Elsevier

Computer Networks

Volume 171, 22 April 2020, 107137
Computer Networks

Deep brain drug-delivery control using vagus nerve communications

https://doi.org/10.1016/j.comnet.2020.107137Get rights and content

Abstract

Vagus nerve stimulation (VNS) uses electrical impulses applied at the neck in order to mitigate the effects of, for example, epileptic seizures. We propose using VNS to provide data pulses to communicate with a drug-delivery system embedded near the brainstem. We model the generation of a vagus nerve compound action potential (CAP), calculating the signal attenuation and the resulting transmission range. The metabolic cost of CAP transmission in terms of the use of adenosine triphosphate (ATP) is also calculated. The channel capacity for on-off keying (OOK) is computed from the CAP characteristics, the neural refractory period and the level of background neural noise. The resulting low bit-rate, unidirectional asynchronous transmission system is analysed for the use of different methods of forward error correction (FEC) to improve bit-error rate (BER). We show a proposed data packet structure that could deliver instructions to an embedded drug-delivery system with multiple addressable drug reservoirs. We also analyse the scope for powering the drug-delivery system with energy harvested from cerebrospinal glucose.

Introduction

Communicating with powered implants embedded in the human body, such as cardiac pacemakers or defibrillators, is an increasingly important part of medical treatment. Wireless communications systems provide a bidirectional flexible link over short ranges [1], but place power requirements of hundreds of microwatts on an implant [2]. Apart from the power requirements, the transmission of commands from an external wireless electromagnetic (EM) module to an implanted device does create security implications and may be subject to hacking [3]. An alternative method is to use the peripheral or cranial nervous system in the body to transport data commands from a transmitter at one point on a nerve to an embedded receiver at another point. The use of neural communications is part of wider research into implanted devices at the micro and nano level [4] where restrictions in antenna size will limit the use of EM systems.

Data communications using action potentials (AP) along a single neuronal axon is proposed by Parcerisa-Giné and Akyildiz [5] as an option for providing a physical link between embedded micro devices. Channel models for communications using neural spikes (APs) and neurotransmitters between hippocampal neurons have been developed by Malak and Akan [6], Ramezani and Akan [7] and Veletić et al. [8]. Data communications through the single median giant axon of the earthworm was modelled by Abbasi et al. [9] who calculated a data throughput based on four different stimulus frequencies, with each frequency representing two bits of information. A neuron channel model using a sub-threshold (non-spiking) stimulus was proposed by Khodaei and Pierobon [10], [11], though sub-threshold impulses have a very short range along an axon [12]. Single neurons are, however, difficult to access and the placement of transmitters and receivers would be particularly challenging. Consequently, it could be more practical to examine the collective stimulus of multiple neurons forming a compound action potential (CAP) to provide a neural data pulse.

There is ongoing research into the use of vagus nerve stimulation (VNS) for the treatment of epileptic seizures [13], depression, heart failure [14], arthritis [15] and Crohn’s disease. At present a VNS system relies on human intervention by the physician and patient to programme the duration and intensity of the stimulus pulses. A more flexible biofeedback system is proposed by Ward et al. [16] using the degree of measured nerve activation to control stimulus delivery and provide a personalised stimulus profile. Non-stimulus based therapies include drug-delivery to the brain, although the protective blood-brain barrier (BBB) presents a challenge for the absorption of drugs [17] to treat, for example, cancer tumours. A drug-delivery system for treating epilepsy is described by Salam et al. [18] with embedded electrodes to detect seizures and a micromechanical pump to deliver the drug from a refillable reservoir located under the scalp. A neural probe with an electrophoretic microfluidic ion pump is proposed by Proctor et al. [19] to deliver variable doses of a single drug across an ion-exchange membrane. Another release mechanism is electrothermal membrane activation, first proposed by Santini et al. [20], where a metallic membrane covers a drug reservoir. An electrical current ruptures the membrane by heating and the drug reservoir releases its contents. Either of these delivery systems could be controlled by a local processor and receive release commands from an external source along a neural pathway.

