<p>Variability in the estimation of the expected number of potential synapses at 14 different displacements using the formula (5) based on axonal and dendritic templates created from 9 different sets consisting of 10 generated L2/3 pyramidal neurons each. Values given are mean, standard deviation, minimum and maximum of for indicated displacement .</p
<p><b>A</b>: Distribution of firing rates of excitatory neurons. The magenta line shows a log-normal...
A convenient and often used summary measure to quantify the firing variability in neurons is the coe...
<p>(A) Time courses of the mean synaptic weight <i>S</i>(<i>t</i>) for different CR stimulation inte...
<p>Results for the sparse data approach, using formula (6). Given numbers are the mean, standard dev...
Panel D illustrates the force standard deviation (mean±std) for all simulated conditions. Here, the ...
Information in a computer is quantified by the number of bits that can be stored and recovered. An i...
Variability is a universal feature among biological units such as neuronal cells as they enable a ro...
<p><b>A</b> Distribution of excitatory (PY) synapses. <b>B</b> Distribution of inhibitory (IN) synap...
Variability is a universal feature among biological units such as neuronal cells as they enable a ro...
Procedures for discriminating between competing statistical models of synaptic transmission, and for...
<p>(<b>A</b>) Distributions of the log normally distributed synaptic input densities (left), and the...
<p>For all subfigures, the mean waveform is plotted in black, SD in red, and 1%–99% quantiles in lig...
Warzecha A-K, Egelhaaf M. Variability in spike trains during constant and dynamic stimulation. Scien...
<p><b>B</b>. Distribution of synaptic weights for , at maximal capacity (). Red: analytical calculat...
<p><b>A–C</b>. The averaged (±s.d.) PSP amplitude (<b>A</b>), CV (<b>B</b>) and percentage failures ...
<p><b>A</b>: Distribution of firing rates of excitatory neurons. The magenta line shows a log-normal...
A convenient and often used summary measure to quantify the firing variability in neurons is the coe...
<p>(A) Time courses of the mean synaptic weight <i>S</i>(<i>t</i>) for different CR stimulation inte...
<p>Results for the sparse data approach, using formula (6). Given numbers are the mean, standard dev...
Panel D illustrates the force standard deviation (mean±std) for all simulated conditions. Here, the ...
Information in a computer is quantified by the number of bits that can be stored and recovered. An i...
Variability is a universal feature among biological units such as neuronal cells as they enable a ro...
<p><b>A</b> Distribution of excitatory (PY) synapses. <b>B</b> Distribution of inhibitory (IN) synap...
Variability is a universal feature among biological units such as neuronal cells as they enable a ro...
Procedures for discriminating between competing statistical models of synaptic transmission, and for...
<p>(<b>A</b>) Distributions of the log normally distributed synaptic input densities (left), and the...
<p>For all subfigures, the mean waveform is plotted in black, SD in red, and 1%–99% quantiles in lig...
Warzecha A-K, Egelhaaf M. Variability in spike trains during constant and dynamic stimulation. Scien...
<p><b>B</b>. Distribution of synaptic weights for , at maximal capacity (). Red: analytical calculat...
<p><b>A–C</b>. The averaged (±s.d.) PSP amplitude (<b>A</b>), CV (<b>B</b>) and percentage failures ...
<p><b>A</b>: Distribution of firing rates of excitatory neurons. The magenta line shows a log-normal...
A convenient and often used summary measure to quantify the firing variability in neurons is the coe...
<p>(A) Time courses of the mean synaptic weight <i>S</i>(<i>t</i>) for different CR stimulation inte...