Elissa Aminoff

The paper examines how scene-preferring brain regions respond to embedded objects in scenes using fMRI data, finding that object composition predicts neural representations, especially within semantic categories.

The paper shows that contextually related objects are more similar in CNN representations than unrelated ones, and this similarity correlates with human behavior in later network layers.

The paper investigates how functional context influences scene processing in specific brain regions, finding that some regions are more sensitive to top-down perceptual expectations than others.

The paper examines spatio-temporal neural dynamics in the human visual cortex using neural network features, finding non-feedforward processes influence early visual cortex activity.