Quantifying Neural Efficiency and Capacity: A Differential Equation Interpretation of Polynomial Contrasts (1606.06249v1)

Abstract: Task based neuroimaging tools for the study of cognitive neuroscience provide insight into understanding how the brain responds to increasing cognitive demand. Theoretical models of neural-cognitive relationships have been developed based on observations of linear and non-linear increases in brain activity. Neural efficiency and capacity are two parameters of current theoretical models. These two theoretical parameters describe the rate of increase of brain activity and the upper limits of the increases, respectively. The current work demonstrates that a quadratic model of increasing brain activity in response to the n-back task is a solution to a differential equation model. This reinterpretation of a standard approach to analyzing a common cognitive task provides a wealth of new insight. The results include brain wide measures of neural efficiency and capacity. The quantification of neural-cognitive relationships provides evidence to support current cognitive neuroscience theories. In addition, the methods provide a framework for understanding the neural mechanisms of working memory. This allows estimation of the effects of experimental manipulations within a conceptual research framework. The proposed methods were applied to twenty-one healthy young adults while engaging in four levels of the n-back task. All methods are easily applicable using standard current software packages for neuroimaging.