Contrast gain control occurs independently of both parvalbumin-positive interneuron activity and shunting inhibition in auditory cortex

Abstract

Contrast gain control is the systematic adjustment of neuronal gain in response to the contrast of sensory input. It is widely observed in sensory cortical areas and has been proposed to be a canonical neuronal computation. Here, we investigated whether shunting inhibition from parvalbumin-positive interneurons-a mechanism involved in gain control in visual cortex-also underlies contrast gain control in auditory cortex. First, we performed extracellular recordings in the auditory cortex of anesthetized male mice and optogenetically manipulated the activity of parvalbumin-positive interneurons while varying the contrast of the sensory input. We found that both activation and suppression of parvalbumin interneuron activity altered the overall gain of cortical neurons. However, despite these changes in overall gain, we found that manipulating parvalbumin interneuron activity did not alter the strength of contrast gain control in auditory cortex. Furthermore, parvalbumin-positive interneurons did not show increases in activity in response to high-contrast stimulation, which would be expected if they drive contrast gain control. Finally, we performed in vivo whole-cell recordings in auditory cortical neurons during high- and low-contrast stimulation and found that no increase in membrane conductance was observed during high-contrast stimulation. Taken together, these findings indicate that while parvalbumin-positive interneuron activity modulates the overall gain of auditory cortical responses, other mechanisms are primarily responsible for contrast gain control in this cortical area.NEW & NOTEWORTHY We investigated whether contrast gain control is mediated by shunting inhibition from parvalbumin-positive interneurons in auditory cortex. We performed extracellular and intracellular recordings in mouse auditory cortex while presenting sensory stimuli with varying contrasts and manipulated parvalbumin-positive interneuron activity using optogenetics. We show that while parvalbumin-positive interneuron activity modulates the gain of cortical responses, this activity is not the primary mechanism for contrast gain control in auditory cortex.

Keywords: auditory cortex; circuit mechanisms; contrast gain control; parvalbumin-positive interneurons; shunting inhibition.

Fig. 1.

Compensation for access resistance. A: we injected a series of 40-pA current pulses into each neuron before each sweep. This allowed us to estimate both R_access and R_input from the change in V_m. Cycles of current injection that included an up state (red traces) were identified by crossing a threshold corresponding to the mean of the V_m distribution. These traces were excluded and the remaining traces (blue) were used to compute the mean V_m response to the current pulses. B: the mean V_m (blue trace) consists of fast and slow exponential components that correspond to R_access and R_input, respectively. A double exponential model was fitted to the mean V_m response to quantify the contribution of R_access so that it could subsequently be compensated for. C: each fit showed a clear minimum in the error function for a range of resistance, R_access, and time constant, τ_access, values. D: estimate of the true V_m in response to I_inj following compensation for R_access. E: an estimate of the remaining R_access following compensation was also obtained for each neuron by quantifying the change in spike threshold under different levels of I_inj. Spikes before (black) and after (blue) correction for R_access using these two methods. F: a linear fit (black line) to mean spike threshold for different levels of I_inj (black circles, standard errors indicated by black lines) can be used to quantify R_access. Error bars appear as a single line due to the minimal variation in threshold between spikes. After correction for R_access, spike threshold is impacted far less by I_inj (blue), demonstrating that R_access has successfully been compensated for. I_inj, injected current; R_access, access resistance; R_input, input resistance; V_m, membrane potential.

Fig. 2.

Input conductance estimation. A: mean V_m recorded for four different levels of current injection during dynamic random chord (DRC) and noise stimulation. Input conductance, G, was estimated at each time point in the stimulus. The broken line indicates a single time point 100 ms into the stimulus for which we estimated a single value of G. B: open circles indicate the V_m recorded at this time point for 25 stimulus repetitions for the four levels of current injection. Blue triangles indicate mean V_m values plotted in A. G could be estimated at this time point from these responses by examining the relationship between injected current and recorded V_m response. This relationship was modeled by fitting a line to these data as Ohm’s law predicts that this relationship should be linear. C: the inverse of the slope of the linear fit was used as the estimate for G for this time point. D: using Ohm’s law, the V_m could be reconstructed from this estimate for G and the known levels of current injection, to validate the estimates. This was necessary as neurons are not perfectly linear devices. I^inj, injected current; V_m, membrane potential.

Fig. 3.

