In today's rapidly advancing world, cutting-edge technologies like artificial intelligence (AI), brain-computer interfaces, and nanotechnology are propelling neuroscience research forward. Scientists at the University of California San Diego (UCSD) have recently developed a groundbreaking transparent brain-computer interface (BCI) that harnesses the power of AI and a nanomaterial called graphene to achieve high-resolution neural recordings from the brain's surface.
According to the World Health Organization (WHO), approximately 16% of the global population, or one in six people, grapple with significant disabilities. Enter brain-computer interfaces, also known as brain-machine interfaces (BMIs), which emerge as promising solutions for individuals who have lost the ability to speak or move.
With a brain-computer interface, individuals can seamlessly control external electronic devices using mere thoughts, enabling them to communicate through synthesized speech, maneuver prosthetic limbs, operate computers, and perform other crucial functions that enhance the quality of life for those with disabilities.
The brain-computer interface market, valued at USD 2 billion in 2023, is projected to reach USD 6.2 billion by 2030, exhibiting a compound annual growth rate (CAGR) of 17.5% from 2020 to 2030, as per the Brain Computer Interface Market Size & Share Report 2030 by Grand View Research.
North America dominated the global revenue share in 2022, accounting for 39.5%. The anticipated growth of the BCI market is fueled by an aging population, leading to an increased prevalence of neurodegenerative disorders such as Alzheimer's, Parkinson's, and Huntington's diseases.
A breakthrough in UCSD's research lies in the unique capability of their brain-computer interface to simultaneously record brain activity through optical imaging and electrical signals. Unlike traditional, opaque BCI implants, this transparent BCI allows neuroscientists to observe brain activity using microscopy. The transparent graphene electrode array records electrical signals from neurons in the outer layers of the brain, while a two-photon microscope captures calcium spikes from neurons as deep as 250 micrometers.
To process this data, UCSD researchers employed an AI model featuring a linear hidden layer, a single-layer bidirectional LSTM (Long Short-Term Memory), or BiLSTM, and a linear readout layer. This AI model learned from the correlation data to predict calcium activity in the deeper parts of the brain based on electrical signals from the outer layer. The result? Neuroscientists can now study brain activity over more extended periods, as subjects move freely instead of being confined under a microscope for brief durations.
In experiments with laboratory mice, the researchers successfully correlated electrical signals recorded by their transparent graphene array with calcium activity in deeper brain regions. According to the study authors, this nanotechnology array can predict both average and single-cell calcium activities from surface potential recordings. With this groundbreaking innovation, the next phase involves expanding research beyond laboratory mouse models.
In conclusion, the UCSD researchers believe that their transparent brain-computer interface has the potential to enhance existing brain-computer interfaces and facilitate less invasive treatments for neurological disorders. The future indeed looks promising as technology continues to open new doors in the realm of neuroscience.