Gordon D. Logan - US grants

Executive control is a fundamental issue in basic research in cognitive science and cognitive neuroscience and in several areas of applied research, including human factors and ergonomics. Executive control is the process by which the mind controls itself, programming itself to perform specific tasks, monitoring performance for speed and accuracy, adjusting strategies, and switching between tasks. This research will extend Logan's theory of executive control to address a broad range of phenomena in the burgeoning literature on switching between tasks. Like many theories of executive control, Logan's theory posits an executive process that programs a subordinate task to do specific tasks. It interprets task switching as re-programming: The executive process develops a new program for the upcoming task and transmits it to the subordinate, much like a programmer installs new software in a computer. Logan's theory goes beyond previous theories of executive control in specifying the subordinate process explicitly and specifically. It adopts a powerful theory of attention and categorization as the theory of the subordinate process, and it describes executive control in terms of programming the subordinate theory to perform tasks. This allows precise, quantitative predictions of performance in a broad range of situations, including those in which people switch from one task to another. The research will consist of three projects. The first will develop quantitative measures of the time required to switch between tasks. In Logan's theory, this switching time represents the time required for the executive to formulate a new program and install it in the subordinate process. The second project will investigate the role of short-term working memory in executive control. It will focus on a new experimental procedure in which subjects are given names of tasks to be performed and then a list of stimuli to perform them on, much like a person remembers a list of errands to be run on the way home from work or a list of chores to be done on a Saturday afternoon. The third project will examine the role of long-term memory in task switching. It will focus on competition and interference produced by recent experience with other tasks performed on the same stimuli, much like switching from workplace roles to social roles in having lunch with the boss. This research will have direct implications for basic research on executive control. It will also have implications for human factors research and job design. With increased advances in technology, people in the workplace are often required to switch between tasks in the same environment; many of us have several windows open at once on our computer screens. Understanding the costs of switching between tasks and learning what can be done to reduce them will allow better design of software, tasks, and jobs.

Stochastic Models of Executive Control in Monkeys and Humans

Abstract

With National Science Foundation support, Drs. Logan, Palmeri, and Schall will conduct a three-year investigation of the executive control processes that underlie flexible responding in monkeys and humans. It is the hallmark of primate intelligence to be able to respond flexibly, focusing on different aspects of the same situation to produce arbitrary responses that are appropriate to current goals. The goal of this project is to specify executive processes computationally and neurally, focusing on the control of attention, categorization, and response preparation. To accomplish this goal, monkeys and humans will perform tasks that require them to make saccadic eye movements toward or away from targets that appear in displays of distractors. Experimental variables will be manipulated to selectively influence attention to the targets, categorization of targets and distractors, and preparation of eye movement responses. The timing and accuracy of eye movements will be recorded in both humans and monkeys performing the task, and the activity of ensembles of neurons in the frontal lobes of monkeys will be recorded while they are performing the task. The overt eye movement behavior of humans and monkeys and the neural activity of monkeys will be described in terms of a mathematically precise computational theory with three distinct components, as follows. (1) An attention component that selects behaviorally-relevant targets from a field of distractors; (2) a categorization component that selects goal-relevant interpretations of target stimuli; and (3) a response preparation component that selects responses necessary to accomplish the goals. The theory provides a common language that makes it possible to relate the overt behavior of humans to the overt behavior of monkeys and to relate the overt behavior of monkeys to the neural activity that underlies it.

The research is significant in three respects. First, it will advance understanding of executive control processes by specifying them concretely in terms of computational and neural processes. Executive control processes are critical in a variety of contexts in the workplace, educational settings, and mental health settings that require people to deal with competing goals and switch between various activities, including the workplace, education, and mental health. The research will have implications for human factors, ergonomics, design of training programs in education and industry, and diagnosis and treatment of mental disorders. Second, the research will advance understanding of neural processes by providing linking propositions that relate single-cell behavior to psychological states of the cognitive processes that the single cells implement. Single-cell behavior makes sense only in the context of the behavior it underlies, and the research will provide that relation. Third, the research will advance understanding of the computations that underlie cognitive processes of attention, categorization, and response preparation. Computational models of these processes are limited by an inability to "open the black box" and observe the inner brain processes that underlie them. Computational models with very different internal processes often predict the same overt behavior. The research will identify cognitive processes with neural behavior, allowing distinctions between these computational models of human and monkey cognition.

