dynamics

Information processing in the human brain can be modelled as a complex dynamical system operating out of equilibrium with multiple regions interacting nonlinearly. Yet, despite extensive study of the global level of non-equilibrium in the brain, quantifying the irreversibility of interactions among brain regions at multiple levels remains an unresolved challenge. Here, we present the Directed Multiplex Visibility Graph Irreversibility framework, a method for analysing neural recordings using network analysis of time-series. Our approach constructs directed multi-layer graphs from multivariate time-series where information about irreversibility can be decoded from the marginal degree distributions across the layers, which each represents a variable. This framework is able to quantify the irreversibility of every interaction in the complex system. Applying the method to magnetoencephalography recordings during a long-term memory recognition task, we quantify the multivariate irreversibility of interactions between brain regions and identify the combinations of regions which showed higher levels of non-equilibrium in their interactions. For individual regions, we find higher irreversibility in cognitive versus sensorial brain regions whilst for pairs, strong relationships are uncovered between cognitive and sensorial pairs in the same hemisphere. For triplets and quadruplets, the most non-equilibrium interactions are between cognitive-sensorial pairs alongside medial regions. Finally, for quintuplets, our analysis finds higher irreversibility when the prefrontal cortex is included in the interaction. Combining these results, we show that multilevel irreversibility offers unique insights into the higher-order, hierarchical organisation of neural dynamics and presents a new perspective on the analysis of brain network dynamics.

biophysics↗

Neurophysiological correlates of short-term recognition of sounds: Insights from magnetoencephalography

Understanding the brains dynamic retrieval and updating of encoded information is a key focus in memory research. This study employed a same versus different auditory paradigm to investigate short-term auditory recognition within a predictive coding (PC) framework, concerning the perceptual interplay between experience-informed predictions and incoming sensory information. Using magnetoencephalography (MEG), we captured the neurophysiological correlates associated with a single-sound, short-term memory task. Twenty-six healthy participants were tasked with recognizing whether presented sounds were same or different compared to strings of standard stimuli. To prompt conscious memory retention, a white noise interlude separated these sounds from the standards. MEG sensor-level results revealed that recognition of same sounds elicited two significantly stronger negative components of the event-related field compared to different sounds. The first one was the N1, peaking 100ms post-sound onset, while the second one corresponded to a slower negative component arising between 300 and 600ms after sound onset. This effect was observed in several significant clusters of MEG sensors, especially temporal and parietal regions of the scalp. Conversely, different sounds produced scattered and smaller clusters of stronger activity than same sounds, peaking later than 600ms after sound onset. Source reconstruction using beamforming algorithms revealed the involvement of auditory cortices, hippocampus, and cingulate gyrus in both conditions. Overall, the results are coherent with PC principles and previous results on the brain mechanisms underlying auditory recognition, highlighting the relevance of early and later negative brain responses for successful prediction of previously listened sounds in the context of conscious short-term memory.

neuroscience↗

Decoding reveals the neural representation of held and manipulate musical thoughts

Vividly imagining a song or a melody is a skill that many people accomplish with relatively little effort. However, we are only beginning to understand how the brain represents, holds, and manipulates these musical "thoughts". Here, we decoded perceived and imagined melodies from magnetoencephalography (MEG) brain data (N = 71) to characterize their neural representation. We found that, during perception, auditory regions represent the sensory properties of individual sounds. In contrast, a widespread network including fronto-parietal cortex, hippocampus, basal nuclei, and sensorimotor regions hold the melody as an abstract unit during both perception and imagination. Furthermore, the mental manipulation of a melody systematically changes its neural representation, reflecting volitional control of auditory images. Our work sheds light on the nature and dynamics of auditory representations, informing future research on neural decoding of auditory imagination.

neuroscience↗

Challenging age-related decline in brain function: Evidence from fast neuroimaging of musical sequence recognition

Aging is often associated with decline in brain processing power and neural predictive capabilities. To challenge this notion, we used the excellent temporal resolution of magnetoencephalography (MEG) to record the whole-brain activity of 39 older adults (over 60 years old) and 37 young adults (aged 18-25 years) during recognition of previously memorised and novel musical sequences. Our results demonstrate that independent of behavioural measures, older compared to young adults showed increased rapid auditory cortex responses (around 100 and 250 ms after each tone of the sequence) and decreased later responses (around 250 and 350 ms) in hippocampus, ventromedial prefrontal cortex and inferior frontal gyrus. Working memory abilities were associated with stronger brain activity for both young and older adults. Our findings unpick the complexity of the healthy aging brain, showing age-related neural transformations in predictive and memory processes and challenging simplistic notions that non-pathological aging merely diminishes neural predictive capabilities.

neuroscience↗

Decreased inter-hemispheric connectivity predicts a coherent retrieval of auditory symbolic material in a laboratory model of cultural transmission

Investigating the transmission of information between individuals is essential to understand how human culture evolved. Coherent information transmission (i.e., transmission without significant modifications or loss of fidelity) helps preserving cultural traits and traditions over time, while innovation may lead to new cultural variants. Although much research has focused on the cognitive mechanisms underlying cultural transmission, little is known on the brain underpinnings of coherent transmission of information. To address this gap, we combined a laboratory model of cultural transmission, the signalling games, with structural (from high-resolution diffusion imaging) and functional connectivity (from resting-state functional magnetic resonance imaging [fMRI]). We found that individuals who exhibited more coherence in the transmission of the information were characterized by lower levels of both structural and functional inter-hemispheric connectivity. Specifically, higher coherence negatively correlated with the strength of bilateral structural connections between frontal and subcortical, insular and temporal brain regions. Similarly, we observed increased inter-hemispheric functional connectivity between inferior frontal brain regions derived from structural connectivity analysis in individuals who exhibited lower transmission coherence. Our results suggest that inter-hemispheric connections may bwe detrimental for preserving coherence in information transmission, while a certain degree of lateralization in the brain may be required.

neuroscience↗

Hierarchical syntax models of music predict theta power during music listening

Linguistic research showed that the depth of syntactic embedding is reflected in brain theta power. Here, we test whether this also extends to non-linguistic stimuli, specifically music. We used a hierarchical model of musical syntax to continuously quantify two types of expert-annotated harmonic dependencies throughout a piece of Western classical music: prolongation and preparation. Prolongations can roughly be understood as a musical analogue to linguistic coordination between constituents that share the same function (e.g., pizza and pasta in I ate pizza and pasta). Preparation refers to the dependency between two harmonies whereby the first implies a resolution towards the second (e.g., dominant towards tonic; similar to how the adjective implies the presence of a noun in I like spicy...). Source reconstructed MEG data of sixty-eight participants listening to the musical piece was then analysed. We used Bayesian Mixed Effects models to predict theta envelope in the brain, using the number of open prolongation and preparation dependencies as predictors whilst controlling for audio envelope. We observed that prolongation and preparation both carry independent and distinguishable predictive value for theta band fluctuation in key linguistic areas such as the Angular, Supramarginal, Superior Temporal and Heschls Gyri, or their right-lateralised homologues, with preparation showing additional predictive value for areas associated with the reward system and prediction. Musical expertise further mediated these effects in language-related brain areas. Results show that predictions of precisely formalised music-theoretical models are reflected in the brain activity of listeners.

neuroscience↗