Decision-making requires balancing speed and accuracy, and understanding the neural basis of how people flexibly adjust to this tradeoff is an important question in cognitive neuroscience. This study examined whether intrinsic brain organization is associated with latent decision-making parameters involved in the speed-accuracy tradeoff (SAT). 

Resting-state fMRI data was used to test whether functional connectivity and the Hurst Exponent in SAT-related regions were associated with the flexibility with which boundary separation and urgency parameters changed between speed and accuracy conditions. Behavioral parameters were estimated using a reinforcement learning advantage racing diffusion (RL-ARD) model applied to an instrumental learning task with speed and accuracy cues which induced the SAT. 

Bayesian correlation analyses did not reveal significant associations between resting-state measures and latent SAT parameters, while showing moderate evidence towards the null hypothesis. These findings suggest that intrinsic connectivity and temporal dynamics may have a limited relationship with SAT adjustments. 

Future studies may focus on network-level approaches instead of seed-based analyses, to see whether the effects might be more distributed than expected across larger functional systems. Moreover, future work can investigate whether changes in the Hurst Exponent from rest to task, rather than the resting Hurst Exponent alone, better capture adaptive decision-making.