فهرست مطالب

  • Volume:6 Issue: 1, Dec 2021
  • تاریخ انتشار: 1401/03/04
  • تعداد عناوین: 9
  • Mohammad Nami *, Kosagi-Sharaf Rao, Seithikurippu R Pandi-Perumal, Babak Kateb Pages 1-4

    Modern neuroscience is on the verge of exploring new frontiers within varioussubdisciplines.The question of how our brain with over hundred billion neurons puts together cognition,emotion and behavior has always been captivating. As such, the study of neural processesthrough which we not only maintain our survival and homeostasis, but also stayproductive and functional, has attracted cognitive neuroscientists for decades. With theadvent of neurotechnologies and ever-growing research facilities, modern neurosciencehas seen a tremendous progress in dealing with such questions. This letter argues the mostreferenced theories with respect to key concepts in affective neuroscience, i.e. fear, loveand related emotions or traits. We hope the present letter is found thought-provoking withregards to further theoretical models and empirical research in affective neuroscience andneuropsychology.

  • Mani Butwall, Kinshuk Gaurav Singh, Raj Pujara, Pranav Modi, Harshvardhan Sharma, Arsh Vishwakarma, Iman Salehi, Mohammad Javad Gholamzadeh, Ali-Mohammad Kamali, Milad Kazemiha, Prasun Chakrabarti, Mohammad Nami * Pages 5-13
    Sleep disorders are very common in today’s world as we all are living a relatively competitive life; where we undervalue our mental health. There are some sleep disorders that share almost similar symptoms yet various pathological underpinnings leading to clinical misjudgments; thereby resulting in the inappropriate treatments. The present study has attempted to investigate possible correlation between various types of sleep predicaments. To do so; we used multiple statistical analysis algorithms as well as prediction models on our database and performed manual testing to draw our conclusion. Our analyses revealed that sleep disorders; and namely sleep apnea-hypopnea syndrome; tend to present with related comorbidities
  • Fatemeh Haghighi, Marzieh Nezamzadeh *, Neda Mohammadi-Mobarakeh Pages 14-23
    Recently, it has been proven that assuming the Gaussian model in DTImethod is inappropriate for propagation in a complex substrate such as human braintissue. High Angular Resolution Diffusion Imaging (HARDI) (or so called q-ball imaging)is known as a model free method that allows to more accurately detect changes in diffusionwith different orientations. In this study, after finding the best angle threshold at the OpticRadiation (OR) level, the length and number of reconstructed nerve fibers in this anglewere measured using q-ball imaging and were compared with DTI.
    Materials and Method
    Tractographs of q-ball images from the human brains of 10healthy volunteers (30 to 50 years old) were studied using a 3-Tesla scanner. 64 directionsof diffusion encoding in two b-values (1000 and 2000 s/mm2), were used for q-ballimaging and in routine b-value of 1000 s/mm2 for DTI. The tractographs were comparedat the OR level with the tractography based on q-ball and DTI images. The results wereanalyzed using t-test. The angle threshold for tractography was selected at 45 degrees bycomparing the tractographs in 13 angles.
    Consequently, the number and length of nerve fibers of OR, measured usingthe q-ball imaging, were significantly higher than those using the DTI. Finally, the betterquality of the tractographs as well as the analyzed quantities, are indicators of larger signalto-noise ratio in q-ball imaging and indicate that q-ball imaging compared to DTI plays animportant role in the development of brain nerve mapping.
    Keywords: MRI, Diffusion tensor imaging, Multi-shell Q-ball Imaging, Tractography
  • Shirin Modarresi *, Golale Modarresi, Maryam Farzad, Erfan Shafiee, Mahshad Maleki, Joy C. Macdermid, David M. Walton Pages 24-32
    Psychological factors have been consistent predictors of recovery followingmusculoskeletal injuries. The Traumatic Injuries Distress Scale (TIDS) is a risk-basedprognostic screening tool that has been developed for predicting recovery from acutemusculoskeletal trauma. The purpose of this study was to translate and cross-culturallyadapt the TIDS to Persian.
    The forward-backward translation technique was used to translate the TIDSfrom English to Persian. The final version was obtained by consensus with the translationcommittee. Cognitive interviews were used to evaluate lingual accuracy and cultural orcontextual appropriateness. 13 participants completed cognitive interviews based on thetalk-aloud and probing approach to explore individual items.
