What Are Brain Computer Interfaces?
Technology is continually reshaping our abilities, redefining what it means to be “able”. In Episode 80 of Neuroverse, Clara and Carolina discuss some of the most transformative applications of neuroscience, engineering, and computation in treating challenging neurological disorders and helping people regain control of their lives.
Brain Computer Interfaces (BCIs) are systems that enable the direct connection and communication between the brain and an external device. BCIs utilize technologies that translate neural activity from the human brain into actionable electrical signals that can be read out. Devices are designed to process such signals to interpret cognitive states and intentions, execute actions and communicate back information.
Brain Computer Interfaces (BCIs) are systems that enable the direct connection and communication between the brain and an external device
Image depicting an implanted microelectrode array (source: UCSD today article)
Typically, BCIs are categorized based on the method of signal acquisition and the type of activity it aims to analyze. On the basis of signal acquisition, BCIs are either invasive (where “intra-cortical electrodes” are implanted directly into the human brain), non-invasive (where electrodes are placed on the scalp and activity is recorded through various different types of methods, for example electroencephalography or functional near-infrared spectroscopy), or semi-invasive (where electrodes are placed on the epidural or the arachnoid space just underneath the skull). Based on the type of signal processed by the devices, BCIs can be either passive (where the BCI monitors unintentional cognitive and emotional states), active (where the device measures activity arising from doing a voluntary task), or reactive (measuring signals produced when an individual reacts to an external stimulus).
In creating unprecedented interfaces between external devices and the human brain, these engineered systems are expanding the frontiers of innovation and providing some of the most novel and personalized solutions to disorders once thought to be untreatable.
Medical and Therapeutic Applications of BCIs
From Signals to Solutions: Innovations in Neurorehabilitation
One of the most well-known applications of BCIs is in neurorehabilitation. Specifically, in supporting individuals with motor and cognitive impairments that arise from injuries such as stroke or spinal cord damage. BCIs drive systems that interpret neural signals related to movement intention to help perform motor tasks and promote neuroplasticity – the brain’s ability to form new neural connections. BCIs also provide neurofeedback – to help train patients enhance a specific brain activity related to a motor task or a cognitive function. By monitoring and interpreting brain states, BCIs enable tailored therapeutic interventions, adapting in real time to an individual’s neural signals and enhance the precision of action.
In 2021, Willet et al. explored how BCIs can help individuals with locked-in-syndrome to communicate. Characterized by the paralysis of nearly all voluntary muscles, locked-in syndrome is one of the most debilitating conditions that exists, preventing individuals from communicating both verbally and/or physically and affecting their ability to interact with the world. The research team created a system that interpreted the motor intentions of a tetraplegic individual, ultimately enabling the patient to write at 90 characters per minute, with a high accuracy of 94%. The study involved interpreting neural signals associated with handwriting. Although the individual could not physically write, the participant performed motor movements mimicking handwriting which the BCI system decoded based on neural activity recordings. The electrodes implanted in the participant’s motor cortex recorded neural signals associated with motor commands for writing. The study utilized an advanced microelectrode array technology to capture these neural patterns with high precision. Using a specialized decoding algorithm, the researchers were able to analyze the temporal and spatial characteristics of the neural patterns, and thereby distinguish between various handwriting strokes and characters. Through continuous updates and refinements to the data processing and algorithm methods, the system’s real time performance with the achieved accuracy levels was particularly impressive.
The research team created a system that interpreted the motor intentions of a tetraplegic individual, ultimately enabling the patient to write at 90 characters per minute, with a high accuracy of 94%.
The technology relied on recording neural signals while the patient visualised handwriting
Beyond just the technical achievement, the results have profound implications for patients with severe motor impairments. By creating a system that interpreted fine motor movements, the study made significant progress in introducing technologies and tools for the purposes of practical communication. By providing an autonomous experience – allowing user-friendly interaction by reducing communication errors and allowing simultaneous motor movements, promising convenience and an improved quality of life.
Restoring Motion: Understanding Motor Functional Recovery
In 2023, Lorach et al. designed and implemented a BCI system designed to restore voluntary motor functions in individuals with severe spinal cord injuries. This technology consisted of a closed-loop system, leveraging a combination of electrocorticography (ECoG) and epidural electrical stimulation (EES) to re-establish motor control. This enabled the translation of neural signals to electrical impulses, activating the appropriate muscles and enabling users to control their lower limb movements. In this study, ECoG was used to identify and capture the neural patterns associated with the intention to move, such as walking or stepping. To improve the ability to produce precise commands, the system employed a hybrid decoding approach that integrates models designed for both continuous movement and discrete mental states. This dual-model strategy allowed the BCI to interpret complex motor intentions from the user’s brain activity, ensuring that the system could accurately translate these signals into commands that control physical movement.
