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Equation 5 · Prepared Fears: How Evolution Biased What the Mind Learns to Dread

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α\alpha

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a learning-rate parameter governing how much of the gap between the two is closed on a given trial. Read the equation part by part below; each part has a contextual explanation and a link to its mathematical background.

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α\alpha

Symbol α

a learning-rate parameter governing how much of the gap between the two is closed on a given trial.

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where V is the current associative strength between a stimulus and an outcome, λ\lambda is the asymptotic strength that outcome supports, and α\alpha is a learning-rate parameter governing how much of the gap between the two is closed on a given trial. Preparedness theory’s defensible empirical content, on the evidence gathered across the last five sections, is that α\alpha is not one constant shared by every stimulus category — it runs higher for a narrow, evolutionarily recurrent set of categories, including snakes, spiders, and disease cues, than for flowers, mushrooms, geometric shapes, or, evidently, automobiles and wall sockets, which acquire an associated fear only rarely and typically…
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where V is the current associative strength between a stimulus and an outcome, λ\lambda is the asymptotic strength that outcome supports, and α\alpha is a learning-rate parameter governing how much of the gap between the two is closed on a given trial. Preparedness theory’s defensible empirical content, on the evidence gathered across the last five sections, is that α\alpha is not one constant shared by every stimulus category — it runs higher for a narrow, evolutionarily recurrent set of categories, including snakes, spiders, and disease cues, than for flowers, mushrooms, geometric shapes, or, evidently, automobiles and wall sockets, which acquire an associated fear only rarely and typically only after a directly aversive personal encounter. Framed this way, the claim is about one parameter of one general mechanism varying by category, not about a dedicated circuit that bypasses general learning altogether, and it is correspondingly easier to state a condition that would falsify it: a category-level learning-rate difference that shrinks to nothing once other variables are properly controlled would refute it directly, in a way the vaguer language of “modules” is harder to pin down enough to refute at all.

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