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Temporal synchrony and gamma-to-theta power conversion in the dendrites of CA1 pyramidal neurons

Nature Neuroscience volume 16, pages 1812–1820 (2013)Cite this article

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Abstract

Timing is a crucial aspect of synaptic integration. For pyramidal neurons that integrate thousands of synaptic inputs spread across hundreds of microns, it is thus a challenge to maintain the timing of incoming inputs at the axo-somatic integration site. Here we show that pyramidal neurons in the rodent hippocampus use a gradient of inductance in the form of hyperpolarization-activated cation-nonselective (HCN) channels as an active mechanism to counteract location-dependent temporal differences of dendritic inputs at the soma. Using simultaneous multi-site whole-cell recordings complemented by computational modeling, we find that this intrinsic biophysical mechanism produces temporal synchrony of rhythmic inputs in the theta and gamma frequency ranges across wide regions of the dendritic tree. While gamma and theta oscillations are known to synchronize activity across space in neuronal networks, our results identify a new mechanism by which this synchrony extends to activity within single pyramidal neurons with complex dendritic arbors.

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Figure 1: Theta-frequency oscillatory synchrony in CA1 neurons.
Figure 2: Inputs across the apical dendrite are synchronized at the same frequency.
Figure 3: Propagation of synchronization frequency to the soma and influence of M-channels on oscillatory synchrony.
Figure 4: Oscillatory synchrony extends to oblique dendrites.
Figure 5: Synaptic inputs across the apical dendrite have similar voltage waveform at the soma.
Figure 6: The voltage waveform at soma is composed exclusively of synchronous frequencies.
Figure 7: Gamma frequency synaptic bursts generate theta-frequency components important for oscillatory synchrony.
Figure 8: Oscillatory synchrony in CA1 neurons during the active theta state of the hippocampal network.

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Acknowledgements

We thank R. Chitwood, N. Dembrow, R. Gray and R. Narayanan for helpful discussions during the course of this study. We also thank members of the Johnston laboratory and L.L. Colgin for comments on earlier versions of this manuscript. This work was supported by grant MH 048432 from US National Institutes of Health to D.J.

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Authors and Affiliations

  1. Institute for Neuroscience Graduate Program, The University of Texas at Austin, Austin, Texas, USA

    Sachin P Vaidya

  2. Center for Learning and Memory, The University of Texas at Austin, Austin, Texas, USA

    Sachin P Vaidya & Daniel Johnston

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Contributions

S.P.V. & D.J. designed the experiments, interpreted the results and wrote the manuscript. S.P.V. performed the experiments, computer simulations and analysis of data.

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Correspondence to Daniel Johnston.

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Integrated supplementary information

Supplementary Figure 1 Theta frequency oscillatory synchrony is observed only at the soma

(a) The dendritic voltage response (normalized for amplitude) to a sinusoidal current of 7 Hz/100 pA (---) into the dendrite (red) and at the soma (black). Note that both responses are measured in the dendrite and do not show synchrony of response as is observed at the soma. They show distinct location-dependence differences in both control condition and with ZD7288; (b) Summary data for experiments described as in (a) with response latency defined as the difference in time between current injection at input site and voltage response at 300 mm from soma (in ms). [Control: Dendrite 3.59±1.15 and Soma 9.83±1.33 (n=8; ***, p=1.45e–06, power(1–β)=0.995, paired t-test); ZD7288: Dendrite 14.21±0.79 and Soma 21.23±1.11 (n=6; ***,p=6.34e-05, power(1–β)=0.999, paired t-test).] (c) Impedance phase profile (ZPP) for voltage response at 300 mm measured by 2s/100pA sinusoids of varying frequency when injected at 300 mm (red) and at the soma (black). Note the absence of synchrony (profiles do not intersect); (d) same as (c) but with ZD7288. (e) Summary data for experiments in (c,d) but described as difference in phase between the somatic and the dendritic responses. Negative values suggest dendritic input precedes the somatic input at 300 mm and vice-versa. Scale bars: 10 ms. Dendritic recording locations same as in Fig.1.

Supplementary Figure 2 ZPPsoma comparison between CA1 neuron, the ball-and-stick model and morphologically realistic model

(a) depicts the impedance phase profile at soma (ZPPsoma) for dendritic input at 300 μm (red) and for local somatic input (black) measured from a representative dual whole-cell recording in a CA1 neuron with HCN channels blocked with 20 μM ZD7288. (b) depicts the same measurements of ZPPsoma in normal conditions i.e in the presence of active HCN conductance. (c) and (d) correspond to (a) and (b), respectively, but in the simple ball-and-stick model (inset). Similarly, (e) and (f) correspond to (a) and (b), respectively, but in the morphologically realistic model (inset).

Supplementary Figure 3 Gradient of inductance achieves oscillatory synchrony with less voltage attenuation

(a) & (b) depict the difference in the phase between the dendritic input and the somatic input when measured at the soma. Negative values indicate the appearance of the somatic input before the dendritic input and vice versa. All responses are measured at 7 Hz for an increasing conductance density of leak in (a) and HCN in (b). Values on the side denote the maximum conductance density in S/cm2 in a sigmoidal distribution of the conductances. Note that the dashed line represents perfect synchrony where there is no difference in phase at the soma for input at any location along the dendrite. (c) summarizes the data in (a),(b) for an input at 300 mm (vertical dotted lines). (d) represents the transfer impedance amplitude for the same data points represented in (c).

