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The aim of this study was the comparison of neurofeedback and biofeedback as a combination, against biofeedback intervention alone on athletic performance. 45 novice basketball players were allocated into three groups and assigned accordingly, two experimental and one control group. The experimental group 1 received 24 biofeedback sessions only, experimental group 2 received 24 biofeedback and neurofeedback sessions combined, whereas the control group didn't receive any form of intervention. Athletic performance scales were used before and after each intervention and multivariate analysis of covariance was used to compare the two groups. Results showed that in comparison to the control group, the athletic performance scales scores in both experimental groups were significantly increased. Furthermore, in experimental group 2 (combined method), we noticed a significantly greater improvement in performance levels than experimental group 1. We concluded that neurofeedback and biofeedback interventions combined, can be used as an effective method to enhance athletic performance.

Objectives: The modulation of the dorsolateral prefrontal cortex (DLPFC) activity enhanced the prospects of substance use disorders rehabilitation, using non-invasive brain stimulation, such as transcranial Direct Current Stimulation (tDCS). Methods: We carried out a randomized sham-controlled clinical trial to assess the effect of repeated tDCS at DLPFC on drug craving in 30 abstinent male methamphetamine users. The participants underwent 5 sessions of 20 minutes bilateral real or sham 2 mA tDCS (anode right/ cathode left) of DLPFC. The Desire for Drug Questionnaire (DDQ) was used for assessing instant craving. The cue-induced craving was rated on a Visual Analog Scale (VAS) after the verbal induction of craving. Results: The findings of this study indicated that cue-induced craving reduced significantly in tDCS related to sham (P

The aim of this study was the comparison of neurofeedback and biofeedback as a combination, against biofeedback intervention alone on athletic performance. 45 novice basketball players were allocated into three groups and assigned accordingly, two experimental and one control group. The experimental group 1 received 24 biofeedback sessions only, experimental group 2 received 24 biofeedback and neurofeedback sessions combined, whereas the control group didn't receive any form of intervention. Athletic performance scales were used before and after each intervention and multivariate analysis of covariance was used to compare the two groups. Results showed that in comparison to the control group, the athletic performance scales scores in both experimental groups were significantly increased. Furthermore, in experimental group 2 (combined method), we noticed a significantly greater improvement in performance levels than experimental group 1. We concluded that neurofeedback and biofeedback interventions combined, can be used as an effective method to enhance athletic performance.

Background: Obesity is one of the most serious public health concerns worldwide. Considering the multifactorial nature and increasing prevalence of obesity, many techniques have been proposed for its treatment, ranging from behavioral interventions to surgeries, but they are often ineffective, invasive, and costly. Furthermore, relapse and weight regain are common. Non-invasive brain stimulation techniques hold promise for modulating food-related brain processes and functions in these patients, potentially through increasing top-down control in response to food cue that supports reduction in calorie intake. Previous findings revealed that transcranial direct current stimulation (tDCS) over dorsolateral prefrontal cortex (DLPFC), a target site related to executive functions that support cognitive control of food craving, modulates the reward–control balance towards facilitation of cognitive control and possibly suppression of reward-related mechanisms that drive food cue-induced craving. However, understanding the neurocognitive mechanisms of tDCS over DLPFC on the brain networks of food craving remains largely unknown. Thus, an experimental clinical trial investigating the modulatory effects of tDCS over food cue-reactivity seems promising. Method: The NeuroStim-Obesity trial is a prospective, randomized, sham-controlled, double-blind single session tDCS trial targeting food craving in those with obesity. Once randomized, a total of 64 subjects (age range 18–61 years) with obesity (Body Mass Index (BMI) between 25-35 kg/m2) complete one session in which they receive either active or sham tDCS over the DLPFC. Active tDCS consisted of 2 mA of current applied continuously for 20 minutes with the anode placed over F4 and the cathode over F3 according to the 10–20 EEG system. The primary outcome is change in neural response to the food cue-reactivity task in the ventral striatum after a single session bilateral tDCS compared to sham stimulation. Secondary outcomes include changes in food craving evaluated by Food Craving Questionnaire-State (FCQ-S). We will also explore the predictive role of brain structural and functional networks assessed by structural, and functional magnetic resonance imaging (MRI) during both task performance and the resting-state that are acquired pre- and post-intervention to predict response to tDCS.Discussion: The results will provide novel insight into neuroscience for the efficacy of tDCS and will advance the field towards precision medicine for obesity. Exploratory results will examine the potential predictive biomarkers for tDCS response, and eventually to provide personalized intervention for treatment of obesity.Trial registration: This trial was retrospectively registered at Iranian Registry of Clinical Trials (IRCT) Identifier: IRCT20121020011172N4 at June 4, 2020, https://www.irct.ir/trial/45482. This protocol was prepared in accordance with the SPIRIT guidelines (Chan et al., 2013a, 2013b).Funding: Funding for this study was provided by the “Cognitive Science and Technologies Council (CSTC) of Iran” to Masoud Nosratabadi at University of Social Welfare and Rehabilitation, Tehran, Iran.

