Bridging Motor and Cognitive Control: It’s About Time!

Abstract

Is how we control our thoughts similar to how we control our movements? Egger et al. show that the neural dynamics underlying the control of internal states exhibit similar algorithmic properties as those that control movements. This experiment reveals a promising connection between how we control our brain and our body.

Humans reconfigure target and distractor processing to address distinct task demands

“…For example, the adjustments to initial conditions in response to task demands and incentives in the current experiment may provide new insight into these other domains. Interestingly, control over initial conditions also play a central role in the neural dynamics of motor preparation (Churchland, Cunningham, Kaufman, Ryu, & Shenoy, 2010; Remington, Egger, Narain, Wang, & Jazayeri, 2018; Remington, Narain, Hosseini, & Jazayeri, 2018), highlighting the similarities across motor and cognitive domains (Ritz, Frömer, & Shenhav, 2020) and offering potential neural predictions for our task.…”

“…If the within-trial dynamics we observe reflect a “task set micro-adjustment” (Ridderinkhof, 2002), then this modeling approach may help unify switching dynamics across executive domains. Interestingly, control over initial conditions also plays a central role in the neural dynamics of motor preparation (Churchland et al, 2010; Remington et al, 2018b, 2018a), highlighting the similarities across motor and cognitive domains (Ritz et al, 2022, 2020) and offering potential neural predictions for our task.…”

Curiosity as a metacognitive feeling

“…Forward models automatically compare expected and observed dynamics of an action, in particular its predicted timing. The neural structures implementing these forward models seem to have been later recruited for the control of thought, i.e., metacognitive control and monitoring (Egger, Remington, Chang, & Jazayeri, 2019;Ritz, Frömer, & Shenhav, 2020). The forward models for cognitive control, however, do not use sensorimotor cues to automatically correct behavior ; nor do they result in automatic compromises between sensory sources; they rather attempt to assess informational quality with an eye to its predicted value (rewards and risks incurred) with respect to commitments to specific alternatives, in ways that are subject-specific, and relate to the agents' current goals and motivations.…”

Neuroscientific approaches to self-regulatory control in sports

“…That said, we feel it is important to call for more neuroscientific research on self-regulated sports performance because key questions have not yet been addressed comprehensively. It will be important to test the dACC's proposed role during sports performance, to analyze the effect of directly manipulating the value of self-regulatory control, to investigate the potential neurocomputational overlap between physical and mental effort (Ritz, Frömer, & Shenhav, 2020), and to get a better understanding of the differences between elite and recreational athletes in the neuronal processing of the self-regulatory demands in sports. We believe these are exciting questions and with this chapter we hope to encourage further research on self-regulatory control in sports.…”