Recent semantic space models learn vector representations for word meanings by observing statistical redundancies across a text corpus. A word's meaning is represented as a point in a high-dimensional semantic space, and semantic similarity between words is quantified by a function of their spatial proximity (typically the cosine of the angle…

In this article, the authors state that the crux of the debate between themselves and Bertenthal and Scheutz (2013) (B&S) is whether imitative compatibility effects reflect the operation of specialized imitation-related mechanisms or instead arise from the same associative learning processes thought to underlie spatial compatibility effects.…

How does the brain learn to recognize an object from multiple viewpoints while scanning a scene with eye movements? How does the brain avoid the problem of erroneously classifying parts of different objects together? How are attention and eye movements intelligently coordinated to facilitate object learning? A neural model provides a unified…

Three computer based experiments, testing human participants in a non-immersive virtual watermaze task, used a blocking design to assess whether two sets of geometric cues would compete in a manner described by associative models of learning. In stage 1, participants were required to discriminate between visually distinct platforms. In stage 2,…

The goal of this work is to extend the theoretical understanding of the relationship between hippocampal spatial and memory functions to the level of neurophysiological mechanisms underlying spatial navigation and episodic memory retrieval. The proposed unifying theory describes both phenomena within a unique framework, as based on one and the…