Background: Road accidents are a major cause of deaths, injuries, and financial losses globally, especially in developing countries. Iran is one of the countries with a high rate of road accidents causing considerable damage in different domains. Therefore, in order to tackle this problem, we need to examine its causes. Objectives: The aim of the present study was to examine the association of risky driving behavior with impulsiveness, attentional bias, and decision-making styles. Patients and Methods: This was a descriptive-correlational study. The sample included 117 male drivers, aged 20 - 34 years, attending car insurance agencies in Tehran. The participants were selected using the convenience sampling method. The data were gathered using the Manchester Driver Behavior Questionnaire (DBQ), the Barratt Impulsiveness Scale (BIS), the Decision-Making Style Scale (DMS), and the Dot Probe Task to assess attentional bias. All data analysis was conducted using Pearson correlation coefficient and multiple regression analysis, by using SPSS, version 22. Results: According to the results of the Pearson correlation coefficient, risky driving behavior was significantly correlated with impulsiveness subscales (P < 0.01) and attentional bias (P < 0.05). In addition, significant relationships were observed between risky driving behaviors and three decision-making styles, including rational (P < 0.05), spontaneous (P < 0.01), and avoidant (P < 0.01). Conclusions: Based on the study results, impulsivity, decision-making styles, and attentional bias as factors influencing drivers’ cognitive skills related to driving, could explain the increase in the frequency of risky driving behavior.

Introduction Clinical decision support system (CDSS) is an analytical tool that converts raw data into useful information to help clinicians make better decisions for patients. Aim The purpose of this study was to investigate the efficacy of neurofeedback (NF), in Attention Deficit Hyperactivity Disorder (ADHD) by the development of CDSS based on artificial neural network (ANN). Methods This study analyzed 122 patients with ADHD who underwent NF in the Parand-Human Potential Empowerment Institute in Tehran. The patients were divided into two groups according to the effects of NF: effective and non-effective groups. The patients' record information was mined by data mining techniques to identify effective features. Based on unsaturated condition of data and imbalanced classes between the patient groups (patients with successful NF response and those without it), the SMOTE technique was applied on dataset. Using MATLAB 2014a, a modular program was designed to test both multiple architectures of neural networks and their performance. Selected architecture of the neural networks was then applied in the procedure. Results Eleven features from 28 features of the initial dataset were selected as effective features. Using the SMOTE technique, number of the samples rose to around 300 samples. Based on the multiple neural networks architecture testing, a network by 11-20-16-2 neurons was selected (specify>00.91%, sensivity=100%) and applied in the software. Conclusion The ANN used in this study has led to good results in sensivity, specificity, and AUC. The ANN and other intelligent techniques can be used as supportive tools for decision making by healthcare providers.

Background: Craving is an important factor in predicting relapse in opioid-dependent patients. Objectives: The aim of the present study was to determine which combination therapy, including emotion regulation training followed by tDCS or tDCS followed by emotion regulation training, is more effective in reducing current drug craving and drug-use thoughts and fantasies in opioid-dependent patients in Zahedan, Iran. Patient and Methods: A quasi-experimental study with a pretest-posttest design and two intervention groups was conducted. From eight randomly-selected centers, asample of 28 patients was selected based on the inclusion and exclusion criteria. They were randomly divided into two intervention groups. The first group received eight sessions of tDCS, followed by eight sessions of emotion regulation training. The second group received eight sessions of emotion regulation training followed by eight sessions of tDCS. The statistical population included all opioid-dependent patients at medium-term residential drug rehabilitation centers in Zahedan, Iran, in 2018 - 2019. The data were gathered using the personal drug use questionnaire, the desires for drug questionnaire (DDQ), and the drug use thoughts, fantasies, and temptations questionnaire. All analyses were performed using SPSS-16. Results: The results of repeated measures ANOVA showed that both sequences had a significant, long-term effect on the reduction of current drug craving and drug-use thoughts and fantasies in opioid-dependent patients. In addition, emotion regulation training followed by tDCS was more effective in reducing current drug craving and drug-use thoughts and fantasies than tDCS followed by emotion regulation training. Conclusions: Combination therapy can significantly reduce drug craving in opioid-dependent patients and starting treatment with emotion regulation training followed by tDCS can lead to better results.

