We are able to simulate random data without interrelationships between items that very much resemble our actual data. We can show that network strength (average of all [partial] correlations) changes as a result of the changing distribution, such that at increasing exponential rates (=steeper decline in the exponential curve, as we see in normal controls), a) negative partial and full correlations become more negative, b) positive partial and full correlations become more positive, although, as a result, c) overall full and partial correlations (i.e. network strength) remain unchanged. For partial correlations, however, we interpret the absolute values. In the case of partial correlations, network strength thus increases as a result of the changing rate. Also, in the case where correlations are in fact positive, network strength will increase as a result of the changing rate. Thus, more pronounced as a result of distribution properties.