Theories of Attention

Attention research attempts to explain how people notice and then make sense of the constant flow of auditory and visual information in the environment.  The answer rests in the senses and brain and how people allocate their scarce attentional resources and limited working memories. 

History of Attention

Attention is one of the oldest problems in psychology.  Models of attention go back to the early Greeks where Aristotle viewed attention as a narrowing of the senses. In the 18^th century, philosophers Christian Wolff and Dugald Stewart studied the ability of a subject to track one sensory object while ignoring others (1982 cited in Hatfield, 1998). Experimental psychologist Wilhelm Wundt examined the direction and content of his thoughts through introspection.  Sigmund Freud discriminated between attended or conscious thought and mental processes inaccessible merely by directing attention.  Definitions, however, remained more philosophical than operational. William James wrote in 1890:

Everyone knows what attention is. It is the taking possession by the mind in clear and vivid form, of one out of what seems several simultaneously possible objects or trains of thought...It implies withdrawal from some things in order to deal effectively with others (James, 1950, p. 403).

During the first half of the 20^th century, behaviorism supplanted James’ pragmatism and became the dominant psychological paradigm in the U.S.  Behaviorists felt attention was too mentalistic and attention as a topic of inquiry languished (Leahey & Harris, 1997).

By 1949, however, advances in biology and physiology reignited interest in cognitive processes by shedding light on some of the physiological bases of cognition.  Evidence that the integrity of the brainstem reticular formation was essential in maintaining an alert state lent legitimacy to attention as an area of study.  Continued research has led to increased understanding of the neurological basis of attention and has allowed scientists to create functional mapping of brain areas activated by attention processes and isolate relevant neurotransmitters such as dopamine and norepinephrine (Posner, 1997).

By the end of World War II, information-processing and the fledgling field of computer science gained attention and popularity, in large part due to the success of Alan Turing’s computational machine in breaking the German Enigma code (Mazlish, 1995; McCarthy, 2004).  This led to a resurgence of interest in cognitive psychology with attention research falling into two broad areas: 1) attention as a selective focusing mechanism or 2) as a processing resource (Hatfield, 1998).

Whether information systems defined or described cognitive functioning, researchers embraced the analogy.  Social constructionists Fernandex-Duque and Johnson (1999) argue that by adopting the “man as machine” metaphor, researchers implicitly defined the parameters of their research which dictated the approach as well as the phenomenon they observed.  In a permutation of McLuhan’s vision of technology redefining society, constructivist suggest that “…ultimately, definitions of attention become theories of attention" (Fernandex-Duque & Johnson, 1999, p. 106; Jones & Yee, 1993, p. 70).  Nevertheless, a group of mostly British researchers were the first to use it to describe their hypotheses about an attention model that mediated information between sensory systems and a limited capacity processing system (Anderson, 1995; Anderson et al., 2002).

Selective Attention Theories

Broadbent is credited with the first model of attention, often described as a “bottleneck theory” because information had to be filtered to restrict the flow to a cognitively manageable amount (Anderson et al., 2002).  In 1958, Broadbent published a seminal paper on selective attention that not only set the path for future research but, perhaps more importantly, established a cognitive approach to psychology.  This  marked a clear theoretical break from the behaviorist’s “black box” theory of the mind that regarded internal processing as both speculative and unnecessary (Bargh, 1996).

Broadbent employed dichotic listening experiments (where subjects heard different auditory tracks in each ear) to test the hypothesis that people have an internal, intentional selection or filtering method that directs attention to focus on certain stimuli over others. His filter theory was a serial processing “early-selection” model where the filtering occurred in the early stages of information processing based on physical properties, such as pitch or volume.  In the bottleneck model, attention is directed to the information that passes the filter or to salient information that leads to a shift in attention limited by single channel processing (Anderson et al., 2002).

In the 1960s, Treisman adapted Broadbent’s model to what became known as attenuation theory. Her research challenged the notion of a solely early-selection model. Also using the dichotic listening technique, Treisman’s subjects repeated out loud (shadowed) a narrative heard in one ear with instructions to disregard a second narrative in the other ear. Treisman observed that subjects’ attention sometimes switched ears unconsciously.  Because of this, Treisman argued that we do not completely filter out all unattended information; we attenuate some information based on both physical properties and semantic selection criteria.

Deutsch and Deutsch (1963, in Anderson, 1995) continued to modify the filter model. Based on their research, they developed a late-selection theory. This work reaffirmed the essential finding that information can be processed outside conscious attention to the extent that it is related to already active or accessible mental representations.

