فهرست مطالب

Caspian Journal of Neurological Sciences - Volume:3 Issue: 9, Jul 2017

Caspian Journal of Neurological Sciences
Volume:3 Issue: 9, Jul 2017

  • تاریخ انتشار: 1396/04/28
  • تعداد عناوین: 7
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  • Fereshteh Saliminia *, Milad Amini-Masouleh Pages 60-65
    Background
    There are some convincing shreds of evidence indicating that memory can direct attention. The local efficiency of an area in the brain, as a quantitative feature in a complex network, indicates how the surrounding nodes can transfer the information when a specific node is omitted. This feature is a scale for measuring efficient integration of information in the brain.
    Objectives
    The purpose of the present study is to predict the reaction time using the local efficiency variable while doing memory-guided attention task.
    Materials And Methods
    The fMRI database of a research done in New York University during a visual search task was used for this study. Thirty-five right-handed healthy participants (51% female, mean age= 21.7 years) were recruited at New York University. SPM was used for pre-processing fMRI images, and CONN was used for calculating the values of local efficiency. SPSS was also used for statistical analysis of the study.
    Results
    Results of the study revealed that local efficiency of the right hippocampus can positively predict the reaction time during memory-guided attention tasks.
    Conclusion
    The findings of the study demonstrated that the hippocampus area has a significant role in the performance of memory-guided attention, and this significant role of the hippocampus reveals that long-term memory uses the hippocampus and affects the movement and attention of eyes on the target.
    Keywords: Reaction Time, Memory, Hippocampus, Attention, Functional Neuroimaging
  • Pooyan Sohrabi-Otaghvari *, Barzin Gavtash, Masoud Sharifi, Shahriar Shahidi Pages 66-71
    Background
    Caffeine is a kind of methylxanthine whose consumption can promote the cognitive and executive functions of the human brain.
    Objectives
    In this study, we seek to investigate the effect of drinking coffee on the period of the eye movement fixation component.
    Materials And Methods
    The research was of the quasi-experimental type. 60 subjects were randomly divided into two groups of thirty. The subjects in one group drank coffee before the experiment was conducted. The other group, which is the control group, did not. Both groups would then read a text, and the eye movement tracking device would record the fixation periods of the subjects’ eyes while reading.
    Results
    The results of the independent t-test comparing the mean fixation time in the two groups demonstrated that the difference was significant at the 0.001 level, where the group that drank coffee before studying had significantly less fixation time than the control group. Additionally, Cohen’s d index of 4.29 determined that the difference lies in the maximum effect size range.
    Conclusion
    It can be concluded that drinking a cup of coffee before studying can lead to decrease in eye movement fixation period and increase in information encoding and processing speed.
    Keywords: Caffeine, Fixation, Ocular, Reading, Eye Movements
  • Hassan Sabourimoghadam, Saied Sabaghypour *, Mohammadtaghi Saeedi, Abbas Shafaei Pages 72-78
    Background
    Based on the studies which have investigated conscious and unconscious processes, simple arithmetic operations such as addition and multiplication can be automatically processed in the brain and affect subsequent responses. However, most studies have focused on addition and multiplication of one-digit numbers. In this research we used subliminal priming paradigm to assess automatic retrieval of subtraction operation for the first time.
    Objectives
    The aim of this study was to use a subliminal priming paradigm in a naming task and investigate the automatic and unconscious processing of the subtraction operation. Research of this kind can help us determine different levels of unconscious and conscious processing in the brain.
    Materials And Methods
    Forty-five graduate student in psychology at the Faculty of Education and Psychology, University of Tabriz (between 18 and 25 years; mean 20.7, SD=2.7) participated in the experiment. For presenting the stimuli, an open-source software (DMDX) was used and presented on a 15-inch monitor. In the experiment, in the congruent condition, the prime was congruent with the target in terms of subtraction calculation result and in the incongruent condition there was no logical connection between the two stimuli. The vocal reaction time (RT) of participants was recorded and paired t-test analysis was conducted for comparison of the two conditions.
    Results
    The data showed that naming the target by the participants is carried out faster when the two stimuli are congruent with each other in terms of the result of the operation.
    Conclusion
    These findings may have implications on the levels of mathematical operations. In conclusion it seems that the calculation of one-digit numbers can happen at the level of simple neuronal circuits and may be carried out without conscious-awareness. The findings confirm the fact that calculating subtraction for one-digit numbers does not require conscious effort and can be processed automatically.
    Keywords: Unconscious (Psychology), Task Performance, Analysis, Mathematical Computing
  • Saeede Shoja-Razavi * Pages 79-87
    Background
    Normal children understand and use embodiment metaphorical expressions since they start learning a language, but children suffering from William’s syndrome even in adulthood have little understanding of such expressions and they can hardly use them.
    Objectives
    This study is an attempt to teach embodiment metaphorical expressions of 4.5-5 year old Persian children suffering from William’s syndrome.
    Materials And Methods
    Ten 4.5-5 year old Persian children with William’s syndrome were studied using dual cards by Bialeka-Pikul in five sessions with required intervals and measuring their amount of their learning through a test of understanding of the Persian language and using such expressions. This method of investigation can be used as a therapeutic protocol in this area. The method used in this study was descriptive-experimental and carried out without making any changes in the variables.
