  Because local field potentials (LFPs) arise from multiple sources in
different spatial locations, they do not easily reveal coordinated activity
across neural populations on a trial-to-trial basis. As we show here, however,
once disparate source signals are decoupled, their trial-to-trial fluctuations
become more accessible, and cross-population correlations become more apparent.
To decouple sources we introduce a general framework for estimation of current
source densities (CSDs). In this framework, the set of LFPs result from noise
being added to the transform of the CSD by a biophysical forward model, while
the CSD is considered to be the sum of a zero-mean, stationary, spatiotemporal
Gaussian process, having fast and slow components, and a mean function, which
is the sum of multiple time-varying functions distributed across space, each
varying across trials. We derived biophysical forward models relevant to the
data we analyzed. In simulation studies this approach improved identification
of source signals compared to existing CSD estimation methods. Using data
recorded from primate auditory cortex, we analyzed trial-to-trial fluctuations
in both steady-state and task-evoked signals. We found cortical layer-specific
phase coupling between two probes and showed that the same analysis applied
directly to LFPs did not recover these patterns. We also found task-evoked CSDs
to be correlated across probes, at specific cortical depths. Using data from
Neuropixels probes in mouse visual areas, we again found evidence for
depth-specific phase coupling of primary visual area and lateromedial area
based on the CSDs.
