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Passive and active shaping of unitary responses from associational/commissural and perforant path synapses in hippocampal CA3 pyramidal cells

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Abstract

Although associational/commissural (A/C) and perforant path (PP) inputs to CA3b pyramidal cells play a central role in hippocampal mnemonic functions, the active and passive processes that shape A/C and PP AMPA and NMDA receptor-mediated unitary EPSP/EPSC (AMPA and NMDA uEPSP/uEPSC) have not been fully characterized yet. Here we find no differences in somatic amplitude between A/C and PP for either AMPA or NMDA uEPSPs. However, larger AMPA uEPSCs were evoked from proximal than from distal A/C or PP. Given the space-clamp constraints in CA3 pyramidal cells, these voltage clamp data suggest that the location-independence of A/C and PP AMPA uEPSP amplitudes is achieved in part through the activation of voltage dependent conductances at or near the soma. Moreover, similarity in uEPSC amplitudes for distal A/C and PP points to the additional participation of unclamped active conductances. Indeed, the pharmacological blockade of voltage-dependent conductances eliminates the location-independence of these inputs. In contrast, the location-independence of A/C and PP NMDA uEPSP/uEPSC amplitudes is maintained across all conditions indicating that propagation is not affected by active membrane processes. The location-independence for A/C uEPSP amplitudes may be relevant in the recruitment of CA3 pyramidal cells by other CA3 pyramidal cells. These data also suggest that PP excitation represents a significant input to CA3 pyramidal cells. Implication of the passive data on local synaptic properties is further investigated in the companion paper with a detailed computational model.

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Abbreviations

ACSF:

Artificial cerebrospinal fluid

AMPA and NMDA uEPSP/uEPSC:

AMPA and NMDA receptor-mediated unitary EPSP/EPSC

A/C:

Associational/commissural

AR:

Adaptation ratio

CC:

Current clamp

CNQX:

6-cyano-7-nitroquinoxaline-2, 3-dione

CV:

Coefficient of variation

D-APV:

D(-)-2-amino-5-phosphonopentanoic acid

DIC:

Differential interference contrast

EC:

Entorhinal cortex

HHW:

Half-height width

Ih :

Hyperpolarization-activated current

KA :

A-type potassium ion channels

MF:

Mossy fiber

PP:

Perforant-path

PV:

Peak value

RN :

Input resistance

str.:

Stratum

TTP:

Time-to-peak

VC:

Voltage clamp

VDC:

Voltage-dependent conductances

Vm :

Membrane voltage

Vh :

Holding membrane voltage

μ:

Mean Gaussian value

τm :

Membrane time constant

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Acknowledgements

This work was supported by NIH Grants AG025633, NS39600, and NS24288. We thank John Cavaretta for technical assistance and Warren Anderson for help in some steps of the analysis.

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Correspondence to Giorgio A. Ascoli.

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Action Editor: Alain Destexhe

Author contributions

All of the authors have contributed to this study. GAA and GB conceived the conceptual framework of the study. TPR, JLB, MF, GAA, and GB conceived and designed the experiments. Experiments were performed by TPR at University of Pittsburgh. JLB, MF, TPR, IS, GAA, GB analyzed and interpreted the data. TPR, JLB, MF, IS, GAA, and GB drafted the article.

