Computerized physical and cognitive training improves the functional architecture of the brain in adults with Down syndrome: A network science EEG study

Author:

Anagnostopoulou Alexandra1,Styliadis Charis1ORCID,Kartsidis Panagiotis1,Romanopoulou Evangelia1,Zilidou Vasiliki1,Karali Chrysi2,Karagianni Maria1,Klados Manousos3,Paraskevopoulos Evangelos14,Bamidis Panagiotis D.1ORCID

Affiliation:

1. Medical Physics Laboratory, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Greece

2. School of Biology, Faculty of Science, Aristotle University of Thessaloniki, Greece

3. Department of Psychology, The University of Sheffield International Faculty, City College, Thessaloniki, Greece

4. Department of Psychology, University of Cyprus, Nicosia, Cyprus

Abstract

Understanding the neuroplastic capacity of people with Down syndrome (PwDS) can potentially reveal the causal relationship between aberrant brain organization and phenotypic characteristics. We used resting-state EEG recordings to identify how a neuroplasticity-triggering training protocol relates to changes in the functional connectivity of the brain’s intrinsic cortical networks. Brain activity of 12 PwDS before and after a 10-week protocol of combined physical and cognitive training was statistically compared to quantify changes in directed functional connectivity in conjunction with psychosomatometric assessments. PwDS showed increased connectivity within the left hemisphere and from left-to-right hemisphere, as well as increased physical and cognitive performance. Our findings reveal a strong adaptive neuroplastic reorganization as a result of the training that leads to a less-random network with a more pronounced hierarchical organization. Our results go beyond previous findings by indicating a transition to a healthier, more efficient, and flexible network architecture, with improved integration and segregation abilities in the brain of PwDS. Resting-state electrophysiological brain activity is used here for the first time to display meaningful relationships to underlying Down syndrome processes and outcomes of importance in a translational inquiry. This trial is registered with ClinicalTrials.gov Identifier NCT04390321.

Publisher

MIT Press - Journals

Subject

Applied Mathematics,Artificial Intelligence,Computer Science Applications,General Neuroscience

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