Attention

Attention is a cognitive process that allows us to select some environmental stimuli and ignore others. From an evolutionary perspective, it is an extremely useful mechanism for human survival because it allows us to organize the information coming from the constantly changing external environment and to regulate mental processes accordingly.

Attention refers to the process by which organisms select a subset of available information to focus on for enhanced processing (often in terms of signal-to-noise ratio) and integration. Attention is usually considered to have at least three aspects: orienting, filtering, and searching, and may be focused on a single source of information or divided among multiple sources. Each of these aspects has specific characteristics that are briefly discussed below. Attention and consciousness are closely related, although the two concepts can be distinguished both conceptually and empirically.

In general, in psychology, attention can be defined as the set of selection processes that the brain undertakes against the stimuli that arrive from the outside world through the sense organs. An often used metaphor is that of a filter that allows only relevant stimuli to pass.

In the early days of psychological science, William James observed that human beings cannot be aware of everything in the face of a very large amount of data and sensory information. In fact, the human cognitive system is a limited system, that is, it has a limited amount of resources for information processing (Broadbent, 1958). In this sense, attention can be traced back to the set of mechanisms and processes that allow us to focus our mental resources on some stimuli or information at the expense of others, thus determining what we are aware of at any given time.

The psychology of attention aims to study attentional processes using specific experimental paradigms, techniques, and tools. In addition to neuroimaging studies that aim to identify brain activity related to attentional processes, there are also traditional techniques that are still used in the literature. For example, it is possible to study the behavior of subjects who are asked to perform certain attentional tasks in the laboratory by measuring their reaction time (TR). Reaction time is the time that elapses between the presentation of a stimulus and the production of a response. The longer the time between stimulus and response, the more processing is required. Some experimental paradigms instead aim to investigate the relationship between attention, the perception of objects or events, and consciousness.

When talking about attention and effective performance, it is important to refer to the theory of arousal, understood as a global state of activation of the individual that can vary from sleep to widespread arousal. Attention is a function that correlates with the level of global activation. The relationship between the level of activation, alertness, and efficiency in task performance is represented by an inverted U-shaped curve. At low levels of activation, the individual is easily distracted (with negative effects on task efficiency), whereas at excessive levels of activation, anxiety negatively affects performance (Yerkes and Dodson theory). According to Yerkes and Dodson’s theory, both too low and too high levels of activation would also increase distractibility and decrease performance.

Orientation

The simplest way to select among multiple stimulus inputs is to orient our sensory receptors toward one set of stimuli and away from another. Seeing and hearing are not usually passive; rather, we actively look or listen to see and hear.

Orienting Reflex

A prototype for orienting is the response of a dog or cat to a sudden sound. The animal quickly adjusts its sensory organs by pricking its ears and turning its eyes, head, and/or body to best receive information about the event. Responses such as eye blinking in the direction of a sound or peripheral movement, as well as associated postural adjustments, skin conductance changes, pupil dilation, heart rate decrease, pause in breathing, and constriction of peripheral blood vessels, occur automatically and are collectively referred to as the orienting reflex.

The most effective orienting stimuli are loud sounds, suddenly appearing bright lights, changes in contours, or movements in the peripheral visual field that are not regular, predictable occurrences. It is as if we have an internal “model” of the immediate stimulus world around us.

When we notice a deviation of the stimulus input from this model, we reflexively orient to that stimulus in order to update the model as quickly as possible (Sokolov, 1975). If the same stimulus occurs repeatedly, it becomes an expected part of our model of the world, and our orienting reflex to it becomes weaker, even if the stimulus is quite strong. A change in the nature of the stimulus, however, will restore the reflex to full strength.

Covert orienting

The overt orienting response to sudden changes in the environment is usually accompanied by another, unseen orienting response, the fixation of attention on the event or object that elicited the reflex. This unseen attentional orienting is called covert orienting. The combination of overt and covert orienting to an event usually results in enhanced perception of that event, including faster identification and awareness of its significance: for example, we can move our eyes to an object (overt attention) or shift attention to it without moving the eyes (covert attention).

Although this covert orienting of attention usually occurs in conjunction with overt orienting, whether reflexive or voluntary, it is possible to covertly attend to an event or stimulus without giving any overt sign that we are doing so (e.g., Helmholtz, 1867/1925; Posner, 1980; Wright & Ward, 2008).

Thus, covert attentional orienting is typically studied separately from overt orienting behaviors, although the two are certainly closely related. The premotor theory of attention (e.g., Rizzolatti et al., 1994) proposes that these attentional systems are supported by the same neural mechanisms, although a detailed examination of the behavioral and physiological data suggests that while the two probably share some neural mechanisms, they are not identical (see discussions in Corbetta & Shulman, 2002; Wright & Ward, 2008).

