24^th International Conference on Neurology & Neurophysiology March 16-17, 2020 Berlin, Germany

Biography:

Arina Serbina is pursuing her graduation from Immanuel Kant Baltic Federal University, specialty bioengineering and bioinformatics; Alexander Bogdanov is a researcher at School of Life Sciences, Immanuel Kant Baltic Federal University (Russia, Kaliningrad). Dr. Yuriy Pankratov - PhD, Associate professor at School of Life Sciences at the University of Warwick, UK.

Abstract:

It has been suggested that the neurons of prefrontal cortex, along with the hippocampus and amygdala, can undergo morphological and molecular remodeling during the development of stress-related disorders, such as PTSD. Pathological remodeling of the GABAergic inhibitory signalling during stress disorders might bring significant contribution to impairment of synaptic plasticity and cognition. In this work we have used an experimental model of PTSD in mice, based on a single prolonged stress protocol and studied alterations in the synaptic transmission and long-term synaptic plasticity in the pyramidal neurons of prefrontal cortex. The stress state in the animals was evaluated with the aid of open field and elevated cross-maze behavioral tests. We have found an increase in the quantal amplitude of GABAergic spontaneous inhibitory synaptic currents (mIPSCs) in the neurons of prefrontal cortex of stressed animals. There was also elevation in the frequency of mIPSCs in neurons of the stress-group vs control group. These results demonstrate that that exposure to stress can cause an up-regulation of the GABAergic inhibitory system in the prefrontal cortex. In the experiments on long-term potentiation (LTP) of field postsynaptic potentials (fEPSP), we have observed that the amplitude of LTP induced by the theta-burst stimulation in the prefrontal cortex synapses of stressed mice was much lower than in the control group. The data obtained suggest that stress-induced up-regulation of inhibitory signalling can affect long-term synaptic plasticity in the prefrontal cortex and thereby contribute to cognitive impairment.

Biography:

Felix-Martin Werner studied human medicine at the university of Bonn. He has been working as a medical teacher in the formation of geriatric nurses, occupational therapists and assistents of the medical doctor at the Euro Academy in Pößneck since 1999. He has been doing scientific work at the Institute of Neurosciences of Castilla and León (INCYL) in Salamanca (Spain) since 2002. With Rafael Coveñas, he assisted at over 30 national and 12 international congresses of neurology and published over 40 reviews about neural networks in neurological and psychiatric diseases. Since 2014,  he has been the member of  the editorial board of the Journal of Cytology  and  Histology.

Abstract:

Many schizophrenic patients who are treated with antipsychotic drug, do not adhere to the pharmacotherpy. Antipsychotic drugs constitute a palliative treatment, and their long-term administration is not secure. Instead of following the pharmacotherapy, some patients tend to consume alcohol and tobacco, and even amphetamines and cannabis. The reason of the patients to not adhere to the pharmacotherapy will be discussed, and the effect of alcohol, tobacco and drugs on the disease outcome will be addressed. Appropriate measures to make the patients to renounce of substances and drugs and to improve the patients’ adherence to the pharmcotherapy will be described. Alterations of classical neurotransmitters in the hippocampus, mesolimbic system and prefrontal cortex will be mentioned. The different compounds of cannabis, tetrahydrocannabidiol (a psychotomimetic) and cannabidiol (exerts antipsychotic actions). The effect of alcohol, tobacco and drugs to worsen the antipsychotic treatment will be pointed out. Appropriate measures to improve the antipsychotic pharmacotherapy and to reduce the consumption of substances and drugs are the administration of long-acting injectable antipsychotic drugs and psychoeducation and cognitive behavioral therapy Some new drugs, for example the cannabis compound cannabidiol that shows antipsychotic properties and ß-varenicline, a nicotinergic cholinergic agonist, might be administered when substance abuse (cannabis, nicotine) occurs.

