Global Nernstian astrocytic depolarization breaks down during local synaptic input

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1. 

   eLife

   Nov 5, 2026

   eLife Assessment

   The authors use a modeling approach to examine the effects of local and global perturbations on the electrophysiological properties of astrocytes: their modeling results suggest that local ionic changes associated with synaptic activity alter the membrane potential in fine distal processes but not in the soma. The work is valuable because it addresses a long-standing question in the field regarding key electrophysiological properties of astrocytes. The conclusions are convincing, but the manuscript would benefit from providing more details about the assumptions underlying the model and from incorporating more realistic astrocyte morphologies into the simulations.

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2. 

   eLife

   Nov 5, 2026

   Reviewer #1 (Public review):

   Summary:

   Nakatani and De Schutter conduct an in-depth computational investigation of astrocyte electrophysiology. Utilizing a conductance-based NEURON model with realistic astrocyte morphology, the study replicates both in vitro and in vivo experimental protocols to characterize local and global depolarizations of the astrocyte membrane. The findings indicate that bath-applied (global) potassium stimuli induce membrane potential changes that follow the potassium equilibrium potential throughout the cell, whereas localized potassium stimulation disrupts this behavior. In the latter case, the local response is governed by the ratio of local conductances. The authors further analyze the observed electrical compartmentalization to identify which molecular components directly affected by synaptic stimuli - such …

   Reviewer #1 (Public review):

   Summary:

   Nakatani and De Schutter conduct an in-depth computational investigation of astrocyte electrophysiology. Utilizing a conductance-based NEURON model with realistic astrocyte morphology, the study replicates both in vitro and in vivo experimental protocols to characterize local and global depolarizations of the astrocyte membrane. The findings indicate that bath-applied (global) potassium stimuli induce membrane potential changes that follow the potassium equilibrium potential throughout the cell, whereas localized potassium stimulation disrupts this behavior. In the latter case, the local response is governed by the ratio of local conductances. The authors further analyze the observed electrical compartmentalization to identify which molecular components directly affected by synaptic stimuli - such as potassium clearance, glutamate transport, and GABAA and NMDA receptors - could plausibly generate this effect under physiological conditions. The study concludes that perisynaptic astrocyte processes (PAPs) can respond to specific synaptic inputs in an electrically isolated manner, exerting minimal influence on the soma.

   The central prediction - that astrocyte processes can be electrically compartmentalized from the soma under local synaptic stimulation, while bath stimulation produces a globally uniform response - is both interesting and surely significant for understanding and measuring astrocyte electrophysiology. However, the manuscript's incomplete model description and disorganized Results section hinder assessment of how well the conclusions are supported. Addressing these issues could render the model a valuable resource for the community and a useful framework for guiding and interpreting voltage-imaging experiments in astrocytes.

   Strengths:

   (1) The study addresses a timely, long-standing question and may pioneer a multiscale approach to quantifying astrocyte electrophysiology beyond the traditional view of an electrically passive, isopotential glial syncytium. The findings are consistent with recent voltage-imaging evidence of localized depolarization in astrocyte processes.

   (2) A key strength of the study is the use of a state-of-the-art, morphologically realistic compartmental model that captures both somatic and peripheral dynamics. This approach addresses spatial and temporal resolutions that are challenging to achieve experimentally.

   (3) Simulating both in vitro-like (bath perfusion) and in vivo-like (local, synapse-driven) stimulation protocols within a unified framework may explain discrepancies observed between experimental results obtained under these differing conditions.

   (4) The model predictions are benchmarked against experimental voltage-imaging data, and the systematic analysis of individual molecular contributors-including potassium channels, glutamate transporters, and synaptic receptors-yields testable predictions.

   (5) The topic is relevant to a broad and multidisciplinary audience, including researchers in glial biology, synaptic physiology, and computational neuroscience.

   Weaknesses:

   (1) Terminology and clarity

   The manuscript relies heavily on jargon and abbreviations, which impedes readability. The central concept of a "Nernstian" depolarization or response, introduced in the title, is unconventional and not explicitly defined. It appears that "Nernstian" refers to a membrane potential that follows the potassium Nernst potential (EK) of the astrocyte. This terminology is ambiguous, as the analysis is restricted to K+ and does not ensure that the astrocyte response excludes contributions from other ion Nernst potentials.

