Efficiency in Rule- vs. Plan-Based Movements Is Modulated by Action-Mode

Abstract

The rule/plan motor cognition (RPMC) paradigm elicits visually indistinguishable motor outputs, resulting from either plan- or rule-based action-selection, using a combination of essentially interchangeable stimuli. Previous implementations of the RPMC paradigm have used pantomimed movements to compare plan- vs. rule-based action-selection. In the present work we attempt to determine the generalizability of previous RPMC findings to real object interaction by use of a grasp-to-rotate task. In the plan task, participants had to use prospective planning to achieve a comfortable post-handle rotation hand posture. The rule task used implementation intentions (if-then rules) leading to the same comfortable end-state. In Experiment A, we compare RPMC performance of 16 healthy participants in pantomime and real object conditions of the experiment, within-subjects. Higher processing efficiency of rule- vs. plan-based action-selection was supported by diffusion model analysis. Results show a significant response-time increase in the pantomime condition compared to the real object condition and a greater response-time advantage of rule-based vs. plan-based actions in the pantomime compared to the real object condition. In Experiment B, 24 healthy participants performed the real object RPMC task in a task switching vs. a blocked condition. Results indicate that plan-based action-selection leads to longer response-times and less efficient information processing than rule-based action-selection in line with previous RPMC findings derived from the pantomime action-mode. Particularly in the task switching mode, responses were faster in the rule compared to the plan task suggesting a modulating influence of cognitive load. Overall, results suggest an advantage of rule-based action-selection over plan-based action-selection; whereby differential mechanisms appear to be involved depending on the action-mode. We propose that cognitive load is a factor that modulates the advantageous effect of implementation intentions in motor cognition on different levels as illustrated by the varying speed advantages and the variation in diffusion parameters per action-mode or condition, respectively.

Does aging amplify the rule-based efficiency effect in action selection?

“…Differences in t 0 between approaches to action selection show that processes not directly involved in the decision differ. In our previous study with healthy young adults, we found significantly higher drift rates (v parameter) in the rule-task than in the plan-task, suggesting, that decision-relevant information processing can be more efficient in the rule-task than in the plantask (Scheib et al, 2018). The DDM is of particular value in the context of aging, as diffusion parameters have previously been shown to be sensitive to aging in a variety of cognitive tasks such as lexical-decision tasks (Ratcliff et al, 2004b), signal detection tasks (Ratcliff et al, 2001), letter discrimination tasks (Thapar et al, 2003), memory (Spaniol et al, 2006), and rapid two-choice decisions in general (Ratcliff et al, 2006(Ratcliff et al, , 2007.…”

“…If-then rules (in some contexts referred to as Implementation Intentions) have been shown to facilitate many cognitive tasks (Gollwitzer and Sheeran, 2006;Wieber et al, 2015). Several motor cognitive studies have demonstrated that using such rules leads to shorter action initiation latency and reduced error rates compared to using a prospective planning approach when producing the same actions (Randerath et al, 2013(Randerath et al, , 2015(Randerath et al, , 2017Scheib et al, 2018;Stoll et al, 2022b). It has been hypothesized that rule-based action selection may have the potential to be particularly effective in improving the successful selection of grips in persons with difficulties in prospective planning.…”

“…Diffusion modeling has been used in many fields of psychology including research on memory and perception research (Ratcliff et al, 2001(Ratcliff et al, , 2004a(Ratcliff et al, ,b, 2006(Ratcliff et al, , 2007Thapar et al, 2003;Spaniol et al, 2006) to decompose reaction time distributions into cognitively meaningful components. Drift diffusion parameters may enable a deeper understanding of ruleand plan-based movement-selection approaches (Scheib et al, 2018; see Figure 1). In binary decision tasks (e.g., selection of pronated vs. supinated grips), the diffusion model allows for the statistical decomposition of reaction time distributions into cognitively meaningful parameters reflecting (among others) the speed of the decision process as the rate of information accumulation (drift rate, v), response caution as the distance between decision thresholds (boundary separation, a), and the duration of non-decision components (e.g., stimulus encoding, preparation of motor response, task switching, visualization) combined in the non-decision time parameter t 0 (Voss et al, 2004).…”

Served Well? A Pilot Field Study on the Effects of Conveying Self-Control Strategies on Volleyball Service Performance

“…Consequently, the effectiveness of goals and plans may depend on where they draw athletes’ attention to. Some findings from research on plans generally support this assumption, albeit suggesting that plans can be more effective than action goals if they have an internal focus on performing the action [44], which seems to be the case in the field of motor actions as well [45]. The existing literature thus points to potentially complex interactions between the content of goals and plans and their effectiveness in the context of sport.…”

Improvement of Apraxia With Augmented Reality: Influencing Pantomime of Tool Use via Holographic Cues

“…Pantomime of tool use is considered as very sensitive in detecting the presence of limb apraxia; typically the pantomime mode appears more sensitive as compared to actual tool use mode (3,15), however performance measures across these modes correlate and individual patterns appear stable (16,17). While both modes may retrieve similar concepts, differences may be represented by missing visuotactile feedback, i.e., the absence of mechanical interaction and cues from real objects, the heightened demand on imagery and the translation from mental images to motor execution (5,10,11,16,18,19). Contextual information may provide critical cues facilitating the access to an adequate motor concept and may constrain the possibilities for action production (15)(16)(17).…”