Active inference is a normative principle underwriting perception, action, planning, decision-
making and learning in biological or artificial agents. From its inception, its associated …

Motivated control refers to the coordination of behaviour to achieve affectively valenced
outcomes or goals. The study of motivated control traditionally assumes a distinction …

The active inference framework, and in particular its recent formulation as a partially
observable Markov decision process (POMDP), has gained increasing popularity in recent …

How is it that thoroughly physical material beings such as ourselves can think, dream, feel,
create and understand ideas, theories and concepts? How does mere matter give rise to all …

This paper provides a worked example of using Dynamic Causal Modelling (DCM) and
Parametric Empirical Bayes (PEB) to characterise inter-subject variability in neural circuitry …

The brain's default mode network (DMN) has become closely associated with self-referential
mental activity, particularly in the resting-state. While the DMN is important for such …

This technical note describes some Bayesian procedures for the analysis of group studies
that use nonlinear models at the first (within-subject) level–eg, dynamic causal models–and …

This paper outlines a hierarchical Bayesian framework for interoception,
homeostatic/allostatic control, and meta-cognition that connects fatigue and depression to …

The free energy principle, an influential framework in computational neuroscience and
theoretical neurobiology, starts from the assumption that living systems ensure adaptive …

With the advent of new analysis methods in neuroimaging that involve independent
component analysis (ICA) and dynamic causal modelling (DCM), investigations have …