   Furthermore, "Nernstian" reflects a modeling choice rather than an alternative such as the Goldman-Hodgkin-Katz formalism. Additional terms in the abstract, including "a variety of biochemicals," "astrocyte peripheries," "isolated peripherals," and "empirical" model, are also ambiguous. Because these terms are central to the main claim, they may confuse readers.

   (2) Framing of the research question

   The introduction is brief and does not clearly articulate the research question or the manner in which the study addresses it. The motivation, which should draw on cell anatomy (including the gap-junction-coupled syncytium), molecular composition, and stimulation protocol, is underdeveloped, and the knowledge gap is not explicitly identified.

   (3) Incomplete model description

   Model design, parameters, and stimulation protocols are often not described or justified, and references are missing (e.g., for K2P, TREK1/TWIK1, and the Na+/K+ pumps). In particular:

   a) it is not explained how the three ionic species (Na+, K+, Cl−) needed to account for synaptic currents interact and are modeled in the extracellular and intracellular spaces, nor how they contribute to the astrocyte membrane potential;
   b) the diffusion formulation (Equation 9) neglects any tangential component of diffusion, an approximation that is left unjustified;
   c) gap junctions are modeled as ohmic currents driven by the potential difference between astrocytes, but the network arrangement, location, and distribution of the coupled astrocytes and of the gap junctions in the simulations are not specified;
   d) the analytical results (Equations 46-50) are not obviously derived from Equation 16, and the essential derivation steps are missing;
   e) it is unclear whether and how the voltage indicator ArcLight is modeled when comparing simulated traces with experimental fluorescence data.

   Overall, the simulation setup lacks clarity, which limits reproducibility and impedes evaluation of the study's conclusions.

   (4) Organization and rationale of the results

   The Results are difficult to interpret owing to unclear organization and an ambiguous rationale. The derivation and application of the scale parameter ΓK (Equation 1) are unclear; in particular, its dependence on axial conductance appears inconsistent with the assumption that intracellular diffusion does not influence PAP responses (cf. van Egeraat et al., Biophys. J. 1993).

   (5) Unsupported or missing results

   Several statements are not supported by the data presented: some claims could not be matched to any evidence (e.g., L104-106), results described in the text could not be located in the figures (L159-164), comparisons are reported as "data not shown" (L140-143), and the source of the "realistic ECS sizes" (L191-194) is unclear. The authors do not demonstrate the validity of the extracellular K+ perturbation used to mimic action potentials.

   (6) Presentation of figures

   The figures are often crowded and stylistically inconsistent. Most importantly, in Figures 3, 4, and 6, the rendering of the noisy experimental data obscures the simulation results they are meant to benchmark, making it difficult for readers to assess agreement between model and experiment.

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3. 

   eLife

   Nov 5, 2026

   Reviewer #2 (Public review):

   Summary:

   Nakatani et al. developed a conductance-based, morphologically realistic computational model of an astrocyte soma and its perisynaptic processes (PAPs) to examine how extracellular potassium shapes the astrocytic membrane potential across spatial scales. The model builds on previously published morphological and electrophysiological data, as well as experimental measurements of transporter and ion-channel expression levels. It incorporates the astrocytic potassium channels Kir4.1, the Na⁺/K⁺-ATPase, the K2P leak channels TREK-1 and TWIK-1, and gap-junctional coupling to neighboring processes via connexin-43. Glutamate transporters (GLT-1), NMDA receptors, and GABA_A receptors are also included to examine neurotransmitter-mediated depolarization.

   The authors propose that a compartmental model that …

   Reviewer #2 (Public review):

   Summary:

   Nakatani et al. developed a conductance-based, morphologically realistic computational model of an astrocyte soma and its perisynaptic processes (PAPs) to examine how extracellular potassium shapes the astrocytic membrane potential across spatial scales. The model builds on previously published morphological and electrophysiological data, as well as experimental measurements of transporter and ion-channel expression levels. It incorporates the astrocytic potassium channels Kir4.1, the Na⁺/K⁺-ATPase, the K2P leak channels TREK-1 and TWIK-1, and gap-junctional coupling to neighboring processes via connexin-43. Glutamate transporters (GLT-1), NMDA receptors, and GABA_A receptors are also included to examine neurotransmitter-mediated depolarization.

