Change Detection - Cog Experiment - Lab Report Example

Change Detection Introduction Change Detection Introduction Objective of the experiment The experimental fundamental objective is to test whether an observer could notice the changes which occurred before his/her eyes. The aspects of dynamism over time are what constitute change. Several mediums in the human body can detect the changes that occur over time. The detection is through observation. At times, changes can occur before the eyes of an observer, but he/she fails to notice those (Styles, 2006). Hypothesis: The hypothesis to this experiment was that the observers did not notice all the changes that took place before their eyes. Determining whether visual attention allocation was independent of change detection was the major problem with the hypothesis. There was allocation of independent variable of the detail level on the target of change and spatial distribution of attention, in this experiment (Hornsby et al, 2009). Subject of the experiment: The subject of this experiment was to carryout change detection tests to determine whether an observer would notice the changes that occurred before his/her eyes. Most people do not notice all the changes which occur before their eyes. This is not because they are blind but due to reasons such as poor or lack of attention required to notice such changes. In order to detecting the changes require much attention and visual simulation. Purpose of the experiment The experimental purpose is to determining the abilities of different observers to notice the changes that occur before their eyes. The dependent variables in the change detection experiment were: visual attention to the dynamic region and the internal mechanism attained by specific visual codes for detailed Scope of the experiment The experiment was carried out with limitations to observation as a method of detecting changes which occurred around an observer or before his/her eyes. Change blindness method was used to elaborate how visual memory is limited to currently features attended to. The use of mechanisms that provide a central perception to the world made the change detection experiment important (Styles, 2006) Method The flicker paradigm was used in the Change detection Cog lab experiment, in order to demonstrate the influence of attention and working memory in change detection (Van Horn et al., 2011). The presence or absence of a flicker between images was the independent variable while accuracy and response time in milliseconds were the dependent variables (Van Horn et al., 2011). The participant sample consisted of 32,789 global participants, including 49 undergraduate students enrolled in Memory and Cognition courses at Houston University, Texas (VanHorn et al., 2011). Some students received an assignment completion grade in exchange for their participation. Participants accessed personal Cog lab accounts and selected the Change Detection experiment within the Attention category (VanHorn et al., 2011). Participants were provided with preliminary instructions and background information, including a notice that the experiment would require at least 15 minutes to complete (VanHorn et al., 2011). The background information section provided participants with information explaining the theory behind the experiment and showing a sample Flicker Paradigm image (VanHorn et al., 2011). Participants were given a preliminary set of instructions for the experiment and reminded to log in to their personal accounts prior to beginning the experiment if they had not already done so (VanHorn et al., 2011). Participants were also informed of the free choice of submitting the results for addition to global data (VanHorn et al., 2011). Once they had finished reading the preliminary information and signing in, participants were prompted to press a button labeled “start experiments” (VanHorn et al., 2011). When each participant pressed the button, two windows appeared on the computer screen (VanHorn et al., 2011). One window contained the instructions for the experiment while the other contained the experimental tasks (VanHorn et al., 2011). Participants were prompted to read the instructions and then close the instruction window and begin the experiment (VanHorn et al., 2011). The experiment consisted of 16 trials, including eight image cycles with a flicker background and eight image cycles with no flicker background (VanHorn et al., 2011). Half of the trials contained identical images, and half contained a changed image (VanHorn et al., 2011). Participants pressed the space bar key to begin each trial and waited a brief period for images to load (VanHorn et al., 2011). Participants pressed the “c” key if they noticed a change between the images, and they pressed the “n” key if they did not notice a change between the two images (VanHorn et al., 2011). Participants were given the option to assign different keys to these functions if desired (VanHorn et al., 2011). Upon completion of the experiment, participants were asked if they wanted to add their data to global results, and they were provided with tables showing individual and class results (VanHorn et al., 2011). The results page included a brief explanation of the experiment along with an explanation of the results and the strength of the effect (VanHorn et al., 2011). Results Table 1: participant PSY4305FA11-6 Data summary Condition Proportion correct RT(Ms) flicker 0.625 8500.5 No flicker 1 6230.5 Table 2: group averages condition Proportion