Abstract

Studies on the neuronal correlates of decision making have demonstrated that the continuous flow of sensorial information is integrated by sensorimotor brain areas in order to select one among simultaneously represented targets and potential actions. In contrast, little is known about how these areas integrate memory information to lead to similar decisions. Using serial order learning, we explore how fragments of information, learned and stored independently (e.g., A > B and B > C), are linked in an abstract representation according to their reciprocal relations (such as A > B > C) and how this representation can be accessed and manipulated to make decisions. We show that manipulating information after learning occurs with increased difficulty as logical relationships get closer in the mental map and that the activity of neurons in the dorsal premotor cortex (PMd) encodes the difficulty level during target selection for motor decision making at the single-neuron and population levels.

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