Development of theoretical frameworks in neuroscience: a pressing need in a sea of data

TL;DR

This paper emphasizes the urgent need for developing clear theoretical frameworks in neuroscience to better integrate data, improve understanding, and guide future research, especially in the context of AI and multi-scale analysis.

Contribution

It advocates for establishing common theoretical structures in neuroscience, detailing essential elements and identifying key areas requiring theoretical development.

Findings

Highlighting the importance of paradigms, models, and scales in theories

Identifying pressing needs in multi-scale integration and coding

Suggesting incorporation of evolutionary principles into theories

Abstract

Neuroscience is undergoing dramatic progress because of the vast data streams derived from the new technologies product of the BRAIN initiative and other enterprises. As any other scientific field, neuroscience benefits from having clear definitions of its theoretical components and their interactions. This allows generating theories that integrate knowledge, provide mechanistic insights, and predict results under new experimental conditions. However, theoretical neuroscience is a heterogeneous field that has not yet agreed on how to build theories or whether it is desirable to have an overarching theory or whether theories are simply tools to understand the brain. Here we advocate for the need of developing theoretical frameworks as a basis of generating common theoretical structures. We enumerate the elements of theoretical frameworks we deem necessary for any theory in neuroscience. In particular, we address the notions of paradigms, models, and scales of organizations. We then identify areas with pressing needs to develop brain theories: integration of statistical and dynamic approaches; multi-scale integration; coding; and interpretability in the context of Artificial Intelligence. We also point out that future theoretical frameworks would benefit from the incorporation of the principles of Evolution as a fundamental structure rather than purely mathematical or engineering principles. Rather than providing definite answers, the objective of this paper is to serve as an initial and succinct presentation of these topics to encourage discussion and further in depth development of each topic.