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  An information-theoretic perspective on the costs of cognition

Zénon, A., Solopchuk, O., & Pezzulo, G. (2019). An information-theoretic perspective on the costs of cognition. Neuropsychologia, 123, 5-18. doi:10.1016/j.neuropsychologia.2018.09.013.

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Zénon, A, Author
Solopchuk, O1, Author           
Pezzulo, G, Author
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1External Organizations, ou_persistent22              

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 Abstract: In statistics and machine learning, model accuracy is traded off with complexity, which can be viewed as the amount of information extracted from the data. Here, we discuss how cognitive costs can be expressed in terms of similar information costs, i.e. as a function of the amount of information required to update a person's prior knowledge (or internal model) to effectively solve a task. We then examine the theoretical consequences that ensue from this assumption. This framework naturally explains why some tasks - for example, unfamiliar or dual tasks - are costly and permits to quantify these costs using information-theoretic measures. Finally, we discuss brain implementation of this principle and show that subjective cognitive costs can originate either from local or global capacity limitations on information processing or from increased rate of metabolic alterations. These views shed light on the potential adaptive value of cost-avoidance mechanisms.

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 Dates: 2019-02
 Publication Status: Published in print
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Title: Neuropsychologia
Source Genre: Journal
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Publ. Info: Oxford : Pergamon
Pages: - Volume / Issue: 123 Sequence Number: - Start / End Page: 5 - 18 Identifier: ISSN: 0028-3932
CoNE: https://pure.mpg.de/cone/journals/resource/954925428258