Stimulus-driven, exogenous, orienting

As with the orienting reflex, abrupt or intense stimuli can induce covert orienting, i.e., capture attention. For example, abruptly appearing letters on a computer monitor capture attention and are responded to more quickly than gradually appearing letters (Jonides & Yantis, 1988; Yantis & Jonides, 1984). When such an abruptly appearing stimulus (a direct cue) appears about 100 msec before another stimulus (a target) at the same spatial location, the latter is processed faster and more accurately than if it had appeared at a different location (e.g., Müller & Humphreys, 1991), presumably because attention is reflexively drawn to the spatial location of the direct cue.

Attention that is reflexively captured in this way is said to be exogenously oriented in a stimulus-driven manner. Attention directed in this stimulus-driven manner doesn’t stay directed to the attracting location for long, however, moving to another location after about 100-200 msec unless the attracting stimulus requires enhanced processing or signals a high probability of a target occurring at that location.

Attention is also drawn to the abrupt appearance of a new perceptual object, even if its appearance is not accompanied by a luminance change, but not to a luminance change that is not associated with the appearance of a new object (Yantis & Hillstrom, 1994). Thus, attention is drawn both to a new perceptual object and to its location (Egeth & Yantis, 1997). Exogenous attentional capture also occurs in hearing and touch.

In addition, a direct cue in one of these modalities, such as a sound, can direct attention to a location so that when a target in another modality, such as a visual pattern, appears there, it is also processed more quickly and accurately (Wright & Ward, 2008).

Part of the cue effect in stimulus-driven orienting appears to be caused by residual sensory activity from the direct cue itself, which also dissipates within 100-200 msec (Wright & Ward, 2008). Indeed, the simultaneous presentation of up to 4 direct cues in the same display can lead to cueing effects at all their locations (Wright & Richard, 2003).

Nevertheless, the cue effect from a single direct cue display is larger than that from multiple cue displays, suggesting that cue effects from a single direct cue arise from both orienting attention and residual sensory activation, whereas those from multiple cue displays arise solely from residual sensory activation (Wright & Richard, 2003).

Neurophysiology of stimulus-driven orienting

The reflexive capture of attention by abrupt or intense stimuli is implemented by a network of brain areas including the superior colliculus, the pulvinar nucleus of the thalamus (both subcortical), and the posterior parietal cortex, as well as areas in the frontal cortex and, of course, the various sensory cortices. Much research suggests that an early model in which the posterior parietal cortex disengages attention from a current target/location, the superior colliculus shifts it to a new target/location, and the pulvinar nucleus engages attention at that new location is roughly correct (Wright & Ward, 2008).

Recent imaging research has provided a more specific picture of the cortical parts of this network, which include the temporal-parietal junction and the ventral-frontal cortex, specifically the inferior frontal gyrus and the middle frontal gyrus, mainly on the right side of the brain (Corbetta & Shulman, 2002).

Goal-directed or endogenous orienting

In addition to reflexive, stimulus-driven orienting, we can also voluntarily (endogenously) orient attention to a location in space or to an object, often based on a cue that tells us where to look or listen, such as an announcement over the loudspeaker that passengers on a particular flight will be disembarking at a particular gate in the airport. Information about where or what to look at or listen to is an expectation of an environmental event, and we often prepare for the event by orienting attention to the location and time of the expected event (LaBerge, 1995). This advance, goal-directed orientation of attention enhances the processing of the event when it occurs (e.g., Posner, 1980).

Costs and benefits of symbolic cues

Goal-directed orienting is typically studied in experiments by presenting a predictive symbolic cue (e.g., an arrow pointing to a possible target location) about where in space a target stimulus will occur, the so-called Posner paradigm (e.g., Posner, 1980). Usually (e.g., on 80% of arrow-cue trials, which can be 80% or more of the total trials), the target will appear there (called valid-cue trials), giving the subject an incentive to focus attention there in advance of the target’s appearance. Sometimes (on 20% of arrow cue trials, when 80% are valid) the target appears at a location other than the cued location (called invalid-cue trials).

Finally, in some implementations, a third group of trials (neutral-cue trials; often 20% or less of total trials) is presented with a neutral (as to target location) cue. On these trials, targets appear randomly at possible locations. Under these conditions, targets on valid-cue trials are attended more quickly than targets on neutral trials (a benefit of orienting to the target location), whereas targets on invalid-cue trials are attended more slowly than targets on neutral trials (a cost of orienting to the wrong location).

Such goal-directed orienting of attention is slower than stimulus-directed orienting, typically taking about 300 msec to reach full effectiveness (Shepard & Müller, 1989). Furthermore, goal-directed attention can be maintained at a location for quite a long time, even several minutes, whereas stimulus-directed attention is usually transient unless goal-directed attention is invoked by a predictive direct cue or an interesting target stimulus. Goal-directed orienting is not automatic and can be interrupted by an attention-capturing stimulus (Müller & Rabbitt, 1989), although it can be maintained even in the presence of such a stimulus if the predictive value of the symbolic cue is high enough (Yantis & Jonides, 1990).

