Our understanding of the neural dynamics of prefrontal cortex (PFC) and its interactions in complex cognitive tasks derives largely from recordings made in monkeys extensively trained on the task at hand. Whilst providing invaluable information, this approach ignores crucial learning and dynamic components of PFC function that occur during training. My previous work and that of others suggests that these components are central to the function of the PFC, and so we lack important information on a key role of PFC. Understanding PFC’s role in task acquisition is therefore an important scientific challenge in of itself, but it will also have important impacts down the line for the domains of cognitive training for education and lesion recovery. PREDYCT will study how the properties of PFC network dynamics change throughout cognitive training in monkeys. To do so I will develop a novel paradigm: longitudinal chronic neurophysiology in free-access cognitive testing combined with regular DREADD (Designer Receptors Exclusively Activated by Designer Drugs) inactivation of prefrontal interactions. I will make longitudinal recordings in monkeys at every stage of cognitive training, starting with naïve animals. I will make concurrent recordings at the single cell, local field, and brain surface levels, to access multi-scale encoding and dynamics, and so that changes in local circuitry can be directly compared to surface recordings from non-invasive methods in humans. I will make these recordings in PFC but also simultaneously in posterior parietal cortex (PPC) to study how this cortical interaction, known to be part of the putative multiple demand network and implicated in cognitive training, is altered during training. I will allow monkeys to self-pace their training using a free-access training apparatus, to make training as naturalistic as possible and extract data about motivation as well as performance. Motivation is a critical element for cognitive training and frontal neurophysiology. To understand causal contributions of cortical interactions I will use chemo-genetic DREADD inactivation punctually throughout training, a technique at the forefront of intervention technology. Together PREDYCT represents a unique methodological combination necessary to address my objectives, and with my research experience and supportive laboratory and team, I am perfectly placed to develop such an approach. The methodological advances also represent a highly significant refinement in the context of the 3Rs for electrophysiological recordings in the monkey. PREDYCT will therefore provide detailed fundamental mechanistic and causal data on the neural basis of cognitive training, data critically absent from the literature. This fundamental information will be applicable in a number of important fields in medicine and human sciences.