Search

Wearable devices and medical sensors revolutionize health monitoring, raising concerns about data privacy in ML for healthcare. This tutorial explores FL and BC integration, offering a secure and privacy-preserving approach to healthcare analytics. FL enables decentralized model training on local devices at healthcare institutions, keeping patient data localized. This facilitates collaborative model development without compromising privacy. However, FL introduces vulnerabilities. BC, with its tamper-proof ledger and smart contracts, provides a robust framework for secure collaborative learning in FL. After presenting a taxonomy for the various types of data used in ML in medical applications, and a concise review of ML techniques for healthcare use cases, this tutorial explores three integration architectures for balancing decentralization, scalability, and reliability in healthcare data. Furthermore, it investigates how BCFL enhances data security and collaboration in disease prediction, medical image analysis, patient monitoring, and drug discovery. By providing a tutorial on FL, blockchain, and their integration, along with a review of BCFL applications, this paper serves as a valuable resource for researchers and practitioners seeking to leverage these technologies for secure and privacy-preserving healthcare ML. It aims to accelerate advancements in secure and collaborative healthcare analytics, ultimately improving patient outcomes.

This paper predicts the ability to externally control the firing times of a cortical neuron whose behavior follows the Izhikevich neuron model. The Izhikevich neuron model provides an efficient and biologically plausible method to track a cortical neuron's membrane potential and its firing times. The external control is a simple optogenetic model represented by an illumination source that stimulates a saturating or decaying membrane current. This paper considers firing frequencies that are sufficiently low for the membrane potential to return to its resting potential after it fires. The time required for the neuron to charge and for the neuron to recover to the resting potential are numerically fitted to functions of the Izhikevich neuron model parameters and the peak input current. Results show that simple functions of the model parameters and maximum input current can be used to predict the charging and recovery times, even when there are deviations in the actual parameter values. Furthermore, the predictions lead to lower bounds on the firing frequency that can be achieved without significant distortion., Comment: 12 pages, 11 figures, 7 tables. Submitted for publication. Portions of this work appeared previously as arXiv:1710.11569, which is the conference version of this article

In this paper, an algorithm is presented to calculate the transition rates between adjacent mesoscopic subvolumes in the presence of flow and diffusion. These rates can be integrated in stochastic simulations of reaction-diffusion systems that follow a mesoscopic approach, i.e., that partition the environment into homogeneous subvolumes and apply the spatial stochastic simulation algorithm (spatial SSA). The rates are derived by integrating Fick's second law over a single subvolume in one dimension (1D), and are also shown to apply in three dimensions (3D). The proposed algorithm corrects the derived rates to ensure that they are physically meaningful and it is implemented in the AcCoRD simulator (Actor-based Communication via Reaction-Diffusion). Simulations using the proposed method are compared with a naive mesoscopic approach, microscopic simulations that track every molecule, and analytical results that are exact in 1D and an approximation in 3D. By choosing subvolumes that are sufficiently small, such that the Peclet number associated with a subvolume is sufficiently less than 2, the accuracy of the proposed method is comparable with the microscopic method, thus enabling the simulation of advection-reaction-diffusion systems with the spatial SSA., Comment: 12 pages, 9 figures. Submitted to IEEE Transactions on NanoBioscience

This paper introduces the application of game theory to understand noisy real-time signalling and the resulting behavioural dynamics in microscopic populations such as bacteria and other cells. It presents a bridge between the fields of molecular communication and microscopic game theory. Molecular communication uses conventional communication engineering theory and techniques to study and design systems that use chemical molecules as information carriers. Microscopic game theory models interactions within and between populations of cells and microorganisms. Integrating these two fields provides unique opportunities to understand and control microscopic populations that have imperfect signal propagation. Two examples, namely bacteria quorum sensing and tumour cell signalling, are presented with potential games to demonstrate the application of this approach. Finally, a case study of bacteria resource sharing demonstrates how noisy signalling can alter the distribution of behaviour., Comment: 10 pages, 10 figures, 1 table. Submitted for publication

This paper predicts the ability to externally control the firing times of a cortical neuron whose behavior follows the Izhikevich neuron model. The Izhikevich neuron model provides an efficient and biologically plausible method to track a cortical neuron's membrane potential and its firing times. The external control is a simple optogenetic model represented by a constant current source that can be turned on or off. This paper considers a firing frequency that is sufficiently low for the membrane potential to return to its resting potential after it fires. The time required for the neuron to charge and for the neuron to recover to the resting potential are fitted to functions of the Izhikevich neuron model parameters. Results show that linear functions of the model parameters can be used to predict the charging times with some accuracy and are sufficient to estimate the highest firing frequency achievable without interspike interference., Comment: 6 pages, 8 figures, 3 tables. To be presented at the 2018 IEEE International Conference on Communications (IEEE ICC 2018) in May 2018

This paper uses a simple optogenetic model to compare the timing distortion between a randomly-generated target spike sequence and an externally-stimulated neuron spike sequence. Optogenetics is an emerging field of neuroscience where neurons are genetically modified to express light-sensitive receptors that enable external control over when the neurons fire. Given the prominence of neuronal signaling within the brain and throughout the body, optogenetics has significant potential to improve the understanding of the nervous system and to develop treatments for neurological diseases. This paper primarily considers two different distortion measures. The first measure is the delay in externally-stimulated spikes. The second measure is the root mean square error between the filtered outputs of the target and stimulated spike sequences. The mean and the distribution of the distortion is derived in closed form when the target sequence generation rate is sufficiently low. All derived results are supported with simulations. This work is a step towards an analytical model to predict whether different spike trains were observed from the same stimulus, and the broader goal of understanding the quantity and reliability of information that can be carried by neurons., Comment: 13 pages, 10 figures. To appear in IEEE Transactions on Biomedical Engineering. A conference version, which was presented at 2017 IEEE Globecom, can be found at arXiv:1704.04795