   The authors propose that a compartmental model that explicitly distinguishes the soma from the PAPs, provides important insights into realistic potassium uptake and the electrophysiological properties of these distinct compartments.

   Strengths:

   (1) Clearing extracellular K⁺ is one of the most fundamental functions of astrocytes. Failures of K⁺ buffering are implicated in epilepsy, spreading depolarization, and several neurodegenerative conditions. Yet how K⁺ handling is divided between perisynaptic processes and the rest of the cell, and how this shapes local membrane potential, remains poorly understood. The study gives a mechanistic account. The soma behaves as a low-resistance K⁺ "sink" with little voltage changes for local K⁺ elevations around the PAPs, while producing much smaller, than expected by simply by Nernst equation. The local membrane potential deviates from E_K because current escapes to the rest of the cell. This framing separates physiological, synapse-scale K⁺ handling from global, pathological K⁺ load.

   (2) The model described here fills an important gap in computational modelling of astrocytes. While computational models are now central to neuroscience, astrocytes and their interactions with neurons remain relatively underrepresented in mainstream computational modeling. Existing models mostly treat either whole-cell K⁺ buffering or the isolated perisynaptic compartment. This is novel in that it connects the two within one framework and provides a tool to address how astrocytes integrate local and global signals.

   (3) Including realistic morphology shows that spatial heterogeneity matters. A key conceptual strength is that the model does not treat the astrocyte as a single, well-mixed, isopotential compartment. Using an EM-informed morphology with perisynaptic astrocytic processes, it shows that stimulus location and spatial extent shape the membrane response. Fine processes, constricted segments, and local conductance ratios generate responses that cannot be predicted from whole-cell properties alone. These questions are difficult to address experimentally because fine processes are below the resolution of conventional electrophysiology, and somatic recordings are limited by space-clamping. An in silico approach is therefore especially valuable, as it allows controlled manipulation of individual variables, such as stimulus location, channel density, and extracellular volume, that cannot be varied independently in tissue.

   (4) It is built using standard, open tools, and therefore the model can be extended with ease by future studies. The model is implemented in NEURON, the most widely used simulator for biophysically detailed cells, with mechanisms written in NMODL and driven through Python. It also uses a previously published astrocyte morphology. Parameters are listed, and the authors state that the model files are in a repository. Together, these make the model accessible and reproducible if the repository link is also provided.

   (5) The model is anchored to experimental data. Kir4.1 and K2P leak conductance were fitted to experimental current-voltage data (Figure S2), and other channel parameters were constrained by the literature. Notably, the authors avoided channel formulations with built-in mechanisms that fix the resting potential, which are common in earlier astrocyte models. The resting potential and K⁺ responses therefore emerge from the conductance rather than being imposed. The model also reproduces established whole-cell behavior, including Nernstian responses to bath K⁺ application, before being used for new predictions.

   (6) The study tests several candidate mechanisms for peripheral depolarization within one framework and offers a way to reconcile conflicting results: K⁺ through Kir4.1, GLT-1, Na⁺/K⁺-ATPase, K⁺/glutamate spillover, and astrocytic GABA_A and NMDA receptors, all of which in principle can produce responses of the observed depolarization under various conditions. The model therefore offers a biophysical explanation for discrepancies in the astrocyte literature.

   (7) The work makes several testable predictions:
   a) the local [K⁺]o required for a given PAP depolarization;
   b) local depolarization depends on the spatial extent of activation;
   c) somatic recordings would not detect PAP depolarizations.

   Weaknesses:

   (1) The Nernst equation itself does not appear to break down; local E_K should still follow it. Rather, the membrane potential deviates from E_K because low-resistance electrical coupling allows current to spread to the rest of the cell. I suggest rewording this statement for accuracy.

   (2) The Methods mention an uploaded repository, but no link is provided. The authors should include a public link and deposit the model in ModelDB or a comparable repository.

   (3) The deployed morphology is hippocampal, not cortical. But the paper's conclusions are for cortical somatosensory astrocytes based on morphological similarity. That deserves additional explanation, especially since PAP geometry is central to the conclusions.

