Task-independent metrics of computational hardness predict human cognitive performance

7Citations
Citations of this article
12Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

The survival of human organisms depends on our ability to solve complex tasks in the face of limited cognitive resources. However, little is known about the factors that drive the complexity of those tasks. Here, building on insights from computational complexity theory, we quantify the computational hardness of cognitive tasks using a set of task-independent metrics related to the computational resource requirements of individual instances of a task. We then examine the relation between those metrics and human behavior and find that they predict both time spent on a task as well as accuracy in three canonical cognitive tasks. Our findings demonstrate that performance in cognitive tasks can be predicted based on generic metrics of their inherent computational hardness.

References Powered by Scopus

A behavioral model of rational choice

9031Citations
N/AReaders
Get full text

brms: An R package for Bayesian multilevel models using Stan

5770Citations
N/AReaders
Get full text

Mental rotation of three-dimensional objects

4396Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Harnessing Computational Complexity Theory to Model Human Decision-making and Cognition

2Citations
N/AReaders
Get full text

A human-like artificial intelligence for mathematics

1Citations
N/AReaders
Get full text

Estimating self-performance when making complex decisions

0Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Franco, J. P., Doroc, K., Yadav, N., Bossaerts, P., & Murawski, C. (2022). Task-independent metrics of computational hardness predict human cognitive performance. Scientific Reports, 12(1). https://doi.org/10.1038/s41598-022-16565-w

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 3

43%

Professor / Associate Prof. 2

29%

Lecturer / Post doc 1

14%

Researcher 1

14%

Readers' Discipline

Tooltip

Psychology 2

40%

Computer Science 1

20%

Neuroscience 1

20%

Engineering 1

20%

Article Metrics

Tooltip
Mentions
News Mentions: 5

Save time finding and organizing research with Mendeley

Sign up for free