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  1. Evaluation Summary:

    The manuscript introduces a new enhancement to the dynamic clamp technique, CapClamp that, analogous to the artificial conductances of standard Dynamic Clamp, allows the experimenter to adjust the somatic time constant by setting a new membrane artificial capacitance independent of any change in input resistance. The technique is shown to have application for studying temporal integration, energetic costs of spiking and bifurcations. The technique is rigorously tested in model and physiological application and is robust when sampling frequency of the feedback (clamp) loop is fast compared to the fastest electrical event in a neuron (usually action potentials), and for vertebrate neurons it should be 20KHz or faster and yet faster for fast spiking neurons.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 and Reviewer #3 agreed to share their names with the authors.)

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  2. Reviewer #1 (Public Review):

    This manuscript describes a new electrophysiological method to manipulate and control the capacitance of the cell membrane. Capacitance is an important property of the membrane of all cells, in particular neurons as applied in this study. Cell membrane capacitance determines how a cell responds to inputs from connected neighbors, and how it generates the activity that the networks it operates in relies on. In this study, the authors have described the theoretical/mathematical basis for the tool they developed, have developed the software necessary to run it (in two separate software platforms), and have tested the accuracy and the limitations of the method. Their results are thorough and clear. The applications that they discuss are interesting and potentially useful for a wide range of experimentalists especially in neuroscience.

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  3. Reviewer #2 (Public Review):

    In the present article, Pfeiffer and colleagues describe a new development of the dynamic-clamp, capacitance clamp, which allows to mimic modifications of capacitance in biological neurons. The authors first demonstrate the feasibility of the technique in a computational neuron model and then apply it to dentate gyrus granule cells, showing that capacitance clamp can be applied to real neurons displaying a complex morphology with multiple compartments and associated capacitance values. While the "classical" dynamic-clamp systems have been used to simulate changes in synaptic inputs, passive and active intrinsic conductances, Pfeiffer and colleagues demonstrate that changes in membrane capacitance, another biophysical parameter influencing neuronal activity, can also be simulated to understand the specific impact of this parameter on neuronal output. As such, this tool is undeniably novel, especially since specific pharmacological manipulations of capacitance are very difficult to achieve. However, as mentioned by the authors, membrane capacitance per unit area does not appear to vary much across neuronal types, species, development, or specific physiological and pathological conditions. The main changes in membrane capacitance reported in the literature are those associated with neuronal growth, in which case it cannot be dissociated from changes in the overall input conductance (passive and active) of the neuron. Considering that membrane capacitance per unit area is essentially constant in all investigated contexts, the main concern about the present study is not on the novelty of the tool but on its potential use to address relevant biological questions.

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  4. Reviewer #3 (Public Review):


    The method is based on sound theoretical footing and clearly explicated.

    The method is rigorously tested in model and experiment and is shown to clearly modify the membrane time constant of the soma of a model cell or living rat dentate gyrus granule cells.

    CapClamp has predictable effects on spike amplitude and the f/I relationship.

    CapClamp is relatively easy and inexpensive to implement (trivially so for current fast Dynamic Clamp rigs.)


    The method requires accurate measurement of the capacitance of the compartment to be clamped (usually this should be the soma). This can be difficult in neurons with complex dendritic architecture.
    The method requires fast clamping feedback; fast compared to the fastest electrical event in a neuron (usually action potentials), and for vertebrate neurons it should be 20KHz or faster and yet faster for fast spiking neurons.

    CapClamp might have limited applicability in many invertebrate neurons where the soma does not place a capacitive load on the integrating segment.

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