Dear colleagues,
It is my pleasure to present to you the fifth issue of 2015 featuring the first WFSBP Consensus Report for Biomarkers of Schizophrenia, part I: Neurophysiology, as well as original investigations with a focus on physiological components of emotional states and affective disorders.
The first WFSBP Consensus Report for Biomarkers of Schizophrenia reviews current literature on the identification and assessment of neurophysiological markers using electroencephalography (EEG) and magnetoencephalography (MEG), transcranial magnetic stimulation (TMS), polysomnography, registration of event related potentials (ERPs), assessment of smooth pursuit eye movements and antisaccade paradigms. The utility of the components for diagnostic purposes and prediction of disease progression and treatment is discussed and promising areas of research are presented.
In a meta-analysis, Aoki and colleagues set out to outline the neural correlates of atypical emotional face processing in individuals with autism. The authors used 13 studies with functional magnetic resonance imaging (fMRI) and emotional-face processing tasks and identified a hyperactivation of the left caudate as the most robust finding.
Jovovic and coworkers set out to develop a structural equation model of negative affectivity that involves interaction of glucocorticoid receptor (GR) signaling, personality dimensions and recent stressful life events. Plasma cortisol levels were collected in patients with major depression (MDD) and in healthy controls. The authors found that GR signalling parameters, neuroticism and extraversion had a direct independent effect on measures of negative affectivity.
Chaspari and colleagues report the development of ecologically valid procedures for collecting reliable and unbiased emotional data towards computer interfaces with social and affective intelligence targeting patients with mental disorders. They introduce the Athens Emotional States Inventory (AESI) as audiovisual database for five emotional states: anger, fear, joy, sadness and neutral. First results yield an accuracy rate of up to 75.15% for automatically recognizing emotions in the inventory.
Lin and colleagues examined respiratory sinus arrhythmia (RSA), a high-frequency spectrum component of heart rate variability (HRV), in suicide attempters with either depressive or bipolar disorder and investigated the relationship of RSA to symptoms and length of hospitalization. Analysis showed that RSA was positively associated with a higher suicidal ideation score and hospitalization length.
Lithgow and coworkers evaluated a potential new biomarker for MDD utilizing the recording of electrical activity from the outer ear canal referred to as electrovestibulography (EVestG). Sensory oto-acoustic features were extracted from EVestG data to compare patients with current MDD symptoms, patients in remission or having mild MDD symptoms and healthy controls. Analysis yielded classification accuracy rates of between 77 and 87% for separating all groups.
By measuring HRV indices, Chang and coworkers examined whether cardiac autonomic function can be used as a biomarker to distinguish bipolar II (BPII) depression from MDD. Results revealed that patients with BDII depression showed cardiac sympathetic excitation with reciprocal vagal impairment, whereas MDD patients showed only the latter. Depression severity contributed to decreased HRV and vagal tone in both patient groups, whereas increased sympathetic tone only in BDII patients.
Finally, a brief report by D’Urso and colleagues presents results on the safety, efficacy, and feasibility of inhibitory transcranial direct current stimulation (tDCS) for the treatment of behavioural abnormalities of autistic patients. Eight out of 10 patients improved in their abnormal behaviours, the remaining two showed no changes. The most significant positive change was found with respect to hyperactivity and non-compliance.
Yours sincerely,
Siegfried Kasper, MD
Chief Editor