Literature DB >> 25411455

Surprise signals in the supplementary eye field: rectified prediction errors drive exploration-exploitation transitions.

Norihiko Kawaguchi1, Kazuhiro Sakamoto2, Naohiro Saito3, Yoshito Furusawa3, Jun Tanji3, Masashi Aoki4, Hajime Mushiake5.   

Abstract

Visual search is coordinated adaptively by monitoring and predicting the environment. The supplementary eye field (SEF) plays a role in oculomotor control and outcome evaluation. However, it is not clear whether the SEF is involved in adjusting behavioral modes based on preceding feedback. We hypothesized that the SEF drives exploration-exploitation transitions by generating "surprise signals" or rectified prediction errors, which reflect differences between predicted and actual outcomes. To test this hypothesis, we introduced an oculomotor two-target search task in which monkeys were required to find two valid targets among four identical stimuli. After they detected the valid targets, they exploited their knowledge of target locations to obtain a reward by choosing the two valid targets alternately. Behavioral analysis revealed two distinct types of oculomotor search patterns: exploration and exploitation. We found that two types of SEF neurons represented the surprise signals. The error-surprise neurons showed enhanced activity when the monkey received the first error feedback after the target pair change, and this activity was followed by an exploratory oculomotor search pattern. The correct-surprise neurons showed enhanced activity when the monkey received the first correct feedback after an error trial, and this increased activity was followed by an exploitative, fixed-type search pattern. Our findings suggest that error-surprise neurons are involved in the transition from exploitation to exploration and that correct-surprise neurons are involved in the transition from exploration to exploitation.
Copyright © 2015 the American Physiological Society.

Keywords:  exploration-exploitation transition; monkey; oculomotor search; supplementary eye field; surprise signal

Mesh:

Year:  2014        PMID: 25411455     DOI: 10.1152/jn.00128.2014

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  8 in total

1.  Reinforcement Learning Model With Dynamic State Space Tested on Target Search Tasks for Monkeys: Extension to Learning Task Events.

Authors:  Kazuhiro Sakamoto; Hinata Yamada; Norihiko Kawaguchi; Yoshito Furusawa; Naohiro Saito; Hajime Mushiake
Journal:  Front Comput Neurosci       Date:  2022-06-02       Impact factor: 3.387

2.  Functional architecture of executive control and associated event-related potentials in macaques.

Authors:  Amirsaman Sajad; Steven P Errington; Jeffrey D Schall
Journal:  Nat Commun       Date:  2022-10-21       Impact factor: 17.694

3.  Abstract goal representation in visual search by neurons in the human pre-supplementary motor area.

Authors:  Shuo Wang; Adam N Mamelak; Ralph Adolphs; Ueli Rutishauser
Journal:  Brain       Date:  2019-11-01       Impact factor: 13.501

4.  Neuronal Correlates of Serial Decision-Making in the Supplementary Eye Field.

Authors:  Zachary M Abzug; Marc A Sommer
Journal:  J Neurosci       Date:  2018-07-16       Impact factor: 6.167

5.  Exploration Disrupts Choice-Predictive Signals and Alters Dynamics in Prefrontal Cortex.

Authors:  R Becket Ebitz; Eddy Albarran; Tirin Moore
Journal:  Neuron       Date:  2017-12-28       Impact factor: 17.173

6.  Reinforcement Learning Model With Dynamic State Space Tested on Target Search Tasks for Monkeys: Self-Determination of Previous States Based on Experience Saturation and Decision Uniqueness.

Authors:  Tokio Katakura; Mikihiro Yoshida; Haruki Hisano; Hajime Mushiake; Kazuhiro Sakamoto
Journal:  Front Comput Neurosci       Date:  2022-02-04       Impact factor: 2.380

7.  Involuntary oculomotor inhibition markers of saliency and deviance in response to auditory sequences.

Authors:  Oren Kadosh; Yoram S Bonneh
Journal:  J Vis       Date:  2022-04-06       Impact factor: 2.004

8.  Cortical microcircuitry of performance monitoring.

Authors:  Amirsaman Sajad; David C Godlove; Jeffrey D Schall
Journal:  Nat Neurosci       Date:  2019-01-14       Impact factor: 24.884

  8 in total

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