Summary: Nicole and I discuss how a signature for visual memory can be coded among the same population of neurons known to encode object identity, how the same coding scheme arises in convolutional neural networks trained to identify objects, and how neuroscience and machine learning (reinforcement learning) can join forces to understand how curiosity and novelty drive efficient learning. Check out Nicole’s Visual Memory Laboratory website. Follow her on twitter: @VisualMemoryLab The papers we discuss or mention: Single-exposure visual memory judgments are reflected in inferotemporal cortex. Population response magnitude variation in inferotemporal cortex predicts image memorability.Visual novelty, curiosity, and intrinsic reward in machine learning and the brain.The work by Dan Yamins’s group that Nicole mentions: Local Aggregation for Unsupervised Learning of Visual Embeddings
