Open Neural Data


In November 2022 the International Brain Laboratory has released an unprecedented Big Open data set with brain recordings. In an international collaboration between 12 different research groups neural activity in 194 different brain regions (that's basically all of them!) was recorded in mice performing a standardized decision-making task. The data contains activity of 32784 neurons, which allows, for the first time, to examine how activity in any part of the brain is related to sensory, cognitive, and motor processing. For the published data the Open Neurophysiology Environment (ONE) API is available to access and process the different types of data files. In this computer programming practical you will learn about the research questions surrounding this exciting dataset and how to access and process the data. First, we will study the available documentation about the data set and the provided API, and learn the basics about brain recordings. Second, we will access and process the data so that it can be analysed. Finally, we will apply modern data science methods (such as clustering, dimensionality reduction, or computational statistics) to analyse the data and learn about information processing in the brain.

Learning Outcomes:
  • obtain hands-on skills in accessing and processing of Big Open Data
  • acquire relevant domain knowledge at the intersection of computer science and neuroscience
  • become familiar with neural signals and how they are processed using data science methods
  • visualize and interpret the results of data analysis


Exercises and reports during the semester



Course type
Lab courses
Summer Term 2023


Project seminar
Takes place every week on Thursday from 12:00 to 14:00 in room NB 3/57.
First appointment is on 06.04.2023
Last appointment is on 13.07.2023


Programming in Python, APIs

This practical course is suitable for Bachelor students.


Link to the IBL dataset:

The Institut für Neuroinformatik (INI) is a central research unit of the Ruhr-Universität Bochum. We aim to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory systems and while acting in those environments through effector systems. Inspired by our insights into such 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 as well as theoretical approaches from physics, mathematics, electrical engineering and applied computer science, in particular machine learning, artificial intelligence, and computer vision.

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

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