On Having No Head: Cognition throughout Biological Systems

Abstract

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.

Keywords: aneural; bioelectric signaling; cognition; computation; information; learning; memory; plants.

FIGURE 1

A scale of cognitive levels. There are many types of cognition, from simple reflexive behaviors all the way to systems that can internally model themselves and their environment to compute counterfactuals and make complex choices. Various biological systems can be considered cognitive to the extent that modeling them at one of these levels provides improved (more accurate or efficient) predictive and control capabilities. Reproduced from Rosenblueth et al. (1943).

FIGURE 2

Parallelism between neural and somatic computational systems. Complex, flexible, goal-seeking behavior (A) is implemented by information processing in the brain (B), which consists of networks of electrically communicating neural cells networks executing physiological circuits (C), which operate because of electrically gated ion channel and electrical synapse proteins (D). Similarly, large-scale goal-directed pattern remodeling and regeneration (E) occurs via bioelectric gradients that coordinate cell activity (F), implemented by physiological circuits in non-neural cells (G) which operate because of the same set of ion channels and electrical synapses (H). The behavior of these systems at the lowest level is achieved by regulating gap junction state and ion channel activity in specific cells (I). Circuit activity is beginning to be tractable in both contexts using optogenetics (J). In behavioral settings, the most effective path toward desired outcomes is to interact with the system at the highest level, rewarding for desired behavior (K). This strategy remains to be tried in patterning contexts, where the current paradigm has been focused on bottom–up approaches and has not yet investigated the top–down strategies that have paid off so well for cognitive science. (A–H) drawn by Alexis Pietak. (I,K) drawn by Jeremy Guay of Peregrine Creative. (J) used with permission from Liu et al. (2014).

FIGURE 3

Cognition at multiple, nested levels of biological organization. Information processing, memory, and flexible decision-making is exhibited by biological systems such as chemical networks, cytoskeletal dynamics, neural networks, tissue, and organ physiological circuits, entire organisms during behavior or pattern formation, and groups of organisms in colonies. The cytoskeleton panel is used with permission from Craddock et al. (2012). Graphic created by Jeremy Guay of Peregrine Creative.