A Neural Hypervector Model of Memory-Driven Spatial Navigation
In this study, we develop an experimental environment for studying human spatial awareness and memory as well as a neuro-computational connectionist model based on hyperdimensional computing, useful for modeling participants’ ability to store and recall stimuli. A qualitative comparison between the proposed model’s confidence, in which it recalls past stimuli, and a participant’s performance in recalling the same past stimuli, was conducted. The results demonstrate that the proposed memory model shows promise for modeling participant performance fall-off, offering a potentially useful tool for neuroergonomics research.
Authors
- Jamison Heard (ORCID: https://orcid.org/0000-0001-6860-0844)
- Esa M. Rantanen (ORCID: https://orcid.org/0000-0001-9666-4458)
- William Gebhardt
- Alexander G. Ororbia (ORCID: https://orcid.org/0000-0002-2590-1310)
Institutions
- Rochester Institute of Technology (US)
Publication Details
- Journal
- Proceedings of the Human Factors and Ergonomics Society Annual Meeting
- Published
- 2025-09-01
- DOI
- https://doi.org/10.1177/10711813251364803
- Primary Topic
- Multimodal Machine Learning Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation