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Contributed Talk Session: Friday, August 15, 11:00 am – 12:00 pm, Room C1.04
Poster Session C: Friday, August 15, 2:00 – 5:00 pm, de Brug & E‑Hall

Using transfer learning to identify a neural network's algorithm

John Morrison¹, Nikolaus Kriegeskorte², Benjamin Peters³; ¹Barnard College, ²Columbia University, ³University of Edinburgh, University of Edinburgh

Presenter: John Morrison

Algorithms generate input-output mappings through operations on representations. In cognitive science, we use algorithms to explain cognitive processes. For example, we use tree-search algorithms to explain planning, reinforcement learning algorithms to explain exploration, and Bayesian algorithms to explain categorization. To what extent do these algorithms describe processes in the brain? The standard method is to look for parts in the brain that correspond to the parts of an algorithm. However, we haven't found many algorithms using this method. This has led some to view cognitive science algorithms as merely normative, indicating the ideal input-output mapping without describing operations in the brain. It has led others to view these algorithms are nothing more than useful fictions; useful insofar as they allow us to predict behavior, but fictional insofar as they inaccurately describe the causes of that behavior. As an alternative, we suggest identifying a neural system's algorithm by assessing how quickly it learns alternative input-output mappings, that is, its transfer learning profile. The basic idea is that, depending on which algorithm is being used, different input-output mappings will be easier to learn, allowing us to recover its original algorithm from its transfer learning profile. We use artificial neural networks to demonstrate that this proposal productively applies to multiple networks and tasks. We conclude that transfer learning is a promising approach for integrating algorithms with neural networks and thus for integrating cognitive science with systems neuroscience and machine learning.

Topic Area: Methods & Computational Tools

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