Brain-computer interfaces (BCIs) are systems that allow for direct communication between the brain and an external device. BCIs record and decode neural activity from the brain, translate it into control signals, and send those signals to an output device to carry out the intended action. This provides a direct communication pathway between the brain and technology, without requiring movement of muscles or peripheral nerves. BCIs have the potential to benefit people with paralysis and other disabilities by enabling control over prosthetic limbs, computer cursors, speech synthesizers, and more. Research into BCIs has expanded rapidly in recent decades, leading to major advances in our understanding of neural coding and decoding. However, many challenges remain in making BCIs fast, accurate, and robust enough for widespread practical use.
Current BCI Systems
A variety of invasive and non-invasive methods exist for recording brain activity for BCI purposes. Invasive BCIs implant electrodes directly into the brain for higher fidelity signals, but carry risks from surgery and potential infection. Non-invasive methods like electroencephalography (EEG) measure signals from the scalp and are lower bandwidth but safer. Common locations for recording include the motor cortex for motor BCIs, visual cortex for sensory BCIs, and prefrontal cortex for higher-level cognition BCIs.
Motor BCIs
Motor BCIs aim to decode movement intentions from neural activity in the motor cortex, the region of the brain responsible for planning and executing voluntary movements. Implanted BCIs have enabled paralyzed humans and animals to control computer cursors, robotic arms, and exoskeletons. In landmark trials, implanted sensors in the motor cortex of paralyzed patients allowed them to control a robotic arm to perform self-feeding motions. Non-invasive motor BCIs using EEG have also succeeded in simple movement control, like moving a cursor on a screen. Challenges include lower signal resolution with EEG, and implants carry risks from surgery.
Sensory BCIs
Sensory BCIs work in the reverse direction, encoding sensory information like vision and touch into patterns of electrical stimulation applied to the appropriate brain regions. This can evoke sensory percepts that serve as a replacement channel for people with deficits. For example, cochlear implants for deafness encode sound into stimulations of the auditory nerve. BCIs for artificial vision stimulate the visual cortex according to images from a camera. Such implants have partly restored visual sensations like motion detection. Work is ongoing to increase the resolution using techniques like recruitment of other senses for encoding.
Cognitive BCIs
Cognitive BCIs seek to monitor or manipulate higher-level brain functions like memory, attention, emotion, decision-making, and consciousness. EEG studies have decoded brain patterns related to focusing attention, remembering items, recognizing people/objects, and making simple choices. Stimulation methods like transcranial magnetic stimulation (TMS) can modify mood and cognitive abilities. Applications include boosting memory before studying, controlling impulses in addiction, regulating mood disorders, and even altering consciousness. Cognitive enhancement for healthy users also creates ethical concerns.
BCI Input Methods
Invasive BCIs
Invasive BCIs use electrodes implanted directly into the brain to record neural activity at the level of single neurons, small populations, or field potentials. This provides the highest quality signals, but requires risky brain surgery.
Common invasive BCI techniques:
- Intracortical arrays - Microelectrode arrays implanted in the cortex record action potentials from individual neurons. Allows precise decoding of motor behaviors.
- Electrocorticography (ECoG) - Electrodes placed below the skull directly on the brain surface record local field potentials from the cortex. Less precise but lower risk than intracortical implants.
- Intracortical optic fibers - Optogenetic sensors inserted into the cortex can record from genetically sensitized neurons that fire on light stimulation. Enables cell-specific recording.
Non-invasive BCIs
Non-invasive BCIs use external sensors that measure brain activity through the intact skull. They avoid surgical risks but have lower signal quality.
Common non-invasive BCI techniques:
- EEG - Electrodes on the scalp record electrical rhythms from the cortex with millisecond accuracy. Most common BCI method due to ease of use. Limited spatial resolution.
- fMRI - Detects blood oxygenation to map brain activation patterns. Good spatial resolution but slow (seconds). Used for mapping and brain states.
- MEG/EEG - Magnetoencephalography detects magnetic fields of brain activity. Combines good temporal resolution with improved 3D localization over EEG.
- fNIRS - Measures hemodynamic signals like fMRI but using optical methods safe for frequent use. Can study cognition and visualization.
BCI Output Devices
BCI outputs utilize the decoded brain activity signals to carry out the user's intention through various actuators.
