# Decision Making on Continuous Scales in Aging and Alzheimers Disease

> **NIH NIH R01** · OHIO STATE UNIVERSITY · 2020 · $495,264

## Abstract

Project Summary/Abstract
 The goal of the project is to develop a model that explains how decisions are made about information that is
continuously distributed across space, with decisions made on continuous scales. The model will provide a
unified explanation of the full range of decision-making data, including accuracy, the distributions of response
times for correct and incorrect responses, how they change with manipulations of independent variables, and
how they differ among individuals and groups of individuals. The totality of these data will place severe
constraints on the development of the model and its success. The tasks used to test the model will ask
participants to make simple decisions quickly; for example, point to the area on a circle that is the brightest.
Brightness is a continuous scale and responses are made on a continuous scale (the circle). Large,
comprehensive bodies of data will be collected for decision-making in perception, long-term memory, working
memory, and numeracy. Statistical properties of the model will be examined and the numbers of observations
needed will be determined for experiments with clinical patients, children, and other populations for whom the
time for testing must be short.
 Four populations of adults will be studied: young adults, adults with Mild Cognitive Impairment (MCI), adults
with early Alzheimer's Disease (AD), and older adults who have no cognitive impairments. The aim will be to
understand how normal aging affects individual components of processing in continuous decision-making and
how MCI and early AD affect the components. Almost no research has been conducted with AD and MCI patients
that models the time course of decision-making and no research has been done for decisions made on
continuous response scales about continuously distributed information. It is not known if the components of
decision-making are the same for MCI and AD patients as for unimpaired older adults and it is not known how
independent variables (e.g., the difficulty of a task) affect performance for MCI and AD patients. It is also not
known whether a modeling approach can uncover preserved skills not discernible from accuracy and RT data
alone.

## Key facts

- **NIH application ID:** 9867967
- **Project number:** 1R01AG057841-01A1
- **Recipient organization:** OHIO STATE UNIVERSITY
- **Principal Investigator:** GAIL A MCKOON
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $495,264
- **Award type:** 1
- **Project period:** 2020-02-01 → 2024-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9867967

## Citation

> US National Institutes of Health, RePORTER application 9867967, Decision Making on Continuous Scales in Aging and Alzheimers Disease (1R01AG057841-01A1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9867967. Licensed CC0.

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