Cells in our bodies sense and process information from their local tissue environment in order to adaptively respond to stimuli. We hypothesise that positive feedback between changes in cell shape (movement) and cell receptors (signalling) dynamically adapt the sensory interface of the cell, aiding information processing and cell decision-making. This idea, known as sensorimotor coupling, is the basis of active perception, a widely studied process in the fields of neuroscience, robotics and psychology that is known to enhance decision-making and other cognitive tasks in higher organisms. Currently, in cell biology, cell sensing (signalling) and motion (movement) are largely investigated independently, using different experimental assays and techniques, such that the level of coupling between these processes has been hard to measure. Here, we propose to investigate sensorimotor coupling in individual cells using a framework employing the information-based measure transfer entropy. Through agentbased computational modelling, we demonstrate its sensitivity to levels of coupling in a variety of simulated cell perturbations. To facilitate biological application, we use cellular readouts that we demonstrate are feasible to measure in real biological cells in vitro. Overall, this work highlights the potential of information theory to quantitatively investigate biological cell function, paving the way for translating theoretical developments to experimental biology.

Endothelial cells (ECs), which line our blood vessels, exhibit dramatic plasticity and diversity of form/behavior at the individual and collective cell level. They re-organize themselves in space and time to extend new blood vessel networks during development and during a huge array of diseases including cancer. Here we will describe, using examples from our integrated in silico/in vitro/in vivo research program, how the Artificial Life (ALife) perspective and approaches have been paramount in driving entirely new experimental biology understanding of the vasculature by capitalizing on the emergent, predictive capacity and testable nature of agent-based models in close combination with in vitro and in vivo experiments. Our agent-based simulations explicitly consider the role of individual EC embodiment, active perception, heterogeneous vs homogeneous collective dynamics, pattern formation and counter-intuitive emergence from feedback in controller networks and many more Alife centric concepts. We recently identified in silico that the time it takes ECs to collectively decide who should move and who should stay during blood vessel branching morphogenesis can be varied by altering tissue environment conditions, including some changes found in tumors. By proceeding to validate these predictions in vitro and in vivo by integrating the studies in the wetlab we have been able to provide a solid new mechanism to explain the diversity of vascular network structures found across tissues and the malformations arising in disease. There is a bright future with untapped potential for the Alife community to further contribute to understanding of animals, including humans, at the cell and tissue level, where many organizational principles of the systems behavior are still lacking. If we take care to be rigorous in how we calibrate our models to biological data and make clear experimentally testable predictions, we will show we can make real change in a experimental cell biology field, traditionally segregated from in silico research. Learning from the plight of the insightful, but ostracized, Androids in Philip K Dicks novel, overcoming our cultural differences and integrating better between the artificial and natural living systems research communities could lead to huge advantages in achieving our common goals to understand life as it is.