Explore dynamical consequences of neurostimulation using neural mass modeling Computational Neurology

Description

Personalization of neurostimulation can improve its efficacy whilst taking into account the increasing complexity of the corresponding technology and the amount of technical choices (regarding stimulation location and stimulation settings). In this project we aim to create a whole-brain neural mass model that can accurately predict the effect of different neurostimulation settings in healthy and neurologically impaired individuals.

Prerequisites: Python programming, completed courses on computational neuroscience

The Institut für Neuroinformatik (INI) is a interdisciplinary research unit of the Ruhr-Universität Bochum. We aim to understand fundamental principles that characterize how organisms generate behavior and cognition while linked to their environments through sensory and effector systems. Inspired by insights into natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental approaches from psychology and neurophysiology, theoretical approaches from physics, mathematics, and computer science, including, in particular, machine learning, artificial intelligence, autonomous robotics, and computer vision.

Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany

Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210