The Computational Theory Of Neural Energy Coding And Its Application In Mental Exploration

The problem of how the nervous system expresses the external information is also known as neural coding problem,which is one of the most important basic problems of cognitive neuroscience.And the electrical activity of neuron is the basis of neural coding.The classic coding theories describe the electrical activity of neuron by action potential and firing rate.These researches now encounter their own bottlenecks.However,energy coding method studies the coding problem by the energy characteristics of neuronal activity which possesses the advantages of globality and economy.This research analyzed the energy coding theory in computational level and applied it to spatial positioning and navigation.First,we discussed the theoretical basis of energy coding,which is the energy characteristics of the neuron.In this study,we calculated neural energy supply and consumption based on the Hodgkin-Huxley model,during firing action potentials and sub-threshold activities using ion-counting and power-integral model.Furthermore,we analyzed energy properties of each ion channel,and found that under these two circumstances,power synchronization of ion channels and energy utilization ratio have significant differences.This is particularly true of the energy utilization ratio,which can rise to above 100%during sub-threshold activity,revealing an overdraft property of energy use.These findings demonstrate the distinct status of the energy properties during neuronal firings and sub-threshold activities.Meanwhile,after introducing a synapse energy model,this research can be generalized to a neural network energy model.And it will be able to integrate with functional magnetic resonance imaging(fMRI)and local field potential(LFP)data.This is potentially important for understanding the relationship between energy supply-consumption of dynamical network activities and the cognitive behaviors.Based on these results,we further studied the application of energy coding methods in constructing cognitive map and mental exploration.Cognitive map which represents the external environment is a way to solve the spatial problems.In the classic model of cognitive map,the system needs large amounts of physical exploration to study spatial environment so as to solve path-finding problems,which costs a lot of time and energy.Although Hopfield’s mental exploration model makes up for the deficiency mentioned above,the efficiency of the path has not been focused in the model.Moreover,this model mainly comes from the artificial neural network,lacking of clear physiological significance.In this work,based on the concept of mental exploration,neural energy coding theory has been applied to the calculation model so as to solve the path search problem:energy field is constructed in the model on the basis of the firing power of place cell clusters,and energy field gradient is calculated which can used to study mental exploration problem.The study shows that the new mental exploration model proposed in the paper can efficiently find the optimal path,and present the learning process with biophysical meaning as well.The new idea verifies the importance of place cell and synapse on spatial memory and the efficiency of energy coding,which help us to understand the theoretical basis for the neural dynamics mechanism of spatial memory.After constructing the mental exploration model on the two-dimensional plane,we further studied that how the three-dimensional space is represented in the brain.It is an empty research area that how does the place cell study and locate the three-dimensional space.In this study,we established a place cell population network model representing the three-dimensional space from the energy prospective.And place field,place field center are defined by energy.Then we analyzed the locating function and energy properties.Results showed that this model presented a good simulation of the characteristics of place cell.Every place cell acquired a unique spatial selectivity,and the locating error of the system is limited in a proper boundary.This model is not only a generalization of the low-dimensional space place cell model in three-dimensional space,but also the generalization of the firing rate model in the energy level.Furthermore,this is a new exploration that a functional neural network is directly built by energy coding method.The study reveals the energy economic principle of the brain in encoding three-dimensional spatial information.This work will lay the foundation for the complete construction of the cognitive model of the brain for the actual three-dimensional space.It will further reveal that how the brain process the locating,navigating and path planning function under the energy economic principle.This will open a new chapter for our understanding of the magical brain.