    Results
    Results of this study showed that after five sessions with this therapeutic method, each of the 10 children with William’s syndrome moved from level one of relative understanding, which means formation of metaphorical structure, to level two of metaphorical understanding of embodiment expressions. In this group, the metaphor of taste with 2.50 points was the highest and the metaphor of shape in the expression with 0.8 point was the lowest.
    Conclusion
    Control groups in filling the blanks had the highest number of correct answers in the characteristic taste followed by the characteristics smell, speed, and color, and had the least points with metaphorical phrases that reflect the use of minimum idiomatic metaphors.
    Keywords: Cognitive Therapy, Metaphor, Linguistics
  • Abdolhossein Shamsi, Ahmad Abedi, Amir Ghamarani, Ahmad Yarmohamadian Pages 88-94
    Background
    The social information processing model is one of the most up-to-date cognitive models in the field of interpersonal interactions. This social-interaction-based model can be successfully used to investigate the reasons for emotional and behavioral problems and prevent them in children and adolescents.
    Objectives
    The present study was conducted to investigate the efficacy of the social information processing model in predicting behavioral disorders in children.
    Materials And Methods
    The present study used a descriptive correlational regression analysis. The study sample comprised 100 primary school students selected from different districts in Isfahan, Iran (2015-2016), using random multistage cluster sampling. Data collection tools included the Achenbach child behavior checklist and social stories by Bryan and Turcasia. The stepwise multivariate regression was used to analyze the data. SPSS software version 18 was also used for statistical analysis of the study.
    Results
    The results indicated that the social information processing model can significantly predict behavioral disorders (p≤0.0001). In other words, behavioral disorders were more prevalent in the students with lower social information scores.
    Conclusion
    The social information processing model was found to predict child behavioral disorders.
    Keywords: Child Behavior Disorders, Cognition, Social Behavior
  • Roghieh Madjidzadeh*, Mansour Hakimjavadi, Masoud Gholamali Lavasani Pages 95-105
    Background
    Although psychological distress can interfere with diabetes care, the effectiveness of Group Cognitive-Behavior Therapy in improving diabetes outcomes is unknown.
    Objectives
    The purpose of this study was to reduce anxiety symptoms and improve glycemic control in diabetic patients. The samples were 24 diabetic patients (12 in experimental group and 12 in control group) aging from 40 to 60 years.
    Materials And Methods
    The anxiety symptoms and glycemic control were assessed prior to and following Group Cognitive-Behavior Therapy (CBT) using self-report instruments and through measuring glycosylated hemoglobin and fasting blood sugar (FBS). SPSS software version 16 was also used for statistical analysis of the study.
    Results
    The results, analyzed by the analysis of covariance, indicated that after group-therapy, there were no significant differences between the two groups in as far as the means of FBS concentration. Moreover, a significant decrease was seen in hemoglobin A1c (HbA1c) concentration after group-therapy in the experimental group. As far as anxiety, no significant difference was observed between the two groups following the therapy; however, after group therapy, the anxiety of the women in the experimental group underwent a significant decrease. In addition, a reduction in anxiety symptoms was observed post group-therapy, and the reoccurred significant changes in the glycemic control.
    Conclusion
    The findings of this pilot study suggest that group-therapy is a feasible intervention for patients with diabetes and anxiety symptoms. However, further research is needed if a development is to be had regarding the interventions that improve glycemic control
    Keywords: Anxiety, Psychotherapy, Diabetes Mellitus
  • Babak Mohammadzadeh * Pages 106-117
    Background
    Identifying mental disorder biomarkers is one of the leading goals of the clinical science.
    Objectives
    This study aimed to provide an artificial intelligence based solution and software program to diagnose the type and severity of mental disorders according to the quantitative electroencephalogram (QEEG) of patients.
    Materials And Methods
    The QEEG data collected from 45 patients addicted to one of the substances (crystal-glass methamphetamine [n=15], tramadol [n=15], heroin/opium [n=15]) and 15 healthy people. They were entered into SPSS version 20 and analyzed by Discriminant Analysis (DA) function and simultaneously used as the Training Group of the artificial neural network (ANN) of the diagnosis software. In order to test and validate the software, in the following, QEEG was also recorded from the remaining 60 subjects (45 addicted and 15 healthy people).
    Results
    The results obtained from the software were 0.836, 0.884, 7.21, 0.19, 0.712, and 0.890, respectively. Meanwhile, the values of these parameters for DA were 0.677, 0.66, 1.99, 0.49, 0.363, and 0.739, respectively. The results of the software significantly improved the diagnosis. Totally nine discriminant functions were obtained for the frontal, parietal and central lobes was obtained according to the delta, Theta, Alpha and Beta variables.
    Conclusion
    As a result, intelligent diagnosis software provided can be used with a high sensitivity and great specificity rather than Paper-Pencil tests for accurate diagnosis of the type of disorder and expressing its severity at a confidence level that is scientifically computed and displayed.
    Keywords: Artificial Intelligence, Diagnosis, Electroencephalography, Neurolinguistic Programming, Discriminant Analysis