Emergent spatial synaptic structure from diffusive plasticity

Sweeney, Yann; Clopath, Claudia

doi:10.1111/ejn.13279

Cited by 7 publications

(1 citation statement)

References 55 publications

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“…It is a perfect example of how a computational model could link the molecular level (calcium concentration) to network dynamics and memory processes. These levels are also linked computationally by the work of Sweeney & Clopath (). They provide a computational approach to a phenomenon, for which the empirical data are clearly not complete, because it is hard to test experimentally in reduced preparations and even harder in vivo.…”

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confidence: 99%

Introduction to the Computational Neuroscience Special Section

Remy

Poirazi

Papoutsi

2017

Eur J of Neuroscience

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Many of us played computer games during our childhood and youth, and some of us still do, while others decided to do something seemingly more useful -like trying to better understand the mammalian brain. Many computer games have a linear progression; individual levels are subdivisions of a larger, more complex world. The practical advantage of having levels is that they divide a game into manageable sections. Upon completion of the easy-to-master entry levels, difficulty and complexity increase and often, prior knowledge and acquired skills are necessary to advance further. A computer game analogy can be applied quite easily to the task of understanding the mammalian brain. Obviously, in this 'game', we enter a multiplayer environment; prior knowledge has been and is acquired by many 'players' in all areas of neuroscience. While physically coexisting within the same structure, each level presents its own themes, rewards and challenges. In the areas of molecular and cellular, cognitive, developmental, behavioural and clinical neuroscience, 'players' progress towards prevailing milestones and research goals. In many cases, it is while we are dealing with the difficulties and specifics that come with our individual entry level that we realize for the first time the complexities and begin to grasp the dimension and complexity of the games' world map. We find out how little we know as individuals and realize how important it is to join forces with other 'players' to crosslink different areas and to link different levels of understanding. This is where theory becomes important. It can provide the quantitative and intellectual framework for linking different areas and different levels of understanding of the nervous system. Models that recapitulate biology on one level can help to generate testable predictions from empirical data and motivate experiments on other levels and in other areas. It can be used, for example, to predict how individual proteins like gap-junction channels may affect the synchrony of networks of many neurons within disease-relevant brain regions such as the basal ganglia. Schwab et al. (2016) use such an approach in this issue and predict that dopamine-regulated gap-junction conductance could be involved in the development of synchrony in the basal ganglia in Parkinson's disease. The spatially localized collective activity of neuronal populations is described by the current-source density. Gratiy et al. (2017) challenge the basic assumptions of the current-source density analysis and show that the extracellular potential is determined not only by the transmembrane currents, but also by extracellular diffusive currents. The authors further estimate the effect of extracellular diffusion in in vivo LFP recordings from the visual cortex and show an effect only at low frequencies. At the single neuron level, empirical data on how ion channels determine the excitability of neurons are robust for some neurons such as the CA1 pyramidal neuron of the hippocampus and detailed biophysical models are already...

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confidence: 99%