# Cognition, Large- And Small-Scale (CLASS): A cognitive neuroscience battery for assessing disruptions in core cognitive processes across multiple rural drug-abuse sub-populations

> **NIH NIH P20** · UNIVERSITY OF NEBRASKA LINCOLN · 2020 · $379,275

## Abstract

PROJECT ABSTRACT
Drug addiction is a significant problem in rural communities, yet rural drug users are understudied compared to
urban populations. In addition, most studies of the human brain in drug abuse and addiction have focused on
the direct effects of drug use or on systems involved with the reward, craving, and impulsivity associated with
it. However, humans also rely on general cognitive mechanisms (such as attention and memory) to perform
daily activities that affect their quality of life (e.g., performing their jobs or planning their health behaviors).
Disturbances in the functions of these cognitive mechanisms can have widespread, significant consequences.
Previous studies have shown that drug abusers do experience deficits in these core cognitive functions, but
relatively little is known about the exact extent or nature of this dysfunction or its potential to predict life and
health outcomes for drug users. This project seeks to collect neuroimaging and behavioral data from a sample
of rural cocaine, methamphetamine, and/or opioid users (plus a sample of non-drug-using controls) to isolate
specific breakdowns in core brain and cognitive functions (Aim 1) and develop models using those breakdowns
to predict individual differences in quality of life and health (Aim 2). Functional magnetic resonance imaging
(fMRI) and electroencephalography (EEG) will be used to measure brain function of drug users and control
subjects as they perform a variety of tasks employing these core cognitive abilities in varying combinations and
levels of complexity. The research team will also obtain measurements of brain structure and use surveys to
assess a large number of variables relating to drug use patterns and other life/health outcomes (e.g., job
success, quality of personal relationships, and physical health outside of drug use). Using these data, the
project will isolate the specific neural and cognitive variables that best predict differences in quality of life and
health at the time of data collection. This project will use state-of-the-art technological and statistical methods
to characterize neural and cognitive dysfunction in drug abusers in more detail than previous studies, which will
lead to greater predictive power. The project will also result in preliminary data on longitudinal follow-ups of
life/health outcomes; future funding proposals will focus on using neurocognitive data to predict outcomes for
months or years after primary data collection. The ability to predict life trajectories is particularly important for
rural drug users, who receive less health care and social services than urban users and thus are more
susceptible to becoming lost to the systems and services that could otherwise help them. This project will
ultimately lead to better characterization of the impact of drug use on rural society, improved prediction of
which rural drug users are most likely to respond to interventions, and better identification of users who are
...

## Key facts

- **NIH application ID:** 9908119
- **Project number:** 5P20GM130461-02
- **Recipient organization:** UNIVERSITY OF NEBRASKA LINCOLN
- **Principal Investigator:** Matthew Robert Johnson
- **Activity code:** P20 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $379,275
- **Award type:** 5
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9908119

## Citation

> US National Institutes of Health, RePORTER application 9908119, Cognition, Large- And Small-Scale (CLASS): A cognitive neuroscience battery for assessing disruptions in core cognitive processes across multiple rural drug-abuse sub-populations (5P20GM130461-02). Retrieved via AI Analytics 2026-06-11 from https://api.ai-analytics.org/grant/nih/9908119. Licensed CC0.

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