Neurophysiology of goal-directed orienting

A specific network of brain areas supports goal-directed attentional orienting. The cortical parts are called the dorsoparietal network (Corbetta & Shulman, 2002). It involves frontal regions, in particular the frontal eye fields (FEF), which also seem to be involved in voluntary orienting to auditory and tactile events (e.g., Shomstein & Yantis, 2004), parietal regions, in particular the intraparietal sulcus (IPS), as well as the relevant sensory cortices and subcortical areas (thalamus and superior colliculus).

In addition, this network interacts with the ventroparietal network (shown in red), presumably through connections between the TPJ and the IPS (shown in blue). It is possible that the interactions between the brain regions of the dorsoparietal and ventroparietal networks are mediated by the synchronization of their activities at different frequencies, particularly in the gamma (30-70 Hz) and alpha (8-14 Hz) ranges (e.g. Doesburg, et al, 2008; see also Varela et al 2001; Ward, 2003).

Inhibition of return

When attention has been directed to a particular location or perceptual object and then shifts to another location or object, it appears to be inhibited from returning to the original location or object for a period of up to 2 seconds (e.g., Posner & Cohen, 1984; Tipper, Driver, & Weaver, 1991). This is referred to as inhibition of return (IOR).

IOR is thought to promote the search for informative objects or locations, and it occurs within and across visual, auditory, and tactile modalities, just as attention does (e.g., Klein, 2000; Spence & Driver, 1998; Ward, 1994), and in infants as young as 6 months of age (Rothbart, Posner, & Boylan, 1990). Although it is possible that IOR arises from inhibition associated with a motor process such as eye movements or manual responses (see Wright & Ward, 2008 for a review of premotor theory in this regard), recent evidence suggests that its neural expression may also arise during perceptual or cognitive processing of stimuli at previously attended locations (e.g., Prime & Ward, 2006).

Focused attention

When attention is directed to a specific location in space, it is called focal or spatial attention. When it is directed to a particular object, whether visual, auditory, somatosensory, olfactory, or gustatory, it is called object-oriented attention. But whether it is directed to a place or an object, the extent of attentional focus can be controlled in a goal- or stimulus-driven manner (see Yantis & Serences, 2003, for a review of spatial and object-oriented attention and their similar cortical mechanisms).

The larger the area over which attention is spread, the less efficient is the processing of information within that area (e.g., Laberge & Brown, 1989). Furthermore, the further away a stimulus is from the center of an attended region, the less efficient the processing (e.g., Eriksen & St. James, 1986). This latter effect is sometimes referred to as the attentional gradient.

Filtering

Attention acts as a filter, extracting more information from attended stimuli and suppressing information extraction from unattended stimuli. The suppression can be so great as to cause what is called inattentional blindness, which occurs for all modalities.

The Cocktail Party Phenomenon

At a noisy cocktail party (or any other kind of party), attentional filtering is rampant. People listen to one conversation, line of music, etc., and filter out the rest as “noise. Cherry (1953) used shadowing to study this phenomenon in auditory attention. In this technique, an observer must repeat aloud (shadow) one of two continuous streams of speech. Close shadowing results in the loss of most of the information in the non-shadowed stream, except sometimes for strong direct cues such as one’s own name or a loud noise, which can cause orienting to that stream. However, the non-shadowed information is stored in short-term memory and can be retrieved when the shadowing is interrupted.

Inattention and change blindness

An analog of auditory shadowing has been used to study visual filtering (Neisser & Becklin, 1975). Subjects shadowed one of two overlapping video programs with similar results: most of the information in the non-shadowed stream was not noticed or remembered. Like auditory filtering, visual filtering allows little of the filtered information to make a lasting impression.

Modern replications of this result have yielded even more dramatic and counterintuitive results, such as the failure to notice a person in a gorilla suit beating his chest and jumping around during a shadowed basketball game (Simons & Chabris, 1999). Even quite dramatic stimuli in simple displays can pass unnoticed if attention is directed elsewhere. This has been termed inattentional blindness (Mack & Rock, 1998). A related phenomenon is change blindness (e.g., Rensink, 2002), in which a scene and the same scene with a change in it are presented for brief periods separated by a blank interval. Until attention is drawn to the changed element, it cannot be reported.

Neurophysiology of filtering

Attentional filtering appears to be accomplished by the activity of the pulvinar nucleus of the thalamus under the direction of other, presumably frontal, cortical areas such as the frontal eye fields (FEF; LaBerge, 1995). The pulvinar nucleus is also thought to be the subcortical area responsible for engaging attention, and it shows increased activity when attention must be used to filter out distracting stimuli (e.g., Corbetta, et al., 1991; Laberge & Buchsbaum, 1990).

