Award Abstract # 1555720
EAGER: Towards High-throughput Nanophotonic Brain-Machine Interfaces

NSF Org: CBET
Division of Chemical, Bioengineering, Environmental, and Transport Systems
Recipient: THE RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK
Initial Amendment Date: September 4, 2015
Latest Amendment Date: September 4, 2015
Award Number: 1555720
Award Instrument: Standard Grant
Program Manager: Aleksandr Simonian
asimonia@nsf.gov
 (703)292-2191
CBET
 Division of Chemical, Bioengineering, Environmental, and Transport Systems
ENG
 Directorate for Engineering
Start Date: September 1, 2015
End Date: August 31, 2018 (Estimated)
Total Intended Award Amount: $299,928.00
Total Awarded Amount to Date: $299,928.00
Funds Obligated to Date: FY 2015 = $299,928.00
History of Investigator:
  • Josep Jornet (Principal Investigator)
    j.jornet@northeastern.edu
  • Michal Stachowiak (Co-Principal Investigator)
Recipient Sponsored Research Office: SUNY at Buffalo
520 LEE ENTRANCE STE 211
AMHERST
NY  US  14228-2577
(716)645-2634
Sponsor Congressional District: 26
Primary Place of Performance: SUNY at Buffalo
Davis Hall
Buffalo
NY  US  14260-4200
Primary Place of Performance
Congressional District:
26
Unique Entity Identifier (UEI): LMCJKRFW5R81
Parent UEI: GMZUKXFDJMA9
NSF Program(s): EFRI Research Projects
Primary Program Source: 01001516DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 010E, 7916, 8089
Program Element Code(s): 763300
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041

ABSTRACT

1555720(Jornet)

For many decades, the interaction between humans and machines has been restricted to the exchange of visual, auditory and tactile information. A conceptual analysis of the existing human-machine interfaces (HMIs) reveals that the amount of useful information that they can transfer is generally not limited by the capabilities of the human brain or those of the machine processor, but by the interfaces between them, such as the sensor organs that are required to handle visual, auditory and tactile information. This is especially true for people with developmental- and aging-related disabilities, whose sensor organs or musculoskeletal system further limit the functionality of traditional HMIs. To overcome such limitation, several brain-machine interfaces (BMIs), which establish a direct path between the brain and a remote machine, have been proposed in the last decade. For example, electroencephalogram (EEG) signals have been successfully utilized to control machines in a non-invasive way and with high temporal resolution. However, EEG-based BMIs cannot be utilized to read the activity from individual neurons, but only their collective response. Similarly, optogenetics-based BMIs, which rely on the use of light to interact with genetically modified neurons in the brain, can be utilized to more accurately read or control the neuronal activity in the brain. However, existing optical devices used for BMIs are highly invasive and difficult to interface with single neurons.

In this project, novel nanophotonic BMIs will be developed by leveraging the state of the art in nanophotonics, nanoelectronics and wireless communications. The proposed technology relies on the use of a distributed network of nano-devices to monitor and control the neuronal activity of the human brain with very high spatial and temporal accuracy and in a minimally invasive way. This technology is expected to significantly change the way in which humans interact with machines and can significantly improve the quality of life of people with disabilities, by providing them a transformative way to interact with the environment and restoring functional abilities as well as cognition capabilities.

The objective of the proposed project is to prove the feasibility of novel nanophotonic brain-machine interfaces based on the use of a distributed network of nano-devices to monitor and control the neuronal activity in the brain. The fundamental idea is to replace existing micro-led arrays and micro-photodetector arrays by a network of coordinated nano-devices, which are able to optically excite individual neurons and measure their activity. The benefits of this approach are several. First, the very small size of optical nano-antennas, below one micrometer in the largest dimension, enables the possibility to measure the neuronal activity in a single neuron with very high accuracy. In addition, the total size of each individual nano-device is expectedly below several tens of cubic micrometers, thus minimizing the invasiveness of this approach. Moreover, by operating at optical frequencies, a very high temporal resolution is possible, which can enable the measurement of high-frequency time-transients in the neuronal activity.
Within this long-term goal, the focus of this two-year EAGER project is on establishing the foundations of distributed neuronal activity monitoring with cooperative nano-devices for next-generation nanophotonic brain-machine interfaces. Contributions will be made along the following three main thrusts: i) Design of optical nano-antennas for efficient detection of visible electromagnetic radiation generated by neuronal activity; ii) Development of a neuronal platform for experimental optogenetics; and, iii) System-level design guidelines for nanophotonic BMIs.

