mat met in works

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a.ott 2020-08-22 11:28:47 +02:00
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@ -20,29 +20,33 @@
\@writefile{toc}{\select@language{english}}
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\citation{walz2013Phd}
\citation{walz2014static}
\citation{todd1999identification}
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\@writefile{lof}{\contentsline {figure}{\numberline {1}{\ignorespaces Comparison of different simple models normed to a baseline fire rate of ~10 Hz stimulated with a step stimulus. In the left column y-axis in mV in the right column the y-axis shows the frequency in Hz. PIF: Shows a continuously increasing membrane voltage with a fixed slope and as such constant frequency for a given stimulus strength. LIF: Approaches a stimulus dependent membrane voltage steady state exponentially Also has constant frequency for a fixed stimulus value. LIFAC: Exponentially approaches its new membrane voltage value but also shows adaption after changes in the stimulus the frequency takes some time to adapt and arrive at the new stable value. LIFAC + ref: Very similar to LIFAC the added absolute refractory period keeps the voltage constant for a short time after the spike and limits high fire rates. {\color {red}(TODO: how to deal with the parameters) } }}{4}{figure.1}}
\citation{walz2013Phd}
\citation{todd1999identification}
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\@writefile{lof}{\contentsline {figure}{\numberline {2}{\ignorespaces Comparison of different simple models normed to a baseline fire rate of ~10 Hz stimulated with a step stimulus. In the left column y-axis in mV in the right column the y-axis shows the frequency in Hz. PIF: Shows a continuously increasing membrane voltage with a fixed slope and as such constant frequency for a given stimulus strength. LIF: Approaches a stimulus dependent membrane voltage steady state exponentially Also has constant frequency for a fixed stimulus value. LIFAC: Exponentially approaches its new membrane voltage value but also shows adaption after changes in the stimulus the frequency takes some time to adapt and arrive at the new stable value. LIFAC + ref: Very similar to LIFAC the added absolute refractory period keeps the voltage constant for a short time after the spike and limits high fire rates. {\color {red}(TODO: how to deal with the parameters)} }}{6}{figure.2}}
\bibdata{citations}
\bibcite{todd1999identification}{{1}{1999}{{Todd and Andrews}}{{}}}
\bibcite{walz2013Phd}{{2}{2013}{{Walz}}{{}}}
\bibcite{walz2014static}{{3}{2014}{{Walz et~al.}}{{}}}
\bibstyle{apalike}
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@ -11,4 +11,10 @@ Walz, H. (2013).
ofElectroreceptors}.
\newblock PhD thesis, Eberhard-Karls-Universität Tübingen.
\bibitem[Walz et~al., 2014]{walz2014static}
Walz, H., Grewe, J., and Benda, J. (2014).
\newblock Static frequency tuning accounts for changes in neural synchrony
evoked by transient communication signals.
\newblock {\em Journal of Neurophysiology}, 112(4):752--765.
