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Anticipating and enacting worlds: moods, illness and psychobehavioral adaptation

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Abstract

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.

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Notes

  1. Predictive processing theorists might try to argue their way out of these objections with the concept of “precisions.” Precisions refer to the probable weightings (likelihood of being true) that are attributed to given predictions. Thus in the dog example, the precision is low, which means the expected error of the prediction is high. Predictive processing theorists sometimes talk about low-precision predictions that have life-altering significance, which the brain therefore takes seriously, despite the high rate of expected error. But none of these arguments obviate the fact that when it comes to expected worries, we want a gap between predictions and outcomes, and further, that the overestimation is often exactly what secures the desired gap. Another attempted rebuttal might be that agents are correctly predicting danger in the area in which 10% of dogs are rabid. But in addition to being ad hoc, there remains a prediction error between over-anticipated worries and their failure to occur, along with the fact that this error is desirable.

  2. Other scientific notions such as relativistic concepts of space and time remain fairly reliant on everyday experience and language insofar as the scientific perspective twists and therefore depends on lived understandings (see Crippen 2015; Merleau-Ponty 1945, pp. vii-xxi), but for contrasting view, see Barrett (2017).

  3. Though not focused on psychiatric conditions, Clark’s Surfing Uncertainty (2016, Ch. 9) dovetails with the claim that depressed individuals are habitually “switched on” to anticipate unfavorable events.

  4. Certain robot vacuums exemplify the principle of the world itself being a good model. Combined with detection-actuation mechanisms, the vacuum’s round body and the fact that it turns into obstacles it hits, the robot cleaner can follow the circular shape of a pillar, the straight line of a wall, or the right angle of a corner (Crippen, 2022b; Crippen and Rolla, 2022). In other words, the vacuum can use the room and things in it to navigate without an internal model of its surroundings.

  5. The above is a majority position, but the literature obviously has exceptions. Facchin (2021) argues that predictive processing need not entail mental simulations. Others (e.g., Bruineberg et al., 2018) attempt to preserve core ideas from predictive processing, while rejecting the theory itself, partly on the grounds that it is too representational (which also means at odds with their ecological and enactive commitments).

  6. Wormwood et al. (2017) inadequately highlight just how ambiguous their stimuli are, which are not presented in their published article. Instead, they place a link appended at the very end of only the e-version of their article (so not in the print or PDF rendering). The link is obscured, i.e., one needs to hit “Supporting Information” for it to appear. The link does not lead to a webpage but instead prompts the download of a docx file that has a variety of information, with two examples of the stimuli they used tucked away on the last page.

  7. Traffanstedt and colleagues (2016) question whether seasonal affective disorder exists, but Young (2016) identifies numerous methodological and conceptual problems in the critique.

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Acknowledgements

I owe a debt to the anonymous reviewers and to the editors of Phenomenology and the Cognitive Sciences, especially Maria Brincker and Desthinie Jane Jarandilla. This article also benefited from discussions at PSI2023 (Current Debates in Philosophy of Science), a conference hosted at Azim Premji University in Bengaluru, India. A special thanks goes to Joerg Fingerhut and Aimée Lê for their thoughtful comments on early drafts. Finally, I am grateful the people at the Dominican Institute for Oriental Studies in Cairo for letting me write there during summer and winter breaks and to individuals at Pusan National University and the Berlin School of Mind and Brain for supplying various supports.

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Crippen, M. Anticipating and enacting worlds: moods, illness and psychobehavioral adaptation. Phenom Cogn Sci (2023). https://doi.org/10.1007/s11097-023-09934-x

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