A Model for Real-Time Computation in Generic Neural Microcircuits

W. Maass, T. Natschlaeger, and H. Markram


A key challenge for neural modeling is to explain how a continuous stream of multi-modal input from a rapidly changing environment can be processed by stereotypical recurrent circuits of integrate-and-fire neurons in real-time. We propose a new computational model that does not require a task-dependent construction of neural circuits. Instead it is based on principles of high dimensional dynamical systems in combination with statistical learning theory, and can be implemented on generic evolved or found recurrent circuitry.

Reference: W. Maass, T. Natschlaeger, and H. Markram. A model for real-time computation in generic neural microcircuits. In S. Becker, S. Thrun, and K. Obermayer, editors, Proc. of NIPS 2002, Advances in Neural Information Processing Systems, volume 15, pages 229-236. MIT Press, 2003.