Neural Energy Properties and Mental Exploration Based on Neural Energy Field Gradient
Neural coding problem is one of the most important basic problems of cognitive neuroscience. The classic coding theories based on firing rate now encounter their own bottlenecks. Energy coding method studies the coding problem by the energy characteristics of neural systems which possesses the advantages of globality and economy. This research analyzed the energy coding theory in computational level and applied it to mental exploration and path optimization. First, we defined and calculated the neural energy supply and consumption based on the Hodgkin-Huxley model during two activity states using ion-counting and power integral method. Then the energy properties of each ion channel are analyzed. The energy efficiency of a neuron is 76% and above 100% under these two circumstances. Finally, we study the mental exploration by energy method and constructed an effective model to find and optimize the path to the target.