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Because local field potentials (LFPs) arise from multiple sources indifferent spatial locations, they do not easily reveal coordinated activityacross neural populations on a trial-to-trial basis. As we show here, however,once disparate source signals are decoupled, their trial-to-trial fluctuationsbecome more accessible, and cross-population correlations become more apparent.To decouple sources we introduce a general framework for estimation of currentsource densities (CSDs). In this framework, the set of LFPs result from noisebeing added to the transform of the CSD by a biophysical forward model, whilethe CSD is considered to be the sum of a zero-mean, stationary, spatiotemporalGaussian process, having fast and slow components, and a mean function, whichis the sum of multiple time-varying functions distributed across space, eachvarying across trials. We derived biophysical forward models relevant to thedata we analyzed. In simulation studies this approach improved identificationof source signals compared to existing CSD estimation methods. Using datarecorded from primate auditory cortex, we analyzed trial-to-trial fluctuationsin both steady-state and task-evoked signals. We found cortical layer-specificphase coupling between two probes and showed that the same analysis applieddirectly to LFPs did not recover these patterns. We also found task-evoked CSDsto be correlated across probes, at specific cortical depths. Using data fromNeuropixels probes in mouse visual areas, we again found evidence fordepth-specific phase coupling of primary visual area and lateromedial areabased on the CSDs.

Cross-population coupling of neural activity based on Gaussian process current source densities