Abstract
Clinical network neuroscience, the study of brain network topology in neurological and psychiatric diseases, has become a mainstay field within clinical neuroscience. Being a multidisciplinary group of clinical network neuroscience experts based in The Netherlands, we often discuss the current state of the art and possible avenues for future investigations. These discussions revolve around questions like “How do dynamic processes alter the underlying structural network?” and “Can we use network neuroscience for disease classification?” This opinion paper is an incomplete overview of these discussions and expands on ten questions that may potentially advance the field. By no means intended as a review of the current state of the field, it is instead meant as a conversation starter and source of inspiration to others.
Highlights
What are the large-scale network principles governing neuronal communication, cognition, and human behavior? In history, there have been two main views on the neural correlates of behavior
We argue that an empirical understanding of the relation between structural network topology and dynamics of functional connectivity is a fundamental prerequisite for the development of models of brain functioning
As a feasible way forward, we propose to complement studies using single time points and large samples in future case-control studies of network topology with longitudinal studies that are tailored to the patient population at hand
Summary
What are the large-scale network principles governing neuronal communication, cognition, and human behavior? In history, there have been two main views on the neural correlates of behavior. The temporal, timevarying dimension of functional connectivity is a key aspect of communication models and a basic expression of mental processes (Avena-Koenigsberger et al, 2017; Chang & Glover, 2010; Hutchison et al, 2013; O’Neill et al, 2018) This dimension is ignored in most studies that investigate the structure-function relationship in the brain, mainly because of difficulties in measuring and quantifying dynamics (Griffa et al, 2017; Lurie et al, 2018; Vidaurre et al, 2018). The work by Kale and colleagues suggests that as long as directionality is strictly controlled in terms of false positives, structural directionality should not be ignored, even if the directionality estimator is not perfect: The specificity of directional connections has a larger effect on estimated network topology than their sensitivity It remains an open question whether these conclusions hold for functional brain networks. The implications of directional brain networks will likely factor into our understanding of neurological and psychiatric disease
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