فهرست مطالب

Caspian Journal of Neurological Sciences
Volume:7 Issue: 25, Apr 2021

  • تاریخ انتشار: 1400/04/13
  • تعداد عناوین: 7
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  • Laleh Esfandiari*, Reza Nilipour, Parviz Maftoon, Vahid Nejati Pages 51-59
    Background

    The P600 brain wave reflects syntactic processes in response to different first language (L1) syntactic violations, syntactic repair, structural reanalysis, and specific semantic components. Unlike semantic processing, aspects of the second language (L2) syntactic processing differ from the L1, particularly at lower levels of proficiency. At higher L2 proficiency, syntactic violations are more likely to result in P600, similar to the L1 native speakers.

    Objectives

    This study aims to assess the effect of proficiency on L2 syntactic processing in late bilinguals and determine whether L1-like cerebral activation patterns will result.

    Materials & Methods

    In this descriptive quantitative research, the subjects were two groups of Persian-English bilinguals (L1=Persian, L2=English; n=10 high-proficient, n=10 low-proficient; gender=female who started learning English as a Foreign Language (EFL) after the age of 15 through explicit instructions. Within the violation paradigm, Event-related Potentials (ERPs) were collected from the subjects in the neurocognitive lab of Shahid Beheshti University, Iran, in 2019- 20. The experimental trials of the ERP task included violated English regular past tense verbs. ERP components were compared with those of the L1 (components closer to P600).

    Results

    The t-value for P600 peak latency differed significantly only for the Incorrect past tense verb (ICV) condition and only in O2 (P=0.039463, t=2.2205, CI: 0.003112- 0.11249, P<0.05) between the two groups (higher in the high proficient group).

    Conclusion

    P600 for the high-proficient group demonstrated that L2 proficiency was a more determinant factor in L1-like cortical representation of L2 than the age of acquisition and or the type of context.

    Keywords: Language, Semantics, Brain waves
  • Reyhaneh Zarifiyan Irani Nezhad*, Ghasem Sadeghi Bajestani, Reza Yaghoobi Karimui, Behnaz Sheikholeslami, Farah Ashrafzadeh Pages 60-73
    Background

    Epilepsy is a brain disorder that changes the basin geometry of the oscillation of trajectories in the phase space. Nevertheless, recent studies on epilepsy often used the statistical characteristics of this space to diagnose epileptic seizures.

    Objectives

    We evaluated changes caused by the seizures on the mentioned basin by focusing on phase space sorted by Poincaré sections.

    Materials & Methods

    In this non-interventional clinical study (observational), 19 patients with generalized epilepsy were referred to the Epilepsy Department of Razavi Hospital (Mashhad, Iran) between 2018 and 2020, which their disease had been controlled after diagnosis and surgery. In evaluating the effects of this disorder on the oscillation basin of the EEG trajectories, we used the MATLAB@ R2019 software. In this computational method, we sorted the phase space reconstructed from the trajectories by using the radial Poincaré sections and then extracted a set of the geometric features. Finally, we detected the normal, pre-ictal, and ictal modes using a decision tree based on the Support Vector Machine (SVM) developed by features selected by a genetic algorithm.

    Results

    The proposed method provided an accuracy of 94.96% for the three classes, which confirms the change in the oscillation basin of the trajectories. Analyzing the features by using t test also showed a significant difference between the three modes.

    Conclusion

    The findings prove that epilepsy increases the oscillations basin of brain activity, but classification based on the segment cannot be applicable in clinical settings.

    Keywords: Electroencephalography, Epilepsy, Decision trees
  • Farzaneh Sadeghian*, Hadiseh Hasani, Marzieh Jafari Pages 74-83
    Background

    Autism Spectrum Disorder (ASD) occurs based on the continuous deficit in a person’s verbal skills, visual, auditory, touch, and social behavior. Over the last two decades, one of the most important approaches in studying brain functions in autistic persons is using functional Magnetic Resonance Imaging (fMRI).

