Background

Databases of Coupled Half Center Oscillators

Action Potentials

Neurons are excitable cells that transmit information through electrical and chemical signaling. The main form of communication between neurons is through action potentials. During an action potential in a neuron, the cell membrane rapidly depolarizes upon the membrane potential exceeding a threshold voltage, driven by the opening of voltage-gated sodium ion channels.

Plot outlining phases of an action potential.

Models

Different quantitative models have been defined to represent the initiation and propagation of an action potential in a neuron, including the integrate-and-fire, Fitzhugh-Nagumo, and Morris-Lecar models. The Hodgkin-Huxley model is a reliable mathematical model that has withstood the test of time as a general model for neurons. The Fitzhugh-Nagumo model describes neural excitability and the Morris-Lecar model portrays the oscillatory behavior of neurons.

Databases of Coupled Half Center Oscillators

Half center oscillators (HCOs) are groups of two neurons that are not rhythmic on their own but when coupled, can produce rhythmic outputs. They are an integral part of central pattern generators (CPGs) which are networks of spinal neurons capable of producing rhythmic patterns without sensory input in organisms [6]. These neural circuits are involved in everyday activities such as breathing, walking, and digestion [7]. Existing work has included the construction of a queryable, computational database of simulations of the half-center oscillator model, a common component of central pattern generators, with varying parameters using a brute-force approach [8]. Classifying different simulations of the electrical activity of oscillator interneurons of a leech central pattern generator by activity characteristics allowed for further analysis of the neurons’ intrinsic and functional properties [8]. Similarly, database construction may be applied to other central pattern generator models and neuron models such as Hodgkin-Huxley in order to gain understanding of how different sets of parameters affect system stability and modulatability and relate to more biological implications. Assembly of this information may also help inform physical experiments, such as in determining reasonable conditions in the modulation of neuronal gap junction circuits in animal organisms [9].

Dynamic Clamp

Various software and hardware have been used to design what is referred to as a dynamic clamp, which uses computation to introduce artificial conductances into biological neurons [13]. These systems can be connected to real neurons to sample membrane potentials in real time to determine current to be driven into the cell [13]. The ability of the dynamic clamp to recreate the electrophysiological conditions of different ion channels allows for it to be used to simulate the effects of applying different drugs to the neurons and investigating their effect in initiating potentials in neuron bursting and spiking. For purposes of this project, the dynamic clamp in use had to be affordable and accessible.

NeuroDyn

CPG models and information can be implemented in many ways including in neuromorphic hardware, neuroprostheses, and three-dimensional models. One such device called NeuroDyn is an analog, silicon, very large scale integration (VLSI) chip that has 4 spiking neurons, 12 conductance-based synapses, and 384 digitally programmable parameters associated with the neurons [11]. It uses low power and compact circuit integration [12] to present a novel neuromorphic engineering device focused on accurately replicating ion channel kinetics and biophysical detail [11]. NeuroDyn has been studied under a wide range of biophysical parameters under a continuous-time platform using the Hodgkin-Huxley and Morris-Lecar models as well as the following three gating variables: sodium, potassium, and leak [12].

Page updated

Google Sites

Report abuse