An innovative neurocognitive study conducted by researchers of the Functional Neuroimaging Laboratory at the Universitat Jaume I and the Center for Brain and Cognition at the Universitat Pompeu Fabra shows that the individual variability that exists in brain connections affects people's learning ability and, in turn, the learning process produces a change in brain networks associated with the trained areas.
The study has been published in the scientific journal Journal of Neuroscience.
Research outcomes conclude that the learning capacity of the human brain can be predicted by studying the initial spontaneous functional connectivity of the brain, in other words, the connection or synchronization of the activity between two or more areas of the brain at rest. "How is configured your brain before you start doing a task can give information to know how much you will learn, and this information is essential from the point of view of psychology. It provides us with a predictive element of how you respond to a learning task," stresses César Ávila, professor in the Department of Basic Psychology, Clinical Psychology and Psychobiology of the Universitat Jaume I.
The researchers took magnetic resonance images (MRI) of the brain at rest and during the performance of a new task before and after a training distributed over two weeks. This task was based on the identification of two phonemes belonging to two Indian languages, Hindi and Urdu, which are difficult to distinguish for a non-native speaker. The study, with a sample of 19 participants, revealed that the initial functional connectivity of the two areas related to training -the frontal operculum/left anterior insula and left superior parietal lobe- were capable of predicting learning. Researchers also noted that participants who showed a greater connection between these areas were the ones who would get a better discrimination between the two phonemes. In addition, after training there was a greater disconnection between these two areas in those participants with a better learning.
Results were confirmed by a second experiment that consisted of a one-hour intensive training for 28 people, which found again the prediction of learning through the study of functional connectivity at rest. "Therefore, we can say that spontaneous brain activity at rest predicts learning ability and helps us understand how learning changes brain function," stated Noelia Ventura-Campos, doctor in Mathematics and researcher at the Universitat Jaume I. Both experiments were conducted with the collaboration of Eresa Grupo Médico at the Provincial Hospital in Castellón.
The innovative methodology developed, consisting of a longitudinal analysis that combines functional magnetic resonance images of the brain in active with images of the brain at rest, enables to interpret brain plasticity associated with a learning process. "This is a new kind of exploration based on studying the great amount of information given by the brain when you do nothing. Knowing how the brain learns has many applications at a clinical and educational level," says César Ávila. In this sense, the researcher highlights that the latest research "is dismantling the belief that the brain ability to be modelled is lost over the age of 20; now, research shows that you can change at any age, adapting to new circumstances, and the study of resting brain patterns can help us to understand precisely how learning changes brain function."
The studies on brain plasticity associated with learning are basic to understand the factors that determine the flexibility of the brain to adapt to a particular situation. "By remodelling the system, people can make use of past experiences to avoid undesirable behaviours or accelerate those that are a benefit," notes Noelia Ventura-Campos. For the researcher, "these studies on brain connectivity changes are probably one of the most important methodological sources for the study of brain plasticity due to learning processes. The generalization of this methodology can help us to determine a priori the possibilities of the brain with subsequent application in the field of education, for example, to determine the best systems to learn languages, mathematics, etc.."
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