64 lines
10 KiB
TeX
Executable File
64 lines
10 KiB
TeX
Executable File
\relax
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\providecommand\hyper@newdestlabel[2]{}
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\@writefile{toc}{\select@language{english}}
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\@writefile{lof}{\select@language{english}}
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\@writefile{lot}{\select@language{english}}
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\@writefile{toc}{\contentsline {section}{\numberline {1}Zusammenfassung}{4}{section.1}}
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\@writefile{toc}{\contentsline {section}{\numberline {2}Abstract}{4}{section.2}}
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\@writefile{toc}{\contentsline {section}{\numberline {3}Introduction}{4}{section.3}}
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\@writefile{lof}{\contentsline {figure}{\numberline {1}{\ignorespaces Example behavior of a p-unit with a high baseline firing rate. Baseline Firing: A 100\tmspace +\thinmuskip {.1667em}ms voltage trace of the recording with spikes marked by the black lines. ISI-histogram: The histogram of the ISI with the x-axis in EOD periods, showing the phase locking of the firing. Serial Correlation: The serial correlation of the ISI showing a negative correlation for lags one and two. Step Response: The response of the p-unit to a step increase in EOD amplitude. In {\color {red}(TODO: color)} the averaged frequency over 10 trials and in {\color {red}(TODO: color)} smoothed with an running average with a window of 10\tmspace +\thinmuskip {.1667em}ms. The p-unit strongly reacts to the onset of the stimulus but very quickly adapts to the new stimulus and then shows a steady state response. FI-Curve: The fi-curve visualizes the onset and steady-state response of the neuron for different step sizes (contrasts). In {\color {red}(TODO: color)} the detected onset responses and the fitted Boltzmann, in {\color {red}(TODO: color)} the detected steady-state response and the linear fit.}}{4}{figure.1}}
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\newlabel{fig:p_unit_example}{{1}{4}{Example behavior of a p-unit with a high baseline firing rate. Baseline Firing: A 100\,ms voltage trace of the recording with spikes marked by the black lines. ISI-histogram: The histogram of the ISI with the x-axis in EOD periods, showing the phase locking of the firing. Serial Correlation: The serial correlation of the ISI showing a negative correlation for lags one and two. Step Response: The response of the p-unit to a step increase in EOD amplitude. In \todo {color} the averaged frequency over 10 trials and in \todo {color} smoothed with an running average with a window of 10\,ms. The p-unit strongly reacts to the onset of the stimulus but very quickly adapts to the new stimulus and then shows a steady state response. FI-Curve: The fi-curve visualizes the onset and steady-state response of the neuron for different step sizes (contrasts). In \todo {color} the detected onset responses and the fitted Boltzmann, in \todo {color} the detected steady-state response and the linear fit}{figure.1}{}}
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\citation{walz2013Phd}
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\citation{walz2014static}
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\citation{todd1999identification}
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\@writefile{toc}{\contentsline {section}{\numberline {4}Materials and Methods}{5}{section.4}}
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\@writefile{toc}{\contentsline {subsection}{\numberline {4.1}Cell recordings}{5}{subsection.4.1}}
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\@writefile{toc}{\contentsline {subsection}{\numberline {4.2}Stimulus Protocols}{6}{subsection.4.2}}
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\newlabel{eq:am_generation}{{1}{6}{Stimulus Protocols}{equation.4.1}{}}
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\newlabel{fig:stim_examples}{{2}{6}{Example of the Stimuli construction. At the top a recording of the fish's EOD. In the middle a part of the recording multiplied with the AM, a step with a contrast of 130\% between 0 and 50\,ms (marked in \todo {color}). At the bottom the resulting stimulus trace when the AM is added to the EOD. This example stimulus is for visualization purposes 50\,ms short. During the measurements the stimulus was 0.4\,s or 1\,s long}{figure.2}{}}
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\@writefile{lof}{\contentsline {figure}{\numberline {2}{\ignorespaces Example of the Stimuli construction. At the top a recording of the fish's EOD. In the middle a part of the recording multiplied with the AM, a step with a contrast of 130\% between 0 and 50\tmspace +\thinmuskip {.1667em}ms (marked in {\color {red}(TODO: color)}). At the bottom the resulting stimulus trace when the AM is added to the EOD. This example stimulus is for visualization purposes 50\tmspace +\thinmuskip {.1667em}ms short. During the measurements the stimulus was 0.4\tmspace +\thinmuskip {.1667em}s or 1\tmspace +\thinmuskip {.1667em}s long. }}{6}{figure.2}}
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\@writefile{toc}{\contentsline {subsection}{\numberline {4.3}Cell Characteristics}{7}{subsection.4.3}}
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\newlabel{eq:CV}{{2}{7}{Cell Characteristics}{equation.4.2}{}}
