# User talk:Jmn96/Final Term Paper

From BIOL 300 Wiki

## Contents

## Student Comments

- Introduction: Great start to the paper, especially the addition of the Significance section. If I had to make a change, I would put the description of the HH model before Izhikevich so that the reader can see a progression from the complexities of HH, then the simplifications of Izhikevich.
- Description: In the assumptions section, I would add "except where indicated" to the current assumption. In the RZ spike behavior, there is a change in the continuity of the spike.
- Results: Make sure to specify that while the giant squid axon is a perfectly valid type of neuron, the limitations of using a model solely based on it are that it cannot be applied to certain scenarios. I'm assuming you will provide the full Bifurcation analysis later.
- Discussion: It may flow better to have the assumptions, limitations, and discrepancies before you begin talking about implications and the overall analysis. That way, the reader can determine whether or not the results can be taken at face value.

--James Mcginnity (talk) 15:52, 30 April 2017 (EDT)

## Instructor Comments

- Term paper survey submitted with term paper?
- Yes.

### Introduction

- Significance of problem?
- Yes.

- Statement of hypothesis?
- Yes, but the hypothesis is rather weak, especially since Izhikevich himself does not argue that his model is an accurate replica of the details of a neuron; rather it captures its general spiking behavior.

- List of references?
- Only 8. Names of authors are misspelled in at least two of the references. This is not an adequate number of references for a scholarly introduction. 5

- Properly formatted references?
- Yes.

### Model Description

- State variables, parameters and inputs to the model clearly distinguished?
- Yes.

- Term-by-term description of model components?
- Yes.

- Have you described model assumptions?
- Yes.

- Description of equation simulation?
- Yes, but no description of any attempt to create and simulate a network of these neurons, as was done by Izhikevich.

### Results

- Results described and compared to original paper?
- Yes, except for the network.

- Have you addressed the original biological hypothesis?
- Yes, but the comparison of the regular spiking Izhikevich neuron to the Hodgkin Huxley model is rather superficial. How do you know that if you adjusted a, b, c, and d you could not get a better match to the spiking properties of the Hodgkin/Huxley model? Also, you have misspelled the name of the person who did the Hodgkin Huxley bifurcation analysis - John Guckenheimer.

- Figures and legends to show results?
- Yes; bifurcation diagram could be much clearer.

- Discrepancies relative to original model?
- Discussed and described.

- Uploaded Mathematica file?
- Yes.

### Discussion

- How well does the model support the original hypothesis?
- Well discussed, but the original hypothesis is not a very strong one.

- Support for hypothesis and assumptions from other data in the literature?
- Some support. Many more references should have been consulted. Much of the discussion repeats points made in the Results section. Greater depth would have made this much better.

- Limitations of results?
- Discussed, but could have been more thorough.

- Discrepancies and how they affect conclusions?
- Discussed, but could have been more thorough.

- Relationship to other work in the field?
- The most recent reference is from 2007; has nothing significant happened in the last ten years?

- Discussion of future work?
- What is proposed is largely completing the replication of the original paper. Again, more depth with appropriate literature citations would have strengthened this section.

### Overall Term Paper Quality

- How well was the model replicated?
- The network aspect of the model was not replicated at all. Otherwise, it was well replicated.

- Based on the term paper, how well did you understand the material?
- Understanding is very good, though some of the discussion of the dynamical systems analysis could have been better.

- How well written is the term paper?
- On the whole, well written.

- How hard was the model extension that you did?
- Moderately difficult; but this has already been done by Izhikevich.

- How good was the extension?
- This could have been better described.

- Mathematica code clear and well annotated?
- Yes, beautifully annotated.

- Mathematica code generates figures when evaluated?
- Not all code generated figures when evaluated.

On the whole, this is a good to very good term paper. More depth in the Introduction and the Discussion by reading, analyzing and citing recent literature would have made this a much stronger paper. In addition, not replicating even a small network meant that a significant part of the paper was not replicated. The comparison to the original Hodgkin Huxley model could have been more focused and more rigorous.

--Hillel Chiel (talk) 09:30, 12 May 2017 (EDT)