فصلنامه علوم اعصاب شفای خاتم
سال یازدهم شماره 1 (پیاپی 54، زمستان 1401)

Alzheimer's disease (AD) is a degenerative and progressive disease of the brain that causes the deterioration of intellectual abilities. Approximately 5% of people over 70 years old and 20% of people over 80 years old suffer from this disease. So far, many tools and methods have been provided to diagnose AD. However, in most of these methods, the interactions and connections of different parts of the brain are not considered. Since AD can affect different structures of the brain, damage to any part of the brain disrupts its interaction with other regions.

The indexes of effective communication between different parts of the brain in two groups of healthy people and subjects with AD were extracted using Granger causality analysis. Following statistical comparisons between the quantitative values of the indexes in different EEG channels, we examined effective communication. Then, we used linear differential analysis to separate the two groups of participants. The data used in the research include EEG signals from 10 healthy subjects and 8 patients with AD (mild and severe).

With the correct diagnosis of all patients and only one wrong diagnosis of a healthy subject, an accuracy of 83.33%, an accuracy of 90%, a sensitivity of 100%, and a diagnosis of 80% were obtained for the test data. The effective communication rate of Fz and Cz channels for healthy people is higher than the effective communication of the Pz channel, while for patients with AD, the lowest effective brain communication was observed in the Fz channel, and the highest communication was observed in the Pz channel and sometimes in the Cz channel.

The results of Granger features are far better than the results of linear features, despite the fact that the number of extracted linear features was more than Granger features. Therefore, the effectiveness of Granger causality has been proven once again, and it can be said that the interaction indices between EEG channels provided valuable information for classification and led to better identification of patients with AD.

With the increasing use of computers and the Internet, computer game addiction has been suggested as a new psychiatric disorder. Much evidence has shown that at the level of neural circuits, computer game addiction is similar to drug addiction, although there are very few studies comparing brain functions. The present study aimed to compare cold executive functions between people addicted to gaming, patients addicted to drugs (Heroin and methamphetamine), and normal people.

The sample consisted of 180 men (45 subjects in 4 groups of heroin-addicted patients, methamphetamine-addicted patients, people addicted to computer games, and normal people) who were selected by the available sampling method. N-back test, continuous performance test, and Passat test were used to determine visual working memory, sustained attention, and auditory working memory. Multivariate variance analysis and univariate variance analysis were used for data analysis.

The results showed that the values of visual working memory, sustained attention, and auditory visual working memory in substance-dependent groups were significantly lower compared to normal and game-dependent groups.

It seems that the game-dependent group is completely similar to the normal group in terms of cold executive functions, and there is no similarity between the game-dependent group and the substance-dependent groups.

 Decision-making is one of the high orders of the brain’s cognitive functions. Most real-world decisions must be made in the face of uncertainty, and human’s process received information from the environment hierarchically. However, in the presence of hierarchy, the sources of the received negative feedback are ambiguous. Therefore, understanding how people reason with incomplete and ambiguous information is one of the main problems of cognitive psychology. People resolve this ambiguity after one or more attempts by evaluating the number of negative feedbacks, the choice confidence, and the expected accuracy of their choice. However, it is not well understood how confidence in lower-level decisions affects higher-level decisions.

We tested this hypothesis with a hierarchical decision-making task in which the subjects participated in a psychophysical experiment to determine the direction of random points and report their confidence about the decision. They were also instructed to make a high-level decision called "environment". From the collected behavioral data, the effects of each factor in hierarchical decisions were statistically isolated and studied by a logistic regression model.

We observed that the average confidence of individuals in the face of consecutive negative feedback has an increasing trend as they approach the switch trial. In the switch trial, it reaches its highest value, which is also higher than the overall average of confidence.

The present study indicates that decision confidence–In the consecutive errors- modulate the switch profile and encodes the probability of switches. These results highlight the critical rule of confidence in hierarchical decision-making and point out that it has a threshold for high-level decision.

Multiple Sclerosis (MS) is a chronic, progressive, and demyelinating disease of the central nervous system that causes numerous physical and psychological complications. The chronic nature and frequent problems faced by patients increase the need for support from others. Social support can play a decisive role in adapting the patient to his illness. The present study aimed to determine the status of social support in patients with MS.

This cross-sectional study was conducted on all MS patients referred to the MS Association and Neurology Clinic of Valiasr Hospital, Zanjan. In order to measure the social support status of patients, a Wax questionnaire was used.

The mean age of 202 patients with multiple sclerosis was 34 ± 6.65 years. Among these patients, 152 (75.2%) were women, 136 (67.3%) were married, and 74 (36.6%) had a university education. The mean total score of social support in these patients was 50.9 ± 9.57. A significant relationship was observed between social support and the variables of marital status, place of residence, education, occupation, and income. Using the multiple linear regression model, the level of education and income predicted up to 28% of social support in these patients.

The results of the present study indicated that the level of social support in patients with MS in Zanjan city was moderate. This requires providing more supportive care from their families and friends in order to increase the patient's ability to face the problems and complications of the disease and achieve a better adaptation. Moreover, the relationship of social support with education and income clarifies the role of socioeconomic factors in the amount of support perceived by the patient and the importance of supportive interventions in the target groups.

The evaluation of attention as one of the human cognitive abilities is of great importance. Although methods for assessing attention ability have been developed and used, the presence of interfering factors has reduced their validity and reliability. Therefore, using the direct outputs of the brain system and analyzing its function in cognitive activities has become very important. This research tries to identify a relationship between event-related potential (ERP) and integrated visual and auditory (IVA) test indices.