How do we control our thoughts and actions? This is a age-old question that penetrates to the heart of studies in mind and behavior. In trying to answer this question, it has been difficult to avoid the invocation of a "homunculus", or controller of the mind that essentially runs the show. The problem with the homunculus is that it sidesteps the fundamental question of control: if the homunculus is controlling the mind, then who or what is controlling the homunculus?

With funding from the National Science Foundation, Dr. Logan and his colleagues will tackle the problem of the homunculus. The aim is to develop theory and experimental procedures that allow us to distinguish between thoughts and actions that are controlled voluntarily by a person (top-down control), from those that are controlled by aspects of the environment (bottom-up control). This research will extend prior work funded by NSF on a formal model of control, in which the environment was the only source of causation for thoughts and actions. The success of this model in accounting for human performance was surprising and informative, because it suggested that top-down control was unnecessary to explain behavior that would otherwise appear volitional. The current research will continue to push this idea in the context of experiments in which participants must voluntarily switch between two tasks. Task switching is known to take a toll on performance, but it is debated whether this toll reflects the workings of voluntary control, or more automatic processes of memory. The proposed experiments and models promise to make substantial headway on this debate.

The "best laid plans of mice and men" often lead to "promised joy" because they provide focus to behavior, allowing individuals to direct actions toward important goals and avoid distraction. With support of the National Science Foundation, Dr. Logan is studying how plans held in memory guide thoughts and actions as individuals work through the steps of a plan. One project focuses on "ad hoc" plans, such as working through a list of chores to be done on a weekend. Successful execution of ad hoc plans requires the maintenance of arbitrary lists of tasks in memory, and the retrieval of appropriate tasks at appropriate times. Experiments in this project are aimed at examining the roles of different kinds of short-term memory (visual, spatial, verbal) in maintaining ad hoc plans, and the different kinds of retrieval processes that operate on it.

A second project is focused on the role of long-term memory in executing familiar as opposed to ad hoc plans, such as making a cup of coffee or driving home from work. All plans are unfamiliar initially, and so must rely on short-term memory. However with practice, the most arbitrary plan can become second nature, recruiting long-term memory to support successful performance. This project is examining the transition from short-term memory to long-term memory and the changes in retrieval processes that accompany it. A third project is focused on the processes that move plan execution from one step to the next, as in remembering the next errand to run when the current one is finished. Together, the three projects are designed to advance our understanding of the control processes that enable individuals to act coherently and flexibly in complex task environments. In doing so, this research is providing basic knowledge that may be of use in designing complex task environments such as the control rooms of ships and power plants, and in training the operators of such environments.

[unreadable] DESCRIPTION (provided by applicant): The proposed research addresses issues in executive control of cognitive processing that are central in basic research in cognitive science, cognitive neuroscience, lifespan development, and individual differences. These issues have direct implications for mental health. Deficits in executive control have been identified in several disorders, including schizophrenia and attention deficit hyperactivity disorder. The main goal of the research is to develop behavioral methods for distinguishing between top-down effects that truly reflect executive control and bottom-up effects that mimic it. This issue is important in designing and interpreting measures of executive control in other areas of research, especially research on deficits in mental disorders. The goal of distinguishing top-down from bottom-up effects will be accomplished by developing and evaluating a priming model that attempts to account for behavior in task-switching experiments purely in terms of bottom-up processes. The footprints of executive control may be seen in the situations in which the priming model fails to provide a complete account. According to the priming model, top-down control may be required for peripheral processes but not for central processes. Perceptual and motor processes and orienting of attention may require executive processing, but memory retrieval does not. This hypothesis leads to two specific aims: (1) To develop the priming model and test its fundamental assumptions in experiments that require switching between central tasks that can be performed by memory retrieval. (2) To push the limits of the priming model by testing it in experiments that require switching perceptual and motor systems and changing the orientation of attention. The first aim will establish the validity of the model, the second will establish its limits and set the stage for a general model of executive control. [unreadable] [unreadable] [unreadable]

