General Laboratory Focus
Cyborgs!
Part human part machine.
Here are examples of some devices that attempt to interface to the human body:
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cochlear implants deliver sound information directly to the auditory nerve for people who are otherwise deaf
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retinal implants deliver vision information directly to the optical nerve for the blind
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spinal cord stimulators block pain at the spinal cord for those suffering from chronic pain
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deep brain implants can fix motor disorders like Parkinsons
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vestibular implants can deliver head motion information directly to the brain for balance disorders
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brain-machine interfaces detect brain activity to control robotic arm or a wheel chair for the paralyzed
We are interested in how we can make computers work seamlessly with the nervous system. Our approach is to first understand the underlying scientific principles at the interface between the machine and the nervous system. Electronics use electrons to process information -- body uses ions. The interface between the two is typically confined near the electrodes implanted in the vicinity of neurons. How neural signals are detected through electron motion in the metal electrodes and how we can manipulate neural signals by manipulating electron motion at the electrodes is the underlying problem.
The work conducted in our laboratory includes:
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Electrophysiology to understand neural activity in response to electrical stimulation
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Computational modeling to predict electrical modulation effects on neurons
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Electronics and microfluidics work to develop novel neural implant concepts and devices
Because our key interest is improving the underlying interface between machines and the nervous system, we do not focus on any one neuroprosthetic application. We are interested in a variety of applications and ones that we have worked on are:
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vestibular prosthesis for balance disorders
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cochlear implants for deafness
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pain block at the peripheral nerve
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detection of cancer within a nerve
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asthma attack suppression
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deep brain stimulation for autism
Current work in the laboratory:
Computational modeling
Computational modeling of neural stimulation. Biological systems are complex. Computational models allow us to focus on only the parts of the biology that are implicated in the phenomena that we are studying. We typically build models from bottom up, meaning we make them as simple as possible, but complex enough to agree with the complete set of experimental data available in the literature. We use computational models to understand and form hypotheses about how both direct current and pulsatile stimuli interact with the nervous system. Our projects range from exploring the effects of electrical fields on single neurons to network effects. This work covers the vestibular system (shown above) as well as the peripheral nerves and the central nervous system.
Aplin, F. P., & Fridman, G. Y. (2019). Implantable Direct Current Neural Modulation: Theory, Feasibility, and Efficacy. In Frontiers in Neuroscience (Vol. 13, p. 379).
Steinhardt, C. R., & Fridman, G. Y. (2020). Predicting Response of Spontaneously Firing Afferents to Prosthetic Pulsatile Stimulation. 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2929–2933.
Yang, F., Anderson, M., He, S., Stephens, K., Zheng, Y., Chen, Z., Raja, S. N., Aplin, F., Guan, Y., & Fridman, G. (2018). Differential expression of voltage-gated sodium channels in afferent neurons renders selective neural block by ionic direct current. Science Advances, 4(4), eaaq1438.
T
This technology is a departure from our focus, but the idea was so cool, we had to pursue it.
MouthLab is a "tricorder" device that we invented here in Fridman Lab. The device currently obtains all vital signs within 30s: Pulse rate, breathing rate, temperature, blood pressure, blood oxygen saturation, electrocardiogram, and FEV1 (lung function) measurement. Because the device is in the mouth, it has access to saliva and to breath and we are focused now on expanding its capability to obtaining measures of dehydration and biomarkers that could be indicative of a wide range of internal disorders ranging from stress to kidney failure and even lung cancer.
This technology is being commercialized by a company called Aidar Health.
Fridman, G. Y., Tang, H., Feller-Kopman, D., & Hong, Y. (2015). MouthLab: a tricorder concept optimized for rapid medical assessment. Annals of biomedical engineering, 43(9), 2175-2184.