Predicting responses to inhibitory synaptic input in substantia nigra pars reticulata neurons

Abstract

The changes in firing probability produced by a synaptic input are usually visualized using the post-stimulus time histogram (PSTH). It would be useful if postsynaptic firing patterns could be predicted from patterns of afferent synaptic activation, but attempts to predict the PSTH from synaptic potential waveforms using reasoning based on voltage trajectory and spike threshold have not been successful, especially for inhibitory inputs. We measured PSTHs for substantia nigra pars reticulata (SNr) neurons inhibited by optogenetic stimulation of striato-nigral inputs, or by matching artificial inhibitory conductances applied by dynamic clamp. The PSTH was predicted by a model based on each SNr cell's phase resetting curve (PRC). Optogenetic activation of striato-nigral input or artificial synaptic inhibition produced a PSTH consisting of an initial depression of firing followed by oscillatory increases and decreases repeating at the SNr cell's baseline firing rate. The phase resetting model produced PSTHs closely resembling the cell data, including the primary pause in firing and the oscillation. Key features of the PSTH, including the onset rate and duration of the initial inhibitory phase, and the subsequent increase in firing probability could be explained from the characteristic shape of the SNr cell's PRC. The rate of damping of the late oscillation was explained by the influence of asynchronous phase perturbations producing firing rate jitter and wander. Our results demonstrate the utility of phase resetting models as a general method for predicting firing in spontaneously active neurons, and their value in interpretation of the striato-nigral PSTH.

A computational model explains and predicts substantia nigra pars reticulata responses to pallidal and striatal inputs

“…7). The PRCs that we obtained for hyperpolarized values of E GABA are qualitatively consistent with those found previously for mouse SNr neurons in brain slices with E GABA ≈ −65 mV ( Simmons et al, 2018 ).…”

“…As such, excitatory responses are expected to result from a GABAergic reversal potential ( E GABA ) that is depolarized close to or above the action potential threshold of a given neuron, while biphasic inhibitory-to-excitatory responses are expected to be mediated by a relatively rapid Cl − accumulation and ongoing depolarization of E GABA during the arrival of GABAergic inputs, which may be accelerated in small dendritic compartments. In keeping with this idea, stimulation of striatal inputs to SNr in mouse brain slices at a slower rate of 2Hz yielded consistent initial inhibitory effects rather than the diversity of SNr responses we observed ( Simmons et al, 2018 ). It is also possible that sustained stimulation of GPe and Str terminals may yield slow short-term depression that contributes to gradual changes in SNr firing rates, but this would not explain the biphasic SNr responses.…”

“…The previous work also exploited PRCs for its analysis but was done using simpler models, in the context of weak coupling, and did not consider the unidirectional case. In fact, given the sparsity of synaptic collaterals within SNr Simmons et al (2018 ), we expect that unidirectional connectivity between SNr neurons would be the dominant motif observed. Thus, our model suggests that GPe firing rates could tune the level of synchrony in SNr, with oscillations emerging when E GABA is below the afterhyperpolarization potential.…”

“…Applying this idea to the SNr, E GABA should be depolarized in in vivo relative to in vitro conditions. Values of E GABA measured in the SNr in vitro typically range between −75 mV and −60 mV ( Connelly et al, 2010 ; Higgs and Wilson, 2016 ; Simmons et al, 2018 ) although values as high as −55 mV have been reported ( Giorgi et al, 2007 ) in some conditions. Because spiking in the SNr is asynchronous in control animals ( Deransart et al, 2003 ; Willard et al, 2019 ), our model would predict that E GABA should be close to −55 mV in vivo (Fig.…”

“…Although striatal inputs are less frequent, their impacts would be affected by chloride accumulation, which could be exaggerated in smaller dendritic compartments, and by associated variability of E GABA . Indeed, past studies have reported E GABA values that vary over a relatively wide range, from −80 to −55 mV, in SNr ( Giorgi et al, 2007 ; Connelly et al, 2010 ; Higgs and Wilson, 2016 ; Simmons et al, 2018 ). Moreover, earlier experiments showed excitatory effects along with inhibitory ones from stimulation of SNr-projecting Str neurons in vivo ( Freeze et al, 2013 ), which could relate to chloride regulation as well.…”