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The efficacy studies of neurocognitive training have focused on the components of the programmes and general methodological questions, not presenting a  rationale  for the individualization of the intervention, even though this is an essential factor for efficacy. The main objective of this manuscript is to propose a framework for the individual planning of neurocognitive training sessions based on the results of neuropsychological assessment. The proposed framework is coined Branched Programmed Neurocognitive Training (BPNT). BPNT is based on the programmed learning approach and inspired on the Luria’s neurocognitive model. The main premises of this framework are the interdependence and hierarchical organization of the cognitive functions, and the individualization of neurocognitive training with multiple patient-tailored paths. The BPNT framework provides guidelines for planning an individualized neurocognitive training in four stages. The potential advantages of this proposal are discussed at various levels, including the role of reward in neurocognitive training and the potential effects of the model on the maintenance and generalization of intervention results. The BPNT framework can be used as an algorithm for the development and adaptation of paper and pencil programmes, as well as computerized rehabilitation platforms. Studies are in place to examine the feasibility of this framework.Implications for rehabilitationIndividualized neurocognitive training guided by neuropsychological assessment is most likely to be effective.Branched Programmed Neurocognitive Training (BPNT) model provides guidelines to organize the neurocognitive training based on the results of neuropsychological assessment.BPNT is based on the programmed learning model and the Luria neurocognitive model, addresses the role of reward in neurocognitive training and considers the fundamental principle of Errorless Learning.BPNT can be used as an algorithm for the development and adaptation of paper and pencil programmes and computerized rehabilitation platforms. Individualized neurocognitive training guided by neuropsychological assessment is most likely to be effective. Branched Programmed Neurocognitive Training (BPNT) model provides guidelines to organize the neurocognitive training based on the results of neuropsychological assessment. BPNT is based on the programmed learning model and the Luria neurocognitive model, addresses the role of reward in neurocognitive training and considers the fundamental principle of Errorless Learning. BPNT can be used as an algorithm for the development and adaptation of paper and pencil programmes and computerized rehabilitation platforms.

Programmed neurocognitive training: proposal of a new approach