Affective bias as a rational response to the statistics of rewards and punishments
Abstract
Affective bias, the tendency to differentially prioritise the processing of negative relative to positive events, is commonly observed in clinical and non-clinical populations. However, why such biases develop is not known. Using a computational framework, we investigated whether affective biases may reflect individuals' estimates of the information content of negative relative to positive events. During a reinforcement learning task, the information content of positive and negative outcomes was manipulated independently by varying the volatility of their occurrence. Human participants altered the learning rates used for the outcomes selectively, preferentially learning from the most informative. This behaviour was associated with activity of the central norepinephrine system, estimated using pupilometry, for loss outcomes. Humans maintain independent estimates of the information content of distinct positive and negative outcomes which may bias their processing of affective events. Normalising affective biases using computationally inspired interventions may represent a novel approach to treatment development.
Article and author information
Author details
Funding
Medical Research Council (MR/N008103/1)
- Michael Browning
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Michael J Frank, Brown University, United States
Ethics
Human subjects: All participants provided written informed consent. The study was reviewed and approved by the Medical Sciences Interdepartmental Research Ethics Committee of Oxford University (ref number MSD-IDREC-C1-2014-216).
Version history
- Received: April 18, 2017
- Accepted: October 3, 2017
- Accepted Manuscript published: October 4, 2017 (version 1)
- Version of Record published: October 9, 2017 (version 2)
- Version of Record updated: October 19, 2017 (version 3)
Copyright
© 2017, Pulcu & Browning
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 4,705
- views
-
- 617
- downloads
-
- 51
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Neuroscience
Functional interactions between the prefrontal cortex and hippocampus, as revealed by strong oscillatory synchronization in the theta (6–11 Hz) frequency range, correlate with memory-guided decision-making. However, the degree to which this form of long-range synchronization influences memory-guided choice remains unclear. We developed a brain-machine interface that initiated task trials based on the magnitude of prefrontal-hippocampal theta synchronization, then measured choice outcomes. Trials initiated based on strong prefrontal-hippocampal theta synchrony were more likely to be correct compared to control trials on both working memory-dependent and -independent tasks. Prefrontal-thalamic neural interactions increased with prefrontal-hippocampal synchrony and optogenetic activation of the ventral midline thalamus primarily entrained prefrontal theta rhythms, but dynamically modulated synchrony. Together, our results show that prefrontal-hippocampal theta synchronization leads to a higher probability of a correct choice and strengthens prefrontal-thalamic dialogue. Our findings reveal new insights into the neural circuit dynamics underlying memory-guided choices and highlight a promising technique to potentiate cognitive processes or behavior via brain-machine interfacing.