attributes. In order to verify the proposed network structure of long-term knowledge, participants of experiments were asked to verify the truth of the statements such as ‘canary is a bird’ or ‘a canary is an animal’ (answer was in Yes/ No). These were generally class-inclusion statements in which the subject was word ‘canary’ (perhaps, you know, it is a bird) and the predicate took the form ‘is a’. A critical finding of such experiments was that as the predicate became hierarchically more remote from the subject in a sentence, participants took longer time to verify that it is true or false.
Thus, people took longer to verify that a ‘canary is an animal’ compared to that which said ‘canary is a bird’ because bird is an immediate superordinate category in which canary is subsumed while animal is a superordinate category which is more distant and remote from the concept canary. According to this view, we can store all knowledge at a certain level that ‘applies to all the members of a category without having to repeat that information at the lower levels in the hierarchy’. This ensures a high degree of cognitive economy , which means maximum and efficient use of the capacity of long-term memory with minimum redundancy. Fig.
. : The Hierarchical Network Model Is dangerous Can bite Animal Has skin Can move around Eats food Breathes Has wings Has feathers Can fly Can sing Is yellow Canary Ostrich Has long thin legs Can’t fly Is tall Swims upstream to lay eggs Is pink Is edible Shark Bird Fish Can swim Has fins Has gills Salmon So far we have discussed concept as unit of representation of knowledge in the long- term memory and looked at various ways in which concepts get organised. Does this mean that knowledge is encoded only in word-like format or can there be other ways of encoding? It has been shown that information can be coded in a perceptual format or in terms of images.
An image is a concrete form of representation which directly conveys the perceptual attributes of an object. If