Marc N. Coutanche, Ph.D. - US grants

DESCRIPTION (provided by applicant): This project examines reward- and memory-driven attention through an investigation of the brain networks underlying these influences. Recent investigations have shown that prior reward, and memory, can both influence attention. These influences, however, are not well accounted for by a classic top-down versus bottom-up framework. There is consequently current uncertainty over whether these influences are best considered top-down, bottom-up, or their own separate class. This work will seek to bring a neurobiological perspective to this debate, using functional magnetic resonance imaging and novel analysis methods. This work will employ informational connectivity; a method developed by the applicant that combines the sensitivity of multi-voxel pattern analysis with the network approach of connectivity, making it ideal for investigating the dynamic regional interactions that underlie attention. The proposed studies will seek to identify common fluctuations in multivariate information between frontoparietal regions, reward and memory networks, and visual cortex, as participants engage in reward-driven, memory-driven, top-down and bottom-up attention. The first aim of this proposal is to reveal the commonalities and differences in how reward-driven and memory- driven attention results from the brain's connectivity patterns. The second aim is to better understand how these influences relate to classic top-down and bottom-up attention, and how reward and memory information is integrated with attentional processing. The final aim is to examine how the brain's informational networks breakdown during attentional distraction, in order to identify the regional connections that are particularly important to overcoming exogenous attentional capture. This research will help improve our understanding of how reward and memory influence the human attentional system.

This project, conducted by a team of researchers at the University of Pittsburgh, will address the need to improve math abilities in American children and adults. According to the 2015 National Assessment of Educational Progress, only 40% of 4th graders, and 33% of 8th graders score at, or above, proficiency level in math, and only about 30% of US adults can complete basic mathematical processes in real-world scenarios such as looking at a thermometer and figuring out the temperature. Such poor math achievement outcomes impose significant burdens, such as in securing employment, on individuals who enter adulthood without achieving basic proficiency, and challenges the capacity of the US to remain competitive in a global economy that is strongly driven by the intellectual capital of its citizens. This project will investigate a foundational skill that underlies math achievement: the ability to recognize visual number symbols by connecting them with the quantities they represent. Using functional magnetic resonance imaging (fMRI) and behavioral measures, the project team will characterize the neural constituents of number knowledge and will test for pathways within this number network that contribute to this "symbolic integration" and math ability. Finally, by studying adults and 8-year-old children, they will test whether the neural substrates of symbolic integration change with age, and if so, whether these changes correspond to shifts in the behavioral profile of symbolic integration and individual difference in math ability. Overall, by focusing on the widely used, but poorly understood, construct of symbolic integration, the proposed work will have broad impact on theories of math ability that make assumptions about these underlying processes and will inform future studies examining math learning trajectories and remediation strategies for struggling math learners. This project is funded by Integrative Strategies for Understanding Neural and Cognitive Systems (NSF-NCS), a multidisciplinary program jointly supported by the Directorates for Computer and Information Science and Engineering (CISE), Education and Human Resources (EHR), Engineering (ENG), and Social, Behavioral, and Economic Sciences (SBE).


The overarching objective of the project is to investigate whether symbolic integration is foundational to math ability in adults and children. The project leverages the larger and more established literature on word recognition to develop and test a symbolic integration hypothesis of number processing. This model posits that formal math ability rests in part upon the integration of visual symbols (i.e., Arabic numerals) with the magnitudes they represent, via both direct (visual-semantic) and indirect (visual-verbal, visual-manual) pathways. An innovative combination of neurobehavioral measures will be used to test the model, through an individual differences study involving 100 adults and 125 8-year-old children. The project team will develop a novel neuroimaging protocol and will use cutting-edge multivariate methods to efficiently and broadly identify and characterize the neural constituents of a number processing network. A likely set of regions includes those involved in visual (fusiform gyrus), verbal (angular gyrus), manual (precental gyrus), and semantic (inferior parietal cortex) coding of number. In addition, resting state data will be acquired from each participant, and used to extract a metric of connectivity between identified visual, verbal, manual, and semantic constituents of number knowledge. A pair of behavioral tasks will measure the associative strength between visual and semantic codes for number (i.e., symbolic integration) in each participant. Using general linear models (GLM), the investigators will then test the prediction that both direct (visual-semantic) and mediated (visual-verbal-semantic; visual-manual-semantic) pathways significantly contribute to symbolic integration skill. Finally, standardized measures of math ability will be obtained from each participant. A GLM will be used to test for a predicted positive relation between individual differences in symbolic integration and math ability. Overall, the work will have a broad impact on theories of math ability and will inform future studies of math learning and intervention.

Cigarette craving is a key feature of smoking, which is the leading preventable cause of death. While smokers often recognize this danger, during moments of temptation the appeal of smoking rises and the habit persists. Unfortunately, research has struggled to develop treatments for craving relief. One approach showing promise is the strategic use of olfactory cues (OCs) to reduce craving. Two studies from the PI?s lab indicate that pleasant OCs reduce cigarette craving. Others have replicated this effect for food craving. Yet little is known about the nature of this urge-reducing effect, its underlying mechanisms, and individual differences that moderate its benefit. This application addresses FOA PAR 18-323: Fundamental Science Research on Mind and Body Approaches by testing this use of a natural product (OCs) to control craving and by testing the ?neurocognitive and behavioral mechanisms underlying? OC-induced craving relief (an FOA objective). Integrating theory and research derived from three disciplines rarely applied to smoking (olfaction, emotion, cognition), the project will test the impact of pleasant OCs on craving. Also pertinent to the FOA, this project will use innovative nonverbal measures of emotion and advanced multi-voxel pattern analyses (MVPA) (along with traditional fMRI analyses) to evaluate precise, theory-driven, underlying mechanisms (working memory, attentional engagement, delay discounting, response inhibition) for how OCs attenuate craving. The project will test why certain smokers may have trouble managing their craving and why OCs may be especially useful for a subset of smokers. Abstinent daily and nondaily smokers (n=250) will attend a multi-session experiment. They will rate a set of OCs on several dimensions, including pleasantness, mood, and related memories. They next perform a series of cognitive tasks during an fMRI session. They will receive in vivo smoking cues, which together with smoking abstinence, elicits robust urges. Next they will sniff an OC (one they had rated earlier as either pleasant or neutral) while urge and mood are assessed. MVPA will be used to generate ?neural fingerprints? for cognitive and affective processes in each smoker to probe the mechanisms underlying their own OC-induced urge reduction, and to inform matching of subjects to OCs. Subjects also will attend a behavioral session using a novel set of craving-related responses, including an urge pressure dynamometer and the Facial Action Coding System, to identify those most sensitive to urge relief, and to generate behavioral proxies for patterns of fMRI activity. As a secondary aim, we will test the effects of OCs on urge and smoking in the field. This translational study, drawing on fMRI and behavioral data regarding the unique power of OCs to alter affective states, will test key mechanisms of urge relief related to neurobehavioral addiction models. This interdisciplinary research also should stimulate future research testing the impact of OCs, alone or with other interventions (e.g., nicotine patches, cognitive therapies) on smoking cessation. Regardless of outcome, this research will provide important data on the interaction of emotional and cognitive processes during craving.