Temporal dynamics of quantity processing: distinct time course and representational patterns revealed by multivariate...

People employ both discrete and continuous quantities to quantify aspects of their environment. However, the temporal dynamics and interactions underlying the processing of these quantitative information remain insufficiently understood. Our study aimed to address this gap by employing a one-back task in conjunction with magnetoencephalography (MEG) to investigate neural responses to dot stimuli representing both discrete (e.g., number of dots) and continuous (e.g., distribution of dots in space) quantities. Our primary finding, derived from representational similarity analysis (RSA), was that processing of field area and numerosity information preceded that of individual information (e.g., individual area and shape), suggesting different timing in the processing of these visual dimensions. Furthermore, within-dimensional temporal generalization analysis revealed distinct temporal patterns of these two different information: numerosity and field area exhibited a combination of chain-like (sequential, non-overlapping processes) and reactivated (initially active, then silent, then reactivated) patterns. Notably, an intermediate 'silent' phase emerged between the initial generalizable representation and subsequent trials, indicating the retrieval of early information to meet subsequent task demands (e.g., the one-back response). In contrast, individual area and shape predominantly followed a chain-like pattern. Furthermore, cross-dimensional temporal generalization analysis showed that numerosity and individual area representations could generalize to each other point-to-point in time, and that early numerosity representations and late individual area representations also generalized to each other, implying both parallel and sequential shared representation of these quantities. Field area showed limited generalization to numerosity and individual area, suggesting that they are processed independently. In summary, our results suggest that quantity processing involves temporally distinct operations with different processing timings and a shared encoding pattern of numerosity and individual area that links these temporally distinct processes.