Psychologist Gordon Logan at Vanderbilt University will use the deceptively simple task of typing to study "cognitive control," that is, how we plan and execute complex actions. Skilled typists appear to effortlessly use an external script (when copying) or an internally generated plan (when composing) to choose the appropriate movement in the form of a key-press 5-6 times per second. However, in a recent experiment, Logan showed that despite such virtuosity, skilled typists do not even know which hand they are using to depress a key at any given moment. The demonstration is clever and simple: try typing a sentence using only your left hand and typing only those letters normally typed with the left hand. Not surprisingly, this instruction slows people down, but it also renders them greatly less accurate (5-6 times more errors are produced), indicating that skilled typists are simply not aware of what they are doing at the most basic level. Logan's theory of cognitive control as applied to typing assumes that proficient typing is the result of the coordination between two "nested feedback loops." The "outer" loop determines the sequence of words to be typed and the "inner" loop translates the words into the appropriate keystrokes. This explains the paradox that skilled typists are not aware of something as basic as which hand they are using: the inner loop automatically and effortlessly determines the sequence of key presses needed to produce the sequence of words planned by the outer loop, but the outer loop does not know or care how the inner loop performs its separate task. This project will examine three aspects of this double-loop model of cognitive control: awareness (how much does the outer loop know about what the inner loop is doing?), structure (do words or some other level of organization, such as letters or phrases, serve as the interface between the two loops?), and feedback (the outer loop is hypothesized to rely on visual feedback while the inner loop is hypothesized to rely on kinesthetic feedback).

A better understanding of the mechanisms of cognitive control could lead to improvements in the way complex skills are taught and practiced. In the domain of typing, a detailed understanding of the process could have implications for the design of keyboards and other text-input devices. With the proliferation of computers in modern culture, typewriting is an essential skill in the workplace, in schools and universities, and in leisure activities. This project will also have an important impact on the broader literature on cognitive control, which is embroiled in a controversy over hierarchical processing. The outer-loop inner-loop theory provides a new perspective on research on automatic and controlled cognitive processes, which are often regarded as opposites. This project shifts the research focus from whether processes are controlled to how processes are controlled.

DESCRIPTION (provided by applicant): The long-term goal of our research is to understand how computational models of performance of visual tasks like locating and shifting gaze to a target a visual array map onto specific neural processes producing that performance. Elucidating this mapping provides converging constraints for discriminating between competing model architectures and provides functional explanations of neural circuit function. The aims of this proposal test, extend, refine, and integrate two major new computational models of target selection during visual search that we have recently developed. Data will consist of performance of monkeys and human participants searching for a target in a visual array in which target location can change unpredictably supplemented by neurophysiological data from FEF that was collected previously. The models provide quantitative accounts of detailed patterns of correct and error saccade behavior during visual search and also provide explanations for the temporal modulation of neurons in frontal eye field (FEF). Unlike previous models of visual search, ours account for the entire range of correct and error response probabilities and response time distributions during efficient and inefficient search, even when the target changes location unexpectedly. Aim 1 will develop, refine, and extend an INTERACTIVE RACE model of saccade target selection. We will test competing model architectures consisting of multiple stochastic accumulators (GO units) that govern when and where a saccade is made, where the nature of the interactions between GO units and the potential inclusion of a STOP unit for exerting cognitive control is manipulated across model variants. Successful models predict response probabilities and response time distributions in monkeys and humans and neural activity observed previously in monkeys. Aim 2 will test, refine, and extend a GATED ACCUMULATOR model of how visual salience is translated into a saccade command. The visual salience representation provided by FEF neurons will be the input to a neural network of stochastic GO units with alternative architectures that implement competing hypotheses about the role of feed forward, lateral and gating inhibition. Aim 3 will integrate these two models. This integration will be guided by new data from human participants performing visual search tasks in which key variables are manipulated to obtain new measures to test competing architectures. PUBLIC HEALTH RELEVANCE: The models tested and refined through this research plan will provide a firm foundation from which to understand disorders of visual attention, orientation and mobility that are consequences of impaired visual search. Elucidation of the mapping between effective mathematical models of behavior and specific brain processes is necessary for translational research seeking to understand how vision and cognition are impacted by injury, disease, or pharmacological interventions.

