Frontiers in Human Neuroscience (Nov 2016)

Allostatic Self-Efficacy: A Metacognitive Theory of Dyshomeostasis-Induced Fatigue and Depression

  • Klaas Enno Stephan,
  • Klaas Enno Stephan,
  • Klaas Enno Stephan,
  • Zina Mary Manjaly,
  • Zina Mary Manjaly,
  • Christoph Daniel Mathys,
  • Lilian A.E. Weber,
  • Saee Paliwal,
  • TIm Gard,
  • TIm Gard,
  • Marc Tittgemeyer,
  • Stephen M Fleming,
  • Helene Haker,
  • Anil K Seth,
  • Frederike Hermi Petzschner

DOI
https://doi.org/10.3389/fnhum.2016.00550
Journal volume & issue
Vol. 10

Abstract

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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 behaviour), the experience of chronic dyshomeostasis may trigger a generalised 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 in the future.

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