    Objectives

    It is common to use all brain regions in functional extraction connectivity, which leads to high dimensional space. In this study, a Genetic Algorithm (GA) has been used to select effective regions for the generation of Functional Connectivity Matrix (FCM) to differentiate between healthy and autistic people. The aim is to increase accuracy, reduce processing time, and lower the dimension of the functional connectivity matrix.

    Materials & Methods

    In this analytical study, the dataset includes 820 fMRI images consisting of 445 healthy samples and 375 people with ASD obtained from the autism brain imaging data exchange database. The K-nearest neighbor classification algorithm and the genetic algorithm were used to optimize the identification of two groups of autism and healthy people.

    Results

    Regarding the large dimensions of the search space, the use of genetic algorithms after 100 replications estimated the accuracy for test and validation data at 61.08% and 62.59%, respectively. The obtained results show that the genetic algorithm can increase the classification accuracy by 10% on test data and 7% on validation data by selecting 67 regions.

    Conclusion

    The obtained results prove that the proposed method is a well-designed system and can differentiate between autistic and healthy people effectively.

    Keywords: Autism spectrum disorder, Functional magnetic resonance imaging, Classification
  • Zeinab Ghanbaryan*, Fatemeh Nemati, Nasim Ghanbari Pages 84-96
    Background

    Words in the Mental Lexicon (ML) construct semantic field through associative and/ or semantic connections, with a pervasive native speaker preference for the former. Non-native preferences, however, demand further inquiry. Previous studies have revealed inconsistent Lexical Access (LA) patterns due to the limitations in the methodology and response categorization.

    Objectives

    To fill the gap, we employed a primed Picture Naming (PN) task for investigating the relations between concepts in the ML of Iranian EFL (English as a foreign language) learners. We also explored whether conscious priming at a long prime-target stimulus onset asynchrony affected the naming latency of the learners with different proficiency levels.

    Materials & Methods

    The participants were 31 EFL learners (11-16 years old) at A1 and A2 levels based on the Common European Framework of Reference for languages. They were recruited in summer 2020 from language institutes in Bushehr and Kazeroon cities, Iran, through a convenience sampling method. They performed a PN task, including 66 prime-target pairs presented in associative, semantic, both semantic and associative, or unrelated conditions. The mixed-effects modeling was used for data analysis.

    Results

    Based on the likelihood ratio test of model comparisons for condition effect (χ2 (1) =9.07, P=0.002), the interaction of condition, frequency, and length was significant in the semantic condition (t=2.72, P=0.008). A slight effect was also observed from the prime frequency in the associative condition (t=1.82, P=0.07).

    Conclusion

    Results indicate one-level access to the ML, which is indeed a function of language proficiency. Findings are further discussed in terms of ML structure and patterns of LA.

    Keywords: Reaction time, Mental processes, Association, Semantics, Vocabulary
  • Jafar Nasiri*, Maryam Sedghi, MohammadHossein Hemat Pages 97-101
    Background

    Agenesis of Corpus Callosum (ACC) is a type of brain dysgenesis with various clinical manifestations.

    Objectives

    This study aimed to investigate the clinical and neurodevelopmental outcomes of patients with ACC.

    Materials & Methods

    In this cross-sectional study, the clinical and neurodevelopmental conditions of 62 patients with complete ACC referred to subspecialty clinics of pediatric neurology, Isfahan University of Medical Sciences, Isfahan, Iran, were investigated. Quantitative data were shown as Mean±SD, and qualitative data as frequency or percentage. In addition, the f Chi-square test was used to compare some data in SPSS version 22.

    Results

    In this study, 62 patients, including 29 boys and 33 girls with a Mean±SD age of 4.99±5.07 years, were included. Among the patients examined, 54.4% were born of consanguineous marriage, 82% had developmental delays, 80.4% had mental retardation, 89.1% had a speech delay, 23.7% had nutritional problems, 42.4% had facial dysmorphic features, and 27.6% had abnormalities of muscle tone. Among the associated problems stated by the patients, 15.5% of them had heart diseases, 22.4% visual disorders, 5.2% hearing deficit, 25.8% behavioral problems, 50% seizures, and 53.3% had abnormal electroencephalogram. Interestingly, 12.9% of the patients had normal or near-normal development.

