# Interacting neural mechanisms of selective visual attention and value-based decision-making

> **NIH NIH K99** · STANFORD UNIVERSITY · 2020 · $113,022

## Abstract

Project Summary / Abstract
This proposal aims to improve brain functions by investigating key, complementary questions about the neural
mechanisms of selective visual attention and value-based decision-making. Selective visual attention and value-
based decision-making are highly interactive. Indeed, patients diagnosed with attention deficit hyperactivity
disorder (ADHD), which affects ~5% of the children in the US, and schizophrenia, which affects ~1.1% of the US
population, suffer not only from severe attentional deficits, but also from profound decision deficits1,2. Selective
visual attention describes the process by which sensory information is filtered in favor of items that are
behaviorally and contextually relevant 3. Value-based decision-making refers to the process by which a subject
chooses from several alternatives based on the subjective values that were assigned to them4. Despite the
importance of these two cognitive functions, however, we are still only at the beginning stages of understanding
the neural circuits that underlie these two cognitive processes. Evidence to date points toward the engagement
of neurons in prefrontal, parietal, and visual cortices in both value-based decision-making and selective visual
attention3,4. However, it is currently debatable to what degree these two cognitive processes are interdependent,
both at the behavioral and the neural circuit level. My long-term goal is a research career focused on investigating
cortical circuits underlying these cognitive processes and applying this knowledge to improve brain functions in
health and disease. Specifically, this proposal aims to investigate the neural circuitry and neural computations
of the above two cognitive functions in non-human primates (NHPs), which are the closest homologs to humans,
using state-of-the-art, high-density multi-electrode array (HDMEA) recordings in prefrontal and visual cortex
(K99). In addition, I will investigate ways to enhance and modulate both cognitive functions using closed-loop
neurofeedback based on HDMEA recordings in prefrontal cortex (K99 and R00), and through pharmaceutical
perturbations of prefrontal dopaminergic activity (R00). The proposal aims at exploring largely uncharted territory
and introduces several innovative experimental approaches and techniques including but not limited to 1) high
density laminar multi-electrode array recordings to investigate large neuronal populations across cortical layers
simultaneously in multiple brain areas, 2) computational approaches for single-trial analyses of large neuronal
populations, 3) new effective and robust neurofeedback protocols, which will be crucial to identify and modulate
signals that are causally linked to specific aspects of behavior and cognition (e.g. selective attention), in order to
effectively and robustly enhance them. The central hypothesis is that the neural mechanisms of selective visual
attention and value-based decision-making are heavily interdependen...

## Key facts

- **NIH application ID:** 9986765
- **Project number:** 5K99EY029759-02
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Xiaomo Chen
- **Activity code:** K99 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $113,022
- **Award type:** 5
- **Project period:** 2019-08-01 → 2021-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9986765

## Citation

> US National Institutes of Health, RePORTER application 9986765, Interacting neural mechanisms of selective visual attention and value-based decision-making (5K99EY029759-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9986765. Licensed CC0.

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