Todd S. Braver - US grants

This proposal tests specific predictions regarding the relationship between cognitive and neurobiological impairments observed in healthy aging. These predictions were derived from a neural-network computational model which postulates specific functional roles for the dopamine (DA) neurotransmitter system and dorsolateral prefrontal cortex (DL-PFC) in cognitive processes related to the control of thoughts and behavior. A growing literature has suggested that healthy aging is associated with disturbances in both DA and PFC function, and with impairments in tasks requiring cognitive control. However, despite accumulating evidence about these age-related cognitive and neurobiological changes, there is still understanding of whether or how they are associated. Based on work with our computational model, we propose three hypotheses regarding the mechanisms by which the functional interaction of the DA system in DL-PFC influences specific cognitive processes, and how these may breakdown in healthy aging. First, we suggest that DL-PFC subserves the representation and maintenance of task-relevant context. Second, we suggest that the DA system serves to regulate the flow of information into DL-PFC. Third, we suggest that as a result of DA disturbances in DL-PFC among older adults, context information represented in DL-PFC cannot be actively sustained and will instead decay over time. These hypotheses lead to specific, detailed, and often counter-intuitive predictions regarding age-related changes in both brain activity and behavior during performance of cognitive control tasks that rely on the representation and maintenance of context. We propose to investigate these hypotheses in both a behavioral and functional neuroimaging study (using functional magnetic resonance imaging, or fMRI, methods) comparing healthy older and younger adults. Both studies will use a single cognitive task designed and validated to be sensitive to the processing of context. To our knowledge, the studies we propose represent the first use of computational models of cognition to make explicit and detailed predictions regarding regional brain activation and behavioral performance in healthy aging. As such, this project promises to generate valuable new empirical data regarding the neurobiological underpinnings of age-related cognitive decline, to significantly advance our theoretical understanding of this process, and to establish the groundwork for developing powerful new behavioral and neuroimaging measures that may eventually have direct clinical applicability.

Abstract

BCS-0001908
PI: Braver

This research will use behavioral, brain imaging, and computational modelling techniques to investigate the neural bases and mechanisms of human cognitive control. A powerful method for elucidating cognitive mechanisms is to tax cognitive processing to the point at which some aspect of its underlying structure is revealed. Here, we use normal emotion as a methodological technique for challenging cognitive processing. This approach might be especially informative because normal emotion has specific influences on self-regulation and control.

In behavioral and brain imaging studies, we will test predictions of the
computational model under two related but distinct types of emotional challenge: induced emotional states, and the delivery of unexpected rewards. Human participants will perform various cognitive tasks either while in emotional states or while receiving unexpected rewards. Using functional magnetic resonance imaging (fMRI), we will identify areas of the brain that are not only critical for cognitive control but also are sensitive to modulation by emotion and reward. We will then perform computer simulations to test whether the model can capture detailed aspects of the behavioral and brain imaging data.

These studies will further scientific knowledge by both testing and extending an existing theory of cognitive control. In particular, it will help refine how our under-standing of specific brain regions (i.e., the prefrontal cortex) might mediate cognitive control, and how normal emotion influences those control systems. This work could enhance our understanding of human performance, and lead to improved techniques for optimizing performance using emotion. In addition, these studies could provide another step toward a detailed understanding of the normal interactions between cognition and emotion. This could be of practical value in helping to understand mental disorders such as depression, anxiety, and drug addiction.

