A Study Of Energy Efficiency In Temperature-sensitive Neurons

The human brain can encode and transmit information through hundreds of billions of neurons and millions of billions of synapses in milliseconds.But the brain needs the energy to transmit information.Therefore,energy consumption plays a very important role in the function and evolution of neurons,neural circuits,and even the whole brain.On the other hand,the limited energy consumption can also be used as external constraints to optimize the connection of neural networks and the generation and transmission of neural signals,and ultimately play a role in saving energy.At present,the proposed ratio of maximum coding ability to energy consumption,that is,energy efficiency has been considered as one of the key principles of neural system evolution under selective pressure.Therefore,the energy efficiency of the nervous system has an important impact on the design,function,and evolution of the brain.Many factors that affect energy efficiency are obtained in experiments and theoretical studies.At the same time,in the biological world,the temperature is an important factor affecting the activity of life,which affects the movement of ions and biological reactions.This paper studies the energy efficiency of temperature-sensitive neurons.Based on Huber Braun(HB)neuron model,the effect of temperature on the information transfer and energy efficiency of HB neurons with pulse input is studied.The results show that when the input signal is strong and the frequency is high,the neurons in the high-temperature area will transmit information with a larger capacity.At the same time,when the temperature is close to high temperatures,the low and medium frequency signal will make the energy efficiency of neurons reach the best value.We also studied how temperature affects the energy efficiency of HB neurons in the process of information transmission.We find that there is an optimal temperature range,which can make energy efficiency reach the optimal value.That is to say,proper temperature allows neurons to carry more input information.Interestingly,the optimal temperature at this time is similar to the survival temperature of species with evolution and adaptability.According to the electrophysiological characteristics of neurons,Hodgkin determined two kinds of basic neurons,which correspond to different dynamic mechanisms of the action potential.Based on the Morris lecar(ML)neuron model,this paper studies the effect of temperature on information processing ability and energy efficiency of class ? and class ? neurons.The energy efficiency of neurons can be maximized by temperature.And this result is consistent with the previous experimental and theoretical research.Interestingly,the effect of temperature on the two kinds of neurons is different.At the same temperature,for the same above threshold DC stimulation,the threshold value of class I neurons is less than that of class ? neurons,but the firing frequency of class ? neurons is greater than that of class ? neurons.However,when the temperature increases,the total entropy rate,and information rate are almost constant at first,and then rapidly decrease to zero.Secondly,we also found that with the increase of temperature,the energy consumption of neurons decreased.However,the energy consumption of class ? neurons is significantly higher than that of class ? neurons.It's also interesting that class ?neurons consume less energy than class ? neurons,but the total entropy and information rate are the same under the same conditions.When the temperature is lower than the optimal temperature,the energy efficiency of class ? neurons is significantly higher than that of class? neurons.However,when the temperature is higher than the optimal temperature,the energy efficiency of class ? neurons is less than that of class ? neurons.