How does the primate brain combine generative and discriminative
  computations in vision?
Benjamin Peters James J. DiCarlo Todd Gureckis Ralf Haefner Leyla Isik Joshua Tenenbaum Talia Konkle Thomas Naselaris Kimberly Stachenfeld Zenna Tavares Doris Tsao Ilker Yildirim Nikolaus Kriegeskorte
Vision is widely understood as an inference problem. However, two contrasting
conceptions of the inference process have each been influential in research on
biological vision as well as the engineering of machine vision. The first
emphasizes bottom-up signal flow, describing vision as a largely feedforward,
discriminative inference process that filters and transforms the visual
information to remove irrelevant variation and represent behaviorally relevant
information in a format suitable for downstream functions of cognition and
behavioral control. In this conception, vision is driven by the sensory data,
and perception is direct because the processing proceeds from the data to the
latent variables of interest. The notion of "inference" in this conception is
that of the engineering literature on neural networks, where feedforward
convolutional neural networks processing images are said to perform inference.
The alternative conception is that of vision as an inference process in
Helmholtz's sense, where the sensory evidence is evaluated in the context of a
generative model of the causal processes giving rise to it. In this conception,
vision inverts a generative model through an interrogation of the evidence in a
process often thought to involve top-down predictions of sensory data to
evaluate the likelihood of alternative hypotheses. The authors include
scientists rooted in roughly equal numbers in each of the conceptions and
motivated to overcome what might be a false dichotomy between them and engage
the other perspective in the realm of theory and experiment. The primate brain
employs an unknown algorithm that may combine the advantages of both
conceptions. We explain and clarify the terminology, review the key empirical
evidence, and propose an empirical research program that transcends the
dichotomy and sets the stage for revealing the mysterious hybrid algorithm of
primate vision.