Brain Computer Interfaces, Neural Engineering, NeuroRobotics

Read the downloadable file, then watch the video lecture, and then complete the quiz. Use the learning objectives below to support your reading.

Learning Objectives:

• Sketch examples of intracellular and extracellular neural recordings

• Describe the differences between local field potentials and single unit recordings

• Explain (verbally and visually) the relationship between a raster plot, multi-unit activity recording, and a local field potential

• Quantify the relative values for amplitude and duration of various neural recordings

• Identify a neural recording based on an labeled plot

Reading Material:

1. Introduction to Neural Recordings

Read the linked articles, then watch the video lecture, and then complete the quiz. Use the learning objectives below to support your reading.

Learning Outcomes:

• Describe the flow of neural information from thought to action

• Explain the "motor homunculus"

• Describe the components that make up a motor unit

• Sketch an example EMG waveform

• Explain the relationship between muscle activation and EMG recording

Reading Material:

1. EMG - Motion Lab Systems

2. The Anatomy of Movement - Brain Connection

These supplemental readings can help reinforce your understanding of the topics.

1. Kandel - Principles of Neural Science - Chapter 34 "The Motor Unit and Muscle Action" - This book chapter provides an excellent summary of neuromuscular encoding. This will be a required reading towards the end of class but is recommended now as supplemental reading.

2. Kolb - Introduction to Brain and Behavior - Chapter 10 "How Does the Brain Produce Movement" - This book chapter provides a nice summary of the Neuromuscular Pathway. This chapter may available for free online through the North Dakota State University.

For those interested in applying their knowledge, this optional research project provides an opportunity to explore real-time EMG control through some low-cost hardware and open-source software. We provide example code in MATLAB.

Read the linked articles, then watch the video lecture, and then complete the quiz. Use the learning objectives below to support your reading.

Learning Outcomes:

• Calculate firing rates from a raster plot

• Model the activity of neurons to decode intended movement

• Explain the concept of "population vectors" in neural decoding

• Describe how firing rate of neurons can be used by models to predict intent

• Provide a real-world explain of neural decoding

Reading Material:

1. Hochberg, Nature, 2006

2. Georgopoulous, Science, 1986

These supplemental readings can help reinforce your understanding of the topics.

1. Taylor, Science, 2002 - Seminal work in the field demonstrating population dynamics for BCI control of a computer mouse. Available online.

2. Velliste, Nature, 2008 - Seminal work in the field demonstrating population dynamics for BCI control of a prostheses. Available online.

Read the linked articles, then watch the video lecture, and then complete the quiz. Use the learning objectives below to support your reading.

Learning Outcomes:

• Explain the pros and cons of decoding neural information at various parts of the body (e.g., brain vs peripheral nerves)

• Compare and contrast spike recordings and population recordings

• Compare and contrast continuous and discrete decoders, and provide examples of each

• Estimate the rough firing rate of neurons

• Identify what features of the neural recordings are used to predict intent

• List various performance metrics that can be used to assess a neural decoder

  
  

Reading Material:

1. Warren, IEEE, 2016.

These supplemental readings can help reinforce your understanding of the topics.

• Raspopovic, J. Neurosci. Methods, 2020  - A great review focusing exclusively on peripheral nerve recordings & decoding.

• Downey, J. Neural Eng., 2018 - A paper highlighting the stability of intracortical recordings.

• Hermann, Critical Reviews of Biomedical Engineering, 2019 - A review on immune responses to intracortical electrode arrays.

• Wu, Neural Computation, 2006 - An original paper formulating the use of a Kalman filter for neural decoding.

Read the linked article, then watch the video lecture, and then complete the quiz. Use the learning objectives below to support your reading.

Learning Outcomes:

• Explain the importance of non-linearity in neural networks

• Calculate the output of a neural network model for a given input

• Describe how abstract filters can be used by a neural network to gain a higher level understanding of how signals correlate

• Identify what parameters of a neural network are trained versus defined (explicitly) by the user

• Sketch a neural network model based on a verbal description (e.g., of the nodes, weights, etc.)

• Describe a neural network (verbally and written out) based on an image

  
  

Reading Material:

1. Tatan, Medium, Understanding CNNs

These supplemental readings can help reinforce your understanding of the topics.

1. Krogh, Nature Biotechnology, 2008 - A short review on Artificial Neural Networks.

For those interested in applying their knowledge, this optional research project provides an opportunity to explore neural decoding using an artificial neural network. We provide example code in MATLAB.

Read the linked article and downloadable file, then watch the video lecture, and then complete the quiz. Use the learning objectives below to support your reading.

Learning Outcomes:

• Draw stimulation waveforms based on written and verbal descriptions

• Label relevant parts of stimulation waveform sketches

• Explain the importance of charge-balanced waveforms in neural stimulation

• Calculate how much charge is delivered from a given neural stimulation waveform

  
  

Reading Material:

1. Lily, Science, 1955.

2. FDA Guidance on Implanted BCIs, 2021.

These supplemental readings can help reinforce your understanding of the topics.

1. Liu, IFESS, 2008 - This is a short summary of capacitive coupling. A blocking capacitor is used in most stimulation devices to help ensure a net-zero charge delivery.

2. Merrill, J. Neurosci. Methods, 2005 - This is an excellent review of neural stimulation. This will be a required reading later, but you can get a head start now!

3. Abbott BurstDR Stimulation - This is a 2022 webpage from Abbott describing their newly patented "Burst Stimulation" which is referred to in the FDA documentation.

Read the linked articles, then watch the video lecture, and then complete the quiz. Use the learning objectives below to support your reading.

Learning Outcomes:

• Identify which parameters of neural stimulation devices should be regulated to ensure safety

• Perform a safety analysis of neural stimulation

• Describe the limitations of the Shannon-McCreery safety analysis

Reading Material:

1. McCreery, IEEE TBME, 1990.

2. Shannon, IEEE TBME, 1992.

These supplemental readings can help reinforce your understanding of the topics.

1. Cogan, J. Neural Eng., 2016 - This is a more modern review of stimulation safety that builds upon the Shannon limit. This paper was used heavily to set the current FDA guidance.