2019
DOI: 10.1101/834614
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Boosting Brain Signal Variability Underlies Liberal Shifts in Decision Bias

Abstract: Strategically adopting 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. Implementing strategic bias shifts is presumed to rely on prefrontal cortex, but the temporal signature of such biases remains elusive. We hypothesized that strategic liberal bias shifts during a continuous target detection task arise through a more uncon… Show more

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Cited by 5 publications
(2 citation statements)
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“…For example, while we observed moderate associations between band-specific rhythm events and entropy here, this non-redundant association nevertheless leaves room for the two measures to diverge in relation to third variables. This is in line with prior work [27,121] showing that despite a dominant influence of linear characteristics on entropy estimates, non-linear contributions can uniquely explain a (smaller) portion of entropy variance.…”
Section: Recommendations For Future Applicationssupporting
confidence: 91%
“…For example, while we observed moderate associations between band-specific rhythm events and entropy here, this non-redundant association nevertheless leaves room for the two measures to diverge in relation to third variables. This is in line with prior work [27,121] showing that despite a dominant influence of linear characteristics on entropy estimates, non-linear contributions can uniquely explain a (smaller) portion of entropy variance.…”
Section: Recommendations For Future Applicationssupporting
confidence: 91%
“…In our study, we set the parameters m = 2 and r = 0.5 considering the recommendations given by previous EEG signal complexity studies (Richman & Moorman 2000;McIntosh et al 2008;Miskovic et al 2016;Kosciessa et al 2020;Kloosterman et al 2019), in which the SD parameter permits normalizing the r parameter by the EEG standard deviation in each particular scale. MSE was calculated for time scale 1 to 34, which allows analysis of entropy from the finest to the coarsest scales, as well as indirect analysis of low frequency bands (B 7.73 Hz).…”
Section: Multiscale Entropy Analysismentioning
confidence: 99%