Public defence in Computer Science, M.Sc. (Tech) Ana Maria Triana Hoyos

Title of the thesis: From Scans to Reality: Effects of Preprocessing and Daily Behavioral Patterns on fMRI Brain Connectivity

Doctoral student: Ana Maria Triana Hoyos
Opponent: Associate Professor Joaquín Goñi Cortés, Purdue University, Yhdysvallat
Custos: Professor Jari Saramäki, Aalto University School of Science, Department of Computer Science

The human brain, a complex and marvellous organ, continues to be a mystery in many ways. Although we have made significant strides in recent years thanks to technologies like functional magnetic resonance imaging (fMRI), many aspects of how the brain operates remain elusive. While there is hope that fMRI could help diagnose and predict outcomes for neurological disorders, the reality is that translating these findings from group studies to individual cases is challenging.

This thesis investigates the sources of variability that make this translation so difficult. It examines how the methods used to prepare fMRI data for study can introduce inconsistencies, and it explores the impact of daily activities such as sleep and physical exercise on brain function. This research is pioneering because it connects the dots between the controlled conditions of the lab and the unpredictable nature of daily life.

Our findings highlight the exciting possibilities that emerge when combining mobile technology like smartphones and wearables with brain imaging. This fusion allows us to monitor and analyze how everyday activities affect brain connectivity. We invite academics, healthcare professionals, and anyone interested in the evolving field of brain research to join us as we discuss how this research enhances our understanding of the human brain in its natural environment.

Key words: Brain connectivity, brain networks, fMRI, preprocessing, brain precision mapping, digital phenotyping, smartphones, wearable technology

Thesis available for public display 10 days prior to the defence at: https://aaltodoc.aalto.fi/doc_public/eonly/riiputus/ 

Contact information:

Doctoral theses of the School of Science: https://aaltodoc.aalto.fi/handle/123456789/52 

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