A Perceptual-Cognition Map
How we sense, perceive, acquire knowledge and think is governed by cognition, so it is important to have some basic understanding of the process. The advent of functional magnetic resonance imaging (fMRI) and position-emission tomography (PCT) which can measure cerebral blood flow in the brain through sensing magnetic signals or low level radiation respectively to determine brain activity levels have greatly deepened our understanding of the processes of cognition (Posner, DiGirolamo & Fernandez-Duque 1997). Quite remarkably, the cognitive process has many similarities with computer information processing steps of acquisition, storage, retrieval, processing, data organization and artificial intelligence structures (Reed 2007).
Perceptual Cognition
Perception is such a complex brain activity that a very large part of the brain function is totally dedicated to this process. All external stimuli are detected by the five senses and environmental energy is transformed into neural electricity via complex biochemical conversions called transduction[i]. Neural electricity carrying information maintained in its original format from the senses travels, cell to cell to the sensory store by the process of neural transmission[ii]. The sensory store is not actually a single area within the brain. Different areas of the brain process sensory information as indicated in figure 1. showing an overview of the cognitive system. The sensory store can only keep unanalyzed sensory information for very brief periods for identification through pattern recognition. Information that cannot be identified through the pattern recognition process will be lost.
Many stimuli can enter the sensory store at one time but only one pattern at a time can enter the pattern recognition stage. This is controlled through perceptual limitation which prevents people from being overloaded with too much information at any one time (Broadbent 1958). The attention function determines the sequence and amount of information that will be identified at one time. This restricts the amount of information that can enter the memory. The filtering stage sorts and limits information entering the memory like a bottleneck (Broadbent 1957). This bottleneck occurs at the entrance to the pattern recognition stage, where only one piece of information can be processed at a time (Deutsch & Deutsch 1963, Norman 1968), thus preventing information overload. This is metaphorically shown as marbles being poured down a funnel as shown in Figure 2..
Pattern recognition is the stage where information is matched with known patterns. There are a number of different theories as to how the brain identifies patterns. Template theories explain pattern identification through matching information with stored shapes or templates. Feature theories explain the use of discovered features that distinguish one pattern from another and structural theories use the relationship between features to recognize patterns. A complete theory and understanding of the pattern recognition process does not exist as yet because identification of an object involves so many visual cues and spatial issues, and the knowledge needed to see any of these cues is so extensive. For example, we can read with ease but the process of understanding words may rely on a number of different and flexible word recognition strategies. There are multiple levels of identification at the feature, word and letter levels which interact to assist comprehension (McCelland & Rumelhart 1981). Our ease in reading presents many problems to theories of how we identify and comprehend words (Grainger & Whitney 2004).
Figure 1. An Overview of the Cognitive System.
Figure 2. Limited Capacity Entrance Channel into the Pattern Recognition Stage.
Figure 3. Demonstration of Colour-Word Conflict.
Perception tasks occur both at the conscious and unconscious level. Different perception tasks require different effort and compete for limited capacity. Some tasks are so well practiced that they become routine and processed automatically. However when one comes up against unusual objects, then a great conscious effort is required to process and recognize them. For example if you look at figure 3. and say the colour and not the word, you will most likely find that this is not so easy as two recognition processes (word and colour) come into conflict which requires conscious resolution.
Probably one of the closest explanations to how our brain processes information in the recognition process is the neural network model (Rumelhart, Hinton & McClelland 1986). This metaphoric concept hypothesizes a network of linked concepts (called nodes) are linked to other nodes, where they interact through excitatory or inhibitory electrical charges. Node activation above a threshold makes us aware of a letter in a word, etc. Neural networks accommodate learning through changing the weights of node activation through excitatory or inhibitory actions. This improves the efficiency of the network in making identifications through being able to process information in parallel, both top-down and bottom-up processing. A pictorial example of a neural network is shown in figure 4.
