Measurement of phase resetting curves using optogenetic barrage stimuli

Highlights

• Optogenetic methods were adapted to measure phase resetting curves (PRCs).

• The PRCs yielded phase models that predicted inter-spike intervals.

• Optogenetic PRC estimation is potentially suitable for in vivo applications.

Abstract

Background

The phase resetting curve (PRC) is a primary measure of a rhythmically firing neuron's responses to synaptic input, quantifying the change in phase of the firing oscillation as a function of the input phase. PRCs provide information about whether neurons will synchronize due to synaptic coupling or shared input. However, PRC estimation has been limited to in vitro preparations where stable intracellular recordings can be obtained and background activity is minimal, and new methods are required for in vivo applications.

New method

We estimated PRCs using dense optogenetic stimuli and extracellular spike recording. Autonomously firing neurons in substantia nigra pars reticulata (SNr) of Thy1-channelrhodopsin 2 (ChR2) transgenic mice were stimulated with random barrages of light pulses, and PRCs were determined using multiple linear regression.

Results

The PRCs obtained were type-I, showing only phase advances in response to depolarizing input, and generally sloped upward from early to late phases. Secondary PRCs, indicating the effect on the subsequent ISI, showed phase delays primarily for stimuli arriving at late phases. Phase models constructed from the optogenetic PRCs accounted for a large fraction of the variance in ISI length and provided a good approximation of the spike-triggered average stimulus.

Comparison with existing methods

Compared to methods based on intracellular current injection, the new method sacrifices some temporal resolution. However, it should be much more widely applicable in vivo, because only extracellular recording and optogenetic stimulation are required.

Conclusions

These results demonstrate PRC estimation using methods suitable for in vivo applications.

Introduction

The phase resetting curve (PRC) measures the input-sensitivity of an oscillating neuron's spike timing, as a function of the oscillation phase at which the input arrives. Thus, the PRC is a primary measure of the input-output relationship of a neuron that fires autonomously, or any neuron operating at an average level of excitation above its rheobase. It has been shown that PRC shapes can predict the tendency of neurons to synchronize or remain asynchronous in response to synaptic or electrical coupling, as well as the strength of synchronization by correlated input (Marella and Ermentrout, 2008, Achuthan and Canavier, 2009, Smeal et al., 2010, Stiefel and Ermentrout, 2016). However, doubt has persisted about the applicability of these findings to in vivo conditions, for two main reasons. First, PRCs have traditionally been measured in neurons firing with great regularity, using single, widely separated stimuli with little resemblance to the barrages of synaptic input thought to occur in vivo. Second, the condition of the cells may be altered by damage during brain slice preparation, deviations from normal physiological temperature or oxygenation, and/or lack of critical neuromodulators.

To address these concerns, it would be valuable to obtain PRCs in vivo. In principle, this could be accomplished by extracellular synaptic stimulation, intracellular current injection, or either direct or synaptic optogenetic stimulation. With any of these methods, it is expected that accurate PRC estimation would be difficult to achieve by the traditional method of low-frequency single-pulse stimulation, because of high levels of ongoing synaptic input producing inter-spike interval (ISI) variability. Even in brain slice preparations, this method requires a long period of data acquisition and generally yields PRCs with a large standard error. However, this limitation has recently been overcome by noise-based methods of PRC estimation, which utilize much higher stimulus densities (Ermentrout et al., 2007, Ota et al., 2009, Wilson et al., 2014). Phase models based on noise-derived PRCs have been shown to predict a large fraction of the observed ISI variance, even with large-amplitude stimuli that one might expect to violate the weak-input assumption of most theoretical studies (Wilson et al., 2014). Because high-density stimuli produce relatively large ISI variance, they should compete better with ongoing synaptic activity, allowing PRC estimation under a wider range of conditions.

In the present study, we extend noise-based PRC estimation to utilize direct optogenetic barrage stimulation of recorded neurons. Because intracellular recording is not required to deliver highly controlled stimuli, extracellular spike recording is sufficient. The method was tested using substantia nigra pars reticulata (SNr) neurons in brain slices from Thy1-channelrhodopsin 2 (ChR2) transgenic mice (Arenkiel et al., 2007), which express ChR2 in multiple brain regions including SNr.