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2020-01-20 15:55:44 +01:00
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For new projects:
Copy project_template/ and adapt according to your needs
How to make a new project
-------------------------
Copy `project_template/` to your `project_NAME/` and adapt according to your needs.
Rename `template.tex` to `NAME.tex` and write questions.
Put data that are needed for the project into the `data/` subfolder.
Put your solution into the `code/` subfolder.
Don't forget to add the project files to git (`git add FILENAMES`).
All projects:
check for time information
Projects
--------
1) project_activation_curve
medium
@@ -22,83 +26,96 @@ b_0 is not defined
OK, difficult
no statistics, but kmeans
5) project_face_selectivity
medium-difficult
(Marius monkey data)
6) project_fano_slope
5) project_fano_slope
OK, difficult
7) project_fano_test
OK -
8) project_fano_time
6) project_fano_time
OK, medium-difficult
9) project_ficurves
7) project_ficurves
OK, medium
Maybe add correlation test or fit statistics
8) project_lif
OK, difficult
no statistics
9) project_mutualinfo
OK, medium
10) project_noiseficurves
OK, simple-medium
no statistics
11) project_numbers
simple
We might add some more involved statistical analysis
12) project_pca_natural_images
medium
Make a solution (->Lukas)
13) project_photoreceptor
OK, simple
14) project_populationvector
difficult
OK
15) project_power_analysis
medium
16) project_random_walk
simple-medium
17) project_serialcorrelation
OK, simple-medium
18) project_stimulus_reconstruction
OK, difficult
19) project_vector_strength
OK, medium-difficult
Unfinished or bad projects
--------------------------
7) project_fano_test
OK
10) project_input_resistance
medium
What is the problem with this project? --> No difference between segments
Improve questions
11) project_isicorrelations
medium-difficult
Need to finish solution
12) project_isipdffit
Too technical
13) project_lif
OK, difficult
no statistics
14) project_mutualinfo
OK, medium
15) project_noiseficurves
OK, simple-medium
no statistics
16) project_numbers
simple
We might add some more involved statistical analysis
17) project_pca_natural_images
medium
Make a solution (->Lukas)
18) project_photoreceptor
OK, simple
19) project_populationvector
difficult
OK
20) project_power_analysis
medium
11) project_isicorrelations
medium-difficult
Quite technical, need to finish solution
21) project_qvalues
-
Interesting! But needs solution.
22) project_random_walk
simple-medium
23) project_serialcorrelation
OK, simple-medium
24) project_shorttermpotentiation
Write questions
25) project_spectra
-
Once we have the spectral chapter finished
Needs improvements and a solution
26) project_stimulus_reconstruction
OK, difficult
27) project_vector_strength
OK, medium-difficult
New project ideas:
------------------
1) project_face_selectivity
Marius monkey data
We need to work out a solution and results
2) Firing rates and spikeing precision
Data: Noise AM of grasshoppers
Analysis: Spike detection, convolution rate versus ISI rate
Discussion: How does spike precision influence rate measures?
3) project_shorttermpotentiation
We need better STD data (Alex Loebel? Jan G might have them!) Write questions.

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\documentclass[a4paper,12pt,pdftex]{exam}
\newcommand{\ptitle}{Activation curve}
\input{../header.tex}
\firstpagefooter{Supervisor: Lukas Sonnenberg}{}%
{email: lukas.sonnenberg@student.uni-tuebingen.de}
\begin{document}
\input{../instructions.tex}
%%%%%%%%%%%%%% Questions %%%%%%%%%%%%%%%%%%%%%%%%%
\section{Estimation of the activation curve}
Mutations in genes, encoding for ion channels, can result in a variety of neurological diseases like epilepsy, autism and intellectual disability. One way to find a possible treatment is to compare the voltage dependent kinetics of the mutated channel with its corresponding wild-type. These kinetics are described in voltage-clamp experiments and the subsequent data analysis.
In this task you will compute and compare the activation curves of the Nav1.6 wild-type channel and a variation named A1622D (the amino acid Alanine (A) at the 1622nd position is replaced by Aspartic acid (D)) that causes intellectual disability in humans.
\begin{questions}
\question In the accompanying datasets you find recordings of cells with WT or A1622D transfections. The cells were all clamped to -70mV for some time to bring all ion channels in the same closed states. They are activated by a step change in the command voltage to a value described in the "steps" vector. The corresponding recorded current (in pA) and time (in ms) traces are also saved in the files.
\begin{parts}
\part Plot the current traces of a WT and a A1622D cell. Because the number of transfected channels can vary the peak values have little value. Normalize the curves accordingly (what kind of normalization would be appropriate?). Can you already spot differences between the cells?
\part \textbf{IV curve}: Find the peak values for each voltage step and plot them against the steps.
\part \textbf{Reversal potential}: Use the IV-curve to estimate the reversal potential of the sodium current. Consider a linear interpolation to increase the accuracy of your estimation.
\part \textbf{Activation curve}: The activation curve is a representation of the voltage dependence of the sodium conductivity. It is computed with a variation of Ohm's law:
\begin{equation}
g_{Na}(V) = \frac{I_{peak}}{V - V_{reversal}}
\end{equation}
\part \textbf{Compare the two variants}: To compare WT and A1622D activation curves you should first parameterise your data. Fit a sigmoid curve
\begin{equation}
g_{Na}(V) = g_{max,Na} / ( 1 + e^{ - \frac{V-V_{1/2}}{k}} )
\end{equation}
to the activation curves. With $g_{max,Na}$ being the maximum conductivity, $V_{1/2}$ the half activation voltage and $k$ a slope factor. Now you can compare the two variants with a few simple parameters. What do the differences mean?
\part \textbf{BONUS question}: Take a good look at your raw data. What other differences can you see? How could you analyse these?
\end{parts}
\end{questions}
\end{document}