5^th International Conference on Neurology and Psychology November 14-15, 2022 Amsterdam, Netherlands

Biography:

Currently, I am a final year medical student studying at Poznan School of Medical Sciences (PUMS) in Poland. Previously, I also completed an undergraduate degree in physiological sciences at Newcastle university in the UK. I have a particular interest in neuroscience and oncology. And therefore, I involved myself in a research project on brain tumors which started two years. During this time, I worked under Dr. Anna-Maria Barciszewska, a consultant neurosurgeon in Poznan.

Abstract:

Meningiomas are the most frequent primary tumors arising in the central nervous system. They typically follow a benign course, with an excellent prognosis for grade I lesions through surgical intervention. Although radiotherapy is a good option for recurrent, progressive, or inoperable tumors, alternative treatments are very limited. mTOR is a protein complex with increasing therapeutical potential as a target in cancer. The current understanding of the mTOR pathway heavily involves it in the development of meningioma. Its activation is strongly dependent on PI3K/Akt signaling and the merlin protein. Both factors are commonly defective in meningioma cells, which indicates their likely function in tumor growth. Furthermore, regarding molecular tumorigenesis, the kinase activity of the mTORC1 complex inhibits many components of the autophagosome, such as the ULK1 or Beclin complexes. mTOR contributes to redox homeostasis, a vital component of neoplasia. Recent clinical trials have investigated novel chemotherapeutic agents for mTOR inhibition, showing promising results in resistant or recurrent meningiomas.

Biography:

Raibagkar specializes in general neurology with additional training in neuromuscular medicine and neuroimmunology; Her clinical interests include neuroimmunology, multiple sclerosis, neuro-infectious disease, neuromuscular disorders as well as general neurology. A graduate of the Smt NHL Municipal College in Gujarat, India, Dr Raibagkar completed her internship at Temple University Hospital in Philadelphia, PA and residency at Massachusetts General Hospital, Brigham & Women’s Hospital and Harvard University in Boston, MA. Dr Raibagkar completed fellowships at Massachusetts General Hospital in advanced general and autoimmune neurology and at Brigham & Women’s and Massachusetts General Hospital in neuromuscular medicine. Dr Raibagkar is board certified in neurology and neuromuscular medicine.

Abstract:

Immune-medicated neurologic disorders include a large spectrum of heterogeneous disorders. Delayed identification and inappropriate management can lead to rapid deterioration with unfavorable consequences. Intensive level care is often indicated with reduced level of consciousness, autonomic dysfunction, seizures, and treatment refractory movement disorders.

Autoimmune and paraneoplastic encephalitis entail range of disorder in which the body’s immune system pathologically attacks the brain. Intensive care monitoring and treatment is commonly necessary for anti N-methyl D aspartate receptor encephalitis. Demyelinating disorders such as tumafactive multiple sclerosis, Marburg variant, Balo concentric sclerosis, and acute disseminated encephalomyelitis may manifest with tumor like presentations and have a high risk of morbidity and mortality. Respiratory compromise and respiratory failure are most common cause of death in the setting of recurrent myelitis in patients with neuromyelitis optica spectrum disorder.

Systemic rheumatologic disorder like neurosarcoidosis, sjogren’s syndrome and systemic lupus erythematosus may have acute neurological decline and therefore understanding neurological involvement is of paramount importance.

Biography:

Hazem Wahba is the neuroscience therapy area medical head, leading the medical team in the development of the scientific part and the implementation of scientific activities in the respective therapeutic area. He initiated innovative RWE, projects and partnerships with the healthcare system to position Novartis as the preferred scientific partner. He has more than 11 years of experience in diverse roles across different multinational pharmaceutical companies. He is the champion in Real-World Evidence for Saudi to support the other franchises Launch Powerhouse to build RWE plans for their key launches. Hazem holds a bachelor’s degree in Pharmaceutical Science from Suez Canal University, Egypt, 2010 and a PharmD Degree from Suez Canal University, Egypt, 2021.

Abstract:

Treatment-pattern data suggest that some patients with multiple sclerosis (MS) in the Kingdom of Saudi Arabia (KSA) may not be receiving optimal treatment. A virtual meeting of ten expert Saudi neurologists, held on October 23, 2020, discussed unmet needs in relapsing–remitting MS (RRMS), and the role of ofatumumab as a suitable treatment in the KSA. Multiple unmet needs were identified: poor quality of life, with high rates of depression and anxiety; a negative impact of MS on work ability; treatment choices that may compromise efficacy for safety or vice versa; inconvenient or complex dosage regimens; and limited access to patient education and support.