The effect of attending to a particular stimulus on neural activity is evident quite early in sensory processing and includes both enhanced response to the attended stimulus and inhibited response to other, unattended stimuli. In vision, for example, Moran and Desimone (1985) showed that responses in visual area V4 of monkeys to the same stimulus depended strongly on whether it was attended or ignored. Appropriately attended stimuli in the receptive field of a V4 neuron elicited a strong response that was dramatically reduced when the same stimulus had to be ignored.

Similarly, attending to a particular feature of objects in the visual field elicits more vigorous responses from neurons in monkey V4 tuned to that feature than when attention is directed to other features of the same objects (see review by Maunsell and Treue, 2006).

In addition, gamma-band synchronization of neural responses from different neurons in V4 to the same stimulus is increased by selective attention, whereas alpha-band synchronization is decreased, possibly serving to enhance the signal produced by attended stimuli relative to that produced by distractors (Fries et al., 2001). A good recent review of these mechanisms can be found in Kastener and Ungerleider (2000).

Divided attention

The term divided attention (or split attention) refers to an individual’s ability to attend to more than one stimulus or event simultaneously. In fact, it is a widespread psychological phenomenon in everyday life, allowing us to perform several activities simultaneously, such as listening to a radio program while driving a car.

In the field of experimental psychology, researchers have mainly used the dual-task paradigm to study the phenomenon of divided attention. The dual-task paradigm implies that the subject is simultaneously engaged in two experimental tasks that involve different skills or have different levels of difficulty.

In everyday or experimental situations, when we are faced with a dual task, two types of cognitive processes come into play: control processes and automatic processes. The former occur under conscious control, are slower, and require a higher cognitive load, while the automatic processes are faster and unconscious. In general, the task at which we are more experienced may require more use of automatic processes (already established learning, e.g., cycling) without interference between the two tasks. In contrast, when two tasks require conscious, serial control processes, we face competition for limited resources and a decline in performance.

With respect to divided attention, so-called capacity theories support the divisibility of cognitive resources between different tasks performed simultaneously and the partial use of attentional resources for different tasks. For example, Kahneman’s model, which integrates structural and capacity theories, first recognizes the inherent limitation of an individual’s resources for performing mental tasks. Second, according to Kahneman’s model, there would be a gradual increase in mobilized resources as a function of demands in the case of a dual task, although this gradual increase reaches a threshold limit. At this threshold, the demands exceed the individual’s resources and interference between tasks is observed.

Dividing attention between two (or more) sources is very difficult. For example, people can’t easily listen to two simultaneous audio streams or watch two overlapping videos while recognizing target events in each, especially when the two sources are spatially separated. Sometimes two aspects of a single object can be attended successfully, but when the two aspects characterize two spatially separate objects, performance is worse in divided attention conditions (Bonnel & Prinzmetal, 1998).

It is also easier to divide attention between information streams in two different sensory modalities, such as vision and hearing, but if the task is more difficult than simply detecting occasional stimuli in these channels, performance is still worse than when attending to only one channel (e.g., Bonnel & Hafter, 1998).

When the task is more difficult, only when the task can be performed automatically in one modality, e.g., typing by an expert typist, can attention be divided without performance decrement, and then only when the response modalities are similarly different (e.g., an expert typist typing a text – visual/manual, while giving a verbal response when she hears her name in an auditory channel – auditory/verbal).

Searching

When we know what we’re looking for but don’t know where to find it, we have to search for it. Attention plays an important role in this search, and search experiments have yielded a great deal of information about its mechanisms.

When observers are presented with a field of items to search for a particular target, they can perform the search very quickly, and in roughly the same time regardless of the number of non-target items, if the target differs from the non-targets in a single feature; this is called easy/pop-out/parallel search. However, if the searcher must detect a combination of features, the search is slow and the time to find the target increases linearly with the number of non-targets; this is called difficult/serial search.

Simple search could be achieved by simply detecting the presence of activation in a particular one of the feature maps generated by sensory processing (feature maps are layers of visual cortex in which the activity of particular neurons signals the presence of a particular feature, such as a slanting line, on the retina). This can be done without directing attention to a specific object in the field. In contrast, difficult search appears to require that attention be directed to each item in turn, which slows the search and makes the total search time dependent on the number of nontarget items (e.g., Woodman & Luck, 1999).

Feature integration theory (e.g., Treisman & Gelade, 1980) explains these data by suggesting that the binding of features into a perceptual object requires focal attention to a particular location. However, this is not the full story, as conjunctions of simple features also sometimes result in very fast search (e.g., Wolfe et al., 1989), and attention can be directed sequentially to items in simple search and to individual features in conjunction search (Kim & Cave, 1995).

Much practice with a difficult search task that always requires the same response to a given stimulus gradually shifts the process from controlled search, in which search time is a function of the number of items in the search set, to automatic search, in which search time is roughly independent of the number of items in the search set (e.g., Schneider & Shiffrin, 1977; Shiffrin & Schneider, 1977). Search functions for controlled and automatic search are similar to those for easy and difficult search.