In terms of broader impact, the project is expected to pave the way for the development of high-throughput nanophotonic BMIs. The proposed approach can significantly simplify and reduce the cost of existing single-neuron monitoring and control platforms, with increased spatial and temporal resolutions. Nanophotonic BMIs have the potential to significantly improve the quality of life of people with disabilities, by providing them a new way to bidirectionally interact with machines and, ultimately, their environment. In particular, the creation of a "direct-path" between the brain and external machines can help to overcome the limitations of people with general or aging-related disabilities and restore human functional abilities and even cognition. For example, neural signals from the brain could be utilized to directly control a computer or even an exoskeleton. Similarly, the proposed technology could help to develop transformative treatments for many developmental- and aging-related diseases, such as Alzheimer's disease or Schizophrenia, whose origin lies at communication problems between consecutive neurons.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 35)
Abbasi, Qammer H. and Yang, Ke and Chopra, Nishtha and Jornet, Josep Miquel and Abuali, Najah Abed and Qaraqe, Khalid A. and Alomainy, Akram "Nano-Communication for Biomedical Applications: A Review on the State-of-the-Art From Physical Layers to Novel Networking Concepts" IEEE Access , v.4 , 2016 10.1109/ACCESS.2016.2593582 Citation Details
A. Dimitri, L. Bayona Chuye, S. Dhiman ,P. Sarder, M.K. Stachowiak, E.K. Stachowiak "iPSC Derived Cerebral Organoids Reveal Early Developmental Malformations In Schizophrenia," Proc. of ASCB Conference , 2017
Balasubramaniam, Sasitharan and Wirdatmadja, Stefanus A. and Barros, Michael Taynnan and Koucheryavy, Yevgeni and Stachowiak, Michal and Jornet, Josep Miquel "Wireless Communications for Optogenetics-Based Brain Stimulation: Present Technology and Future Challenges" IEEE Communications Magazine , v.56 , 2018 10.1109/MCOM.2018.1700917 Citation Details
C. A. Benson, J. Kimm, M. Nafari, Z. Zhu, D. Huangfu, T. A. Ignatowski, P. Claus, J. M. Jornet, M. K. Stachowiak, and E. K. Stachowiak "In vitro generation and modification of human neuronal networks and photonic-genetic analyses" Proc. of Society for Neuroscience , 2016
Donohoe, Michael and Balasubramaniam, Sasitharan and Jennings, Brendan and Jornet, Josep Miquel "Powering In-Body Nanosensors With Ultrasounds" IEEE Transactions on Nanotechnology , v.15 , 2016 10.1109/TNANO.2015.2509029 Citation Details
Donohoe, Michael and Jennings, Brendan and Jornet, Josep Miquel and Balasubramaniam, Sasitharan "Nanodevice Arrays for Peripheral Nerve Fascicle Activation Using Ultrasound Energy-Harvesting" IEEE Transactions on Nanotechnology , v.16 , 2017 10.1109/TNANO.2017.2723658 Citation Details
Elayan, Hadeel and Johari, Pedram and Shubair, Raed M. and Jornet, Josep Miquel "Photothermal Modeling and Analysis of Intrabody Terahertz Nanoscale Communication" IEEE Transactions on NanoBioscience , v.16 , 2017 10.1109/TNB.2017.2757906 Citation Details
Elayan, Hadeel and Shubair, Raed M. and Jornet, Josep M. "Bio-electromagnetic THz propagation modeling for in-vivo wireless nanosensor networks" 2017 11th European Conference on Antennas and Propagation (EUCAP) , 2017 10.23919/EuCAP.2017.7928627 Citation Details
Elayan, Hadeel and Shubair, Raed M. and Jornet, Josep M. "Characterising THz propagation and intrabody thermal absorption in iWNSNs" IET Microwaves, Antennas & Propagation , v.12 , 2018 10.1049/iet-map.2017.0603 Citation Details
Elayan, Hadeel and Shubair, Raed M. and Jornet, Josep Miquel and Johari, Pedram "Terahertz Channel Model and Link Budget Analysis for Intrabody Nanoscale Communication" IEEE Transactions on NanoBioscience , v.16 , 2017 10.1109/TNB.2017.2718967 Citation Details
Elayan, Hadeel and Shubair, Raed M. and Jornet, Josep Miquel and Mittra, Raj "Multi-layer Intrabody Terahertz Wave Propagation Model for Nanobiosensing Applications" Nano Communication Networks , v.14 , 2017 10.1016/j.nancom.2017.08.005 Citation Details
(Showing: 1 - 10 of 35)

