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Articles, Cellular/Molecular

Ionic Current Correlations Underlie the Global Tuning of Large Numbers of Neuronal Activity Attributes

Shunbing Zhao and Jorge Golowasch
Journal of Neuroscience 26 September 2012, 32 (39) 13380-13388; DOI: https://doi.org/10.1523/JNEUROSCI.6500-11.2012
Shunbing Zhao
1Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers University, Newark, New Jersey 07102, and
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Jorge Golowasch
1Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers University, Newark, New Jersey 07102, and
2Department of Mathematical Sciences, New Jersey Institute of Technology, Newark, New Jersey 07102
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  • Figure 1.
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    Figure 1.

    STNS and pyloric network activity. A, Schematic diagram of the STNS. The paired CoGs and OG contain modulatory projection neurons (colored cells) that send axons to the STG through the stomatogastric nerve (stn). Most pyloric neurons are motor neurons that project their axons via individual nerves [pyloric dilator nerve (pdn), pyloric constrictor nerve (pyn) shown] to their target muscles via the lateral ventricular nerve (lvn) or through the medial ventricular nerve (mvn). B, Schematic diagram of the core of the pyloric network. The anterior burster (AB) and both PD neurons are all strongly electrically coupled to each other. LP receives inhibition from AB and inhibits both PD neurons, while it also reciprocally inhibits the PY neurons. C, The triphasic pyloric rhythm was recorded simultaneously from the lvn and pdn and intracellularly from one of the two PD neurons and the LP neuron. The arrows above the lvn recording highlight the onset (on) and termination (off) of the PD and LP neuron bursts. Red lines and arrows point out the other neuronal activity attributes measured in this study. IPSPs in PD are elicited by the action potentials of the LP neuron.

  • Figure 2.
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    Figure 2.

    Measurement and fitting of ionic currents. IA, IHTK, and IH were measured as described in Materials and Methods. A, Shown here is one example of the three leak-subtracted currents measured in a single PD neuron. Command voltages for IA and IHTK were −30 to +20 mV, and for IH −60 to −100 mV, in increments of 10 mV. Superimposed in red are traces from the same cell after 10−7 m TTX was added to the bath showing only minor differences in the currents recorded under these two conditions. B, Current traces from a different PD neuron recorded in normal saline and using the same protocols as in A (black). Superimposed (in red) are fits to the raw current traces with Hodgkin-Huxley-type equations. C, Recordings of each of the two PD neurons in a single preparation. Dynamic clamp currents (bottom trace) were calculated using the voltage recording from PD1 to change GA, GH, and GHTK as indicated, and was injected into both PD1 and PD2 neurons. Note the similarity in the voltage excursions. Top trace is from the lvn.

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    Figure 3.

    Spiking frequency dependence on IA, IHTK, and IH. A total of 125 conductance combinations of these three currents were injected, using dynamic clamp, back into the same PD neurons in which they were originally measured. Left panels show spiking frequency changes (percentage of control level) expressed as a function of the change in ionic conductance levels. Each point is the average ± SD of 11 cells. The gray plane is obtained from a multivariate linear regression analysis with the equation Z = βXAX + βYAY + β0. Right panels show the projections of the planes on the left onto two dimensions, with activity levels represented by the color code shown on the right-hand-side bar. The black dashed lines were calculated as the level set when Z = 0. A, GH vs GHTK. B, GA vs GHTK. C, GA vs GH.

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    Figure 4.

    Relationship among GA, GHTK, and GH define distinct attributes. Coefficients derived from the multivariate linear analysis (Z = βA XA + βH XH + βHTK XHTK + β0) listed in Table 3 define four activity attribute categories (A–D) relative to the correlated variation of the ionic conductances examined. Top shows the conductance relationships that determine these categories; bottom graphically shows the activity attributes in each category. A positive sign means that to maintain constant at attribute value (e.g., at control levels, corresponding to Z = 0), currents must grow together; a negative sign means that attribute invariance requires a current to grow and the other to decrease.