A common explanation for the process of automatization is that with increasing practice, attention is slowly withdrawn from task control until the process requires minimal effort and is said to be automatic. In automatic search, responses are ballistic, so they’re difficult to inhibit and not well remembered. Many lapses of attention in everyday life can result from such automatic responses (e.g., Reason, 1984). On the other hand, automatic processing allows for better divided attention performance.

Theories of attention

Each of the major aspects of attention, orienting, filtering, and searching, has spawned numerous theories, both at the psychological and the neurological level. Early theories focusing on filtering suggested that information processing in the brain is structurally limited, with an early filter based on physical properties such as location and spectral content that allows only a few selected stimuli to pass (e.g., Broadbent, 1958).

Demonstrations that at least some processing occurs even on the rejected channels led to the rejection of these early selection theories in favor of late selection theories, which hypothesize that all sensory information undergoes preliminary analysis. Instead, the processing bottleneck occurs just before entry into long-term memory (e.g., Deutsch & Deutsch, 1963). There is physiological evidence to support both approaches, and they probably occur under different circumstances (e.g., Pashler, 1996).

Failures of divided attention have led to the idea that attention is a limited resource that, when demanded by one task, is unavailable for another (e.g., Kahneman, 1973). On the other hand, the demonstration that time sharing between perceptual or cognitive tasks is possible, especially when one task is overlearned or automatic, has led to the idea that there are multiple attentional resources that can be shared among tasks, provided there are no conflicts (e.g., Wickens, 1984).

According to this approach, central resources (e.g., encoding, comparison, memory) interact with spatial and verbal codes, sensory modalities, and response systems to constrain performance. This approach has been criticized as too flexible (e.g., Navon, 1984), although the idea of limited attentional resources is still widely used.

Another class of theories attempts to capture the mechanisms of attentional orientation. Some of these have been mentioned above. Among the most general and useful are the approaches of Corbetta and Shulman (e.g., 2002), Laberge (e.g., 1995), and Shipp (e.g., 2004). Many of these theories emphasize the concept of salience, i.e., that attention is directed to the most salient of available locations or objects, with salience being a combination of bottom-up and top-down contributions.

Shipp (2004) discusses several salience models and combines them all into a theory of the physiology of the orienting system, with a salience map in the pulvinar nucleus of the thalamus combining inputs from other such maps throughout the brain. In this theory, IOR is explained by a decrease in the salience of a recently inspected location or object.

Finally, there are other models that attempt to capture certain aspects of attention in a computational or mathematical framework. The episodic theory of Sperling and Weichselgartner (1995) is particularly general and accommodates a variety of possible mechanisms. In this approach, general temporal transition functions are assumed for the movement of attention and the onset and offset at particular locations. These temporal functions refer to an attentional focus that can have a variety of characteristics, such as size and intensity.

Thus, the theory can accommodate a variety of results from studies of all the aspects discussed above. More recently, Taylor (e.g., Taylor & Rodgers, 2002, CODAM model) has proposed a neural network model of attentional control that is neurophysiologically realistic. There are also theories of attentional oscillations and the entrainment of attentional focus to rhythmic events such as music (e.g., Large & Jones, 1999). These dynamical theories are also mathematical, as is the description of the oscillators. None of these theories has yet gained general acceptance. Follow the links below for discussions of several specific theories.

The control of attention

Attention can be voluntary (or endogenous) or automatic.

An example of voluntarily directed attention is Posner’s classic experiment. This experiment uses the “spatial cueing paradigm” to study the shifting of attention. The subject stands in front of a monitor and is asked to maintain his gaze on a fixation point (e.g., a cross on the screen). Next to the cross there are two squares, and during the experiment a target stimulus appears at certain times within these squares. The subject’s task is to detect the appearance of the target as quickly as possible. In addition, an arrow appears just before the square, indicating with high probability the location of the target’s appearance.

By measuring the subject’s reaction time, it was found that individuals responded faster when the arrow correctly indicated the position of the target’s appearance. In this sense, subjects were able to preemptively shift their attention to the indicated location, allowing for faster information processing. In this spatial suggestion paradigm, attention is directed voluntarily, as the subject directs attention to the square indicated by the arrow, knowing that there is a reasonable probability that the arrow correctly precedes the appearance of the target.

Attention can also be directed automatically (or exogenously), that is, independently of the subject’s will. For example, this type of automatic attentional orientation is observed when a new and unexpected peripheral light signal appears. Automatic can be defined as an orientation of attention that is independent of cognitive load and resistant to suppression, acting almost as a reflex.

Beyond laboratory experiments, the components of voluntary and automatic orienting of attention often coexist in our daily lives. For example, when our goal is to search for something, it often happens that our attention is distracted by the presence of another object. In general, it is believed that attention can be automatically captured by events, stimuli, and information that are irrelevant to the subject’s purpose and task.

