Publications

Abstract

Humans can easily extract the rhythm of a complex sound, like music, and move to its regular beat, like in dance. These abilities are modulated by musical training and vary significantly in untrained individuals. The causes of this variability are multidimensional and typically hard to grasp in single tasks. To date we lack a comprehensive model capturing the rhythmic fingerprints of both musicians and non-musicians. Here we harnessed machine learning to extract a parsimonious model of rhythmic abilities, based on behavioral testing (with perceptual and motor tasks) of individuals with and without formal musical training (n = 79). We demonstrate that variability in rhythmic abilities and their link with formal and informal music experience can be successfully captured by profiles including a minimal set of behavioral measures. These findings highlight that machine learning techniques can be employed successfully to distill profiles of rhythmic abilities, and ultimately shed light on individual variability and its relationship with both formal musical training and informal musical experiences.

Abstract

The aim of this meta-analysis is twofold: (a) to assess cognitive impairments in isolated rapid eye movement (REM) sleep behavior disorder (iRBD) patients compared to healthy controls (HC); (b) to quantitatively estimate the risk of developing a neurodegenerative disease in iRBD patients according to baseline cognitive assessment. To address the first aim, cross-sectional studies including polysomnography-confirmed iRBD patients, HC, and reporting neuropsychological testing were included. To address the second aim, longitudinal studies including polysomnography-confirmed iRBD patients, reporting baseline neuropsychological testing for converted and still isolated patients separately were included. The literature search was conducted based on PRISMA guidelines and the protocol was registered at PROSPERO (CRD42021253427). Cross-sectional and longitudinal studies were searched from PubMed, Web of Science, Scopus, and Embase databases. Publication bias and statistical heterogeneity were assessed respectively by funnel plot asymmetry and using I2. Finally, a random-effect model was performed to pool the included studies. 75 cross-sectional (2,398 HC and 2,460 iRBD patients) and 11 longitudinal (495 iRBD patients) studies were selected. Cross-sectional studies showed that iRBD patients performed significantly worse in cognitive screening scores (random-effects (RE) model = –0.69), memory (RE model = –0.64), and executive function (RE model = –0.50) domains compared to HC. The survival analyses conducted for longitudinal studies revealed that lower executive function and language performance, as well as the presence of mild cognitive impairment (MCI), at baseline were associated with an increased risk of conversion at follow-up. Our study underlines the importance of a comprehensive neuropsychological assessment in the context of iRBD.

Abstract

A long-standing debate in cognitive neurosciences concerns the effect of music on verbal learning and memory. Research in this field has largely provided conflicting results in both clinical as well as non-clinical populations. Although several studies have shown a positive effect of music on the encoding and retrieval of verbal stimuli, music has also been suggested to hinder mnemonic performance by dividing attention. In an attempt to explain this conflict, we review the most relevant literature on the effects of music on verbal learning and memory. Furthermore, we specify several mechanisms through which music may modulate these cognitive functions. We suggest that the extent to which music boosts these cognitive functions relies on experimental factors, such as the relative complexity of musical and verbal stimuli employed. These factors should be carefully considered in further studies, in order to reliably establish how and when music boosts verbal memory and learning. The answers to these questions are not only crucial for our knowledge of how music influences cognitive and brain functions, but may have important clinical implications. Considering the increasing number of approaches using music as a therapeutic tool, the importance of understanding exactly how music works can no longer be underestimated.

Abstract

The auditory scene is a mental representation of individual sounds extracted from the summed sound waveform reaching the ears of the listeners. Musical contexts represent particularly complex cases of auditory scenes. In such a scenario, melody may be seen as the main object moving on a background represented by the accompaniment. Both melody and accompaniment vary in time according to harmonic rules, forming a typical texture with melody in the most prominent, salient voice. In the present sparse acquisition functional magnetic resonance imaging study, we investigated the interplay between melody and accompaniment in trained pianists, by observing the activation responses elicited by processing: (1) melody placed in the upper and lower texture voices, leading to, respectively, a higher and lower auditory salience; (2) harmonic violations occurring in either the melody, the accompaniment, or both. The results indicated that the neural activation elicited by the processing of polyphonic compositions in expert musicians depends upon the upper versus lower position of the melodic line in the texture, and showed an overall greater activation for the harmonic processing of melody over accompaniment. Both these two predominant effects were characterized by the involvement of the posterior cingulate cortex and precuneus, among other associative brain regions. We discuss the prominent role of the posterior medial cortex in the processing of melodic and harmonic information in the auditory stream, and propose to frame this processing in relation to the cognitive construction of complex multimodal sensory imagery scenes.