The final state of a complex system is not predictable from the observation of the initial state of few variables. The central nervous system (CNS) is a perfect paradigm of complex biological system, with the intriguing conundrum of its emerging properties (e.g. consciousness, intelligence). During the last decade, the cellular components and the extracellular milieu of the CNS have been studied and isolated without a clear network-based understanding. On the other hand, artificial intelligence and deep learning can predict bio-functional states of the CNS with a strict neuron-centred paradigm, ruling out non-neuronal cells and the extracellular matrix.

The pathology of the CNS is particularly difficult to unravel for similar reasons. Originally, naturally occurring lesions were used to mark cornerstones of CNS functioning but these mechanistic models, although historically essential, have been surpassed. Hence, many pathological conditions, from vascular to inflammatory and neurodegenerative diseases, were considered cell autonomous. The idea that a particular population of affected neurons alone suffices to produce a disease is not valid anymore.

Single cell analyses with both time-gated and space-resolved ‘omics are the new frontier of understanding the biological complexity. However, the amount of information is overwhelming and slight variations of the initial conditions may lead to completely different results. Systems biology approaches together with data analyses and prediction algorithms can aid to decipher the new paradigms of non-cell autonomous functional states, pathophysiology and emergent properties of the CNS.

This research topic welcomes articles focused on systems biology applied to neuroscience pathophysiology. The topic is open for clinical and basic science projects, favouring translational ideas. The topic is inclusive of all fields of neuroscience, as long as the approach is considering the system and not one specific element.

This research topic seeks manuscripts (original research, methods, review and opinion articles) involving but not limited to:
- Novel methods of modelling the CNS
- ‘omic approaches to CNS modelling
- Modelling of neurological diseases, such as on neurodegeneration, inflammation epilepsy and genetic or functional diseases.
- Novel approaches to modelling in neuro-oncology.

Topic Editor Glenn Watson is currently employed by SK Life Science. All other Topic Editors declare no conflicts of interest with this Topic.

Submit your idea

Impact

Frontiers in Systems Biology

Submit your idea

Impact