    Participants (age range 22-58) had no problems in questions two, six, eight, and11. Participants identified potential issues in 4/6 areas of a cognitive interview codingsystem: comprehension/clarity, inadequate response definition, perspective modification,reference point, and calibration across items. These issues informed changes made toarrive at the final version of the P-TIDS.
    The TIDS, which is a tool to assess psychological distress followingmusculoskeletal trauma was translated and culturally adapted to Persian. Throughcognitive interviewing, some issues were identified that were related to cross-culturalinterpretation and application of the items that were resolved through rewording andrecalibration of the tool. The TIDS-Pcan be a significant addition to the toolbox of Persianhealthcare providers for assessing the risk of developing chronic pain post-musculoskeletaltrauma. Psychometric studies are now underway to further evaluate the properties of thetranslated tool.
    Keywords: Traumatic Injuries Distress Scale, Musculoskeletal injuries, Prognosis, Cross cultural adaptation, cognitive interview
  • Yashvi Bhavsar, Khyati Mistry, Nishchay Parikh, Himani Shah, Adarsh Saraswat, Helia Givian, Mojataba Barzegar, Maryam Hosseini, Khojaste Rahimi Jaberi, Archana Magare, Mohammad Javad Gholamzadeh, Hadi Aligholi, Ali-Mohammad Kamali, Prasun Chakrabarti, Mohammad Nami * Pages 33-53
    This paper contains an analysis and comparison of different classifiers on different datasetsof Psychiatric Disorders- Personality Disorder, Depression, Anxiety, Schizophreniaand Alzheimer's disease. Psychiatric disorders are also referred to as mental disorders,abnormalities of the mind that result in persistent behavior which can seriously cause dayto day function and life. Stochastic in AI refers to if there is any uncertainty or randomnessinvolved in results and are used during optimization; Using this process also helps toprovide precise results. The study of stochastic process in AI uses mathematical knowledgeand techniques from probability, set theory, calculus, linear algebra and mathematicalanalysis like Fourier analysis, real analysis, and functional analysis. this technique is usedto construct neural network for making artificial intelligent mode for processing andminimizing human effort. This paper contains classifiers like SVM, MLP, LR, KNN, DT,and RF. Several types of attributes are used and have been trained by Weka tool, MATLAB,and Python. The results show that the SVM classifier showed the best performance for allthe attributes and disorders researched in this paper.
    Keywords: Alzheimer’s disease, Anxiety, Artificial Intelligence, depression, DT, KNN, Logistic regression, MLP, Personality Disorder, RF, Schizophrenia, SVM
  • Ytanvi Patel, Shreyansh Dalwadi, Nen Bakraniya, Apurva Desai, Nirmal Kachhiya, Het Parikh, Mohammad Javad Gholamzadeh, Ali- Mohammad Kamali, Milad Kazemiha, Prasun Chakrabarti, Mohammad Nami * Pages 54-63
    Schizophrenia (SZ) is a mental illness that impairs a person's mental capacity, emotionaldispositions, and personal and social quality of life. Manual SZ patient screening is timeconsuming,expensive, and prone to human mistakes. As a result, a autonomous, relativelyaccurate, and reasonably economical system for diagnosing schizophrenia patients isrequired. Machine learning methods are capable of learning subtle hidden patterns fromhigh dimensional imaging data and achieve significant correlations for the classificationof Schizophrenia. In this study, the diverse types of symptoms of the affected person areselected which have the weights assigned by cross-correlations and the model classifiesthe probability of schizophrenia in the person based on the highest weighted symptomspresent in the report of the patient using machine learning classifiers. The classificationis made by various classifiers in which the Support Vector Machine (SVM) gives thebest result. In the neuroscience domain, it has been one of the most popular machinelearningtools. SVM with Radial Basis Function kernel helps to distinguish betweenpatients and healthy controls with significant accuracy of 76% without normalization andPrincipal Component Analysis (PCA). The K nearest neighbor’s algorithm also with nonormalization and PCA showed an accuracy of 73% in predicting SZ which is remarkablyclose to the SVM given the small size dataset.
