In this scenario, the past may only influence the future via the present.
This means no additional information about the future is gained by finding
out about the past (assuming we know the present). To identify a Markov
blanket in a system wherein we know the conditional dependencies,
we can follow a simple rule. The blanket for a given variable comprises
its parents (the variables it depends on), its children (the variables that
depend on it) and, in some settings, the other parents of its children.

The Markov blanket in figure 3.1 distinguishes states internal to the
adaptive system (i.e., brain activity) from external states of the environment.
Furthermore, it identifies two additional states, labeled sensory states
and active states, which form the blanket that (statistically) separates
internal and external states. Statistical separation means that if we
knew about the active and sensory states, the external states would
offer no additional information about internal states (and vice versa).