Psychiatry must follow this path. The quest for pathophysiological markers goes back to Emil Kraepelin and continued for many years thereafter. With the advent of psychodynamic thinking, the search for pathophysiology diminished and was replaced by the search for internalized conflicts. Part of the reason for the failure of that pathophysiological quest included limitations in the scientific methods available to investigators. The development of imaging technology has brought Inhibitors,research,lifescience,medical a dramatic change in the power available to investigators. Discriminates In an article published in Science, 3 it was demonstrated that data derived from quantitative electroencephalography (EEG) were
strongly correlated with DSM diagnoses. The data were age-corrected and Z-transformed, so as to make it possible to use appropriately powerful statistical techniques (“neurometric analysis”) (Figure 1). Discriminate Inhibitors,research,lifescience,medical equations could then be written, which, on the basis of EEG findings, could reliably separate psychiatric patients from normals and classify patients along the lines of the DSM nomenclature. The importance
of this finding was initially not fully recognized and brushed aside as “merely correlational in nature.” Nevertheless, there was a consistent and replicable demonstration of abnormal brain activity as a function of diagnostic category. A major limitation of the methodology Inhibitors,research,lifescience,medical was that the signal is derived from the scalp, and the source of the signal Inhibitors,research,lifescience,medical was not localized three-dimensionally (Figure 2). Figure 1. Z transform of data derived from quantitative electroencephalography (qEEG). Figure 2. Power distribution in different diagnostic categories. It became clear over time that some features of the abnormal signal did not change with treatment or even with clinical improvement. It Inhibitors,research,lifescience,medical can only be concluded that the signal was a mixture of state and trait variables. Nevertheless, it was clear that the patients who improved clinically tended to move toward the normal space and were less abnormal statistically than they had been prior to successful treatment. because Cluster analysis
An interesting question then arose. While it is possible to group patients according to their abnormal quantitative EEG (qEEG) findings, does this mean that the groups were homogeneous within themselves? The technique of discriminate analysis cannot address this question. On the other hand, the use of a cluster analysis technique will check details assist in resolving this issue.4 As can be seen in Figure 3, a perfect discriminate will separate a group into variable sets, but it does not identify where they are located along the vector that separates those variable sets. The cluster analysis will permit an examination of which person identified as belonging to a discriminate group most resembles his or her neighbor.
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