Literature DB >> 32744502

Boosts in brain signal variability track liberal shifts in decision bias.

Niels A Kloosterman1,2, Julian Q Kosciessa1,2, Ulman Lindenberger1,2, Johannes Jacobus Fahrenfort3,4, Douglas D Garrett1,2.   

Abstract

Adopting particular decision biases allows organisms to tailor their choices to environmental demands. For example, a liberal response strategy pays off when target detection is crucial, whereas a conservative strategy is optimal for avoiding false alarms. Using conventional time-frequency analysis of human electroencephalographic (EEG) activity, we previously showed that bias setting entails adjustment of evidence accumulation in sensory regions (Kloosterman et al., 2019), but the presumed prefrontal signature of a conservative-to-liberal bias shift has remained elusive. Here, we show that a liberal bias shift is reflected in a more unconstrained neural regime (boosted entropy) in frontal regions that is suited to the detection of unpredictable events. Overall EEG variation, spectral power and event-related potentials could not explain this relationship, highlighting that moment-to-moment neural variability uniquely tracks bias shifts. Neural variability modulation through prefrontal cortex appears instrumental for permitting an organism to adapt its biases to environmental demands.
© 2020, Kloosterman et al.

Entities:  

Keywords:  brain signal variability; cognitive flexibility; decision bias; human; neuroscience; perceptual decision making; signal detection theory

Mesh:

Year:  2020        PMID: 32744502      PMCID: PMC7398662          DOI: 10.7554/eLife.54201

Source DB:  PubMed          Journal:  Elife        ISSN: 2050-084X            Impact factor:   8.140


  63 in total

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3.  Top-down modulation in human visual cortex predicts the stability of a perceptual illusion.

Authors:  Niels A Kloosterman; Thomas Meindertsma; Arjan Hillebrand; Bob W van Dijk; Victor A F Lamme; Tobias H Donner
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4.  Cortical activity is more stable when sensory stimuli are consciously perceived.

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5.  The intrinsic attractor manifold and population dynamics of a canonical cognitive circuit across waking and sleep.

Authors:  Rishidev Chaudhuri; Berk Gerçek; Biraj Pandey; Adrien Peyrache; Ila Fiete
Journal:  Nat Neurosci       Date:  2019-08-12       Impact factor: 24.884

6.  Adaptive coding for dynamic sensory inference.

Authors:  Wiktor F Młynarski; Ann M Hermundstad
Journal:  Elife       Date:  2018-07-10       Impact factor: 8.140

7.  The evolution of lossy compression.

Authors:  Sarah E Marzen; Simon DeDeo
Journal:  J R Soc Interface       Date:  2017-05       Impact factor: 4.118

8.  Frontal eye field neurons signal changes in decision criteria.

Authors:  Vincent P Ferrera; Marianna Yanike; Carlos Cassanello
Journal:  Nat Neurosci       Date:  2009-10-25       Impact factor: 24.884

9.  Noise during rest enables the exploration of the brain's dynamic repertoire.

Authors:  Anandamohan Ghosh; Y Rho; A R McIntosh; R Kötter; V K Jirsa
Journal:  PLoS Comput Biol       Date:  2008-10-10       Impact factor: 4.475

10.  Repeated Measures Correlation.

Authors:  Jonathan Z Bakdash; Laura R Marusich
Journal:  Front Psychol       Date:  2017-04-07
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  1 in total

1.  Decision-Making in the Human-Machine Interface.

Authors:  J Benjamin Falandays; Samuel Spevack; Philip Pärnamets; Michael Spivey
Journal:  Front Psychol       Date:  2021-02-11
  1 in total

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