Early use of highly effective disease-modifying treatments (DMTs) results in better patient outcomes than starting with less effective treatments and downstream escalation, but this strategy may be underutilized in the KSA. B cells are important in MS pathogenesis, and treatments targeting these may improve clinical outcomes. Ofatumumab differs from other B cell–depleting therapies, being a fully human monoclonal antibody that binds to CD20 at a completely separate site from the epitope bound by ocrelizumab, and being administered by subcutaneous injection. When compared with teriflunomide in two randomized, phase 3 clinical trials in patients with RRMS, ofatumumab was associated with significant reductions in annualized relapse rates, rates of confirmed disability worsening, and active lesions on magnetic resonance imaging. The incidence of adverse events, including serious infections, was similar with the two treatments.

Ofatumumab is a valuable first- or second-line treatment option for RRMS in the KSA, particularly for patients who would benefit from highly effective DMTs early in the disease course, and for those who prefer the convenience of self-injection. Future research will clarify the position of ofatumumab in RRMS treatment, and comparative cost data may support the broad inclusion of ofatumumab in formularies across the KSA.

Biography:

I was born in Kerman, Iran. She passed her high school in one of the “National Organization for Development of Exceptional Talents” schools. She got a master degree in computer engineering and a PhD in cognitive neuroscience. Now she works as an assistant professor in Shahid Bahonar University of Kerman and researches in the field of cognitive neuroscience. She uses ERPs (Event- related Potentials) technique for studying the brain and applies machine learning models to further analysis the brain signals. She is very interested in better cognition of the brain especially studying brain disease through mathematical and engineering tools.

Abstract:

Background

Time perception is essential for the precise performance of many of our activities and the coordination between different modalities. But it is distorted in many diseases and disorders. Event-related potentials (ERP) have long been used to understand better how the human brain perceives time, but machine learning methods have rarely been used to detect a person's time perception from his/her ERPs.

New Method

In this study, EEG signals of the individuals were recorded while performing an auditory oddball time discrimination task. After features were extracted from ERPs, data balancing, and feature selection, machine learning models were used to distinguish between the oddball durations of 400ms and 600ms from standard durations of 500ms.

Results

ERP results showed that the P3 evoked by the 600ms oddball stimuli appeared about 200ms later than that of the 400ms oddball tones. Classification performance results indicated that support vector machine (SVM) outperformed K-nearest neighbors (KNN), Random Forest, and Logistic regression models. The accuracy of SVM was 91.24, 92.96, and 89.9 for the three used labeling modes, respectively. Another important finding was that most features selected for classification were in the P3 component range, supporting the observed significant effect of duration on the P3. Although all N1, P2, N2, and P3 components contributed to detecting the desired durations.

Comparison with Existing Method(s)

This study is the first to report common classification evaluation metrics for time perception detection.

Conclusion

Therefore, results of this study suggest the P3 component as a potential candidate to detect sub-second periods in future researches on brain-computer interface (BCI) applications.

Biography:

He has received Bachelor in. Engg. (Industrial Electronics) degree in 1990 and Masters in Engg. (Electronics Engg.) degree in 2001-02, from S.G.B. Amravati University, Amravati, Maharashtra, India. Presently, he is working as Professor & Head with Electronics and Telecommunication Engineering Department in Shri Sant Gajanan Maharaj College of Engineering, SHEGAON, Maharashtra, 444203, India . He has been awarded the Ph.D. degree in Biomedical Neuro-signal/Image analysis and processing, from School of Medical Science and Technology, Indian Institute of Technology, Kharagpur, West Bengal, India in 2016-17. He is a member of IEEE and life member of ISTE and IETE. He was co-opted as an executive member of IETE Centre Amravati, Maharashtra, India for consistent three year. His research interests encompass Neuro-signal processing, analysis, classifications and prediction. Bio-signal/image analysis and processing, disease prediction, and computational intelligence methods with emphasis on adaptive digital signal processing with an embedded system design.

Abstract:

Meditation has a metaphysical impact on human brain functioning. It is of utmost required to infer the cognitive effects of meditation using an electroencephalogram (EEG). In this novel work, the analyses of EEG signals’ features are extracted for cognitive effects on a human brain for meditation intervention of 25 subjects. To analyze the meditation effects, this study examines the feasibility of statistical, spatial, spectral, coherence features, and time-frequency analysis of EEG signals for control and meditator group. Based on the effective features the various classifiers are used to compare the accuracy and distinguish a subject as control or meditator.