Power could be delivered to an implanted device by a long-life battery [21], although this would have to be replaced at regular intervals, requiring repeated surgical intervention. The alternative is to use some form of energy harvesting to power the implant directly or to recharge a battery. Ultrasound energy harvesting operates at shallow skin depths and will not penetrate through the bone of the skull. It is possible to power implants wirelessly with (i) near-field short-range EM inductive resonant coupling using coiled antennas at frequencies up to 20 MHz, (ii) mid-field coupling (900 MHz) or (iii) far-field (2.5 GHz) EM powering [22]. The use of EM power harvesting is subject to technical constraints to meet recommended safety levels and prevent tissue damage through excessive heating [23]. The specific absorption rate (SAR) describes the quantity of EM power that can be absorbed by a tissue and is defined as:SAR=σE2ρ.The conductivity of the tissue is σ, the density is ρ and the electric field strength is E. The SAR value is expressed in Watts per kilogram and is averaged over 1 g or 10 g of tissue. In the US the exposure limits for an unrestricted environment, set by the FCC, are 4 W/kg for 10g of tissue in the extremities (hands, wrists, feet, ankles) and 1.6 W/kg for 1 g of head, neck and trunk tissue. In other jurisdictions the equivalent ICNIRP and IEEE guidelines specify 2 W/kg for 10 g of head, neck and trunk tissue and 4 W/kg for 10 g of any other limbs [24]. The SAR limits can be converted to power intensities at different frequency ranges and a typical value is 2 W/m2 for up to 200 MHz and 10 W/m2 for frequencies greater than 200 MHz [24]. Powering by EM would also require the wearing of an external powering source if true mobility was required. Ideally the implanted device should have a long-life biocompatible power harvesting system that would not have the potential to cause tissue damage and would not depend on external modules.

In previous work [25] we modelled the use of ultrasound to provide harvested power for subcutaneous nanowire-based nanodevices. We then extended that work by modelling the use of arrays of coupled nanodevices for selective neural stimulation [26]. The resulting CAPs were modelled as a data communications system (200 bit/s maximum rate) using on-off keying (OOK) [27]. Our stimulus and communications system is optimised for nerves that are at a shallow depth, are not shielded by bone and can be readily accessed for device array implantation.

In this paper we model a specific potential application: the use of neural data pulses transmitted along the vagus nerve to communicate with a programmable, multi-reservoir, drug-delivery system in the brain as shown in Fig. 1. The vagus nerve is a cranial nerve extending from the brainstem and branching to thoracic, abdominal and retroperitoneal organs. The normal neuronal signals serve to moderate functions such as heart rate, breathing and rate of digestion. Two main trunks (branches), the left and the right, can be accessed either side of the neck. The left branch of the vagus nerve, where VNS electrodes are normally placed in humans, does not include cardiac branches with motor neurons and so does not cause cardiac side effects. The main side effects are hoarseness, cough or shortness of breath [13], with no interference to normal brain function [14].

The neural stimulus system delivers current pulses ( > 0.2 mA) comparable to those delivered by FDA-approved vagus nerve stimulation (VNS) systems (0.2 mA to 5 mA). Asynchronous data packets composed of CAPs could deliver instructions to an embedded device using a unidirectional neural transmission system. Detecting neural data pulses requires lower power than receiving wireless EM signals. Unidirectional transmission implies that no acknowledgement or resend messages can be sent in the reverse direction. We, therefore, analyse the use of forward error correction (FEC) in the receiver to improve performance. The main contributions of our work are as follows:

  • A model of the generation and propagation of a stimulated neural CAP along the vagus nerve, which shows that it is possible to deliver a maximum OOK data rate of 200 bit/s at ranges between 60 mm and 100 mm;

  • An evaluation of the metabolic energy cost of CAP generation in terms of the use of adenosine triphosphate (ATP);

  • An analysis of the bit error rate (BER) and the coding gain using a selection of FEC methods;

  • A proposal for simple packet structure for programmable drug-release commands;

  • An assessment of the viability of using glucose energy harvesting for powering an implanted drug-delivery system.