Supplementary Figure 4 The spatial distribution of HCN channels achieves maximum transfer at synchronization frequency

(a),(b)&(c) depict the difference in the phase between the dendritic input and the somatic input when measured at the soma. Negative values indicate the appearance of the somatic input before the dendritic input and vice versa. All responses are measured at 7 Hz for an increasing conductance density of HCN channels for sigmoidal distribution in (a), linear in (b) and uniform in (c). Values on the side denote the maximum conductance density in S/cm2 in the distal dendritic region of the model. Note that the dashed line represents perfect synchrony where there is no difference in phase at the soma for input at any location along the dendrite. (d) shows the total HCN conductance for a sigmoidal, linear and uniform gradient with maximum conductance density of 10–3 S/cm2, which achieves perfect synchrony in (a),(b) and (c). (e) shows that linear and sigmoidal gradients have significantly higher transfer impedance at synchronization frequency than that in a uniform gradient irrespective of the maximum conductance density of the distribution. (f) shows that transfer impedance amplitude is maximum at synchronization frequency in sigmoidal or linear distribution but not in the unifrom distribution. (e)&(f) describe impedance measurements from 300 mm in the dendrite to the soma.

Supplementary Figure 5 Dependence of oscillatory synchrony on the voltage dependence of activation and kinetics of HCN channels

(a) shows the alterations in the voltage dependence of activation (V1/2) of the HCN conductance tested. (d) describes the scaling of the voltage dependence of activation/deactivation time constants. (b) & (e) depict the difference in the phase between the dendritic input and the somatic input when measured at the soma for a sinusoid of 7 Hz. Negative values indicate the appearance of the somatic input before the dendritic input and vice versa. (c) & (f) depict the influence of these alterations on synchronization frequency. Note that variations in V1/2 significantly altered oscillatory synchrony at 7 Hz in (b) and synchronization frequency in (c) while scaling of the activation/deactivation time constants did not (e,f). HCN conductance in this simulation had a sigmoidal distribution with a maximum conductance value of 1 x 10-3 S/cm2.

Supplementary Figure 6 Voltage dependence of SyncFreq

(a) depicts the voltage dependence of synchronization frequency in a model neuron with maximum HCN conductance of 0.25 x 10–3 S/cm2 (sigmoidal distribution). Note that Synchronization Frequency is restricted to sub-threshold potentials. (b) & (c) show the ZPPsoma at two distinct voltages in (a). Note the presence of oscillatory synchrony at –68 mV in (b) and its absence at –57 mV in (c). (d) shows that the voltage dependence of synchronization frequency is also dependent on the HCN conductance in the model neuron. The numbers depict the HCN conductance in S/cm2.

Supplementary Figure 7 Addition of ZD7288 alters the band-pass filtering of SyncFreqs

(a) & (b) describe the synaptic current injected by the dynamic clamp system at 300 mm to simulate a single synaptic event in (a) and a burst of 5 events at 60 Hz in (b), along with the corresponding voltage waveform recorded at soma in 4 different cells after application of 20 μM ZD7288. (c),(d),(e) ⊕ (f) analyze the frequency components in the corresponding dendritic currents or somatic voltage waveforms for traces depicted in (a) and (b). Note that although the frequency components in the synaptic current input are similar to that in control (Fig. 6), the voltage waveform at the soma is now composed of low-frequency components that do not show synchrony at the soma (Fig. 1d).

Supplementary Figure 8 Accuracy of dynamic clamp over current clamp for high-frequency synaptic inputs

A model cell was injected with synaptic current described either by an alpha-EPSC function in current clamp (red) or by calculating conductance using a single exponential decay model in the dynamic clamp system (black). (a) Conductance amplitude and exponential decay was adjusted in the dynamic clamp system so that both injections produced a similar EPSP waveform. (b), (c) & (d) show that with higher burst frequencies, there are significant differences between current injected by the two systems reflected here in the voltage amplitudes. This is because the dynamic clamp system accounts for the driving force during multiple opening events which is unaccounted for in the current clamp thus injecting a more realistic current waveform.

Supplementary Figure 9 Measurement of impedance phase profile (ZPP) by chirp versus sinusoids

ZPP measurements from 5 different cells are depicted where the solid lines indicate ZPP measured by a chirp stimulus (0 to 15 Hz in 15 s) and ⊕ depicts Impedance phase measured by a 2s sinusoid at a given frequency (0 to 15 Hz; increment 1 Hz). Red indicates measurements of ZPP when the stimulus was injected in the dendrite and black represents ZPP when the stimulus injection was at the soma. Note that no stimulus dependent differences were found in the measurement of ZPP.

Supplementary Figure 10 Time-frequency analysis using continuous wavelet transform

(a)–(d) depicts the time domain signals from Fig. 6 and their scaleogram (Time-Frequency Analysis) obtained by the continuous wavelet transform method. Note that the lower frequencies have a higher spectral resolution but bad temporal resolution and higher frequencies have lower spectral resolution but good temporal resolution. Traces on the right depict the time series average of the scaleogram.

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Vaidya, S., Johnston, D. Temporal synchrony and gamma-to-theta power conversion in the dendrites of CA1 pyramidal neurons. Nat Neurosci 16, 1812–1820 (2013). https://doi.org/10.1038/nn.3562

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