This authoritative reference provides a comprehensive examination of the nature and functions of attention and its relationship to broader cognitive processes. The editor and contributors are leading experts who review the breadth of current knowledge, including behavioral, neuroimaging, cellular, and genetic studies, as well as developmental and clinical research. Chapters are brief yet substantive, offering clear presentations of cutting-edge concepts, methods, and findings. The book addresses the role of attention deficits in psychological disorders and normal aging and considers the implications for intervention and prevention. It includes 85 illustrations. New to This Edition*Significant updates and many new chapters reflecting major advances in the field.*Important breakthroughs in neuroimaging and cognitive modeling.*Chapters on the development of emotion regulation and temperament.*Expanded section on disorders, including up-to-date coverage of ADHD as well as chapters on psychopathy and autism.*Chapters on cognitive training and rehabilitation.
This authoritative reference provides a comprehensive examination of the nature and functions of attention and its relationship to broader cognitive processes. The editor and contributors are leading experts who review the breadth of current knowledge, including behavioral, neuroimaging, cellular, and genetic studies, as well as developmental and clinical research. Chapters are brief yet substantive, offering clear presentations of cutting-edge concepts, methods, and findings. The book addresses the role of attention deficits in psychological disorders and normal aging and considers the implications for intervention and prevention. It includes 85 illustrations. New to This Edition*Significant updates and many new chapters reflecting major advances in the field.*Important breakthroughs in neuroimaging and cognitive modeling.*Chapters on the development of emotion regulation and temperament.*Expanded section on disorders, including up-to-date coverage of ADHD as well as chapters on psychopathy and autism.*Chapters on cognitive training and rehabilitation.
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Overview
This authoritative reference provides a comprehensive examination of the nature and functions of attention and its relationship to broader cognitive processes. The editor and contributors are leading experts who review the breadth of current knowledge, including behavioral, neuroimaging, cellular, and genetic studies, as well as developmental and clinical research. Chapters are brief yet substantive, offering clear presentations of cutting-edge concepts, methods, and findings. The book addresses the role of attention deficits in psychological disorders and normal aging and considers the implications for intervention and prevention. It includes 85 illustrations. New to This Edition*Significant updates and many new chapters reflecting major advances in the field.*Important breakthroughs in neuroimaging and cognitive modeling.*Chapters on the development of emotion regulation and temperament.*Expanded section on disorders, including up-to-date coverage of ADHD as well as chapters on psychopathy and autism.*Chapters on cognitive training and rehabilitation.
Product Details
| ISBN-13: | 9781609189877 |
|---|---|
| Publisher: | Guilford Publications, Inc. |
| Publication date: | 11/15/2011 |
| Sold by: | Barnes & Noble |
| Format: | eBook |
| Pages: | 514 |
| File size: | 22 MB |
| Note: | This product may take a few minutes to download. |
About the Author
Michael I. Posner, PhD, is Professor Emeritus at the University of Oregon and Adjunct Professor of Psychology in Psychiatry at the Weill Cornell Medical College in New York, where he served as founding director of the Sackler Institute for Developmental Psychobiology. Dr. Posner is well known for his work with Marcus Raichle on imaging the human brain during cognitive tasks; the book Images of Mind resulted from that collaboration. He has worked on the anatomy, circuitry, development, and genetics of three attentional networks underlying maintaining alertness, orienting to sensory events, and voluntary control of thoughts and ideas. Dr. Posner’s methods for measuring these networks have been applied to a wide range of neurological, psychiatric, and developmental disorders. His research on the training of attention in young children and adults to understand the interaction of specific experience and genes in shaping attention is described in Educating the Human Brain, coauthored with Mary K. Rothbart. Dr. Posner has received numerous awards, including seven honorary degrees, election to the National Academy of Sciences of the USA, and the National Medal of Science.
Read an Excerpt
Cognitive Neuroscience of Attention
By Michael I. Posner
The Guilford Press
Copyright © 2004 The Guilford PressAll right reserved.
