Computation and Representation in Cognitive Neuroscience

Cognitive neuroscientists explain cognitive capacities in terms of neural computations over neural representations (e.g., Bechtel 2008). By many measures, their explanations are successful. They are so successful that mainstream cognitive psychology and cognitive science are being absorbed within cognitive neuroscience (Boone and Piccinini 2016). If successful scientific explanation is the measure of what’s real, then cognition involves neural computation over neural representations. Some philosophers beg to differ. On one hand, some insist that computational and representational explanations—or, at any rate, computational and representational explanations of a non-neural sort—are distinct and autonomous from neuroscientific ones (Fodor 1997; Burge 2010). Knoll (this issue) updates this autonomist view for the era of cognitive neuroscience. He concedes that neuroscientific evidence can inform psychological explanation. Nevertheless, he defends the classic autonomist view that some representations and computations have causal powers that their neural realizers lack. On the other hand, antirealists about computation and representation promote non-computational or non-representational explanations of cognition. According to antirealism, computation and representation are at best helpful glosses and at worst misleading metaphors. Cognition is best explained without positing computation and representation.