Selective attention

Selective attention refers to the ability to focus on the target stimulus, the object of interest, and to process in a privileged way the information relevant to achieving a specific goal. The information that receives attention is selected and processed more efficiently, has access to consciousness, and guides the response.

Faced with a complex environment full of stimuli, the individual must be able to select some of these stimuli-objects and neglect others in order to achieve a goal and/or perform a behavior. Through selective attention and spatial attention, the focus of attention is directed to a delimited part of space and some stimuli that fall within the focus of attention are considered relevant and reach the level of consciousness.

A typical example is the phenomenon of the cocktail party, where one can pay attention to a single conversation despite the presence of many others that could interfere: although the sound emissions of different guests are picked up by the acoustic receptors, the individual, through selective attention, selects and analyzes only those coming from some interlocutors.

Several theoretical contributions have attempted to understand and explain the moment in the information processing process at which attention intervenes and selects the information to be processed. A first theoretical approach refers to the early selection of information, while other theories advocate a late selection of information. Both approaches share the idea that attention acts as a filter that allows only a limited amount of information to pass through and be processed. The difference lies in the point at which this filter intervenes in the overall process of elaboration, i.e., at an earlier or later stage.

According to early selection theories, attention acts as a filter that excludes from processing most of the information coming from outside, and the selection is already implemented at the level of sensory input. An example of an early selection theory is Broadbent’s filter theory, which refers to the dichotic listening paradigm. This paradigm requires the subject to pay attention only to messages transmitted to one ear and to ignore information transmitted to the other ear. According to this theory, there would be an initial phase of information processing during which all stimuli are rapidly analyzed in parallel by the sensory system (S) simultaneously and stored for a short period of time. This initial processing would be followed by a more advanced phase of serial processing by the perceptual system (P). A filter, placed between the S and P systems, selects stimuli that have access to the more advanced levels of processing.

A similar theory is Treisman’s attenuated filter theory. Building on Broadbent’s classic filter theory, the author revises the concept of attentional filtering itself from an attenuation perspective: the filter would not completely eliminate the processing of irrelevant information, but would attenuate its processing and keep it subthreshold. Such subthreshold stimuli could, under certain conditions, be reactivated and reprocessed by the subject in a more complex and conscious manner.

Thus, according to the early selection approach, information selection occurs before the semantic content is processed, with a progressive decay of information that is not selected because it is considered irrelevant upstream. According to late selection theories, however, the processing of irrelevant information is complete and does not decay a priori.

For example, Deutsch and Deutsch’s (1963) theory assumes that all information and stimuli of varying relevance are processed at the semantic level. Selective attention only comes into play when a response must be selected to be given. In this sense, selective attention allows to control the access of information to consciousness.

One of the classic experiments on selective attention is the Stroop test. In the Stroop experiment, the subject is shown words written in different colors. The task is to say aloud the color of the ink used to write the word. Thus, the color is the relevant information for performing the task, while the meaning of the word (which is not to be read) is the irrelevant information. The stimuli presented in the Stroop experiment can be neutral, congruent, or incongruent. Neutral is when only text or only color is presented. Congruence is when the word “red” is written in red, and incongruence is when the word “red” is written in green. Recall that the required response is the name of the color, i.e., red in the first case and green in the second.

Stroop (1935) found that participants in a naming task had slower response times when the ink color differed from the meaning of the written word, even though they were instructed to ignore the meaning of the word. Thus, the Stroop effect is to produce a response with a slower latency in the incongruent condition and a faster latency in the congruent condition. The purpose of the Stroop experiment is to create a cognitive and semantic interference: in this case, for example, the mind tends to mechanically read the meaning of the word (for example, it reads the word “red” and thinks of the color “red”, but the ink used is a different color). For this reason, the Stroop test is a well-established experimental procedure for studying selective attention.

As supported by late selection theories, the individual would engage in some form of processing even of information or stimuli to which he or she does not voluntarily pay direct and “conscious” attention.

With the advent of cognitivism, the first studies linking attention and consciousness focused on so-called subliminal perception. In psychology, the term “subliminal perception” refers to those phenomena in which a stimulus influences behavior even when it is “unconsciously” perceived by the subject, for example, because it is presented too quickly.

In studies using the priming paradigm, a stimulus called the “prime” is presented first, followed immediately by a second stimulus called the “target,” which requires the subject to make a response. Some studies related to the speed of linguistic comprehension have provided empirical support for the delayed selection theories: the subject would understand with less reaction time words that are semantically related to the prime. Conversely, when the target stimulus to be recognized is not semantically related to the prime, reaction times increase. In this sense, the explanatory hypothesis is that the representations of irrelevant information are first activated and semantically processed, and only later inhibited because they are irrelevant.

Attention and consciousness

Attention is closely related to consciousness. Both are integrative, but also selective. Inattentional blindness seems to indicate that items that are not in attention are not consciously perceived. Indeed, the relationship is so close that Taylor’s CODAM model of attention is claimed to provide, through the consequent discharge of attentional control signals, two important aspects of consciousness, namely the sense of ownership of conscious experience and its immunity to error through misidentification.

