Brain-computer interfaces for memory enhancement: Scientometric analysis and future directions
Year: 2025
Type: article
Abstract: Brain-computer interfaces have the potential to transform society by enhancing brain function. These electronic devices could enable the rapid acquisition of knowledge, preserve memories, and detect neurological conditions affecting memory in their early stages. Their capacity to store and retrieve experiences could bridge generational knowledge gaps. In order to develop such devices, significant challenges need to be overcome, including the need for a deeper understanding of brain mechanisms, ethical concerns about privacy and control, and socio-economic barriers to accessibility. Addressing these challenges is essential for their widespread adoption, which could eliminate inequalities in education. This study searched the scientific literature on brain-computer interfaces and memory enhancement in order to detect scientometric trends. A Boolean search was conducted in Scopus in July 2025. This identified 1148 publications. Most were written in English (98.3 %), were articles (55.7 %), and were published in the Journal of Neural Engineering (5.1 %). There was a gradual increase in the number of publications from 2000 to 2018, with a sudden increase from 2019 onwards. The most frequently co-occurring words in the abstracts were “interface”, “feature”, “technology”, and “training”. The median page count was 9 and the median number of citations was 5. More citations were received by publications that were older, had more authors, or were articles. Only 75 publications were written by a single author, most of whom resided in the United States. With continued advancements, fully functional memory-enhancing brain-computer interfaces may be realized within the next 100 years, profoundly impacting human life.
Author: Marianna Evangelia Kapsetaki
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $2,590
OpenAlex ID: W4415199435