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 unconstrained neural regime (higher entropy) suited to the detection of unpredictable events. Human participants performed a visual target detection task reporting faint target stimuli within a stream of non-targets via button press, while we measured their electroencephalogram (EEG). Subjects were instructed in separate conditions to maximize the number of detected targets ('liberal' condition) and to minimize false detections ('conservative' condition) by penalizing either missed targets or false alarms. To measure neural variability, we developed a novel algorithm based on multi-scale entropy (MSE) that directly quantifies the temporal irregularity of the EEG signal in longer and shorter timescales. Upregulation of entropy in frontal brain regions indeed strongly characterized the degree to which individuals shifted from a conservative to a liberal bias, both across subjects and within single participants. Overall EEG signal variation and oscillatory (spectral) dynamics could not account for this relationship. Our results suggest that modulation of neural variability in frontal regions is instrumental for permitting an organism to tailor its decision bias to environmental demands. Significance StatementThe ability to bias choices depending on the task context allows organisms to adapt to their environment. A liberal bias, for example, suits a situation when it is crucial to detect all events that might unpredictably occur, whereas a more conservative attitude pays off when avoiding errors is key. How the brain maintains such biased states over time remains unknown. We hypothesized that strategic liberal bias shifts arise through more unconstrained, irregular neural activity (higher entropy) suited to an unpredictable environment. Enhanced entropy in frontal regions indeed strongly reflected how much individuals shifted their bias to become more liberal. Modulation of neural variability through prefrontal cortex thus appears instrumental for tailoring decision biases to environmental demands.

Standard multiscale entropy reflects neural dynamics at mismatched temporal scales: What’s signal irregularity got to do with it?

“…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.…”

Multiscale entropy of ADHD children during resting state condition

“…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).…”