About this Research Topic
A brain-computer interface (BCI) provides a direct connection between cortical activity and external devices. BCIs may use non-invasive methods such as the Electroencephalogram (EEG) or invasive methods such as the Electrocorticogram (ECoG) or neural spike recordings. In the last decades, many BCI approaches have been developed, based on slow waves, evoked potentials (EPs), steady-state evoked potentials (SSEPs), code-based EPs or motor imagery (MI) paradigms, with the aim of bringing medical applications that help people to the market. The first BCI systems were used to spell, control prosthetic devices, or move cursors on a computer screen. Early BCI work focused on locked-in or completely locked-in patients. Nowadays, many more clinical applications of BCIs technology are being developed.
Several neurological disorders impair voluntary movements and communication, despite intact cognitive functioning. The spectrum of BCI usage for control is extremely wide and includes neural prostheses, wheelchairs, home environments, humanoid robots and much more.
Another exciting clinical application of BCIs focuses on facilitating the recovery of motor function after a stroke or spinal cord injury. BCIs for rehabilitation integrate BCIs with conventional methods and devices for rehabilitation to enhance the brain’s reorganization of corticospinal and cortico-muscular connections after acute, sub-acute, or chronic lesions.
Beside motor deficits, BCI-induced brain plasticity might contribute to the treatment of high-order cortical dysfunctions, such as improving social and emotional behaviors in autism spectrum disorder, training inhibitory control and working memory in ADHD, as well as contributing to the rehabilitation of cognitive deficits related to dementia. Moreover, BCI-based brain training can help preserve cognitive performance in healthy older adults, promoting successful aging and reducing the social burden of the population’s increasing aging. BCIs are also used to establish closed-loop control of brain sensing and stimulation technology to improve, for example, tremor, or to provide sensation.
Finally, BCIs may increase the diagnostic accuracy of brain disorders. For instance, BCIs could be used to detect neural signatures of cognitive processes in persons diagnosed with disorders of consciousness (DOC), provide real-time functional brain mapping for neurosurgery, improve visual function assessment in glaucoma, etc.
Overall, different BCI approaches have the potential to enter into mainstream clinical practice, improving the assessment, rehabilitation, and management of several neurological diseases. This Research Topic aims to collect original research manuscripts and reviews describing breakthrough applications of invasive and non-invasive BCIs in all aspects of medicine.
Keywords: Brain-computer interfaces, clinical applications, neuro-rehabilitation, neurofeedback, invasive and noninvasive
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