Dynamic Deconstructive Psychotherapy has used neuroscience findings to propose the specific neuroaffective deficits in processing of the emotion experiences as etiology of the borderline personality disorder. The purpose of this study was to evaluate the efficacy of the Dynamic Deconstructive Psychotherapy to improve the symptoms in patients diagnosed with the borderline personality disorder by remediation of neuro-affective defects. This study was designed as a randomized controlled trial using the pre-test, post-test and a control group. Thirty patients who were diagnosed with borderline personality disorder meeting the inclusion criteria, randomly divided into two groups. Both groups evaluated using both Borderline Evaluation of Severity over Time (BEST) and Patient Health Questionnaire Mood Scale (PHQ-9) questionnaires at the baseline and the over course of the treatment. Data analysis using repeated measures ANOVA indicated that the effect of measuring time (p=0.001) and time/group (p=0.010) on linear combination of the severity of borderline disorder and depression were significant. This result supports the efficacy of Dynamic Deconstructive Psychotherapy based on the neurocognitive remediation of the emotion processing using association, attribution and alterity techniques.
Borderline Personality Disorder; Neuro-cognitive; Emotion Possessing; Remediation; Psychotherapy.
Today, in all human societies, exceptional people, especially people with intellectual disability are regarded. Students and children mentally retarded in physical skills such as strength have serious shortcomings. This study aimed town to investigate the effect of sensory-motor training on muscle strength in children with educable mental retardation.
Materials and Methods: A quasi-experimental study was conducted. Thirty mentally retarded girls from primary school were selected through purposive sampling. Then, they were homogenized based on their pretest scores and were divided into two groups: fifteen experimental & fifteen control. That because of the evaluating reduction, the number of the control group reached ten. In this research, A Dynamometer and vertical jump test- was used to test physical strength. Sensory stimulation and physical exercises were practiced by the experimental group during twenty-four sessions. Each session was forty-five minutes long and was held three times a week. The control group performed the class programs. After twenty-four sessions both groups were tested. To investigate the research hypothesis Paired T-test and ANOVA2 × 2 and by SPSS software (version 21) were used. There were no significant differences between the two groups with regard to improving the muscle strength (p>0.05).
Statistical results showed no significant differences between the two groups with regard to improving the musclestrengt. Although applying the integrated sensory- motor is common among occupational therapists, it does not yield satisfactory results for muscle strength, according to the results of this study. Simultaneous utilization of other reference frames beside the sensory-motor Integration may result in better outcomes.
Sensory- Motor Integration; Muscular strength; Educable Mental Retardation
Long-term psychological stress can highly influence brain structure and functions. However, there are only few studies using electroencephalogram (EEG) that have examined this fact. The current study demonstrates a brain-computer interface (BCI) to classify EEG correlates of long-term mental stress in various mental states. The study was performed on 26 healthy right-handed university students and examination period was considered as a long-term mental stressor. Two groups of subjects were selected based on their stress levels evaluated by perceived stress scale (PSS-14). The subjects' EEG data were collected during eyes-open resting state and while they exposed to positive and negative emotional stimuli scored by self-assessment manikin questionnaire (SAM). Several types of features were extracted from EEG data including power spectrum density (PSD), laterality index (LI), correlation coefficient (CC), Canonical correlation analysis (CCA), magnitude square coherence estimation (MSCE), mutual information (MI), phase-slope index (PSI), Granger causality (GC) and directed transfer function (DTF). Subsequently, the extracted features were discriminated using several types of classifiers including k-nearest neighbor (KNN), support vector machine (SVM) and naive Bayesian (NB) classifiers. The proposed BCI was validated by one leave out method and investigation was done in different time windows using low and high frequency resolutions, 7 and 36 frequency bands respectively. The results showed that proposed system can accurately recognize subjects' stress level in various mental states. Moreover, the MI as a functional and DTF as effective connectivity methods yield the highest classification accuracy compared to other feature extraction methods.
Long-term mental stress; Electroencephalography; Emotional states; Classification
In this article, we show that how human decision makers behave in interactive decisions. We interpret
the players’ behavior with help of the concept of hyper-rationality. These interpretations help to
enlarge our understanding of the psychological aspects of strategy choices in games. With help of
this concept can be analyzed social sciences and society based on cognitive psychology approach such
that human society can be understood easily and predicted more fluently. In addition, we introduce
a new game in which there is a dilemma that this dilemma occurs in most societies. We investigate
this dilemma based on the claim that each player is hyper-rational. In this dilemma, a weak trust
has been created between players, but it is fragile. In many cases, our study provides a framework
to move towards cooperation between human decision makers.
Game theory; Decision making; Rationality; social dilemma game
Source determination in an inverse problem from the over-specified data plays a crucial role in cognitive
modeling. In this paper, an accurate and fast method is proposed for solving the one-dimensional
inverse problem concerning diffusion equation with source control parameter. The proposed method
is based on applying a compact finite difference scheme for spatial components and solving the system
that arised from this scheme by multigrid.
Brain activity; Inverse problem; Control parameter; Computational modeling