\end{thebibliography}

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@ -2,9 +2,10 @@
\BOOKMARK [1][]{section.2}{Abstract}{}% 2
\BOOKMARK [1][]{section.3}{Introduction}{}% 3
\BOOKMARK [1][]{section.4}{Materials and Methods}{}% 4
\BOOKMARK [2][]{subsection.4.1}{Leaky Integrate and Fire Model}{section.4}% 5
\BOOKMARK [2][]{subsection.4.2}{Cell recordings}{section.4}% 6
\BOOKMARK [2][]{subsection.4.3}{Stimulus Protocols}{section.4}% 7
\BOOKMARK [2][]{subsection.4.4}{Fitting of the Model}{section.4}% 8
\BOOKMARK [1][]{section.5}{Results}{}% 9
\BOOKMARK [1][]{section.6}{Discussion}{}% 10
\BOOKMARK [2][]{subsection.4.1}{Cell recordings}{section.4}% 5
\BOOKMARK [2][]{subsection.4.2}{Stimulus Protocols}{section.4}% 6
\BOOKMARK [2][]{subsection.4.3}{Cell Characteristics}{section.4}% 7
\BOOKMARK [2][]{subsection.4.4}{Leaky Integrate and Fire Model}{section.4}% 8
\BOOKMARK [2][]{subsection.4.5}{Fitting of the Model}{section.4}% 9
\BOOKMARK [1][]{section.5}{Results}{}% 10
\BOOKMARK [1][]{section.6}{Discussion}{}% 11

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@ -14,7 +14,7 @@
\newcommand{\todo}[1]{{\color{red}(TODO: #1) }}
\newcommand{\todo}[1]{{\color{red}(TODO: #1)}}
\newcommand{\AptLepto}{{\textit{Apteronotus leptorhynchus \:}}}
\newcommand{\lepto}{{\textit{A. leptorhynchus}}}
@ -112,6 +112,91 @@ Außerdem erkläre ich, dass die eingereichte Arbeit weder vollständig noch in
\section{Materials and Methods}
\subsection{Cell recordings}
The cell recordings for this master thesis were collected as part of other previous studies (\cite{walz2013Phd}, \citep{walz2014static})\todo{ref other studies} and is described there but will also be repeated below . The data of \todo{how many} \AptLepto were used. \todo{sizes range, EOD range, number of cells}
The in vivo intracellular recordings of P-unit electroreceptors were done in the lateral line nerve . The fish were anesthetized with MS-222 (100-130 mg/l; PharmaQ; Fordingbridge, UK) and the part of the skin covering the lateral line just behind the skull was removed, while the area was anesthetized with Lidocaine (2\%; bela-pharm; Vechta, Germany). The fish were immobilized for the recordings with Tubocurarine (Sigma-Aldrich; Steinheim, Germany, 2550 $\mu l$ of 5\. mg/ml solution) and placed in the experimental tank (47 $\times$ 42 $\times$ 12\,cm) filled with water from the fish's home tank with a conductivity of about 300$\mu$\,S/cm and the temperature was around 28°C.
All experimental protocels were approved and complied with national and regional laws (files: no. 55.2-1-54-2531-135-09 and Regierungspräsidium Tübingen no. ZP 1/13 and no. ZP 1/16 \todo{andere antrags nummern so richtig ?})
For the recordings a standard glass mircoelectrode (borosilicate; 1.5 mm outer diameter; GB150F-8P, Science Products, Hofheim, Germany) was used, pulled to a resistance of 50-100M$\Omega$ using Model P-97 from Sutter Instrument Co. (No-
vato, CA, USA). They were filled with 1M KCl solution. The electrodes were controlled using microdrives (Luigs-Neumann; Ratingen, Germany) and the potentials recorded with the bridge mode of the SEC-05 amplifier (npi-electronics GmbH, Tamm, Germany) and lowpass filtered at 10 kHz.
During the recording spikes were detected online using the peak detection algorithm from \cite{todd1999identification}. It uses a dynamically adjusted threshold value above the previously detected trough. To detect spikes through changes in amplitude the threshold was set to 50\% of the amplitude of a detected spike while keeping the threshold above a minimum set to be higher than the noise level based on a histogram of all peak amplitudes. Trials with bad spike detection were removed from further analysis.
The fish's EOD was recorded using using two vertical carbon rods (11\,cm long, 8\,mm diameter) positioned in front of the head and behind its tail.. the signal was amplified 200 to 500 times and band-pass filtered (3 1500 Hz passband, DPA2-FX, npi-electronics, Tamm, Germany). The electrodes were placed on isopotential lines of the stimulus field to reduce the interference of the stimulus in the recording. All signals were digitized using a data acquisition board (PCI-6229; National Instruments, Austin TX, USA) at a sampling rate of \todo{Hz range} kHz
The recording and stimulation was done using the ephys, efield, and efish plugins of the software RELACS (\href{www.relacs.net}{www.relacs.net}). It allowed the online spike and EOD detection, pre-analysis and visualization and ran on a Debian computer.