    Conclusion

    The prevalence of developmental delays, speech and language disorders, mental retardation, facial deformities, seizures, and abnormal muscle tone were common in the patients with ACC.

    Keywords: Agenesis of corpus callosum, Epilepsy, Brain
  • Seyyed Hadi Rafiee*, Somayyeh Taklavi, Abbas Abolghasemi, Hamidreza Hatamian Pages 104-117
    Background

    Multiple Sclerosis (MS) is one of the most common neurological diseases that severely affects the patients‘ quality of sleep.

    Objectives

    This study aimed to compare the effectiveness of reality therapy and positive psychotherapy on sleep quality in women with MS.

    Materials & Methods

    The research method was quasi-experimental with a pre-test, post-test design and a control group. The study population included all women with MS referred to the Guilan MS Association in the summer and fall of 2019 who were selected by purposive sampling method. They were randomly assigned in three groups of 15 people for reality therapy training, positive psychotherapy, and control group. Both experimental groups received eight 90-minute sessions of psychotherapy interventions, but the control group received no training. The Pittsburgh Sleep Quality Index (PSQI) was used to collect data. Data analysis was performed by Multivariate Analysis of Covariance (MANCOVA) and Bonferroni post hoc test in SPSS version 22.

    Results

    Both reality therapy and positive psychotherapy significantly improved sleep quality in women with MS (P<0.01). Also, based on the results, the sleep quality of the reality therapy group showed a greater and more significant improvement compared to the positive treatment (F=19.43, P<0.01).

    Conclusion

    According to the obtained results, both methods have good practical capabilities for clinical interventions to improve sleep quality in patients with MS. Reality therapy is more effective than positive psychotherapy on the quality of sleep in women with MS.

    Keywords: Reality therapy, Psychotherapy, Sleep hygiene, Multiple sclerosis
  • Mohammad Haghani Dogahe*, Alireza Feizkhah, Sara Seddighi, Pejman Kiani, Fatemeh Shafaei Pages 116-129
    Background

    Traumatic brain injury is believed to be a public health disorder with some complications. Post Traumatic Neurocognitive Disorders (PTND) received much attention among these complications because of the high prevalence of mild traumatic brain injuries. On the other hand, advanced neuroimaging is increasingly becoming an exciting modality in the field of traumatic brain injury. Magnetic resonance spectroscopy (MRS) provides a new window to understand the detailed biochemistry alterations following traumatic brain injury. Therefore, some researchers have addressed the relations between MRS data and PTND.

    Objectives

    The research aimed to achieve the biochemistry alterations following TBI and find the relations between these alterations and PTND based on published literature in this field.

    Materials & Methods

    With this mind, a systematic search in MEDLINE and EMBASE databases performed to identify relevant published articles without date limitation. The systematic search keyword-targeted all MRS data relevant to the post traumatic neurocognitive disorders.

    Results

    Of the search results, a total of 22 journal articles were reported relations between MRS data and neurocognitive disorders. A variety of questionnaires and computerized tests has been used to detect neurocognitive outcomes. Most studies focused on N-acetyl aspartate (NAA), Choline (Cho), Creatine (Cr), Myo-inositol (MI), and their ratios. As MRI scanners are becoming stranger detecting extra-metabolites such as glutamate, glutamine and glutathione are more reliable. In this regard a few studies reported significant relations between alterations in these metabolites and PTND.

    Conclusion

    MRS is a powerful tool that can provide important data to detect long-term neurocognitive disorders following TBI.

    Keywords: Magnetic resonance spectroscopy, Brain injuries, Brain concussion, Neurocognitive disorders