Abhishek Prasad, Ph.D.
Associate Professor of Biomedical Engineering
The Miami Project to Cure Paralysis
1095 NW 14th Terrace (R-48)
Miami, FL 33136
Areas Of Research
Abhishek Prasad is currently an Associate Professor in the Department of Biomedical Engineering at the University of Miami. He received his M.S. in Biomedical Engineering from Louisiana Tech University and Ph.D. in Biomedical Engineering from the New Jersey Institute of Technology and University of Medicine and Dentistry in NJ.
The goal of his Neural Interfaces Lab is to develop brain and spinal cord machine interfaces to restore communication and control in paralyzed individuals. The lab also seek to understand and mitigate various material and biological failure mechanisms in neural implants.
Brain and spinal cord machine interfaces for spinal cord injury
Foreign body response in neural implants
Development of rehabilitative neuroprosthetics require recording of neuronal signals reliably for long periods of time. While innovative developments of high-density microelectrode probes have enabled the recording of signals from large neuronal ensembles, the current systems have been unable to access such signals for more than several years. Our lab combines material, biological, and functional perspectives to understand underlying mechanisms governing the effects of chronic electrode implantation leading to performance degradation and electrode failure. Since electrode failure is multi-factorial in nature, we intend to develop ways to mitigate each of those failure modes to build better microelectrodes. Our lab is investigating better and alternate materials for electrodes and insulation that will minimize the corrosion and delamination problem. To mitigate the foreign body response due to implanted materials, we are using therapeutic and pharmacological approaches to reduce the neuroinflammation and oxidative stress that occurs after an electrode implant.
Neuromodulation in the spinal cord
Brain machine interfaces (BMIs) restore communication and control in individuals with paralysis or injuries to the nervous system. Generally, invasive BMIs use single neurons or neuronal population activity, local field potentials (LFPs), and electrocorticography (ECoG) signals as control signals. Our lab is investigating alternate sources for extracting neural control signals in the central nervous system, ways to incorporate information from more structures involved in motor processing in the controller architecture, and design better modeling architectures for decoding neural activity. We seek to develop a neural interface, spinal cord machine interface (SCMI), that can be used for neuroprosthetic applications and serve as a new platform to test novel neural devices. Through these studies, we also seek to understand the underlying neurophysiology of the spinal motor circuits during learned behaviors.
Neural decoders for brain machine interfaces
Brain-Machine Interfaces (BMIs) aim to restore function to those living with paralysis. At the core of the BMI is the decoder, which translates the neural signal into executable actions. One of the limitations of present decoders in its applications to activities of daily living is getting a supervised error signal to control the manipulator smoothly. In our recent work, we have developed an alternative BMI framework based on an actor-critic Reinforcement Learning (RL) paradigm that eliminates the need for a supervised error signal. Our current works seeks to reduce the non-stationarities in the biological feedback so that it can be incorporated reliably in the BMI decoder architecture.
Brain computer interface (BCI) – FES for hand functions in spinal cord injury
In the United States, there are over 33,000 people living with complete tetraplegia due to a traumatic spinal cord injury (SCI). Restoration of hand and arm function is ranked as the highest priority for people living with complete tetraplegia, because it would offer greater independence and improved quality of life. Activation of paralyzed hand muscles by functional electrical stimulation (FES) has been shown to restore control following complete spinal cord injury. A variety of control signals have been used, but most require head or arm movements, which may interfere with activities of daily living. Alternatively, natural signals from the brain can be used for control. Through these studies, we seek to create a BCI-FES as an assistive system for tetraplegics and study neuroplastic changes that may occur during BCI usage.
- I Cajigas, K C Davis, B Meschede-Krasa, N W Prins, S Gallo, J A Naeem, A Palermo, A Wilson, S Guerra, B A Parks, L Zimmerman, K Gant, A D Levi, W D Dietrich, L Fisher, S Vanni, J M Tauber, I C Garwood, J H Abel, E Brown, M E Ivan, A Prasad, J Jagid*, “Implantable Brain-Computer Interface for Neuroprosthetic-Enabled Volitional Hand Grasp Restoration in Spinal Cord Injury”, Brain Communications, 2021 Oct 21;3(4):fcab248. doi: 10.1093/braincomms/fcab248 (2021)
- R Mylavarapu, N W Prins, E A Pohlmeyer, A M Shoup, S Debnath, S Geng, J C Sanchez, O Schwartz, A Prasad*, “Chronic recordings from the marmoset motor cortex revelas modulation of neural firing and local field potentials overlap with macaques”, Journal of Neural Engineering, 18 (2021) 0460b2, https://doi.org/1741-2552/ac115c. (2021)
