Egidio D’Angelo, MD, Ph.D.
Full Professor of Physiology & Director, Brain Connectivity Center, University of Pavia, Italy
Realistic modeling: new insight into the functions of the cerebellar network
Realistic modeling is an approach based on the careful reconstruction of neurons synapses starting from biological details at the molecular and cellular level. This technique, combined with the connection topologies derived from histological measurements, allows the reconstruction of precise neuronal networks. Finally, the advent of specific software platforms (PYTHON-NEURON) and of super-computers allows large-scale network simulation to be performed in reasonable time. This approach inverts the logics of older theoretical models, which anticipated an intuition on how the network might work. In realistic modeling, network properties “emerge” from the numerous biological properties embedded into the model.
This approach is illustrated here through an outstanding application of realistic modeling to the cerebellar cortex network. The neurons (over 105) are reproduced at a high level of detail generating non-linear network effects like population oscillations and resonance, phase-reset, bursting, rebounds, short-term and long-term plasticity, spatiotemporal redistrbution of input patterns. The model is currently being used in the context of he HUMAN BRAIN PROJECT to investigate the cerebellar network function.
Correspondence should be addressed to
Dr. EgidioD’Angelo,
Laboratory of Neurophysiology
Via Forlanini 6, 27100 Pavia, Italy
Phone: 0039 (0) 382 987606
Fax: 0039 (0) 382 987527
dangelo@unipv.it
Acknowledgments
This work was supported by grants from European Union to ED (CEREBNET FP7-ITN238686, REALNET FP7-ICT270434) and by grants from the Italian Ministry of Health to ED (RF-2009-1475845).
Karmeshu, Ph.D.
Dean & Professor, School of Computer & Systems Sciences & School of Computational & Integrative Sciences, Jawaharlal Nehru University, India.
Interspike Interval Distribution of Neuronal Model with distributed delay: Emergence of unimodal, bimodal and Power law
The study of interspike interval distribution of spiking neurons is a key issue in the field of computational neuroscience. A wide range of spiking patterns display unimodal, bimodal ISI patterns including power law behavior. A challenging problem is to understand the biophysical mechanism which can generate the empirically observed patterns. A neuronal model with distributed delay (NMDD) is proposed and is formulated as an integro-stochastic differential equation which corresponds to a non-markovian process. The widely studied IF and LIF models become special cases of this model. The NMDD brings out some interesting features when excitatory rates are close to inhibitory rates rendering the drift close to zero. It is interesting that NMDD model with gamma type memory kernel can also account for bimodal ISI pattern. The mean delay of the memory kernels plays a significant role in bringing out the transition from unimodal to bimodal ISI distribution. It is interesting to note that when a collection of neurons group together and fire together, the ISI distribution exhibits power law.
Seeram Ramakrishna, Ph.D.
Director, Center for Nanofibers & Nanotechnology, National University of Singapore
Biomaterials: Future Perspectives
From the perspective of thousands of years of history, the role of biomaterials in healthcare and wellbeing of humans is at best accidental. However, since 1970s with the introduction of national regulatory frameworks for medical devices, the biomaterials field evolved and reinforced with strong science and engineering understandings. The biomaterials field also flourished on the backdrop of growing need for better medical devices and medical treatments, and sustained investments in research and development. It is estimated that the world market size for medical devices is ~300 billion dollars and for biomaterials it is ~30 billion dollars. Healthcare is now one of the fastest growing sectors worldwide. Legions of scientists, engineers, and clinicians worldwide are attempting to design and develop newer medical treatments involving tissue engineering, regenerative medicine, nanotech enabled drug delivery, and stem cells. They are also engineering ex-vivo tissues and disease models to evaluate therapeutic drugs, biomolecules, and medical treatments. Engineered nanoparticles and nanofiber scaffolds have emerged as important class of biomaterials as many see them as necessary in creating suitable biomimetic micro-environment for engineering and regeneration of various tissues, expansion & differentiation of stem cells, site specific controlled delivery of biomolecules & drugs, and faster & accurate diagnostics. This lecture will capture the progress made thus far in pre-clinical and clinical studies. Further this lecture will discuss the way forward for translation of bench side research into the bed side practice. This lecture also seeks to identify newer opportunities for biomaterials beyond the medical devices.