    Keywords: Schizophrenia (SZ) Classification, Healthy Controls (HC), Support Vector Machine (SVM), Magnetic Resonance images (MRI), Principal Component Analysis (PCA), Functional MRI (fMRI), Structural MRI (sMRI), Independent Component Analysis (ICA)
  • Sreemoy Kanti Das, G. S Chakraborthy, Tulika Chakrabarti, Prasun Chakrabarti, Mohammad Javad Gholamzadeh *, Mohammad Nami Pages 64-71
    Various plant species of genus Epipremnum have already been reportedto have different types of pharmacological activities. However, another plant of the samegenus Epipremnum aureum has not been scientifically exposed to a significant extent todate. Although it contains many bioactives, it has only been studied for antidepressantactivity. The present study aims to evaluate the nootropic potential of standardized extractof Epipremnum aureum against scopolamine-induced amnesia in experimental animals.
    The nootropic potential of Epipremnum aureum was evaluated using an elevatedplus maze and Morris water maze apparatus. A dose of 400mg/kg and 600mg/kg was usedto access the nootropic activity. Scopolamine (0.4 mg/kg) was used to induce amnesia inmice. Additionally, the anti-acetylcholinesterase activity of the extract was evaluated bymeasuring the level of acetylcholinesterase in the mice brain.
    Epipremnum aureum was found to increase memory and reverse the amnesicaction of scopolamine in a dose-dependent manner. In elevated plus maze and Morriswater maze, Epipremnum aureum decreased the transfer latency as compared to the controlgroup. Further biochemical investigation revealed an increased level of acetylcholine anddecreased level of TBARS resulting in reversing the effect of scopolamine in amnesic mice.
    Epipremnum aureum showed positive results in reversing the amnesiaaction of scopolamine which may be the probable mechanism for its memory retentionactivity. Based on the experimental outcome, the present study provides a piece of scientificevidence for the nootropic potential of Epipremnum aureum in experimental animals.
    Keywords: Acetyl-cholinesterase, Morris water maze, Elevated plus maze, thin-layer chromatography
  • Mehrdad Afarid, Hooman Rezaie, Behzad Khademi, Mohammad Javad Gholamzadeh *, Mohammad Nami Pages 72-80
    This study is aimed at profiling cognitive functions in patients with age-relatedmacular degeneration (AMD).
    This cross-sectional investigation enrolled 45 patients with AMD and 45 age- andsex-matched controls. The overall cognitive performance in AMD sufferers versus controlsubjects was assessed using the Persian version of Addenbrooke’s Cognitive Examinationbattery (ACE-R). Subjects’ sleep quality was also evaluated using the Pittsburgh SleepQuality Index (PSQI). The mean global assessment and subscale scores were statisticallycompared between groups.
    The mean global scores for ACE-R in AMD and control groups (80.4±12.3 and86 ± 9.6, respectively) were found to be statistically different (p=0.018). On the other hand,there was no significant difference (p=0.793) between the AMD and control groups interms of PSQI scores (9.7±2.8 and 9.8±2.8, respectively).
    AMD patients seem to have cognitively underperformed in memoryand verbal fluency domains compared to the control group. Evidence on cognitiveimpairments in patients with AMD may possibly herald neurocognitive insufficienciesand have common pathological mechanisms with dementias.
    Keywords: Age-Related Macular Degeneration, Cognitive Performance, Sleep quality, Dementia
  • Mohammad Javad Gholamzadeh, Reza Fereidooni * Pages 81-85
    Obstructive sleep apnea (OSA) is associated with arousals due to thecessation of breathing during sleep. On the other hand, sleep spindles, an EEG wave mainlyseen in stage 2 of non-REM sleep (N2), are responsible for many functions including themaintenance of sleep. We aimed to investigate the association between sleep spindles andOSA and compare the additional polysomnography (PSG) metrics in a group of patientswith OSA.
    Materials and Method
    Fifty consecutive patients with moderate and severe OSA wererecruited. Association of apnea-hypopnea index (AHI) with spindles in N2 and arousalswere evaluated. Other PSG metrics were compared in the moderate versus severe group.
    Body mass and snore indices were significantly more in the severe group (p=0.002and p<0.001, respectively). Arousals were more frequently seen in severe OSA cases(p=0.064). Sleep spindle index did not have any relationship with AHI and the numberof arousals. However, arousals were weakly correlated with AHI (Spearman’s rho= 0.293,p=0.039) and snore index (Spearman’s rho= 0.365, p=0.010).
    Severity of OSA did not show a clear correlation with spindle density in N2.Further studies with larger samples and a control group are needed to prove a relationshipbetween sleep spindles and OSA.
    Keywords: Sleep Spindle, Obstructive Sleep Apnea, Polysomnography