Finn, A.
Statistical learning has been put forth as a powerful learning mechanism that can be used to effortlessly-even automatically-extract meaningful
information from our information-dense worlds. The effortless nature of this learning, alongside robust demonstrations of statistical learning
in infants, has led us to conclude that statistical learning is a form of implicit learning. In the present talk, I examinewhether statistical
learning is best construed as falling under the canonical umbrella of unconscious implicit memory or conscious explicit memory. I will present
a series of experiments in which I measure statistical learning over a delay and in complex environments to assess how learning decays over
time and capacity limitations. In so doing, I will relate patterns to what is known about implicit and explicit learning systems. Using a
developmental lens, I will further explore the neural substrates of statistical learning-both structural and functional-asking whether the
neurobiology of statistical learning overlaps most with neural regions that are canonically associated with explicit or implicit processes and,
crucially, whether these substrates shift with brain development. I will conclude with a framework for how to situate statistical learning with
respect to other work on memory, highlighting that this relationship is dynamic, changing greatly with age.