Receive a weekly summary and discussion of the top papers of the week by leading researchers in the field.

In Neuroscience and biobehavioral reviews

In this paper, we show that organisms can be modeled as hierarchical Bayesian control systems with small world and information bottleneck (bow-tie) network structure. Such systems combine hierarchical perception with hierarchical goal setting and hierarchical action control. We argue that hierarchical Bayesian control systems produce deep hierarchies of goal states, from which it follows that organisms must have some form of 'highest goals'. For all organisms, these involve internal (self) models, external (social) models and overarching (normative) models. We show that goal hierarchies tend to decompose in a top-down manner under severe and prolonged levels of stress. This produces behavior that favors short-term and self-referential goals over long term, social and/or normative goals. The collapse of goal hierarchies is universally accompanied by an increase in entropy (disorder) in control systems that can serve as an early warning sign for tipping points (disease or death of the organism). In humans, learning goal hierarchies corresponds to personality development (maturation). The failure of goal hierarchies to mature properly corresponds to personality deficits. A top-down collapse of such hierarchies under stress is identified as a common factor in all forms of episodic mental disorders (psychopathology). The paper concludes by discussing ways of testing these hypotheses empirically.

Goekoop Rutger, de Kleijn Roy

2021-Jan-23

Organisms, active inference, biological networks, bow-tie motif, entropy, free energy, goal hierarchy, goal-directed learning, hierarchical Bayesian control systems, hierarchical Bayesian inference, higher goals, human behavior, information bottleneck structure, machine learning, mental disorders, moral functioning, network theory, personality, psychopathology, stress, variational auto-encoders