Summary
Motion and cognition share an evolutionary history, as evidenced by the neuronal responses corresponding to the same areas when movement and the thought of movement occur. Given that cognition occurs not only in the head but is also embodied, studying movement might be a direct way of understanding cognitive processes in organisms. Movement has been studied as an output of mental processes and a mediator and predictor of cognition. It has also been used as a measure of executive functions and as a way of understanding spatial cognition. As suggested by other authors, studying behavior through movement might help describe the components of the cognitive algorithms that operate when movement occurs.We find it essential to focus on studying movement not merely as a causal relationship between brain activity and behavior but as an active component of a cognitive process, all of this working under anActive Inference framework. By using deep learning algorithms such as DeepLabCut and Keypoint-Moseq to analyze human interaction with objects and the environment, we can describe how movement provides a clue to how humans relate to and understand the materials they have built, shaping their understanding of the environment. As part of the XSCAPE ERC Synergy Grant Project (ERC-2020-SyG 951631), the Material Minds Lab, we research the intricate relationship between human interaction with materials and the environment and its profound impact on our perception of the world. Through the study of movement combined with other methodologies, we explore how ancient societies organized themselves based onthe materials they crafted, and how our cognition is intertwined with these artifacts.
Keywords
Embodied cognition. Movement. Active Inference. Human-environment interaction.