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The human nervous system processes a continuous stream of multi-modal input from a rapidly changing environment. A key challenge for neural modeling is to explain how the neural microcircuits (columns, minicolumns, etc.) in the cerebral cortex whose anatom ...
Fault-tolerant design methods for VLSI circuits, which have traditionally been addressed at system level, will not be adequate for future very-deep submicron CMOS devices where serious degradation of reliability is expected. Therefore, a new design approac ...
Most simple neuron models are only able to model traditional spiking behavior. As physiologists discover and classify different electrical phenotypes, computational neuroscientists become interested in using simple phenomenological models that can exhibit ...
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 computation ...
The local microcircuitry of the neocortex is structurally a tabula rasa, with the axon of each pyramidal neuron having numerous submicrometer appositions with the dendrites of all neighboring pyramidal neurons, but is functionally highly selective, with sy ...
It is quite difficult to construct circuits of spiking neurons that can carry out complex computational tasks. On the other hand even randomly connected circuits of spiking neurons can in principle be used for complex computational tasks such as time-warp ...
We introduce a two-dimensional integrate-and-fire model that combines an exponential spike mechanism with an adaptation equation, based on recent theoretical findings. We describe a systematic method to estimate its parameters with simple electrophysiologi ...
Temporal integration of information and prediction of future sensory inputs are assumed to be important computational tasks of generic cortical microcircuits. It has remained open how cortical microcircuits could possibly achieve this, especially since the ...
We describe evolution of spiking neural architectures to control navigation of autonomous mobile robots. Experimental results with simple fitness functions indicate that evolution can rapidly generate spiking circuits capable of navigating in textured envi ...
We give an overview of the EPFL indoor flying project, whose goal is to evolve neural controllers for autonomous, adaptive, indoor micro-flyers. Indoor flight is still a challenge because it requires miniaturization, energy efficiency, and control of non-l ...