Editors' ChoiceNeuroscience

Learning, Customized for Your Brain

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Science Translational Medicine  15 Feb 2012:
Vol. 4, Issue 121, pp. 121ec27
DOI: 10.1126/scitranslmed.3003839

Whether we like it or not, learning is essential throughout life. How can we make the learning of new skills or knowledge more efficient? Zhang et al. have approached this topic from a new perspective using a multidisciplinary approach. These authors creased a mathematical model of the biochemical signals that control memory formation to design an improved training protocol, which they then tried out in a simple animal, which showed better learning.

Zhang et al. built a computation model that simulated the speed and duration of the biochemical reactions of the protein kinase A (PKA) and extracellular signal-regulated kinase (ERK) signaling cascades, which play a central role in formation of long-term memories. The PKA is activated very quickly, but its action is short-lived; ERK is activated slowly, but lasts longer. The model predicted that teaching protocols that incorporated training sessions of variable lengths, scheduled unevenly over time, were more effective than were the training protocols typically used, which have fixed duration and frequency. Even more interesting, the authors developed a new training protocol on the basis of this prediction and applied it to the sea hare Aplysia, which can learn to retract its siphon when stimulated by a light electrical stimuli on its body. The authors found that training bouts of different lengths, scheduled irregularly, led to an improved learning of the task that lasted longer than when training consisted of a simple fixed-schedule protocol.

Although this study used computational simulation and a simple animal model, it points in an exciting direction. These results exemplify the power of understanding the biomolecular mechanisms of complex behaviors—and the harnessing of foundational understanding to develop new, better learning strategies. The human nervous system is much more complex than that of a sea hare, of course; nevertheless, mechanisms of learning generally follow the same principles. We can look forward to similar studies in human subjects to further test the validity of the computation model. By developing training protocols according to fundamental principles, we may be able to master more of our brain power for acquisition of new skills and recovery of lost functions.

Y. Zhang et al., Computational design of enhanced learning protocols. Nat. Neurosci. 15, 294–297 (2011). [Abstract]

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