   (4) Astrocytic NMDA receptors best fit the observed depolarizations. However, because the experiments in Armbruster et al. were performed in the presence of APV, an NMDA receptor antagonist, the authors suggest that the responses may involve APV-insensitive NMDA receptor subunits. This explanation would be stronger if supported by evidence that these subunits are expressed in cortical astrocyte PAPs.

   (5) For activation of GABA_A receptors on astrocyte PAPs, the source of GABA is unclear, since the stimulated ascending axons are glutamatergic. The model shows these receptors could explain the data, not how they might be activated. This deserves an explanation.

   (6) I also recommend adding a discussion paragraph on the functional implications of heterogeneous astrocytic control of potassium homeostasis. Do the results suggest that astrocytes efficiently buffer K⁺ under normal conditions but fail during widespread K⁺ accumulation?

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4. 

   eLife

   Nov 5, 2026

   Reviewer #3 (Public review):

   Summary:

   This study uses computational modeling to examine how local synaptic activity influences astrocyte membrane potential and, in particular, whether the classical Nernstian relationship between extracellular potassium concentration and astrocyte membrane potential is maintained throughout the astrocyte. The authors focus on the possibility that local ionic changes associated with synaptic activity produce membrane potential responses in fine astrocytic processes that differ from those predicted by a global Nernstian relationship. The study addresses an important and longstanding question in astrocyte physiology and provides a potentially useful computational framework for examining how cellular morphology, membrane conductances, and local synaptic inputs shape astrocyte membrane potential. The central …

   Reviewer #3 (Public review):

   Summary:

   This study uses computational modeling to examine how local synaptic activity influences astrocyte membrane potential and, in particular, whether the classical Nernstian relationship between extracellular potassium concentration and astrocyte membrane potential is maintained throughout the astrocyte. The authors focus on the possibility that local ionic changes associated with synaptic activity produce membrane potential responses in fine astrocytic processes that differ from those predicted by a global Nernstian relationship. The study addresses an important and longstanding question in astrocyte physiology and provides a potentially useful computational framework for examining how cellular morphology, membrane conductances, and local synaptic inputs shape astrocyte membrane potential. The central conclusion is that Nernstian behavior can break down during local synaptic input, particularly in fine astrocytic processes. The modeling framework could therefore be useful for understanding how the spatial organization of astrocytes influences their responses to local neuronal activity. However, the strength and generality of this conclusion depend on several biological assumptions that are not sufficiently considered in the current model or discussion.

   Strengths:

   This computational modeling addresses a longstanding question in astrocyte physiology dating back to the 1960s: whether astrocyte membrane potential (VM) follows the Nernstian prediction in response to changes in extracellular K+ concentration ([K+]e). Significant recent progress in astrocyte studies has provided a renewed opportunity to revisit this question. In this regard, the effort to develop a conductance-based NEURON model that incorporates understanding of astrocyte structure and physiology is highly valuable. The model has also shown the potential to simulate how changes in astrocyte membrane Na+, Ca2+, and Cl+ permeabilities, resulting from synaptic inputs, could alter the relative K+ permeability, and therefore the Nernstian behavior of astrocyte VM at different subregions of astrocytes. These questions are important to astrocyte physiology and remain technically challenging to experimentally evaluate. However, several concerns about the omission of recent studies on astrocyte structure and function from the model and the physiological interpretation of the Nernstian behavior of astrocytes need to be addressed before the conclusions can be adequately supported.

   Weaknesses:

   (1) The premise of the modeling:
   The cellular context should be clearly stated. The model is intended to simulate rodent grey matter cortical protoplasmic astrocytes, but not white matter fibrous astrocytes or other specialized astrocyte populations, which differ morphologically and, to some extent, functionally.

   (2) The architecture of astrocytes:
   This model can be refined by incorporating recent advances in our understanding of astrocyte morphology (PMID: 35283239, PMID: 31550514). For example, (a) the branching pattern of astrocytic processes, particularly the terminal processes (or leaflets), which is a key element of the model; (b) the location of synapses within an astrocytic domain. Specifically, synapses can make contact with virtually every structural component of an astrocyte, from the soma to different levels of processes, including endfeet contacting blood vessels. This anatomical evidence is in sharp contrast to the prevailing perisynaptic astrocytic process (PAP) concept adopted in the modeling; and (c) the existence of a large quantity of reflective astrocytic processes that loop back and form gap junctional coupling at their stemming points that wrap around bundles of axons or large dendrites, forming a scaffold-like architecture (also see PMID:32312988 in your reference list). This may create regions of strong local astrocyte VM response to activity-dependent elevations of [K+]e, which could be an important feature to consider in the modeling.

