Cognitive ontology in terms of cognitive homology – The role of brain, behavior, and environment for individuating cognitive categories
By Beate Krickel and Mariel Goddu
How should we categorize the mind’s capacities? This is the cognitive ontology question: how to carve up cognition in a way that supports scientific prediction, explanation, and generalization. The answer matters: If we classify cognitive processes poorly, our theories and models of cognition risk confusion, redundancy, and missed connections.
There is now broad agreement among scientists and philosophers that many of our current cognitive categories—like “attention,” “memory,” and “perception”—are due for revision: they’re based on non-scientific, armchair introspection, and they are anthropocentric (human-focused). However, scholars disagree on both how deep of a revision is necessary and what role neuroscience should play in it.
Incremental approaches to cognitive ontology refine existing categories and are typically pursued top-down: first, the cognitive category is revised; then, the question of how these categories are realized in the brain is addressed. Radical approaches, by contrast, seek to replace the existing cognitive categories altogether. They usually take a bottom-up approach: they start from neural categories or neural data and try to derive cognitive categories from there.
In our recent article, we propose a novel, evolutionarily informed answer to the cognitive ontology question. Our approach retains an incremental, top-down structure, and it also highlights the importance of neuroscience for deriving cognitive categories. According to our approach, however, understanding brain data and brain anatomy is not enough: neuroscientific evidence must be considered in combination with the role that organism-environment interactions play in the development of cognitive capacities.
We suggest that cognitive ontology should be based on cognitive homologies: cognitive capacities that are “the same across species” in the evolutionary sense of homology. (For example, the bat’s wing, the human arm, and the whale’s flipper are homologous: they’re all versions of the same, evolutionarily conserved forearm structure.) There are at least two previous approaches to cognitive homology in the philosophical literature. However, we identify problems with each.
We then show that the challenges for these existing accounts can be avoided by making use of a recent account from philosophers James DiFrisco, Alan Love, and biologist Günter Wagner. Their account proposes a developmental notion of homology: traits are homologous if they develop as a result of the same “character identity mechanism,” or “ChIM.” (“Character” is another word for “trait.”) We apply the ChIM concept to cognition: cognitive capacities are homologous if they are due to the same cognitive ChIM.
What are ChIMs?Standard accounts of homology emphasize common ancestry, but they leave open the question of what stabilizes the identity of a trait across evolutionary time. Character identity mechanisms address this problem: ChIMs are developmental mechanisms that ensure the stability of trait identity across phylogeny. They have three key features:
- Mechanistic architecture: ChIMs are cohesive developmental mechanisms with a recognizable structure that explains why a trait remains traceable across evolution.
- Causal necessity and non-redundancy: They occupy the “knot” in a bowtie-like causal topology, where they are necessary for, and non-redundant in, producing the trait.
- Evolutionary conservation: Because of their causal role and mechanistic complexity, ChIMs are more likely to be conserved across lineages.
Extending this idea to cognition, we propose that cognitive ChIMs are developmental mechanisms by which organisms acquire cognitive capacities. If two species exhibit a cognitive capacity produced by the same cognitive ChIM, then they are homologous –– and thus the same capacity.
Consider the case of human syntax and birdsong. Both involve the production of patterned sequences for communication. Yet the capacities differ: human syntax is generative and compositional, while birdsong syntax is more limited and tied to specific behavioral contexts. So, are human syntax and birdsong different cognitive capacities, or two versions of the same capacity?
On our account, the decisive factor for answering this question is the developmental mechanism: Do the two capacities derive from the same cognitive ChIM? Only if they are due to the same trait-determining, causally necessary, and nonredundant developmental mechanism can they be considered the same cognitive capacity. Thus, we must ask: What are the necessary and non-redundant components in the developmental mechanisms for birdsong and for human syntax? And: Are these the same for both capacities?
There seem to be at least some important similarities between the developmental mechanisms for human syntax and birdsong at the neural level. For example, neurons in the caudomedial nidopallium (NCM) of songbirds play an essential role in song learning. Computational and physiological similarities have been identified between these neurons and cortical cell types in mammals. Furthermore, the development of human syntax and of birdsong share features at the behavioral level: both human syntax and birdsong depend on so-called “experience-expectant” input –– stimuli that are typically available (“expected”) in the organism’s environment ––during early life. Infants must hear language, and juvenile birds must hear adult songs. In both cases, the developing organism must also engage in practice — babbling or subsong — before fully acquiring the capacity.
To establish whether these similarities are sufficient to show that these two cognitive capacities are due to the same ChIM, more research (both empirical and theoretical) is needed. Empirically, all components that are necessary for humans to develop syntax and for birds to learn to produce songs must be identified. Then, one must establish whether these ChIMs share a common mechanistic architecture that stabilizes trait identity.
Although it is only a partial illustration, this example shows two important things. First, the developmental mechanisms for cognitive capacities do not merely involve neural components. They crucially involve learning, and thus, interactions between the organism and their environment. Second, even prima facie unrelated cognitive capacities—human syntax and birdsong—develop in strikingly similar ways.
Our cognitive ChIM approach to cognitive homology has three main implications:
- Neural mechanisms are indispensable, but not exclusive. Brain regions and processes matter, but they must be situated in developmental and ecological contexts.
- Learning is central. Many cognitive traits depend on experience-expectant input and practice, so cognitive ChIMs must include environmental and behavioral factors.
- Cognitive homology is fruitful for cognitive ontology. Cognitive ChIMs provide a principled way to decide when to unify or separate capacities across species, avoiding both premature lumping and arbitrary splitting.
Our article provided a proof of concept. We wanted to show that there is a sensible notion of cognitive homology, and that this notion provides a promising, interesting, and novel starting point for thinking about cognitive ontology. We will continue to develop this idea in further work.
A highly stimulating contribution that places the discussion on cognitive ontology on a new, evolutionarily grounded footing.
I particularly appreciate the proposal to define cognitive categories in terms of shared developmental mechanisms (ChIMs) rather than by phenomenological or functional similarity.
One possible extension would be to apply the principle of homology also within the individual system itself.
If ChIMs describe the diachronic stability of cognitive features across evolutionary timescales, one might ask whether analogous mechanisms exist synchronously within an organism — mechanisms responsible for the momentary integration of cognitive processes.
From this perspective, cognition would not only be the outcome of evolutionary conservation but also of an autocatalytic integrative process within the brain, leading to recursive self-coherence — a kind of internal “collapse” of causal structure that gives rise to conscious experience.
This suggests a complementary framework:
– Homology explains the continuity of cognitive mechanisms in evolution (ChIMs).
– Coherence explains their self-integration in the moment of experience (causal core / collapse).
Together, these principles could form a more complete theory of cognitive identity — one that unites phylogenetic stability with phenomenological emergence.