\subsection{Stimulus Protocols}
% image of Baseline stimulus as baseline doesn't mean no stimulus here
% image of Fi curve stimulus sinusoidal step
% image of SAM stimulus
The stimuli used during the recordings were presented from two vertical carbon rods (30 cm long, 8 mm diameter) as stimulus electrodes. They were positioned at either side of the fish parallel to its longitudinal axis. The stimuli were computer generated, attenuated and isolated (Attenuator: ATN-01M, Isolator: ISO-02V, npi-electronics, Tamm, Germany) and then send to the stimulus electrodes.
For this work three types of recordings were made baseline, frequency-Intensity curve (FI-Curve) and sinusoidal amplitude modulation (SAM).
The 'stimulus' for the baseline recording is purely the field the fish produces itself. So the situation with no outside influence.
For the other two stimuli a certain kind of amplitude modulation (AM) of the fish's EOD was the goal. The recordings for the FI-Curve used a step change in the EOD amplitude. This step change was produced by recording the EOD of the fish multiplying this trace with the wanted step change (the amplitude modulation) and then playing the modified EOD back through the stimulus electrodes in the right phase. This causes constructive interference between the fish's EOD and the AM signal and results in the stimulus carrying the wanted AM (see Figure \ref{fig:am_generation}).
This system as seen in equation \ref{eq:am_generation} works for any AM. In the
\todo{contrast ranges, presentation windows/durations, changing stimulus parameters}
\begin{equation}
Stimulus = EOD(t) * AM(t) + EOD(t) \todo{acceptable?}
\label{eq:am_generation}
\end{equation}
\begin{figure}
\centering
\begin{minipage}{0.5\textwidth}
\raisebox{50mm}{\large\sffamily A}\hspace{-2ex}
\includegraphics[width=0.95\textwidth]{figures/amGeneration.pdf}
\end{minipage}\hfill
\begin{minipage}{0.5\textwidth}
\includegraphics[width=\textwidth]{figures/stimuliExamples.pdf}
%\caption{second}
\end{minipage}
\caption{use real EOD data?\label{fig:stim_examples}}
\end{figure}
\subsection{Cell Characteristics}
Baseline
p-Value:
\begin{equation}
p = \frac{neuron frequency}{EOD frequency}
\end{equation}
coefficient of variation:
\begin{equation}
CV = \frac{STD(ISI)}{\langle ISI \rangle}
\end{equation}
serial correlation: \todo{check!}
\begin{equation}
sc_i = \frac{\langle ISI_{k+j} ISI_k \rangle - \langle ISI_k \rangle^2}{VAR(ISI)}
\end{equation}
burstiness: \todo{what definition? still use it? }
vector strength:
FI-Curve:
explain detection of f-points
\subsection{Leaky Integrate and Fire Model}
@ -167,37 +252,6 @@ Finally a noise current and an absolute refractory period where added to the mod
\caption{}
\end{figure}
\subsection{Cell recordings}
The cell recordings for this master thesis were collected as part of other previous studies \cite{walz2013Phd}\todo{ref other studies} and is described there but will also be repeated below . The data of \todo{how many} \AptLepto were used. \todo{sizes range, EOD range, number of cells}
The in vivo intracellular recordings of P-unit electroreceptors were done in the lateral line nerve . The fish were anesthetized with MS-222 (100-130 mg/l; PharmaQ; Fordingbridge, UK) and the part of the skin covering the lateral line just behind the skull was removed, while the area was anesthetized with Lidocaine (2\%; bela-pharm; Vechta, Germany). The fish were immobilized for the recordings with Tubocurarine (Sigma-Aldrich; Steinheim, Germany, 2550 $\mu l$ of 5\. mg/ml solution) and placed in the experimental tank (47 $\times$ 42 $\times$ 12\,cm) filled with water from the fish's home tank with a conductivity of about 300$\mu$\,S/cm and the temperature was around 28°C.