ISBN: 1-59385-048-4
Chapter One
A Systems-Level Perspective on Attention and Cognitive ControlGuided Activation, Adaptive Gating, Conflict Monitoring, and Exploitation versus Exploration
Jonathan D. Cohen, Gary Aston-Jones, and Mark S. Gilzenrat
THE SCOPE OF ATTENTION
An understanding of attention is arguably one of the most important goals of the cognitive sciences and yet also has proven to be one of the most elusive. Most attention researchers will agree that a major problem has been agreeing on a definition of the term and the scope of the phenomena to which it applies. There are no doubt as many explanations for this state of affairs as there are those who consider themselves "attention researchers." However, most will probably agree that, in large measure, this is because attention is not a unitary phenomenon-at least not in the sense that it reflects the operation of a single mechanism, or a single function of one or a set of mechanisms. Rather, attention is the emergent property of the cognitive system that allows it to successfully process some sources of information to the exclusion of others, in the service of achieving some goals to the exclusion of others. This begs an important question: If attention is so varied a phenomenon, how can wemake progress in understanding it? There are two simple answers to this question: Be precise about the specific (aspects of the) phenomena to be studied, and be precise about the mechanisms thought to explain them.
In this chapter, we address a particular type of attentional phenomenon-that associated with cognitive control. Furthermore, we focus on an account that addresses not only the functional characteristics of this form of attention but also how it is implemented in neural machinery. This neurally oriented approach is attractive not only because it is intrinsically interesting to understand how the mechanisms of the brain give rise to the processes of the mind but more specifically because this exercise has proven useful in generating insights into how controlled attention operates at the systems level. By assuming that information is represented as patterns of activity, and information processing occurs as the flow of activity, it becomes possible to understand how information represented in one part of the system can influence the processing of information in other parts of the system-that is, how attention and control operate at the systems level. The sections that follow develop this idea in greater detail, first by providing a particular example of controlled attention and how it can be modeled in terms of explicit processing mechanisms, then by showing how it can explain some of the most important observations that have been made about attention and control, and finally by reviewing recent elaborations of the basic model that have begun to address broader questions about the psychological and neural mechanisms that underlie cognitive control.
AN EXAMPLE
To see how attentional effects can be understood in terms of specific processing mechanisms, it is useful to consider an example of a model of a specific task. There are now models of a variety of tasks that could serve this purpose well. Here, we focus on a model of the Stroop task (Cohen, Dunbar, & McClelland, 1990), because this task has occupied such a central role in studies of attention (both basic and clinical), because the model illustrates in a relatively straightforward manner the principles of interest, and because this model has been used to explain a wide array of findings using the Stroop task. This model was developed within the connectionist or parallel distributed processing (PDP) framework, which has been described and elaborated in great detail elsewhere (e.g., McClelland, 1993; O'Reilly & Munakata, 2000; Rumelhart, McClelland, & PDP Research Group, 1986), and therefore we assume it is familiar (or accessible) to the reader.
In the Stroop task (Stroop, 1935), subjects must attend to one dimension of a stimulus (e.g., the color in which a word is displayed) and ignore a competing but prepotent dimension (e.g., the word itself). For example, subjects are asked to name the color of an incongruent stimulus, such as the word green displayed in red. In our model, units are arranged into two pathways (Figure 6.1). Stimulus units representing the color project to associative units in the color-naming pathway, which project in turn to verbal response units. The word pathway converges on the same set of verbal response units. Furthermore, connections are stronger in the word pathway, capturing the assumption that written words are more frequently and consistently mapped to their pronunciations than are visual color stimuli to the utterance of their names. As a result, with no additions to the model, it will respond to the incongruent Stroop stimulus above by "reading" the word (i.e., activating the "green" response unit). In fact, this is how human subjects respond if not instructed otherwise. That is, they produce the strongest (e.g., most familiar or salient) response to a stimulus. Critically, however, they can respond to the weaker dimension of a stimulus when asked to do so (i.e., name the color in the Stroop task). This an elementary-and perhaps the most studied-form of controlled, or voluntary, attention.
