Intensive short-term dynamic psychotherapy provided by novice psychotherapists: effects on symptomatology and psychological structure in patients with anxiety disorders.

This study examines the effectiveness of psychotherapy provided by novice therapists, in an attempt to clarify the controversial relationship between treatment effectiveness and therapist experience. To achieve this, we examined the short- and long-term effectiveness of intensive short-term dynamic psychotherapy (ISTDP) in the treatment of patients with the Diagnostic and Statistical Manual of Mental Disorder, IV edition - Text Revision anxiety disorders, as provided by novice psychology trainees. Twenty-two patients with anxiety disorders were provided ISTDP. Patients improved significantly on all outcome indices, including the global assessment of functioning, the symptom checklist and the inventory of interpersonal problems, at the end of the treatment and at 6 and 12 month follow-up. In addition to these results, there was marked structural personality change as evidenced by ratings on the Shedler Westen assessment procedure (SWAP-200), at the same assessment moments; the SWAP-200 psychological health index score showed a meaningful increase in adaptive psychological resources and capacities, while the mean number of personality diagnoses decreased from the beginning to the end of therapy, and all patients maintaining their gains in 6-12 month follow-up. We conclude that ISTDP provided by novice psychotherapists is efficacious in bringing broad and in-depth change to pathology that can perpetuate anxiety disorders and other psychiatric conditions.

Cortical alpha rhythms are correlated with body sway during quiet open-eyes standing in athletes: a high-resolution EEG study.

Electroencephalographic (EEG; Be-plus Eb-Neuro) and stabilogram (RGM) data were simultaneously recorded in 19 elite karate and 18 fencing athletes and in 10 non-athletes during quiet upright standing at open- and closed-eyes condition in order to investigate the correlation between cortical activity and body sway when the visual inputs are available for balance. Our working hypothesis is that, at difference of non-athletes, athletes are characterized by enhanced cortical information processing as indexed by the amplitude reduction of EEG oscillations at alpha rhythms (about 8-12 Hz) during open- referenced to closed-eyes condition (event-related desynchronization, ERD). Balance during quiet standing was indexed by body "sway area". Correlation between alpha ERD and event-related change of the sway area was computed by a non-parametric test (p<0.05). It was found that alpha ERD (10-12 Hz) is stronger in amplitude in the karate and fencing athletes than in the non-athletes at ventral centro-parietal electrodes of the right hemisphere (p<0.02). Furthermore, there was a statistically significant correlation in the karate athletes between right ventral centro-parietal alpha ERD and body sway area (r=0.61; p<0.008): specifically, the greater the alpha ERD, the greater the percentage reduction of the body sway area when the visual inputs were available. These results suggest that parasylvian alpha ERD of the right hemisphere may reflect the cortical information processing for the balance in elite athletes subjected to a long training for equilibrium control.

The implicit function as squashing time model: a novel parallel nonlinear EEG analysis technique distinguishing mild cognitive impairment and Alzheimer's disease subjects with high degree of accuracy.

Objective. This paper presents the results obtained using a protocol based on special types of artificial neural networks (ANNs) assembled in a novel methodology able to compress the temporal sequence of electroencephalographic (EEG) data into spatial invariants for the automatic classification of mild cognitive impairment (MCI) and Alzheimer's disease (AD) subjects. With reference to the procedure reported in our previous study (2007), this protocol includes a new type of artificial organism, named TWIST. The working hypothesis was that compared to the results presented by the workgroup (2007); the new artificial organism TWIST could produce a better classification between AD and MCI. Material and methods. Resting eyes-closed EEG data were recorded in 180 AD patients and in 115 MCI subjects. The data inputs for the classification, instead of being the EEG data, were the weights of the connections within a nonlinear autoassociative ANN trained to generate the recorded data. The most relevant features were selected and coincidently the datasets were split in the two halves for the final binary classification (training and testing) performed by a supervised ANN. Results. The best results distinguishing between AD and MCI were equal to 94.10% and they are considerable better than the ones reported in our previous study ( approximately 92%) (2007). Conclusion. The results confirm the working hypothesis that a correct automatic classification of MCI and AD subjects can be obtained by extracting spatial information content of the resting EEG voltage by ANNs and represent the basis for research aimed at integrating spatial and temporal information content of the EEG.