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\newlabel{eq:VS}{{3}{7}{Cell Characteristics}{equation.4.3}{}}
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\newlabel{eq:SC}{{4}{7}{Cell Characteristics}{equation.4.4}{}}
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\@writefile{lof}{\contentsline {figure}{\numberline {3}{\ignorespaces {\color {red}(TODO: place right in text)}On the left: The averaged response of a cell to a step in EOD amplitude. The beginning (at 0\tmspace +\thinmuskip {.1667em}s) and end (at 1\tmspace +\thinmuskip {.1667em}s) of the stimulus are marked by the gray lines. The detected values for the onset ($f_0$) and steady-state ($f_{inf}$) response are marked in {\color {red}(TODO: color)}. $f_0$ is detected as the highest deviation from the mean frequency before the stimulus while $f_{inf}$ is the average frequency in the 0.1\tmspace +\thinmuskip {.1667em}s time window, 25\tmspace +\thinmuskip {.1667em}ms before the end of the stimulus. On the right: The fi-curve visualizes the onset and steady-state response of the neuron for different stimuli contrasts. In {\color {red}(TODO: color)} the detected onset responses and the fitted Boltzmann, in {\color {red}(TODO: color)} the detected steady-state response and the linear fit.}}{8}{figure.3}}
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\newlabel{fig:f_point_detection}{{3}{8}{\todo {place right in text}On the left: The averaged response of a cell to a step in EOD amplitude. The beginning (at 0\,s) and end (at 1\,s) of the stimulus are marked by the gray lines. The detected values for the onset ($f_0$) and steady-state ($f_{inf}$) response are marked in \todo {color}. $f_0$ is detected as the highest deviation from the mean frequency before the stimulus while $f_{inf}$ is the average frequency in the 0.1\,s time window, 25\,ms before the end of the stimulus. On the right: The fi-curve visualizes the onset and steady-state response of the neuron for different stimuli contrasts. In \todo {color} the detected onset responses and the fitted Boltzmann, in \todo {color} the detected steady-state response and the linear fit}{figure.3}{}}
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\@writefile{toc}{\contentsline {subsection}{\numberline {4.4}Leaky Integrate and Fire Model}{8}{subsection.4.4}}
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\citation{benda2003universal}
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\newlabel{eq:basic_voltage_dynamics}{{5}{9}{Leaky Integrate and Fire Model}{equation.4.5}{}}
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\newlabel{eq:adaption_dynamics}{{6}{9}{Leaky Integrate and Fire Model}{equation.4.6}{}}
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\newlabel{eq:currents_lifac}{{7}{9}{Leaky Integrate and Fire Model}{equation.4.7}{}}
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\@writefile{lof}{\contentsline {figure}{\numberline {4}{\ignorespaces Comparison of different simple models normed to a spontaneous firing 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. }}{10}{figure.4}}
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\newlabel{fig:model_comparison}{{4}{10}{Comparison of different simple models normed to a spontaneous firing 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}{figure.4}{}}
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\newlabel{eq:full_voltage_dynamics}{{8}{10}{Leaky Integrate and Fire Model}{equation.4.8}{}}
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\@writefile{lof}{\contentsline {figure}{\numberline {5}{\ignorespaces The stimulus modification in the model. The fish's EOD is simulated with a sin wave. It is rectified at the synapse and then further low-pass filtered in the dendrite.}}{11}{figure.5}}
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\newlabel{fig:stim_development}{{5}{11}{The stimulus modification in the model. The fish's EOD is simulated with a sin wave. It is rectified at the synapse and then further low-pass filtered in the dendrite}{figure.5}{}}
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\@writefile{lot}{\contentsline {table}{\numberline {1}{\ignorespaces Overview about all variables of the model that are fitted.}}{11}{table.1}}
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\newlabel{tab:parameter_explanation}{{1}{11}{Overview about all variables of the model that are fitted}{table.1}{}}
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\@writefile{toc}{\contentsline {subsection}{\numberline {4.5}Fitting of the Model}{11}{subsection.4.5}}
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\bibdata{citations}
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\bibcite{benda2003universal}{{1}{2003}{{Benda and Herz}}{{}}}
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\bibcite{todd1999identification}{{2}{1999}{{Todd and Andrews}}{{}}}
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\bibcite{walz2013Phd}{{3}{2013}{{Walz}}{{}}}
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\bibcite{walz2014static}{{4}{2014}{{Walz et~al.}}{{}}}
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\bibstyle{apalike}
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\@writefile{toc}{\contentsline {section}{\numberline {5}Results}{12}{section.5}}
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\@writefile{toc}{\contentsline {section}{\numberline {6}Discussion}{12}{section.6}}
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