Various neuroscientific theories maintain that brain oscillations are important for neuronal computation, but opposing views claim that these macroscale dynamics are ‘exhaust fumes’ of more relevant processes. Here, we approach the question of whether oscillations are functional or epiphenomenal by distinguishing between measurements and processes, and by reviewing whether causal or inferentially useful links exist between field potentials, electric fields, and neurobiological events. We introduce a vocabulary for the role of brain signals and their underlying processes, demarcating oscillations as a distinct entity where both processes and measurements can exhibit periodicity. Leveraging this distinction, we suggest that electric fields, oscillating or not, are causally and computationally relevant, and that field potential signals can carry information even without causality.

The algorithm of the prefrontal working memory system on sequence memory tasks is not well understood, whereas it is well understood for the hippocampal episodic memory system. This work shows a mathematical duality between working and episodic sequence memory. This leads to a computational understanding of sequence working memory—as structured activity slots. This theory algorithmically explains recurrent neural network (RNN) and prefrontal representations during sequence memory tasks.