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

For many decades, the interaction between humans and machines has been restricted to the exchange of visual, auditory and tactile information. The analysis of the existing human-machine interfaces (HMIs) reveals that the amount of useful information that can be exchanged between humans and machines is not limited by the capabilities of the human brain or those of the machine processor, but by the interfaces between them (e.g., the speed at which we can type on a keyboard or read from a screen). To overcome such limitation, direct brain-machine interfaces (BMIs) have been developed within the last few years. Such interfaces generally rely on the use of electrodes to measure brain activity, through which control an external computer. However, electrical BMIs cannot be utilized to reversely control the brain from the computer. Recently, the use of light to control neurons and read their activity has been demonstrated thanks to the developments in the fields of biophotonics and optogenetics. Nevertheless, such optical BMIs rely on traditional optical components, which are large and cannot simply be integrated in the brain. 

The work completed during this two-year project symbolizes the first steps towards novel nanophotonic BMIs. The fundamental idea is to replace the conventional macro-sized optical devices currently utilized in existing optogenetic platforms, by a network of coordinated nano-devices, which are able both to excite individual neurons as well as to measure their activity. Each nano-device is equipped with an optical nano-transceiver and nano-antenna, which is able to both emit and detect optical radiation at a pre-established frequency or wavelength. The proposed platform enables bi-directional BMIs. In one direction, the network of nano-devices is utilized to excite the neurons with specific temporal and spatial patterns needed to trigger the desired response of the brain. In the other direction, the information from the neurons collected by the nano-devices is aggregated and relayed to an external controller for signal processing and interfacing with a machine. 

The key project outcomes of this effort are summarized as follows. First, we have developed a framework to design plasmonic nano-antennas that allow us to interact with optical signals in the same way conventional antennas allow us to interact with electromagnetic waves at radio- and micro-wave frequencies. The developed nano-antennas, when working in conjunction with nano-lasers and nano-photodetectors, can be utilized to both excite and measure the response of neurons in living systems. Second, we developed an experimental platform consisting of genetically-modified light-sensitive neuronal cells, in which the optical nano-devices have been tested. With this platform, we have been able to experimentally demonstrate and study different type of biological processes controlled by light. Finally, we have we have proposed a new architecture for nanophotonic BMIs, named wireless optogenetic neural dust, in which miniature motes, integrated by a nano-laser, nano-antenna, nano-detector, a control unit and a piezoelectric nano-generator are powered by means of ultra-sounds and able to control and monitor neurons through light. We have also studied how light propagates between the optical devices and the actual neurons to be activated, as well as how acoustic signals propagate between a brain mounted powering device and the brain implanted energy-harvesting nano-devices.

This proposed nanophotonic BMIS are expected to significantly change the way in which humans interact with machines and can significantly improve the quality of life of people with disabilities, by providing them a transformative way to interact with the environment and restoring functional abilities and even cognition. For example, the direct control of machines from the brain can help to overcome the limitations in the ?interfaces? between them, namely, the sensor organs or locomotion apparatus. At the same time, the proposed technology can help to broaden the understanding of the developmental- and aging-related diseases, such as Schizophrenia or Alzheimer, whose origin lies at communication problems between consecutive neurons, and, ultimately, enable transformative treatments.


Last Modified: 12/05/2018
Modified by: Josep M Jornet

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