Image from original paper by Lorach et al., 2023
Another component of the system that played a pivotal role in its success was the calibration of decoders. This process involved mapping ECoG signals to specific motor tasks, and refining these mappings during repeated sessions. This process was essential as it ensured that the BCI system was accurate and responsive to the user’s intentions, adapting through the stages of rehabilitation.
While this technology is a true representation of the potentials of engineering to improve the quality of life and medical outcomes, there is an assessment to be made about its potential risks, which include surgical costs and complications, contraindications, and limited device performance. Whether technology does more good than bad depends on how effectively such risks are calculated, addressed, and mitigated. An important consideration must also be made about the ethical considerations for the family members and potential psychological impacts on the patient.
Pathways to Relief: Pain Management through BCI
Pain management remains a significant challenge in clinical settings, especially for patients suffering from neuropathic pain. Pharmacological treatments or physical therapies, despite being accessible, may not always be effective or suitable for all patients. BCI systems assist in both pain detection (identification of pain-related neural signals) as well as intervention (in modulating or alleviating pain by influencing said neural activity). Pain detection primarily uses imaging techniques such as EEG, fMRI and MEG to detect underlying neuronal and vascular activity to monitor pain related responses, thereby supporting pain assessment. Similarly, detection involves techniques such as neuromodulation or neurofeedback to improve recovery and reduce pain perception.
In one striking example, a group of researchers created and validated a BCI system to help detect pain through real-time monitoring. This system integrated both EEG and skin conductance measures. EEG measures brain activity, while skin conductance reflects autonomic arousal associated with pain. This dual signal approach aimed to enhance the accuracy of pain detection. Using a probabilistic classification approach, combining information from both signals, the device was able to achieve over 82% accuracy in detecting induced pain in healthy subjects. The study also showed something that is consistent with existing knowledge on neural biomarkers of pain - the EEG data revealed a decrease in alpha and beta power in response to painful stimuli.
An important application of BCI is the mitigation of pain
Further to pain detection, the researchers introduced a novel therapeutic intervention to reduce pain – using Transcutaneous Electrical Nerve Stimulation (TENS) and Virtual Reality (VR). By addressing both physical sensations and cognitive components associated with pain perception, the combined approach provided a comprehensive treatment that aimed to alleviate pain more effectively than traditional methods. While the intervention was extremely effective in healthy patients experiencing pain, the intervention reduced only 50% of reported pain in patients with neuropathic pain. The discrepancy between healthy and clinical populations further underscores the need for more work in pain research, addressing issues such as experimental consistency and rigour, and conceptualizing the complexities in pain experience.
Finding a Voice: Communication Aids for Locked in Syndrome
While engineering and neuroscientific advancements are truly worthy of mention, it is important to develop technologies keeping in mind the user and the nature of their interactions with the system. In a notable study, researchers worked to help facilitate communication for a patient diagnosed with amyotrophic lateral sclerosis (ALS), and after reaching a complete locked-in state, required a transition from one technology to another.
Image depicting the experience of locked-in syndrome (created by ChatGPT)
Initially, the patient used a non-invasive BCI system based on eye movements to communicate. This system worked by detecting eye movements to signify "yes" responses and no eye movements to indicate "no." They trained a binary support vector machine (SVM) to differentiate between these two states, which were then used to select letters auditorily, allowing the patient to form words and sentences.
The effectiveness of this system was significant yet limited. The patient managed to communicate at an average rate of one character per minute. However, the inherent variation in eye movement posed a significant challenge, where slight random changes in eye movement could impact efficiency. Despite the potential for errors and ambiguities, the system proved useful in conveying practical needs and personal messages, such as requests for assistance, social interaction, and feedback about the technology.
As the patient's condition progressed and their ability to use eye movements deteriorated, preparations were made for the implantation of an intracortical BCI system. The invasive BCI system promised greater reliability by directly interfacing with the brain’s neural activity. The surgical procedure, performed in March 2019, involved the implantation of two microelectrode arrays into the patient’s dominant left motor cortex. The first array was placed in the hand area of the primary motor cortex, and the second in the supplementary motor area (SMA). Post-surgery, a neural signal processor was employed to record and process neural signals.
