Learning relative values in the striatum induces violations of normative decision making

نویسندگان

  • Tilmann A Klein
  • Markus Ullsperger
  • Gerhard Jocham
چکیده

To decide optimally between available options, organisms need to learn the values associated with these options. Reinforcement learning models offer a powerful explanation of how these values are learnt from experience. However, human choices often violate normative principles. We suggest that seemingly counterintuitive decisions may arise as a natural consequence of the learning mechanisms deployed by humans. Here, using fMRI and a novel behavioural task, we show that, when suddenly switched to novel choice contexts, participants' choices are incongruent with values learnt by standard learning algorithms. Instead, behaviour is compatible with the decisions of an agent learning how good an option is relative to an option with which it had previously been paired. Striatal activity exhibits the characteristics of a prediction error used to update such relative option values. Our data suggest that choices can be biased by a tendency to learn option values with reference to the available alternatives.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Decision Theoretic Norm-Governed Planning

We propose Normative Dec-POMDPs, a model of collective decision making in the presence of complex norms, with violations of norms classified according to their relative severity. We extend the PBPG algorithm in order to solve Normative Dec-POMDPs and propose a heuristic that improves its scalability without affecting the policy quality.

متن کامل

Adaptive neural coding: from biological to behavioral decision-making.

Empirical decision-making in diverse species deviates from the predictions of normative choice theory, but why such suboptimal behavior occurs is unknown. Here, we propose that deviations from optimality arise from biological decision mechanisms that have evolved to maximize choice performance within intrinsic biophysical constraints. Sensory processing utilizes specific computations such as di...

متن کامل

Moving Towards Accountability for Reasonableness – A Systematic Exploration of the Features of Legitimate Healthcare Coverage Decision-Making Processes Using Rare Diseases and Regenerative Therapies as a Case Study

Background The accountability for reasonableness (A4R) framework defines 4 conditions for legitimate healthcare coverage decision processes: Relevance, Publicity, Appeals, and Enforcement. The aim of this study was to reflect on how the diverse features of decision-making processes can be aligned with A4R conditions to guide decisio...

متن کامل

Measuring the overall performances of decision-making units in the presence of imprecise data

Data envelopment analysis (DEA) is a method for measuring the relative efficiencies of a set of decision-making units (DMUs) that use multiple inputs to produce multiple outputs. In this paper, we study the measurement of DMU performances in DEA in situations where input and/or output values are given as imprecise data. By imprecise data we mean situations where we only know that the actual val...

متن کامل

Prioritising, Ranking and Resource Implementation - A Normative Analysis

Background Priority setting in publicly financed healthcare systems should be guided by ethical norms and other considerations viewed as socially valuable, and we find several different approaches for how such norms and considerations guide priorities in healthcare decision-making. Common to many of these approaches is that interventions are ranked in relation to each other, following the appli...

متن کامل

ذخیره 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 8  شماره 

صفحات  -

تاریخ انتشار 2017