Contextual guidance: An integrated theory for astrocytes function in brain circuits and behavior
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Abstract (arXiv)
The participation of astrocytes in brain computation was formally hypothesized in 1992, coinciding with the discovery that these glial cells display a complex form of Ca2+ excitability. This fostered conceptual advances centered on the notion of reciprocal interactions between neurons and astrocytes, which permitted a critical leap forward in uncovering many roles of astrocytes in brain circuits, and signaled the rise of a major new force in neuroscience: that of glial biology. In the past decade, a multitude of unconventional and disparate functions of astrocytes have been documented that are not predicted by these canonical models and that are challenging to piece together into a holistic and parsimonious picture. This highlights a disconnect between the rapidly evolving field of astrocyte biology and the conceptual frameworks guiding it, and emphasizes the need for a careful reconsideration of how we theorize the functional position of astrocytes in brain circuitry. Here, we propose a unifying, highly transferable, data-driven, and computationally-relevant conceptual framework for astrocyte biology, which we coin contextual guidance. It describes astrocytes as contextual gates that decode multiple environmental factors to shape neural circuitry in an adaptive, state-dependent fashion. This paradigm is organically inclusive of all fundamental features of astrocytes, many of which have remained unaccounted for in previous theories. We find that this new concept provides an intuitive and powerful theoretical space to improve our understanding of brain function and computational models thereof across scales because it depicts astrocytes as a hub for circumstantial inputs into relevant specialized circuits that permits adaptive behaviors at the network and organism level.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Nov 2022.
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Citing papers per year: 2023: 1; 2024: 3; 2025: 2.
6 papers.
- 2024Neural timescales from a computational perspectivecited by 3
- 2025Three-Factor Learning in Spiking Neural Networks: An Overview of Methods and Trends from a Machine Learning Perspectivecited by 3
- 2025Intrinsic Goals for Autonomous Agents: Model-Based Exploration in Virtual Zebrafish Predicts Ethological Behavior and Whole-Brain Dynamicscited by 3
- 2024Augmenting learning in neuro-embodied systems through neurobiological first principlescited by 2
- 2023Astrocytes as a mechanism for meta-plasticity and contextually-guided network functioncited by 1
- 2024Synergistic pathways of modulation enable robust task packing within neural dynamicscited by 0
- 2025Intrinsic Goals for Autonomous Agents: Model-Based Exploration in Virtual Zebrafish Predicts Ethological Behavior and Whole-Brain Dynamics30 May 2025
- 2025Three-Factor Learning in Spiking Neural Networks: An Overview of Methods and Trends from a Machine Learning Perspective6 Apr 2025
- 2024Neural timescales from a computational perspective4 Sep 2024
- 2024Synergistic pathways of modulation enable robust task packing within neural dynamics2 Aug 2024
- 2024Augmenting learning in neuro-embodied systems through neurobiological first principles5 Jul 2024
- 2023Astrocytes as a mechanism for meta-plasticity and contextually-guided network function6 Nov 2023