Courses

nanoHUB-U: Introduction to Bioelectricity (2015)

This course will use fundamental engineering and mathematical tools to understand and analyze basic bioelectricity and circuit theory in the context of the mammalian nervous system. The latest update to this course includes an introduction to basic bioelectric hardware, software, and signal processing to build your first wireless neural prosthesis! A list of recommended supplies can be found within Unit 7 in the course outline.

  1. bioelectrity
  2. bioengineering
  3. biosensors/sensing
  4. Hodgkin-Huxley Model
  5. ionic conductance
  6. nano/bio
  7. nanoHUB-U
  8. NCN Group - Biotechnology and Medicine
  9. sensors/sensing

nanoHUB-U

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nanoHUB-U

 

Scientific Overview Video

(non-YouTube version)

Course Description:

This course is for students who are interested in learning about relating the systems of the human body that involve or communicate with bioelectrical systems, including the heart, brain, muscles, and the neuromuscular system that connects them all together. The objective of this course is to establish a background and to dig deeper into some of the applications of bioelectricity to medicine. Students will learn about how bioelectricity can be used to record and control the way the body electric behaves.

What you will Learn:

  • Introduction to the nervous system, with an overview of neurons, glia, basic central and peripheral nervous system organization, and simple neural circuits (e.g. vestibulo-ocular reflex, stretch, etc…)
  • Chemical basis of electrical signals. Derivation of membrane resting potential, ion channels, Nernst and Goldman equations. Action potentials with both saltatory and passive conduction. Types of neurotransmitters along with both direct and indirect modulation pathways.
  • Electrophysiological recording techniques including: patch-clamp, voltage-clamp, extracellular electrodes etc…
  • Electrical models of cells in standard resistor and capacitor component terms. Means of modeling current flows through cellular circuits using both Matlab and SPICE. Incorporation of discrete passive and active components into the model to simulate the presence of electrodes, amplifiers, etc
  • The Hodgkin-Huxley model of the action potential. It’s validation in the giant squid axon, and what it tells us about temperature dependence as well as sensitivity to causal, nonlinear, and subthreshold oscillatory effects
  • Introduction to basic bioelectric hardware, software, and signal processing to build your first wireless neural prosthesis!

Prerequisites: 

The prerequisites of this course are freshmen physics to understand the basics of circuits, resistors and capacitors, and differential equations to follow along with the mathematics and the derivations of the core conductor cable and the Hodgkin-Huxley equations.

Recommended Reading:

Neuroscience, Dale Perves, et al

Course Outline:

Unit 1: Introduction to the Nervous System

  • L1.1: Basic Organization of CNS & PNS
  • L1.2: Simple Neural Circuits (VOR, stretch)
  • L1.3: Electrical Signals in Cells
  • L1.4: Resting Potential of Neuron Membranes
  • L1.5: Nernst Equation

Unit 2: Chemical Basis of Electrical Signals

  • L2.1: TIC and DOC
  • L2.2: Time & Space in Propagating Signals
  • L2.3: Ion Channels
  • L2.4: Post-synaptic Receptors
  • L2.5: Neurotransmitters and Pathology

Unit 3: Models of Biological Conductors

  • L3.1: Electrical Variables in Cells
  • L3.2: Core Conductor Model
  • L3.3: Observations from Action Potentials
  • L3.4: Derivation of the Cable Model
  • L3.5: Time-dependent Solutions

Unit 4: The Hodgkin-Huxley Model

  • L4.1: Alan Hodgkin and Andrew Huxley
  • L4.2: Ionic Conductances
  • L4.3: Derivation of the Hodgkin-Huxley Equation
  • L4.4: Insights from Hodgkin-Huxley
  • L4.5: Further insights from Hodgkin-Huxley

Unit 5: Applications of Bioelectricity

  • L5.1: Parkinson’s Disease
  • L5.2: Epilepsy
  • L5.3: Drug Addiction
  • L5.4: Targeted Muscle Reinnervation
  • L5.5: Optogenetics

Unit 6: Numerical Methods

  • L6.1: Discrete-Time Solutions to Continuous-Time Problems
  • L6.2: Euler Method
  • L6.3: Runge-Kutta Method
  • L6.4: Solving Hodgkin-Huxley
  • L6.5: 4th Order Runge-Kutta HH Solution in Python

Unit 7:  Practicum

  • L7.1: Analog Front End
  • L7.2: Filtering
  • L7.3: Analog-to-Digital Conversion
  • L7.4:  Full System
  • L7.5: Bioelectric Prosthesis Control

 

 

 

 

Licensing

 

Creative Commons BY License