This method allows for the design and implementation of virtual reality experiments that collect physiological data from human participants. The experiments in virtual environment framework is implied to facilitate this process. The main advantage of this technique is the control of extraneous variables while collecting data from various sources, including physiological devices.
The implications of this technique extend toward cognitive science in general because of the potential for studying the relationship between cognition and emotion in a controlled environment. Though this method can provide insight into navigation behavior specifically, it can also be applied to other fields, such as environmental perception, behavioral geography, and decision making. Generally, individuals new to this method will struggle because the knowledge required to collect and analyze physiological measures is sometimes beyond that provided by a cognitive science curriculum.
Visual demonstration of this method is important because it provides other researchers with a step-by-step guide for collecting physiological data that includes the placement of electrodes. To begin, open the EDA-ECG software and create a new settings file. Set the sampling rate to 1, 000 hertz and select the appropriate number of channels.
Then, save the settings file and re-save a version of this file with a new name for the experimental session. Next, perform an open circuit zero on the EDA electrodes to obtain a baseline measurement of system conductivity. Open the experiment settings menu in the software and enter the experiment parameters.
Then, click start experiment. First, ask the participant to read the information sheet and sign an informed consent form. Then, use a wet tissue to clean the index and ring fingers of the participant's non-dominant hand.
After ensuring the participant's fingers are dry, connect the two EDA electrodes to the medial phalanges. Place the white, black, and red electrodes on the participant's body between the ribs according to the text protocol. Then, connect the three color-coded ECG wires to their corresponding electrodes.
While the participant completes the questionnaires, close the two side walls of the cubicle and prepare for the physiological measurement. Attach the blood pressure cuff to the non-dominant arm. Connect the two EDA wires to the electrodes on the participant's fingers.
Ensure the electrodes are attached to the correct locations. Then, turn off the light above the monitor and dim the overhead lights to the lowest setting. Next, zero the EDA channel to obtain a measure of the participant's starting level of skin conductants.
In the EDA-ECG software, open the Bio Amp dialog box. Then, choose the signal range in which the heart beat signal covers around one-third of the preview window. Start the recording with the software and ensure the signal is visible in the software window on the experimenter's monitor.
Then, start the blood pressure recording by pressing the appropriate button on the blood pressure machine. In the open unity software, click start measurements. Ask the participant to watch the baseline nature video.
Ask the participant to complete the training maze in order to practice using the joystick. In the training maze game, the participant will follow the arrows and collect floating gems. After this, instruct the participant to complete the navigation task.
Let the participant run through the navigation task. After the participant completes the navigation task, stop the EDA and ECG recording. Then, remove the blood pressure cuff, disconnect the cables to the ECG electrodes, and remove the EDA electrodes from the participant's fingers.
Inform the participant that they will be asked another series of questions on the computer, and that they may ask questions if necessary. In the evaluation menu in the eve software, press the add event marker button to mark the events in the physiological measurement files. Then, save the EDA-ECG file in the physiological measurement file in the EDA-ECG software.
Next, use the evertools package to export the experimental data for backup. Finally, tidy up the equipment and clean the electrodes with alcohol pads. Using this protocol, 60 participants were studied to investigate the effective stress on the acquisition of spatial knowledge during navigation.
As predicted, the physiological data indicated higher arousal for the stress group than the no stress group in terms of heart rate, but not in terms of EDA. In general, there was also a negative relationship between self-reported navigation ability and time required to learn the virtual environment. According to the visualized trajectories, the participants from the stress group also appeared to be more efficient in the virtual environment.
This indicates that higher arousal and spatial ability may be related to more efficient navigation behavior. This technique can pave the way for researchers in the field of cognitive science to explore the relationship between stress and human navigation behavior using virtual reality and physiological measures.
