Human brains considered as directed graphs I assume that human brains can be considered as directed graphs with neurons as nodes and synapses as edges. I explicitly don't want to consider the weights, the dynamics of neural activity (based on the weights), and the adjustment of weights (learning) - just brains as static unweighted finite directed graphs.
Sensor neurons may be those having in-degree 0, actor neurons may be those having out-degree 0. (0 meaning "essentially 0".)
Considering human brains as finite directed graphs, for each question concerning finite directed graphs there should be an answer with respect to human brains.
Such questions might be:


*

*How long is the shortest path from a sensor to an actor neuron?

*How long is the longest (direct) path from a sensor to an actor neuron?

*What is the (global/local) layer structure (on different levels of granularity)?

*What is the (global/local) cycle structure (on different levels of granularity)?
I find it hard to get answers to such questions considering human brains as directed graphs, because neuro-scientists don't think in terms of graphs, but for example in terms of signal paths and neuro-anatomy. But then - for them - "anything goes", and "everything is connected to everything" - which is not very helpful.

I would be very glad for any reference treating (formally) human
  brains as directed graphs.

 A: There is empirical evidence that the connectivity in the brain has the characteristics of a directed small-world network.
Small-world directed networks in the human brain: Multivariate Granger causality analysis of resting-state fMRI (Wei Lao et al., 2010):

Small-world organization is known to be a robust and consistent
  network architecture, and is a hallmark of the structurally and
  functionally connected human brain. However, it remains unknown if the
  same organization is present in directed influence brain networks
  whose connectivity is inferred by the transfer of information from one
  node to another. Here, we aimed to reveal the network architecture of
  the directed influence brain network using multivariate Granger
  causality analysis and graph theory on resting-state fMRI recordings.
  We found that some regions acted as pivotal hubs, either being
  influenced by or influencing other regions, and thus could be
  considered as information convergence regions. In addition, we
  observed that an exponentially truncated power law fits the
  topological distribution for the degree of total incoming and outgoing
  connectivity. Furthermore, we also found that this directed network
  has a modular structure. More importantly, according to our data, we
  suggest that the human brain directed influence network could have a
  prominent small-world topological property.

More recent studies of the human brain as a directed graph are summarised in section 7.3 of this review article.
A: Human brains as graphs were considered by Kolmogorov and his students. Some results were published in the article О реализации сетей в трехмерном пространстве
А.Н. Колмогоров, Я.М. Барздинь - Проблемы кибернетики, 1967. You can find English translation of this work in the book A. N. Kolmogorov, Selected works - Information theory and the theory of algorithms, page 194.  
