I finished my studies at the Helsinki University of Technology (TKK) in spring 2006. I studied electrical engineering at the Department of electrical and communication engineering. Still, I have always been interested in the incredible cognitive abilities - as well as weaknesses - of a human being. Because of that I chose to study Cognitive Technology as my major subject. My major has given me insight into human information processing, communication, emotions and neurocognitive mechanisms behind them. Moreover, I chose Biomedical Engineering to my minor subject in order to further deepen my understanding of modern brain research, medical engineering and the rapidly evolving technology behind these interesting fields.
I started at LCE on May 2005 as a summer treinee and from Septemper on I worked on my master's thesis. During the summer 2005 I worked in collaboration with Ville Mannari studying cortical feature extraction in visual cortical areas. Our main interest was low level visual feature extraction and for that reason we focused mainly on primary visual cortex(V1). We strongly believe that one good way to gain deeper and more fruitful understanding about cortical information processing is to put traditional neuroanatomical and -physiological approaches and computational approach into strong and open interraction. This kind of method or approach to study cortical information processing is called computational neuroscience. During the summer I mainly concentrated to explore the current knowledge about the neuroanatomy and -physiology of the cortex while Ville paid more attention on the mathematical feature extraction model we call Biologically Inspired Feature Extraction Model(BIFEM). From Septemper 2005 on I worked on my master's thesis but the research of the BIFEM continued by the other members of the group.
The goal of my master's thesis was to design and define a controller that is able to make predictions from input data. The controller implemented and introduced in my master's thesis is at many points inspired by the current knowledge about cerebellar system because the cerebellar system of vertebrates is known to act as a system that can learn to predict reflexes from the signals that it receives through its input channel called mossy fibers. The controller is a top-down model of cerebellum meaning that the main aim of the model is not to mimic the neuroanatomical structure of cerebellum or the neurophysiological properties of the neurons in as much detail as possible. Rather, the aim of the model is to catch the phenomenas of the cerebellum that are found in many psychophysical experiments like in classical eye-blink conditioning. Take a closer look at my thesis and download it from here.
From spring 2006 on I have worked for GE Healthcare Finland.