Human Cogntive Architecture - Pattern Recognition

One may be tempted to suppose that we, who experience the world through vision, experience a very different world from the worlds expereinced by bats or dolphins, who rely more on hearing, dogs or rats who make greater use of smell … or spiders or scorpoins who are attuned to mechanical variations. But at sufficiently abstract level, our worlds are all the same three dimensional Euclidean world – Roger Shepard (Solso 1994) (73)

Visual pattern recognition influences several areas -computer vision, machine learning, robotics, neuroscience, psychology, biological vision, AI, cognitive science, biological perception, visual arts and all aspects of or daily life (object recognition).

This paper focuses on visual cognition and pattern recognition; as these influences the human cognitive architecture more than tactile and auditory pattern recognition. Pattern recognition is the key phenomenon in visual cognition it distinguishes human cognitive architecture and bridges top-down and bottom up information processing approach. It also connects inside with outside.

Thus connecting human wetware (mind brain complex) to wide-ware of the world.

I have used visual arts and illusion to explain pattern recognition because in spite of being abstract and illusive they present interesting good case for schema construction using top-down and bottom up processing. I claim that in pattern recognition top-down processing plays a critical role. This paper is divided into following section: Brain Visual System Complex, Visual Arts, Pattern Recogntion in Non Humans and Instructional implication has been explained using the theories of visual literacy. Brain Visual System Complex

Evolutionary story Soslo has depicted 248 million years of organic evolution using 31 day January month of 2000.

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Insects, dinosaurs, reptiles evolved a well-developed eyes during this period. On January 31 at 11. 59 am human like form appeared and within last 10 minutes falls the entire history if visual arts (Solso 1994) (24). Human eyes are not the most complex visual system the eyes of simple insects are more complex they have many lenses and receptors, while we have just one lens with receptors. Evolutionary biology emphasises that brain and visual system have evolved together as a visual cognitive complex in human.

While simple brained animals have complex optical system; it seems complex brain offsets the need of a complex visual system in humans (Solso 1994) (14). Based on Darwinian Evolutionary Theory- human capability to identify, recognise and differential patterns (like dark, from light, blues, from greens, straight lines from curved and moving objects from stationary) has significantly increased the chances of survival. Cognitive psychology elucidates that raw data of sensory signals is meaningless and random. But when these signals fall on a decoding visual system and brain complex they weave a rich pattern of meaningful relation.

Most intriguing part is the corresponding, concurrent and complimentary evolution of sensory system, brain and the central nervous system (Solso 1994) (47) Search for meaningful pattern recognition involves at least three parameters: ? What is an object? ? Where is it? ? What is it doing? Pylyshyn elucidates that behind the “smart” functionality of the visual system is messy yet sophisticated hardware: As the light sensitive surface of the eye are two dimensional, so the sense of depth in visual system comes from the source of information. After ecades of research we now know that part of information of depth comes from the difference between the patterns the two eyes receive. With all our understanding of stereo vision we are still far removed from understanding how does this difference in 2d vision translates to 3d experience? A very small part fovea has sufficient acuity to recognise pattern. Moreover eyes focal length differs for different colours. There is a blind spot 10-13 degrees away from fovea. To add the mess the eyes are in constant motion jumping around in rapid saccades several times in each second.

Retina our primary contact with the world is not uniform nor it is flat and has uneven distribution of cones & rods. Lastly it is continuously smeared with the moving information. However brain builds a uniform, detailed, gapless, 3d-video patterns from the sketchy inputs in the face of such dynamic and impoverished information processing system. Pyhshyn claims strategies like focal attention play a critical role in connecting vision and cognition (Pylyshyn 2003) (5). Evolutionary biology favours the case that top-down processing in pattern recognition is the key distinguishing factor of human architecture.

