Abstract

Meaning has traditionally been regarded as a problem for philosophers and psychologists. Advances in cognitive science since the early 1960s, however, broadened discussions of meaning, or more technically, the semantics of perceptions, representations, and/or actions, into biology and computer science. Here, we review the notion of “meaning” as it applies to living systems, and argue that the question of how living systems create meaning unifies the biological and cognitive sciences across both organizational and temporal scales.

Highlights

  • The “problem of meaning” in biology can be traced to the Cartesian doctrine that animals are automata, and that humans are automata controlled by spirits

  • The general turn from metaphysics toward language in mid-20th-century philosophy further reinforced this Cartesian division by localizing the study of meaning within the study of language, understood as human natural language characterized by a recursive grammar, and arbitrarily-large lexicon, and an associated collection of interpretative practices

  • Human cognition was widely assumed within the representationalist cognitive science that largely replaced behaviorism from the 1960s onward to replicate this tripartite structure of public natural language, either because it was implemented in an underlying “language of thought” or “mentalese” having a expressive syntax, semantics, and pragmatics [1], or because it was implemented by natural language itself [2]

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Summary

Introduction

The “problem of meaning” in biology can be traced to the Cartesian doctrine that animals are automata, and that humans are automata (bodies) controlled by spirits (minds). We use the term “living system” instead of “organism” in formulating these questions to emphasize their generality: we ask these questions of living systems at all scales, from signal transduction pathways within individual cells to communities, ecosystems, and extended evolutionary lineages In addressing these questions, we build on our previous work on memory in biological systems [35] and on evolution and development as informational processes operating on multiple scales [36,37]. We explicitly consider the self-representations implemented by humans [52,53,54,55], and suggest that locating the self-representations operative in other organisms and in sub- or supra-organismal systems represents a key challenge to the Life Sciences [24] We integrate these themes from an evolutionary perspective, suggesting that meaning is itself a multi-scale phenomenon that characterizes all living systems, from molecular processes to Life on Earth as a whole. The fundamental goal of the Life Sciences is, from this perspective, to understand how living systems create meaning

Meanings Require Reference Frames
System—Environment Interaction as Information Exchange
Meaning for Escherichia coli
Implementing RFs Requires Energy
RFs Are State-Space Attractors
RFs Set Bayesian Expectations
Only Meaningful Differences Are Detectable
The Evolution of Meaning Is the Evolution of RFs
From Multi-Component States to Objects
Objects as Reference Frames
Embedding Objects in Space
Embedding Objects in Time
Active Inference Requires Attention
What Is the RF for Salience?
Salience Allocation Differences Self-Amplify
How Are Memories Stored and Accessed?
Heritable Memories Encode Morphology and Function
Experiential Memories and Learning
Reconsidering the Cognitive Role of Grammatical Language
How Do Living Systems Represent Themselves?
Conclusion
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