This challenge has two parts, a simulation and real data.
Simulation: Data are simulated as superposition of bivariate
unidirectional interaction plus additive mixed and non-white noise.
The simulations were done with AR-models with uniformly distributed
input. The challenge is to estimate the causal direction. For each out
of 1000 examples you get +1 point for the correct answer, -10 points
for the wrong answer, and 0 points for no answer.
Real Data: These are high quality EEG data for 10 subjects
for 19 channels. The data contain a prominent peak at around 10 Hz
predominantly in occipital (back) channels.
No ground truth is known.
A submission must be a single 19x19 matrix
corresponding to a causality estimate between all pairs of channels
averaged across subjects. Any submission will be visualized
and, with the agreement of the authors, put on the net for
an open discussion.