Impacts of hybrid synapses on the noise-delayed decay in scale-free neural networks |
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| Affiliation: | 1. Department of Physiology, College of Basic Medical Sciences, Third Military Medical University, Chongqing 400038, PR China;2. Battalion 8 of Cadet Brigade, Third Military Medical University, Chongqing 400038, PR China;3. Battalion 11 of Cadet Brigade, Third Military Medical University, Chongqing 400038, PR China;4. Department of Orthopedics, Daping Hospital, Third Military Medical University, Chongqing 400042, PR China;1. Division of Paediatric Endocrinology, University Children''s Hospital Heidelberg, Heidelberg, Germany;2. Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Germany;3. Institute of Molecular Biomedicine, Faculty of Medicine, Comenius University, Bratislava, Slovakia;4. Max-Planck Research Group at the Institute for Anatomy and Cell Biology, University of Heidelberg, Germany;5. Department of Psychiatry (UPK), University of Basel, Switzerland;1. Department of Neurology, Boston Children''s Hospital, Harvard Medical School, Boston, MA, USA;2. Department of Neurology, New York University Comprehensive Epilepsy Center, New York University Langone Medical Center, New York University School of Medicine, New York, NY, USA;3. Department of Child Neurology, Hospital Sant Joan de Déu, Universidad de Barcelona, Barcelona, Spain;4. Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA;5. Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA |
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| Abstract: | We study the phenomenon of noise-delayed decay in a scale-free neural network consisting of excitable FitzHugh–Nagumo neurons. In contrast to earlier works, where only electrical synapses are considered among neurons, we primarily examine the effects of hybrid synapses on the noise-delayed decay in this study. We show that the electrical synaptic coupling is more impressive than the chemical coupling in determining the appearance time of the first-spike and more efficient on the mitigation of the delay time in the detection of a suprathreshold input signal. We obtain that hybrid networks including inhibitory chemical synapses have higher signal detection capabilities than those of including excitatory ones. We also find that average degree exhibits two different effects, which are strengthening and weakening the noise-delayed decay effect depending on the noise intensity. |
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