Frontiers in Neuroengineering

Aims & Scope

This journal is closed for submissions.

Article submissions related to Neuroengineering are welcomed in Neural Technology, a specialty section of Frontiers in Neuroscience, which continues the mission of this closed specialty journal.

Frontiers in Neuroengineering is devoted to promoting research integrating neuroengineering, nanotechnologies and neurosciences.

Convergence between neurobiology and quantum-, nano- and micro-sciences is particularly emphasized as an extremely promising way toward substantial discoveries in brain research and as a technological foundation for future neuroprosthetics and brain-machine interfacing.

This interdisciplinary approach that involves neuroengineering, modeling, nanotechnology, imaging, and the development of micromachining and other devices to solve important emerging problems in clinical neurosciences, opens great new challenges.

We therefore invite original contributions on a wide range of topics that present the fruit of such interdisciplinary convergence or that provide stimuli for future alliances.

We aim to provide an interactive forum for cutting-edge studies on the nervous system, on new materials and techniques for interfacing neurons with artificial devices, on novel molecular tools to probe the complexity of the brain at the system-, network-, cellular-, subcellular- and molecular level.

Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar

Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Biochemistry, Genetics and Molecular Biology, Engineering and Neuroscience, designed to support cutting-edge academic discovery.

Licensing & Copyright

This journal operates under an Open Access model. Articles are freely accessible to the public immediately upon publication. The content is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), allowing users to share and adapt the work with proper attribution.

Copyright remains with the author(s), and no permission is required for non-commercial use, provided the original source is cited.

Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• The blood-brain barrier: an engineering perspective

  Citation: 502

  Authors: Andrew D., Mao, Amanda F., Jeffrey D., Dwight E., Peter C.

• Brain-computer interface-based robotic end effector system for wrist and hand rehabilitation: results of a three-armed randomized controlled trial for chronic stroke

  Citation: 262

  Authors: Kai Keng, Cuntai, Kok Soon, Chuanchu, Longjiang, Ka Yin, Gopal J., Christopher Wee Keong, Karen Sui Geok

• P300 brain computer interface: current challenges and emerging trends

  Citation: 248

  Authors: Reza, Brendan Z., Christoph, Eric W., Sonja C., Andrea

• Organic electrode coatings for next-generation neural interfaces

  Citation: 203

  Authors: Ulises A., Andrew J., Laura A., Nigel H., Rylie A.

• Detection of self-paced reaching movement intention from EEG signals

  Citation: 163

  Authors: Eileen

• Poly(3,4-ethylene dioxythiophene) (PEDOT) as a micro-neural interface material for electrostimulation

  Citation: 158

  Authors: Seth

• PEDOT–CNT Composite Microelectrodes for Recording and Electrostimulation Applications: Fabrication, Morphology, and Electrical Properties

  Citation: 157

  Authors: Ramona, Kai, Birgit, Gordon Steve, Gerhard, Udo, Wolfgang, Alfred, Martin

• Brain-computer interface with somatosensory feedback improves functional recovery from severe hemiplegia due to chronic stroke

  Citation: 156

  Authors: Takashi, Keiichiro, Kimiko, Naoki, Mari, Tetsuo, Masahiko, Toshiyuki, Akio, Meigen, Junichi

• Abiotic-biotic characterization of Pt/Ir microelectrode arrays in chronic implants

  Citation: 155

  Authors: Abhishek, Qing-Shan, Robert, Viswanath, Roxanne C., Toshikazu, Wolfgang J., Justin C.

• Decoding spectrotemporal features of overt and covert speech from the human cortex

  Citation: 148

  Authors: Stéphanie, Peter, Chris, Hans-Jochen, Nathan E., Jochem, Gerwin, Robert T., Brian N.