To explain this ability, we make the following set of modifications to the model. First, we assume that at-rest units have relatively low activity. This corresponds well with the properties of neurons (especially those in cortical areas), which typically exhibit relatively low firing rates at rest. This can be seen in Figure 6.2a, by noting that for an input of zero, the activity of the unit is also near zero. Second, we include an additional set of task demand units, each of which corresponds to one of the tasks subjects are asked to perform (color naming and word reading). We assume that each of these units is connected to all of the associative units in the corresponding pathway. Thus, the color-naming unit is connected to the associative units in the color-naming pathway, and similarly for the word-reading unit. When one of these task demand units is activated, it sends activity to all the associative units in the corresponding pathway. This has the effect of sensitizing these units to input from the stimulus units. Because this effect sits at the core of how attention operates in this model, it is important to consider this in greater detail.
Figure 6.2a illustrates the activation function for a unit-that is, the function that determines its activity based on the summed input it receives from other units. Note that this function is nonlinear. This is central to our account of attentional effects. Recall that units have low activity at rest (that is, when their input is zero). In this range the activation function is relatively flat. In other words, even if one of the stimulus units were to be activated and pass activity to the corresponding associative unit, this would have limited impact on the activity of that associative unit. Now assume that one of the task-demand units is activated. This passes activity to the associative units in that pathway. Let us assume further that the amount of activity is sufficient to move these units to the midpoint of their activation function, where this is steepest. Note that this does not provide any specific information to that pathway. That is, all the units in that pathway have been equally activated, so none drive one response more than the others. However, now any input to these units from the stimulus units will have a large impact on their activity. Even a small excitatory input to one of these associative units will quickly drive its activity up, while inhibitory input to the other will drive its activity down. In other words, the effect of activating the task-demand unit is to bias the associative units in that pathway, placing them in the sensitive range of their activation function. This serves to modulate the responsivity of those units, making them more sensitive to the inputs. This, in turn, allows the system to respond selectively to one source of information while ignoring another. For example, by activating the color-naming task-demand unit, the model can now respond to the color of the stimulus even when a conflicting word stimulus is present. That is, the model exhibits attention. This attentional effect derives from the ability of the task-demand units to guide the flow of activity along one pathway, while attenuating the flow along another. For this reason, we have come to refer to this as the guided activation theory of cognitive control (Miller & Cohen, 2001).
ATTENTION AND RELATED CONSTRUCTS
Models that implement the guided activation theory provide a quantitative account of attentional effects in a wide range of tasks (e.g., Braver, Barch, & Cohen, 1999; Braver & Cohen, 2001; Cohen, Servan-Schreiber, & McClelland, 1992; Cohen, Romero, Serven-Schreiber, & Farah, 1994; Dehaene & Changeux, 1989, 1991; Mozer, 1988; O'Reilly, Noelle, Braver, & Cohen, 2002; O'Reilly & Munakata, 2000; Phaff, van der Heijden, & Hudson, 1990; Servan-Schreiber, Bruno, Carter, & Cohen, 1998; Schneider & Detweiler, 1988). Equally important, it provides a unifying account of a constellation of processes and constructs related to attention. These are considered in the remainder of this section.
Controlled versus Automatic Processing
This is one of the oldest, and most fundamental constructs in cognitive psychology (Posner & Snyder, 1975; Shiffrin & Schneider, 1977). This distinction is cast largely in terms of the reliance on attention. Controlled processes are defined as those that rely on attention for execution, while automatic processes are defined as those that can be carried out without attention. One of the earliest applications of this construct was to the Stroop task (Posner & Snyder, 1975). Color naming was considered to be controlled because it relies on attention. Without attention to the color, subjects will read the word. Furthermore, the color has no impact on word reading, even when it conflicts with the word being read. Conversely, word reading is automatic because it does not appear to rely on attention. Even when asked to name the color, if a conflicting word is present it slows the response to the color (the classic Stroop effect; MacLeod, 1991; Stroop, 1935). This is thought to reflect the fact that the word is processed even without the allocation of attention. However, there are problems with a simple dichotomous distinction between color naming and word reading in terms of controlled versus automatic processing.
