Modelling human choices: MADeM and decision‑making

Mavritsaki, Eirini and Aldrovandi, Silvio and Bridger, Emma K. (2017) Modelling human choices: MADeM and decision‑making. BMC Neuroscience, 18. p. 59. ISSN 1471-2202

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Abstract

In this work, we present a novel approach, to our knowledge, to investigating
the underlying brain processes involved in decision making
using a computational model for decision making that is based on
the Multiple Attribute Decision Making (MADeM) model. In decision
making humans need to first evaluate the options available in the
decision-making context and the way in which such evaluations are
made is subject to debate. A growing body of recent literature [1] has
suggested that people evaluate options in relative terms – that is, people
are highly sensitive to the context in which an evaluation (and/or a
choice) is made. For example, an individual product (e.g., a ready meal
or a holiday) is evaluated with reference to other products (e.g., other
ready meals, other holidays) available in the decision-making context
[2].
The presented work is comprised of behavioral experiments and computational
modelling work. The experiments we developed allow us in
combination with MADeM, to further investigate the decision-making
mechanisms at the cognitive and neuronal level. In the behavioral
work participants chose between pairs of items, sampled across different
choice domains (e.g., flats to rent and monetary gambles), which
differed in terms of two features (e.g., rent cost and distance from a
station for flats). Difficulty of choice was manipulated across trials by
varying the distance in quality between the two features; for example,
in a dominated trial an item was higher in quality on both attributes,
whilst in a difficult trial participants were required to perform tradeoffs
between the two features.
MADeM is based on previous modelling work on visual attention using
the spiking Search over Time and Space model (sSoTS). [3]. MADeM
is separated into three layers; two layers for the two attributes simulated
in the above experiment and one layer that gives us the outcome
of the decision-making process. All layers are comprised by pools of
excitatory and inhibitory neurons with properties as shown in Mavritsaki
et al. [3]. Based on the levels of excitation and competition one of
the choices will be higher activated in the Outcome pool and therefore
this will be the selected choice. The preliminary results of this
study show that the model successfully simulate the results from the
behavioral studies using the organization presented above.

Item Type: Article
Uncontrolled Keywords: decision making, attention, modelling
Subjects: C800 Psychology
Divisions: Faculty of Business, Law and Social Sciences > School of Social Sciences > Dept. Psychology
Depositing User: Eirini Mavritsaki
Date Deposited: 18 Jun 2018 08:47
Last Modified: 18 Jun 2018 08:47
URI: http://www.open-access.bcu.ac.uk/id/eprint/6048

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