Material attention: A method to measure the effect of regimes of attention on decision making, using information theory and Markov chain models

We present a method to quantify the Regime of Attention (RoA) characteristic of an agent or population that engages with the material world. Using a method called Gaze Entropy Analysis we derived a collection of information theory-based methods to characterize the flow of uncertainty of an agent that synchronizes with a generative process. We further derived Gaze Entropy Profiles (GEP) serving as proxy for the exploration-exploitation trade-offs strategies that an agent employs to accomplish a free viewing task. We show that this process can be modelled as a growth process defining block entropy and excess entropy. We further suggest that: (1) such a process may be viewed as a special case of variational free energy minimization; and (2) that the transient information (T), understood as the amount of information an observer needs to extract to synchronize with a process, can be interpreted as a measure of how much information has been efficiently externalized to participate in cognitive processing without being stored in the brain. We demonstrate that the proposed method is sufficiently sensitive to describe the bidirectional interaction between an agent and a variety of material environment; that is, from the bottom-up perspective, how materiality elicits a characteristic RoA, and from the top-down perspective, how an agent´s or population's generative model constrains the RoA. In conclusion, our method proposes a formal way of using information theory to build a quantifiable definition of a RoA that can be used experimentally and can be extended to other neurophysiological signals.

Regime of attention. Gaze entropy. Block entropy. Active inference. Free energy. Transient information.