The Mathematical Neuroscience Prize ceremony, 15 October, 2013

Acceptance speech:
First Annual Mathematical Neuroscience Prize

Brain Tech Israel 2013
Tel Aviv, October 14, 2013
Haim Sompolinsky, acceptance speech

I am honored to receive the first annual mathematical neuroscience prize and I thank the donor of the prize and Israel Brain Technology for orchestrating it, as well as Prof. Bert Sakmann for his warm words. I would like to thank my dear parents who came here to celebrate with me, for instilling in my own young nervous system the love of knowledge, the passion for inquiry, and the joy of discovery. 

Thanks to the wonderful students and colleagues that I was fortunate to have and in particular, to Hanoch Gutfreund and the late Daniel Amit, with whom I took the first steps from physics to neuroscience. It is a great pleasure to share the prize with my colleague and friend Larry Abbott, whose creative ideas and insights deeply influenced my own work throughout my career. 

This prize is a token of recognition of the new emerging field of theoretical and computational neuroscience. Leaders of this field come from diverse specialties including physics, mathematics, computer science and engineering. This is no accident. The cross fertilization of different disciplines and the continuous influx of novel ideas and new skills are crucial for making progress in our understanding of the immensely complex brain. We must ensure that computational neuroscience continues to be an interdisciplinary meeting place for the best minds from all corners of science and technology.

This conference celebrates recent breakthrough advances in neurotechnologies that transform neuroscience into a BIG science that generates massive amounts of data on the structure and activity of the nervous system. These advances open new exciting opportunities for translating neuroscience results to clinical and technological applications. 

With these developments, the need for theory becomes more urgent than ever, as the increasingly complex data remain useless without testable hypotheses and mathematical models about the underlying functional principles. And these principles often defy our intuition about computing and information processing. It is increasingly clear that each brain function, from a single percept to a simple action, is the product of the concerted activities of of millions of nerve cells and billion of synapses, forming large dynamical networks whose structures continuously change in response to new experiences. Indeed, the goal of the work of Larry and I and our colleagues has been to develop mathematical theories and models that address this unique distributed, collective, and adaptive character of neural computation.

The changing landscapes of neuroscience has also impacted our approach to neurological disorders, shifting the focus from single isolated molecular pathways to system wide dynamical dysfunctions that result from the convergence of multiple molecular and genetic mechanisms. 
This paradigm shift calls for greater collaboration between computational neuroscientists and clinical researchers to gain a better insight into the so-called dynamical diseases of the brain. 

Thus, computational neuroscience is a vibrant and ambitious enterprise that uses mathematical theories and models to cope with the most daunting challenges, from answering fundamental questions about the function of the brain and its relation to the mind, to addressing the computational problems posed by the quest to heal brain's debilitating diseases. 

Before closing, I would like to acknowledge the generosity of the agencies that funded my work and in particular the Edmond and Lily Safra Center for Brain Sciences, the Gatsby Charitable Foundation, and the Swartz Foundation.