Figure 4. An Example of a Neural Network.
One of the advantages of a neural network is the ability to process information either top-down, where information in our memory helps us recognize information or bottom-up, where information from the sensory store is sent to the short term or working memory to enable quick identification of information. Information held within a neural network enables a person to look, in the case of writing, at either the word level, letter level and feature level, which implies where we can interpret incomplete words and sentences (McCelland & Rumelhart 1981, Grainer & Whitney 2004). Figure 5. shows this process pictorially.
Figure 5. The Word Recognition Process.
Another bottleneck occurs between pattern recognition information entering the short term working memory. This is not a perceptual problem but one of the selection of which sequence of information goes into memory. This is more a capacity limitation on how much mental work can be undertaken at any one time. Factors that influence the sequence of information entering the short term working memory include memory capacity, arousal, enduring dispositions, momentary interventions and conscious and unconscious evaluations (Kahneman 1973).
The patterning mechanism is a channel or bias that screens, distorts or otherwise patterns information in particular ways. This can also be thought of as knowledge structures which put information into patterns we already understand. Thus the content of the knowledge structure will influence perception. Hillerbrand (1989) postulates that this mechanism is another way the brain cuts down on information overload, so that information can be easily encoded into memory. This assists a person make sense of things out of confusion and uncertainty where thinking is focused on finding things that one is already familiar with. For example, when we learn to drive a car, we must concentrate on every decision and action we take. Once we are familiar with the skills of driving a car, we do this without taking any conscious actions. This is the advantage of patterning. This mechanism may also partly explain why people have different perspectives from the same stimuli and may also partly explain why some people see opportunity while others don’t (Baron & Ward 2004), although this process is far from understood.
The patterning mechanism could be the beginning of the brain’s self organizing system where incoming information is organized into patterns and sequences that can be processing according to already established meanings. According to de Bono (1993, P. 49) patterning is a fixed way of seeing things and inhibits creativity, as it is part of the fixed mental model we have.
Therefore perception is influenced by prior knowledge and other preconceptions, heuristics and biases we have (these will be discussed later during the chapter). Thus ideas are the result of logical hindsight, rather than foresight to gain insights into things and issues (Pang 1972). This is extremely useful for people carrying out their work like doctors making a diagnosis, mechanics inspecting an engine for faults, airline pilots, and farmers, etc, doing the routine parts of their jobs. It helps give them their specialist intuition. Thus returning to our previous funnel metaphor, there are really a number of funnels, each representing certain pre-existing mental models through which we perceive. This affects our perception, reasoning and decision making processes. Figure 6. shows a metaphorical diagram of the patterning process.
Figure 6. Metaphorical Diagram of the Patterning Process.
According to Uchasaran, Westhead & Wright (2004) the ability to manipulate or change patterns (which are like lenses or glasses we look through), gives the person the ability to look at perceived information in different ways[iii]. Patterns thus guide our approaches to reasoning, decision making and problem solving and are affected by bias, delusion, distortion, heuristics and socio-cultural influences that influence the structure of our schemata.
Mental Cognition
There are two memory functions, the working or short term memory and the long term memory. The working or short term memory is where text comprehension, reasoning and problem solving takes place. The working or short term memory has a very limited storage capacity and can only hold information for a very short length of time. The working or short term memory is the interface between stimuli and information from the environment and information from our long term memory.
Research has shown (Baddeley 1992, 2001, Baddeley & Hitch 1974) the working or short term memory is made up of a phonological part, a visual-spatial part, a memory and a central processing function. A different part of the brain handles the phonological information (Awh et. al. 1996), where information is identified and new words can be learned and stored in the long term memory (Saarilouma 1992). The working memory function plays a major role in how logical reasoning and decisions are reached (Gilhooly, et. al. 1993). A pictorial model of the working or short term memory is shown in figure 7.
Figure 7. A pictorial model of the working or short term memory.