Common BCI output devices:
- Computer cursors - Enable point and click control of computers for communication, web surfing, creativity tools, and more, using decoded intents from the motor cortex.
- Robot/prosthetic arms - Allow paralyzed users to perform reaching and grasping motions by controlling robotic limbs through decoded movement plans.
- Wheeled robots - Users can navigate robotic vehicles around environments by simply thinking of intended directions and movements.
- Exoskeletons - Powered robotic suits that a user wears can be controlled to facilitate walking, limb movement, and grasping.
- Muscle stimulators - Electrical stimulation activated by BCIs can induce contractions of paralyzed muscles for restoring movements like standing or walking.
- Speech synthesizers - Allow users to produce audible speech by decoding intended words and commands from cortical activity. Useful for verbal communication.
- Sensory stimulators - Actuators for vision, touch, and hearing activated by a BCI can provide sensory feedback to users based on environment sensors.
Advances in Invasive BCIs
Invasive BCI technology has progressed rapidly in recent years, helped by advances in materials, microfabrication, and neural decoding:
- Biocompatible electrodes - Electrode materials like graphene, conductive polymers, silicon, iridium oxide enable safer long-term implants with reduced scarring.
- High-density microECoG - Micro scale ECoG grids with up to 1000 channels cover large cortical areas with high resolution, and can last years without notable immune response.
- Neural dust motes - Tiny wireless implants, the size of dust particles, can record from tissue without wires. Allows broad distribution across the brain.
- Optogenetics - Genetically sensitized neurons activated by light enable cell-specific recording and stimulation when combined with optic fiber electrodes.
- Machine learning decoders - Algorithms like deep neural networks can continually improve at decoding movement plans from population neural activity in the motor cortex of paralyzed patients.
- Bidirectional BCIs - Implants that combine recording and stimulation allow paralyzed users to receive artificial tactile feedback when controlling a robotic limb, closing the loop.
These advances have improved grasp control, reach accuracy, and incorporated tactile feedback for prosthetic limbs controlled by implants. Work is ongoing to increase the number of controllable degrees of freedom as well as perception of pressure, texture, warmth, and other sensations.
Non-Invasive BCI Progress
Though lower bandwidth than implants, non-invasive BCIs have also seen major improvements in decoding abilities:
- Dry EEG electrodes - Electrodes that don't require scalp preparation or gels, enabling quick setup of EEG systems. Improving wearability.
- Active electrodes - Novel electrode materials and integrated electronics amplify signals right at the scalp, increasing signal-to-noise ratio.
- Convolutional neural networks - Deep learning now rivals human accuracy at decoding motor intentions from EEG signals for 2D movement control.
- Motion artifact removal - Algorithms can isolate neural signals from muscle movement contamination, improving decoding during ambulation.
- Focused ultrasound - Gentle pulses of ultrasound can briefly "open" the blood-brain barrier, allowing drugs, nanoparticles, or viral vectors to selectively alter brain tissue function non-invasively.
- Transcranial alternating current stimulation - Applying oscillating electric fields can entrain neural firing patterns related to motor skills and cognition.
Though most progress has involved EEG for noninvasive BCIs, other modalities like MEG, fNIRS, and fMRI continue being explored to enhance decoding from different brain regions. Overall, wearability, ease of use, and control speed continue to improve gradually for non-invasive interfaces.
Emerging BCI Applications
Beyond assisting people with paralysis, BCIs are enabling a host of new applications:
- Neuroprosthetics - BCIs can link not just to arms but artificial legs, hands, and exoskeletons, allowing thoughts to control full body motion. Enables wheelchair-bound mobility
- Neurorehabilitation - BCI devices can strengthen pathways between damaged brain areas and muscles using intention-driven stimulation after brain injuries like stroke.
- Memory enhancement - Studies show transcranial stimulation directed by cognitive BCIs can boost memory performance and motor learning in healthy subjects.
- BCI virtual reality - VR environments that adapt in real-time based on users' brain states via BCI create more seamless and reactive experiences.
- Artistic creativity - Some artists are exploring BCIs as a new medium, using them to create music, images, and performances based on imagined ideas.
