MADHD-NET : Multimodal ADHD prediction model with Brain connectivity Networks

In this project, a novel framework for MADHD-NET will be developed with EEG and eyetracking measures. The project also highlights the different connectivity networks for ADHD subjects with different attention levels (based on cognitive events) and age groups.

In Nordic countries including Sweden, awareness of Attention Deficit / Hyperactivity Disorder (ADHD) appears to be increasing, with higher reported rates of diagnosis and treatment in recent years [1]. Despite such increases, adults with ADHD may still be undertreated, and rates of treatment discontinuation in adolescents and young adults are higher than expected considering the persistence of the disorder in later life. It can be noted that from 2004 to 2014, the number of children diagnosed with ADHD has increased in Sweden [2]. Therefore, the primary purpose of this project is to integrate Electroencephalogram (EEG) and eye-tracking data to predict the attention levels of ADHD participants across different age groups through various cognitive tasks. Secondly, this project identifies brain connectivity patterns for ADHD participants to find out the information flow among brain regions, accelerating the future research scope of ADHD individuals in neuroscience, clinical, and biomedical engineering fields. Besides EEG and eye-tracking data, the cognitive and questionnaires-based measures highlight the manifestations of psychiatric behavior of ADHD participants.

1. Polyzoi, M., Ahnemark, E., Medin, E., & Ginsberg, Y. (2018). Estimated prevalence and incidence of diagnosed ADHD and health care utilization in adults in Sweden–a longitudinal population-based register study. Neuropsychiatric disease and treatment, 1149-1161.
2. Rydell, M., Lundström, S., Gillberg, C., Lichtenstein, P., & Larsson, H. (2018). Has the attention deficit hyperactivity disorder phenotype become more common in children between 2004 and 2014? Trends over 10 years from a Swedish general population sample. Journal of Child Psychology and Psychiatry, 59(8), 863-871.
3. Clarke AR, Barry RJ, McCarthy R, Selikowitz M. EEG Analysis of Children with Attention-Deficit/Hyperactivity Disorder and Comorbid Reading Disabilities. J Learn Disabil (2002) 35(3):276–85. 4. Szuromi, B., Czobor, P., Komlósi, S., & Bitter, I. (2011). P300 deficits i

Project leader: Foteini Simistira Liwicki

Funded by: Kempestiftelserna External link.

Project duration: 2025-2027