ReviewFrontiers in neuroscience2018
A New Frontier: The Convergence of Nanotechnology, Brain Machine Interfaces, and Artificial Intelligence.
Review in Frontiers in neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
16 citing papers in PubMed.
- Brain-Computer Interfaces: The Dawn of a New Era in Disease Treatment.Exploration (Beijing, China) · 2026Review
- A novel method based on a multiscale convolution neural network for identifying lung nodules.Scientific reports · 2025Article
- Theoretical investigation on sensing of dopamine and tyramine neurotransmitters by the BJournal of molecular modeling · 2025Article
- Directional hand movement can be classified from insular cortex SEEG signals using recurrent neural networks and high-gamma band features.Scientific reports · 2025Article
- Study on the Effect of the Envelope of Terahertz Unipolar Stimulation on Cell Membrane Communication-Related Variables.Research (Washington, D.C.) · 2025Article
- Wearable Technology and Its Influence on Motor Development and Biomechanical Analysis.International journal of environmental research and public health · 2024Review
- Review on brain-computer interface technologies in healthcare.Biophysical reviews · 2023Review
- Who Wants to Enhance Their Cognitive Abilities? Potential Predictors of the Acceptance of Cognitive Enhancement.Journal of Intelligence · 2023Article
- Nanotechnology: A Revolution in Modern Industry.Molecules (Basel, Switzerland) · 2023Review
- Emerging Materials, Wearables, and Diagnostic Advancements in Therapeutic Treatment of Brain Diseases.Biosensors · 2022Review
- Artificial Neural Network Modelling for Optimizing the Optical Parameters of Plasmonic Paired Nanostructures.Nanomaterials (Basel, Switzerland) · 2022Article
- Mycology-Nanotechnology Interface: Applications in Medicine and Cosmetology.International journal of nanomedicine · 2022Review
- Brain-Computer Interfaces in Neurorecovery and Neurorehabilitation.Seminars in neurology · 2021Article
- Plasticity and Adaptation in Neuromorphic Biohybrid Systems.iScience · 2020Review
- The combination of brain-computer interfaces and artificial intelligence: applications and challenges.Annals of translational medicine · 2020Review
- Neural Modulation of the Primary Auditory Cortex by Intracortical Microstimulation with a Bio-Inspired Electronic System.Bioengineering (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A confluence of technological capabilities is creating an opportunity for machine learning and artificial intelligence (AI) to enable "smart" nanoengineered brain machine interfaces (BMI). This new generation of technologies will be able to communicate with the brain in ways that support contextual learning and adaptation to changing functional requirements. This applies to both invasive technologies aimed at restoring neurological function, as in the case of neural prosthesis, as well as non-invasive technologies enabled by signals such as electroencephalograph (EEG). Advances in computation, hardware, and algorithms that learn and adapt in a contextually dependent way will be able to leverage the capabilities that nanoengineering offers the design and functionality of BMI. We explore the enabling capabilities that these devices may exhibit, why they matter, and the state of the technologies necessary to build them. We also discuss a number of open technical challenges and problems that will need to be solved in order to achieve this.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.