Neural engineering and brain-computer interfaces hold tremendous promise to revolutionize health care and perhaps even the way we interact with consumer electronics. As we learn more about how the brain functions in both health and disease, devices that can record from neurons and stimulate the nervous system to restore health or possibly augment function are becoming increasingly important.
Students on the Neurotechnology pathway learn to develop devices and algorithms that interact directly with the brain, spinal cord and peripheral nervous system. There is also a Neural Computation and Engineering minor available at the University of Washington, which includes classes in this focus area. In addition to building advanced skills in neural engineering, the minor provides training in advanced computational algorithms and neuroethics.
This pathway is a good fit for students who are interested in:
- Medical devices and bioengineering
- Embedded computing and closed-loop control algorithms
- Wireless power and data systems
- Machine learning and computational algorithms
- A career focused on improving medical patients’ quality of life
- A rapidly growing field with exciting startups in both medical and consumer devices
Does a student need a graduate degree specializing in this area to be marketable in industry?
No. Students with a BSECE and a focus in neurotechnology can obtain entry level positions with medical device companies. Some students also pursue a master’s or doctoral degree at the UW, UC Berkeley, Stanford, John Hopkins University, Carnegie Mellon or Case Western Reserve University.
How is neurotechnology applied in the real world?
Neurotechnology has many applications in the real world, for example:
- Designing brain-computer interfaces to record neural signals directly from the brain for health or consumer applications
- Building closed-loop neural stimulators to deliver symptom-relieving stimulation deep within the brain for people with Parkinson’s disease, essential tremor or mental health challenges
- Developing spinal stimulators to restore movement to people experiencing paralysis by delivering electrical stimulation to the spinal cord
- Creating wireless power and data systems to deliver power to an implanted neural device and pass high-bandwith data in and out of the body without the need for wires penetrating the skin
- Authoring machine learning algorithms to interpret neural data and help to understand brain function or cure disease
- Developing implantable electrodes to interface with the brain or peripheral nervous system for fine-grained recording or stimulation
How can neurotechnology be applied to medical conditions?
Examples of neural engineering applied to medical conditions include using deep brain stimulators to sense brain signals and deliver closed-loop electrical stimulation to improve symptoms of Parkinson’s disease, obsessive-compulsive disorder, depression and other neurological disorders. Electrical stimulation of the spinal cord is also being used to restore movement for the first time to people with paralysis following spinal cord injury. Students in this field work at the intersection of medical devices, signal processing, control algorithms, and machine learning to improve health and function for people with neurological disease and injury.
Are there ethical considerations in neurotechnology?
Yes. The primary goal of neurotechnology is to improve quality of life for people with injuries or disorders of the brain or nervous system. As the field approaches the ability to enhance function for people without medical conditions, academic and public interest in neuroethics (the study of ethical issues surrounding neurotechnology) grows stronger. For example, some of the ethical issues being explored at UW ECE and in the Center for Neurotechnology involve asking what devices and algorithms should be advanced in an equitable manner while preserving privacy, the end-users’ control of neural devices and the information these devices may extract directly from brain signals.
Areas of Impact
Computing Data and Digital Technologies
Understanding the vast amount of information that can be recorded from the brain and peripheral nervous system requires advanced computational methods such as artificial neural networks and machine learning. Real-time processing to convert recorded signals into treatments also requires embedded digital processing to provide low-power computing and short-latency control loops.
Health and Medicine
Neurotechnology is one of the fastest-growing areas of medicine, fueled by advances in engineered devices and algorithms. It also leverages our accelerating understanding of how the brain and nervous system function and recover from injury, providing new treatment opportunities for novel devices that interact with neural tissue.
Robotics and Manufacturing
Rehabilitation using neurotechnology often leverages robotic exoskeletons and other automated treatments. In addition, the design and manufacturing of implanted medical devices requires knowledge of ASIC design to minimize heat dissipation inside the body, reduce the need for wireless power transfer and enable efficient real-time computing.
Related Career Paths
Students graduating with a focus in neurotechnology will be prepared to pursue careers in many different types of organizations, for example:
- Large medical device companies such as Medtronic, Boston Scientific, Abbot/St. Jude
- Consumer electronics companies breaking into the Neurotech space such as Intel, ARM, Meta
- Smaller neural engineering companies such as Blackrock Neurotech, Galvani Bioelectronics, ONWARD medical, Cadence Neurosience and many others
- Exciting new startups such as Neuralink, Kernel, and Cala Health
These courses are suggested for those following the Neurotechnology pathway but are not required to complete the BSECE degree program:
EE 460 — Introduction to Neural Engineering
This survey course provides an exciting introduction to the field of neural engineering. Learn how retinal implants restore vision and cochlear implants return hearing to people with deafness. Also take a deep dive into brain-computer interfaces, learn to process real brain signals and apply advanced signal-processing techniques to neural data.
EE 466 — Neural Computation and Engineering Laboratory
This hands-on lab teaches students how to record activity from live neurons and deliver electrical stimulation to control the nervous system. Then, students will develop an amplifier to record electrical activity from their own arm and deliver stimulation to a lab partner to provide ‘remote control’ of their hand movements. Finally, students will master advanced decoding algorithms such as Kalman filters to interpret neural data in real-time.
EE 461 — Neural Engineering Tech Studio (Capstone)
Work in a dynamic team of four students with diverse technical expertise to ideate and prototype a neural engineering device. This fast-paced capstone design course takes a student through the process of user-centered design, customer discovery, device prototyping and demonstration within a 10-week quarter. A large library of neural engineering devices is available to leverage and adapt, as well as a budget for each team to create their own unique prototype. The course culminates in a shark-tank style pitch to real industry judges to determine the winner.
EE 497 (winter quarter) and EE 498 (spring quarter) — Engineering Entrepreneurial Capstone (ENGINE)
The Engineering Entrepreneurial Capstone program (ENGINE) is the culmination of a student’s electrical and computer engineering education at UW ECE. The program provides a unique opportunity for students to develop skills in collaborative systems engineering, project management, and most importantly, working in teams on real-world problems from industry-sponsored projects. The program is overseen by UW ECE faculty and students are guided by practicing engineers. The course culminates in a showcase of student projects, which is attended by industry sponsors and held at the end of spring quarter every year.
Students studying neurotechnology should consider the following pathways:
Enriching Your Path
The following courses are also recommended:
- See courses listed under the Neural Computation and Engineering minor.