Abstract
We employ toy models to re-examine the notion of causality and its implications in unravelling networks in neuroscience. We conclude that even though multivariate representations of neural dynamic data is indispensable, current popular terminologies for addressing connectivity are insufficiently precise and may even be misleading for fully describing the breadth of information multivariate models now provide. This imposes the need to consider a brand new link centered paradigm of network description where the directed nature of the links plays a central role.
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Baccalá, L.A., Sameshima, K. (2014). Causality and Influentiability: The Need for Distinct Neural Connectivity Concepts. In: Ślȩzak, D., Tan, AH., Peters, J.F., Schwabe, L. (eds) Brain Informatics and Health. BIH 2014. Lecture Notes in Computer Science(), vol 8609. Springer, Cham. https://doi.org/10.1007/978-3-319-09891-3_39
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DOI: https://doi.org/10.1007/978-3-319-09891-3_39
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