Yerkes and Dodson (1908) noted that the efficacy of learning in rats varies with level of arousal, such that low and high arousal predicted poorer learning than a medium level of arousal. Berlyne (1960) proposed that curiosity modulates the likelihood of learning, with low and high curiosity leading to poorer learning outcomes than a medium level of curiosity. Kinney and Kagan (1976) proposed that infants have a tendency to attend maximally to stimuli of moderate complexity (or discrepancy with respect to a family of stimuli) compared to

overly simple or overly complex stimuli. The key difference between signaling pathway these past observations is that the proposed mediating mechanism (arousal, curiosity, discrepancy) was not defined quantitatively and was not assessed independently of the measure of attention itself. That

is, stimuli were chosen based on intuitions about how they related to the mediating mechanism, and when a U-shaped function was obtained, the mediating mechanism was interpreted as verified. In contrast, Kidd et al. (2012) quantitatively defined information complexity before presenting the stimulus sequences and eliminated the effects of Trichostatin A mouse a variety of other potential mediators of the obtained U-shaped function. The results of Kidd et al. (2012) raise a variety of unanswered questions. First, what enables infants (and monkeys) to implicitly notice that they are failing to “understand” the complex events and why are they choosing to terminate these fixation? One possibility is that learners are evaluating the choice between “making progress” in understanding a sequence of events and failing to see any benefit in attempting to learn something that is more complex compared to reallocating attention to something

that is not yet known but may be simpler to learn. That is, attention is selective and can be allocated to multiple sources of information. Learners may have, by prior experience, learned that if a sequence of events is not “mastered” within some period of time, they are likely to find other sources that can be more effectively “mined” for information and are more readily accessible. However, a limitation of the Kidd et al. work is that allocation of attention was not linked to the efficacy of learning. It is possible that the “sweet spot” of the Goldilocks function is where information is best learned, but it is also possible that learning occurs best on the rising portion of the function where information is slightly more complex. There are hints in a recent study by Tummeltshammer and Kirkham (2013) that learning is in fact facilitated when an intermediate level of predictability is present. A third limitation of the Goldilocks results is that so far they only apply to sequential events and only to stimuli that are not “special” in some way. The choice of sequential events was driven by the goal of quantitatively characterizing the information complexity of the stimuli (i.e.