fano correction
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$\mu$. It is a common measure in neural coding because a Poisson
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$\mu$. It is a common measure in neural coding because a Poisson
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process---for which each spike is independent of every other---has a
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process---for which each spike is independent of every other---has a
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Fano factor of one.
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Fano factor of one.
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The table contains spike counts from a neuron measured in twelve
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The accompanying file contains two vectors with spike counts from
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trials.
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two neurons measured in a time window of 1s.
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\begin{center}
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\begin{tabular}{cccc}
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\multicolumn{4}{c}{\bf number of spikes} \\ \hline\\
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36 & 28 & 38 & 35\\
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32 & 30 & 35 & 29\\
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29 & 24 & 26 & 34
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\end{tabular}
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\end{center}
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\begin{parts}
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\begin{parts}
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\part Plot the spike counts of both neurons appropriately.
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\part Use {\em Eden, U. T., \& Kramer, M. (2010). Drawing
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\part Use {\em Eden, U. T., \& Kramer, M. (2010). Drawing
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inferences from Fano factor calculations. Journal of
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inferences from Fano factor calculations. Journal of
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neuroscience methods, 190(1), 149--152} to construct a test that
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neuroscience methods, 190(1), 149--152} to construct a test that
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uses the Fano factor as test statistic and tests against the Null
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uses the Fano factor as test statistic and tests against the Null
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hypothesis that the spike counts come from a Poisson process.
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hypothesis that the spike counts come from a Poisson process.
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\part Plot the spike counts appropriately.
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\part Implement the test and use it on the data above.
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\part Implement the test and use it on the data above.
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\end{parts}
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\end{parts}
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