However, the two concepts are distinct. Attention is usually conceptualized as the enhancement of signal-to-noise ratio, both by inhibiting the processing of unattended stimuli and by enhancing the processing of attended stimuli. Consciousness refers primarily to phenomenal experience itself, and secondarily to aspects of that experience such as its wholeness, its sense of self-ownership (first-person ontogeny), the ability to report its contents verbally or in other ways, and the awareness of being conscious (metaconsciousness).

There are several models of the relationship between attention and primary or phenomenal consciousness, including that of Taylor and most others, in which cognitive material (sensations, perceptions, cognitions, memories, etc.) is either attended or unattended, with attended items being experienced and also reportable, and so on. A competing model holds, among other things, that all cognitive material is either conscious or unconscious, with attention selecting some of the conscious material for enhanced processing, making it reportable (e.g., Lamme, 2003).

Lamme’s model assumes that all reentrant neural processing gives rise to conscious experience, but that only the experience selected by attention is reportable. This implies that there can be consciousness without attention, but that only conscious material can be attended to. In contrast, Koch and Tsuchiya (2007) provide evidence for a more complete dissociation between the two, i.e., attention with and without consciousness, and consciousness with and without attention. In this latter view, attention and consciousness are separate processes in the brain, but are closely related. There is no definitive way to choose between these models.