Norman's (1968, in Leahey & Harris, 1997) developed a “Pertinence” model that, rather than stimulus driven, involved top down processing.  In this model, a combination of sensory activation combined with top-down mediation (processing vis à vis an existing personal knowledge base to establish relevance) received the focus of conscious attention. This was supported by Cherry’s previous work (1953, in Bargh, 1996) known as the “cocktail party effect,” which showed that self-relevant information is processed even when conscious attention is focused elsewhere, such as when you hear your own name mentioned from across the room.

Selective attention experiments suggested that alongside attended information, input is filtered and kept unavailable to conscious processing for later activation.  It is hypothesized that this information is stored briefly in short-term memory for retrieval if relevance is triggered (Anderson, 1995).  Posner (1997) reports that physiological studies in the late seventies isolated activity in a thalamic gating mechanism controlled from prefrontal sites during attention processing. Research since then has pointed to the involvement of higher cortical levels, still possibly in conjunction with thalamic mechanisms (Puce et al., 1999).

Divided Attention Theories

The study of divided attention has focused primarily on dual-task studies where subjects attempt to perform two separate tasks under different types of condition. The research suggests that there are three main factors that impact dual-task performance: 1) how similar the tasks are to one another; 2) how much the subject has practiced the task; and 3) how difficult the tasks are (Anderson, 1995).

Divided attention tasks raise the question of how much capacity the system has, how capacity is divided among tasks, and how the use of this capacity is modified by learning.  In the previous theories, capacity was assumed to be a fixed amount.  Researchers began to address the question of cognitive processing as not just a function of the system’s capacity, but also of the drain on resources (Leahey & Harris, 1997).  The divided attention research has made an indispensable contribution to learning theory and pedagogics.

Automaticity

How familiar or practiced a person is with a task influences the attention it commands. Researchers such as Shiffrin and Schneider (1977) highlighted the difference between automatic and deliberate processes (Leahey & Harris, 1997). In their view, automatic processes, like driving a car, don’t demand the allocation of attention that a deliberate process, such as carrying on a conversation, demands. The focus on automatic and controlled processes argues both for the existence of dual-processing and for a relative demand placed on processing resources.  The more a process has been practiced, the less attention it requires.  The question has arisen as to whether a highly practiced process requires conscious attention at all (Anderson, 1995). Anderson, Matessa, and Lebiere (1997) make a similar distinction on attention allocation effects between declarative knowledge—something that can be communicated verbally—and procedural knowledge—something you know how to do like riding a bike.  Kahneman (1973) developed a capacity model that assumes a limit to the ability to do mental work, but the allocation of capacity is self-directed.  Kahneman argued that many factors were implicated in the ability to divide attention including the amount of effort a task required which he detailed in a “cost-analysis” model of attention relative to effort.

Researchers continued to test the conceptualizations of the underlying mechanisms of attention.  Some studies found that words could be visually processed and activate a semantic association without a person’s awareness. In other work, evidence suggested that the selection of words for meaning appeared to suppress the availability of other words (Posner, 1997).  Another area of inquiry focused on the orienting reflex that redirects and orients attention unconsciously toward an unexpected stimulus (Ashcraft, 2002).  Unpredictability was identified as another important variable in determining the allocation of processing capabilities (Anderson, 1995). Unpredictability in stimuli has been shown to capture attention, but the allocation of attention shifts away as gradual habituation occurs (Leahey & Harris, 1997).

These types of research findings shifted the view of attention models from an early information bottleneck system to one that prioritized several aspects of cognitive processing: consciousness, motor activities, and memory. Concurrent advances in biology suggested that higher level processing mechanisms of attention activate frontal areas of the brain, which contributes to coordination of cognitive activities.

In more recent years, the focus of studies of attention has moved away from the auditory modality toward the visual modality, with the development of visual search models.

Visual Attention

Unlike auditory information, visual information is limited by the field of vision we choose. The physical attributes of the eye modifies the field of vision by changing the field of focus. When light enters the eye, it is converted into neural energy by a photochemical process. Of the two kinds of photoreceptors in the eye, cones and rods, the cones are responsible for color vision and have the highest resolution and acuity. Rods require less light to trigger and are the conduits of black and white vision. Cones are concentrated in a small area of the retina called the fovea. Visual attention is directed by the position of the eye, which centers input on the fovea to provide the maximum amount of detail. The peripheral vision detects global information, such as movement (Carlson, 1998a).

