Learning new tasks can permanently alter the brain’s nerve cells

Interesting research published recently in the online journal Nature shows that (at least in mice), motor learning promotes rapid and persistent physical changes in the connections between brain cells:

Novel motor skills are learned through repetitive practice and, once acquired, persist long after training stops. Earlier studies have shown that such learning induces an increase in the efficacy of synapses in the primary motor cortex, the persistence of which is associated with retention of the task. However, how motor learning affects neuronal circuitry at the level of individual synapses and how long-lasting memory is structurally encoded in the intact brain remain unknown. Here we show that synaptic connections in the living mouse brain rapidly respond to motor-skill learning and permanently rewire.

From there, it gets a little technical for us –  “postsynaptic dendritic spines on the output pyramidal neurons in the contralateral motor cortex” – but we’ve got a pretty good handle on the conclusion:

Rapid, but long-lasting, synaptic reorganization is closely associated with motor learning. The data also suggest that stabilized neuronal connections are the foundation of durable motor memory.

The study looked at motor learning, and we’re obviously a little more interested in non-motor cognitive skills that relate to language and reading development, but the study calls to mind a Stanford University study of the impact of Fast ForWord training on students with dyslexia. That study used behavioral and functional MRI measures to document improvements in oral language and reading performance, as well as increased activity in the areas of the brain responsible for phonological processing (which exhibit deficits in children and adults with dyslexia). The Stanford study didn’t get to the level of analyzing dendritic spines, but certainly the changes in brain activity suggest a similar underlying change in the structure of neurons after training with Fast ForWord.

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