The results demonstrate that the Support Vector Machine (SVM) gives better accuracy than Artificial Neural Network (ANN) and k-Nearest Neighbors (KNN). The statistical analysis shows that the Variance and Sample Entropy decreased in meditators whereas, in spatial analysis, the Mahalanobis distance increased. The spectral analysis stated that theta power has increased 88% of subjects whereas the alpha power is increased for the entire subjects after meditation. The coherence observed in the pre-frontal lobes’ electrode pair is more in the meditators than in the control groups. Eventually, meditation improves relaxation, cognitive functions, calmness, and mental concentration.

Biography:

Abstract:

The human race is one of the youngest species on earth and considers itself very intelligent compared to other species. Indeed, humanity has advanced in all spheres and enjoys a lifestyle of comfort and luxury compared with earlier generations. Nevertheless, this same intelligent humanity is causing various problems for itself and other species as well as non-living things. Today, professionals, students, and people in general are familiar with the theories on intelligence developed in the West. However, despite the importance and comprehensiveness of these theories, we seem to lack an understanding of the wisdom provided by ancient scriptures like the Bhagavad Gita regarding what intelligence is. This paper deals with interpreting and comprehending intelligence based on the Bhagavad Gita. It also addresses why emotional intelligence is essential, dives deeper into the understanding of the five parameters of emotional intelligence identified by Daniel Goleman, and helps comprehend them from the perspective of the Bhagavad Gita. According to the Bhagavad Gita, awareness and understanding of the comprehensive meaning of intelligence and emotional intelligence can inspire academicians, professionals, and students to strengthen and enhance their emotional intelligence rather than focus only on their intelligence quotient (IQ). Such an approach would provide a sustainable solution to various issues and help humans have sustainable and purposeful lives.

Biography:

Dr. Kanika K. Ahuja is Professor, Department of Psychology, Lady Shri Ram College for Women, University of Delhi. She has about 25 years of teaching, research and professional experience. Her current areas of interest are social psychology, gender issues and organizational behavior. She is the editor of The Learning Curve, a peer-reviewed journal published by Lady Shri Ram College, since 2018. She has published about forty articles in leading journals, authored books and text books, and presented several papers and key note addresses in national and international conferences. She conducts workshops for parents, teachers and students in schools, as also soft skill training, recruitment and psychometric projects for corporates and GoI. She has done research projects on conflict resolution and peace building in Kashmir, creating sustainable global partnerships in higher education, gender gap in mathematics, body image, and enhancing self-esteem among young school girls. She also delivered a TED-X talk titled “Mirror Mirror on the wall….I’m sexy, Damn you all”

Abstract:

Statement of the Problem: Cyber sexual harassment (CSH) has surfaced as an offshoot of work from home and the hybrid mode of working ushered by the pandemic. Previous research has highlighted the impact of such harassment especially on women employees, such as economic vandalism, lowered organizational commitment, work stress, absenteeism, intention to quit, and even mental health issues. Methodology: The present study aimed to assess the relationship between CSH of women and job satisfaction using the survey method. The sample comprised of 123 women employed in varied private sector organizations in India. The inclusion criteria were women under the age of 40 years working from home at least once a week over the last 6 months. Tools included adapted version of Ritter’s scale of cyber-sexual harassment (2013) and Generic Job Satisfaction Scale (MacDonald & MacIntyre, 1997). Results showed 5.6% participants reported being sexually harassed online. Further, a significant, albeit small correlation between cyber sexual harassment and job satisfaction (r=-0.237) was found. In addition, simple linear regression analysis showed that only 4.8% of the variance in job satisfaction was explained by CSH. The low prevalence of CSH may be due to ambiguity over what counts as sexual harassment in the online medium, hesitancy in reporting, lack of policies to address this form of harassment and general normalization of CSH. Conclusion & Significance: While the results indicate a low prevalence of CSH, this does not mean that women in the workforce are not experiencing CSH. In fact, 5.67% of the sample reported being victims of this phenomenon, while 9.76% were unsure of whether they had experienced it or not. This indicates the need to formulate clear guidelines, legal boundaries, and visible enforcement vehicles. It must be the primary responsibility of every organisation to ensure a safe and secure working space for its employees, be it offline or online.