By looking one direction or another, we are choosing to filter information and employing our maximum visual processing resources. Narrowing the field of focus gives the most possible information from that part of the visual field. However, to get information from another part of the field, the focus must shift and this takes time. Research by LaBerge (1983, in Anderson, 1995) showed that attention is most concentrated in the center of fovea and diminishes toward the edges, so processing complex visual information requires that the focal point must move around in the visual field. The speed with which we process information is facilitated by both physical and content cues (Duncan & Humphreys, 1992).

Pattern Recognition and Attention

Pattern recognition involves translating elements in the environment into examples of concepts already in memory as an aid to processing visual cues. This is how we attach meaning to the information we receive. The processes in pattern recognition are applicable across the senses (Anderson, 1995).

Early visual processing is based on elementary visual features. Lower levels of visual processing include binary response (on-off) cells which create edge and bar detectors in the cortex (Posner, 1997). The information is received in the retina as two-dimensional. There are a number of visual cues that create a representation of three-dimensional space. These include:

1. Texture gradients: elements tend to appear closer together as distance increases
2. Stereopsis: the eyes perceive from slightly different angles and therefore receive slightly different views of the environment; and
3. Motion parallax: when you move, the objects closer to you appear to move faster than the ones farther away (Anderson, 1995).

Object Centered Perception.

Our brains automatically organize objects into units according to a set of principles discovered by gestalt psychologists (Wertheimer, 1938). As illustrated in Figure 2, these principles of organization provide a perceptual shorthand for quickly processing and interpreting basic shapes, allowing a pattern to emerge as a whole.  The Gestalt principles form a basic building block in understanding how context influences perception.(Leahey & Harris, 1997).

Some of the gestalt principles include: (a) figure and ground: elements are distinguished based on contrast; (b) similarity: similar elements are seen as groups; (c) proximity: elements close together are seen as a group; (d) closure: elements are perceptually closed to be seen as complete figures; (e) continuity: continuation of elements to form patterns; (f) symmetry: objects are perceived as symmetrical shapes formed around their center; and (g) area: the larger of two overlapping areas is seen as ground; the small area as figure.

Feature Integration

One of the most influential psychological models integrating perception into visual attention is the feature integration theory developed by Treisman and Gelade in 1980. According to this model, during the first step of visual processing several primary features are coded with separate feature maps.  These are later integrated in a saliency map that can be accessed in order to direct attention to the most relevant areas (Carlson, 1998a).

Treisman distinguishes two kinds of visual search tasks, feature search and conjunction search. Feature search is being performed quickly and pre-attentively for targets defined by primitive features, such as color, orientation, and intensity, which appear to be processed in parallel. Conjunction search is an additive, serial search for targets defined by a conjunction of primitive features and takes longer as the number of distracters increases.  There is evidence that this type of search involves visual orienting and requires conscious attention (Posner, 1997; Treisman, 1998).

Neisser and Becklen (1975, in Anderson, 1995) performed the visual equivalent of the auditory shadowing tasks and found that subjects can focus simultaneously both narrowly and broadly when scanning for a meaningful events by using both physical and content cues. Neisser’s work was extended by Mack and Rock (1999) to examine whether subjects missed seeing things while during periods of directed focus.  This work, where significant events went unnoticed because subject’s attention was attuned elsewhere, is referred to as inattentional blindness and has extensive ramifications in real-world situations, from skills like piloting to delivering instructional communications.

Networks

Vision has provided a central structure for bridging the gap between human information-processing approaches and neuroscientific approaches to selectivity in attention Posner (1997).

When neural network models initially appeared in the 1940s, there was little public interest or funding.  In the late 1970s, the movement was rejuvenated by interdisciplinary cooperation from diverse fields made possible by improved communications technologies and media.  The mid 1980s saw a new theoretical model, connectionism, based on using simplified models of the brain known as neural networks.  Neural networks are made up of large numbers of units that send information based on the strength, or weight, of connections between the units.  This approach equates attention processes to the effects of the synapses that link one neuron to another throughout the brain (Carlson, 1998a).

The combined cognitive neuroscience of attention is based on these fundamental premises:  1) the attentional system of the brain has been shown to be partially separate from other information processing systems; 2) the attention function happens in a network of anatomical areas, not in a single area or as a collective function; and 3) brain areas involved in attention have different functions and specific functions are assigned to different areas(Kandel & Wurtz, 2000).