Varying levels of controlled attention in individuals partly explains differences in peoples’ perception and reasoning. Controlled attention is important for maintaining task goals in working memory, scheduling actions, maintaining task information during distraction, and suppressing irrelevant information (Engle & Oransky 1999). Another major difference between people is how people group and structure information in collective chunks. A study by de Groot (1965) found that the difference between master and ordinary chess players was the difference in perception and memory, rather than differences in deciding planned moves. Master chess players would tend to group the pieces on the board into familiar patterns of past games to remember. However where pieces were placed randomly on the board, there was no difference between the master’s and ordinary player’s ability to recall the placement of the pieces on the board. Further studies showed the memory depends on being able to retrieve certain chunks of information from the long term memory when required (Chase & Simon 1973). This indicates that prior knowledge influences our perception and the way we code and retrieve information.
There is no known limit in long term memory capacity. The long term memory is where information is stored for the working or short term memory to retrieve or deposit information as required. Three basic processes occur within the long term memory. The first is acquisition of information. This is our ability to learn. Secondly, information must also be retained until it is needed by the short term or working memory, as required. Finally information must be able to be retrieved for use by the short term memory, through a particular retrieval strategy.
The long term memory contains three main types of memory, the episodic memory, the semantic memory and the procedural memory. The semantic memory stores temporary information about recollections of events and personal experiences. The semantic memory contains general knowledge that is not associated with any time or context. Procedural memory stores actions, skills and operations, rather than factual information like the first two. Factual information seems much easier to lose than procedural information (Warrington & Weiskrantz 1986).
Both our experience and theoretical knowledge influences our judgments. Our judgments and ideas develop through learning and are stored as various cognitive devices called heuristics, which are logic rules that assist with decision making. There are also a number of mechanisms that can influence the logic and reasoning process that enter into the working or short term memory and patterning bias processes from the long term memory. These will be discussed later during the chapter.
The ability to recall information depends upon the kinds of operations and the way information is organized and encoded in the long term memory (Tulving & Thomson 1973). Memory codes can differ in how they elaborate and store information in memory. Additional associations and elaborations are stored along with the basic information (Anderson & Reder 1979), so that information is easier to retrieve. Very often mood and emotions are stored with autobiographical events to assist recall (Eich, Macaulay & Ryan 1994). Information is often stored as visual images for better retention. Visual storage enables easy elaboration on perceived information. Visual memory is much better than the memory of words, thus staying in memory much longer, although susceptible to distortion through elaboration over time. Therefore memories will contain both information from the external environment and elaborated information from our memory, shifting our recollection of actual reality to the point where it becomes impossible to distinguish between real and imagined events.
The future perceptions of people are influenced by the way they categorize information in memory. The patterns of categorization are the means by how we identify objects in the external world. How relationships between chunks of information are developed will relate to how a person sees the environment. This helps reduce complexity, but the way things are related can also affect meaning. For example we tend to try to classify objects together for simplicity of understanding, rather than look at their unique characteristics. This reduces our need for constant learning.
The categorization of objects aids our perception and prompts quick responses in relation to them, i.e., fire, hot, keep away. How we organize memories greatly influences our views on things. For example, through the stereotyping of objects, people and events we create manageable views of the world. Categorization creates simplicity but when they are based on erroneous assumptions they add to the creation of distorted views of things (Canter & Genero 1986). Through stereotyping we tend to view people of the same social category as being similar. Once we categorize a person, his or her traits become exaggerated, which distorts actual reality. People tend to discard information that differentiates one person from another and focus upon our stereotyped knowledge to form our views (Reed 2007, P. 194). Other psychotic pathologies also tend to create distorted perception of actual reality and meaning. This will be extensively discussed later in the chapter.