Extraordinarily, the technology relied on the ability of the patient to learn how to modulate their own neural activity. The patient was trained to modulate their neural firing rates to match the frequency of the auditory feedback. Initially, the tones presented were either rising or descending, corresponding to “yes” or “no,” respectively. This auditory feedback was crucial for the patient to understand and control their neural activity. Although the training process was time-consuming, it proved very effective. The patient was able to use this method to select letters, ultimately forming meaningful phrases and words. The system’s ability to facilitate volitional communication in a completely locked-in state underscores the potential of BCIs to offer new avenues for interaction and expression, even when traditional methods are no longer feasible.
Extraordinarily, the technology relied on the ability of the patient to learn how to modulate their own neural activity. The patient was trained to modulate their neural firing rates to match the frequency of the auditory feedback.
Despite the promising results, a significant consideration is that in ALS the motor cortex —which plays a crucial role in generating and modulating neural signals— continuously degenerates. This can impact the effectiveness of the BCI system in detecting neural activity effectively. Moreover, the time required for training can be considerable. The process of learning to control neural activity to match specific auditory tones requires extensive practice and adaptation, which can be a barrier to immediate and effective communication for patients who are already in the late stages of the disease. This example, like many other BCI technologies, is more likely to remain as a case study.
Mind over Machine: BCI and Personal Agency
The past few examples have demonstrated how BCIs have made a remarkable stride in the recent years, where effective systems decode neural activity and translate information into actionable commands, holding promise for enhancing the quality of life for individuals with severe motor impairments. Despite such significant progress, there is less attention given to the subjective experience of control, or agency – the sense of being in command of one’s actions.
Autonomy may be crucial for successful BCIs
Illustration by Jim Tsinganos (Source joanakompa.com)
In another insightful study, researchers explored how different types of sensory feedback influence the sense of agency in BCI users. The group utilized a sophisticated set up, featuring a 96-channel microelectrode array implanted in the hand area of the left primary motor cortex (M1) and a neuromuscular stimulator (NMES). This advanced technology enabled precise decoding of neural activity and targeted stimulation. The research focused on manipulating sensory feedback—both visual and sensory—to investigate how different feedback modalities impact the participant’s sense of agency.
This revealed that congruent feedback, where visual and sensory cues were aligned with the intended movement, significantly enhanced participants’ sense of agency. Furthermore, the study explored how sensory feedback helps update and integrate sensory information with motor commands. By providing congruent feedback, the BCI system supported better integration of sensory input, leading to an improved perception of control. This integration is crucial for effective motor control and rehabilitation, as it ensures that the participant's intentions and actions are aligned with the feedback received.
The study also addressed the therapeutic potential of enhancing the sense of autonomy in BCI users. Many patients using BCIs experience a plateau in therapeutic progress, where further improvements become challenging. By focusing on the sense of agency, the research aimed to break through this plateau and enhance therapeutic outcomes. The findings suggest that improving the sense of autonomy through congruent feedback could help make BCI therapy more effective.
Future Considerations & Conclusion
Overall, BCIs represent a transformative frontier in medicine, revolutionizing the way we interact with machines to combat lost functions due to neurological disorders or injuries. Despite their remarkable potential, the development and application of BCIs face numerous challenges. For instance, implanted electrodes are susceptible to degradation over time, affecting the quality and stability of recordings obtained. Advancements in materials engineering could prove beneficial to enhance electrode longevity and make chronic implantation more feasible. Similarly, ECoG and EEG based measurements are computationally extensive, necessitating advancements in both hardware and algorithms to manage and interpret vast amounts of data.
Image source: The Digital Speaker
The future of BCIs involves broadening their clinical applications to include both motor and cognitive therapies, requiring refining devices, technologies and systems to a wider range of patients and conditions. The development of cost-effective solutions and strategies to enhance accessibility is essential for making BCIs more widely available. As these challenges are met, BCIs hold the remarkable promise of transforming healthcare and enhancing human capabilities.
Listen to the episode here to find out more!
This article was written by Purnima BR and edited by Clara Lenherr
Purnima is Master's student in Cognitive Neuroscience at the University of Sheffield who is enthusiastic about the neural basis of cognition, and how advances in diagnostic visualization can help inform treatments for neuropsychiatric conditions.
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