CMIC Seminar: On computer simulations of self-organization in brain development

Speaker: Roman Bauer, Institute of Neuroscience, Newcastle University
UCL Contact: Dominique Drai (Visitors from outside UCL please email in advance).
Date/Time: 18 Jan 17, 13:00 - 14:00
Venue: Roberts 421

Abstract

Based on the vast improvements of computing power in the last few years, it has become possible to conduct neuroscientific research using highly detailed models. These models often incorporate biologically plausible morphology and electrical activity patterns. However, one crucial aspect that has been neglected in many computational studies of the brain is its self-organizing development. Our brains are the result of a well-orchestrated developmental process that starts from a single precursor cell, the zygote.

In this talk I will argue that improving our understanding of neural development is a key ingredient for a deeper understanding of neural structure and function. The interaction between genetic rules and the extracellular environment is in the center of this investigation. In this context, I will present some of my work, which comprises agent-based models across different spatial scales (from local microcircuits to long-range axonal projections to interareal connectivity).

Roman Bauer

Roman Bauer is an MRC Skills Development Fellow at Newcastle University. He received his Bachelor's and Master's Degree in Computational Science and Engineering from ETH Zuerich, Switzerland. Afterwards, he did his doctoral studies at the Institute for Neuroinformatics (INI) at ETH and University Zuerich, working on computer simulations of brain development. He joined Newcastle University as an RA in September 2013, and started his MRC fellowship project in September 2016.

Roman Bauer’s research focus is on neural development. He devises and analyses computational and statistical models of how cortical and retinal tissue evolves during development, in order to better understand the dynamics leading to healthy and pathological states. These models incorporate the interaction between genetic rules and physical laws of the extracellular environment. Since such a detailed approach can be very demanding from a computational point of view, his research also involves modern computing approaches and IT-related collaboration.