Neural correlates of instance complexity


Quantification of cognitive resource requirements is relevant for understanding the allocation of limited resources during the decision-making process. Many models have been put forward in this domain. In general, these models involve a trade-off in which the system (either a biological organism or an electronic computer) maximises an objective function that incorporates both a benefit and a cost.

In this project we study how decision-makers estimate the cognitive resources required to make a particular decision. It is an open question how people solve this problem, which needs to be addressed in order to develop an overarching model of resource allocation in the brain.

Using functional MRI and the knapsack problem, we tested whether instance complexity is encoded in the brain and, if this is the case, how it is encoded.


Can humans detect instance complexity?
How is instance complexity encoded in the brain?

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