The Neural efficiency score: Validation and application

Abstract

We propose an indirect measure of the efficiency of neural processing: the neural efficiency score (NES). The basis for this measure is the hazard function on the reaction time distribution from a task, h(t), which can be interpreted as an instantaneous measure of work being accomplished, and which has been foundational in characterizations of perceptual and cognitive workload capacity (e.g., Townsend & Ashby, 1978; Townsend & Nozawa, 1995; Townsend & Wenger, 2004). We suggest that the global field power on electroencephalographic (EEG) data (Skrandies, 1989, 1990) can function as a proxy for actual energy expended, and then place h(t) and GFP in a ratio to give a measure that can be interpreted as work accomplished relative to energy expended. To make this proposal plausible, we first need to show that the GFP can be interpreted in terms of energy expended, and we do this using previously unpublished data from an earlier study (Wenger, DellaValle, Murray-Kolb, & Haas, 2017) in which we simultaneously collected EEG and metabolic data during the performance of a cognitive task. Having shown that the GFP can be used as a proxy for energy expended, we then demonstrate the interpretability of the NES by applying it to previously unpublished data from a more recent study (Newbolds & Wenger, 2024). These outcomes suggest the potential for broad applicability of the NES and its potential for characterizing the efficiency of neural energy expenditure in the performance of perceptual and cognitive work.