Exploring the Neurobiology of the Sensory-Motor System

A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Sensory and Motor Neuroscience".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 211

Special Issue Editors


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Guest Editor
School of Pharmacy, South University, Savannah, GA 31406, USA
Interests: sensory; perception; motor; cognitive; temporal-spatial; time dimension
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Guest Editor
Independent Researcher, Bregenz, Austria
Interests: temporal memory; subthreshold membrane potential oscillations; gamma–theta code; pattern separation

Special Issue Information

Dear Colleagues,

The successful execution of movements must be combined with veridical perception, key to the survival of prehistoric humans in hostile environments. Selection pressures may have played a key role in the development of the cognitive functions of humans. One of the major areas of neuroscience research has been how the time dimension can be represented in a three-dimensional Euclidean model of the brain. Accurate representation of the time dimension in the brain can help us understand how movements are generated by the brain during various types of tasks.

We invite papers from different disciplines, such as computational neuroscience, neurobiology, and clinical research, that can shed light on representation as well as the role of the time dimension in the cognitive functions of the brain.

Dr. Daya Shankar Gupta
Dr. Hubert Löffler
Guest Editors

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Keywords

  • sensory
  • perception
  • motor
  • execution
  • cognitive functions
  • space of the brain
  • temporal-spatial
  • time dimension

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Published Papers (1 paper)

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Review

18 pages, 715 KB  
Review
Exploring Imagined Movement for Brain–Computer Interface Control: An fNIRS and EEG Review
by Robert Finnis, Adeel Mehmood, Henning Holle and Jamshed Iqbal
Brain Sci. 2025, 15(9), 1013; https://doi.org/10.3390/brainsci15091013 - 19 Sep 2025
Abstract
Brain–Computer Interfaces (BCIs) offer a non-invasive pathway for restoring motor function, particularly for individuals with limb loss. This review explored the effectiveness of Electroencephalography (EEG) and function Near-Infrared Spectroscopy (fNIRS) in decoding Motor Imagery (MI) movements for both offline and online BCI systems. [...] Read more.
Brain–Computer Interfaces (BCIs) offer a non-invasive pathway for restoring motor function, particularly for individuals with limb loss. This review explored the effectiveness of Electroencephalography (EEG) and function Near-Infrared Spectroscopy (fNIRS) in decoding Motor Imagery (MI) movements for both offline and online BCI systems. EEG has been the dominant non-invasive neuroimaging modality due to its high temporal resolution and accessibility; however, it is limited by high susceptibility to electrical noise and motion artifacts, particularly in real-world settings. fNIRS offers improved robustness to electrical and motion noise, making it increasingly viable in prosthetic control tasks; however, it has an inherent physiological delay. The review categorizes experimental approaches based on modality, paradigm, and study type, highlighting the methods used for signal acquisition, feature extraction, and classification. Results show that while offline studies achieve higher classification accuracy due to fewer time constraints and richer data processing, recent advancements in machine learning—particularly deep learning—have improved the feasibility of online MI decoding. Hybrid EEG–fNIRS systems further enhance performance by combining the temporal precision of EEG with the spatial specificity of fNIRS. Overall, the review finds that predicting online imagined movement is feasible, though still less reliable than motor execution, and continued improvements in neuroimaging integration and classification methods are essential for real-world BCI applications. Broader dissemination of recent advancements in MI-based BCI research is expected to stimulate further interdisciplinary collaboration among roboticists, neuroscientists, and clinicians, accelerating progress toward practical and transformative neuroprosthetic technologies. Full article
(This article belongs to the Special Issue Exploring the Neurobiology of the Sensory-Motor System)
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