First, it is not clear that any cognitive process can occur entirely independently of attention. For example, although an individual is reading the words on this page, presumably he or she is not doing so out loud. Thus word reading, at least as it is practiced in the Stroop task, is not entirely independent of attention and control. Second, it is not clear that color naming is always dependent on attention and control. In a clever experiment, MacLeod and Dunbar (1988) had participants learn associations between arbitrary shapes (displayed in black and white) and names for them that happened to be color words. At various points during training, they tested their participants' ability to name shapes that were displayed in colors that conflicted with their names. As might be guessed, they found that early in training a shape's color interfered with the ability to provide its name. In other words, in this task, color naming behaved as if it were the automatic process, contradicting the traditional suggestion that it is controlled. Kahneman and Treisman (1984) reviewed a number of other attentional findings, concluding that all processes rely on attention to some degree, and that this may vary in a graded fashion. This is consistent with MacLeod and Dunbar's findings (which also demonstrated that, as subjects became more proficient at shape naming, the color of the shape came to influence this less, while the shape's name came to interfere with color naming). Our model offers a mechanistically explicit account of these findings.
As noted earlier, in the absence of any input from the task-demand units, neither color naming nor word reading can be carried out. This is because the associative units in both pathways rest in too unresponsive a region of their activation function. Thus, even word reading requires attention. At the same time, connections in the word-reading pathway are stronger. Thus, the amount of activity of the task-demand unit needed to support word reading is less than that needed for color naming. In other words, word reading relies less on attention or control than does color naming. It is critical to note, however, that even in the absence of task-demand unit activity some information can flow along a pathway. Although this may not be enough to elicit an overt response, it may be enough to influence processing. Thus color naming can be influenced by information in the word pathway and therefore demands more attention when the word conflicts with the color name than when it is congruent. However, this effect is relative. For example, when color naming competes with a weaker process, the reverse will be true. This was the situation in MacLeod and Dunbar's (1998) shape-naming experiment, in which the association of a shape with a color word is weaker than a color with a color word. Thus, different processes vary in the degree to which they rely on attention, and this also varies for a given process based on the context in which it is carried out. From this perspective, the distinction between controlled and automatic processing is not dichotomous and absolute but, rather, graded and relative: Some processes are more automatic than others, and processes vary in their automaticity based on the context in which they occur. While this demands quantitative rather than qualitative characterization of processes, our model offers a framework in which such quantification can be carried out in terms of the connection strengths in the relevant pathways.
Types of Attention
We began the previous section by defining controlled processes as those that rely on attention. But how do we define attention? In our model, attention can be defined as the influence that activity in the task-demand units has on processing in the color and word pathways. Note that this does not rely on any qualitatively distinct mechanisms. Attention arises from the flow of activity between units and over connections that are qualitatively identical to those used to actually perform the task.
Continues...
