| Title: |
Neural Mechanisms Behind Identification of Leptokurtic Noise and Adaptive Behavioral Response |
| Authors: |
d'Acremont, Mathieu; Bossaerts, Peter |
| Source: |
Cerebral Cortex, 26(4), 1818-1830, (2016-04) |
| Publisher Information: |
Oxford University Press |
| Publication Year: |
2016 |
| Collection: |
Caltech Authors (California Institute of Technology) |
| Subject Terms: |
anterior insula; fronto-parietal control network; leptokurtic noise; outliers; reinforcement learning |
| Description: |
Large-scale human interaction through, for example, financial markets causes ceaseless random changes in outcome variability, producing frequent and salient outliers that render the outcome distribution more peaked than the Gaussian distribution, and with longer tails. Here, we study how humans cope with this evolutionary novel leptokurtic noise, focusing on the neurobiological mechanisms that allow the brain, 1) to recognize the outliers as noise and 2) to regulate the control necessary for adaptive response. We used functional magnetic resonance imaging, while participants tracked a target whose movements were affected by leptokurtic noise. After initial overreaction and insufficient subsequent correction, participants improved performance significantly. Yet, persistently long reaction times pointed to continued need for vigilance and control. We ran a contrasting treatment where outliers reflected permanent moves of the target, as in traditional mean-shift paradigms. Importantly, outliers were equally frequent and salient. There, control was superior and reaction time was faster. We present a novel reinforcement learning model that fits observed choices better than the Bayes-optimal model. Only anterior insula discriminated between the 2 types of outliers. In both treatments, outliers initially activated an extensive bottom-up attention and belief network, followed by sustained engagement of the fronto-parietal control network. ; © 2016 The Author. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. This work was supported by the Ronald And Maxine Linde Institute for Economic and Management Sciences at the California Institute of Technology and through US National Science Foundation (grant SES-1061824). Funding to pay the Open ... |
| Document Type: |
article in journal/newspaper |
| Language: |
unknown |
| Relation: |
https://authors.library.caltech.edu/communities/caltechauthors/; https://doi.org/10.1093/cercor/bhw013; https://pmc.ncbi.nlm.nih.gov/articles/PMC4785960/; eprintid:64498 |
| DOI: |
10.1093/cercor/bhw013 |
| Availability: |
https://doi.org/10.1093/cercor/bhw013; https://pmc.ncbi.nlm.nih.gov/articles/PMC4785960/ |
| Rights: |
info:eu-repo/semantics/openAccess ; Other |
| Accession Number: |
edsbas.C35E5B03 |
| Database: |
BASE |