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"Investigating interactions between neural populations and their relationship to coding and behavior lies at the core of neuroscience. Covariance-based approaches are commonly used to study interactions in both local and brain-wide, multi-area circuits. The effective directionality of signal flow, in particular, can be inferred from the temporal structure of cross-covariance functions. Recent studies revealed that the directionality of inter-areal interactions can shift rapidly, depending on stimuli and task demands. These findings suggest that experimentally measured covariance metrics reflect not only the underlying synaptic connectivity but also dynamic influences such as inputs from other regions. Understanding how these metrics relate to circuit-level mechanisms remains a challenging task that warrants theoretical approaches.(...)"
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visual cortical areas recurrent neural networks inter-area interactions directionality cross-covariances