[unreadable] DESCRIPTION (provided by applicant): This proposal explores the neural and psychological mechanisms that underlie economic decision-making behavior in older adults. Economic decisions are a critical component of everyday life, and may have special relevance for older adults (e.g., saving vs. spending decisions, retirement planning, health care choices, and medication compliance). Basic research in the cognitive neuroscience of aging has suggested that older adults show declines in the ability to control thoughts and actions based on internal goals, and that this may stem from age-related changes in the function of the lateral prefrontal cortex and mid-brain dopamine system. Yet currently, almost nothing is known about whether and how these cognitive and neural changes associated with advancing age impact economic-related behaviors. [unreadable] [unreadable] The current proposal provides a highly novel perspective on this issue, by leveraging and integrating theoretical developments in three areas: a) the cognitive neuroscience of aging; c) neural mechanisms of cognitive control; and c) behavioral economics research. Through the use of novel experimental paradigms and state-of-the-art neuroimaging methods, the proposed studies will systematically examine core components of economic decision-making that may be particularly impacted by age-related changes in cognitive control, including risk-taking and uncertainty, inter- temporal choice, exploration, affective framing effects, and individual difference influences. The findings of these studies promise to provide critical new data regarding economic choice behavior in older adults, and the relationship of such behavior to age-related changes in the neural substrates of cognitive control. [unreadable] [unreadable] This project has high relevance for public health by providing critical information regarding how older adults make economic decisions (e.g., saving vs. spending money) in terms of age-related changes in brain function. An improved understanding of the brain basis of age-related changes in economic decision-making will be critical for determining why and how older adults might be impaired in some decision-related behaviors but not others, and in developing appropriate corrective interventions to address such impairments. [unreadable] [unreadable] [unreadable] [unreadable] [unreadable]

ABSTRACT This project focuses on exploring the psychological and neural mechanisms that underlie the interaction of motivation and cognitive control, and how this interaction might be influenced by different dimensions of individual difference. Motivation may provide a basic mechanism of cognitive self-regulation. The primary hypothesis tested in this project is that cognitive and behavioral goals are activated, prioritized, and maintained according to their motivational value to the individual. Moreover, different affective and motivational states may have distinct influences on cognitive processing and cognitive control. The current proposal provides an innovative and theoretically-driven cognitive neuroscience approach towards this question, by examining three different affective/motivational dimensions - other-oriented (social) vs. self-oriented, intrinsic vs. extrinsic, and positive affect vs. reward-based motivation - in terms of their influence on the neural mechanisms of cognitive control. Specifically, in a large-sample neuroimaging study we will explore how differences between these motivational states impact behavior and brain activity dynamics during performance of a cognitive task with high control demands (cued task-switching). A key component of the project will be to comprehensively and rigorously examine the moderating influence of individual differences in theoretically relevant motivational traits. Clear-cut and theoretically-guided testable hypotheses are provided regarding how each motivational dimension might impact components of cognitive control, and the associated neural circuitry. This project promises to have substantial significance by filling an important gap in knowledge regarding the role of motivation as a basic mechanism of cognitive self-regulation. As such, this work may have long-term impact on educational and workplace practices, and treatments for debilitating clinical disorders, such as schizophrenia, depression, ADHD, and substance abuse.

PROJECT DESCRIPTION (ABSTRACT) This proposal explores the neural and psychological mechanisms that underlie economic decision-making behavior in older adults. Economic decisions are a critical component of everyday life, and may have special relevance for older adults (e.g., saving vs. spending decisions, retirement planning, health care choices, and medication compliance). Basic research in the cognitive neuroscience of aging has suggested that older adults show declines in the ability to control thoughts and actions based on internal goals, and that this may stem from age-related changes in the function of the lateral prefrontal cortex and mid-brain dopamine system. Yet currently, very little is known about whether and how these cognitive and neural changes associated with advancing age impact economic-related behaviors. The current proposal provides a highly novel perspective on this issue, by leveraging and integrating theoretical frameworks from three areas: a) the cognitive neuroscience of aging; b) neural mechanisms of cognitive control; and c) behavioral economics research. A unifying theme of the proposed studies is the use of the discounting framework. This framework provides a means of formally modeling how various cost factors, such as the delay, probability, or cognitive effort, are combined with the size of the outcome to determine its (discounted) subjective value, and whether choices involving gains and losses differ in this regard. The proposal extends our previous collaborative efforts using this framework to a series of studies that integrate behavioral, mathematical modeling, and neuroimaging methods. A key feature of these studies is the use of innovative experimental paradigms that enable discovery of fundamental components of economic decision-making, as well as determination of how cognitive control interacts with affective and motivational factors, and how these components and their interaction are affected by advancing age. The findings of these studies promise to provide critical new data regarding economic choice behavior in older adults, which might be used to develop interventions that can promote adaptive decision-making throughout the life course.

