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The evidence shows that productivity is fundamental to cognition and phenomenology. Productivity requires an expandable memory, a necessary condition on Turing-completeness (or universal computation). Neural nets and dynamic systems are thought to be necessarily incapable of Turing-completeness due to structural instability, so that they are impossible to build or find in nature. Therefore if phenomenology is evidence for anything in nature, outside of the "epoché", it is evidence, first and foremost, for the language of thought. That is because the language of thought can trivially recruit memory as needed for productivity, which is an eidetic phenomenological law. Neuroscience is starting to gather evidence for the possibility that a productive symbolic system exists, not between associated neurons, but inside of them, via molecular machinery. This machinery and its symbolic operations have the potential to explain transcendental phenomenology, as it goes beyond associationism, empiricism and their resultant psychologism. Just as Mendel explained Darwin's descent taxonomics, so emerging neuroscience might finally explain Husserl's cognitive taxonomics, setting the stage for a new synthesis in cognitive science.