True believers in real patterns Looking at history from twelfth century till date we find philosophers and thinkers instinctively find patterns in chaos right. Plato, Pythogorus, Euclid, Ptolemy, Coprinicus, Newton, Einstein etc all the thinkers have been searching ways to establish order in chaos. It seems that we love to accept linearity, smoothness and stability in the face of the world that is largely unsmooth and random. But are we looking for real patterns and are these patterns inside or they are out side and how do we assign meaning to these patterns. As per Dennett

We use folk psychology interpretation of each other as believers, intenders and the like – to predict what people will do next. .. Folk psychology helps us understand and empathise with the others, organise our memories, interpret our emotions and flavour our vision in thousand ways, but the heart of all these is enormous power that predictive folk psychology. Without the predictive power we could not have any interpersonal relations at all; human activity would be just so much like “Brownian motion” (Dennet 1991) Dennett presents a interesting story which aims to answer the above questions.

He claims objective pattern “pops out” when we view the world through appropriate lenses. Like in the consequence of 2, 4, 6, 8,……. are different yet when seen through arithmetic lens the exhibit a common pattern add 2 pops out. Similarly intentional stance is the only lens that can help recognise real patterns (Clark 2001) (52-53). Dennett uses an John Conways game of life to highlight real patterns make available potent generalisations and predictions further claims that to miss a pattern is to miss some thing real and explanatory useful, even though every thing that occurs depends on the underlying simple rules (Clark 2001). 52-53) This elaborates the point the intentional stance is crucial for us to believe and attach meaning to pattens. True believers will always believe in real patterns. Intelligence of the human information processing system lies on our capability to recognise, predict and generalise real patterns. Visual Arts: Symbol manipulation Kose in paper summarises the views of these three thinkers. For all symbols gets meaning from convention. Goodman thinks denotation is the primary vehicle for representing. Gardener stresses on specific set of skills in rder to produce or read meaning with a particular symbols system. Cassier emphasis art objects derive meaning from the process of creation for him action and psychology of the artist is the key to understand. I feel representation is the core of cognitive architecture and symbolism is at the core of representation but it is difficult to take reductionist view. It does not seem relevant to elaborate this debate here. However the discussion brings three key concepts to focus: conventionality, specific skill set and artistic/aesthetic experience.

All the three points are relevant to process of pattern recognition. Illusion: Limits of Pattern Recognition Solso surmises critical role of experience and top-down approach in view art. The viewing of art causes an immediate conscious experience in people. We see colours, shapes, contours, objects, distances, and interactions (among other things) and, when all of these impressions are sensed, the brain brings meaning and comprehension to the art object. …Our mind supplies reasonable inferences to our consciousness about a visual scene, which may be, in fact, absent in the object.

We ‘see’ behind occluded objects, feel motion, and react emotionally to provocative themes even though these things may not literally exist. In the cognition of art, our past knowledge supplies consciousness with context. Experience colours art. We understand Picasso’s Guernica, Michelangelo’s, Sistine Chapel, and Rembrandt’s Self-portrait (1658) better because we can feel the intensity of women and children being victimized in the embittered Spanish Civil War, know the Biblical story of creation and man’s fall from grace, and comprehend the weathered features of an old man’s face (Solso 2000).

A viewer’s intention in viewing art and personal history strongly influences what he or she looks at in an object. This, in turn, determines which patterns of neural activity are aroused. In addition to situational demands, each person views art with a unique personal history which biases his or her attentional focus — a Nebraska farmer might attend to different features in Grant Wood’s American Gothic than would a New York fashion designer (Solso 2000). E H Gombrich illustrates core of top-down approach and important element of cognitive architecture the guided projection:

It is without the support from any structure that the beholder must mobilise his memory of the visible world and project it into the mosaic of strokes and the dabs on the canvas before him. It is here, therefore principle of guided projection reaches its climax. The image, it might be said had no firm anchorage left on the canvas it is only conjured up in our minds. The willing beholder responds to the artist’s suggestions because he enjoys the transformation that occurs in front of his eyes (Gombrich 1986). Artists use various cues to fool the system to activate the relevant schema in viewers mind using top-down processing.