Project Summary (Abstract) This proposal explores the neural and psychological mechanisms that underlie older adult decision-making. Basic research in the cognitive neuroscience of aging has suggested that older adults show declines in the ability to control thoughts and actions based on internal goals, and that this may stem from age-related changes in the function of the lateral prefrontal cortex and mid-brain dopamine system. Yet currently, very little is known about whether and how these cognitive and neural changes associated with advancing age impact different forms of decision-making. The current proposal provides a novel perspective on this issue, by focusing on interactions between motivation and cognitive control. Decisions that are both high in motivational value but also heavy in cognitive demand are likely to be some of the most salient and impactful in every day life for older adults, including health choices (what to eat and drink; whether and how often to exercise; medications, treatments, and drugs to take), social interactions (who to approach and who to avoid, whether to pursue solitary or group activities), and financial decisions (what to purchase, how much to save, whether to gamble or purchase insurance) Yet currently almost nothing is known about how motivation ? cognitive control interactions change with advancing age or their impact on decision-making. The proposal relies on a recent theoretical framework, value-based cognitive control (VBCC), which postulates that motivational value serves to counteract the subjective and computational costs of engaging in cognitive control. A key implication of the VBCC framework is that age-related changes in decision-making should be most prominent under conditions that make the highest demands on motivation-cognition integration functions. The project directly tests this hypothesis, utilizing innovative and powerful new experimental paradigms and state- of-the-art neuroimaging methods to provide insight into the core neural mechanisms underlying age-related changes in decision-making. In Aim 1 the focus is on age differences in the control mechanisms that enable motivational integration, using a novel task in which the subjective motivational value of cognitive task performance varies as a function of both the monetary and liquid incentives available. In Aim 2, the focus is on age differences in the control mechanisms that enable delay-of-gratification, using a new task probing self-control in terms of repeated decisions to wait for a delayed reward, while foregoing an immediately available one. In both Aims, the central prediction is that older adults will show a reduced ability to successfully modulate cognitive control processes in lateral prefrontal cortex when this depends on integrating neural signals of current motivational value (arising from dopaminergic circuits involve the ventromedial prefrontal cortex and ventral striatum). This project will provide a necessary basic science foundation that has the potential to translate into a more comprehensive understanding of the key factors that impact older adult decision-making behaviors, and how to address and compensate for these when necessary.

NSF 1835209
NCS-FO: Modeling Individual Differences in Cognitive Control as Variation in Neural Activation Trajectories
Abstract:
This award supports fundamental research to examine how activity within brain networks allows humans to adapt their behavior in order to achieve goals and complete mental tasks. Such processes within the brain, referred to as cognitive control, are thought to differentiate individuals in terms of mental abilities that are critical for successful navigation in activities of daily life, such as planning, problem solving and reasoning. Current brain imaging methods enable examination of the activity and interactions among brain networks as individuals perform various tasks, thus providing a window into the mechanisms of cognitive control. However, research efforts to date have mostly used imaging data to generate snapshots of brain activity that are averaged across groups of individuals and many different events while performing a task. In this research program, the investigators develop a new form of analysis to characterize the moment-to-moment fluctuations in brain activity, within each individual, as they transition from rest to cognitively demanding task conditions. In particular, efforts will be directed towards the development of a computational model that can predict how brain networks coordinate activity over seconds-level timescales in response to changing task conditions. A key aspect of the effort will be to develop unique models for each individual, drawing from a large database of previously obtained neuroimaging data. In these data, individuals perform a range of tasks requiring different cognitive control strategies, some proactive (sustained) versus others reactive (transient). Thus, application of the model will reveal how the brains of these individuals differentially respond to various types of cognitive demand. The development of this model also provides a unique opportunity for education and outreach; specific efforts will be directed toward the development of a software platform through which members of the public can work with demonstration models to probe and learn about how different patterns of brain activity relate to cognitive function.

