Literature DB >> 31058383

A roadmap to integrate astrocytes into Systems Neuroscience.

Ksenia V Kastanenka1, Rubén Moreno-Bote2,3, Maurizio De Pittà4, Gertrudis Perea5, Abel Eraso-Pichot6, Roser Masgrau6, Kira E Poskanzer7, Elena Galea3,6.   

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.
© 2019 Wiley Periodicals, Inc.

Entities:  

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

Mesh:

Year:  2019        PMID: 31058383      PMCID: PMC6832773          DOI: 10.1002/glia.23632

Source DB:  PubMed          Journal:  Glia        ISSN: 0894-1491            Impact factor:   7.452


  184 in total

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