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[projects] little updates

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This commit is contained in:
Jan Benda 2019-01-11 14:07:34 +01:00
parent ae51f8c3e1
commit e826428446
7 changed files with 38 additions and 27 deletions
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4
projects/README
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@ -11,14 +11,12 @@ no statistics, but kmeans
project_fano_slope
OK, difficult
Add t-test
project_fano_test
OK -
project_fano_time
OK, difficult
Add t-test
OK, medium-difficult
project_ficurves
OK, medium

12
projects/project.mk
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@ -1,14 +1,10 @@
BASENAME=$(subst project_,,$(notdir $(CURDIR)))
latex:
pdflatex $(BASENAME).tex
pdflatex $(BASENAME).tex
pdf: $(BASENAME).pdf
$(BASENAME).pdf : $(BASENAME).tex ../header.tex ../instructions.tex
pdflatex -interaction=scrollmode $< | tee /dev/stderr | fgrep -q "Rerun to get cross-references right" && pdflatex -interaction=scrollmode $< || true
pdflatex -interaction=scrollmode $< | tee /dev/stderr | fgrep -q "Rerun to get" && pdflatex -interaction=scrollmode $< || true
watch :
@ -19,7 +15,11 @@ clean:
rm -rf *.log *.aux *.out auto
rm -f `basename *.tex .tex`.pdf
rm -f *.zip
pdflatex $(BASENAME).tex
latex:
pdflatex $(BASENAME).tex
zip: latex
zip: pdf
rm -f zip $(BASENAME).zip
zip $(BASENAME).zip *.pdf *.m data/* $(ZIPFILES)

16
projects/project_fano_slope/fano_slope.tex
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@ -1,6 +1,6 @@
\documentclass[a4paper,12pt,pdftex]{exam}
\newcommand{\ptitle}{Stimulus discrimination}
\newcommand{\ptitle}{Stimulus discrimination: gain}
\input{../header.tex}
\firstpagefooter{Supervisor: Jan Benda}{phone: 29 74573}%
{email: jan.benda@uni-tuebingen.de}
@ -95,10 +95,11 @@ spikes = lifboltzmanspikes(trials, input, tmax, gain);
the neuron? Plot them for the four different values of the gain
used in (a).
\part Think about a measure based on the spike-count histograms
that quantifies how well the two stimuli can be distinguished
based on the spike counts. Plot the dependence of this measure as
a function of the gain of the neuron.
\part \label{discrmeasure} Think about a measure based on the
spike-count histograms that quantifies how well the two stimuli
can be distinguished based on the spike counts. Plot the
dependence of this measure as a function of the gain of the
neuron.
%
For which gains can the two stimuli perfectly discriminated?
@ -110,6 +111,11 @@ spikes = lifboltzmanspikes(trials, input, tmax, gain);
results in the best discrimination performance. How can you
quantify ``best discrimination'' performance?
\part Another way to quantify the discriminability of the spike
counts in response to the two stimuli is to apply an appropriate
statistical test and check for significant differences. How does
this compare to your findings from (\ref{discrmeasure})?
\end{parts}
\end{questions}

16
projects/project_fano_time/fano_time.tex
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@ -1,6 +1,6 @@
\documentclass[a4paper,12pt,pdftex]{exam}
\newcommand{\ptitle}{Stimulus discrimination}
\newcommand{\ptitle}{Stimulus discrimination: time}
\input{../header.tex}
\firstpagefooter{Supervisor: Jan Benda}{phone: 29 74573}%
{email: jan.benda@uni-tuebingen.de}
@ -87,10 +87,11 @@ input = 15.0; % I_2
observation time $T$? Plot them for four different values of $T$
(use values of 10\,ms, 100\,ms, 300\,ms and 1\,s).
\part Think about a measure based on the spike-count histograms
that quantifies how well the two stimuli can be distinguished
based on the spike counts. Plot the dependence of this measure as
a function of the observation time $T$.
\part \label{discrmeasure} Think about a measure based on the
spike-count histograms that quantifies how well the two stimuli
can be distinguished based on the spike counts. Plot the
dependence of this measure as a function of the observation time
$T$.
For which observation times can the two stimuli perfectly
discriminated?
@ -103,6 +104,11 @@ input = 15.0; % I_2
results in the best discrimination performance. How can you
quantify ``best discrimination'' performance?
\part Another way to quantify the discriminability of the spike
counts in response to the two stimuli is to apply an appropriate
statistical test and check for significant differences. How does
this compare to your findings from (\ref{discrmeasure})?
\end{parts}
\end{questions}

6
projects/project_lif/lif.tex
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@ -96,7 +96,7 @@ time = [0.0:dt:tmax]; % t_i
Write a function that implements this leaky integrate-and-fire
neuron by expanding the function for the passive neuron
appropriate. The function returns a vector of spike times.
appropriately. The function returns a vector of spike times.
Illustrate how this model works by appropriate plot(s) and
input(s) $E(t)$, e.g. constant inputs lower and higher than the
@ -115,8 +115,8 @@ time = [0.0:dt:tmax]; % t_i
r = \frac{n-1}{t_n - t_1}
\end{equation}
What do you observe? Does the firing rate encode the frequency of
the stimulus? Look at the spike trains in response the sine waves
to figure out what is going on.
the stimulus? Look at the spike trains in response to the sine
waves to figure out what is going on.
\end{parts}
\end{questions}

6
projects/project_noiseficurves/noiseficurves.tex
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@ -63,8 +63,8 @@ spikes = lifspikes(trials, current, tmax, Dnoise);
of this neuron?
\part Compute the $f$-$I$ curves of neurons with various noise
strengths \texttt{Dnoise}. Use for example $D_{noise} = 1e-3$,
$1e-2$, and $1e-1$.
strengths \texttt{Dnoise}. Use for example $D_{noise} = 10^{-3}$,
$10^{-2}$, and $10^{-1}$.
How does the intrinsic noise influence the response curve?
@ -76,6 +76,8 @@ spikes = lifspikes(trials, current, tmax, Dnoise);
responses of the four different neurons to the same input, or by
the same resulting mean firing rate.
How do the responses differ?
\part Let's now use as an input to the neuron a 1\,s long sine
wave $I(t) = I_0 + A \sin(2\pi f t)$ with offset current $I_0$,
amplitude $A$, and frequency $f$. Set $I_0=5$, $A=4$, and

5
projects/project_pca_natural_images/pca_natural_images.tex
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@ -32,9 +32,8 @@ In you zip file you find a natural image called {\tt natimg.jpg}.
\begin{thebibliography}{1}
\bibitem{BG} Buchsbaum, G., \& Gottschalk, A. (1983). Trichromacy,
opponent colours coding and optimum colour information transmission
in the retina. Proceedings of the Royal Society of London. Series B,
Containing Papers of a Biological Character. Royal Society (Great
Britain), 220(1218), 89–113.
in the retina. Proceedings of the Royal Society of London B. Royal
Society (Great Britain), 220(1218), 89–113.
\end{thebibliography}