Not sure about the neuroscience context, but if you have two large ("high-dimensional") vectors of variables that have a population correlation of zero ("independent"), then the dot product of a sample is likely to be close to zero ("orthogonal") due to the law of large numbers.

probably a reference to the curse of dimensionality