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CompletedNSF NCS (NeurIoT)2021–2024

NCS: Memory via Real-world Integration of Brain & IoT Perception (NSF 2435642)

NSF NCS established the NeurIoT foundation for synchronizing brain recordings with real-world multimodal sensing to study memory-relevant behavior and support context-aware neurotechnology research.

Agency
NSF NCS (NeurIoT)
Status
Completed
Themes
1
NCS: Memory via Real-world Integration of Brain & IoT Perception

Overview

Project narrative

The NCS project explored how IoT sensing and neural measurements can be integrated to model human cognitive state in realistic environments, with emphasis on episodic memory and event boundaries.

It introduced a multi-task research framework spanning sensing/synchronization, semantic alignment of neural and environmental signals, and early concepts for memory-related stimulation workflows.

This project served as a predecessor platform for subsequent NIH efforts focused on scalable real-world data capture and translational memory applications.

The project also seeded Trustworthy Mixed Reality research on SLAM reliability and interpretable feature adaptation for human-centered sensing.

Capabilities

What the project enables

Portable sensor and neural-data synchronization workflows in real-world settings

Semantic alignment strategies connecting perceived context with neural dynamics

Prototype-ready design concepts for context-aware memory experimentation

Open and reproducible project artifacts for follow-on research programs

Foundational XR tracking reliability analysis methods for real-world cognitive studies

Use Cases

Where this work applies

Building real-world cognitive-state datasets that combine brain and IoT signals

Analyzing memory-related neural responses under rich environmental context

Seeding follow-on work on adaptive memory support and neurotechnology safety

Developing trustworthy mixed-reality data pipelines that bridge IoT context and behavior

Figures

Project artifacts

NeurIoT system architecture for synchronized sensing and neural recording.
NeurIoT system architecture for synchronized sensing and neural recording.
In-the-wild participant instrumentation used during early NeurIoT deployments.
In-the-wild participant instrumentation used during early NeurIoT deployments.
High-level neurosymbolic visual odometry pipeline studied for reliable mixed reality operation.
High-level neurosymbolic visual odometry pipeline studied for reliable mixed reality operation.
Taxonomy of algorithmic, environmental, and locomotion challenges in human-centered XR tracking.
Taxonomy of algorithmic, environmental, and locomotion challenges in human-centered XR tracking.

Publications

Selected papers

Related Work

Nearby projects

NIH / 2024–2029

Neuroscience-in-the-Wild: Memory & Sensor Fusion

This project integrates smartphone-based experiential sensing, wearables, and intracranial neural recordings to study autobiographical memory formation during real-world behavior and to inform future memory-enhancing neuromodulation.