Tyrand, R. | bioRxiv Science

bioRxiv2023

Self-regulation of attention in children in a virtual classroom environment: a feasibility study

Attention is a crucial cognitive function that enables us to selectively focus on relevant information from the surrounding world to achieve our goals. When this sustained ability to direct attention is impaired, individuals face significant challenges in everyday life. This is the case for children with Attention Deficit Hyperactivity Disorder (ADHD), a complex neurodevelopmental disorder characterized by impulsive and inattentive behavior. While psychostimulant medications are currently the most effective treatment for ADHD, they often come with unwanted side effects, and sustaining the benefits can be difficult for many children. Therefore, it is imperative to explore non-pharmacological treatments that offer longer-lasting outcomes. Here, we proposed a groundbreaking protocol that combines electroencephalography-based neurofeedback (EEG-NFB) with virtual reality (VR) as an innovative approach to treating attention deficits. By integrating a virtual classroom environment, we aimed to enhance the transferability of attentional control skills while simultaneously increasing motivation and interest among children. The present study demonstrated the feasibility of this approach through an initial assessment involving a small group of healthy children, showcasing its potential for future evaluation in children diagnosed with ADHD. Encouragingly, the preliminary findings indicated high engagement rates and positive feedback from the children participating in the study. Additionally, the pre-and post-protocol assessments using EEG and fMRI recordings appeared to converge towards an improvement in attentional function. Although further validation is required to establish the efficacy of the proposed protocol, it represents a significant advancement in the field of neurofeedback therapy for ADHD. The integration of EEG-NFB and VR presents a novel avenue for enhancing attentional control and addressing behavioral challenges in children with ADHD.

neuroscience↗

bioRxiv2017

Focal Versus Distributed Temporal Cortex Activity For Speech Sound Category Assignment

Percepts and words can be decoded from largely distributed neural activity measures. The existence of widespread representations might, however, conflict with the fundamental notions of hierarchical processing and efficient coding. Using fMRI and MEG during syllable identification, we first show that sensory and decisional activity co-localize to a restricted part of the posterior superior temporal cortex. Next, using intracortical recordings we demonstrate that early and focal neural activity in this region distinguishes correct from incorrect decisions and can be machine-decoded to classify syllables. Crucially, significant machine-decoding was possible from neuronal activity sampled across widespread regions, despite weak or absent sensory or decision-related responses. These findings show that a complex behavior like speech sound categorization relies on an efficient readout of focal neural activity, while distributed activity, although decodable by machine-learning, reflects collateral processes of sensory perception and decision.

neuroscience↗