Thank you for visiting this repository! Bellow you can find some information about this project:
We aim to raise awareness about algorithmic decision-making in the field of neuroscience by building an open curriculum
As the amount and complexity of data collected in neuroscience increases, advanced algorithmic techniques have become imperative for analysing them. In particular, machine learning (ML) is used to infer intentions based on neural activity, in an attempt to control external devices. Algorithmic decisions can majorly improve the lives of patients suffering from neurological disorders, e.g. through neural implants that automatically detect and stop epileptic seizures before they occur, or by enabling communication in individuals who cannot control their bodies.
While the use of algorithms has an enormous potential for bringing positive change, this comes with a huge cost, as algorithms are often treated as a black box.
In interdisciplinary fields such as neuroscience, there is often a gap in expertise, as researchers come from very diverse fields as psychology vs. engineering. As a result, researchers from less computational fields might be using algorithms without fully understanding their assumptions, while researchers who are developing algorithms may not be fully aware of the social and ethical implications of their use (i.e. privacy, stigma).
The main goal of this proposal is to raise awareness about the use of algorithmic decision-making in the field of neuroscience by building an open resource. This will consist of material and tutorials on the appropriate use of ML and signal-processing techniques for analysing neuroscientific data. The resource will comprise of a mixture of theory and hands-on exercises, aiming at making computational techniques accessible to all academic and citizen scientists.
Behind this project there is an interdisciplinary team of people working in neuroscience, electrical engineering and computer engineering. Some of the main contributors are:
- Athina Tzovara: I am a neuroscientist, working at the University of Bern. In my research I am using computational and electrophysiological techniques to study human cognition, while advocating open science and open education.
- Elpiniki:
- Pinar:
- Samuel Gerster:
We welcome new contributions and ideas! Here you can find the roadmap of this project and here the issues we're currently working on.
You're very welcome to join our slack channel for any questions or new ideas!