When the pattern recognition (perception) departs from the external world, to disagree with the physical reality, it means one is experiencing an illusion. However illusion differs from the truth (Gregory 1997). Pylyshyn starts his book Seeing and Visualising with a honest statement by Galeolio: “…. if the man had been born blind, philosophy would be more perfect, because it would be more perfect, because it would lack many false assumption that have been taken from the sense of sight. ” (Pylyshyn 2003) ( Preface) Illusion expose limits or the leaky architecture of two complex structures brain and the visual system.

Top-down processing: Pattern recognition of the objects involves knowledge of the world as the sensory data is impoverished and hardly relevant (Gregory 1997). Bottom up Processing: Pattern recognition of the objects uses information from the optic array, which contains sufficient information to guide behaviour. Evolution has produced organisms that are sensitive to the invariants in the optic array and does not require prior knowledge (Gregory 1997). These two approaches cause different type of illusions. Cognitive Illusion due top-down processing resulting in misrepresenting of knowledge.

Physical Illusion due to the disturbance of light, between objects and the eyes, are different from illusions due to the disturbance of sensory signals of eye, though both might be classified as ‘physical’. Physical causes: In human vision ‘top-down’ seems to be more important than ‘bottom-up’. This might be because there are more downwards fibres from the cortex to the lateral geniculate bodies LGN ‘relay stations’ than bottom-up from the eyes (Gregory 1997). Classification Visual illusions can provide evidence of object knowledge and working rules for vision, but only when the phenomena are explained and classified (Gregory 1997).

A tentative classification is presented, in terms of appearances and kinds of causes in Appendix B (Gregory 1997). Types of illusions: Gregory divides appearances of illusions into classes based on errors of language ambiguities, distortion, paradoxes and fictions. There seems to deeper connection in language and visual system. It kind of connects Chomkys deep structure and surface structures theory. Ambiguities Perception changes while the input from the eyes remain same. A retinal image is infinitely ambiguus which could respond to infinitely possibilities but we see only one (Gregory 1997). Paradox

False assumptions creates paradox. Distortions Illusion due to distortion of retinal signals, perspective, brightness, colour. Fictions Suggests fictional forms Opt- Art The pictures are extremely distrubing, Jazzing, moving and generating ghostly shapes (Gregory 1997). Model to understand top-down and bottom-up processing To the ‘bottom-up’ signals and ‘top-down’ knowledge, Gregory adds ‘sideways’ rules. Both top-down and sideways are knowledge. These can be considered as ‘ins-and-outs’ of [pic] Tentative ‘flat box’ of’ vision. As usual, signals from the eyes and the other senses are ‘bottom-up’.

Conceptual and perceptual object knowledge are shown in separate ‘top-down’ boxes. Knowledge as embodied in the general rules. is introduced ‘sideways’. Perceptual learning seems to work largely by feedback from behaviour (Gregory 1997). The historical study of systematic misperceptions (illusions), combined with a recent explosion of techniques to measure and stimulate neural activity, has provided a rich source for guiding neurobiological frameworks and experiments to better understand the cognitive architecture (Eagleman 2001). Arts & Brain: Search for essentials E. H.

Gomrich highlights Plato from Sohpists and makes strong point on the very basis of representation “that we make a house by the art of building, and by art of painting we make another house, a sort of man-made dreams (pin-ups and comics) produced for those who are awake? ” (Gombrich 1986) Zeki claims that like brain visual arts is search for essential. The pre-eminent function of the brain is the acquisition of knowledge about the world around us. Just as brain searches for constancies and essentials, so does art (Zeki 2002) (Preface). .. the artist can find the models that he depicts in his mind, his inner vision, not the external world.

When artists try to fool the brain and its record, they can only do so with respect to its stored memory. Even when they don’t know much about the brain, artists were and are aware of the reality of perception and the appearance of the painting (Zeki 2002). V. S. Ramachandran and William Hirstein while explaining Peak Shift Affect take different view, art is a process of selection and amplification of the essentials. The purpose of art, surely, is not merely to depict or represent reality (western art) —for that can be accomplished very easily with a camera—but to enhance, transcend, or indeed even to distort reality.

