The ability to simultaneously record the activity from tens to hundreds to thousands of
neurons has allowed us to analyze the computational role of population activity as
opposed to single neuron activity. Recent work on a variety of cortical areas suggests
that neural function may be built upon the activation of population-wide activity patterns,
the neural modes, rather than on the independent modulation of individual neural activity.
These neural modes, the dominant covariation patterns within the neural population,
define a low dimensional neural manifold that captures most of the variance in the
recorded neural activity. What constrains the population dynamics to low dimensional
manifolds? Recent conjectures focus on the role of low rank network connectivity. Is this
hypothesis supported by the statistics of cortical connectomes?