International audience; There is growing interest in non-invasive brain stimulation (NIBS) as a novel treatment option for substance-use disorders (SUDs). Recent momentum stems from a foundation of preclinical neuroscience demonstrating links between neural circuits and drug consuming behavior, as well as recent FDA-approval of NIBS treatments for mental health disorders that share overlapping pathology with SUDs. As with any emerging field, enthusiasm must be tempered by reason; lessons learned from the past should be prudently applied to future therapies. Here, an international ensemble of experts provides an overview of the state of transcranial-electrical (tES) and transcranial-magnetic (TMS) stimulation applied in SUDs. This consensus paper provides a systematic literature review on published data - emphasizing the heterogeneity of methods and outcome measures while suggesting strategies to help bridge knowledge gaps. The goal of this effort is to provide the community with guidelines for best practices in tES/TMS SUD research. We hope this will accelerate the speed at which the community translates basic neuroscience into advanced neuromodulation tools for clinical practice in addiction medicine.

According to the American Psychiatry Association, Attention deficit hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders in the childhood. Considering the importance of cognitive approaches to rehab such a disorder, the purpose of the present study is to design a clinical decision support system to propose suitable computerized cognitive rehabilitation programs. At first, the scores of parameters of attention and response control in the IVA test were extracted. Then, by interviewing with experts and analyzing the results, a set of computerized cognitive rehabilitation programs (Captain Log, Lumosity, Maghzine) to empower attention and response control parameters were selected, modeled and implemented as if-then rules. To design and implement the system, the MATLAB (2016 b) programming environment was used. Designed clinical decision support system was able to provide computerized cognitive rehabilitation programs with regard to defective attention and response control parameters. It could help therapists and psychiatrists to improve the symptoms and rehab the children and adolescents with Attention deficit hyperactivity disorder.

Empirically, mental health and mental illness are not opposite ends of a single measurement continuum. In view of this fact, Keyes (J Health Soc Behav, 43:207–202, 2002) operationalizes mental health as a syndrome of symptoms of both positive feelings (emotional well-being) and positive functioning (psychological and social well-being) in life. In his comprehensive model, the presence of mental health is described as flourishing in life, and the absence of mental health is characterized as languishing in life. The aim of this study was to investigate the discriminatory power of Big Five personality traits in discriminating among the levels of mental health continuum using an Iranian university student sample. Findings revealed that respondents with different levels of mental health differed significantly on four of the five personality traits (extraversion, neuroticism, conscientiousness, and agreeableness). All in all, the results of this study converged with prior findings about the importance of Big Five personality traits in predicting well-being.

Aim of the study was to assess the relationship between social participation and Sense of Community in a sample of University students and the impact of such variables on Social well being. A further aim was to assess the generality of the relationships between these constructs across different countries, and specifically, the USA, Italy and Iran. The sample includes 200 Italian, 125 American and 214 Iranian University students, male and female. Results show higher levels of social participation, Sense of Community and Social well being among American students. Sense of Community is positively correlated with social participation in all three samples; however, only among Italian students social participation positively predicts Social well being. Implications of results will be discussed.

Introduction: Attention Deficit/Hyperactivity Disorder (ADHD) is a disorder of neurobiological behavioral system. This disorder includes features such as attention deficit, impulsivity, and chronic, disproportionate-with-growth hyperactivity which reduce the child's ability to regulate, control, organize his behavior and cause attention deficit in activity of daily living (ADL). ADHD is one of the most common childhood disorders. The aim of this study was to investigate the effect of QEEG-based biofeedback on behavioral and attention factors of 7 to 14 year-old boys diagnosed with ADHD. Method: 40 boys diagnosed with ADHD were randomly assigned into the experimental and control groups. Integrated Visual and Auditory (IVA) test and Children's Behavioral Check List (CBCL) were used before the treatment and after 8 intervening weeks of treatment in both groups. Moreover, the brain mapping (QEEG) of the experimental group was used to design a treatment protocol. The experimental group received 24 sessions of neurofeedback therapy three times a week. The acquired data was analyzed using the Analysis of Covariance (ACNOVA). Results: Our findings demonstrated a significant difference in test results between the experimental and control groups upon IVA and CBCL tests following the neurofeedback intervention. Moreover, there was a significant difference between pre- and post-tests in the neurofeedback group. Interaction effect was insignificant at the time. Conclusion: Results of the present study showed that neurofeedback can bring significant improvements in attention factors especially, sustained attention and children's externalizing behaviors. As such, neurofeedback may be considered as one of the therapeutic modalities used along with core therapies and medication, though, more research is needed to compare the clinical effects of different treatment protocols with one another.