- Passive BCIs - Interfaces that silently monitor brain states during everyday computer use can adapt interfaces to user engagement, attention, workload,
Here is the continuation of the essay:
Advances in Sensory Feedback BCIs
Early BCIs focused on decoding motor signals, but work is accelerating on bi-directional systems that incorporate sensory feedback:
- Intracortical microstimulation - Delivering patterns of electrical stimulation via implanted arrays to targeted areas of sensory cortex can induce artificial tactile, visual, or auditory sensations.
- Non-invasive sensory modulation - Techniques like transcranial magnetic stimulation (TMS) and focused ultrasound paired with EEG/MEG can induce sensory effects without implants.
- Biomimetic sensory encoding - Machine learning can translate data from sensors like cameras and microphones into activation patterns that mimic normal sensory cortex input. Improves realism of induced sensations.
- Artificial cochleas and retinas - Implantable replacements for damaged sensory organs, like retinal and cochlear implants, are improving in resolution and compatibility with BCIs.
- Robotic skin with sensors - Artificial skin embedded with pressure and temperature sensors on prosthetic limbs allows sensation of touch on a BCI-controlled robot arm.
- Closed-loop sensory control - Integration of sensory feedback enables fluid adjustment of BCI-driven prosthetics or speech synthesizers until output matches the user’s thought.
By better replicating natural neural coding patterns, sensory BCIs aim to make induced perceptions feel more seamless and realistic. This could benefit assistive devices, virtual reality, and augmented human senses.
Trends in Cognitive and Memory BCIs
In addition to sensorimotor functions, advances are enabling BCIs for directly interfacing with higher cognition:
- Real-time fMRI neurofeedback - Users can voluntarily modulate activation in regions of their brain related to emotional, perceptual, and cognitive processes based on real-time fMRI readouts.
- Memory enhancement - Transcranial stimulation directed by EEG signatures of memory function can improve recall performance in temporal lobe regions used for memory encoding and storage.
- BCI authentication - Classifiers can identify individuals with high accuracy based on characteristic patterns in their brain activity, providing enhanced identity verification and device security.
- Emotion and mood decoding - Algorithms can now extract emotional states like happiness, sadness, stress, and more from EEG/MEG signals and facial EMG in real-time as feedback.
- Attention monitoring - BCIs tuned to prefrontal and parietal activity associated with vigilant focus could maintain engagement by altering tasks in response to wavering attention.
- Unconscious state decoding - Signatures of awareness and consciousness in EEG/MEG readings enable BCIs to detect and communicate with patients in vegetative states.
Though still early stage, cognitive BCIs have compelling applications from enhancing education and training to improving mental health care. Ethical standards will be critical as these tools develop.
The Future of BCIs
Upcoming BCI breakthroughs may come from multimodal interfaces combining different brain imaging techniques:
- Hybrid EEG-fNIRS - Combines EEG's precise timing with fNIRS imaging of oxygenated hemoglobin concentrations in the outer cortex.
- MEG-EEG fusion - Merges MEG's 3D localization with EEG's fast dynamics. Promising for decoding movement, working memory, and visual processing.
- EEG-fMRI integration - Marries fMRI's whole brain coverage with EEG's direct measurement of cortical activity. Could improve spatial precision of EEG.
- MRI-ultrasound combination - Focused ultrasound can locally interact with tissue to open the blood-brain barrier, while MRI confirms targeting. May enable non-invasive deep brain stimulation.
- Multielectrode array platforms - Single implants integrating multiple types of electrodes and sensors maximize information collection from each brain region.
In addition, future BCIs may move beyond electronics and biology to incorporate new technology:
- Optogenetic nanoparticles - Nano-scale neural dust motes containing optogenetic proteins could enable wireless cell-specific control and recording throughout the brain.
- Magnetogenetics - Proteins engineered to activate neurons on exposure to magnetic fields could provide wireless and precisely targeted control of brain regions.
- Ultrasonic neural dust - Early research indicates ultrasound waves can power and communicate with tiny implanted neural devices containing piezoelectric crystals. Energy efficient.
- Synthetic biology - Genetically engineered neurons implanted in specific brain regions could wirelessly interface with electronics, sensing conditions and delivering outputs.
Though significant challenges remain, the coming decades of BCI research hold incredible potential for enhancing both assistive devices and human brain functions. Such tools require ethically informed development and application for benefits to outweigh risks. With appropriate wisdom guiding advancement, BCIs may one day seamlessly augment senses, memories, emotions, and intellectual abilities.
No comments:
Post a Comment