Amygdala inputs to prefrontal cortex guide behavior amid conflicting cues of reward and punishment

Orchestrating appropriate behavioral responses in the face of competing signals that predict either rewards or threats in the environment is crucial for survival. The basolateral nucleus of the amygdala (BLA) and prelimbic (PL) medial prefrontal cortex have been implicated in reward-seeking and fear-related responses, but how information flows between these reciprocally connected structures to coordinate behavior is unknown. We recorded neuronal activity from the BLA and PL while rats performed a task wherein competing shock- and sucrose-predictive cues were simultaneously presented. The correlated firing primarily displayed a BLA→PL directionality during the shock-associated cue. Furthermore, BLA neurons optogenetically identified as projecting to PL more accurately predicted behavioral responses during competition than unidentified BLA neurons. Finally photostimulation of the BLA→PL projection increased freezing, whereas both chemogenetic and optogenetic inhibition reduced freezing. Therefore, the BLA→PL circuit is critical in governing the selection of behavioral responses in the face of competing signals.National Institutes of Health (U.S.) (Award 1R25-MH092912-01)National Institute of Mental Health (U.S.) (Grant R01- MH102441-01)National Institutes of Health (U.S.) (Award DP2- DK-102256-01

A common mechanism underlies changes of mind about decisions and confidence

Decisions are accompanied by a degree of confidence that a selected option is correct. A sequential sampling framework explains the speed and accuracy of decisions and extends naturally to the confidence that the decision rendered is likely to be correct. However, discrepancies between confidence and accuracy suggest that confidence might be supported by mechanisms dissociated from the decision process. Here we show that this discrepancy can arise naturally because of simple processing delays. When participants were asked to report choice and confidence simultaneously, their confidence, reaction time and a perceptual decision about motion were explained by bounded evidence accumulation. However, we also observed revisions of the initial choice and/or confidence. These changes of mind were explained by a continuation of the mechanism that led to the initial choice. Our findings extend the sequential sampling framework to vacillation about confidence and invites caution in interpreting dissociations between confidence and accuracy

Customized Bundle Pricing for Information Goods: A Nonlinear Mixed-Integer Programming Approach

This paper proposes using nonlinear mixed-integer programming to solve the customized bundle-pricing problem in which consumers are allowed to choose up to N goods out of a larger pool of J goods. Prior work has suggested that this mechanism has attractive features for the pricing of information and other low-marginal cost goods. Although closed-form solutions exist for this problem for certain cases of consumer preferences, many interesting scenarios cannot be easily handled without a numerical solution procedure. In this paper, we investigate the efficiency gains created by customized bundling over the alternatives of pure bundling or individual sale under different assumptions about customer preferences and firm cost structure, as well as the potential loss of efficiency caused by pricing with incomplete information about consumer reservation values. Our analysis suggests that customized bundling enhances sellers' profits and enhances welfare when consumers do not place positive values on all goods, and that this consumer characteristic is much more important than the shape of the valuation distribution in determining the optimal pricing scheme. We also find that customized bundling outperforms both pure bundling and individual sale in the presence of incomplete information, and that customized bundling still outperforms other simpler pricing schemes even when exact consumer valuations are not known ex ante.information goods, electronic commerce, customized bundle, pricing, nonlinear programming, integer programming

Geometry And Local Optimality Conditions For Bilevel Programs With Quadratic Strictly Convex Lower Levels

This paper describes necessary and sufficient optimality conditions for bilevel programming problems with quadratic strictly convex lower levels. By examining the local geometry of these problems we establish that the set of feasible directions at a given point is composed of a finite union of convex cones. Based on this result, we show that the optimality conditions are simple generalizations of the first and second order optimality conditions for mathematical (one level) programming problems. 1 INTRODUCTION A bilevel program is defined as the problem of minimizing a function f (the upper level function) in two different vectors of variables x and y subject to (upper level) constraints, where the vector y is an optimal solution of another constrained optimization problem (the lower level problem) parameterized by the vector x. References [2] and [17] survey the extensive research that has been done in bilevel programming. 2 Chapter 1 It is interesting to note that any minimax probl..

Environmental project evaluation using intuitionistic fuzzy information

An intuitionistic fuzzy set (IFS) is a generalization of a fuzzy set characterized by a truth membership function and a false membership function. The former is a lower bound on the grade of membership of the evidence in favor of a particular element belonging to the set and the latter is a lower bound on the negation of that element belonging to the set, derived from evidence against that element belonging to the set. A similar concept is a vague set, though vague sets have been shown to be identical to IFSs. In the context of project evaluation, an IFS may be used to represent the degree to which a project satisfies a criterion or factor and the degree to which it does not. Aggregation of such IFSs has been considered in recent years to identify a best project in terms of several factors. A particular desirable way to aggregate IFSs is in terms of an ordered weighted average (OWA) which can be expressed in different forms, such as arithmetic and geometric. In an OWA, weights are applied to the position of an element in the aggregation. In addition, hybrid OWA operators may be developed to not only weight the position of elements in the aggregation but the element itself. A simple example based on a hypothetical but realistic example by Horsak and Damico [4] is given which involves the location of a hazardous waste disposal facility (PCB-contaminated transformer fluids) at one of three sites based on 10 factors