But are everyday chemicals hidden causes of birth defects, mental impairment and other bad things?
This way of thinking about diseases prescinds from theorizing about underlying causes of a disease entity in favor of a concentration on observable phenomena, not hidden causes.
The subject's inverse problem is to recognize (estimate) the hidden causes of their sensory signals, under some prior assumptions (the perceptual model) about these causes.
There is a general qualitative relationship between the two quantities, however, because the prior precision of hidden causes within hierarchical perceptual models controls the relative weight of upcoming sensory information and prior (past) beliefs in forming the actual posterior representation.
In these models, hidden causes link hierarchical levels, whereas hidden states link dynamics over time.
In this model, the second-level hidden causes are simply driven by prediction errors and assume a constant frequency.
Here, (f (i ), g (i ) ) are nonlinear functions of hidden states and causes that generate hidden causes for the level below and – at the lowest level – sensory inputs.
In doing so, prediction units at all levels in the hierarchy come to represent the (hidden) causes of sensory input at multiple levels of description.
These hidden causes correspond to the (generalised) motion (that is position, velocity, acceleration, etc). of a target that the oculomotor system is tracking.
Intercurrent medical conditions like constipation, dehydration, electrolyte abnormalities, pneumonia or urinary tract infection, may be hidden causes to psychosis and should be investigated and treated appropriately before starting antipsychotic treatment.
