Topic: network complexity

Observations that have received little attention indicate that complexity is important for flexibility and adaptability of natural behavior and the remarkably efficient learning of the brain. The term complexity implies meaningful structural richness, which exists in systems that offer a plurality of possible solutions. The existence of multiple solutions in the neuronal network enables the brain to interpret a diverse set of sensory inputs and can allow it to operate and respond flexibly across a wide array of contexts. Hence it is important to study factors that can enable network complexity

Several studies highlight motivation's crucial role in motor decision-making for maximizing potential rewards. However, how explicit rewards impact the neural dynamics of decision-making processes and their effects on neural organization at the network level, is still unexplored. To address this gap, we analyzed neuronal activity recorded from the premotor cortex (PMd) of three monkeys while performing a modified version of the stop signal task. In this task, the motivation to either act or inhibit action was manipulated using Cues that informed about different reward contexts. We conducted an