From Neuroelectrodynamics to Thinking Machines

Endogenous Bioelectric Signaling Networks: Exploiting Voltage Gradients for Control of Growth and Form

Living systems exhibit remarkable abilities to self-assemble, regenerate, and remodel complex shapes. How cellular networks construct and repair specific anatomical outcomes is an open question at the heart of the next-generation science of bioengineering. Developmental bioelectricity is an exciting emerging discipline that exploits endogenous bioelectric signaling among many cell types to regulate pattern formation. We provide a brief overview of this field, review recent data in which bioelectricity is used to control patterning in a range of model systems, and describe the molecular tools being used to probe the role of bioelectrics in the dynamic control of complex anatomy. We suggest that quantitative strategies recently developed to infer semantic content and information processing from ionic activity in the brain might provide important clues to cracking the bioelectric code. Gaining control of the mechanisms by which large-scale shape is regulated in vivo will drive transformative advances in bioengineering, regenerative medicine, and synthetic morphology, and could be used to therapeutically address birth defects, traumatic injury, and cancer.

On Having No Head: Cognition throughout Biological Systems

The central nervous system (CNS) underlies memory, perception, decision-making, and behavior in numerous organisms. However, neural networks have no monopoly on the signaling functions that implement these remarkable algorithms. It is often forgotten that neurons optimized cellular signaling modes that existed long before the CNS appeared during evolution, and were used by somatic cellular networks to orchestrate physiology, embryonic development, and behavior. Many of the key dynamics that enable information processing can, in fact, be implemented by different biological hardware. This is widely exploited by organisms throughout the tree of life. Here, we review data on memory, learning, and other aspects of cognition in a range of models, including single celled organisms, plants, and tissues in animal bodies. We discuss current knowledge of the molecular mechanisms at work in these systems, and suggest several hypotheses for future investigation. The study of cognitive processes implemented in aneural contexts is a fascinating, highly interdisciplinary topic that has many implications for evolution, cell biology, regenerative medicine, computer science, and synthetic bioengineering.

Molecular bioelectricity: how endogenous voltage potentials control cell behavior and instruct pattern regulation in vivo

In addition to biochemical gradients and transcriptional networks, cell behavior is regulated by endogenous bioelectrical cues originating in the activity of ion channels and pumps, operating in a wide variety of cell types. Instructive signals mediated by changes in resting potential control proliferation, differentiation, cell shape, and apoptosis of stem, progenitor, and somatic cells. Of importance, however, cells are regulated not only by their own V_mem but also by the V_mem of their neighbors, forming networks via electrical synapses known as gap junctions. Spatiotemporal changes in V_mem distribution among nonneural somatic tissues regulate pattern formation and serve as signals that trigger limb regeneration, induce eye formation, set polarity of whole-body anatomical axes, and orchestrate craniofacial patterning. New tools for tracking and functionally altering V_mem gradients in vivo have identified novel roles for bioelectrical signaling and revealed the molecular pathways by which V_mem changes are transduced into cascades of downstream gene expression. Because channels and gap junctions are gated posttranslationally, bioelectrical networks have their own characteristic dynamics that do not reduce to molecular profiling of channel expression (although they couple functionally to transcriptional networks). The recent data provide an exciting opportunity to crack the bioelectric code, and learn to program cellular activity at the level of organs, not only cell types. The understanding of how patterning information is encoded in bioelectrical networks, which may require concepts from computational neuroscience, will have transformative implications for embryogenesis, regeneration, cancer, and synthetic bioengineering.