A, left: Confocal micrograph of a ChR2-eYFP-positive neuron in a section of mouse auditory cortex. Middle: PV-positive neuron in a slice labeled with a PV antibody and counterstained with a red fluorescent dye. Right: merged image of green (ChR2-eYFP) and red (PV) channels showing coexpression of ChR2-eYFP and PV in the same neuron. Scale bar: 10 μm. B: same as in A but for coexpression of Arch-GFP and PV in two neurons. C: example PSTHs of responses of a MU to 50-ms noise bursts with (blue traces) and without (black traces) optogenetic activation of PVIs. We removed the first 50 ms of the PSTH to exclude photoelectric artifacts from the analysis. All PSTHs show suppression of peak responses under conditions of increased PVI activity (blue), but no suppression of baseline activity (t < 0). D: PSTHs of noise responses for a MU with (amber traces) and without (black traces) optogenetic suppression of PVIs. As in C, control traces with no optogenetic stimulation are shown in black. E: histograms showing the effect of PVI activation (blue) and suppression (amber) on peak firing rate in the PSTH for all MUs that showed noise-evoked responses. PVI activation resulted in inhibition of evoked responses, while PVI suppression resulted in disinhibition of responses to noise stimuli. F: effects of optogenetic manipulations on evoked neural activity across the depth of cortex. Amber circles correspond to individual MUs under PVI suppression (n = 121), while blue circles correspond to individual MUs under PVI activation (n = 28). Units whose responses are illustrated in C and D are indicated here by black circles. PVI activation suppressed noise responses across all cortical layers and did not vary significantly over cortical depth. However, the strength of the disinhibition of noise-evoked responses observed during PVI suppression was found to decrease with cortical depth. G: histograms showing the effect of PVI activation (blue) and suppression (amber) on baseline activity in the PSTH for the same MUs as in E and F. PVI activation had no effect on baseline activity, while suppression resulted in disinhibition of baseline responses. H: effects of optogenetic manipulations on baseline activity across the depth of cortex for the same MUs as in E and F. Units whose responses are illustrated in C and D are again indicated here by black circles. Effects on baseline activity were consistent across the depth of cortex. Arch, archearhodopsin; ChR2, channelrhodopsin; eYFP, enhanced yellow fluorescent protein; GFP, green fluorescent protein; MU, multiunit; MUA, multiunit activity; PSTH, peristimulus time histogram; PV, parvalbumin; PVI, PV-positive interneurons.

Fig. 4.

Effect of PVI suppression on STRF shape. A: example STRFs estimated for the light-off condition. Spectrotemporal features that increase the MUA amplitude are shown in warmer colors while suppressive features are shown in cooler colors. B: STRFs estimated for the same MUAs as in A, but under light-on conditions during Arch-mediated PVI suppression. Color scaling is the same as in A. This manipulation results in a small increase in peak STRF coefficient. STRFs had similar shapes under light-off and light-on conditions (A and B). C–F: comparison of STRF parameters under light-off (abscissa) versus light-on (ordinate) conditions. A small but significant change was observed in best frequency (C) under light-on conditions. The bandwidth of frequency tuning (D) and temporal integration window (E) remained unaffected. The largest STRF coefficient increased during PVI suppression (F). Arch, archearhodopsin; BF, best frequency; BW, bandwidth; MUA, multiunit activity; PVI, parvalbumin-positive interneurons; STRF, spectrotemporal receptive fields.

Fig. 5.

Predictive performance of STRFs across light conditions. Correlation coefficients (CCs) between actual responses and responses predicted by light-off STRFs for both light-off (abscissa) and light-on (ordinate) conditions. STRFs fitted under light-off conditions showed a slight decrement (<2%) in predicting light-on condition responses. These findings indicate that tuning was largely unaffected by manipulation of PVI activity. PVI, parvalbumin-positive interneurons; STRF, spectrotemporal receptive fields.

Fig. 6.

Effect of PVI suppression on auditory cortex responses. A: negligible reduction in baseline activity (R_min) produced by PVI suppression during low-contrast stimulation. B: a more substantial increase in the maximum response (R_max) was also observed. C: a small subtractive change in the offset of responses occurred during PVI suppression. D: the asymmetrical effects on R_min and R_max led to an increase in gain during PVI suppression. E: a small reduction in R_min was also observed under high-contrast stimulation. F: a similar increase in R_max was observed under high-contrast stimulation. G: unlike under low-contrast stimulation, PVI suppression produced a small increase in offset during high-contrast stimulation. H: the robust increase in gain observed under low-contrast stimulation was also observed during high-contrast stimulation. I: the similarity of the effects on gain under low and high-contrast stimulation resulted in this manipulation leaving the strength of contrast gain control unaffected. Arch, archearhodopsin; MUA, multiunit activity; PVI, parvalbumin-positive interneurons; R_min; 5th percentile of the response of the multiunit activity; R_max, maximum response as the 95th percentile; S, range of responses in a particular light condition (“on” vs. “off”) and contrast condition (“low” vs. “high”).

Fig. 7.

