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Review
. 2020 Jan;68(1):5-26.
doi: 10.1002/glia.23632. Epub 2019 May 6.

A roadmap to integrate astrocytes into Systems Neuroscience

Affiliations
Review

A roadmap to integrate astrocytes into Systems Neuroscience

Ksenia V Kastanenka et al. Glia. 2020 Jan.

Abstract

Systems neuroscience is still mainly a neuronal field, despite the plethora of evidence supporting the fact that astrocytes modulate local neural circuits, networks, and complex behaviors. In this article, we sought to identify which types of studies are necessary to establish whether astrocytes, beyond their well-documented homeostatic and metabolic functions, perform computations implementing mathematical algorithms that sub-serve coding and higher-brain functions. First, we reviewed Systems-like studies that include astrocytes in order to identify computational operations that these cells may perform, using Ca2+ transients as their encoding language. The analysis suggests that astrocytes may carry out canonical computations in a time scale of subseconds to seconds in sensory processing, neuromodulation, brain state, memory formation, fear, and complex homeostatic reflexes. Next, we propose a list of actions to gain insight into the outstanding question of which variables are encoded by such computations. The application of statistical analyses based on machine learning, such as dimensionality reduction and decoding in the context of complex behaviors, combined with connectomics of astrocyte-neuronal circuits, is, in our view, fundamental undertakings. We also discuss technical and analytical approaches to study neuronal and astrocytic populations simultaneously, and the inclusion of astrocytes in advanced modeling of neural circuits, as well as in theories currently under exploration such as predictive coding and energy-efficient coding. Clarifying the relationship between astrocytic Ca2+ and brain coding may represent a leap forward toward novel approaches in the study of astrocytes in health and disease.

Keywords: astrocytes; decoding; dimensionality reduction; energy-efficient coding; predictive coding.

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Conflict of interest statement

Authors declare no conflict of interest.

Figures

Figure 1.
Figure 1.. Workflow in Systems Neuroscience.
A central problem in Neuroscience is to explain how electrical and chemical signals are used in the brain to represent and process information. The workflow depicts the stages and tools currently used to decipher neuronal codes. In red squares we highlight the elements that are relevant to the study the role of astrocytic Ca2+ in neuronal coding.

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