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

Learning new words is an increasingly common necessity in everyday life. External factors, among which music and social interaction are particularly debated, are claimed to facilitate this task. Due to their influence on the learner’s temporal behavior, these stimuli are able to drive the learner’s attention to the correct referent of new words at the correct point in time. However, do music and social interaction impact learning behavior in the same way? The current study aims to answer this question. Native German speakers (N = 80) were requested to learn new words (pseudo-words) during a contextual learning game. This learning task was performed alone with a computer or with a partner, with or without music. Results showed that music and social interaction had a different impact on the learner’s behavior: Participants tended to temporally coordinate their behavior more with a partner than with music, and in both cases more than with a computer. However, when both music and social interaction were present, this temporal coordination was hindered. These results suggest that while music and social interaction do influence participants’ learning behavior, they have a different impact. Moreover, impaired behavior when both music and a partner are present suggests that different mechanisms are employed to coordinate with the two types of stimuli. Whether one or the other approach is more efficient for word learning, however, is a question still requiring further investigation, as no differences were observed between conditions in a retrieval phase, which took place immediately after the learning session. This study contributes to the literature on word learning in adults by investigating two possible facilitating factors, and has important implications for situations such as music therapy, in which music and social interaction are present at the same time.