In this lecture, I propose a new foundation for understanding representation, computation, intentionality, and thought in neurocognitive systems. I argue that neural representation and computation are real, mechanistic, and situated, rejecting both classical symbolic theories of mind and purely associationist alternatives. Building from contemporary neuroscience, I offer a novel account of basic intentionality: by simulating nonactual conditions while tracking departures from actual ones, neural systems can successfully represent absent, possible, false, and nonexistent scenarios.