Controlled Information Transfer Through An In Vivo Nervous System

Nitric oxide modulates NMDA receptor through a negative feedback mechanism and regulates the dynamical behavior of neuronal postsynaptic components

Nitric oxide (NO) is known to be an important regulator of neurological processes in the central nervous system which acts directly on the presynaptic neuron and enhances the release of neurotransmitters like glutamate into the synaptic cleft. Calcium influx activates a cascade of biochemical reactions to influence the production of nitric oxide in the postsynaptic neuron. This has been modeled in the present work as a system of ordinary differential equations, to explore the dynamics of the interacting components and predict the dynamical behavior of the postsynaptic neuron. It has been hypothesized that nitric oxide modulates the NMDA receptor via a feedback mechanism and regulates the dynamic behavior of postsynaptic components. Results obtained by numerical analyses indicate that the biochemical system is stimulus-dependent and shows oscillations of calcium and other components within a limited range of concentration. Some of the parameters such as stimulus strength, extracellular calcium concentration, and rate of nitric oxide feedback are crucial for the dynamics of the components in the postsynaptic neuron.

N4Sim: The first Nervous NaNoNetwork Simulator with Synaptic Molecular Communications

The unconventional nature of molecular communication necessitates contributions from a host of scientific fields making the simulator design for such systems to be quite challenging. The nervous system is one of the largest and most important nanonetworks of the body. Several molecular and nano communication simulators exist in literature along with a few neural network simulators, however, most existing simulators are not specific for the nervous system since they ignore the synaptic diffusion because of the computational complexity required to model it. Additionally, information and communication theoretical (ICT) analysis of the system is not directly supported by existing neural network simulators. In this work, we present and describe Neural NaNoNetwork Simulator, N4Sim, which can resolve these issues in existing simulators. We describe key components of the simulator and methods to solve the synaptic communication in a fast and efficient manner. Our model for the synaptic communication channel is comparable in accuracy to those achieved by Monte Carlo simulations while using a fraction of time and processing resources. The presented simulator opens a large set of design options for applications in nervous system.

A Co-purification Method for Efficient Production and Src Kinase-mediated Phosphorylation of Aplysia Cortactin

Cortactin is an actin-binding protein that regulates processes like cell migration, endocytosis, and tumor cell metastasis. Although cortactin is associated with actin-cytoskeletal dynamics in non-neuronal cells and cell-free systems, the exact mechanisms underlying its fundamental roles in neuronal growth cones are not fully explored. Recent reports show that Aplysia Src2 tyrosine kinase induces phosphorylation of cortactin as a mechanism to control lamellipodia protrusion and filopodia formation in cultured Aplysia bag cell neurons ( He et al., 2015 ; Ren et al., 2019 ). In order to provide in vitro evidence for Src2-mediated phosphorylation of cortactin, we developed a robust and cost-effective method for the efficient expression and purification of Aplysia cortactin and Src2 kinase that can be used for biochemical studies including phosphorylation assays. By co-purifying cortactin and Src kinase with a phosphatase (YopH) from Yersinia enterocolitica, we eliminated the problem of non-specific phosphorylation of induced proteins by bacterial kinases and also reduced costs by bypassing the need for commercial enzymatic treatments. This protocol is reproducible and can be modified to produce homogenous non-phosphorylated proteins during recombinant protein expression in Escherichia coli.

Engineering calcium signaling of astrocytes for neural-molecular computing logic gates

This paper proposes the use of astrocytes to realize Boolean logic gates, through manipulation of the threshold of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hbox {Ca}^{2+}$$\end{document}Ca2+ ion flows between the cells based on the input signals. Through wet-lab experiments that engineer the astrocytes cells with pcDNA3.1-hGPR17 genes as well as chemical compounds, we show that both AND and OR gates can be implemented by controlling \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hbox {Ca}^{2+}$$\end{document}Ca2+ signals that flow through the population. A reinforced learning platform is also presented in the paper to optimize the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hbox {Ca}^{2+}$$\end{document}Ca2+ activated level and time slot of input signals \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_b$$\end{document}Tb into the gate. This design platform caters for any size and connectivity of the cell population, by taking into consideration the delay and noise produced from the signalling between the cells. To validate the effectiveness of the reinforced learning platform, a \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hbox {Ca}^{2+}$$\end{document}Ca2+ signalling simulator was used to simulate the signalling between the astrocyte cells. The results from the simulation show that an optimum value for both the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hbox {Ca}^{2+}$$\end{document}Ca2+ activated level and time slot of input signals \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_b$$\end{document}Tb is required to achieve up to 90% accuracy for both the AND and OR gates. Our method can be used as the basis for future Neural–Molecular Computing chips, constructed from engineered astrocyte cells, which can form the basis for a new generation of brain implants.

Impact of Long Term Plasticity on Information Transmission Over Neuronal Networks

The realization of bio-compatible nanomachines would pave the way for developing novel diagnosis and treatment techniques for the dysfunctions of intra-body nanonetworks and revolutionize the traditional healthcare methodologies making them less invasive and more efficient. The network of these nanomachines is aimed to be used for treating neuronal diseases such as developing an implant that bridges over the injured spinal cord to regain its normal functionality. Thus, nanoscale communication paradigms are needed to be investigated to facilitate communication between nanomachines. Communication among neurons is one of the most promising nanoscale communication paradigm, which necessitates the thorough communication theoretical analysis of information transmission among neurons. The information flow in neuro-spike communication channel is regulated by the ability of neurons to change synaptic strengths over time, i.e. synaptic plasticity. Thus, the performance evaluation of the nervous nanonetwork is incomplete without considering the influence of synaptic plasticity. In this paper, we focus on information transmission among hippocampal pyramidal neurons and provide a comprehensive channel model for MISO neuro-spike communication, which includes axonal transmission, vesicle release process, synaptic communication and spike generation. In this channel, the spike timing dependent plasticity (STDP) model is used to cover both synaptic depressiofan and potentiation depending on the temporal correlation between spikes generated by input and output neurons. Since synaptic strength changes depending on different physiological factors such as spiking rate of presynaptic neurons, number of correlated presynaptic neurons and the correlation factor among them, we simulate this model with correlated inputs and analyze the evolution of synaptic weights over time. Moreover, we calculate average mutual information between input and output of the channel and find the impact of plasticity and correlation among inputs on the information transmission. The simulation results reveal the impact of different physiological factors related to either presynaptic or postsynaptic neurons on the performance of MISO neuro-spike communication. Moreover, they provide guidelines for selecting the system parameters in a bio-inspired neuronal network according to the requirements of different applications.

Analysis of Light Propagation on Physiological Properties of Neurons for Nanoscale Optogenetics

Miniaturization of implantable devices is an important challenge for future brain-computer interface applications, and in particular for achieving precise neuron stimulation. For stimulation that utilizes light, i.e., optogenetics, the light propagation behavior and interaction at the nanoscale with elements within the neuron is an important factor that needs to be considered when designing the device. This paper analyzes the effect of light behavior for a single neuron stimulation and focuses on the impact from different cell shapes. Based on the Mie scattering theory, the paper analyzes how the shape of the soma and the nucleus contributes to the focusing effect resulting in an intensity increase, which ensures that neurons can assist in transferring light through the tissue toward the target cells. At the same time, this intensity increase can in turn also stimulate neighboring cells leading to interference within the neural circuits. This paper also analyzes the ideal placements of the device with respect to the angle and position within the cortex that can enable axonal biophoton communications, which can contain light within the cell to avoid the interference.