A Neural Mechanism for the Opportunity Cost of Time
نویسندگان
چکیده
24 Recent interest has focused on a class of decision problems in which subjects encounter options serially and 25 must decide when to leave an option in search of a better one, rather than directly comparing simultaneously 26 presented options. Although such problems have a rich history in animal foraging and economics, relatively 27 little is known about their neural substrates. Suggestively, however, a separate literature has argued that 28 the key decision variable in these tasks – the opportunity cost of time, given by the average reward rate – 29 may also govern behavioral vigor and may be reported by tonic dopamine (DA). 30 In this study, we test whether this putative dopaminergic opportunity cost signal plays an analogous role 31 in serial decisions by examining the behavior of patients with Parkinson’s disease (PD), on and off their 32 DA replacement medication, in a patch-foraging task. In these tasks, subjects’ decisions about when to 33 leave a depleting resource implicitly reflect their beliefs about the opportunity cost of time spent harvest34 ing that resource. Consistent with the opportunity cost hypothesis, umedicated patients harvested longer 35 than matched controls, and medication remediated this deficit. These effects were not explained by motor 36 perseveration. Our results suggest a functional role for DA, and an associated cognitive deficit in PD, in a 37 type of decision process that may be distinct from (but related to) the neuromodulator’s well studied roles 38 in behavioral invigoration and learning from rewards. 39 Significance Statement 40 This study addresses two important questions whose answers are, unexpectedly, linked. First, what is the 41 scope of cognitive functions of the neuromodulator dopamine, whose contributions – for instance, as assessed 42 by both the motoric and more subtle cognitive deficits of patients with PD, which depletes dopamine – range 43 from movement to reward and decision-making? Second, what are the neural mechanisms supporting an 44 important but understudied class of problems, in which, rather than choose among a set of alternatives (like 45 apples and oranges), one makes serial decisions about whether to stick with an option (like a job, or a mate) 46 or seek another? We demonstrate a novel cognitive deficit in PD that integrates this function into the web 47 of DA’s contributions. 48
منابع مشابه
STRUCTURAL DAMAGE DETECTION BY MODEL UPDATING METHOD BASED ON CASCADE FEED-FORWARD NEURAL NETWORK AS AN EFFICIENT APPROXIMATION MECHANISM
Vibration based techniques of structural damage detection using model updating method, are computationally expensive for large-scale structures. In this study, after locating precisely the eventual damage of a structure using modal strain energy based index (MSEBI), To efficiently reduce the computational cost of model updating during the optimization process of damage severity detection, the M...
متن کاملProject Time and Cost Forecasting using Monte Carlo simulation and Artificial Neural Networks
The aim of this study is to present a new method to predict project time and cost under uncertainty. Assuming that what happens in projects implementation which is expressed in the form of Earned Value Management (EVM) indicators is primarily related to the nature of randomness or unreliability, in this study, by using Monte Carlo simulation, and assuming a specific distribution for the time an...
متن کاملA Novel Technique for Joint Energy and Reserve Dispatch Considering Lost Opportunity Cost
This paper presents a novel solution method for joint energy and Spinning Reserve (SR) dispatch problem. In systems in which the Lost Opportunity Cost (LOC) should be paid to generators, if the LOC is not considered in the dispatch problem, the results may differ from the truly optimum solution. Since the LOC is a non-differentiable function, including it in the formulation makes the problem so...
متن کاملGDOP Classification and Approximation by Implementation of Time Delay Neural Network Method for Low-Cost GPS Receivers
Geometric Dilution of Precision (GDOP) is a coefficient for constellations of Global Positioning System (GPS) satellites. These satellites are organized geometrically. Traditionally, GPS GDOP computation is based on the inversion matrix with complicated measurement equations. A new strategy for calculation of GPS GDOP is construction of time series problem; it employs machine learning and artif...
متن کاملUsing Neural Networks with Limited Data to Estimate Manufacturing Cost
Neural networks were used to estimate the cost of jet engine components, specifically shafts and cases. The neural network process was compared with results produced by the current conventional cost estimation software and linear regression methods. Due to the complex nature of the parts and the limited amount of information available, data expansion techniques such as doubling-data and data-cr...
متن کاملA new study of an EOQ model for deteriorating items with shortages under inflation and time discounting
We discuss the effects of inflation and time discounting on an EOQ model for deteriorating items under stock-dependent demand and time-dependent partial backlogging. The inventory model is studied under the replenishment policy starting with no shortages. We then use MATLAB to find the optimal replenishment policies. The objective of this model is to maximize the total profit (TP) which inclu...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2016