We investigated the relationships between perceptions of similarity and interaction in spontaneously dancing dyads, and movement features extracted using novel computational methods. We hypothesized that dancers’ movements would be perceived as more similar when they exhibited spatially and temporally comparable movement patterns, and as more interactive when they spatially oriented more towards each other. Pairs of dancers were asked to move freely to two musical excerpts while their movements were recorded using optical motion capture. Subsequently, in two separate perceptual experiments we presented stick figure animations of the dyads to observers, who rated degree of interaction and similarity between dancers. Mean perceptual ratings were compared with three different approaches for quantifying coordination: torso orientation, temporal coupling, and spatial coupling. Correlations and partial correlations across dyads were computed between each estimate and the perceptual measures. A systematic exploration showed that torso orientation (dancers facing more towards each other) is a strong predictor of perceived interaction even after controlling for other features, whereas temporal and spatial coupling (dancers moving similarly in space and in time) are better predictors for perceived similarity. Further, our results suggest that similarity is a necessary but not sufficient condition for interaction.

As music unfolds in time, structure is recognized and understood by listeners, regardless of their level of musical expertise. A number of studies have found spectral and tonal changes to quite successfully model boundaries between structural sections. However, the effects of musical expertise and experimental task on computational modelling of structure are not yet well understood. These issues need to be addressed to better understand how listeners perceive the structure of music and to improve automatic segmentation algorithms. In this study, computational prediction of segmentation by listeners was investigated for six musical stimuli via a real-time task and an annotation (non real-time) task. The proposed approach involved computation of novelty curve interaction features and a prediction model of perceptual segmentation boundary density. We found that, compared to non-musicians', musicians' segmentation yielded lower prediction rates, and involved more features for prediction, particularly more interaction features; also nonmusicians required a larger time shift for optimal

Introduction: There is evidence from earlier trials for the efficacy of music therapy in the treatment of depression among working-age people. Starting therapy sessions with relaxation and revisiting therapeutic themes outside therapy have been deemed promising for outcome enhancement. However, previous music therapy trials have not investigated this issue.Objective: To investigate the efficacy of two enhancers, resonance frequency breathing (RFB) and listening homework (LH), when combined with an established music therapy model (trial registration number ISRCTN11618310).Methods: In a 2 × 2 factorial randomised controlled trial, working-age individuals with depression were allocated into groups based on four conditions derived from either the presence or absence of two enhancers (RFB and LH). All received music therapy over 6 weeks. Outcomes were observed at 6 weeks and 6 months. The primary outcome was the Montgomery Åsberg Depression Rating Scale (MADRS) score.Results: There was a significant overall effect of treatment for the primary outcome favouring the breathing group (d = 0.50, 95% CI 0.07 to 0.93, p = 0.02). The effect was larger after adjustment for potential confounders (d = 0.62, 95% CI 0.16 to 1.08, p = 0.009). Treatment effects for secondary outcomes, including anxiety (anxiety scale of Hospital Anxiety and Depression Scale) and quality of life (RAND-36), were also significant, favouring the breathing group. The homework enhancer did not reach significant treatment effects.Conclusion: We found that the addition of RFB to a music therapy intervention resulted in enhanced therapeutic outcome for clients with depression.

Background Depression is among the leading causes of disability worldwide. Not all people with depression respond adequately to standard treatments. An innovative therapy that has shown promising results in controlled trials is music therapy. Based on a previous trial that suggested beneficial effects of integrative improvisational music therapy (IIMT) on short and medium-term depression symptoms as well as anxiety and functioning, this trial aims to determine potential mechanisms of and improvements in its effects by examining specific variations of IIMT. Methods/design A 2 × 2 factorial randomised controlled trial will be carried out at a single centre in Finland involving 68 adults with a diagnosis of depression (F32 or F33 in International Statistical Classification of Diseases and Related Health Problems 10th revision). All participants will receive 6 weeks of bi-weekly IIMT, where they are invited to improvise music and reflect on those improvisations with a music therapist in a one-to-one setting. Potential enhancements to IIMT will include: home-based listening to recorded improvisations (LH) from IIMT sessions to facilitate integration of therapeutic processing into daily life; and resonance frequency breathing (RFB), a breathing exercise at the beginning of each session to facilitate emotional expression and processing. Participants will be randomised in a 1:1:1:1 ratio into each combination (IIMT alone or with one or both enhancements). The primary outcome is depressive symptoms measured by the Montgomery–Åsberg Depression Rating Scale (MADRS) at 6 weeks. Secondary outcomes are depressive symptoms at 6 months; anxiety, quality of life, and functioning at 6 weeks and 6 months; and adverse events. Secondary underlying mechanisms/process variables are self-rated momentary depression level before every IIMT session; and homework compliance in IIMT + LH. Statistical analyses involve an intention-to-treat approach, using a linear mixed-effects model examining the main effects (LH vs no LH; RFB vs no RFB) and interaction effects (LH × RFB). Discussion This trial will contribute to understanding the mechanisms of IIMT and may further enhance the effectiveness of an intervention that was previously shown to be superior to standard care alone for adults with depression. Trial registration ISRCTN11618310 . Registered on 26 January 2018.

Cerebello-hippocampal interactions occur during accurate spatio-temporal prediction of movements. In the context of music listening, differences in cerebello-hippocampal functional connectivity may result from differences in predictive listening accuracy. Using functional magnetic resonance imaging (fMRI), we studied differences in this network between 18 musicians and 18 nonmusicians while they listened to music. Musicians possess a predictive listening advantage over nonmusicians facilitated by strengthened coupling between produced and heard sounds through lifelong musical experience. Thus, we hypothesized musicians would exhibit greater functional connectivity than nonmusicians as a marker of accurate online predictions during music listening. To this end, we estimated the functional connectivity between cerebellum and hippocampus as modulated by a perceptual measure of the predictability of the music. Results revealed increased predictability-driven functional connectivity in this network in musicians compared to nonmusicians, which was positively correlated with the length of musical training. Findings may be explained by musicians' improved predictive listening accuracy. Our findings advance the understanding of cerebellar integrative function.