Poster
in
Workshop: Shared Visual Representations in Human and Machine Intelligence (SVRHM)

Measuring the Alignment of ANNs and Primate V1 on Luminance and Contrast Response Characteristics

Stephanie Olaiya · Tiago Marques · James J DiCarlo


Abstract:

Some artificial neural networks (ANNs) are the current state-of-the-art in modeling the primate ventral stream and object recognition behavior. However, how well they align with luminance and contrast processing in early visual areas is not known. Here, we compared luminance and contrast processing in ANN models of V1 and primate V1 at the level of single-neuron. Model neurons have luminance and contrast response characteristics that differ from those observed in macaque V1 neurons. In particular, model neurons have responses weakly modulated by changes in luminance and show non-saturating responses to high contrast stimuli. While no model perfectly matches macaque V1, there is great variability in their V1-alignment. Variability in luminance and contrast scores is not correlated suggesting that there are trade-offs in the model space of ANN V1 models.

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