The word ‘rasa’ (might be similar Platonic ideal form) appears repeatedly in Indian art manuals and has no literal translation, but roughly it means ‘the very essence of. ’ So a sculptor in India, for example, might try to portray the rasa of childhood (Plate 2), or the rasa of romantic love, or sexual ecstasy (Plate 3), or feminine grace and perfection (Plate 4). …the peak shift effect: If a rat is rewarded for discriminating a rectangle from a square, it will respond even more vigorously to a rectangle that is longer and skinnier that the prototype.

An evocative sketch of a female nude may be one which selectively accentuates those feminine form-attributes that allow one to discriminate it from a male figure; Finally, given constraints on allocation of attentional resources, art is most appealing if it produces heightened activity in a single dimension (e. g. through the peak shift principle or through grouping) rather than redundant activation of multiple modules. Consider the way in which a skilled cartoonist produces a caricature of a famous face, say Nixon’s.

What he does (unconsciously) is to take the average of all faces, subtract the average from Nixon’s face (to get the difference between Nixon’s face and all others) and then amplify the differences to produce a caricature. The final result, of course, is a drawing that is even more Nixon-like than the original (Hirstein 1999). ADD DIAGRAM 3 A circle represent the loaf of bread (they are round in Viena), a curve added on top will turn into a shopping bag, two little squiggles on its handle will shrink into a purse, now by adding a tail here was a cat (Gombrich 1986).

Gombridge uses the simple drawing game to emphasize the power of metamorphosis. Once the tail is added the purse gets destroyed and cat is created; you cannot see the one without obliterating the other. This is simply highlights our capacity to recognise, amplify and generalise a pattern (Gombrich 1986). The way the language of art refers to the visible world is so obvious (due to bottom up processing) and so mysterious (top down processing) that is still largely unknown except to the artists (high-stung on visual schema) themselves who can use it as we use languages – without needing to know its rammar and syntax (Gombrich 1986). So we see Zeki’s focus on Inner Vision, Plato’s emphasis on dream, Ramchandran principle of peak shift affect and Gombridge drawing experiment. All point to the same core function of the brain, using top-down approach to recognise, predict, amplify and generalise the pattern. Schema Development Gombrich in his book Arts and Illusion attempts to address the issue of art universals (schema) and peculiarities (creativity) in artists using science, psychology, and philosophy. Core of his version his is the theory of “schemata development and correction”.

This is derived from the idea that the artist “begins not with his visual impression but with his idea or concept” and that the artist uses adjusts this idea to fit, as well as it can, the object, landscape, or person before him or her. Gombrich calls this theory “making and matching. ” E H Gombrich while highlighting F. C. Ayers point claims that no artist can imitate reality without schema: The trained drawer acquires a mass of schemata by which he can produce schema of an animal, flower or a house quickly upon the paper.

This serves as a support for the representation of his memory images and he gradually modifies the schema until it corresponds to that with which he would express. Many drawers who are deficient in schemata and can draw well from another drawing cannot draw from the object. The dry psychological phenomenon formula correction can tell us a good deal, not only about the essential unit between medieval and post medieval but also of their vital difference. To Middle Ages schema is the image; to post medieval artists, it is the starting point of corrections, adaptation, the means to probe reality and to wrestle with the particular (Gombrich 1986). .. For it is not only the scientists of the stamp of Camper who can examine the schema and test its validity. Since the time Leonardo, at least, every great artist has done the same, consciously, unconsciously. Upto 19th century artist where more like trained drawers and focus was on universal features ideal pattern (schema). However in late 18th and early 19th Century artists turned against the traditional methods. Gombrige classifies this period as struggle against schema (Gombrich 1986). Gmobridge mentions a statement by Constable who is the centre of the struggle for schemata.

Constbale explains elegantly his position in the history of visual arts: I have endeavoured to draw a line between genuine arts (peculiarities or uniqueness) and the mannerism (traditional schemata), but even the greatest painters have never been wholly untainted by manner. Painting is science and should be pursued as the inquiry into the laws of nature. Why, then, may not landscape painting be considered a branch of natural philosophy, of which pictures are but experiments? (Gombrich 1986) Gombridge – To a see patch on a close canvas as a distant mountain is to transform it in according to its meaning.