correct RT(MS) Flicker 0.6681318 12039.019 No flicker 0.9347075 7659.8706 Table 3: Global Averages condition proportion RT(Ms) Flicker 0.6403061 13904.6 No flicker 0.9260204 9916.597 Three sets of results were calculated for the Change Detection experiment, including data for Participant PSY4305FA11-6, group data for 49 University of Houston-Downtown students, and global data for all 32,789 participants (VanHorn et al., 2011). The independent variable was the presence or absence of flicker condition (VanHorn et al., 2011). The dependent variables that were measured included; accuracy and reaction time (VanHorn et al., 2011). Table 1 contains the data summary for participant PSY4305FA11-6. Her accuracy rate was 62.5% for flicker trials and 100% for non-flicker trials (VanHorn et al., 2011). Her reaction time was 8,500 milliseconds for flicker trials and 6,230.5 milliseconds for non-flicker trials; a difference of 2269.5 milliseconds (VanHorn et al., 2011). Table 2 contains the data summary for 49 University of Houston-Downtown students. The accuracy rate for this group was 64.0% for the flicker trials and 92.6% for the non-flicker trials (VanHorn et al., 2011). Reaction time for the group was 13,904.6 milliseconds for the flicker trials and 9,916.597 Milliseconds for non-flicker trials (VanHorn et al., 2011). Table 2a shows the standard deviation across participants for both dependent variables (VanHorn et al., 2011). Standard deviation for the accuracy measure was 0.1685428 for flicker trials and 0.15711918 for non-flicker trials (VanHorn et al., 2011). Standard deviation for the reaction time measure was 6,052.056 Milliseconds for the flicker condition and 5,365.99 milliseconds for the non-flicker trials (VanHorn et al., 2011). Table 3 contains the global data summary for all 32,789 participants. The accuracy rate was 66.81% for the flicker trials and 93.47% for the non-flicker trials (VanHorn et al., 2011). Average reaction time was 12,039.019 Milliseconds for flicker trials and 7,659.8706 Milliseconds for non-flicker trials (VanHorn et al., 2011). Table 3a shows the standard deviation across participants for both dependent variables (VanHorn et al., 2011). Standard deviation for the accuracy measure was 0.15750276 for flicker trials and 0.11047521 for non-flicker trials (VanHorn et al., 2011). Standard deviation for the reaction time measure was 21981.3 milliseconds for the flicker trials and 20508.248 Milliseconds for the non-flicker trials (VanHorn et al., 2011). Discussion In all three of the data sets that were examined, the accuracy rate was significantly higher for non-flicker trials and the reaction time was significantly quicker for non-flicker trials (VanHorn et al., 2011). These findings support the hypothesis that attention and working memory are key components of change detection (VanHorn et al., 2011). Participant PSY4305FA11-6 demonstrated a higher than average accuracy rate on non-flicker trials, and a slightly lower than average accuracy rate on flicker trials. These results could be accounted for by individual differences, or insufficient time spent searching for changes in flicker trials. The reaction time standard deviation measures for both groups were extremely large, ranging from 5,366 milliseconds to 21,981 milliseconds. In the global data set shown in table 3a, standard deviation for reaction time in the non-flicker trials is nearly triples the average reaction time measure. These data could be accounted for in one of two ways. Some of the participants may have been inattentive during the trials; therefore, increasing time spent on each trial. There is a big probability that participants spent greater amounts of time on each trial in efforts to be certain of their responses, while others rushed through each trial. VanHorn et al. (2011) provided support for the existence of change blindness, and the contributions of attention and working memory. Wilford and Wells (2010) examined the processing mechanisms involved in change detection and discovered a distinction between change detection and change localization. It was hypothesized that change detection for faces would be different from change detection for objects such as houses because facial processing tends to be more holistic than object processing (Wilford& Wells, 2010). This idea is supported by specialization in the fusiform face area that has been found in FMRI studies (Goldstein, 2011). Wilford and Wells (2010) defined change detection as noticing that a change has occurred, and change localization as knowing where the change occurred. They found that change localization was reduced in change detection trials with faces, and concluded that holistic processing has a negative effect on change localization (Wilford & Wells, 2010). These findings support the role of attention in change detection (VanHorn et al., 2011) because holistic processing does not allow for attention to every detail. Eased attentional focus (Tseng & Bridgeman, 2011). REFERENCES Styles E. (2006). The Psychology of Attention.2nd The Revised Edition. Psychology Press, 2006. Hornsby K. S. (2009). Spatial Information Theory: 9th International Conference, COSIT 2009, AberWrach, France, September 21-25, 2009, Proceedings. The Illustrated Edition. Springer 2009. Goldstein E. B. (2010). Sensation and Perception.8Th Illustrated Edition. London: Cengage learning, 2010. VanHorn, D., Francis, G., & Neath, I. (2011). CogLab Online Version 2.0 (4thed.). Belmont, CA: Thompson/Wadsworth Learning. Read More