Biography:

Dharitri Parmar is working as Professor in Physiology since 2007 and as teacher in medical college since 1992. She has contributed more than 23 years of career as medical faculty after post graduation in Government Medical College, Surat, India which is affiliated to Veer Narmad South Gujarat University (VNSGU). She is multifaceted personality who is interested in academic and administrative activities. She has acted as additional Dean for 2 years. She has guided more than 7 students for post graduation studies during her career. Under her guidance number of papers are published so as she has reviewed many manuscripts for different journals. She loves to travel with work. She has visited more than 50 medical institutes for the purpose of assessment of medical school for its standardization, to conduct examination, to conduct interview for recruitment, as guest lecturer etc. within India and overseas.

Abstract:

Sleep and wakefulness are important physiological manifestations of brain, even for clinicians. Review on Physiology of Sleep includes wakefulness as they are interchangeable, interdependent states. On discussion with introduction to sleep which includes sleep cycle; types of sleep; sleep waves neurotransmitters, pathways, circuits and receptors are summarised. Role of higher centres, parts of brain and other factors (steroid, biological rhythm, aging etc) are reviewed. Its implication in various sleep disorders and recent advances in neurophysiology related to sleep are described.

Biography:

Abstract:

Objective: To determine the efficacy of short-interval program of constraint-induced movement therapy on hand function training in asymmetric hand impairment cerebral palsy.

Study design: Randomized single-blinded controlled trial study.

Subjects: Asymmetric hand impairment cerebral palsy in Srisangwal School, Foundation for the Welfare of the Crippled System.

Methods: Sixteen cerebral palsy spastic triplegia (8-14 years old) were assigned randomly to either CIMT or control group. Both groups participated in occupational therapy program for 1 hour per day, 5 days per week for 8 weeks. CIMT group wore slings on their less impaired arms during therapy session and the slings were removed at the end of each session. To assess the effect of hand function of participants by the Jebsen-Taylor Test of Hand Function, counting the number of the coins that patient was able to put in the box within 3 minutes and stereognosis before training and after training for 8 weeks.

Results: Sixteen cerebral palsy spastic triplegia were divided equally into two groups. One participant in the control group was dropped out from the study because he had surgical intervention in his impaired arm. There was statistically significant (P< 0.05) improvement of hand function by Jebsen-Taylor Test of Hand Function and counting the amounts of the coins in the box within 3 minutes after training for 8 weeks in CIMT group but there was no significance in control group.

Conclusion: CIMT is efficacious to improve fine motor function in asymmetric hand impairment cerebral palsy.

Biography:

Maryam Noorbakhshnia works for University of Isfahan, Department of Biology - Faculty of Sciences.

Abstract:

Background and Aim: Alzheimer's disease is a neurodegenerative disorder that is associated with progressive degeneration of hippocampal and cortical neurons that leads to memory loss. Overexpression and production of amyloid-beta (Aβ) is the most significant factor in the pathogenesis of Alzheimer's disease. Recent studies have found a role for the gut microbiota in the gut-brain axis, which can affect cognitive and memory abilities. The purpose of this study was to investigate the effect of lactobacilli on the spatial memory and expression of APP gene in the hippocampus of Aluminum chloride (AlCl3) induced animal model of Alzheimer's disease.

Methods: Adult male wistar rats weighing (240–250 g) were used. Animals received either saline, Alcl3 (100 mg/kg), lactobacilli, or lactobacilli plus ALCL3 by oral gavage for 42 days. Lactobacilli contained L.plantarum, L.rhamnosus, and L.reuteri. Morris water maze test was used for evaluating spatial memory. After completion of the behavioral test, animals were sacrificed and hippocampi dissected, and stored at -80°C. Finally, the level of APP gene expression was evaluated by Real-Time PCR.

Results: Our results indicated that ALCL3 significantly impaired spatial memory and intensified hippocampal APP gene expression. Pre-treatment with lactobacilli improved memory in control rats and prevented memory and APP deterioration in ALCL3 treated rats.

Discussion: lactobacilli used in this study can prevent destructive effect of AlCl3 on memory and can introduce as a way to prevent Alzheimer's disease, possibly via decreasing APP gene expression. However, more investigations are necessary to know related cellular and molecular mechanisms.

Biography:

Reshu Gupta works as Assistant Professor in R.U.H.S. College of Medical Sciences-India.

