Bioelectric networks as determinants of biological growth and form: from pre-neural circuits to electroceuticals
Traumatic injury, birth defects, and even cancer and aging: most biomedical problems would be resolved if we had control over 3D living anatomy. In order to control what structures cells build, we need to understand how cellular collectives make decisions - how do groups of cells know what to build and when to stop? My lab works at the intersection of developmental biology, computer science, and cognitive science. By building molecular tools to read and write the bioelectric patterns in coupled cellular networks (all tissues, not specifically neurons), we have uncovered a fascinating system of physiological "software" that runs on genome-specified cellular hardware. These bioelectric networks store the setpoints for anatomical homeostasis, and serve as the primitive memory of the tissue for anatomical target morphology. We have shown how this information can be modified in vivo, to exert remarkable control over growth and form. We are now creating machine learning systems to assist with the design of electroceuticals - blends of ion channel drugs guided by computational models of bioelectric circuits that restore correct voltage prepatterns and lead to repair. Our computational and biophysical approaches to modulating bioelectrical pattern memories in vivo may contribute to the repair of birth defects, induction of limb regeneration, and tumor normalization.
Tufts University, Medford, MA, USA