Coding of color and form in the geniculostriate visual pathway (invited review).

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Deep learning in neural networks: An overview (2014, neutral): “…2012; Felleman & Van Essen, 1991; Hubel & Wiesel, 1968; Hung, Kreiman, Poggio, & DiCarlo, 2005; Kobatake & Tanaka, 1994; Kriegeskorte et al., 2008; Lennie & Movshon, 2005; Logothetis, Pauls, & Poggio, 1995; Perrett, Hietanen, Oram, Benson, & Rolls, 1992; Perrett, Rolls, & Caan, 1982); compare a…”
How does the brain solve visual object recognition? (2012, neutral): “The IT Population Appears Sufficient to Support Core Object Recognition Although visual information processing in the first stage of the ventral stream (V1) is reasonably well understood (see Lennie and Movshon, 2005 for review), processing in higher stages (e.g., V4, IT) remains poorly understood.”
Selectivity and tolerance (“invariance”) both increase as visual information propagates from cortical area V4 to IT (2010, background): “…V1 neurons are known to be activated by small image patches that contain energy at a particular orientation and spatial frequency (for review, see Lennie and Movshon, 2005); a hypothetical neuron that requires a more complex conjunction of local oriented segments to evoke a response would have a…”
Hierarchical Modular Optimization of Convolutional Networks Achieves Representations Similar to Macaque IT and Human Ventral Stream (2013, background): “Encoding models of lower-level visual responses (RGC, LGN, V1, V2) have been relatively successful [21, 4] (but cf. [26]).”