Abstract:

Biography:

Ni Hong has completed his PhD and works in the Children’s Hospital of Soochow University (China) as Pediatric Neurologist with main interest in Pediatric neurological rehabilitation, cerebral palsy and epilepsy since 1995. He is a professor and director of the Department of Brain Sciences at the Institute of Pediatrics, Suzhou University. He is now a member of the Chinese Society of Microcirculation Council and a member of the Brain Science Committee of the Chinese Medical Association Pediatrics Branch.

Abstract:

Many endocrine regulators are widely expressed and secreted in the brain, and play important neuromodulatory roles in physiological and pathological processes such as brain development, brain function protection, and brain injury repair. In addition, many endocrine regulators undergo significant changes in the serum and cerebrospinal fluid of neurological diseases and can be used as biological markers for early diagnosis, prognosis and treatment of diseases. In recent years, significant progress has been made in understanding the effects of endocrine modulators on pediatric neurological diseases, especially epilepsy, dravet syndrome, autism spectrum disorder, cerebral palsy and ADHD. These advances stem from a series of research advances on specific endocrine regulators such as melatonin, leptin and ghrelin, as well as ketogenic diet (KD) . KD is a nutritional therapy that has been found to be beneficial against refractory epilepsy, and has also been proposed to treat many other neurological disorders. Recently, we opened a column in the magazine “Frontiers in Endocrinology” in collaboration with scholars from Italy and India: "Endocrine Modulators of Neurological Processes: Potential Treatment Targets of Pediatric Neurological Diseases". Here, we summarize the new progress of the articles published in the column, hoping to provide useful clues for future research.

Biography:

Junping Zhao has completed his PhD and MD from Medical School of Chinese PLA and Chinese PLA General Hospital. He is the honorary director of Institute of Medical Informatics, Chinese PLA General Hospital; Beijing P.R.China. He has published more than 50 papers in reputed journals and is an expert of medical informatics and ophthalmologist.

Abstract:

Vessel segmentation is a challenging problem in medical image segmentation, as it requires knowing the location of each tiny blood vessel and understanding the global semantic information. Previous method has demonstrated that long-range dependencies information plays an important role in understanding global segmentation information. To capture long-range dependencies information, researchers often use non-local structure. However, it requires too much computing power and a large amount of GPU memory. In this paper, we present a deformed non-local (DNL) neural network structure for retinal vessel segmentation. DNL inherits the structure of the Non-local module, but it changes the operation rules of non-local weight matrix multiplication, which can greatly reduce the problem of excessive computation and memory usage. Meanwhile, we introduce the atrous spatial pyramid pooling module to increase the receptive field of the networks, which showed that it is effective to resample features at different scales for accurately and efficiently classifying regions of an arbitrary scale. The proposed method was evaluated on retinal vessel datasets and experimental results show that it outperforms state-of-the-art methods. For a 128 × 128 input, DNL is around 2.5 times faster than a non-local block on GPU.

Biography:

Junping Zhao has completed his PhD and MD from Medical School of Chinese PLA and Chinese PLA General Hospital. He is the honorary director of Institute of Medical Informatics, Chinese PLA General Hospital; Beijing P.R.China. He has published more than 50 papers in reputed journals and is an expert of medical informatics and ophthalmologist.

Abstract:

Vessel segmentation is a challenging problem in medical image segmentation, as it requires knowing the location of each tiny blood vessel and understanding the global semantic information. Previous method has demonstrated that long-range dependencies information plays an important role in understanding global segmentation information. To capture long-range dependencies information, researchers often use non-local structure. However, it requires too much computing power and a large amount of GPU memory. In this paper, we present a deformed non-local (DNL) neural network structure for retinal vessel segmentation. DNL inherits the structure of the Non-local module, but it changes the operation rules of non-local weight matrix multiplication, which can greatly reduce the problem of excessive computation and memory usage. Meanwhile, we introduce the atrous spatial pyramid pooling module to increase the receptive field of the networks, which showed that it is effective to resample features at different scales for accurately and efficiently classifying regions of an arbitrary scale. The proposed method was evaluated on retinal vessel datasets and experimental results show that it outperforms state-of-the-art methods. For a 128 × 128 input, DNL is around 2.5 times faster than a non-local block on GPU.