? DESCRIPTION (provided by applicant): Theories of attention and learning differ in the roles they prescribe to memory representations. Theories of attention almost universally propose that visual working memory representations determine which objects are the focuses of processing in complex visual scenes. However, models of learning propose that after a handful of trials, the control of visual cognition should shift from being driven by visual working memory to representations in long-term memory. In this project we will bring these ideas from models of learning to bear on the processing of visual information. To test these model predictions in a definitive manner, we will develop methods of measuring electrical brain activity that we can use to track what information is being actively held in visual working memory, simultaneously with independent measures of the representations in visual long-term memory. Our preliminary data indicate that these electrophysiological tools can provide trial-by-trial indices of memory representations controlling visual cognition. Our integrated modeling and neuroscientific approach will allow us to more quickly lay a theoretical foundation for understanding the top-down control of visual processing. This can then be used to understand the nature of deficits in clinical populations and to refine potential treatments.

PROJECT SUMMARY Support is requested to advance an innovative, productive collaboration aimed at linking mind, brain, and behavior using performance, neurophysiological, and electrophysiological measures from monkeys and humans performing visual search and visual decision making tasks. The general goal is to derive the connections from spike trains in monkeys to behavior in humans using computational models that specify mental states mathematically, link them to brain states in particular neurons, and explain how the neural computations produces behavior. Our Gated Accumulator Model (GAM) assumes a stochastic accumulation of evidence to threshold for alternative responses. Model assessment involves quantitatively testing alternative model architectures on predictions of behavioral measures, response probabilities and distributions of correct and error response times, as well as neural measures and how these change with set size and target-distractor discriminability in previously collected data from monkeys performing visual search. While our previously funded research aimed to understand the architecture of evidence accumulation in GAM and the relationship of model accumulators to the observed dynamics of movement-related neurons in FEF, our newly proposed research aims to understand computationally the nature of the evidence that drives that accumulation and its relationship to the measured dynamics of visually-responsive neurons in FEF. Aim 1 compares the quality of salience evidence in lateralized EEG signals and neural discharges from visually-responsive neurons in monkeys performing visual search as input evidence to a network of stochastic accumulators to predict behavior. Aim 2 addresses a major challenge to the neural accumulator framework by determining whether movement neuron dynamics in FEF actually ramp or step. Aim 3 evaluates alternative architectures for an abstract Visual Attention Model (VAM) of the evidence driving accumulation to jointly predict observed behavior and the measured dynamics of visually-responsive neurons. Aim 4 extends VAM to more complex visual tasks involving filtering and selection. The result will be a broader and deeper understanding of the visual processes that select targets and control eye movements. Computational models like VAM and GAM may be at the ?just right? level of abstraction. They capture essential details of the computation in ways that explain neural activity and behavior in single participants, whether monkey or human. These models can be used to understand normal behavior as well as illness, disability, and disease; the best-fitting parameters can characterize individual differences in behavior and provide markers for brain measures. These models can also inform neurological conditions that have a biophysical basis at the level of individual neurons and neural circuits, offering insight into what neurons and circuits compute and how they do it.