Disciplines/fields: Neuroimaging, Neurophysiology, Cognitive Neuroscience, Pathophysiology, Pattern Recognition

Duration: 4 sessions

Course Content

Neural development during human childhood and adolescence as well as neurodegeneration during adulthood involves highly coordinated and sequenced events, characterized by both progressive (e.g., cell growth and myelination) and regressive processes (e.g., cell death and atrophy). Neurodegenerative diseases such as Alzheimer's disease or schizophrenia alter brain structures in diverse and abnormal modes.

The course will give an overview over transformation mechanisms and patterns in human brain structure during the life course and the pathological cascade of neurodegenerative diseases as well as its functional / cognitive correlates. Based on the neuroanatomical changes, the course will also deal with computational approaches to model those structural transformations to study potential variables affecting individual trajectories, monitoring treatment studies, and predict future trajectories.

Objectives

We aim to understand which transformations within the human brain structure occur during (1) normal maturation and (2) aging, but also in (3) neurodegenerative diseases, like schizophrenia and Alzheimer’s disease. Further, we aim (4) to link those transformations to functional performances (e.g. cognition) as well as (5) to model transformations in brain structure with the help of pattern recognition techniques.

Literature

Easy-to-read introduction (in German):
BrainAGE – Wie alt sieht mein Gehirn aus? Bild der Wissenschaft plus, Oktober 2014. http://www.klaus-tschira-preis.info/download/2014/bdw_Tschira_2014-1.pdf
Scientific background:
Bennett KP & Campbell C (2003). Support vector machines: hype or hallelujah? SIGKDD Explorations, 2, 1-13.
Franke, K (2014). BrainAGE – A novel machine learning approach for identifying abnormal age-related brain changes. Südwestdeutscher Verlag für Hochschulschriften.
Jagust W & D’Esposito M (2009). Imaging the Aging Brain. Oxford: University Press.
Tipping ME (2000). The Relevance Vector Machine. In: SA Solla, TK Leen, & KR Müller (Eds.) Advances in Neural Information Processing Systems 12, MIT Press: Cambridge, MA: 652-658.
Toga, AW, Thompson PM, Sowell ER (2006). Mapping Brain Maturation. Trends in Neurosciences, 29(3): 148-159.

Vita

1996 – 2004 Diploma studies in Psychology at the University of Halle, Germany

1999 – 2001 International MA program „Psychology of Excellence“ at the University of Munich, Germany

2004 – 2007 Research assistant at the ZNL (Transfer centre for neurosciences and learning), University of Ulm, Germany

2007 – 2013 Research assistant in the Structural Brain Mapping Group, University Hospital Jena, Germany

2011 – 2013 PhD studies in Cognitive Neuroscience at the University of Zurich, Switzerland

since 2013 Post-Doc in the Structural Brain Mapping Group, University Hospital Jena, Germany

Link

http://www.neuro.uni-jena.de/