Neural structural representations are cerebral map- or model-like structures that structurally resemble what they represent. These representations are absolutely central to the “cognitive neuroscience revolution”, as they are the only type of representation compatible with the revolutionaries’ mechanistic commitments. Crucially, however, these very same commitments entail that structural representations can be observed in the swirl of neuronal activity. Here, I argue that no structural representations have been observed being present in our neuronal activity, no matter the spatiotemporal scale of observation. (...) My argument begins by introducing the “cognitive neuroscience revolution” (Sect. 1 ) and sketching a prominent, widely adopted account of structural representations (Sect. 2 ). Then, I will consult various reports that describe our neuronal activity at various spatiotemporal scales, arguing that none of them reports the presence of structural representations (Sect. 3 ). After having deflected certain intuitive objections to my analysis (Sect. 4 ), I will conclude that, in the absence of neural structural representations, representationalism and mechanism can’t go together, and so the “cognitive neuroscience revolution” is forced to abandon one of its commitments (Sect. 5 ). (shrink)

Predictive processing theorists have claimed PTSD and depression are maladaptive and epistemically distorting because they entail undesirably wide gaps between top-down models and bottom-up information inflows. Without denying this is sometimes so, the “maladaptive” label carries questionable normative assumptions. For instance, trauma survivors facing significant risk of subsequent attacks may overestimate threats to circumvent further trauma, “bringing forth” concretely safer personal spaces, to use enactive terminology, ensuring the desired gap between predicted worries and outcomes. The violation of predictive processing can (...) go in the opposite direction too, as when depression coincides with energy-depletion, and hence objectively strenuous situations in which things look farther away because they are (accurately anticipated to be) harder to reach. These examples partly encapsulate what predictive processing theorists call “active inference,” yet with differences. In the first case, actions fruitfully obviate predictions rather than fulfilling them. In the second, mental models do not dysregulate bodily processes, making coping harder. Instead, problems (e.g., personal obstacles, gastric illness) deplete energy, eliciting a depressive and adaptive slow-down. Some predictive proponents apply correspondence criteria when alleging mismatches between internal models and the world, while incongruously asserting that the brain did not evolve to see things veridically, but to execute actions. An alternative is to adopt pluralistic, pragmatic epistemologies suited to the complexity of mind. The upshot is that mental outlooks can depart from the norm without epistemically being distorted and that mismatches between anticipatory worries and outcomes, when they actually exist, can be a measure of adaptive and epistemic success. (shrink)

I discuss Clark’s predictive processing/extended mind hybrid, diagnosing a problem: Clark’s hybrid suggests that, when we use them, we pay attention to mind-extending external resources. This clashes with a commonly accepted necessary condition of cognitive extension; namely, that mind-extending resources must be phenomenally transparent when used. I then propose a solution to this problem claiming that the phenomenal transparency condition should be rejected. To do so, I put forth a parity argument to the effect that phenomenal transparency cannot be a (...) necessary condition on cognitive extension: roughly, since internal cognitive resources can fail to be transparent when used, by parity, external resources can fail to be phenomenally transparent too. Further, I argue that phenomenal transparency is not even a reliable indicator of cognitive extension; hence its absence should not be considered a problem for Clark’s extended mind-predictive processing hybrid. Lastly, I consider and allay a number of worries my proposal might raise, and conclude the paper. (shrink)