The Computational Modeling of Sensitive Periods

By Michael S. C. Thomas, Mark H. Johnson

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Fiona M. Richardson
2. Martial Mermillod
3. Aurélia Bugaiska
4. Patrick Bonin
5. Michael S. C. Thomas
6. German Ignacio Parisi
7. Vincenzo Lomonaco
8. Hichem Sahbi

Citations in the corpus

• The stability-plasticity dilemma: investigating the continuum from catastrophic forgetting to age-limited learning effects (2013, background): “Of course, other factors as competition effects, loss of resources, and assimilation effects are important to produce age limited learning effects (Thomas and Johnson, 2006) and are important to control as possible confounded variables.”
• Critical periods and catastrophic interference effects in the development of self-organizing feature maps. (2008, methodology): “For example, in a review of computational models of sensitive periods in development, Thomas and Johnson (2006) pointed out that the Hebbian learning algorithm (from which most neural network learning algorithms are derived) includes a learning rate parameter e that determines the size of the weig”