These transformation explain the paradox that world cannot look like a picture, but a picture can look like a world. … it is not the ‘innocent eye’ but the inquiring mind that knows how to probe the ambiguities of vision. Gombrich brings an interesting point to notice- Art is a story of schema creation by trial & error and testing. A search for consistencies through anticipation and testing. Bruman and Postman- All cognitive process are represent making a hypothesis (pattern) and matching (pattern) (Gombrich 1986). Nuerological basis for schema in Artist in brain The eye (and other sensory organs) and brain are now thought to be onceptually related. Many theorists suggest that the eye is an extension of the primary visual cortex. Most visual signals follow a well known neurological route (from the retina, to the lateral geniculate bodies, to the primary visual cortex in the occipital lobe) (Solso 2000). The study was conducted on distinguished portrait artists and a novice. The artist selected for this task, HO, is one of Britain’s most. The non-artist used in this study who served as a control subject (AH) was a graduate student in psychology at Stanford University; 32 years old, right handed male with no formal training in art (Solso 2000).

Findings: Study suggest two main findings. First they confirm that an area of the brain frequently associated with facial identification was specifically activated. Second, the lower level of activation of the artist indicates that he may be more efficient in the processing of facial features than the novice (Solso 2000). Thus, these two main findings considered together suggest that an expert portrait artist, who frequently sees and draws faces, dedicates relatively less energy to the processing of faces and more to the processing of these features in terms of their associated correlates.

In a phrase, the artist thinks portraits more than he ‘sees’ them. Thus we see pattern recognition is more case of schema construction using top-down processing. Aesthetics: Celebration of Pattern recognition: Geyer makes an interesting argument substantiating the point that aesthetic celebration of celebration of our capability of pattern recognition. Geyer highlights Gombrich to state a point that the act of pattern construction is what makes us perceivers rather than mere responders to the stimuli.

Lettvin has done close examination of the frogs visual system in his paper “What the frog’s eye tells the frog’s brain” Geyers refers to this paper to summarise Frogs visual system: Frogs have four types of visual receptors in the retinas of their eyes. On type responds to large contrast differences, another to changes in contrast, the third to changes in light intensity, and the fourth responds to small, dark, circular objects which are moving toward the frog. This last receptor is called the “bug detector”, and when it is triggered the automatic response is for the frog’s tongue to shoot out and catch the triggering object (Geyer 1988).

The frog does not decide whether it is hungry or even whether the object is a bug, but just shoots out its tongue. All of the frog’s visual processing is “peripheral, in the retina of the eye. This peripheral sensory apparatus is a rudimentary stimulus/response mechanism, as opposed to our complex, central interpreting system (Geyer 1988). This discussion re-inforces that Frog’s visual system far more complicated than humans while humans brain is far more complicated than Frogs. Concept of focal attention or instinct to search for order/structure and this seems to be unique feature of human eye-brain complex.

Geyer claims that while perceiving an aesthetics experience one assumes, predicts and attempts to realize (invent or discover) a existing pattern, when the pattern is actually found the aesthetic inquiry and the experience ends. However, perception in general is a necessary function for human beings, and perception is a process of editing and ordering information from the senses. Thus seeking order is a biologically necessary operation, as essential to our survival as eating and reproducing.

Aesthetic experience, as seeking order just for the sake of seeking order, is a celebration of perception. The pleasure in this experience is primal, as it is in eating when hungry and copulating. It is there to encourage a basic need. No wonder evolution has favored perception in the aesthetic phenomenon (Geyer 1988). Neurological basis for aesthetic being a function perceivers processing Using interesting experimental settings Rolf Reber, Nobert Schwarz and Piotr Winkielman propose that aesthetic pleasure is a function of the perceiver’s processing dynamics.

