Serious philosophical engagement with neuroscience dates back at least to Patricia Churchland’s Neurophilosophy (1986). As computational neuroscience matured, Churchland became one of its main philosophical champions (Churchland, Koch, and Sejnowski 1990; Churchland and Sejnowski 1992). She was joined by Paul Churchland (1995, 2007) and others (Eliasmith 2013; Eliasmith and Anderson 2003; Piccinini and Bahar 2013; Piccinini and Shagrir 2014). All these authors hold that theorizing about mental computation should begin with the brain, not with Turing machines or other inappropriate tools drawn from logic and computer science. They also hold that neural network modeling should strive for greater biological realism than connectionist models typically attain. Chris Eliasmith (2013) develops this neurocomputational viewpoint through the Neural Engineering Framework, which supplements computational neuroscience with tools drawn from control theory (Brogan 1990). He aims to “reverse engineer” the brain, building large-scale, biologically plausible neural network models of cognitive phenomena.