Abstract Iconicity refers to a resemblance between word form and meaning. Previous work has shown that iconic words are learned earlier and processed faster. Here, we examined whether iconic words are recognized better on a recognition memory task. We also manipulated the level at which items were encoded—with a focus on either their meaning or […]

This paper proposes a neural network model that estimates the rotation angle of unknown objects from RGB images using an approach inspired by biological neural circuits. The proposed model embeds the understanding of rotational transformations into its architecture, in a way inspired by how rotation is represented in the ellipsoid body of Drosophila. To effectively […]

Contemporary neural network models often overlook a central biological fact about neural processing: that single neurons are themselves complex, semi-autonomous computing systems. Both the information processing and information storage abilities of actual biological neurons vastly exceed the simple weighted sum of synaptic inputs computed by the “units” in standard neural network models. Neurons are eukaryotic […]