Toward a Formal Theory of Cognitive Effort: Application of Linear Control Theory to a Simple Cognitive Model of Controlled Processing
Abstract
Cognitive effort is a defining feature of cognitive control but theories about its origin and purpose have long been controversial. Recently, it has been proposed that cognitive effort can be understood using linear control theory, a mathematical formalism developed in the engineering literature to control dynamical systems. On this view, effort levels reflect the energy required by the cognitive control system to support representational states that deviate from the intrinsic dynamics of the cognitive system. Although this approach has been used to characterize the energy landscape of neural networks abstracted from the human structural and functional connectome, it has yet to make contact with neurocomputational models of cognitive control. Here we demonstrate the potential of this approach by applying LCT to a classic computational model of cognitive control, and discuss its broader significance in the context of other models of cognitive effort and future studies that can test the theory.
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BibTeX
@misc{holroyd2026toward,
title = {{Toward a Formal Theory of Cognitive Effort: Application of Linear Control Theory to a Simple Cognitive Model of Controlled Processing}},
author = {Clay Holroyd},
howpublished = {PsyArXiv},
year = {2026},
month = sep,
doi = {10.31234/osf.io/32vs7_v3},
url = {https://osf.io/preprints/psyarxiv/32vs7_v3/},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Toward a Formal Theory of Cognitive Effort: Application of Linear Control Theory to a Simple Cognitive Model of Controlled Processing
AU - Clay Holroyd
PY - 2026
DA - 2026/09/17
PB - PsyArXiv
DO - 10.31234/osf.io/32vs7_v3
UR - https://osf.io/preprints/psyarxiv/32vs7_v3/
AB - Cognitive effort is a defining feature of cognitive control but theories about its origin and purpose have long been controversial. Recently, it has been proposed that cognitive effort can be understood using linear control theory, a mathematical formalism developed in the engineering literature to control dynamical systems. On this view, effort levels reflect the energy required by the cognitive control system to support representational states that deviate from the intrinsic dynamics of the cognitive system. Although this approach has been used to characterize the energy landscape of neural networks abstracted from the human structural and functional connectome, it has yet to make contact with neurocomputational models of cognitive control. Here we demonstrate the potential of this approach by applying LCT to a classic computational model of cognitive control, and discuss its broader significance in the context of other models of cognitive effort and future studies that can test the theory.
ER -