An understanding of the underlying neural structure has provided a better understanding of covert and overt orienting to visual locations.  Psychologists previously defined visual orienting in terms of eye movements that place the stimulus on the fovea.  Research based on the neural network model has shown that it is possible to change the attentional priority to the new stimulus covertly without any chance in eye or head position.  The covert shift of attention appears to function as a way of guiding the eye to appropriate areas of the visual field (Carlson, 1998a).

The introduction of the neural network metaphor also addressed some of the dissatisfaction with the linear programming model that had been raised by various psychologists.  Neisser was one who argued against the use of the linear programming metaphor for cognition contending that the focus on laboratory work, rather than real-life observations, raised questions about their ecological validity (Cohen, 1995).

Part II. Color

Color is the perception of light.  It affects us psychologically and physically, attracting our attention, influencing our moods, perceptions, and performance.  Colors carry meaning and provide a language of communication through which we express identity, emotion, and information. The study of color—what it is, how we see it, how it affects us--crosses the disciplines of physics, physiology, and psychology.

The human eye can detect differences in light intensity and wavelengths and this information is transformed into chemical messages for the brain.  Color vision is the product of the physical evolution of the eye.  Primate research has suggested the development of color vision is a survival mechanism; enhanced red vision allows better ability to distinguish between berries and foliage when gathering food (Osorio et al., 2004).  Some scientists believe that the development of color vision was helpful in avoiding predators through color camouflage (Carlson, 1998a).

The Physics of Color

Color is the way our eyes perceive light, not an intrinsic property of light itself.  Light is a constant flow of electromagnetic waves that vary in length produced by a vibrating electrical charge.

Each electromagnetic wave has a distinct frequency, wavelength, and energy and make up a continuous range of frequencies known as the electromagnetic spectrum.  Visible light waves are approximately 380 to 760 nanometers, a small area relative to the entire spectrum, as illustrated in Figure 4 (Kaiser, 2005).  The range of wavelengths we call visible light are not qualitatively different than the rest of the spectrum; this is just the range that we can see.

Isaac Newton is famous for investigating the refractive properties of light and discovering  that light could be separated into a rainbow of colors using a prism. Newton identified seven pure colors which he called the spectrum; his choice of number influenced by Descartes’ seven note music system and his interest in alchemy (Gage, 1993).

Color is a subjective experience dictated by the spectral composition of the light reaching the eye.  Our perception of the color of light is determined by three dimensions: hue, saturation and brightness.  The hue is the variation among the distance between the peaks of the waves, or wavelengths.  The brightness is due to the intensity of the electromagnetic radiation.  The saturation is the purity of the light. A color is fully saturated and pure if it is made up of light of all one wavelength.  Each color we see is the result of a different wavelength. As shown in Figure 4, violet has the shortest wavelength and red has the longest. If the radiation contains all wavelengths, we perceive no hues, it appears white.  The human eye can perceive approximately 2 million colors, however, most colors we perceive are not pure, but are mixtures of several wavelengths (Carlson, 1998a).

The color of an object is produced by the way in which the surface of the object absorbs and reflects various wavelengths of light. Smooth services reflect and rough surfaces scatter and diffuse.  Objects that appear blue are actually absorbing the wavelengths of all visible light except those corresponding to blue light.

The context of an object plays a significant role in our perception of color because the spectral composition of the background influences the eye’s perception of an object’s color.  An illustration of this phenomenon can be found in the color studies of artist Josef Albers, where the center orange square appears to be much brighter against the black square (Figure 5) than against the medium orange square (Figure 6) in spite of the fact that they are the same color.

Figure 1: Color Studies (Albers, 1971)

Figure 2: Color Studies (Albers, 1971)

At the same time, our visual perception can accommodate changes in lighting, so we are not fooled into thinking the color of an object has changed when it is in the shade.  There are times, however, when object appears to be the exact same color in one lighting condition, but not under others.  This phenomenon is called metamerism and is a common concern among artists and designers trying to maintain color equivalencies across technologies.

The Physiology of Color Vision

As discussed on page 5 (Visual Attention), when the light enters the eye, it passes through the lens and falls on the cones and rods in the retina.  Color vision depends on special pigments in the eye that absorb electromagnetic radiation stored in the rods and cones (Carlson, 1998a).  The electromagnet energy is converted into an impulse within a nerve cell to communicate with the brain.  Normal human visual system uses a three cone systems to represent the spectral properties of an object. With less than three signal paths, it would not be possible to capture different mixtures of multiple wavelengths or the information that creates depth of field (Lennie, 2000).

