Why do neuroscientists perform experiments with language models?

Abstract

This paper examines why neuroscientists in the 2020s are using large language models rather than brains as research subjects, from temporal, systemic, and career-oriented perspectives. First, we reviewed the evolution of neuroscience into big science and the development of integrated data platforms since the 2010s. Next, as a new movement, we discussed the emergence of representation alignment and NeuroAI, which use pre-trained DNNs including large language models as research targets and platform. Furthermore, we introduced our research on quantifying psychological constructs using language models and discussed its significance as analytical platform of psychological constructs. Through this, we explore the potential of pre-trained DNN as a new research method in neuroscience and consider the career turning point faced by early-career (neuro)scientists.