Bacteria populations rely on mechanisms such as quorum sensing to coordinate complex tasks that cannot be achieved by a single bacterium. Quorum sensing is used to measure the local bacteria population density, and it controls cooperation by ensuring that a bacterium only commits the resources for cooperation when it expects its neighbors to reciprocate. This paper proposes a simple model for sharing a resource in a bacterial environment, where knowledge of the population influences each bacterium's behavior. Game theory is used to model the behavioral dynamics, where the net payoff (i.e., utility) for each bacterium is a function of its current behavior and that of the other bacteria. The game is first evaluated with perfect knowledge of the population. Then, the unreliability of diffusion introduces uncertainty in the local population estimate and changes the perceived payoffs. The results demonstrate the sensitivity to the system parameters and how population uncertainty can overcome a lack of explicit coordination., Comment: 5 pages, 6 figures. Will be presented as an invited paper at the 2017 IEEE Information Theory Workshop in November 2017 in Kaohsiung, Taiwan

Optogenetics is an emerging field of neuroscience where neurons are genetically modified to express light-sensitive receptors that enable external control over when the neurons fire. Given the prominence of neuronal signaling within the brain and throughout the body, optogenetics has significant potential to improve the understanding of the nervous system and to develop treatments for neurological diseases. This paper uses a simple optogenetic model to compare the timing distortion between a randomly-generated target spike sequence and an externally-stimulated neuron spike sequence. The distortion is measured by filtering each sequence and finding the root mean square error between the two filter outputs. The expected distortion is derived in closed form when the target sequence generation rate is sufficiently low. Derivations are verified via simulations., Comment: 6 pages, 5 figures. Will be presented at IEEE Global Communications Conference (IEEE GLOBECOM 2017) in December 2017

This paper introduces AcCoRD (Actor-based Communication via Reaction-Diffusion) version 1.0. AcCoRD is a sandbox reaction-diffusion solver designed for the study of molecular communication systems. It uses a hybrid of microscopic and mesoscopic simulation models that enables scalability via user control of local accuracy. AcCoRD is developed in C as an open source command line tool and includes utilities to process simulation output in MATLAB. The latest code and links to user documentation can be found at https://github.com/adamjgnoel/AcCoRD/. This paper provides an overview of AcCoRD's design, including the motivation for developing a specialized reaction-diffusion solver. The corresponding algorithms are presented in detail, including the computational complexity of the microscopic and mesoscopic models. Other novel derivations include the transition rates between adjacent mesoscopic subvolumes of different sizes. Simulation results demonstrate the use of AcCoRD as both an accurate reaction-diffusion solver and one that is catered to the analysis of molecular communication systems. A link is included to videos that demonstrate many of the simulated scenarios. Additional insights from the simulation results include the selection of suitable hybrid model parameters, the impact of reactive surfaces that are in the proximity of a hybrid interface, and the size of a bounded environment that is necessary to assume that it is unbounded. The development of AcCoRD is ongoing, so its future direction is also discussed in order to highlight improvements that will expand its potential areas of application. New features that are being planned at the time of writing include a fluid flow model and more complex actor behavior., Comment: 42 pages, 21 figures, 2 tables. To appear in Nano Communication Networks

Molecular communication is an emerging paradigm for systems that rely on the release of molecules as information carriers. Communication via molecular diffusion is a popular strategy that is ubiquitous in nature and very fast over distances on the order of a micron or less. Existing closed-form analysis of the diffusion channel impulse response generally assumes that the transmitter is a point source. In this paper, channel impulse responses are derived for spherical transmitters with either a passive or absorbing receiver. The derived channel impulse responses are in closed-form for a one-dimensional environment and can be found via numerical integration for a three-dimensional environment. The point transmitter assumption (PTA) is formally defined so that its accuracy can be measured in comparison to the derived spherical transmitter impulse responses. The spherical transmitter model is much more accurate than the PTA when the distance between a transmitter and its receiver is small relative to the size of the transmitter. The derived results are verified via microscopic particle-based simulations using the molecular communication simulation platform AcCoRD (Actor-based Communication via Reaction-Diffusion). A spherical transmitter variation where molecules are released from the surface of a solid sphere is also considered via simulation., Comment: 6 pages, 2 tables, 4 figures. Presented at the 28th Biennial Symposium on Communications (BSC 2016) in June 2016

This paper presents an analytical comparison of active and passive receiver models in diffusive molecular communication. In the active model, molecules are absorbed when they collide with the receiver surface. In the passive model, the receiver is a virtual boundary that does not affect molecule behavior. Two approaches are presented to derive transforms between the receiver signals. As an example, two models for an unbounded diffusion-only molecular communication system with a spherical receiver are unified. As time increases in the three-dimensional system, the transform functions have constant scaling factors, such that the receiver models are effectively equivalent. Methods are presented to enable the transformation of stochastic simulations, which are used to verify the transforms and demonstrate that transforming the simulation of a passive receiver can be more efficient and more accurate than the direct simulation of an absorbing receiver., Comment: 6 pages, 3 figures, 3 tables. Will be presented at IEEE Globecom 2016