EEG signals (19 channels) and IVA tests of 28 healthy volunteers (22 men and 6 women with an age range of 22 to 32 years) were recorded simultaneously. ERPs to auditory and visual stimuli were obtained by the simultaneous averaging method of extraction and brain topography for each stimulus. Using the Lucas-Kanade method, the optical flow was obtained on brain maps and movement vectors were identified and drawn in consecutive maps. The motion vectors show the location and the number of changes in the activity of each map compared to the other samples. Based on the local connectivity criteria, features were extracted from the brain graphs. The indicators of attention and response control, including vigilance, concentration, speed, caution, stability, endurance, and understanding, were obtained based on the IVA test and were estimated by the support vector-regression machine.

In order to evaluate the regression, the correlation index was calculated, which are vigilance (0/80), Focus (0/81), Speed (0/85), Prudence (0/88), consistency (0/90), Stamina (0/85), and comprehension (0/80).

According to the high correlation coefficients obtained between the local characteristics of optical flow extracted from the brain graph of the ERP signals and the attention indicators in the IVA test, it can be suggested that there is a significant relationship between the electrical activity of the brain and the ability to pay attention.

Separation anxiety disorder is one of the most common emotional disorders in childhood and adolescence and an important risk factor for mental health throughout life. The research aimed to determine the effectiveness of attachment-based psycho-educational interventions in reducing the symptoms of separation anxiety disorder in children and the parenting methods of mothers of affected children.

This research method of this research was semi-experimental with a pre-test, post-test, and follow-up design with a control group. Seven counseling and psychotherapy centers in Tehran, Iran were selected by random cluster method, after the initial screening of children with emotional disorders listed for school age, six mothers of these children were referred from the centers, after the sample drop, and finally, twenty-four of the remaining mothers were randomly assigned to the experimental and control groups. The data was collected using Spirafkin and Gado's Children's Disease Symptoms Questionnaire and the Alabama Parenting Questionnaire.

The results showed that the psycho-educational attachment-based package significantly reduces the symptoms and severity of separation anxiety disorder, and this effect was also significant in the follow-up phase. Furthermore, the mentioned package increased the parenting methods of mothers' involvement as well as positive parenting and significantly reduced poor monitoring/supervision and inconsistency.

The psycho-educational attachment-based training package can be considered an efficient program to improve the parenting practices of mothers and reduce the symptoms of separation anxiety disorder in children.

Transcranial electrical stimulation (tES) is a non-invasive brain stimulation technique that can produce temporary changes in the excitability of cortical areas by applying a weak electrical current to the skull. The specialists’ tendency to use tES as a complementary or alternative tool for the treatment of psychiatric and neurological disorders has grown significantly in the last decade. This research has explained the nature of electrical stimulation of the brain, the stimulating devices, its history, underlying physiological mechanisms, and their applications in the treatment of neurological and psychiatric disorders. It also has taken a coherent look at the effects of cognitive training along with tES in the treatment of psychiatric patients.

In the field of the effectiveness of tES intervention on mood disorders, anxiety, attention deficit-hyperactivity disorder, autism, obsessive-compulsive disorder, and schizophrenia, research conducted and showed that this treatment method is effective in improving the cognitive performance, moderating the negative emotions, and reducing the symptoms of individuals’ disease. Based on this, along with psychotherapy and medical treatment, tES can be used as a non-invasive treatment to help patients with psychiatric problems.

Alzheimer's disease is an irreversible neurodegenerative nervous disorder. Currently, both factors of amyloid-beta plaques and tau hyperphosphorylation, as well as the synergistic effects of these two factors, are leading changes in this disease. The researchers’ efforts to entirely cure the disease have not been successful because of the complexities of the pathophysiology of the disease. Furthermore, the blood-brain barrier is a serious challenge in delivering novel drugs. In recent years, different strategies have been developed to improve the cognitive skills of patients.

Nowadays, the disappearance of the boundaries between different sciences has led to the development of new strategies which often offer non-invasive methods. These methods, such as biophysical interventions, improve the treatment of neurodegenerative diseases, such as Alzheimer's disease. This narrative review aims to describe some of these strategies and discuss their pros/cons over the traditional methods of drug consumption.

MicroRNAs (miRNAs) are small, noncoding RNA molecules that act as highly potent post-transcriptional regulators of gene expression. Over past decades, miRNAs were found to modulate brain development and brain function. Schizophrenia (SCZ) is a complex and severe psychiatric disorder and both genetic and environmental risk factors are implicated in SCZ. Recent studies have identified that dysregulation of miRNAs expression contributes to the pathogenesis of SCZ.

Identification of SCZ- related miRNAs may be potential biomarkers in the diagnosis and more efficient therapies of SCZ. In this review, we provide an overview of the recent findings of the SCZ-associated dysregulation of miRNAs.

The purpose of this review is to update the significance of existing biomarkers as well as new biomarkers that are emerging and can be clinically implemented in the near future. Due to the heterogeneity in the occurrence and diagnosis of TBI, in the last two decades, studies related to the acquisition of biomarkers for this major health challenge in the world have increased exponentially. Detection of various biomarkers, such as the molecules in cerebrospinal fluid and blood, as well as imaging approaches, have been widely evaluated.

In several studies, these biomarkers are used to measure the severity of brain damage, identify patients at higher risk for adverse outcomes, and predict the duration of recovery. Despite the significant progress in this field, each of the existing biomarkers has its own limitations, so many studies on new biomarkers such as microRNA, extracellular vesicles and neurometabolites are being conducted. As a result, updating the new findings of these biomarkers has great biological and clinical importance.