# Characterizing the computational and neural basis of deficits in decision making in Alzheimer's disease

> **NIH NIH R21** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2020 · $445,500

## Abstract

Project Abstract
Perceptual decision making relies on cognitive processes such as acquiring and integrating sensory information,
holding information in working memory, incorporating biases, setting a speed-accuracy regime, and planning a
motor response. Many of these processes are affected (compared to age-matched controls) in patients with early
Alzheimer's disease (AD). The neural correlates of these cognitive processes have been identified in persistently
active neurons in frontal and parietal association cortex. We will test the hypothesis that disruption of persistent
activity underlies some of the deficits seen in decision making in AD.
Our first aim is to characterize the ability of patients with AD to incorporate evidence, environmental biases, and
time pressure into their decisions. We will leverage the insights into the neural and computational basis of these
abilities obtained from a well-studied perceptual decision making task. By comparing the performance of patients
in this task against age matched controls, we will gain insights into the nature of the neural computations that
are disrupted in early AD. The experiments also have the potential to uncover new behavioral markers for early
AD.
Our second aim is to mimic the deficits seen in AD in the macaque monkey by manipulating persistent activity
in parietal association cortex while they perform the same perceptual decision task. We will bilaterally express
inhibitory chemogenetic DREADD receptors (Designed Receptors Exclusively Activated by Designer Drugs) in
a subregion of parietal cortex with neurons that show persistent activity in this decision making task. Preliminary
data shows that we can successfully change decision making behavior with this approach. We will build upon
these results by investigating how integrating evidence, incorporating biases, and deciding under time pressure
is affected by this manipulation in the same task as used with AD patients.
Together, our results will provide insights into the computations that underlie decision making, their neural
implementation in the primate brain, and how failure to sustain persistent activity in association cortex can lead
to deficits in decision making in AD. Our long-term goal is to develop behavioral assays for early diagnosis and
to gain insight into fundamental mechanisms that will ultimately lead to new therapeutic targets in AD.

## Key facts

- **NIH application ID:** 9962082
- **Project number:** 1R21AG067108-01
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** MICHAEL NEIL SHADLEN
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $445,500
- **Award type:** 1
- **Project period:** 2020-05-15 → 2023-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9962082

## Citation

> US National Institutes of Health, RePORTER application 9962082, Characterizing the computational and neural basis of deficits in decision making in Alzheimer's disease (1R21AG067108-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9962082. Licensed CC0.

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