The bottom-up information transfer process and top-down attention control underlying tonal working memory

Abstract

Tonal working memory has been less investigated by neuropsychological and neuroimaging studies and even less in terms of tonal working memory load. In this study, we analyzed the dynamic cortical processing process of tonal working memory with an original surface-space-based multivariate pattern analysis (sf-MVPA) method and found that this process constituted a bottom-up information transfer process. Then, the local cortical activity pattern, local cortical response strength, and cortical functional connectivity under different tonal working memory loads were investigated. No brain area’s local activity pattern or response strength was significantly different under different memory loads. Meanwhile, the interactions between the auditory cortex (AC) and an attention control network were linearly correlated with the memory load. This finding shows that the neural mechanism underlying the tonal working memory load does not arise from changes in local activity patterns or changes in the local response strength, but from top-down attention control. Our results indicate that the implementation of tonal working memory is based on the cooperation of the bottom-up information transfer process and top-down attention control.

SF-MVPA: A from raw data to statistical results and surface space-based MVPA toolbox

“…Surface space-based MVPA has attracted increasing attention because it can avoid the interference of non-gray matter tissues and avoid collecting information from discontinuous brain regions. Some surface space-based MVPA algorithms have been proposed ( Oosterhof et al, 2010 ; Chen et al, 2011 ; Li et al, 2022a , b ). However, due to the difficulty of obtaining searchlight from the surface space, these algorithms all use complex surface searchlight acquisition methods, which makes the programming implementation of these algorithms difficult.…”

“…An fMRI sample dataset is provided to familiarize users with and test the toolbox. The dataset is from a tonal working memory load experiment ( Li et al, 2022a ). In this experiment, the subjects were presented with a sequence of tones, and 20 s later, they were presented with another sequence of tones.…”

“…The T1-weighted structural data (1 × 1 × 1 mm) and T2*-weighted functional data (2.5 × 2.5 × 2.5 mm, TR = 1 s) were collected. For detailed scanning parameters, please refer to Li et al (2022a) .…”

“…(2.5 × 2.5 × 2.5 mm, TR = 1 s) were collected. For detailed scanning parameters, please refer to Li et al (2022a).…”

“…To address these issues, researchers proposed surface space-based MVPA methods ( Oosterhof et al, 2010 ; Chen et al, 2011 ; Li et al, 2022a , b ). These MVPA methods obtain circular searchlights directly from the surface space (although there are differences in details of acquiring searchlights).…”