Controlling brain dynamics: Landscape and transition path for working memory
Fig 6
Landscape control identifies the optimal combination of stimulation targets for the improvement of behavioral performance.
(A) Scheme of simplified distributed working memory model which is composed of 30 interconnected excitatory areas with a gradient of local coupling strengths. (B) An illustration of the landscapes of the simplified model before and after landscape control (LC). Before control, the resting state is deep and stable; after control, the memory state becomes dominant and the system is more inclined to stay in the memory state. (C) The change of the occupancy of memory state before and after LC under different global coupling strengths G. (D) The external stimulation currents of each brain area identified by LC for the improvements of working memory. (E) The top 8 optimal stimulation targets for the improvement of working memory function. The corresponding stimulation currents are indicated by colors. (F) By landscape control, the change of inter-areal connectivity in the prefrontal network can be identified to achieve larger occupancy of desired memory state.