The Effect Of Motoric And Perceptual Learning On Reaction Times

Attention is thought to be selective-focused on one subject at a time. Traditionally, it has been assumed that automatic processing is involuntary, it does not require attention, and is relatively fast; whereas, controlled processing is voluntary, does require attention, and is relatively slow. We can conclude from this that the more we repeat a certain material or tasks the more it becomes automatic and effortless to us.

The reaction timer from Maths Is Fun (2014) is specific to three decimal places. The accuracy of the chosen source reduces the risk of statistical measures being slightly greater or less than they would be if only one or two decimal places were provided. Unlike other reaction timers that are available online, this particular source requires the subject to complete five trials before the mean is calculated. Undertaking multiple trials will be vital to this investigation because if the subject was to anticipate the event or have one delayed response, the trials that follow would reveal such errors, therefore increasing the reliability of the results.

Ullsperger, Bylsma, and Botvinick (2005) investigated whether the findings of Mayr, Awh, and Laurey (2003) can be replicated and how much they can be shown across different task performances. Their specific study was motivated by a prior experiment where Gratton, Coles, and Donchin (1992) found that after an incompatible type trial reaction times were reduced and target processing occurred more frequently than flanker processing on the next trial. Botvinick, Braver, Barch, Carter, and Cohen (2001) believed that this follows the conflict monitoring hypothesis where incompatible trials involve a conflict with the response leading to greater top-down information processing (Botvinick, Nystrom, Fissell, Carter, & Cohen, 1999). However, Mayr et. al (2003) argued that the congruency sequence effect found by Gratton et al. (1992) was due to repetition priming because of stimulus repeats in a flanker task. This may have led to a faster reaction time with repeated trials. Mayr et al. (2003) used two experiments to present evidence for their argument. Both experiments failed to show the effect found by Gratton et al. (1992) when target and stimulus items did not repeat from trial to trial.

ABSTRACT: The purpose of this experiment was to test whether a delay before recall would affect the serial position effect. The experiment was done by getting participants to take part in a simple tests; hearing words read out, then after they are read out, recalling them and writing them down. Two of these tests took place, one without a gap before recall, and one with. The results only partly supported previous research, with both tests showing a higher number of people remembering words at the start of the list, but unlike previous research findings, the last words of the list were not remembered

By doing so is finding support for hypothesis, “AA reflects a failure to consolidate short-lived encoded information into a durable form of memory” (Chen and Wyble,2016). In other words, AA shows brief information does not become a permanent and stable memory, stored in long-term memory. In order, find supporting evidence the authors performed 5 experiments. The first experiment tested consisted of elimination of AA by having participants report an attribute of the stimulus instead of the location, in order to separate the dependence of AA and location. The results suggested location information of the target was automatically stored. Experiment two tested, if AA only occurred because of the familiarity and repetition of targets However, despite eliminating the familiarities and repetition of targets AA still occurred. Lastly, the last three experiments were identical, but with changes in variables and tested the hypothesis. Experiment 3a results showed a weakening in AA by forcing the participants to consolidate the key attribute into memory. Experiment 3b showed the weakening in 3a was caused by having participants maintaining attributes in memory after delayed tasks. Lastly, 3c provided support the previous experiments in which participants were able to find the

After consent was given and the proceedings of the examination were briefly explained, EEG electrodes were attached to the subjects and they were given detailed instructions. Participants performed multiple tasks throughout the experiment, and the order of the tasks were counterbalanced across the participants. The participants were seated approximately two feet viewing distance and were instructed to press the right button mouse button if the center arrow was facing to the right and press the left button if the center arrow was facing to the left. Before the exam that was used for analysis, participants were given a practice block containing 30 trials where they were instructed to be as quick and accurate as possible. Then, the actual task was administered with 11 blocks of 30 trials. The participants received feedback on their performance. If a participant received a score of 75% or lower, a message of “Please try to be more accurate” was given. On the contrary, if the participant received above 90% a message of “Please try to respond faster” was displayed. However, if a participant was between 75% and 90%, the participant received a message that said “You’re doing a great job.”

Overall what the study shows is that as the time between cue and target increases people's performance tends to shift inversely. This is displayed as shorter instances (100ms) found individuals responding faster, relative to when they were longer (500ms) to which individuals would respond slower if they appeared on the same side, with only a minor increase when they appeared on the opposite. Another interesting finding from the study was that trail validity had no statistically significant effect on response times, essentially meaning that how likely a target was to appear had no real effect on how well individuals performed in the study.

