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Articles

Cognitive systems and the changing brain

Pages 224-241 | Received 17 Mar 2017, Accepted 17 Mar 2017, Published online: 05 May 2017
 

Abstract

The notion of cognitive system is widely used in explanations in cognitive psychology and neuroscience. Traditional approaches define cognitive systems in an agent-relative way, that is, via top-down functional decomposition that assumes a cognitive agent as starting point. The extended cognition movement challenged that approach by questioning the primacy of the notion of cognitive agent. In response, [Adams, F., and K. Aizawa. 2001. The Bounds of Cognition. Oxford, UK: Wiley-Blackwell.] suggested that to have a clear understanding of what a cognitive system is we may need to solve “the demarcation challenge”: the problem of identifying a reliable way to determine which mechanisms that are causally responsible for the production of a certain cognitive process constitute a cognitive system responsible for such process and which ones do not. Recently, [Rupert, R. 2009. Cognitive Systems and the Extended Mind. Oxford: Oxford University Press.] offered a solution based on the idea that the mechanisms that constitute a cognitive system are integrated in a particular sense. In this paper I critically review Rupert’s solution and argue against it. Additionally, I argue that a successful account of cognitive system must accommodate the fact that the neural mechanisms causally responsible for the production of a cognitive process are diachronically dynamic and yet functionally stable. At the end, I offer a suggestion as to how to accommodate this diachronic dynamicity without losing functional stability. I conclude by drawing some implications for the discussion on cognitive ontologies.

Acknowledgments

Special thanks to Matthew Stanley for discussions on previous drafts. Thanks also to three reviewers for their suggestions.

Disclosure statement

No potential conflict of interest was reported by the author.

Notes on contributor

Felipe De Brigard is Assistant Professor in the departments of Philosophy, Psychology and Neuroscience, and the Center for Cognitive Neuroscience at Duke University. He also directs the Imagination and Modal Cognition Laboratory associated with the Duke Institute for Brain Sciences. His research centers on the interaction between memory and imagination, particularly counterfactual thinking, and it has been published in philosophical, psychological and neuroscientific venues.

Notes

1. Since, presumably, most cognitive tasks would have engaged many mn at some point or another, actual chance is probably way below .5.

2. Notice that there is a complicated issue here having to do with how are we to individuate cognitive tasks. I am assuming that remembering the address of the MoMA is an instance of the larger cognitive task of retrieving semantic information. As such, the cognitive system that supports Inga's retrieval of the MoMA's address would be the cognitive system that supports retrieval of semantic information, maybe even the cognitive system for semantic memory, rather than a cognitive system for remembering addresses or museum locations. However, as we will see, this turns out to be a huge assumption, likely not determinable in the bottom-up way of Rupert's proposal.

3. Here I am over-simplifying, of course, by equating brain region to brain mechanism. At best, a region is a proxy for a mechanism, but not identical to it. However, for the sake of the argument, I am going to overlook the important yet difficult issue of what is the precise relationship between a brain region and a brain mechanism. 

4. I’m not implying that fMRI studies alone can tell us which brain regions or mechanisms are necessary for bringing about a certain task. To infer necessity we need much more than neuroimaging; we probably would need experiments involving neuro-interventions, neurospsychological testing, neural and behavioral dissociations, etc. But, as mentioned before (endnote 3), for the sake of the argument I am using these hypothetical BOLD signal changes as idealized measures of a mechanism's engagement during a task.

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