Theories of Color Vision

Trichromatic Theory

In 1800, Thomas Young postulated that there must be three types of receptors in the retina of the eye, each sensitive to a different hue because the eye could reproduce all colors by using combinations of three primary colors: red, green, and blue (Kaiser, 2005). This theory was later refined by Hermann von Helmholtz and is referred to as the Young-Helmholtz theory. The existence of three classes of cones with spectrally selective photopigments has since been proved to be correct (Carlson, 1998a; Sharpe et al., 1999).   This is the same logic that drives the physics of an RGB television screen.

Opponent Process Theory

The physiologist Ewald Hering opposed Helmholtz’ view of a three sensory point system for color reception.  Hering felt that Helmholtz’ system was not consistent with human experience.  He postulated that the perception of colors is mediated by an opponent process, where detecting one color means inhibiting another.  Hering envisioned four color receptors functioning in pairs with their opposites: red/green and yellow/blue alongside a receptor for light/dark.  In this model, one sensation captured the red-green variation; it would be excited by red light and inhibited by green light, and so on (Kastner & Ungerleider, 2000).

Red light stimulates cone receptor for red, causing excitation of red/green cell, producing perception of red. b) Green light stimulates cone receptor for green, causing inhibition of red/green cell producing green. c) Yellow light stimulates receptors for red and green equally, but not blue receptor.  Red/green stimulation causes yellow/blue stimulation producing perception of yellow.  d) Blue light stimulates receptor for blue, causing inhibition of yellow/blue cell, producing perception of blue.

Hering’s theory also accounted for the afterimage effect that causes the an image to remain after stimulus is removed.  Be Hering’s account, afterimages occur when the photoreceptors are over stimulated and lose sensitivity, thus the surrounding cones send out a strong signal, which appears as the opposite, or complimentary, color of the original image (Carlson, 1998b).

To see an afterimage of the picture below, stare at it for thirty seconds, then immediately look at a blank wall or piece of white paper to see the afterimage. In the afterimage, the colors of the United States flag will be corrected.

For some time, Hering’s opponent theory was seen in opposition to Helmholtz’ trichromatic approach, but eventually scientists found physiological evidence that supported both systems.  At the level of the retinal cell, the three-color code is translated into an opponent color system (Cole & Dain, 2004).

Color Constancy.

As discussed above, the visual system accommodates changes in light, from bright to ambient, in maintaining perception of color.  The compensation is thought to be made by comparing the color composition of each point in the visual field with the average color of the entire scene and then adjusting the perception to be consistent (Lennie, 2000).

Color Perception Deficits.

Much of what scientists have learned about color vision comes from studying animals and people with injury-related or genetic vision deficits.  Defects in color vision appear to result from anomalies in one or more of the three types of cones.  Red/green color deficiency, or color blindness, is the most common.  Color blindness is normally diagnosed through clinical testing.

An individual with normal color vision will see a “5” revealed in the dot pattern. An individual with Red/Green (the most common) color blindness will see a “2” revealed in the dots.

Color Perceptual Effects.

Color unites sensation and the mechanics of the nervous system with the psyche.  Emotion, memory, learning, imagination, dream imagery, and motivation are all psychological areas impacted by color.  Even the basic questions of perception and illusion are fundamentally psychological ones before they are physical or aesthetic ones.

Newton invented the color wheel, which was the first modern explanation of color mixing.  Splitting sunlight into red, orange, yellow, green, cyan, blue and indigo, he joined the end of the spectrum to show the natural progression of colors.  Newton’s color mixing was based on an additive color system that involves mixing involves multiple sources of light with different wavelengths of color in each source. Combining all wavelengths will result in white, as illustrated in Figure 11.  The mixing of paints and other pigments, more familiar to most people, is a subtractive process that involves a single source of light and multiple pigments each with different absorption qualities. Mixing all paints produces black, as illustrated in

In describing his findings, however, Newton drew on the metaphor of painter’s primary colors, which was introduced and adopted in England in the early 1660s.  (Particularly influential was Robert Boyle’s Experiments and Considerations Touching Colours which discussed the mixing of colors by painters, dyers and others and established the newly identified primary set (Gage, 1993)).

Artists were fascinated by Newton’s demonstration that light was responsible for color.  According to Gage (1993), however, it was not until the middle of the 19^th century that artists consistently understood that color mixing with light is different from the subtractive system of mixing colors in substances.  The notion that color from light was illusory stubbornly persisted, in spite of the scientific proof to the contrary.

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