   (3) Astrocyte membrane potential is not an autonomous feature of individual astrocytes:
   If the goal is to simulate astrocyte VM, astrocyte syncytial coupling cannot be ignored. Specifically, the very low astrocyte-to-astrocyte pathway resistance (4.2 MΩ) provides strong electrical coupling that equalizes the VM of astrocytes within a syncytium to a uniform level, a property termed astrocyte syncytial isopotentiality (PMID: 26435164; PMID: 30277762). Experimental studies have demonstrated that coupling among 7-9 astrocytes is sufficient to maintain this isopotential state. Thus, the VM of an individual astrocyte is not determined solely by its own K+ conductance and transmembrane K+ gradient, but rather the result of the electrotonic spatiotemporal summation of voltage across the syncytium. A realistic model that seeks to predict astrocyte VM should incorporate syncytial coupling as a fundamental component.

   (4) The historical debate about the Nernstian behavior of astrocyte VM in response to [K+]e:
   The authors should acknowledge the longstanding debate over the Nernstian behavior of glial VM in response to changes in [K+]e. This relationship was first described in the seminal neuroglia studies of Kuffler and colleagues in 1966, using optic nerve neuroglia, which are likely equivalent to fibrous astrocytes in rodent white matter. They reported a slope of ~58 mV per 10-fold change in [K+]e (PMID: 5966434). This interpretation was subsequently challenged by a series of in vivo studies of neuroglia VM in cortical grey matter, including Pape and Katzman (1972; PMID: 5016004), Ransom and Goldring (1973; PMID: 4805015), and Futamachi and Pedley (1976; PMID: 1276917). Importantly, the Futamachi study provided early in vivo evidence consistent with syncytial isopotentiality, although the existence of the astrocyte syncytium could not be demonstrated experimentally until the later work of Ransom and colleagues in 1981 (PMID: 7248773). This historical literature should be introduced in the Introduction to establish the significance of the present modeling work.

   (5) Astrocyte syncytial isopotentiality:
   The authors should consider that syncytial isopotentiality is a system-wide feature of both grey and white matter astrocytes. At minimum, this means that somatic astrocyte VM recordings are not consistent with a simple Nernstian prediction of VM in response to changes in [K+]e. Therefore, a model of astrocyte VM should account for syncytial coupling rather than treating VM as a property determined by individual astrocytes.

   (6) Distinguish K+ Nernstian behavior from multi-ion permeability and transporter-mediated flux:
   Conceptually, the high and near-exclusive K+ permeability of the resting astrocyte VM provides the basis for applying the Nernst equation to describe VM. In the present, Na+ and Ca2+ permeabilities are also introduced without a clear distinction between the conditions under which a Nernst equation remains applicable and those in which it does not. The authors should clearly define Nernstian behavior as referring specifically to K+ permeability. When the Na+ and Ca2+ permeabilities, resulting from the activation of AMPA/NMDA receptors, are involved in astrocyte across-membrane ionic activities, the VM follows the GHK prediction. Additionally, the model includes Na+-dependent transporters, which do not represent channel-mediated permeability. The authors should therefore distinguish channel-mediated ionic permeability from transport-mediated ionic flux when describing and modeling changes in astrocyte VM.

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5. 

   eLife

   Nov 5, 2026

   Author response:

   We thank the reviewers for the overall positive review that declares our results convincing. We will revise the paper to improve the presentation of the model and results as suggested by the reviewers. The revision will be accompanied by a more detailed response.

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6. 

   Version published to 10.7554/elife.112921.1 on eLife

   Nov 5, 2026
7. 

   Version published to 10.7554/elife.112921 on eLife

   Nov 5, 2026
8. 

   Version published to 10.64898/2026.06.23.734112v2 on bioRxiv

   Aug 12, 2026
9. 

   Version published to 10.64898/2026.06.23.734112v1 on bioRxiv

   Jun 29, 2026