This article is organised as follows: the activation of the vagus nerve is described in Section 2; the data link protocol and error correction in Section 3; the drug-delivery system components, data packet structure and powering in Section 4; and our conclusions are presented in Section 5.

Section snippets

Vagus nerve stimulation

When a neuron is stimulated, an AP propagates down the neuron’s axon to a terminating synapse [12]. The AP cycle duration, typically 5 ms, is called the Refractory Period (Tref) and a second stimulus applied during this interval will not result in another action potential. The extracellular action potential or single fibre action potential (SFAP) is measured on the outside of the neuron with respect to the surrounding extracellular medium. This is smaller in magnitude (on the order of

Neural data link protocol

The modelled neural CAP communications channel is serial, unidirectional, low bit-rate and therefore suitable for asynchronous transmission, where the sender and receiver have separate clocks. Asynchronous data link messages (packets) are of short duration to ensure that the clocks remain closely aligned to each other. A packet usually consists of a start-bit, a character coded as pulses (usually an 8-bit byte) and a stop-bit. Such a packet would have a length of 10 bits and a transmission time

Drug-delivery system

The embedded drug-delivery system that receives the data packets will have (i) an electrode attached to the vagus nerve near the brain stem to detect the CAP pulse, (ii) an amplification and conversion system to boost the signal power and create a digital bitstream, (iii) a microcontroller unit (MCU) to collect and interpret the bitstream, (iv) a drug-delivery mechanism and addressable reservoirs to respond to processor instructions and (v) a power source sufficient to meet all energy demands.

Conclusions

Using the vagus nerve for the transmission of digital CAP pulses is an advancement on existing therapeutic neurostimulation. The left branch of the vagus nerve can be accessed at the neck and is at a shallow enough depth to allow ultrasound pulses to penetrate and activate a neural stimulus array. The stimulus pulses travel towards the brainstem and can be intercepted by a receiving electrode and a drug-delivery system. The maximum OOK bit rate of 200 bit/s is constrained by the neural

CRediT authorship contribution statement

Michael Donohoe: Conceptualization, Methodology, Software, Writing - original draft. Brendan Jennings: Supervision, Writing - review & editing. Sasitharan Balasubramaniam: Supervision, Writing - review & editing.

Declaration of Competing Interest

The authors declare that they do not have any financial or nonfinancial conflict of interests.

Acknowledgements

This work is supported by the Academy of Finland FiDiPro programme for the project “Nanocommunications Networks” 2012 - 2016, and the Finnish Academy Research Fellow programme under Project no. 284531. It is also partly funded by the Irish Higher Education Authority under the Programme for Research in Third Level Institutions (PRTLI) cycle 5, which is co-funded by the European Regional Development Fund (ERDF), via the Telecommunications Graduate Initiative, and by Science Foundation Ireland via

Michael Donohoe received a BSc in Physics from University College Galway, Ireland, in 1980. He is at present a Ph.D. student in the Telecommunications Software and Systems Group (TSSG) of the Waterford Institute of Technology, Ireland. Prior to this he worked in the telecommunications industry especially in the areas of network planning, project implementation, R&D and product management. His research interests include embedded nanodevices, energy harvesting and in-body communications networks.

References (57)

  • R. Ritter et al.

    Telemetry for implantable medical devices: part 1 - media properties and standards

    IEEE Solid State Circuits Mag.

    (2014)
  • R. Sarpeshkar et al.

    Low-power circuits for brain-machine interfaces

    IEEE Trans. Biomed. Circuits Syst.

    (2008)
  • D. Malak et al.

    A communication theoretical analysis of synaptic multiple-access channel in hippocampal-cortical neurons

    IEEE Trans. Commun.

    (2013)
  • H. Ramezani et al.

    Information capacity of vesicle release in neuro-spike communication

    IEEE Commun. Lett.

    (2018)
  • M. Veletić et al.

