Dynamic Representation of Inhibitory Control in a Go/No-Go Task:
Evidence from Multivariate Pattern Analysis
Abstract
Inhibitory control represents a fundamental cognitive function essential
to human behavior. However, the precise neural mechanisms underlying
this process remain incompletely elucidated. This study investigated the
dynamic representation of inhibitory control by using a Go/No-Go task
and the multivariate pattern analysis (MVPA). Decoding analysis revealed
that neural representations of inhibitory control emerged around 100 ms
post-stimulus, earlier than traditionally observed ERP components.
Temporal generalization analysis identified distinct phases of static
and dynamic neural representations, suggesting a complex, multi-stage
process of inhibitory control. Weight projection analysis highlighted
the involvement of occipital, prefrontal, and parietal regions,
indicating the recruitment of diverse neural networks throughout the
task. Additionally, brain and behavior correlation results found that
decoding accuracy between 340-500 ms post-stimulus was significantly
correlated with response times, linking neural representations to
behavioral outcomes. These findings provide new insights into the
temporal dynamics and neural mechanisms of inhibitory control, extending
beyond conventional ERP analyses. The study demonstrates the utility of
MVPA in uncovering subtle neural patterns associated with cognitive
control processes and offers a more comprehensive understanding of the
neural basis of inhibitory control.