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    Figure 5.

    GH dominates over the potassium conductances in their influence on all activity attributes in PD neurons. Each ionic conductance coefficient (derived from the 4-D multivariate linear analysis) is plotted as a (signed) fraction of the total. Each normalized coefficient was calculated by dividing its raw value by the sum of the absolute values of the three coefficients for each activity attribute (listed on the left). Different in-bar fills are simply to highlight differences in the sign of the coefficients.

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    Figure 6.

    The variances of the activity of the unperturbed and the dynamic clamp-injected PD neuron closely match. The CV of the unperturbed neurons (N = 20) and the mean unexplained variance (1 − R2) of the dynamic clamp-perturbed PD neurons (from multivariate linear analysis, N = 11) for each activity attribute are plotted against each other. Except for deviations observed at low levels of variability, these two sources of variation appear to be closely correlated with each other (ρ = 0.769, p = 0.009, Pearson Product moment correlation test).

Tables

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    Table 1.

    Hodgkin-Huxley equation parameters used in fits shown in Figure 2, and equations in text

    IA (1)IA (2)IHTK (1)IHTK (2)Ih
    Vm−1510−1020−75
    Km−5−15−10−2050
    Vh−40−40−2525
    Kh105120
    Tm-low1100112000
    Tm-hi601005012000
    Th-low30200550
    Th-hi80400550
    Gmax (nS)15004010001200150
    Erev (mV)−80−80−80−80−10
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    Table 2.

    Activity attributes in the unstimulated system

    AttributeAverageSDCV
    Slope (mV/s)0.0940.0480.511
    Spike number5.71.190.209
    Spike frequency (Hz)29.08.90.308
    High bound (mV)−40.44.50.111
    Low bound (mV)−57.15.30.093
    LPon0.390.080.205
    LPoff0.690.080.116
    PDoff0.220.0380.173
    Amplitude (mV)16.82.90.173
    Period (Hz)0.830.270.325
    • Except for period and LP phases, attributes correspond to those of PD neurons (n = 20).

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    Table 3.

    Coefficients from multivariate linear regression analysis (Z = βAXA + βHXH + βHTKXHTK + β0) of each of the 10 activity attributes measured in this study

    AttributeβAβHβHTKR2βA + βH + βHTK
    Slope−0.746***1.826***−1.127***0.764−0.047
    Spike number−0.604***1.224***−0.721***0.596−0.101
    High bound0.138***−0.206***0.170***0.4650.102
    Low bound0.019**−0.329***0.027***0.721−0.283
    LPoff−0.066***0.551***−0.044**0.7050.441
    Spike frequency−0.565***0.781***−0.748***0.503−0.532
    LPon−0.084**0.784***−0.0490.5720.651
    PDoff−0.477***1.430***−0.092*0.6490.861
    Amplitude−0.214***−0.605***−0.304***0.712−1.123
    Period0.033−1.866***0.0700.491−1.763
    • ↵*p < 0.05,

    • ↵**p < 0.01,

    • ↵***p < 0.001. N = 11. R2 from the linear fits indicates the amount of variance explained by these relationships.

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The Journal of Neuroscience: 32 (39)
Journal of Neuroscience
Vol. 32, Issue 39
26 Sep 2012
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Ionic Current Correlations Underlie the Global Tuning of Large Numbers of Neuronal Activity Attributes
Shunbing Zhao, Jorge Golowasch
Journal of Neuroscience 26 September 2012, 32 (39) 13380-13388; DOI: 10.1523/JNEUROSCI.6500-11.2012

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Ionic Current Correlations Underlie the Global Tuning of Large Numbers of Neuronal Activity Attributes
Shunbing Zhao, Jorge Golowasch
Journal of Neuroscience 26 September 2012, 32 (39) 13380-13388; DOI: 10.1523/JNEUROSCI.6500-11.2012
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