When participants engaged in switch trials they had higher reaction times and error rates than on repeat trials. As evidenced by task-set reconfiguration hypothesis the mean reaction times for switch trials were higher (M= 1454.90, SD= 350.23) as opposed to (M=1241.16, SD= 305.90) for repeat trials (Monsell, 2003). That means that participants took longer to respond on switch trials versus repeat trials. This effect was also found on the mean error rate switch trials (M=.1215, SD= .1305) as opposed to repeat trials (M= .0885, SD= .1622). Participants made more errors on switch trials than they did on repeat trials. While these results are consistent with task-set reconfiguration theory we did not collect any background information on the participants. Therefore, factors such as participants with ADHD could have affected the results although this elates more to younger adolescents (Oades & Christiansen,

Elsner and Hommel (2004), test the hypothesis that learning of relationships between actions and perceptual consequences is accomplished by using associative learning. Stage one of the studies on action-affect learning, required participants to respond to arrows with key presses that were followed by a distractor tone at a period of either 50, 1000, or 2000ms. In stage two, respondents were required to respond to the previously irrelevant tone. Condition one highlights consistencies between tone-key press relationships and the learning phase. Whereas the other condition portrays inconsistencies. In terms of contiguity, they concluded that temporal contiguity is an important mechanism in both animal and human associative learning, (Elsner &Hommel, 2004). However, they argue that relying solely on contiguity would not obtain valid results – supporting Rescorla’s argument that contiguity is not sufficient enough in explaining associative learning. Although, Rescorla concludes that contiguity is not an adequate explanation of associative learning, more modern research suggests it is a collaborative factor. Elsner and Hommel (2004) conclude that action-effect acquisition is dependent on temporal proximity of action and effect on the contingency or frequency of their co-occurrence.

During the practice phase of the study, participants were trained on how to respond to our motion stimuli within the testing apparatus for this study. Participants viewed dot motion in one of eight directions and blindly keyed in the corresponding direction of motion on a number pad with arrows taped onto it. The direction of the dots changed for each trial and was randomized. This task served two purposes: the first was to train the participants to use the blindly use the directional pad during the task and the second was to check for any possible visual deficits that may interfere with the experiment. Participants had to complete 16 test items without getting more than 2 wrong in order to move on to the next part of the study. One participant was not able to reach this performance requirement even after explicit coaching, and therefore did not continue with the study and was replaced.

The experiment took place in an isolated, dim-light and sound-attenuated room with video control. During task performances, participants were seated in front of a monitor at a viewing distance of approximately 40-60 cm. The stimuli were presented with Presentation (neurobehavioral systems), a stimulus delivery and experiment control program. Participants could give a response with joysticks that were placed at both arms of the chair. The research assistant remained in the same room as the participants, however, interaction took only place during the breaks. The length of the experiment varied due to the tracking paradigm (see 2.3.3 Experimental design and task) and length of breaks.

The purpose of this experiments was to study the effects of hand preference on mental rotation. We did so by conducting an experiment where half of the participants were asked to use their dominant hand to respond to images rotating at one of four degrees or to use their non-dominant hand. I hypothesize a main effect for angle and hand dominance as well as interaction between the two variables in effecting the response time as well as the accuracy rate.

The reaction time (RT) of students was measured in the experiment to determine whether light or sound stimulus initiates a quicker response time. The question of whether or not RT was related to movement time (MT) was also challenged. Each student performed two test in random order; one testing the reaction time of a red light stimulus, or visual reaction time (VRT); and the other testing the reaction time of a “beeping” sound stimulus, or auditory reaction time (ART). The student completed the VRT trial by simply receiving the stimulus and pressing a button. The student placing and holding their hand on a button starts the ART trial. Once the student receives the stimulus (beep) they press the adjacent button as fast as they can. The ART trial does not only include the data of the RT, but also the data from the MT. Having previous knowledge that light travels faster than sound; one can predict that VRT is faster than ART. The prediction that MT is independent upon RT can be made with the thought that there are so many opposing variables that could affect the MT of an individual unrelated RT such as old age

Last year as a 2nd bachelor degree seeking student, I volunteered to participate in a motor learning study about putting golf balls that aimed to replicate previous studies [my basis for my proposal] that revealed learners studying and practicing a motor skill with the expectation of having to teach the skill could experience enhanced motor learning compared to learners expecting to be tested on the skill. One idea for future research was to conduct a similar study with novice, student pilots who had never received flight instruction to attempt a replication of similar findings in the development of motor learning theory, specifically the development of theory regarding the acquisition phase of learning a new skill (Daou, Lohse, & Miller, 2016).

“Reaction Time” is the interval of time between the application of a stimulus and the detection of a response and has been thought to differ based upon the effects of modality and warning signals. In the “Reaction Time” experiment