Computational protocol: Benefits of Instructed Responding in Manual Assembly Tasks: An ERP Approach

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Protocol publication

[…] During the experiment, at least two experimenters were constantly present in the laboratory in order to assure that experimental procedures were strictly followed. The experimenters were seated behind an opaque board (so that participants could not see them during the task) and they observed the participants through a red-blue-green (RGB) camera that recorded the entire experiment.Participants were seated in a comfortable chair in front of an improvised workplace including the improvised machine (Figure ). In order to extract the ERP component from continuous EEG recording, a single functional modification in the simulated assembly task was made. Simultaneously with the simulated assembly process, the participants were subjected to either the Numbers (Figure ) or Arrows (Figure ) task to prompt initiation of the assembly operation. Both tasks were presented on the 24” screen from a distance of approximately 100 cm in a balanced order across participants (with a 15 min break between the tasks). The screen was height adjustable and the center of the screen was set to be level with participants’ eyes. Upon presentation of the stimuli on the screen, the participants were instructed to complete the previously explained assembly operation (also graphically presented in Figure ).All the stimuli were presented for 1000 ms on a black screen background. In both tasks the appearance of the stimuli was randomized, with the condition that forbade the two consecutive appearance of the “no-go” stimuli (digit “3” in Numbers, and red arrow in Arrows task). Additionally, in the Numbers tasks, five randomly allocated digit sizes were presented to increase the demands for processing the numerical value and to minimize the possibility that subjects would set a search template for some perceptual feature of the “no-go” trial (the digit “3”). Digit font sizes were 60, 80, 100, 120 and 140 in Arial text font (similar to Dockree et al., ). The main difference between the tasks is that in the Arrows tasks the participants were instructed to initiate the simulated operation with the right hand (step 2) if the white arrow was pointing to the right, or with the left hand (step 3) if pointing left (as depicted on Figure ), while in the Numbers task, the participants could freely choose between step 2 or step 3 (from the Figure ) upon seeing the digit. Each task consisted of 500 stimuli, where the probability of appearance of the “no-go” stimuli was set at 10% (50 in total), while the “go” stimuli were presented 450 times. The inter-stimulus interval (ISI) between two consecutive “go” stimuli was on average 11,240 ms (STD = 410 ms), while between “no-go” and following “go” stimuli the average ISI was 3210 ms (STD = 120 ms). The duration of the each task was around one and a half hours, upon which participants had a 15 min break, before starting the second task. Thus, the whole experiment lasted around 3 h and 15 min.The task specifications were programmed in Simulation and Neuroscience Application Platform (SNAP), developed by the Swartz Center for Computational Neuroscience (SCCN). As explained in Bigdely-Shamlo et al. () and Gramann et al. (), SNAP is a python-based experiment control framework that is able to send markers as strings to Lab Streaming Layer (LSL). LSL is a real-time data collection and distribution system that allows multiple continuous data streams as well as discrete marker timestamps to be acquired simultaneously in an eXtensible Data Format (XDF). This data collection method provides synchronous, precise recording of multi-channel, multi-stream data that is heterogeneous in both type and sampling rate (Bigdely-Shamlo et al., ; Gramann et al., ), and is obtained via a local area network (LAN). [...] EEG signal processing was performed offline using EEGLAB (Delorme and Makeig, ) and MATLAB (Mathworks Inc., Natick, MA, USA). EEG data were first bandpass filtered in the 1–35 Hz range, following which the signals were re-referenced to the average of the mastoid channels (Tp9 and Tp10). Further, an extended infomax Independent Component Analysis (ICA) was used to semi-automatically attenuate contributions from eye blink and (sometimes) muscle artifacts (as explained in Viola et al., ; De Vos et al., , ). After this data preprocessing, ERP epochs were extracted from −200 to 800 ms with respect to timestamp values of “go” and “no-go” stimuli indicated by the SNAP software. Baseline values were corrected by subtracting mean values for the period from −200 to 0 ms from the stimuli. The identified electrode sites of interest for the ERP analysis in this study were Fz, Cz, CPz and Pz, as the P300 component is most prominent over the central and parieto-central scalp locations (Picton, ).For the “no-go” condition we extracted and averaged the ERPs across the trials. For the “go” condition, the ERPs that preceded the “no-go” condition were calculated. Following these steps, the grand average (GA) ERPs across participants were formed. Further, the P300 amplitude was calculated for both “go” and “no-go” conditions and for each experimental condition, using mean amplitude measure (Luck, ) in the time window from 350 to 450 ms, with regard to the time stamps of the stimuli. Finally, the statistical analysis on the obtained results was carried out. […]

Pipeline specifications

Software tools ERICA, EEGLAB
Application Clinical electrophysiology
Organisms Homo sapiens