Effect of PVI activation on STRF shape. A, left: two example STRFs estimated for the light-off condition. Spectrotemporal features that increase the MUA amplitude are shown in warmer colors while suppressive features are shown in cooler colors. Right: STRFs estimated for the same MUs as in left panels but under light-on conditions, during ChR2-mediated PVI activation. Color scaling is the same as for the left panels. This manipulation results in suppression of STRF coefficients, but STRF shapes are largely the same under both light-off and light-on conditions. B: comparison of STRF parameters under light-off (abscissa) versus light-on (ordinate) conditions. We observed no significant changes in best frequency, spectral bandwidth, or temporal integration window. The largest STRF coefficients were significantly reduced during PVI activation. C: predictive performance of STRFs across light conditions. STRFs fitted under light-off conditions predicted responses under light-on and light-off conditions equally well, indicating that tuning was largely unaffected by PVI activation. D: effect of PVI activation on auditory cortex responses. A reduction in baseline activity (R_min) was produced by PVI activation during low and high-contrast stimulation (first column). A comparable reduction in the maximum response (R_max) was also observed (second column). PVI activation produced a subtractive change in the offset of responses (third column). A reduction in gain was also observed during PVI activation (fourth column). E: PVI activation increased the strength of contrast gain control. BF, best frequency; BW, bandwidth; CCs, correlation coefficients; CGC, contrast gain control; ChR2, channelrhodopsin; G_relative, relative gain change (between conditions); MU, multiunit; MUA, MU activity; PVI, parvalbumin-positive interneurons; R_min; 5th percentile of the response of the multiunit activity; R_max, maximum response as the 95th percentile; S, range of responses in a particular light condition (“on” vs. “off”) and contrast condition (“low” vs. “high”); STRF, spectrotemporal receptive fields.

Fig. 8.

Contrast response of putative PVIs. A: spike waveforms and PSTHs of spiking responses of putative PVIs and non-PVIs to high-contrast DRC stimuli with light-off (black) and light-on (blue). Spike widths (ms) are shown above the waveforms. B: scatter plot of spike widths (abscissa) against the strength of the optogenetic response (ordinate), measured as the ratio of firing rates during light-on over light-off conditions. To be classified as a putative PVI (red), units were required to show a significant increase in firing rate during light stimulation and to have spike widths of < 0.25 ms. C: contrast response of putative PVIs. Histogram of the change in firing rates of putative PVIs in response to a doubling of stimulus contrast. Units that showed a significant increase in firing rate are shown in purple and units that showed a significant decrease are shown in orange. No systematic effect of contrast on firing rates was observed. DRC, dynamic random chord; PSTH, peristimulus time histogram; parvalbumin-positive interneurons; PV, parvalbumin; PVI, parvalbumin-positive interneuron.

Fig. 9.

Contrast-dependent membrane potential responses. A–D: mean V_m responses to 1-s high-contrast (red) and low-contrast (blue) DRCs for four different auditory cortex neurons. Broken lines indicate the onset of a 50-ms 80 dB SPL noise burst. E: mean V_m showed a very small increase under high-contrast compared with low-contrast stimulation. F: the amplitude of the noise-evoked PSP was increased under low-contrast stimulation, relative to high-contrast stimulation. Ratios in the corner of plots indicate the number of neurons above the identity line, y = x, over the total number of neurons. DRC, dynamic random chord; PSP, postsynaptic potential; V_m, membrane potential.

Fig. 10.

Membrane potential variability in auditory cortex is not contrast dependent. A: a power law function was used to map V_m to firing rate for each unit. Some units, such as this one, showed an increase in the gain of this relationship under high-contrast stimulation. B: other units showed no change in gain with stimulus contrast. C: histogram of gain changes resulting from increased contrast. No units showed the reduction in gain that would be expected if membrane voltage variance was a determining factor. The broken line corresponds to the median increase in gain with increased contrast. D: four representative units showing PSPs evoked by noise stimuli during high (red) and low (blue) contrast stimulation. Shaded areas indicate the standard deviation of V_m responses across trials. E: membrane potential standard deviation during DRC stimulation did not change with stimulus contrast. F: similarly, the standard deviation of PSP responses did not show a systematic change with stimulus contrast. Ratios in the corner of plots indicate the number of neurons above the y = x identity line over the total number of neurons. DRC, dynamic random chord; EPSP, excitatory postsynaptic potential; PSP, postsynaptic potential; σ_Vm, standard deviation of V_m; V_m, membrane potential.

Fig. 11.

Input conductance during high- and low-contrast stimulation. A–C: membrane potential responses recorded under four different levels of current injection for three representative units, during high- (red) and low- (blue) contrast stimulation. Broken lines indicate the timing of noise stimulus presentation. D–F: gain, G, estimated for these same three units under high (red) and low (blue) contrast stimulation. G: histogram of % change in G in response to an approximate doubling of stimulus contrast. Gain, G, showed no systematic variation with stimulus contrast. H: scatter plot of contrast-dependent changes in PSP amplitude (abscissa) and G (ordinate). The change in G between contrast conditions was far smaller than changes that would be required to account for the contrast-dependent scaling of the evoked V_m response. The ratio in the corner indicates the number of neurons above the identity line, y = x, over the total number of neurons. PSP, postsynaptic potential; V_m, membrane potential.