Neural coupling mechanism in fMRI hemodynamics

Abstract

AbstractNeural activity alters with the changes in cerebral blood flow (CBF) and blood oxygen saturation. Despite that these changes can be detected with functional magnetic resonance imaging (fMRI), the underlying physiological mechanism remains obscure. Upon activation of the specific brain region, CBF increases substantially, albeit with 6–8 s delay. Neuroscience has no scientific explanation for this experimental discovery yet. This study proposed a physiological mechanism for generating hemodynamic phenomena from the perspective of energy metabolism. The ratio of reduction (NADH) and oxidation states (NAD+) of nicotinamide adenine dinucleotide in cell was considered as the variable for CBF regulation. After the specific brain region was activated, brain glycogen was rapidly consumed as reserve energy, resulting in no significant change in the ratio of NADH and NAD+ concentrations. However, when the stored energy in the cell is exhausted, the dynamic equilibrium state of the transition between NADH and NAD + is changed, and the ratio of NADH and NAD+ concentrations is significantly increased, which regulates the blood flow to be greatly increased. Based on this physiological mechanism, this paper builds a large-scale visual nervous system network based on the Wang–Zhang neuron model, and quantitatively reproduced the hemodynamics observed in fMRI by computer numerical simulation. The results demonstrated that the negative energy mechanism, which was previously reported by our group using Wang–Zhang neuronal model, played a vital role in governing brain hemodynamics. Also, it precisely predicted the neural coupling mechanism between the energy metabolism and blood flow changes in the brain under stimulation. In nature, this mechanism is determined by imbalance and mismatch between the positive and negative energy during the spike of neuronal action potentials. A quantitative analysis was adopted to elucidate the physiological mechanism underlying this phenomenon, which would provide an insight into the principle of brain operation and the neural model of the overall brain function.