All experimental protocels were approved and complied with national and regional laws (files no. 55.2-1-54-2531-135-09, no. and no. \todo{andere antrags nummern} )
For the recordings a standard glass mircoelectrode (borosilicate; 1.5 mm outer diameter; GB150F-8P, Science Products, Hofheim, Germany) was used, pulled to a resistance of 50-100M$\Omega$ using Model P-97 from Sutter Instrument Co. (No-
vato, CA, USA). They were filled with 1M KCl solution. The electrodes were controlled using microdrives (Luigs-Neumann; Ratingen, Germany) and the potentials recorded with the bridge mode of the SEC-05 amplifier (npi-electronics GmbH, Tamm, Germany) and lowpass filtered at 10 kHz.
During the recording spikes were detected online using the peak detection algorithm from \cite{todd1999identification}. It uses a dynamically adjusted threshold value above the previously detected trough. To detect spikes through changes in amplitude the threshold was set to 50\% of the amplitude of a detected spike while keeping the threshold above a minimum set to be higher than the noise level based on a histogram of all peak amplitudes. Trials with bad spike detection were removed from further analysis.
The fish's EOD was recorded using using two vertical carbon rods (11\,cm long, 8\,mm diameter) positioned in front of the head and behind its tail.. the signal was amplified 200 to 500 times and band-pass filtered (3 1500 Hz passband, DPA2-FX, npi-electronics, Tamm, Germany). The electrodes were placed on isopotential lines of the stimulus field to reduce the interference of the stimulus in the recording. All signals were digitized using a data acquisition board (PCI-6229; National Instruments, Austin TX, USA) at a sampling rate of \todo{Hz range} kHz
The recording and stimulation was done using the ephys, efield, and efish plugins of the software RELACS (\href{www.relacs.net}{www.relacs.net}). It allowed the online spike and EOD detection, pre-analysis and visualization and ran on a Debian computer.
\subsection{Stimulus Protocols}
% image of Baseline stimulus as baseline doesn't mean no stimulus here
% image of Fi curve stimulus sinusoidal step
% image of SAM stimulus
\begin{figure}[H]
\includegraphics[scale=0.6]{figures/stimuliExamples.pdf}
\label{fig:stim_examples}
\caption{}
\end{figure}
\subsection{Fitting of the Model}

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@ -3,9 +3,10 @@
\contentsline {section}{\numberline {2}Abstract}{3}{section.2}
\contentsline {section}{\numberline {3}Introduction}{3}{section.3}
\contentsline {section}{\numberline {4}Materials and Methods}{3}{section.4}
\contentsline {subsection}{\numberline {4.1}Leaky Integrate and Fire Model}{3}{subsection.4.1}
\contentsline {subsection}{\numberline {4.2}Cell recordings}{5}{subsection.4.2}
\contentsline {subsection}{\numberline {4.3}Stimulus Protocols}{6}{subsection.4.3}
\contentsline {subsection}{\numberline {4.4}Fitting of the Model}{6}{subsection.4.4}
\contentsline {section}{\numberline {5}Results}{6}{section.5}
\contentsline {section}{\numberline {6}Discussion}{6}{section.6}
\contentsline {subsection}{\numberline {4.1}Cell recordings}{3}{subsection.4.1}
\contentsline {subsection}{\numberline {4.2}Stimulus Protocols}{4}{subsection.4.2}
\contentsline {subsection}{\numberline {4.3}Cell Characteristics}{4}{subsection.4.3}
\contentsline {subsection}{\numberline {4.4}Leaky Integrate and Fire Model}{5}{subsection.4.4}
\contentsline {subsection}{\numberline {4.5}Fitting of the Model}{7}{subsection.4.5}
\contentsline {section}{\numberline {5}Results}{7}{section.5}
\contentsline {section}{\numberline {6}Discussion}{7}{section.6}