Brain-in-the-Loop Neurotechnologies: Real-Time Readouts, Adaptive Neuromodulation, and Computational Frontiers for Precision Brain Control

Brain-in-the-loop neurotechnologies are an emerging field that combines neuroscience, engineering, and computational methods to monitor and modulate brain activity in real time. These systems use neuroimaging to track brain states and apply targeted brain stimulation to influence neural function dynamically. This integration helps uncover how brain activity relates to behavior, linking basic neural mechanisms to higher-order cognitive processes.
Despite recent progress, key challenges remain, particularly in designing seamless interactions between brain signals and computational models and in understanding how these systems can adapt responsively to changes in brain activity. There is ongoing debate about the effectiveness of these technologies and their real-world applications, especially in contexts that involve direct modulation or control of brain function.

This research topic invites contributions that advance basic and computational neuroscience through novel approaches. The focus is on the development of open- and closed-loop systems guided by real-time neuroimaging feedback, leveraging tools from control theory, signal processing, and artificial intelligence. The goal is to drive innovation in adaptive neuromodulation technologies that respond to brain dynamics in real time.
We welcome articles addressing, but not limited to, the following themes:

- Non-invasive and invasive brain stimulation techniques guided by neuroimaging readouts (e.g., resting-state, induced, and evoked activities) for adaptive and targeted neuromodulatory strategies.
- Application of sensory stimulation (e.g., SSVEP, ASSR, SSSR) in open- or closed-loop systems using electrical, magnetic, ultrasound, or somatosensory modalities.
- Pipelines and architectures for online analysis of neuroimaging readouts, leveraging artificial intelligence in neurotechnology.
- Neurophysiological models informed by physics-based or biological principles and their implications for personalized data mining and neuromodulation strategies.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Data Report
• Editorial
• FAIR² Data
• Hypothesis and Theory
• Methods
• Mini Review
• Original Research
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Data Report
• Editorial
• FAIR² Data
• Hypothesis and Theory
• Methods
• Mini Review
• Original Research
• Perspective
• Review
• Technology and Code

Keywords: neuroimaging, deep learning, brain stimulation, neurotechnology, computational neuroscience and control theory

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.