Functional neuroimaging has allowed for detailed spatial and temporal characterizations of brain network activation in an effort to elucidate the neural underpinnings of cognitive control. However, such analyses usually rely on static snapshots of neural activation patterns in individual brain regions and/or correlational indices of inter-regional co-activation (i.e., functional connectivity). Further progress in understanding distinctions between cognitive states and cognitive control strategies requires more precise descriptions of the brain dynamics that govern how patterns of neural activity (trajectories) evolve across time. Leveraging recent advancements in optimization theory that allow for reliable high-dimensional parameter estimation, this award will support the validation and parameterization of single-subject dynamical models using high-resolution, long-duration resting-state fMRI data from the Human Connectome Project, which contains data from over 1000 individuals. Subsequent model analysis will characterize individual differences in terms of brain network dynamics, focusing on quantitative metrics of the ruggedness of the attractor landscape (which indicates the diversity of achievable trajectories) and the consequent energetic costs incurred by shifting between cognitive states and strategies. Hypothesis testing will be conducted with a unique follow-up dataset, consisting of a subset of HCP participants and monozygotic (identical) twins (over 100 in total) tracked in multiple neuroimaging sessions, under conditions that systematically manipulate cognitive control strategies.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Over the past 30 years, the scope of Systems Neuroscience has expanded enormously. Functional brain imaging has provided the opportunity to study the neural mechanisms of complex cognitive functions in humans. Concurrently, powerful techniques such as optogenetics have made it possible to dissect neural circuits with unprecedented resolution. In parallel, computational approaches such as deep networks and Bayesian models are increasingly central to the field as a whole, putting a premium on advanced quantitative skills and literacy. Clearly Systems Neuroscience is now a trans-disciplinary field, integrating theoretical frameworks and techniques from molecular biology, neurophysiology, cognitive science, ethology, computer science, statistics, and more. In the face of this remarkable expansion, PhD programs face three challenges. First, although the body of knowledge relevant to Systems Neuroscience has increased in breadth and depth, students also face increased pressure to conduct research, publish, and get independent funding early in their career. Second, systems-level research is conducted in multiple departments and PhD programs. At Washington University, these include the PhD programs in Neuroscience, Psychology, and Biomedical Engineering. Yet, students coming from different disciplines often do not speak each other?s language. Third, a successful career in science requires a broad portfolio of professional skills ? writing papers and grant proposals, collaborating with colleagues with different scientific backgrounds, presenting results in scientific venues and to wider audiences, navigating the academic job market ? that exceed the normal coursework. The Cognitive, Computational and Systems Neuroscience (CCSN) pathway was developed in response to these challenges. CCSN is an elite pathway available for graduate students in years 3-4, with eligibility from multiple PhD programs relevant to Systems Neuroscience broadly defined. The emphasis of CCSN is on trans- disciplinary training and professional skills development. To access the pathway, students must complete (in years 1-2), three pre-requisite and foundational courses on systems neuroscience, cognitive science and animal behavior, and computational neuroscience. In year 3, CCSN students take two additional courses ? one providing foundational knowledge and hands-on training with advanced quantitative methods and data-science tools, and the other allowing them to develop a trans-disciplinary grant proposal ? which often becomes an actual NRSA application ? shaped by peer, instructor, and committee feedback. In year 4 (and throughout the pathway), CCSN students take part in multiple Career Development activities, including mentoring junior students, organizing scientific events, interacting with external speakers, participating in informal dinners with CCSN faculty, and taking part in community outreach. The CCSN pathway has existed for ~15 years and has a demonstrated history of remarkable success. Here we request funds for 5 fellowships. Contingent on the success of this application, Washington University will provide matching funds for an additional 5 slots.