A dynamic clamp protocol to artificially modify cell capacitance
- Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Germany
- Bernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin, Germany
- Institute for Integrative Neuroanatomy, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Germany
- Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Germany
Figures
Figure 1 with 1 supplement
Adding or removing artificial capacitance via the CapClamp.
(A) Physically, membrane capacitance varies with surface area, thickness and lipid composition (B) Virtual capacitance modification via the CapClamp is a form of dynamic clamp, a fast feedback loop …
Figure 1—figure supplement 1
Impedance analysis of an RC circuit coupled to the capacitance clamp.
(A) Injection of an oscillating current at 300 Hz (left) and at 3 kHz (right) to a passive cell (RC-circuit) with voltage responses clamped at an increased (middle) and a decreased capacitance …
Figure 2
Simulation of the capacitance clamp in a conductance based neuron model.
(A) Neurons coupled to the CapClamp are compared with control neurons with an altered capacitance (depicted as a difference in membrane area). (B) Spiking at 0.6-fold decreased (90 pF), original …
Figure 3
Clamping capacitance in rat dentate gyrus granule cells (DGGCs).
(A) Morphology of a DGGC (left) and response to a hyperpolarizing current injected at the soma, fit via a sum of exponential terms with a slow , v0 and a fast component , v1 (middle), which can …
Figure 4
Repetitive spiking and action potential shapes in DGGCs clamped at different capacitances.
(A) Spiking at decreased 0.6-fold (left), original (middle) and increased 3-fold (right) near capacitance . (B) Spike shapes (top) and capacitance clamp currents (bottom) for increasing …
Figure 5
Applying the capacitance clamp to study neuronal signaling and physiology.
Temporal integration: (A) Brief current pulses of 3ms length with interstimulus intervals of 5ms and 50ms (top) and voltage responses of an exemplary DGGC at a decreased (12 pF) and an increased (62 …
Appendix 1—figure 1
Analysis of the capacitance clamp as a discrete feedback filter.
(A) Block diagram of the coupled system: RC circuit with original capacitance Cc and capacitance clamp feedback current. (B) Block diagram of the target system: RC circuit with target capacitance …
Tables
Table 1
Spike shape and firing frequency in a biophysical neuron model at 60 pA as well as f-I curve gain and local gain reduction for a decreased, the original and an increased capacitance, comparing simulations of an actually altered capacitance with the CapClamp.
Values are shown as actual(clamped).
| C (pF) | f (Hz) | (mV) | (ms) | AHP (mV) | Gain (Hz/) | ΔGain (Hz/ per 10 pF) |
|---|---|---|---|---|---|---|
| decreased 90 | 34.9 (34.3) | 45.7 (55.0) | 0.30 (0.30) | –77.8 (-79.7) | 6.5 (6.5) | –0.67 (-0.67) |
| original 150 | 22.1 | 33.9 | 0.39 | –71.5 | 3.8 | –0.22 |
| increased 210 | 17.8 (18.9) | 21.4 (20.1) | 0.48 (0.48) | –66.0 (-64.7) | 2.9 (2.9) | –0.11 (-0.10) |
Key resources table
| Reagent type (species) or resource | Designation | Source or reference | Identifiers | Additional information |
|---|---|---|---|---|
| Strain, strain background (Rattus norvegicus, male and female) | Wistar Rat (wild type) | Wistar Institute of Philadelphia, Pennsylvania | ||
| Peptide, recombinant protein | Avidin conjugated AlexaFluor-647 | Thermo Fisher Scientific | RRID:AB_2336066 | |
| Software, algorithm | Fiji distribution of ImageJ software | imagej.net | RRID:SCR_003070 | |
| Software, algorithm | Neutube | neutracing.com | https://doi.org/10.1523/ENEURO.0049-14.2014 | |
| Software, algorithm | RELACS | relacs. sourceforge.net | RRID:SCR_017280 | |
| Software, algorithm | RELACS CapClamp | This paper | https://doi.org/10.5281/zenodo.6322768 | Capacitance clamp code for RELACS, see "Data and software availability" in Appendix 1 |
| Software, algorithm | RTXI | rtxi.org | https://doi.org/10.1371/journal.pcbi.1005430 | |
| Software, algorithm | RTXI CapClamp | This paper | https://doi.org/10.5281/zenodo.5553946 | Capacitance clamp code for RTXI, see "Data and software availability" in Appendix 1 |
| Software, algorithm | Brian 2 | brian-team/ brian2 | https://doi.org/10.7554/eLife.47314 |
Table 2
Multi-exponential fit and corresponding circuit parameters in the recorded dentate gyrus granule cells (N = 18) and a multicompartment model based on a reconstructed DGGC morphology (see "Multicompartment model of a dentate gyrus granule cell" in Methods).
| DGGCs (mean ± std) | Multicomp. model | |
|---|---|---|
| Exp. fit | ||
| 15.1±4.8 ms | 15.1 ms | |
| R0 | 127.1±44.6 MΩ | 119.2 MΩ |
| 0.77±0.24 ms | 0.18 ms | |
| R1 | 34.5±14.7 MΩ | 12.3 MΩ |
| Circuit | ||
| 21.0±9.4 pF | 13.0 pF | |
| 854.2±394.0 MΩ | 1158.0 MΩ | |
| 52.5±19.8 MΩ | 15.5 MΩ | |
| 105.8±33.0 pF | 113.7 pF | |
| 155.5±59.9 MΩ | 132.8 MΩ |
Appendix 1—table 1
Comparison of online and offline fits to charging curves in the recorded dentate gyrus granule cells (N = 18).
| Online fit (mean ± std) | Offline fit (mean ± std) | |
|---|---|---|
| Two comp. | ||
| 14.9±4.8 ms | 15.1±4.8 ms | |
| R0 | 136.9±47.5 MΩ | 127.1±44.6 MΩ |
| 0.41±0.23 ms | 0.77±0.24 ms | |
| R1 | 25.1±14.1 MΩ | 34.5±14.7 MΩ |
| Circuit | ||
| 14.9±4.7 pF | 21.0±9.4 pF | |
| 1106.3±519.3 MΩ | 854.2±394.0 MΩ | |
| 34.9±19.9 MΩ | 52.5±19.8 MΩ | |
| 99.1±33.7 pF | 105.8±33.0 pF | |
| 159.6±58.1 MΩ | 155.5±59.9 MΩ |
