Short-Term Orchestral Music Training Modulates Hyperactivity and Inhibitory Control in School-Age Children: A Longitudinal Behavioural Study

Survey studies have shown that participating in music groups produces several benefits, such as discipline, cooperation and responsibility. Accordingly, recent longitudinal studies showed that orchestral music training has a positive impact on inhibitory control in school-age children. However, most of these studies examined long periods of training not always feasible for all families and institutions and focused on children’s measures ignoring the viewpoint of the teachers. Considering the crucial role of inhibitory control on hyperactivity, inattention and impulsivity, we wanted to explore if short orchestral music training would promote a reduction of these impulsive behaviors in children. This study involved 113 Italian children from 8 to 10 years of age. 55 of them attended 3 months of orchestral music training. The training included a 2-hour lesson per week at school and a final concert. The 58 children in the control group did not have any orchestral music training. All children were administered tests and questionnaires measuring inhibitory control and hyperactivity near the beginning and end of the 3-month training period. We also collected information regarding the levels of hyperactivity of the children as perceived by the teachers at both time points. Children in the music group showed a significant improvement in inhibitory control. Moreover, in the second measurement the control group showed an increase in self-reported hyperactivity that was not found in the group undergoing the music training program. This change was not noticed by the teachers, implying a discrepancy between self-reported and observed behavior at school. Our results suggest that even an intense and brief period of orchestral music training is sufficient to facilitate the development of inhibitory control by modulating the levels of self-reported hyperactivity. This research has implications for music pedagogy and education especially in children with high hyperactivity. Future investigations will test whether the findings can be extended to children diagnosed with ADHD

Learning to Change

A paper published over 20 years ago by Susan Iversen and Mortimer Mishkin on reversal learning continues to inform cognitive neuroscience toda

Balancing the Brain: Resting State Networks and Deep Brain Stimulation

Over the last three decades, large numbers of patients with otherwise treatment-resistant disorders have been helped by deep brain stimulation (DBS), yet a full scientific understanding of the underlying neural mechanisms is still missing. We have previously proposed that efficacious DBS works by restoring the balance of the brain's resting state networks. Here, we extend this proposal by reviewing how detailed investigations of the highly coherent functional and structural brain networks in health and disease (such as Parkinson's) have the potential not only to increase our understanding of fundamental brain function but of how best to modulate the balance. In particular, some of the newly identified hubs and connectors within and between resting state networks could become important new targets for DBS, including potentially in neuropsychiatric disorders. At the same time, it is of essence to consider the ethical implications of this perspective

Critical scaling of whole-brain resting-state dynamics

The online version contains supplementary material available at https://doi.org/10.1038/s42003-023-05001-y.Scale invariance is a characteristic of neural activity. How this property emerges from neural interactions remains a fundamental question. Here, we studied the relation between scale-invariant brain dynamics and structural connectivity by analyzing human resting-state (rs-) fMRI signals, together with diffusion MRI (dMRI) connectivity and its approximation as an exponentially decaying function of the distance between brain regions. We analyzed the rs-fMRI dynamics using functional connectivity and a recently proposed phenomenological renormalization group (PRG) method that tracks the change of collective activity after successive coarse-graining at different scales. We found that brain dynamics display power-law correlations and power-law scaling as a function of PRG coarse-graining based on functional or structural connectivity. Moreover, we modeled the brain activity using a network of spins interacting through large-scale connectivity and presenting a phase transition between ordered and disordered phases. Within this simple model, we found that the observed scaling features were likely to emerge from critical dynamics and connections exponentially decaying with distance. In conclusion, our study tests the PRG method using large-scale brain activity and theoretical models and suggests that scaling of rs-fMRI activity relates to criticality.A.P.-A. was supported by a Ramón y Cajal fellowship (RYC2020-029117-I) from FSE/Agencia Estatal de Investigación (AEI), Spanish Ministry of Science and Innovation. A.P.-A. and G.D. were supported by the EU Fet Flagship Human Brain Project SGA3 (945539). G.D. was supported by the Spanish Research Project AWAKENING (PID2019-105772GB-I00/AEI/10.13039/501100011033), financed by the Spanish Ministry of Science, Innovation and Universities (MCIU), State Research Agency (AEI). M.L.K. is supported by the Centre for Eudaimonia and Human Flourishing (funded by the Pettit and Carlsberg Foundations) and Center for Music in the Brain (funded by the Danish National Research Foundation, DNRF117).Peer ReviewedPostprint (published version

metastability and its dynamical cortical core

In the human brain, spontaneous activity during resting state consists of rapid transitions between functional network states over time but the underlying mechanisms are not understood. We use connectome based computational brain network modeling to reveal fundamental principles of how the human brain generates large-scale activity observable by noninvasive neuroimaging. We used structural and functional neuroimaging data to construct whole- brain models. With this novel approach, we reveal that the human brain during resting state operates at maximum metastability, i.e. in a state of maximum network switching. In addition, we investigate cortical heterogeneity across areas. Optimization of the spectral characteristics of each local brain region revealed the dynamical cortical core of the human brain, which is driving the activity of the rest of the whole brain. Brain network modelling goes beyond correlational neuroimaging analysis and reveals non-trivial network mechanisms underlying non-invasive observations. Our novel findings significantly pertain to the important role of computational connectomics in understanding principles of brain function

On screen experiment showed that becoming a parent for the first time shifted people's priorities from themselves to their infant at 1 year of age

ACKNOWLEDGEMENTS We are grateful to the student researchers who helped with the data collection. FUNDING INFORMATION This study was funded by The Center for Music in the Brain, which is funded by the Danish National Research Foundation (DNRF 117, awarded to PV). The project was further funded by an European Research Council Consolidator Grant CAREGIVING (no. 615539) to MLK.Peer reviewedPublisher PD

Sleep-deprived new mothers gave their infants a higher priority than themselves

ACKNOWLEDGEMENT Special thanks to all the student researchers who helped with the data collection over the years. FUNDING INFORMATION This study was funded by The Center for Music in the Brain which is funded by the Danish National Research Foundation (DNRF 117, awarded to PV). The project was further funded by a European Research Council Consolidator Grant CAREGIVING (No. 615539) to MLK.Peer reviewedPublisher PD