Abstract
Sex-based modulation of cognitive processes could set the stage for individual differences in vulnerability to neuropsychiatric disorders. While value-based decision making processes in particular have been proposed to be influenced by sex differences, the overall correct performance in decision making tasks often show variable or minimal differences across sexes. Computational tools allow us to uncover latent variables that define different decision making approaches, even in animals with similar correct performance. Here, we quantify sex differences in mice in the latent variables underlying behavior in a classic value-based decision making task: a restless two-armed bandit. While male and female mice had similar accuracy, they achieved this performance via different patterns of exploration. Male mice tended to make more exploratory choices overall, largely because they appeared to get 'stuck' in exploration once they had started. Female mice tended to explore less but learned more quickly during exploration. Together, these results suggest that sex exerts stronger influences on decision making during periods of learning and exploration than during stable choices. Exploration during decision making is altered in people diagnosed with addictions, depression, and neurodevelopmental disabilities, pinpointing the neural mechanisms of exploration as a highly translational avenue for conferring sex-modulated vulnerability to neuropsychiatric diagnoses.
Highlights
Almost every neuropsychiatric condition shows sex and/or gender biases in risk, presentation, etiology, and prognosis (Green et al, 2019; Grissom and Reyes, 2018; Shansky, 2019)
We have recently shown that examining the latent strategies underlying task performance --rather than differences in final performance--can reveal that individual males and females can take very different strategic paths to the learning of actionoutcome associations (Chen et al, 2020)
A crucial question remained unanswered: what computational differences made the males more exploratory? To address this question, we turned to reinforcement learning (RL) modeling to look for individual variability in latent cognitive parameters that could influence exploration and exploitation (Daw et al, 2006; Ishii et al, 2002; Jepma and Nieuwenhuis, 2011; Pearson et al, 2009)
Summary
Almost every neuropsychiatric condition shows sex and/or gender biases in risk, presentation, etiology, and prognosis (Green et al, 2019; Grissom and Reyes, 2018; Shansky, 2019) This raises the possibility that sex-modulated biological mechanisms could modulate cognitive processes that confer vulnerability and/or resilience to mental health challenges. An underrecognized source of variability in cognitive tasks is that there can be multiple ways to achieve the same level of performance on the primary dependent variables used to assess these tasks, such as “number of correct responses” This means that equivalent levels of performance could mask individual differences in how males and females are solving the same problem. We applied computational tools to characterize sex differences in the latent variables underlying behavior to understand sex differences in a key cognitive process regulating reward-guided behaviors: balancing exploration and exploitation
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