They review variables known to influence aesthetic judgments, such as figural goodness, figure–ground contrast, stimulus repetition, symmetry, and prototypicality, and trace their effects to changes in processing fluency. The mail claim is against theories that trace aesthetic pleasure to objective stimulus features per se, they propose that beauty is grounded in the processing experiences of the perceiver, which are in part a function of stimulus properties (Processing Fluency and Aesthetic Pleasure: Is Beauty in the Perceiver’s Processing Experience? (Rolf Reber 2004)

Pattern recognition might be the key phenomenon to understand aesthetic phenomenon for what it is. Pattern recognition in Non-human Pattern recognition and object parsing experiments in human the experiments were conducted on humans by XU Carey Welch 1999; Needham & Baillergeon 1998 and Spelk in 1993. This experiment conducted on humans was taken as the base to comapre object parsing in adult Rheshus Monkey and human infants. Four experiments are investigating how semi-free-ranging rhesus monkeys form representation of and inferences about visible object presented under natural conditions. Experiments use methods in previous training is required by monkeys.
• Preferential looking experiments which are common in human infants were used to allows direct comparisons. Experiment displays testing infant’s sensitivity spatiotemporal temporal or featural information (Yuko Munakata 2001). Findings Sensitivity to hands: Humans infants take account of the human hands in analyzing the motion and objects. However monkeys show no sensitivity to the moving hands. – Because human infants are endowed with the capability to attend to the ways inanimate objects are manipulated by other humans.

Object boundaries: Adult monkey and human infant above 11 months of age use featural Information processing model to perceive object boundaries. Experiment suggests that monkeys categories food such that they are likely to have “food kind” (color and shape perception) representations (Yuko Munakata 2001). Successful use of featural information model by monkeys casts doubt on the thesis representation of objects is uniquely human capability. It further seems that even animals do top-down conceptual based processing.

Diagrams: logic of pattern recognition The are irregular presentation that artists have been using to create meaningful spatial representation. Now lets see what is the case with the regular patterns so called diagrams. This section looks at issue why do we sue diagrams. Proving theorem is geometry is efficient and easy using diagrams as they provide spatial representation to abstract problems. David Hilbert makes a claim that digram based Euclidean geometry makes hidden assumptions hence it is an effective device for geometrical problems.

However the question the whether diagrams are merely heuristic or can provide rigorous means of proving theorem is still a debatable topic. Though claim from (Allewein and Barwise 1996) has revived the argument in favour of diagram as rigorous means of problem solving (Pylyshyn 2003). The Venn diagram representation of sets, illustrates that certain properties of the visual system (the ease with which we locate an element in particular region) can be exploited to facilitate reasoning.

Such externalisation exploit the perceptual system to help us recognise patterns (Pylyshyn 2003). Gardener (1982) provides a fascinating discussion of diagrammatic inventions of Leonhard Euler, Sir William Hamilton, Allan Marquand, Johann Lambert, Charles Peirce Lewis Carrol (Charles Dodgson), and Gerrit Marie Mes. There is something obvious about the vision that provides functions that are not as readily available in other forms of reasoning. Vision provides primitive operation for a number of functions (shape recognition, detection of relational properties)

The usefullness if diagrams, graphs, charts, and other visual devices relies on the fact that people are good at visually detecting certain geometrical relations. Diagrams enable visual system to keep track of where the information is located in the real world rather than encoding it all in memory argued strongly by O’ Regan (1992). While examing diagrams we don’t look for general properties but also at what properties hold the resulting construction (Pylyshyn 2003) (445)

Involvement of visual system is more than goes beyond merely recognising that a certain pattern is present in a particular drawing (Pylyshyn 2003) (446). Spatial metaphors facilitate communication of complex idea and working through bastract problems as diagrams use external memory to represent spatial patterns . (Talmy 2000) (Pylyshyn 2003) (445) In a nutshell, drawing a diagram enables in principle to see the relationships that are entailed by what you recalled, however sparse the set of explicitly noticed relationships might be.

In prevision sections I have explained that top down processing in pattern recognition involved in representing meaning in visual arts and also responsible for the break down of patterns in illusion. Even in the abstract process like aesthetic experience key phenomenon is top down processing in pattern recognition. Finally in logical or regular use of visuals is also governed by top-down processing and the key phenomenon is pattern recognition. Right stated by Descartes in 17th Century “ …………” Instructional Implication: Visuals Literacy “Visually literacy is training for visual thinking”.