- C Bennett, A Alvarez-Ciara, W D Dietrich, A Prasad*, “The complement cascade at the Utah micro electrode-tissue interface”, Biomaterials, 268:120583, https://doi.org/10.1016/j.biomaterials.2020.120583. (2021)
- C Liu#, M A Nguyen#, N C Kleinhenz, G A B Colmenares, A F Chebbi, S Duque, B Bernard, J-H Olivier*, A Prasad*, “Surface modifications of an organic polymer-based microwire platform for sustained release of an anti-inflammatory drug”, ACS Applied Biomaterials, 3, 7, 4613-4625, doi/10.1021/acsabm.0c00506. (2020)
- E Dugan, C Bennett, I Tamames, D W Dietrich, C King, A Prasad*, S Rajguru*, Therapeutic Hypothermia Reduces Cortical Inflammation associated with Utah Array Implants”, Journal of Neural Engineering, Apr 29;17(2):026035. doi: 10.1088/1741-2552/ab85d2. (2020)
- N W Prins, R Mylavarapu, A M Shoup, S Debnath, A Prasad*, “Spinal cord neural interfacing in common marmoset”, Journal of Neural Engineering , https://doi.org/10/1088/1741-2552/ab4104, September 2019. (2020)
- C Bennett, F Mohammed, A Alvarez-Ciara, M A Nguyen, W D Dietrich, S M Rajguru, W J Streit, A Prasad*, “Neuroinflammation, oxidative stress, and blood-brain barrier (BBB) disruption in acute Utah electrode array implants and the effect of deferoxamine as an iron chelator on acute foreign body response”, Biomaterials , vol 188, January 2019, pages 144-159. (2019)
- E K Allseits, V Agrawal, A Prasad, C Bennett, K J Kim, “Characterizing the impact of sampling rate and filter design on the morphology of lower limb angular velocities”, IEEE Sensors, dot: 10.1109/JSEN.2019.2899724. (2019)
- S Debnath, N W Prins, E Pohlmeyer, R Mylavarapu, S Geng J C Sanchez, A Prasad*, “Long-term stability of neural signals from microwire arrays implanted in motor cortex and striatum”, Biomedical Physics & Engineering Express, doi.org/10.1088/2057-1976/aada67 (2018)
- K Gant#, S Guerra#, L Zimmerman, B Parks, N W Prins, A Prasad*, “EEG-controlled functional electrical stimulation for hand opening and closing in chronic complete cervical spinal cord injury”, Biomedical Physics & Engineering Express, doi:10.1088/2057-1976/aabb13 (2018). #Authors had equal contribution
- C Bennett, M Samikkannu, F Mohammed, W D Dietrich, S M Rajguru, A Prasad*, “Blood brain barrier (BBB)-disruption in intracortical silicon micro electrode implants”, Biomaterials, doi: 10.1016/j.biomaterials.2018.02.036 (2018)
- Z Xie, O Schwartz, A Prasad*, “Decoding of finger trajectory from ECoG using deep learning”, Journal of Neural Engineering, doi: 10.1088/1741-2552/aa9dbe (2017)
- N W Prins, E Pohlmeyer, S Debnath, R Mylavarapu, S Geng J C Sanchez, D Rothen, A Prasad*, “Common marmoset (Callithrix jacchus) as a primate model for behavioral neuroscience studies”, Journal of Neuroscience Methods, doi: 10.1016/j.neumeth.2017.04.004 (2017)
- N W Prins, J C Sanchez, A Prasad*, “Feedback for reinforcement learning based brain-machine interfaces using confidence metrics”, Journal of Neural Engineering, vol 14(3) (2017)
- A Prasad*, Q-S Xue, R Dieme, V Sankar, R C Mayrand, T Nishida, W J Streit, J C Sanchez, “Abiotic-biotic characterization of Pt/Ir microelectrode arrays in chronic implants”, Frontiers in Neuroengineering, 7:2. doi: 10.3389/fneng.2014.00002 (2014)
- N Prins*, J C Sanchez, A Prasad, “Handling uncertainty in biological critic feedback in actor-critic reinforcement learning based brain machine interfaces”, Frontiers in Neuroscience, doi: 10.3389/fnins.2014 (2014)
- V Sankar, E Patrick, R Dieme, J C Sanchez, A Prasad*, T Nishida, “Electrode impedance analysis of chronic tungsten micro-wire neural implants: understanding abiotic vs. biotic contributions”, Frontiers in Neuroengineering, doi: 10.3389/fneng.2014.00002 (2014)
- S Roset*, K Gant, A Prasad, J C Sanchez, “An adaptive brain actuated system for augmenting rehabilitation”, Frontiers in Neuroscience, doi: 10.3389/fnins.2014.00415 (2014)
- A Prasad*, Q-S Xue, V Sankar, T Nishida, G Shaw, W J Streit, J C Sanchez, “Comprehensive characterization and failure modes of tungsten microwire arrays in chronic neural implants”, Journal of Neural Engineering, 9(5): 056015 (2012)
- A Prasad*, J C Sanchez, “Quantifying long-term microelectrode array functionality using chronic in vivo impedance testing”, Journal of Neural Engineering, 9(2):026028 (2012)
- W J Streit*, Q S Xue, A Prasad, V Sankar, E Knott, A Dyer, J Reynolds, T Nishida, G Shaw, J C Sanchez, “Electrode failure: tissue, electrical, and material responses”, IEEE PULSE, 3(1), pp. 30-33 (2012)
- A Prasad*, M Sahin, “Can motor volition be extracted from the spinal cord?”, Journal of Neuroengineering and Rehabilitation, 9(1):41 (2012)
- A Prasad, M Sahin*, “Characterization of neural activity recorded from the descending tracts of the rat spinal cord”, Frontiers in Neuroscience, 4:21. doi:10.3389/fnins.2010.00021 (2010)
- A Prasad, M Sahin*, “Extraction of motor activity from the cervical spinal cord of behaving rats”, Journal of Neural Engineering, 3(4), pp. 287-292 (2006)
Society for Neuroscience (SfN)
Biomedical Engineering Society (BMES)