Neural signatures of vigilance decrements predict behavioural errors before they occur
- Macquarie University, Australia
- University of Cambridge, United Kingdom
Abstract
There are many monitoring environments, such as railway control, in which lapses of attention can have tragic consequences. Problematically, sustained monitoring for rare targets is difficult, with more misses and longer reaction times over time. What changes in the brain underpin these 'vigilance decrements'? We designed a multiple-object monitoring (MOM) paradigm to examine how the neural representation of information varied with target frequency and time performing the task. Behavioural performance decreased over time for the rare target (monitoring) condition, but not for a frequent target (active) condition. This was mirrored in neural decoding using Magnetoencephalography: coding of critical information declined more during monitoring versus active conditions along the experiment. We developed new analyses that can predict behavioural errors from the neural data more than a second before they occurred. This facilitates pre-empting behavioural errors due to lapses in attention and provides new insight into the neural correlates of vigilance decrements.
Data availability
We have shared the Magnetoencephalography data (i.e. time series) as well as behavioral data in Matlab '.mat' format on the Open Science Framework website at https://osf.io/5aw8v/ with the DOI: 10.17605/OSF.IO/5AW8V. We have also uploaded a video of the "Multiple-Object-Monitoring" paradigm, developed for this study, for easier understanding of the task at the same address. The mentioned address is dedicated to this project and we will regularly update the contents to make them easier to follow for other researchers.
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Neural signatures of vigilance decrements predict behavioural errors before they occurOpen Science Framework, DOI 10.17605/OSF.IO/5AW8V.
Article and author information
Author details
Hamid Karimi-Rouzbahani
Funding
Australian Research Council (DP170101780)
- Anina N Rich
Australian Research Council (FT170100105)
- Alexandra Woolgar
MRC Cognition and Brain Sciences Unit (SUAG/052/G101400)
- Alexandra Woolgar
The Royal Society (NIF\R1\192608)
- Hamid Karimi-Rouzbahani
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Peter Kok, University College London, United Kingdom
Ethics
Human subjects: The Human Research Ethics Committee of Macquarie University approved the experimental protocols and the participants gave informed consent before participating in the experiment. The approval identifier is 52020297914411.
Version history
- Received: July 3, 2020
- Accepted: April 2, 2021
- Accepted Manuscript published: April 8, 2021 (version 1)
- Version of Record published: April 21, 2021 (version 2)
- Version of Record updated: August 8, 2023 (version 3)
Copyright
© 2021, Karimi-Rouzbahani et al.
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.
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Neural signatures of vigilance decrements predict behavioural errors before they occur
eLife 10:e60563.
https://doi.org/10.7554/eLife.60563
Further reading
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- Neuroscience
The central tendency bias, or contraction bias, is a phenomenon where the judgment of the magnitude of items held in working memory appears to be biased toward the average of past observations. It is assumed to be an optimal strategy by the brain and commonly thought of as an expression of the brain’s ability to learn the statistical structure of sensory input. On the other hand, recency biases such as serial dependence are also commonly observed and are thought to reflect the content of working memory. Recent results from an auditory delayed comparison task in rats suggest that both biases may be more related than previously thought: when the posterior parietal cortex (PPC) was silenced, both short-term and contraction biases were reduced. By proposing a model of the circuit that may be involved in generating the behavior, we show that a volatile working memory content susceptible to shifting to the past sensory experience – producing short-term sensory history biases – naturally leads to contraction bias. The errors, occurring at the level of individual trials, are sampled from the full distribution of the stimuli and are not due to a gradual shift of the memory toward the sensory distribution’s mean. Our results are consistent with a broad set of behavioral findings and provide predictions of performance across different stimulus distributions and timings, delay intervals, as well as neuronal dynamics in putative working memory areas. Finally, we validate our model by performing a set of human psychophysics experiments of an auditory parametric working memory task.