Related keywords

References

  1. Attention by Lawrence M. Ward is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.
  2. Bonnel A-M Hafter E. (1998) Divided attention between simultaneous auditory and visual signals. Percep. Psychophys. 60:179–190.
  3. Bonnel A-M Prinzmetal W. (1998) Dividing attention between the color and the shape of objects. Percep. Psychophys. 60:113-124.
  4. Broadbent DE. (1958) Perception and communication. New York: Pergamon Press.
  5. Cherry C. (1953) Some experiments on the recognition of speech with one and two ears. J. Acoust. Soc. Amer. 25:975–979.
  6. Corbetta M Miezin F Dobmeyer S Shulman G Petersen S. (1991) Selective and divided attention during visual discrimination of shape, color, and speed: Functional anatomy by positron emission tomography. J. Neurosci. 11:2383–2402.
  7. Corbetta M Shulman GL. (2002) Control of goal-directed and stimulus-driven attention in the brain. Nature Rev. Neurosci. 3:201–215.
  8. Deutsch JA Deutsch D. (1963) Attention: Some theoretical considerations. Psychol. Rev. 70:80—90.
  9. Doesburg SM Roggeveen AB Kitajo K Ward LM (2008) Large-scale gamma-band phase synchronization and selective attention. Cereb. Cortex 18:386-396.
  10. Egeth HE Yantis S (1997) Visual attention: Control, representation, and time course. Ann. Rev. Psychol. 48:269–297.
  11. Fries P Reynolds JH Rorie AE Desimone R (2001) Modulation of oscillatory neural synchrony by selective attention. Science 291:1560-1563.
  12. Helmholtz H von (1867/1925) Treatise on physiological optics (Trans. From 3rd German edition). New York: Dover.
  13. Jonides J Yantis S. (1988) Uniqueness of abrupt onset in capturing attention. Percep. Psychophys. 43:346–354.
  14. Kahneman D. (1973) Attention and Effort. Englewood Cliffs, NJ: Prentice-Hall.
  15. Kastner S Ungerleider LG (2000) Mechanisms of visual attention in the human cortex. Ann. Rev. Neurosci. 23:315-341.
  16. Klein RE. (2000) Inhibition of return. Trends Cog. Sci. 4:138-147.
  17. Koch C Tsuchiya N (2007) Attention and consciousness: Two distinct brain processes. Trends Cog. Sci. 11:16-22.
  18. LaBerge D (1995) Attentional processing: The brain’s art of mindfulness. Cambridge, MA: Harvard University Press.
  19. LaBerge D Buchsbaum MS (1990) Positron emission tomographic measurements of pulvinar activity during an attention task. J. Neurosci. 10:613–619.
  20. Lamme VAF. (2003). Why visual attention and awareness are different. Trends Cog. Sci. 7:12–18.
  21. Large EW Jones MR (1999) The dynamics of attending: How people track time-varying events. Psychol. Rev. 106:119—159.
  22. Mack A Rock I. (1998) Inattentional blindness. Cambridge, MA: MIT Press.
  23. Maunsell JHR Treue S (2006) Feature-based attention in visual cortex. Trends in Neurosci. 29:317-322.
  24. Moran J Desimone R (1985) Selective attention gates visual processing in the extrastriate cortex. Science 229:782-784.
  25. Müller HJ Humphreys GW. (1991) Luminance-increment detection: Capacity-limited or not? J. Exp. Psychol.: Hum. Percep. Perfor. 17:107–124.
  26. Navon D. (1984) Resources: A theoretical soup stone? Psychol. Rev. 91: 216–234
  27. Neisser U Becklin R. (1975) Selective looking: Attending to visually specified events. Cog. Psychol. 7: 480-494.
  28. Pashler H. (1996) The Psychology of Attention. Cambridge, MA: MIT Press.
  29. Posner MI. (1980) Orienting of attention. Quart. J. Exp. Psychol. 32:3–25.
  30. Posner MI Cohen Y. (1984) Components of visual attention. In H. Bouma DG Bouhuis (Eds.), Attention & Performance X (531–556). Hillsdale, N.J.: Erlbaum.
  31. Prime DJ Ward LM. (2006) Cortical expressions of inhibition of return. Brain Res. 1072:161–174.
  32. Reason J. (1984) Lapses of attention in everyday life. In R Parasuramen DR Davies (Eds) Varieties of Attention (515-549). Orlando: Academic.
  33. Rensink RA. (2002) Change detection. Ann. Rev. Psychol. 53:245–277.
  34. Rizzolatti G Riggio L Sheliga BM (1994) Space and selective attention. In C Umilta M Moscovitch (Eds) Attention and Performance XV (231-265). Cambridge, MA: MIT Press.
  35. Rothbart MK Posner MI Boylan A. (1990) Regulatory mechanisms in infant development. In JT Enns (Ed) The Development of Attention: Research and Theory (47-66). Amsterdam: Elsevier.
  36. Schneider W Shiffrin RM. (1977) Controlled and automatic human information processing I: Detection, search and attention. Psychol. Rev. 84:1-66.
  37. Simons DJ Chabris CF. (1999) Gorillas in our midst: Sustained inattentional blindness for dynamic events. Perception 28:1059-1074.
  38. Shiffrin RM Schneider W. (1977) Controlled and automatic human information processing II: Perceptual learning, automatic attending, and a general theory. Psychol. Rev. 84:127-190.
  39. Shipp S. (2004) The brain circuitry of attention. Trends Cog. Sci. 8:223–230.
  40. Sokolov EN. (1975) The neuronal mechanisms of the orienting reflex. In NE Sokolov OS Vinogradova (Eds), Neuronal mechanisms of the orienting reflex (217–238). New York: Wiley.
  41. Sperling G Weichselgartner E. (1995) Episodic theory of the dynamics of spatial attention. Psychol. Rev. 102:503-532.
  42. Spence C Lloyd D McGlone F Nicholls MER Driver J. (2000) Inhibition of return is supramodal: A demonstration between all possible pairings of vision, touch, and audition. Exp. Brain Res. 134:42–48.
  43. Taylor JG & Rogers M. (2002) A control model of the movement of attention. Neural Networks 15: 309-326
  44. Tipper SP Driver J Weaver B. (1991) Object-centred inhibition of return of visual attention. Quart. J. Exp. Psychol. A 43:289—298.
  45. Treisman AM & Gelade G. (1980) A feature-integration theory of attention. Cognitive psychology, 12 (1), 97-136.
  46. Varela F Lachaux J-P Rodriguez E Martinerie J. (2001) The brainweb: Phase synchronization and large-scale integration. Nat. Rev. Neurosci. 2:229–239.
  47. Ward LM. (1994) Supramodal and modality-specific mechanisms for stimulus-driven shifts of auditory and visual attention. Can. J. Exp. Psychol. 48:242—259.
  48. Ward LM. (2003) Synchronous neural oscillations and cognitive processes. Trends Cog. Sci. 7:553–559.
  49. Wickens CD. (1984) Processing resources in attention. In R Parasuramen DR Davies (Eds) Varieties of Attention (63-101). Orlando: Academic.
  50. Wolfe JM Cave KR Franzel SL.(1989) Guided search: An alternative to the feature integration model for visual search. J. Exp. Psychol.: Hum. Percep. Perform. 15:419–433.
  51. Woodman GF Luck SJ. (1999) Electrophysiological measurement of rapid shifts of attention during visual search. Nature 400:867–869.
  52. Wright RD Richard CM. (2003) Sensory mediation of stimulus-driven attentional capture in multiple-cue displays. Percep. Psychophys. 65:925–-938.
  53. Wright RD Ward LM. (2008) Orienting of Attention. New York: Oxford University Press.
  54. Yantis S Hillstrom AP. (1994) Stimulus-driven attentional capture: Evidence from equiluminant visual objects. J. Exp. Psychol.: Hum. Percep. Perform. 20:95–107.
  55. Yantis S Jonides J. (1984) Abrupt visual onsets and selective attention: Evidence from visual search. J. Exp. Psychol.: Hum. Percep. Perform. 10:601–621.
  56. Yantis S Serences JT (2003) Cortical mechanisms of space-based and object-based attentional control. Curr. Opin. Biol. 13:187-193.
Subscribe
Notify of
guest

0 Comments
Inline Feedbacks
View all comments
Scroll to Top