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Appendix

Appendix

Detailed description of sweep categorization

The data sweep parameter extraction method is denoted here in ‘single quotes’, whose values are reported in Table 1. Unless otherwise indicated, times are relative to the stimulus artifact and response values are always treated as positive even for EPSCs. Sweeps showing a trend slope, either positive or negative, within the ‘pre-stimulation test window’ preceding the stimulus artifact with a magnitude greater than the ‘maximum trend’ were rejected from further processing, as were sweeps showing smoothed values in the ‘pre-stimulation test window’ larger than the ‘minimum peak value’. Sweeps with peak values greater than the “minimum peak” value but estimated latencies lower than the minimum “allowed latency” were similarly rejected from further processing. Single-peak responses were those having a dual-exponential fit with error no greater than the ‘maximum fit error’ and estimated latency, peak time, and HHW within the limits provided by ‘allowed latency’, ‘allowed peak time’, and ‘maximum half-height width’, respectively. Furthermore, single-peak responses should have peak values greater than or equal to the ‘minimum peak value’. Finally, single-peak responses should also have no local peaks larger than the main peak prior to the half-height crossing point, even if the times of such peaks are outside the range of ‘allowed peak time’. Multi-peak sweeps were those not identified as single-peak responses but having peak values in excess of the ‘minimum peak value’ within ‘allowed peak time’ limits and having latencies no greater than the maximum ‘allowed latency’. Sweeps were categorized as failures when the estimated latency was larger than the maximum ‘allowed latency’ and no peaks with values larger than the ‘minimum peak value’ were found prior to the end of the ‘allowed latency’ interval, provided that the minimum-to-maximum range of response values in the time interval from the ‘minimum peak time’ to the maximum ‘allowed latency’ was less than the ‘minimum peak value’. Sweeps not otherwise categorized and meeting the minimum-to-maximum range test for the latency interval were also categorized as failures provided that no peaks were found with values larger than the ‘minimum peak value’. All other cases were categorized as undetermined. See Supplementary Figure 3 for a flowchart of this categorization procedure.

Mathematical details of fitting procedure

The decay time constant was estimated using a closed-form solution to a method described by Richardson and Silberberg (2008) that minimizes the total variance of a perturbation in an exponentially decaying system. Briefly, the method used here models a decaying response as:

$$ \dot{y} = - {{y} \left/ {{\tau + \varepsilon }} \right.} $$

where y is the response value (e.g. EPSP) over time, τ the decay time constant, and ε a random noise source. For values of y over a given time interval, a value of τ is sought that minimizes the total variance of the noise term. The optimal value for τ is found as:

$$ \tau = \frac{2}{{y_0^2 - y_1^2}}\int_{{\,{t_0}}}^{{ {t_1}}} {{y^2}dt} $$

where y is the EPSP or EPSC value relative to rest, t 0 is the start time of the interval over which the estimate is made, t 1 is the end time, y 0 is the value of y at t 0, and y 1 is the value at t 1.

Single-peak responses were identified by fitting the smoothed response to a dual-exponential of the form:

$$ \begin{array}{*{20}l}{{y(t) = y_{{rest}} + a{\left[ {\exp {\left( { - \frac{{t - b}}{{\tau _{2} }}} \right)} - \exp {\left( { - \frac{{t - b}}{{\tau _{1} }}} \right)}} \right]} + \varepsilon _{{noise}} {\left( t \right)}{\text{if}}t > b} \hfill} \\ {{y{\left( t \right)} = y_{{rest}} + \varepsilon _{{noise}} {\left( t \right)}{\text{otherwise,}}} \hfill} \\ \end{array} $$

where y(t) is the response value at a given time, y rest is the value of the voltage or current at rest, t is time relative to the stimulus artifact, b is latency, and τ1 and τ2 are the rising and falling time constants. The fitting procedures determines values for y rest , a, b, τ1 and τ2 to minimize the error measure \( {{{{\rm var} \left( {{\varepsilon_{{noise}}}} \right)}} \left/ {{{\rm var} (y)}} \right.} \) for t values over an interval beginning with the pre-stimulation test interval up through a minimum fitting window interval (Table 1) from the peak of the response or up through the trailing half-height crossing, whichever comes last. Fitting was done using the R functions for the Nelder-Mead simplex method except in cases where convergence is not achieved, in which case a quasi-Newton method is also used. To better fit the rising portion of EPSP, an assumed membrane time constant (Table 1) was included in the fitted model in the form of an exponential decay kernel that is convolved with the dual exponential response.

Two latency estimates were derived, one directly from the sweep data and the other from the fitting procedure. For EPSP, the value derived directly from sweep data was more reliable and thus was used in the categorization process, whereas for EPSC, the value derived from the fitting procedure was used. In cases where one of the latency estimates could not be determined, the other was substituted for the purpose of sweep categorizations. Sweeps where no reliable latency estimate was derived were categorized as undetermined.

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Perez-Rosello, T., Baker, J.L., Ferrante, M. et al. Passive and active shaping of unitary responses from associational/commissural and perforant path synapses in hippocampal CA3 pyramidal cells. J Comput Neurosci 31, 159–182 (2011). https://doi.org/10.1007/s10827-010-0303-y

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  • DOI: https://doi.org/10.1007/s10827-010-0303-y

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