Abstract
We are constantly faced with decisions between alternatives defined by multiple attributes, necessitating an evaluation and integration of different information sources. Time-varying signals in multiple brain areas are implicated in decision-making; but we lack a rigorous biophysical description of how basic circuit properties, such as excitatory-inhibitory (E/I) tone and cascading nonlinearities, shape attribute processing and choice behavior. Furthermore, how such properties govern choice performance under varying levels of environmental uncertainty is unknown. We investigated two-attribute, two-alternative decision-making in a dynamical, cascading nonlinear neural network with three layers: an input layer encoding choice alternative attribute values; an intermediate layer of modules processing separate attributes; and a final layer producing the decision. Depending on intermediate layer E/I tone, the network displays distinct regimes characterized by linear (I), convex (II) or concave (III) choice indifference curves. In regimes I and II, each option’s attribute information is additively integrated. In regime III, time-varying nonlinear operations amplify the separation between offer distributions by selectively attending to the attribute with the larger differences in input values. At low environmental uncertainty, a linear combination most consistently selects higher valued alternatives. However, at high environmental uncertainty, regime III is more likely than a linear operation to select alternatives with higher value. Furthermore, there are conditions where readout from the intermediate layer could be experimentally indistinguishable from the final layer. Finally, these principles are used to examine multi-attribute decisions in systems with reduced inhibitory tone, leading to predictions of different choice patterns and overall performance between those with restrictions on inhibitory tone and neurotypicals.
Highlights
When choosing between cereals on a grocery store shelf, one might consider multiple attributes, such as each alternative’s flavor or healthiness
Individual attribute values can be coded in the orbitofrontal cortex (OFC), as modulated by the timing of presentation or the offers present, prior to integration as a choice signal in the dorsolateral prefrontal cortex [22]
Utilizing analytical tools from economics, we find that the E/I tone of the intermediate layer creates distinct regimes defined by their choice indifference curve: a linear weighting of attribute values; a convex preference for balanced attributes; or a concave preference with increased weighting of the larger attribute value
Summary
When choosing between cereals on a grocery store shelf, one might consider multiple attributes, such as each alternative’s flavor or healthiness. Individual attribute values can be coded in the orbitofrontal cortex (OFC), as modulated by the timing of presentation or the offers present, prior to integration as a choice signal in the dorsolateral prefrontal cortex (dlPFC) [22]. It is hypothesized this process can allow for parallel computation of individual values or actions, and may produce a clearer separation between representations of choice alternatives where the decision is reached, yet a rigorous mechanistic description is lacking. A mechanistic description is all the more important as transformations along a hierarchy can be highly nonlinear, providing an additional layer of flexibility when engaging in sophisticated choices
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