Abstract
Despite its prevalence in studying the causal roles of different brain circuits in cognitive processes, electrical microstimulation often results in inconsistent behavioral effects. These inconsistencies are assumed to be due to multiple mechanisms, including habituation, compensation by other brain circuits, and contralateral suppression. Considering the presence of reinforcement in most experimental paradigms, we hypothesized that interactions between reward feedback and microstimulation could contribute to inconsistencies in behavioral effects of microstimulation. To test this, we analyzed data from electrical microstimulation of the frontal eye field of male macaques during a value-based decision-making task and constructed network models to capture choice behavior. We found evidence for microstimulation-dependent adaptation in saccadic choice, such that in stimulated trials, monkeys’ choices were biased toward the target in the response field of the microstimulated site (Tin). In contrast, monkeys showed a bias away from Tin in non-stimulated trials following microstimulation. Critically, this bias slowly decreased as a function of the time since the last stimulation. Moreover, microstimulation-dependent adaptation was influenced by reward outcomes in preceding trials. Despite these local effects, we found no evidence for the global effects of microstimulation on learning and sensitivity to the reward schedule. By simulating choice behavior across various network models, we found a model in which microstimulation and reward-value signals interact competitively through reward-dependent plasticity can best account for our observations. Our findings indicate a reward-dependent compensatory mechanism that enhances robustness to perturbations within the oculomotor system and could explain the inconsistent outcomes observed in previous microstimulation studies.
Significance Statement Electrical microstimulation has been used to study the causal contributions of certain brain areas or circuits to cognition and behavior. Nonetheless, the overall impact of microstimulation on behavior remains inconclusive, hinting at neural mechanisms that interact with experimental perturbation of neural activity. We hypothesized that this interaction could be driven by the reward feedback animals receive while performing tasks, either with or without external perturbations. Using computational modeling and data from microstimulation during a reward-dependent decision-making task, we found microstimulation and reward-value signals competitively interact within the oculomotor system. This interaction enhances the system’s robustness to both internal and external perturbations. Our results have important implications for employing microstimulation in basic and clinical research.
Footnotes
We thank Chanc VanWinkle Orzell for her helpful comments on the manuscript. his work is supported by the National Science Foundation (CAREER Award BCS1943767 to A.S.) and the National Institutes of Health (NIH EY014924 to T.M.).