COMPUTATION OF NEURONAL ENERGY BASED ON INFORMATION CODING

By re-examining the energy model for neuronal activities, we show the inadequacy in the current understanding of the energy consumption associated with the activity of a neuron. Specifically, we show computationally that a neuron first absorbs energy and then consumes energy during firing action, and this result cannot be produced from any current models of neurons or biological neural networks. Based on this finding, we provide an explanation for the observation that when neurons are excited in the brain, blood flow increases significantly while the incremental consumption of oxygen is very small. We can also explain why external stimulation and perceptual emergence are synchronized.