Cell assembly detection in 3D bioprinted hiPSC neural constructs from Autism Spectrum Disorder patients

• Grant number: 25/23715-2
• Support Opportunities: Scholarships abroad - Research Internship - Post-doctor
• Start date: February 01, 2026
• End date: January 31, 2027
• Field of knowledge: Biological Sciences - Morphology - Cytology and Cell Biology
• Principal Investigator: Marimélia Aparecida Porcionatto
• Grantee: Cristiano Soares Simões
• Supervisor: Eleonora Russo
• Host Institution: Escola Paulista de Medicina (EPM). Universidade Federal de São Paulo (UNIFESP). Campus São Paulo. São Paulo , SP, Brazil
• Institution abroad: Scuola Superiore Sant'Anna, Italy
• Associated to the scholarship: 24/15729-0 - Electrophysiological correlates of ASD in hiPSC-derived bioprinted neural constructs, BP.PD

Abstract

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition associated with impaired connectivity during circuit formation. In the last few years, our group has consistently established a method to record high-resolution neuronal activity during cell maturation through three-dimensional bioprinted constructs derived from human induced pluripotent stem cells and multielectrode array technology. Still, maturing circuits pose significant challenges to connectivity analysis due to high non-stationarity of the signals and large variability in the temporal organization of firing patterns across developmental stages. Therefore, refined connectivity analysis techniques are required to extract reliable and meaningful connectivity-related electrical biomarkers from the acquired signals. Here our novel collaboration with the group of Dr. Eleonora Russo, at the Sant'Anna School for Advanced Studies (SSAS), Pisa, Italy, offers such an opportunity. Her group has developed a pioneering unsupervised machine-learning algorithm for cell assembly detection (CAD) that analyzes correlated firing patterns across several different time resolutions at once, accounting for non-stationary signal properties without excessive computational burden. The internship proposed here is a key step for the successful completion of the ongoing project in Brazil, since Dr. Russo's CAD technique can explore the full potential of our data in a way that no other method available in our lab can. The opportunity of working under close supervision of Dr. Russo will assure the best possible benefit from this technique and strengthen the collaboration between UNIFESP and SSAS, besides advancing translational research on ASD.