Cognitive enrichment through art: a randomized controlled trial on the effect of music or visual arts group practice on cognitive and brain development of young children.

BACKGROUND: The optimal stimulation for brain development in the early academic years remains unclear. Current research suggests that musical training has a more profound impact on children's executive functions (EF) compared to other art forms. What is crucially lacking is a large-scale, long-term genuine randomized controlled trial (RCT) in cognitive neuroscience, comparing musical instrumental training (MIP) to another art form, and a control group (CG). This study aims to fill this gap by using machine learning to develop a multivariate model that tracks the interconnected brain and EF development during the academic years, with or without music or other art training. METHODS: The study plans to enroll 150 children aged 6-8 years and randomly assign them to three groups: Orchestra in Class (OC), Visual Arts (VA), and a control group (CG). Anticipating a 30% attrition rate, each group aims to retain at least 35 participants. The research consists of three analytical stages: 1) baseline analysis correlating EF, brain data, age, gender, and socioeconomic status, 2) comparison between groups and over time of EF brain and behavioral development and their interactions, including hypothesis testing, and 3) exploratory analysis combining behavioral and brain data. The intervention includes intensive art classes once a week, and incremental home training over two years, with the CG receiving six annual cultural outings. DISCUSSION: This study examines the potential benefits of intensive group arts education, especially contrasting music with visual arts, on EF development in children. It will investigate how artistic enrichment potentially influences the presumed typical transition from a more unified to a more multifaceted EF structure around age eight, comparing these findings against a minimally enriched active control group. This research could significantly influence the incorporation of intensive art interventions in standard curricula. TRIAL REGISTRATION: The project was accepted after peer-review by the Swiss National Science Foundation (SNSF no. 100014_214977) on March 29, 2023. The study protocol received approval from the Cantonal Commission for Ethics in Human Research of Geneva (CCER, BASEC-ID 2023-01016), which is part of Swiss ethics, on October 25, 2023. The study is registered at clinicaltrials.gov (NCT05912270).

PRoNTo: pattern recognition for neuroimaging toolbox.

In the past years, mass univariate statistical analyses of neuroimaging data have been complemented by the use of multivariate pattern analyses, especially based on machine learning models. While these allow an increased sensitivity for the detection of spatially distributed effects compared to univariate techniques, they lack an established and accessible software framework. The goal of this work was to build a toolbox comprising all the necessary functionalities for multivariate analyses of neuroimaging data, based on machine learning models. The "Pattern Recognition for Neuroimaging Toolbox" (PRoNTo) is open-source, cross-platform, MATLAB-based and SPM compatible, therefore being suitable for both cognitive and clinical neuroscience research. In addition, it is designed to facilitate novel contributions from developers, aiming to improve the interaction between the neuroimaging and machine learning communities. Here, we introduce PRoNTo by presenting examples of possible research questions that can be addressed with the machine learning framework implemented in PRoNTo, and cannot be easily investigated with mass univariate statistical analysis.

EEG anomalies in adult ADHD subjects performing a working memory task.

Functional imaging studies have revealed differential brain activation patterns in attention deficit hyperactivity disorder (ADHD) adult patients performing working memory (WM) tasks. The existence of alterations in WM-related cortical circuits during childhood may precede executive dysfunctions in this disorder in adults. To date, there is no study exploring the electrophysiological activation of WM-related neural networks in ADHD. To address this issue, we carried out an electroencephalographic (EEG) activation study associated with time-frequency (TF) analysis in 15 adults with ADHD and 15 controls performing two visual N-back WM tasks, as well as oddball detection and passive fixation tasks. Frontal transient (phasic) theta event-related synchronization (ERS, 0-500 msec) was significantly reduced in ADHD as compared to control subjects. Such reduction was equally present in a task-independent manner. In contrast, the power of the later sustained (∼500-1200 msec) theta ERS for all tasks was comparable in ADHD and control groups. In active WM tasks, ADHD patients displayed lower alpha event-related desynchronization (ERD, ∼200-900 msec) and higher subsequent alpha ERS (∼900-2400 msec) compared to controls. The time course of alpha ERD/ERS cycle was modified in ADHD patients compared to controls, suggesting that they are able to use late compensatory mechanisms in order to perform this WM task. These findings support the idea of an ADHD-related dysfunction of neural generators sub-serving attention directed to the incoming visual information. ADHD cases may successfully face WM needs depending on the preservation of sustained theta ERS and prolonged increase of alpha ERS at later post-stimulus time points.