Marja-Leena Linne

Dr.Tech., Docent

Biography

As an electrical engineer with PhD in information technology, I have combined biology and engineering to become an electrophysiologist and computational neuroscientist. The biophysically and biochemically detailed computational models of neural systems developed by me and by my research group explain the various types of neurotransmission and neuroplasticity observed in vitro and in vivo and promote our understanding of complex phenomena emerging in the brain circuitry. I am part of the EU FET Flagship Human Brain Project through the competitive call in 2013.

I am leading Computational Neuroscience Research Group  at Tampere University of Technology (TUT), Department of Signal Processing (SGN). I am also Coordinator of the INCF National Node of Finland in 2010-2015. 

I also work actively in many scientific organizations in my field. I am an elected board member of international organization OCNS. I also work actively in the Training Committees of INCF and FENS which promote integration of in vitro/vivo and in silico studies in neuroscience.

I have research experience and track record in computational neuroscience, biophysics, and cellular and tissue level electrophysiology, as well as in computational systems biology. I graduated seven Ph.D.s and supervised two postdoctoral researchers and several M.Sc. and B.Sc. theses as primary supervisor appointed by the faculty. I have taught undergraduate and graduate level courses in computational neuroscience, neuroinformatics, cellular electrophysiology, cell biology and digital and signal processing.

My research contributions include both experimental and computational studies to better understand the bioelectrical and biochemical phenomena underlying information processing in neural cells and in small-scale networks in the brain. The work has involved  developing new methods, including new stochastic simulation techniques to model cellular excitability. In addition, I have done extensive work on comparative evaluation of algorithms, tools, and computational models in the fields of computational neuroscience and computational systems biology.

Over the past couple of years, I have extended my studies to include modeling of neuronal growth and activity to better understand the relationship between structure and function in neuronal networks in vitro. I am also interested in the role of glial cells in the information processing and learning.

In addition to computational work, I have experience and track record in using primary and secondary cell cultures (e.g. cerebellar granule cell and cortical cell cultures, SH-SY5Y neuroblastoma cell cultures, glial-neuronal co-cultures) and electrophysiological recordings techniques (e.g. single-channel patch clamp, whole-cell patch clamp, two-electrode voltage clamp, and microelectrode arrays on cultured cells).