Abstract
This paper outlines a hierarchical Bayesian framework for interoception, homeostatic/allostatic control, and meta-cognition that connects fatigue and depression to the experience of chronic dyshomeostasis. Specifically, viewing interoception as the inversion of a generative model of viscerosensory inputs allows for a formal definition of dyshomeostasis (as chronically enhanced surprise about bodily signals, or, equivalently, low evidence for the brain's model of bodily states) and allostasis (as a change in prior beliefs or predictions which define setpoints for homeostatic reflex arcs). Critically, we propose that the performance of interoceptive-allostatic circuitry is monitored by a metacognitive layer that updates beliefs about the brain's capacity to successfully regulate bodily states (allostatic self-efficacy). In this framework, fatigue and depression can be understood as sequential responses to the interoceptive experience of dyshomeostasis and the ensuing metacognitive diagnosis of low allostatic self-efficacy. While fatigue might represent an early response with adaptive value (cf. sickness behavior), the experience of chronic dyshomeostasis may trigger a generalized belief of low self-efficacy and lack of control (cf. learned helplessness), resulting in depression. This perspective implies alternative pathophysiological mechanisms that are reflected by differential abnormalities in the effective connectivity of circuits for interoception and allostasis. We discuss suitably extended models of effective connectivity that could distinguish these connectivity patterns in individual patients and may help inform differential diagnosis of fatigue and depression in the future.
Highlights
Fatigue is a prominent symptom of major clinical significance, in chronic fatigue syndrome (CFS) per se, but across a wide range of immunological and endocrine disorders, cancer and neuropsychiatric diseases
We describe how homeostatic regulation can be regarded as a problem of hierarchical Bayesian inference and control, not dissimilar to previous accounts but with three novel aspects: (i) an explicit discussion of how conventional homeostatic concepts can be transformed into Bayesian counterparts, including an extremely simple but concrete illustration of how active inference could mediate homeostatic control; (ii) the extension of active inference to a formal definition of allostatic control; and (iii) the addition of a metacognitive layer to the interoceptive hierarchy
We revisited how traditional homeostatic concepts can be merged with Bayesian perspectives on interoception, leading to formal definitions for dyshomeostasis and allostasis
Summary
Fatigue is a prominent symptom of major clinical significance, in chronic fatigue syndrome (CFS) per se, but across a wide range of immunological and endocrine disorders, cancer and neuropsychiatric diseases (for overviews, see Wessely, 2001; Chaudhuri and Behan, 2004; Dantzer et al, 2014). It is the most frequent (Stuke et al, 2009) symptom in Multiple Sclerosis (MS), with major impact on quality of life. We consider how such extended generative models might become useful for differential diagnosis of fatigue in the future
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