Methodological considerations for the force-matching task

Abstract

The force-matching task integrates haptic technology and electrical engineering to determine an individual's level of sensory attenuation to somatic stimuli. The task requires a detailed methodology to facilitate reliable and replicable estimates, and there has been a distinct lack of re-evaluation of the methodological processes related to this paradigm. In this task, participants are asked to match a force delivered to their finger, either by pressing directly on their own finger with their other hand (known as the direct condition) or by controlling the device using an external potentiometer to control the force indirectly through a torque motor (known as the slider condition). We analysed 138 participants to determine 1) the optimal number of replications (2, 4, 6, or 8 replications) of the target force, 2) the optimal time window (1-1.5 s, 1.5-2 s, 2-2.5 s and 2.5-3 s) to extract the estimate of sensory attenuation, 3) if participants' performance during the task improved, worsened or was stable across the experimental period regardless of condition, and 4) if learning effects were related to psychological traits. Results showed that the number of replications of the target forces may be reduced from 8 without compromising the estimate of sensory attenuation, the optimal time window for the extraction of the matched force is 2.5-3 s, the performance is stable over the duration of the experiment and not impacted by the measured psychological traits. In conclusion, we present a number of methodological considerations which improve the efficiency and reliability of the force-matching task. HIGHLIGHTS: • The force-matching task determines an individual's level of sensory attenuation • The optimal number of replications of the target force may be reduced from 8 • The optimal time window to extract the matched force is 2.5-3.0 s • The estimate of sensory attenuation is stable across the duration of the task.

Keywords: Force-matching; Methodology; Perception; Sensorimotor; Sensory attenuation.

Fig. 1

Standard box plots showing the distribution of mean force error values across participants in the direct and slider conditions. A statistically significant difference was determined between the direct and slider conditions

Fig. 2

Confidence interval plot of mean force error and 95% confidence intervals across different time windows in the direct condition

Fig. 3

Confidence interval plot of mean force error and 95% confidence intervals across different time windows in the slider condition

Fig. 4

Confidence interval plot of mean force error and 95% confidence intervals across trial sessions (1–64). Conditions were counterbalanced across participants. No observable trend or learning effects are identified

Fig. 5

Histogram of the error coefficient showing the individual variation between participants. The error coefficient represents the slope of the mean force error of 64 trails, calculated via a linear regression analysis for each subject