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Table of Contents
1. Progress in Attention Research, Michael I. Posner
I. Cognitive Science
2. On the Modes and Domains of Attention, Raymond M. Klein and Michael A. Lawrence
3. Boolean Map Approach to Visual Attention, Liqiang Huang and Harold Pashler
4. Symbolic and Connectionist Models of Attention, Hongbin Wang, Xun Liu, and Jin Fan
5. Models of Visual Search: From Abstract Function to Biological Constraint, Glyn W. Humphreys and Eirini Mavritsaki
6. Inhibitory Mechanisms in the Attentional Networks: A Multidisciplinary Approach, Luis J. Fuentes, Ana B. Vivas, Linda K. Langley, Qi Chen, and Carmen González-Salinas
7. Dynamic Cognitive Control and Frontal–Cingulate Interactions, Cameron S. Carter and Marie K. Krug
8. Discrete Resource Limits in Attention and Working Memory, Edward F. Ester, Edward K. Vogel, and Edward Awh
II. Imaging
9. Two Attentional Networks: Identification and Function within a Larger Cognitive Architecture, Gordon L. Shulman and Maurizio Corbetta
10. Clutter and Attention in Multivoxel Functional Magnetic Resonance Imaging, Leila Reddy and Nancy Kanwisher
11. A Frontoparietal Attention System in Human and Monkey Brain: Constructing and Assembling the Fragments of Thought and Behavior, John Duncan and Tom Manly
12. Nervous Anticipation: Top-Down Biasing across Space and Time, Anna C. Nobre, Gustavo Rohenkohl, and Mark G. Stokes
13. Microstructural Properties of White Matter Tracts Are Linked to the Efficiency of Specific Attention Networks, Bruce D. McCandliss
14. Tracking the Allocation of Attention in Visual Scenes with Steady-State Evoked Potentials, Søren K. Andersen, Matthias M. Müller, and Steven A. Hillyard
III. Neuroscience
15. Using Nonhuman Primates to Study the Micro- and Macro-Dynamics of Neural Mechanisms of Attention, Geoffrey F. Woodman and Charles E. Schroeder
16. Top-Down Control of Attention by Rhythmic Neural Computations, Earl K. Miller and Timothy J. Buschman
17. Neural Mechanisms of Saccade Target Selection: Evidence for a Stage Theory of Attention and Action, Jeffrey D. Schall and Kirk G. Thompson
18. Neural Circuits Controlling Visual Attention, Tirin Moore, Brittany Burrows, Katherine M. Armstrong, Robert J. Schafer, and Mindy H. Chang
19. Attentional Modulation of the Firing Patterns of Hippocampal Neurons, David Clayton Rowland and Clifford George Kentros
IV. Development
20. Resting State Studies on the Development of Control Systems, Damien A. Fair, Nico U.F. Dosenbach, Steven E. Petersen, and Bradley L. Schlaggar
21. Development of Error Detection, Andrea Berger, Chananel Buchman, and Tamar Green-Bleier
22. Attentional Control and Emotion Regulation in Early Development, Martha Ann Bell and Susan D. Calkins
23. Development of Temperament and Attention: Behavioral Genetic Approaches, Kirby Deater-Deckard and Zhe Wang
V. Deficits and Interventions
24. Typical and Atypical Development of Attention, B J. Casey and Megan Riddle
25. “Abstraction of Mind”: Attention in Autism, Jeanne Townsend, Brandon Keehn, and Marissa Westerfield
26. Cingulate–Frontal–Parietal Function in Health and Disease, George Bush
27. Understanding Attention through Evolutionary and Epidemiological Genetics: Attention-Deficit/Hyperactivity Disorder as an Extreme Phenotypic Variant, Mauricio Arcos-Burgos and Maximilian Muenke
28. Action Control in Times of Conflict: Analysis of Reaction Time Distributions in Healthy and Clinical Populations, K. Richard Ridderinkhof, Wery P. M. van den Wildenberg, and Scott A. Wylie
29. Early Selective Attention Abnormalities in Psychopathy: Implications for Self-Regulation, Joseph P. Newman and Arielle R. Baskin-Sommers
30. Attentional Impairments in Children with Chromosome 22q11.2 Deletion Syndrome, Tony J. Simon and Steven J. Luck
31. Training the Brain: Nonpharmacological Approaches to Stimulating Cognitive Plasticity, Redmond G. O’Connell and Ian H. Robertson
32. Training of Working Memory and Attention, Torkel Klingberg
Interviews
Researchers, students, and clinicians in neuroscience, neuropsychology, psychiatry, neurology and neurosurgery, and clinical and cognitive psychology. May serve as a text in graduate-level seminars in cognitive neuroscience.