# Post-trial obligations in neurotechnology

> **NIH NIH RF1** · UNIVERSITY OF WASHINGTON · 2020 · $155,458

## Abstract

Project Summary
The proposed supplement will study how stakeholders of implanted neural devices approach the
issue of post-trial obligations towards participants and use this data to inform an expert consensus
document to guide the field. At present, there is no clear ethical, legal, or policy guidance
regarding what researchers should provide participants after a study ends. Participants face
uncertainty about continued maintenance of their device or how to pay for removal if the system
is not effective. Using discourse analysis, we will examine the issue of post-trial obligations in
policy documents, academic literature, and interview data from diverse stakeholders of neural
interface research – end-users, researchers, industry representatives, funders, and regulators.
These interviews will attempt to understand what stakeholders feel is owed to research
participants after a trial concludes, the challenges in providing such care, and the impact on the
research enterprise for making such commitments. The empirical data will then be presented at
a consensus building meeting that brings together stakeholders to collectively deliberate about
post-trial topics. The aim of the workshop is to create consistent guidance for developers and
funders of implanted neural devices.

## Key facts

- **NIH application ID:** 10129798
- **Project number:** 3RF1MH117800-01S3
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Sara Goering
- **Activity code:** RF1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $155,458
- **Award type:** 3
- **Project period:** 2018-09-22 → 2022-09-20

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10129798

## Citation

> US National Institutes of Health, RePORTER application 10129798, Post-trial obligations in neurotechnology (3RF1MH117800-01S3). Retrieved via AI Analytics 2026-06-14 from https://api.ai-analytics.org/grant/nih/10129798. Licensed CC0.

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