The diagnosis of mental disorders: the problem of reification

A pressing need for interrater reliability in the diagnosis of mental disorders emerged during the mid-twentieth century, prompted in part by the development of diverse new treatments. The Diagnostic and Statistical Manual of Mental Disorders (DSM), third edition answered this need by introducing operationalized diagnostic criteria that were field-tested for interrater reliability. Unfortunately, the focus on reliability came at a time when the scientific understanding of mental disorders was embryonic and could not yield valid disease definitions. Based on accreting problems with the current DSM-fourth edition (DSM-IV) classification, it is apparent that validity will not be achieved simply by refining criteria for existing disorders or by the addition of new disorders. Yet DSM-IV diagnostic criteria dominate thinking about mental disorders in clinical practice, research, treatment development, and law. As a result, the modernDSMsystem, intended to create a shared language, also creates epistemic blinders that impede progress toward valid diagnoses. Insights that are beginning to emerge from psychology, neuroscience, and genetics suggest possible strategies for moving forward

Resurrecting melancholia

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65798/1/j.1600-0447.2007.00958.x.pd

Anhedonia in schizophrenia and major depression: state or trait?

<p>Abstract</p> <p>Background</p> <p>In schizophrenia and major depressive disorder, anhedonia (a loss of capacity to feel pleasure) had differently been considered as a premorbid personological trait or as a main symptom of their clinical picture. The aims of this study were to examine the pathological features of anhedonia in schizophrenic and depressed patients, and to investigate its clinical relations with general psychopathology (negative, positive, and depressive dimensions).</p> <p>Methods</p> <p>A total of 145 patients (80 schizophrenics and 65 depressed subjects) were assessed using the Physical Anhedonia Scale and the Social Anhedonia Scale (PAS and SAS, respectively), the Scales for the Assessment of Positive and Negative Symptoms (SAPS and SANS, respectively), the Calgary Depression Scale for Schizophrenics (CDSS), and the Hamilton Depression Rating Scale (HDRS). The statistical analysis was performed in two steps. First, the schizophrenic and depressed samples were dichotomised into 'anhedonic' and 'normal hedonic' subgroups (according to the 'double (PAS/SAS) cut-off') and were compared on the general psychopathology scores using the Mann-Whitney Z test. Subsequently, for the total schizophrenic and depressed samples, Spearman correlations were calculated to examine the relation between anhedonia ratings and the other psychopathological parameters.</p> <p>Results</p> <p>In the schizophrenic sample, anhedonia reached high significant levels only in 45% of patients (n = 36). This 'anhedonic' subgroup was distinguished by high scores in the disorganisation and negative dimensions. Positive correlations of anhedonia with disorganised and negative symptoms were also been detected. In the depressed sample, anhedonia reached high significant levels in only 36.9% of subjects (n = 24). This 'anhedonic' subgroup as distinguished by high scores in the depression severity and negative dimensions. Positive correlations of anhedonia with depressive and negative symptoms were also been detected.</p> <p>Conclusion</p> <p>In the schizophrenic sample, anhedonia seems to be a specific subjective psychopathological experience of the negative and disorganised forms of schizophrenia. In the depressed sample, anhedonia seems to be a specific subjective psychopathological experience of those major depressive disorder forms with a marked clinical depression severity.</p

A multi-layer network approach to MEG connectivity analysis

Recent years have shown the critical importance of inter-regional neural network connectivity in supporting healthy brain function. Such connectivity is measurable using neuroimaging techniques such as MEG, however the richness of the electrophysiological signal makes gaining a complete picture challenging. Specifically, connectivity can be calculated as statistical interdependencies between neural oscillations within a large range of different frequency bands. Further, connectivity can be computed between frequency bands. This pan-spectral network hierarchy likely helps to mediate simultaneous formation of multiple brain networks, which support ongoing task demand. However, to date it has been largely overlooked, with many electrophysiological functional connectivity studies treating individual frequency bands in isolation. Here, we combine oscillatory envelope based functional connectivity metrics with a multi-layer network framework in order to derive a more complete picture of connectivity within and between frequencies. We test this methodology using MEG data recorded during a visuomotor task, highlighting simultaneous and transient formation of motor networks in the beta band, visual networks in the gamma band and a beta to gamma interaction. Having tested our method, we use it to demonstrate differences in occipital alpha band connectivity in patients with schizophrenia compared to healthy controls. We further show that these connectivity differences are predictive of the severity of persistent symptoms of the disease, highlighting their clinical relevance. Our findings demonstrate the unique potential of MEG to characterise neural network formation and dissolution. Further, we add weight to the argument that dysconnectivity is a core feature of the neuropathology underlying schizophrenia