A New Work Mechanism on Neuronal Activity

Abstract

By re-examining the neuronal activity energy model, we show the inadequacies in the current understanding of the energy consumption associated with neuron activity. Specifically, we show computationally that a neuron first absorbs and then consumes energy during firing action potential, and this result cannot be produced from any current neuron models 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 oxygen consumption is very small. We can also explain why external stimulation and perception emergence are synchronized. We also show that negative energy presence in neurons at the sub-threshold state is an essential reason that leads to blood flow incremental response time in the brain rather than neural excitation to delay.

The essence of neuronal activity from the consistency of two different neuron models

“…2) is well consistent with the calculated results (Fig. 3) of the Wang-Zhang's neuron model [6,11]. It should be emphasized that the H-H model is established at the molecular level and that our model is directly based on the neuron.…”

“…For this purpose, a novel theory of neural coding has been proposed in neuroscience researches [4][5][6][7][8][9][10][11][12][13], which provides a new perspective on how to understand the nature of neuronal activity. The core of this coding theory is that there is a unique correspondence between various neuronal membrane potentials and their neural energy expenditure, which makes it possible to convert the firing patterns of a variety of complex, highly nonlinear membrane potentials into new neural information processing methods that are processed in an energy's firing pattern and have been named as neural energy coding [7][8][9][10][11][12][13].…”

“…However, neural energy provides an effective scheme for solving the above problems. (4) Since the energy is a scalar, whether it is a single or neuron population, or whether it is a network or a behavioral, as well as a linear or a nonlinear neural model, their dynamic responses can be used to describe patterns of energy coding by superposition of neural energy [4,[6][7][8][9][10][11][12]. Thus, global information about the inherent, intrinsic, and functional neural activities can be obtained, while it cannot be achieved by other traditional coding theories [15,[17][18][19][20][21].…”

“…In our previous work, a novel neuron biophysical model named Wang-Zhang was proposed [8]. By modifying this model, we presented the energy function of a single neuron membrane potential and its computational method; thus, we found a new working mechanism of neuronal activity [6]. Our study indicates that neuron does not only consume energy in traditional sense, while it firstly absorbs energy from the blood flow and then consumes energy, so this important finding modifies the traditional point of view that neuron only consumes energy.…”

“…In order to prove the validity of Wang-Zhang's neuron biophysical model [6,11], this study used the H-H model to calculate the energy characteristics of action potentials and membrane potentials. Since almost all previous studies focused on how neural energy will be changed by neural activities.…”