People who develop an efficient organization system to encode and retrieve information will have good memories. Memories are usually organized through hierarchical and relational structures (Ericsson 1985) in what is called a semantic network, consisting of concepts and links that specify relationships between them. Within a semantic network, information is clustered in schemata. A schema is a cluster of knowledge that represents a general procedure, an object precept, an event or event sequence or a social situation (Thorndyke 1984). A schema is an organization of past experiences which have been encoded into abstract concepts to fit into a cognitive structure. There are a number of models which propose how a schema is constructed, as we are not completely sure how knowledge is actually organized. Structures continually develop and change as new information is blended with existing information.
Figure 8. A Metaphoric View of a Relational Memory Network.
This form of information organization can be represented as a relational network which emphasizes concepts linked to various bits of relevant information that create a holistic picture in memory. This relational structure shown in figure 8. bares some physical resemblance to the neural networks shown in Figure 9. previously. The relational concept allows for ease of information retrieval via multiple paths. This kind of relational network, although not yet proven to physically exist, is consistent with the way we think in many situations (Collins & Loftus 1975, Meyer & Schvaneveldt 1976, Ratcliff & McKoon 1988).
Figure 9. A pictorial script for running a 100 metres race.
Routine activities which make up a large amount of our knowledge are encoded into specific schema called scripts (Schank & Abelson 1977). A script is simply a sequence of knowledge about what happens during routine activities in a structure like a flowchart. Schemas and scripts help a person to make sense and meaning of the world around them. Incoming information is understood much easier when it is integrated with information a person already has stored in memory. Present information is immediately compared with prior information, ideas and judgments to look for similarities from where meaning can be inferred. Through this process we are able to construct a mental model based on both the new information and abstracts from our memory (Glenberg, Meyer & Linden 1987). Figure 3.16. shows a script for running a 100 metres race.
Mental models have both advantages and disadvantages. Through mental models, a person can make inferences, i.e., to make conclusions based on unconscious rules of logic or heuristics. This helps create very quick meaning out of a situation. This was very necessary in previous times when mankind was a hunter and came across dangerous situations where they had to make very quick fight or flight decisions. Inferences activate meaning and cut down on uncertainty.
Actual reality can have many different interpretations. For example, what appears to be a snake at the bank of a river could in reality be a stick or branch of a tree. Inferences cut down the risk of the situation through erring on potentially dangerous versions of reality. Therefore abstracted inferences in complex situations can distort actual realities. We see this process in how people reinterpret history making inferences about past people and events (Erickson & Mattson 1981) and how witnesses in court can give unreliable descriptions based on abstract inferences of their memory (Loftus 1975, Harris 1978).
Originally published in Ovi Magazine 22nd January 2013
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Notes and References
Anderson, J. R. and Reder, L. M. (1979). An elborative processing explanation of depth of processing, In: Cermak, L. S. and Graik (Editors), Levels of processing in human memory, Hillsdale, NJ, Erlaum.
Awe, E, Jonides, J., Smith, E. E., Schumacher, E. H., Koeppe, R. A. and Katz, S. (1996). Dissociation of storage and rehearsal in verbal working memory: Evidence from PET, Psychological Science, Vol. 7, pp. 25-31.
Baddeley, A. D. (1992). Is working memory working? The fifteenth Barlett Lecture, Quarterly Journal of Experimental Psychology, Vol. 44A, pp. 1-31.
Baddeley, A. D. (2001). Is working memory still working?, American Psychologist, Vol. 56, pp. 851-864.
Baddeley, A. D. and Hitch, G. (1974). Working Memory, In: Bower, G. H. (Editor), The Psychology of learning and motivation, Orlando, FL, Academic Press, (Vol.8), pp. 17-90.
Baron, R. A. and Ward, T. B. (2004). Expanding entrepreneurial cognition’s toolbox: potential contributions from the field of cognitive science, Entrepreneurship, Theory and Practice, Vol. 28, No. 6, pp. 553-575.
Broadbent, D. E. (1957). A Mechanical Model for human Attention and Immediate Memory, Psychological Review, Vol. 64, pp. 205-215.
