Learning Outside the Brain: Integrating Cognitive Science and Systems Biology

Abstract

Learning is commonplace in organisms such as ourselves and even in organisms as far distant as the bee and the octopus. Such learning is implemented by brains, or neuronal networks, and has been extensively studied within ethology, psychology, cognitive science, and neuroscience.Whether learning also takes place in nonneuronal settings has remained a matter of sustained controversy, too often dominated by ideological views. In this survey, I will explain how learning can be rigorously interpreted as a form of information processing and then explore the evidence for whether learning also takes place in organismal contexts outside the brain, such as physiology, development, and individual cells. I will try to explain why it is important to build bridges in this way between cognitive science and systems biology, why concepts and methods from various branches of engineering may be helpful in this task, and what the eventual impact may be on how we think about the organism.

Emergent Simplicities in Stochastic Intergenerational Homeostasis

“…Perhaps this is the most startling and elegant simplicity of all. While excitement has been building around the general possibility that single cells may serve as useful arenas for exploring the phenomenology of learning without neurons [35, 36], our work here shows that the bacterial cell size, under balanced growth conditions, is not a repository of cellular memory, and therefore cannot serve as a diffuse living brain with a capacity for learning on intergenerational timescales.…”

An integrative systems biology view of host-pathogen interactions: The regulation of immunity and homeostasis is concomitant, flexible, and smart

“…(Epigenetic here means simply “non-genetic”.) The implication was that single cells have the computational capabilities for complex learning [see also references 226-231 in ( 60 )]. It was proposed that cells of all types are not only programmed to respond to signals, that is, to “information”, but also participate in the definition of information while sensing each other’s activities ( 2 ).…”

“…The goal is to categorize biochemical activity in the environment in terms of the most regular patterns and to generate, dynamically, a phenotypic mapping of those that can be used later ( 2 ). A contemporary article on biological learning, aiming at conceptually integrating cognitive science and systems biology, essentially rephrases (and greatly expands and elaborates) this concept: a cell (or a more complex biological “agent”) implements information processing that involves the construction of a representation, or internal model, of its environment ( 60 ).…”

“…While general interest in integrating cognitive science and systems biology is increasing ( 60 – 62 ), sporadic, longstanding efforts to conceptualize the immune system as a cognitive system [e.g., ( 2 , 24 , 37 , 45 )] and to tentatively define cell learning algorithms [e.g ( 1 , 9 , 21 – 23 )] remain largely overlooked by mainstream immunologists (prompting Jeremy Gunawardena to make the not-entirely precise statement that “immunologists have not felt the urge, so far, to draw on the resources of cognitive science”). We now overview some of these efforts.…”

“…In the immune system, associative learning would be linked to intrinsic cellular tunability, not limited to receptor expression ( 23 ). Obviously, temporal association as such is ill-defined and is only one of several characteristics defining “features” that cells require in order to generate a useful phenotypic mapping, or representation, of their environment ( 2 , 60 ). [For a useful glossary of terms from learning theory, such as associative memory, see reference ( 66 )]…”