    On the upper bound of the information capacity in neuronal synapses

    IEEE Trans. Commun.

    (2016)
  • N.A. Abbasi et al.

    Controlled information transfer through an in vivo nervous system

    Sci. Rep.

    (2018)
  • A. Khodaei et al.

    An intra-body linear channel model based on neuronal subthreshold stimulation

    2016 IEEE International Conference on Communications (ICC)

    (2016)
  • A. Khodaei et al.

    Subthreshold linear modeling of dendritic trees: acomputational approach

    2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

    (2016)
  • J. Malmivuo, R. Plonsey, Bioelectromagnetism - Principles and Applications of Bioelectric and Biomagnetic Fields,...
  • S. Krahl

    Vagus nerve stimulation for epilepsy: a review of the peripheral mechanisms.

    Surg. Neurol. Int.

    (2012)
  • R.H. Howland

    Vagus nerve stimulation

    Curr. Behav. Neurosci. Rep.

    (2014)
  • F.A. Koopman et al.

    Vagus nerve stimulation inhibits cytokine production and attenuates disease severity in rheumatoid arthritis

    Proc. Natl. Acad. Sci.

    (2016)
  • M.P. Ward et al.

    A flexible platform for biofeedback-driven control and personalization of electrical nerve stimulation therapy

    IEEE Trans. Neural Syst. Rehabil. Eng.

    (2015)
  • X. Dong

    Current strategies for brain drug delivery

    Theranostics

    (2018)
  • M.T. Salam et al.

    An implantable closedloop asynchronous drug delivery system for the treatment of refractory epilepsy

    IEEE Trans. Neural Syst. Rehabil. Eng.

    (2012)
  • C.M. Proctor et al.

    Electrophoretic drug delivery for seizure control

    Sci. Adv.

    (2018)
  • J.T. Santini Jr et al.

    A controlled-release microchip

    Nature

    (1999)
  • R. Jegadeesan et al.

    Enabling wireless powering and telemetry for peripheral nerve implants

    IEEE J. Biomed. Health Inform.

    (2015)
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    Michael Donohoe received a BSc in Physics from University College Galway, Ireland, in 1980. He is at present a Ph.D. student in the Telecommunications Software and Systems Group (TSSG) of the Waterford Institute of Technology, Ireland. Prior to this he worked in the telecommunications industry especially in the areas of network planning, project implementation, R&D and product management. His research interests include embedded nanodevices, energy harvesting and in-body communications networks.

    Dr. Brendan Jennings received the BEng and Ph.D. degrees from Dublin City University, Dublin, Ireland, in 1993 and 2001, respectively. He is the Head of Graduate Studies for the Waterford Institute of Technology, Ireland and a Principal Investigator with CONNECT, Ireland’s national centre for communications networking research. He has spent periods as a Visiting Researcher with the KTH Royal Institute of Technology, Sweden, and in EMC Research Europe, Ireland. He regularly serves on the organization and technical program committees of a number of network and service management related conferences. He will serve as Executive Chair for the IEEE ICC 2020 conference, to be held in Dublin, Ireland in June 2020. His research interests include network management, cloud computing, and nanoscale communications.

    Dr. Sasitharan Balasubramaniam received his Bachelor (Electrical and Electronic Engineering) and Ph.D. degrees from the University of Queensland in 1998 and 2005, respectively, and Masters (Computer and Communication Engineering) degree in 1999 from the Queensland University of Technology. He is currently Director of Research at the Telecommunication Software and Systems Group, Waterford Institute of Technology, Ireland, where he has worked on a number of Science Foundation Ireland projects. Sasitharan is in the Steering Committee of the ACM NanoCom conference which he co-founded. In 2018 he received the ACM/IEEE NanoCom Outstanding Milestone award, and he is also the IEEE Nanotechnology Council Distinguished Lecturer. He is currently an editor for the IEEE Internet of Things journal, Elsevier Nano Communication Networks, and Elsevier Digital Communication Networks. His current research interests includes molecular and nano communications, and Internet of (Bio-Nano) Things.

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