Broadbent, D. E. (1958). Perception and Communication, London, Pergamon Press.
Cantor, N. and Genero, N. (1986). Psychiatric diagnosis and natural categorization: A close analogy, In: Milton, T. and Klerman, G. (Eds.), Contemporary directions in psychotherapy: Toward DSM IV, New York, Guilford.
Chase, W. G. and Simon, H. A. (1973). Perception in chess, Cognitive Psychology, Vol. 4, pp. 55-81.
Collins, A. M. and Loftus, E. F. (1975). A spreading activation theory of semantic processing, Psychological Review, Vol. 82, pp. 407-428.
de Bono, E. (1993). Sur/petition, Bodmin, Cornwall, Hartmolls Ltd.
De Groot, A. D. (1965). Thought and choice in chess, The Hague, Mouton.
Deutsch, J. A. and Deutsch, D. (1963). Attention: Some theoretical considerations, Psychological Review, Vol. 70, pp. 80-90.
Eich, E., Macauley, D. and Ryan, L. (1994). Mood dependent memory for events of the personal past, Journal of Experimental Psychology, General, Vol. 123, pp. 201-215.
Engle, R. W. and Oransky, N. (1999). The evolution from short-term memory: Multistore to dynamic models of temporary storage, In: Sternberg, R. (Editor), The nature of Cognition, Cambridge, MA, MIT Press.
Erickson, T. and Mattson, M. (1981). From words to meaning: A semantic illusion, Journal of Verbal learning and Verbal Behavior, Vol. 20, pp. 540-552.
Gilhooly, R. H., Logie, R. H., Wetherick, N. E. and Wynn, V. (1993). Working memory and strategies in syllogistic-reasoning tasks, Memory & Cognition, Vol. 21, pp. 115-124.
Glenberg, A. M., Meyer, M. and Linden, K. (1987). Mental models contribute to foregrounding during text comprehension, Journal of Memory and Language, Vol. 26, pp. 69-83.
Grainer, J. and Whitney, C. (2004). Does the Human Mind Raed Wrods as a Whole?, Trends in Cognitive Science, Vol. 8, pp. 58-59
Harris, R. J. (1978). The effect of jury size and judge’s instructions on memory for pragmatic implications from courtroom testimony, Bulletin of the Psychonomic Society, Vol. 11, pp. 129-132.
Hillerbrand, E. (1989). Cognitive differences between experts and novices: implications for group supervision, Journal of Counseling and Development, Vol. 67, No. 5, pp. 293-296.
Kahneman, D. (1973). Attention and Effort, Englewood Cliffs, NJ, Prentice-Hall.
Loftus, E. E. (1975). Leading questions and the eyewitness report, Cognitive Psychology, Vol. 7, pp. 560-572.
Meyer, D. E. and Schvaneveldt, R. W. (1976). Meaning, Memory, Structure, and Mental Processes, Science, Vol. 192, pp. 27-33.
McClelland, J. L. and Rumelhart, D. E. (1981). An interactive-activation model of context effects in letter perception, Part 1. An Account of Basic Findings, Psychological Review, Vol. 88, pp. 375-407.
Norman, D. A., (1968). Toward a theory of memory and attention, Psychological Review, Vol. 75, pp. 522-536.
Pang, J. (1972). Towards a certain “contextualism” II. (Foresight vs. Hindsight) vs. Insight, Philosophia Mathematics, s1-9, No, 2, pp. 158-167.
Posner, M. I., DiGirolamo, G. J. and Fernandez-Duque, D., (1997). Brain Mechanisms of Cognitive Skills, Consciousness and Cognition, Vol. 6, pp. 267-290.
Ratcliff, R. and McKoon, G. (1988). A retrieval theory of priming in memory, Psychological Review, Vol. 95, pp. 385-408.
