2026-10-14

Cognitive effort is closely linked to prefrontal control, but the control demands imposed by working memory remain poorly understood at the level of neural circuits. We formulated frontoparietal regulation as a feedback-control problem in a conductance-based spiking network comprising an intraparietal ring attractor and a recurrent dorsolateral prefrontal cortex (dlPFC) actuator. A local data-driven task-actuator model was identified around the cue-offset mnemonic state and used to design linear-quadratic regulation. Increasing memory load produced a strong monotonic rise in realized post-cue control effort, driven primarily by sustained dlPFC recruitment. Cue-aligned selective routing supported higher mnemonic loads with substantially less control effort than spatially nonspecific routing. Mean-matched open-loop stimulation reproduced much of the nominal retention benefit, whereas state-dependent feedback provided greater robustness when mnemonic activity was perturbed. Finite-horizon analysis revealed a strongly anisotropic, effectively low-dimensional control geometry dominated by a common mnemonic direction, with much weaker access to item-differentiating directions. These results link increasing working-memory demand to greater sustained prefrontal control requirements and show how frontoparietal routing geometry shapes the efficiency and robustness of mnemonic regulation.