August13, 2014.

Accordingto Paivo 1971, in his theory of cognition (duo coding theory)observed that, the human mind was capable of expanding its cognitionthrough verbal association and visual imagery as password code tofuture cognition(Ungerleider &amp Mishkin, 1982).Although visual and verbal codes are processed differently in thehuman brain, all are stored in the human mind inform of mental codewhich are later retrieved to recall information (Paivo, 1971). Manyresearchers are of view that, visual information is reinforced whenaccompanied by verbal codes that in turn enhance more cognition inthe human brain(Biederman, 1987).Cognition is a process in the human mind and relies on existingknowledge in order to generate new information. The cognition processis through conscious or unconscious means by which abstract andconcrete knowledge is processed to make new meaning or retrieve oldinformation.

Inthis experiment, the aim was to ascertain the level of cognition andlearning involving sequence of abstract images like visual passwordscompared to a sequence of objects. Researchers in psychology agreethat it is easier to recognize ordinary visual objects compared toabstract visual images such as pins or passwords that involve numeric(Matlin, 2009).Ideally, the human mind has multiple sources in the semantic systemof encoding ordinary objects than abstract images that do notresemble any real or related object and cannot be easily recognized(Peterson &amp Rhodes, 2003).As such, the recognition and learning of abstract images are hard andslow in the human mind. The following is an analysis report on anexperiment conducted to assess how hard it was to learn and recognizeabstract visual images compared to real objects.

Resultsand discussion

Inthis study the focus was to examine how difficult it was forindividuals to recognize and learn abstract images and real objectsin relation to accuracy and time of recognition (Grill-Spector &ampKanwisher, 2005). The results indicated that the capacity torecognize accurately and in time, abstract and object images observedpreviously depended to a small extent on the time lapse after theimages were displayed(Sternberg &amp Sternberg, 2009).During the learning process and the trials an assessment of theparticipants showed that they were accurate in recognizing both theabstract and object images.

However,most subjects recognized object images better compared to abstractvisual images regardless of time lapse between the initial display ofthe objects and abstract images and the second time they weredisplayed for recognition. Similarly, the length of time taken duringthe learning trials had no effect on the accuracy of the recognizedobjects and abstract images. The meaning is that, there is nocorrelation between the independent variable (length of display time)and the dependent variable (accuracy in identifying images) (Lycan,1999).

Inthe same line, the duration of time that lapsed before the abstractand object images were shown indicated that the subjects were slow inrecognizing the abstract images compared to the object images(Renaud, &amp De Angeli, 2009).The overall, study results support the hypothesis and past literaturestudies that it is hard to learn and recognize abstract images evenif the number of trial times was repeated(Sternberg &amp Sternberg, 2009).


Theabove study conforms to past study findings and theoreticalhypothesis that it is hard to learn and recognize abstract images.The capacity of the human memory is limited in the semantic system ofencoding abstract images it is easier to recognize ordinary objectsthan abstract visual images such as pins or passwords that involvenumeric. While the retention and accuracy capacity to rememberabstract images is confined to limited memory time, the accuracy oflearning and recognizing object images is less affected by time. Insummary, the mental ability, processing, ‘computation’ andcomprehension capacity of the memory span involving abstract visualimages is limited in the human brain regardless of time spentlearning the abstract visual images.


Biederman,I. (1987). Recognition by components: A theory of human imageunderstanding. PsychologicalReview,94, 115-147.

Grill-Spector,K., and Kanwisher, N. (2005). Visual recognition. PsychologicalScience16 21 52-160

Lycan,W.G., (Ed.). (1999). Mindand Cognition: An Anthology,2nd Edition. Malden, Mass: Blackwell Publishers, Inc.

MatlinM. (2009). Cognition.Hoboken, NJ: John Wiley &amp Sons, Inc.

Paivio,A (1971). Imagery and verbal processes. New York: Holt, Rinehart, andWinston.

Peterson,M. A. &amp Rhodes, G. (Eds.). (2003). Perception of faces, objectsand scenes: Analytic and Holistic Processes. New York: OxfordUniversity Press

Renaud,K., and De Angeli, A. (2009). Visual Passwords: Cure-all or snakeoil. Communicationsof the ACM. Vol.52 Issue 12, p135-140.

Sternberg,R. J., &amp Sternberg, K. (2009). Cognitive psychology (6th Ed.).Belmont, CA: Wadsworth, Cengage Learning.

Ungerleider,L.G., Mishkin, M., 1982. Twocortical visual systems: Analysis of Visual Behaviour, 549–586.