Rumelhart, D. E., Hinton, G. E. and McCelland, J. L. (1986). A general framework for parallel distributed processing, In: Rumelhart, D. E., McCelland, J. L. and the PDP
Reed, S. K. (2007). Cognition: Theory and Applications 7th Edition, Belmont, CA, Thomson-Wadsworth.
Saarilouma, P. (1992). Visuospatial and articulatory interference in chess players’ information intake, Applied Cognitive Psychology, Vol. 6, pp. 77-89.
Schank, R. and Abelson, R. (1977). Scripts, goals, and understanding, Hillsdale, NJ, Erlbaum.
Thorndyke, P. W. (1984). Applications of schema theory in cognitive research, In: Anderson, J. R. and Kosslyn, S. M. (Eds.), Tutorials in Learning and Memory, San Francisco, Freeman.
Tulving, E. and Thomson, D. M. (1973). Encoding specificity and retrieval processes in episodic memory, Psychological Review, Vol. 80, pp. 352-373.
Ucbasaran, D., Westhead, P. and Wright, M. (2004). Human capital based determinants of opportunity identification, In: Bygrave, W., Brush, D et. al (Eds.), Frontiers of Entrepreneurship Research, Wellesley, MA, Babson College, pp. 430-444.
Warrington, E. K. and Weiskrantz, L. (1970). Amnesic syndrome: Consolidation or retrieval?, Nature, Vol. 228, pp. 628-630.
[i] Transduction occurs in different ways depending upon the receptor. The eye contains photoreceptors which contain photopigments. When exposed to light these photopigments breakdown and produce electricity that is transported through neurons to the retina. In the ear small hair-like outgrowths called cilia make up mechanoreceptors where vibrations caused by sound waves disrupt the cilia causing an electrical charge in the receptor. Olfactory receptors at the base of the nasal cavity called the olfactory epithelium. These receptors are located on cilia and when they come in contact with an odour molecule they transmit neural electricity. There are approximately 1000 different types of receptor in the nose to differentiate various odour molecules (Ressler, Sullivan & Buck 1994). There are also a number of free nerve endings that can detect sensations like coolness, tingling and warmth, etc. The tongue contains about 10,000 chemoreceptors on our taste buds or papillae. Each bud contains around 150 receptor cells. Molecules of the food or other substance carrying a taste connect with the receptors via saliva and bind. Changes in membrane permeability will cause changes in electricity potentials. Taste is detected through different chemical molecules causing different charge micro-voltages. Finally haptic receptors are varied and range from free nerve endings to specialized receptors that are at various locations on and in the body that work on a number of different principals.
[ii] Neural transmission from cell to cell occurs through impulses that travel from the dendrite of a cell (a branched tree like structure projecting from the neuron cell) to terminal buttons at the end of axons (the thin branches of neural cells) of other cells. The terminal buttons connect to the dendrites of other cells at the synapse (junction between the terminal button of one neuron and the dendrite of another neuron). When an electrical impulse reaches the synapse, this triggers the release of neurotransmitters (electrically charged enzymes and proteins) that pass along an electrical charge to the next neuron.
[iii] The metaphor of seeing things through tinted or coloured glasses has been used for hundreds of years to describe various delusions or biases people may have. L. Frank Baum’s character Dorothy in the Wonderful Wizard of Oz asked the guardian of the gates why everyone has to wear green glasses in the Emerald City. The guardian replied so everything in the Emerald City would look green, so that people would think it really is an Emerald City (Baum 1999, pp. 130-131). Today for example, green is associated with envy, i.e., “green with envy”, blue is associated with depression, i.e., “the blues”, and rose or red is associated with optimistic delusion, i.e., “a rosier world”. Popular media has adapted this metaphor and used many ad hoc terms like ‘green glasses’, Dole-coloured glasses’ and ‘private sector glasses’, etc (Doyle 2001). Edward de Bono (1985) uses the colour metaphor to change patterns of thinking through his “Six Thinking hats”.