diff --git a/nonlinearbaseline.tex b/nonlinearbaseline.tex
index 0d233b5..a26bb49 100644
--- a/nonlinearbaseline.tex
+++ b/nonlinearbaseline.tex
@@ -706,6 +706,7 @@ The average firing rate during stimulation, $r_s = \langle r(t) \rangle_t$, is g
 The neuron is driven by the stimulus and thus its spiking response depends on the time course of the stimulus. To characterize the relation between stimulus $s(t)$ and response $x(t)$, we calculated the first- and second-order susceptibilities in the frequency domain.
 
 Fast fourier transforms (FFT) $\tilde s_T(\omega)$ and $\tilde x_T(\omega)$ of $s(t)$ and $x(t)$, respectively, were computed according to $\tilde x_T(\omega) = \int_{0}^{T} \, x(t) e^{- i \omega t}\,dt$ for $T=0.5$\,s long segments with no overlap, resulting in a spectral resolution of 2\,Hz for the experimental data.  For simplicity  we use angular frequencies $\omega=2\pi f$ instead of frequencies $f$. In the experimental data, most stimuli had a duration of 10\,s and were chopped into 20 segments. Spectral measures were computed for single trials of neural responses, series of spike times, \eqnref{eq:spikes}. For spectral parameters used in simulations, see below.
+\notejb{Update FFT parameter. Describe binary spiketrain normalized by dt and plain FFT. Power spectra scaled by dt/nfft, bispectra by dt**2/nfft.}
 
 The power spectrum of the stimulus $s(t)$ was estimated as 
 \begin{equation}
@@ -734,7 +735,7 @@ describes nonlinear interactions that generate responses at the sum and differen
 The second-order susceptibility
 \begin{equation}
   \label{eq:susceptibility}
-  \chi_{2}(\omega_{1}, \omega_{2}) = \frac{S_{xss} (\omega_{1},\omega_{2})}{2\sqrt{S_{ss} (\omega_{1}) S_{ss} (\omega_{2})}}
+  \chi_{2}(\omega_{1}, \omega_{2}) = \frac{S_{xss} (\omega_{1},\omega_{2})}{2 S_{ss} (\omega_{1}) S_{ss} (\omega_{2})}
 \end{equation}
 normalizes the second-order cross-spectrum by the spectral power at the two stimulus frequencies.
 % Applying the Fourier transform this can be rewritten resulting in: