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Psicothema was founded in Asturias (northern Spain) in 1989, and is published jointly by the Psychology Faculty of the University of Oviedo and the Psychological Association of the Principality of Asturias (Colegio Oficial de Psicólogos del Principado de Asturias).
We currently publish four issues per year, which accounts for some 100 articles annually. We admit work from both the basic and applied research fields, and from all areas of Psychology, all manuscripts being anonymously reviewed prior to publication.

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Cortical surface area variations within the dorsolateral prefrontal cortex are better predictors of future cognitive performance than fluid ability and working memory

Francisco J. Román1, Susanne M. Jaeggi2, Kenia Martínez,1 Jesús Privado3, Lindsay B. Lewis4,5, Chi-Hua Chen2, Sergio Escorial3, William S. Kremen2, Sherif Karama4,5, and Roberto Colom1

1 Universidad Autónoma de Madrid,
2 University of California (USA),
3 Universidad Complutense de Madrid,
4 Montreal Neurological Institute (MNI), and
5 McGill University, Montreal (Canada)

Background: Are cognitive and biological variables useful for predicting future behavioral outcomes? Method: In two independent groups, we measured a set of cognitive (fluid and crystallized intelligence, working memory, and attention control) and biological (cortical thickness and cortical surface area) variables on two occasions separated by six months, to predict behavioral outcomes of interest (performance on an adaptive version of the n-back task) measured twelve and eighteen months later. We followed three stages: discovery, validation, and generalization. In the discovery stage, cognitive/biological variables and the behavioral outcome of interest were assessed in a group of individuals (in-sample). In the validation stage, the cognitive and biological variables were related with a parallel version of the behavioral outcome assessed several months later. In the generalization stage, the validation findings were tested in an independent group of individuals (out-of-sample). Results: The key finding revealed that cortical surface area variations within the right dorsolateral prefrontal cortex predict the behavioral outcome of interest in both groups, whereas the cognitive variables failed to show reliable predictive validity. Conclusions: Individual differences in biological variables might predict future behavioral outcomes better than cognitive variables concurrently correlated with these behavioral outcomes.

Las variaciones de superficie cortical en la corteza dorsolateral prefrontal predicen mejor el futuro desempeño cognitivo que la inteligencia fluida y la memoria operativa. Antecedentes: ¿Predicen las variables cognitivas y biológicas el futuro desempeño cognitivo? Método: en dos grupos independientes de participantes se miden variables cognitivas (inteligencia fluida y cristalizada, memoria operativa y control atencional) y biológicas (grosor y superficie cortical) en dos ocasiones separadas por seis meses, para predecir el desempeño en la tarea n-back valorado doce y dieciocho meses después. Se completan tres etapas: descubrimiento, validación y generalización. En la de descubrimiento se valoran en un grupo de individuos las variables cognitivas/biológicas y el desempeño a predecir. En la de validación, se relacionan las mismas variables con una versión paralela de la n-back completada meses después. En la de generalización, los resultados de la validación se replican en un grupo independiente de individuos. Resultados: las variaciones de superficie cortical en la corteza dorsolateral prefrontal derecha predicen el desempeño cognitivo en los dos grupos independientes de individuos, mientras que las variables cognitivas no contribuyen a la predicción del desempeño futuro. Conclusiones: las diferencias individuales en determinadas variables biológicas predicen el desempeño cognitivo mejor que las variables cognitivas que correlacionan concurrentemente con ese desempeño.

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Impact factor 2022:  JCR WOS 2022:  FI = 3.6 (Q2);  JCI = 1.21 (Q1) / SCOPUS 2022:  SJR = 1.097;  CiteScore = 6.4 (Q1)