Transitions in cognitive evolution

Abstract

The evolutionary history of animal cognition appears to involve a few major transitions: major changes that opened up new phylogenetic possibilities for cognition. Here, we review and contrast current transitional accounts of cognitive evolution. We discuss how an important feature of an evolutionary transition should be that it changes what is evolvable, so that the possible phenotypic spaces before and after a transition are different. We develop an account of cognitive evolution that focuses on how selection might act on the computational architecture of nervous systems. Selection for operational efficiency or robustness can drive changes in computational architecture that then make new types of cognition evolvable. We propose five major transitions in the evolution of animal nervous systems. Each of these gave rise to a different type of computational architecture that changed the evolvability of a lineage and allowed the evolution of new cognitive capacities. Transitional accounts have value in that they allow a big-picture perspective of macroevolution by focusing on changes that have had major consequences. For cognitive evolution, however, we argue it is most useful to focus on evolutionary changes to the nervous system that changed what is evolvable, rather than to focus on specific cognitive capacities.

Moral considerability of brain organoids from the perspective of computational architecture

“…As such, the biological processes that implement cognition have undergone significant reorganizations across evolutionary time. Barron and colleagues propose a theory to explain these major transitions, which they argue ‘should be identified [through] structural changes in the systems that implement cognition’ [ 35 ]. The authors propose five ‘computational architectures’ that are defined by how basic operations, representations, memory, and control flows are managed [ 36 ].…”

“…Control flow is particularly important, the authors claim, because it determines how different parts of the nervous system coordinate, share information, and influence one another. ‘Hence changes in control flow are important for determining what specific cognitive capacities are evolvable’ once a new architecture has been established [ 35 ]. Evidence for any given architecture should provide clues as to what kinds of cognitive processes an organoid might be able to implement under appropriate experimental conditions.…”

“…Neural ensembles responsible for different capacities can process information in parallel with varying temporal and spatial scales. This enables ‘the abstraction of information, operating with sequences of information or the production of complex sequences of behavior, and forward modeling of the consequences of action’ [ 35 ]. The same information can be multiplexed for distinct purposes, including valence processing, memory retrieval, association, and motor coordination.…”

“…Taken together, an evolutionary and computational perspective could help situate next generation HBOs within a broader theory of how cognition emerges, and evolves, from the organizing principles of neural systems. Specifically, Barron and colleagues offer a theory to explain major transitions in cognitive evolution that, as I will argue, could be used as a heuristic for determining the epistemological criteria for moral consideration of brain organoids [ 35 ]. They speculate that foundational changes in how neural systems control the flow of information were necessary for new cognitive-phenotypic spaces to open up for selection to act on and propagate new cognitive capacities along evolutionary lineages.…”

From empirical problem-solving to theoretical problem-finding perspectives on the cognitive sciences

“…These are just examples of some problem-inducing constraints which happen to have broad applicability. Related constraints under the general 'plausibility' umbrella are evolvability (Barron, Halina, & Klein, 2023;Brown, 2014;Kaznatcheev, 2019;Rich, Blokpoel, de Haan, & van Rooij, 2020), learnability (Angluin, 1992), and developability (Abouheif et al, 2014;Laland et al, 2015), among others (see Blokpoel, 2018, for a similar overview of theoretical constraints on explanations of cognitive capacities). Many other types exist, of various levels of generality and applicability.…”