Neuromorphic Computing and Extended Memory

doi:10.1007/s13164-026-00800-8

Neuromorphic Computing and Extended Memory

2026-02-01

3

PRE

AI

DOI：10.1007/s13164-026-00800-8

Original

Original request for help

Save

Abstract

En 中文

This paper examines the potential of memory augmentation devices and neuro-morphic computing systems as empirical supports for the Extended Mind Thesis (EMT). By integrating recent advancements in brain-computer interfaces (BCIs) and memory-augmented neural networks (MANNs) with a detailed case study in neuromorphic computing, we illustrate how brain-like external memory systems can functionally complement and extend biological cognitive processes. Our analy-sis utilizes a three-stage framework-encoding, storage, and retrieval-to critically assess the dynamic interplay between internal neural mechanisms and engineered memory modules. We also address a potential objection to extended memory ques-tioning whether the extension pertains to the memory process or relearning process. Ultimately, this study not only refines our theoretical understanding of the mind-technology interfaces but also lays the groundwork for practical applications in cog-nitive enhancement, neurorehabilitation, and next-generation artificial intelligence.

Keywords:

Extended Memory

Memory Augmentation

Neuromorphic Computing

Brain-Computer Interfaces

Artificial Intelligence

Neuromorphic Computing and Extended Memory

Abstract

Journal

Organization