Data Analysis

Data Analysis Project Introduction Implicit memory is a type of memory that does not require conscious recollection of past experiences that have led to that memory forming (Roediger, 1990). Implicit memory is often demonstrated in the improvement of skills, such as performance in cognitive, motor or perceptual tasks, where the individual can not explicitly say how this improvement has occurred (Atkinson et al, 20003). Implicit memory can be shown in visual search tasks, where the participant implicitly remembers where an object will be found due to the context in which the object was last viewed. This is called the “Contextual Cueing effect” (Chun and Jiang, 1998). The contextual cueing paradigm was first coined by Chun and Jiang (1998) in their study on implicit learning in a visual search task. They claimed that if an objects spatial location remains constant across trials it will guide their spatial attention more effectively to the correct location of the object in any following trials. In this experiment participants took part in a visual search task in which they were either shown a display they had already seen before (old display condition) or a new display that was unfamiliar to them. In the old display the target object appeared in the same spatial location and there were 12 different display that could appear in this condition . In the new display the target appeared in a novel location amongst the distracter items. The results showed that reaction times were indeed faster in the old display trials than the new display, demonstrating the contextual cueing effect. The visual context in which an object is presented effects where we might look for the object later on. Other cues could include the colour and size of an object (Chun, 2000). There are at least two separate things that need to happen for contextual cueing to occur. There must be some learning of the spatial location of a target when the first display is shown. If this does not happen the visual system will not recognise the repeated displays in following conditions. Secondly the information that is implicitly remembered must be capable of guiding the spatial attention to the location of the target (Lleras and von Muhlenen, 2004). An example of contextual cueing in everyday life would be if you were looking for milk in a supermarket. You

would know immediately where the object is through implicit learning of the layout of the supermarket and the context in which the milk is found., thus it would not take long to find the object. However if the supermarket were to change the stores layout, the implicit memory is of no use, thus it would take longer to find the object as the context in which the object is usually found has changed. Implicit learning may also be affected by our emotional state. In Levine and Burgess study (1997) participants were assigned to either a positive or negative emotions group. The experimenters manipulated moods by randomly assigning undergraduate participants with a grade from “A” to “D” on a surprise quiz. They were then asked to recall a narrative and describe their emotional state. Levine and Burgess found that participants who were in the negative mood group recalled less of the narrative than the positive mood group. Research has shown that the negative emotion of fear causes the amygdala to release the two stress chemicals cortisol and vasopressin. To cope with the stress the body shuts down our higher order, top own processing, impairing the formation of memories and our level of performance (Adolphs, 1995). Hypothesis 1 - there will be faster reaction times in the old display condition than the new display condition. Hypothesis 2 - Fear will produce slower reaction times than the count only and control mood groups.

Results The participants mean reaction times were calculated for each display condition (old and new) and for each mood condition (count only group, fear group and the control group). In the control group the mean reaction time in the old condition was 1004 ± 40ms. The mean reaction time in the new condition for the control participants was 1109 ± 50ms. An independent samples t-test showed there to be a significant 105 ± 49ms contextual cueing effect between old and new display reaction times. In the count only group the mean reaction time in the old condition was 1001 ± 55ms. The mean reaction time in the

new condition for the count only participants was 1112 ± 57ms. Again using an independent samples t test a significant 111 ± 10ms contextual cueing effect between old and new display reaction times. For the Fear group the mean reaction time in the old condition was 1041 ± 41ms. The mean reaction time in the new condition for the fear group was 1112 ± 31ms. Using an independent samples t-test a significant 71 ± 49ms contextual cueing effect between old and new display reaction times in the fear group.

Table to show the mean reaction times in each of the mood groups for the old and new display Mood

Old Display

New Display

Control

1004

1109

Count only

1001

1112

Fear

1041

1112

The data in this experiment was averaged across all participants and plotted as a function of epoch separately for the control group, the count only group and the fear group (see graphs below). All three graphs show that overall reaction times decreased with increased epoch. As demonstrated earlier, reaction times were quicker during the old display type than the new, again demonstrating the contextual cueing effect.

A factorial analysis of variance was then conducted on the data to see whether there was a main effect for display type, mood or a display x mood interaction. The within subject factor was the type of display (old/new). The between subjects factor was the mood of the participants (either control/count only/fear participants). There were 5 different epoch’s. The factorial analysis of variance showed there were significant main effects for epoch, F(4,24) = 986.75, p < 0.05, significant main effect for display type F(1,27) = 326.53, p < 0.05. There was also a significant display x mood interaction, F(2,27) = 5.79, p < 0.05.

Two follow up one way analysis of variances were then conducted separately for the old and new display types to explore whether reaction times differ significantly across the 3 mood groups. For the old display there was a statistically significant difference at the p < .05 level in reaction times across the three mood groups: F(2,27) = 10.31, p < .05. Post - hoc comparisons, using Tukey HSD test indicated that the mean scores for the control

group (M = 1004.7, SD = 19.54) was significantly different from the fear group (M = 1041.44, SD = 16.997). The Count only group (M = 1000.74, SD = 28.2) did not differ significantly from either the control group or the fear group. A second one-way analysis of variance was carried out on the data from the new display. For the new display there was not a statistically significant difference in the reaction times across the three mood groups.

Discussion The results showed a significant main effect for display type. The old display condition produced significantly quicker reaction times than the new condition. This concurs with the first research hypothesis and further demonstrates the contextual cueing effect. It shows that participants had implicitly remembered where the target had first appeared, thus they knew where to look for the object when the familiar context arose. The results also showed that the participants who were experiencing fear had slower reaction times than the other two mood groups. This too supports my second hypothesis, showing that fear actually impaired performance. On flaw of the study is the extent to which fear was actually induced. For some the task could have seemed menial, they may have got bored or distracted therefore affecting the validity of their level of fear. Other participants may have been very confident in their ability to do this task, thus would not be feeling much, if any fear. This begs the question of how much fear would a counting task produce? It certainly would not produce the same amount of fear and anxiety as doing a bungee jump. This then questions the validity of the task as it is possible that not all participants in that condition went through that emotion. On the other hand it could have produced an unethical amount of fear. The participants were told that their performance was related to intelligence and that their reaction times would be compared with other participants. This could have produced an unhealthy amount of fear and participants with a low self esteem may have reacted badly.

The majority of participants in this study were male (21 out of 30 participants). These results cannot be generalised to the female population. It could be that males are better/worse at visual search tasks than women, thus these results would not be valid. Also, women have been found to be more emotional than men (Barrett et al, 1998), so it could be that they were more affected (i.e. felt more fear) than the men in the fear group. The size of the sample is also questionable. There were only 30 participants in the experiment. It would be hard to generalise such a small number to the rest of the population. Also the mean age on the participants was quite young (23.7 years), again making it hard to generalise. It could be that younger people are better/worse at visual search tasks or that they would be more/less effected by someone trying to induce fear into them. The experiment was conducted in a laboratory setting. This allows for experimental control making this type of experiment more reliable and consistent. However this environment lacks ecological validity and cannot be generalised to everyday life in an everyday setting. Being in a laboratory with experimenters could have induced anxiety in the participants who were in the control or count only group, thus affecting the validity of the results. It could be that all participants felt some kind of fear, therefore making the results for the control and count only group irrelevant. Conclusion This study illustrates how implicit learning and contextual cues can affect performance in a visual search task. It also demonstrates that when you feel anxious or fearful your performance in such a task will be impaired. This study instigates the investigation of emotions on implicit learning. Further studies could address the impact of positive emotions (excitement), on implicit memory. Would this too impair performance? Or would positive emotions bring about better performance in visual search tasks.

References

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