This concept has many interpretations and is influenced by various areas like visual language, perceptual and cultural coding, creativity, visual and verbal relationships, deconstructionism, social, theoretical foundations and research. This concept has significantly from 1960 onwards (Dwyer 1994). Visualisation as Rehearsal Rehearsal may be considered to be any activity which causes the learner to hold the information longer in the short term memory. Weinstin and Mayer 1986: Rehearsal strategies are desigined to repeat information while it is in short term memory (Dwyer 1994).

Murray and Mosberg 1982 indicated that longer and individual can be involved in rehearsal activities (taking notes, inspecting and interacting with visuals etc) in which he/she is actively processing information, the greater is the possibility that this information will be moved to the long term memory and thus resulting in schema development (Dwyer 1994). Information processing approach focuses on how the human memory system acquires, transforms, compacts, elaborates, encodes, retrieves, and uses information (Dwyer 1994).

Gregory in model to explain top- down processing role of side ways role and qualia while misses out on memory structures while Klatzky 1980 focuses on the process of patter recognition in context to memory structures but it misses out top-down and qualia. Hence I present an adapted model that best explains the process of pattern recognition. Adapted from Klatzky Model 1980 and Gregory model of Top-down and bottom up processing. Challenges in the use of visuals as instructional The objective of the instructional strategy should be to develop guidelines for effective use of different kinds of visualisations.

To meet educational objectives, guidelines would possess high degree of predictability for the design and visualisation, to ensure that majority of learners receive the intended message in effective manner. This goal is not easy to achieve as due to different kind of illustrations (line drawings, detailed, shaded line drawings, drawings of models, realistic photographs) are not equally effective in achieving different educational objectives for students with different background studying in different cultural/learning settings (Dwyer 1994). Hence there need for effective visual testing.

Visual testing Instructional environment purposely designed to facilitate student acquisition, storage and retrieval of designated information. Even though visualization is commonly used to facilitate student information acquisition, most of evaluation strategies currently used are of verbal pencil and paper type (Dwyer 1994). Dwyer and DeMel: “ probably the oldest learning is that any change in the retrieval (evaluation) environment from that which occurred in the original learning environment produces marked decrements in learner performance. Thus most important steps in the research focusing on cognitive information acquisition is the development of instruction unit which contains several different levels of learning (facts, concepts, rule/procedures, problem solving strategies) and appropriate type of tests must be designed to measure the problem solving at each level. Instructional Consistency/ Congruency Canelos presents a useful conceptual rationale for the development of instructional module for research purpose. The paradigm assumes a hierarchy of learning objectives.

Students will not achieve the rules/principle level if they do not posses pre-requisite conceptual base. However if the students possess the conceptual base and the instructional environment does not bring does not bring together relevant concepts in a manner which facilitates rule / principle level integration, learning will not occur. The process of working with objectives, interaction and testing provides instructional congruency while instructional consistency aims to verify that the prerequisite kinds of learning are present; it also requires that the objectives for each category be stated specifically.

This Unit development is critical as it alerts the researcher to the fact that the learner are going to be processing information at a different intellectual levels and that different type of instructional experiences need to developed to facilitate the different levels of learning. Visual literacy is becoming less complex as the basic notion of learning with the visuals is becomes more universally accepted. However the field is becoming complicated because of new theories, and new technologies but has a significant implication instruction (Dwyer 1994). Phases in learning Hierarchy and Instructional Consistency/ Congruency Matrix

Conclusion I have explained three points first intentionality in pattern recognition makes us unlike the dust particles in Brownian motion. Second- Illusion are good example to understand the leaky architecture of the visual system and brain complex. I have explained that illusion might be caused due to physical causes that bottom up processing dominating or they can be due to cognitive factors that is top-down processing dominates. History of illusion gives insight into the neural basis of visual system. Third- I have explained aesthetic experience, as is the most evolved feature of human beings.