Effects of contraction bias on the decision process in the macaque prefrontal cortex

Abstract

Our representation of magnitudes such as time, distance, and size is not always veridical because it is affected by multiple biases. From a Bayesian perspective, estimation errors are considered to be the result of an optimization mechanism for the behavior in a noisy environment by integrating previous experience with the incoming sensory information. One influence of the distribution of past stimuli on perceptual decisions is represented by the regression toward the mean, a type of contraction bias. Using a spatial discrimination task with 2 stimuli presented sequentially at different distances from the center, we show that this bias is also present in macaques when comparing the magnitude of 2 distances. We found that the contraction of the first stimulus magnitude toward the center of the distribution accounted for some of the changes in performance, even more so than the effect of difficulty related to the ratio between stimulus magnitudes. At the neural level in the dorsolateral prefrontal cortex, the coding of the decision after the presentation of the second stimulus reflected the effect of the contraction bias on the discriminability of the stimuli at the behavioral level.

Prefrontal Cortex Neural Correlates of the Contraction Bias in Frequency Discrimination

“…In contrast to a previous study focusing on the decisional stage of PFC neurons [21], our research investigates the earlier stages of the task, namely the stimulation and maintenance epochs. Our findings reveal that the Bayesian estimator is consistently reflected in the state-space geometry from the presentation of the first stimulus until the end of the delay period.…”

“…Collectively, these factors can contribute to the emergence of perceptual biases [2]- [10]. These biases manifest in various forms, such as the central tendency observed in tasks involving magnitude or duration reproduction [11]- [15], the contraction bias observed in delayed comparison tasks [7], [10], [16]- [21], and the phenomenon of serial dependence observed in delayed response experiments [22]- [24]. A normative Bayesian account posits that perception emerges through the integration of a noisy representation of the stimulus with prior knowledge about the sensory environment [1], [19], [25].…”

“…Our current understanding of the relationship between neural activity and the contraction bias is still quite limited. However, there are some notable studies that have shed light on this topic [7], [20], [21]. One such study by Akrami et al (2018) highlighted the importance of working memory in the manifestation of the contraction bias.…”

“…Additionally, another study by Sarno et al (2022) explored how the contraction bias modulates dopamine activity in the midbrain. Benozzo and Genovesio (2023) analyzed the activity of prefrontal neurons to investigate the effects of the contraction bias on the decision-making process. While these studies are intriguing, they do not address the issue of how Bayesian computations leading to the contraction bias manifests in the activity of cortical neurons.…”