Many people find it easy to follow a conversation while on a busy city street, but this seemingly simple task requires sophisticated processing of sounds. The brain must accurately distinguish speech sounds from background noise, even though the volumes and pitches of those sounds overlap. To make this possible, neurons that process sounds continually adjust the relationship between the volume of a sound and the size of their response. This helps the brain to distinguish more precisely between different sounds, but how this works remains unclear.

Zinc ions form part of almost 3,000 different enzymes and regulatory proteins, and also help neurons to communicate with one another at junctions called synapses. Changes to the amount of zinc ions at the synapses have been seen in disorders including depression and Alzheimer’s disease. By imaging the brains of mice, Anderson, Kumar et al. now show that zinc ions affect how the healthy brain processes sounds.

Treating the mice with a substance that temporarily mops up zinc ions changed how neurons responded to sounds of different volumes. This revealed that zinc ions cause excitatory neurons, which activate neighboring cells, to increase their responses to sounds. Conversely, zinc ions cause inhibitory neurons, which reduce the activity of other cells, to decrease their responses to sounds. The overall effect is to change the balance of excitatory and inhibitory activity in areas of the brain that process sound. Anderson, Kumar et al. propose that these changes make it easier for the brain to process and distinguish different sounds as the environment changes from quiet to loud and vice versa.

As well as revealing a role for zinc ions in normal hearing, these findings may help us to understand disorders such as tinnitus and auditory neuropathies (conditions where the nerve that carries signals from the ear to the brain is damaged, leading to hearing loss). Both tinnitus and auditory neuropathies involve changes in the brain’s ability to increase or decrease its responses to sounds with particular characteristics – processes that may involve the activity of zinc ions.

As a constituent for nearly 3000 proteins, zinc plays a key role in protein structure, enzymatic catalysis, and cellular regulation (Vallee, 1988). Although the chemistry and biology of zinc metalloproteins have historically dominated the field of zinc biology, there is a growing appreciation for a signaling role of free, mobile zinc found in secretory tissues such as the prostate, pancreas, and especially the brain (Frederickson et al., 2005; Kelleher et al., 2011). In many brain areas, including the neocortex, limbic structures and auditory brainstem, high concentrations of synaptic zinc are found in glutamatergic excitatory presynaptic vesicles (Frederickson et al., 2005). In the hippocampus, more than half of presynaptic glutamatergic contain synaptic zinc (Sindreu et al., 2003), attesting to zinc’s abundance and importance in synaptic function.

Ex vivo studies established that synaptic zinc is an inhibitory neuromodulator of AMPA receptors, NMDA receptors, and vesicular release probability at lower frequencies of synaptic activity (Kalappa et al., 2015; Anderson et al., 2015; Vergnano et al., 2014; Pan et al., 2011; Vogt et al., 2000; Perez-Rosello et al., 2013). In contrast, during higher frequencies of synaptic activity and during enhanced vesicular release probability, synaptic zinc inhibits synaptic responses during the first few stimuli but enhances steady state responses during subsequent stimuli (Kalappa and Tzounopoulos, 2017). However, it is unknown whether and how zinc affects neuronal processing in vivo.

To answer this question, we investigated the role of synaptic zinc in shaping the sound-evoked activity in cortical neurons of awake mice. Namely, we investigated whether synaptic zinc modulates the relationship between sound intensity and the amplitude of neuronal evoked responses – termed gain modulation. Gain modulation controls the dynamic range of neuronal responses to sounds and is a fundamental feature of sound processing enabling adaptation to changes in sound stimulus statistics, as well as central compensation to peripheral damage (Wen et al., 2012; Dean et al., 2005; Watkins and Barbour, 2008; Rabinowitz et al., 2011; Natan et al., 2017; Chambers et al., 2016). We used widefield transcranial imaging of the genetically-encoded calcium indicator GCaMP6 to identify the effects of synaptic zinc on populations of specific neuronal types in the auditory cortex, and two-photon imaging to interrogate the effects of zinc on individual layer 2/3 neurons. Our results highlight synaptic zinc as a novel modulator of cortical responses to sound.

We began our exploration by visualizing sound-evoked responses in the auditory cortex of awake mice. To image and quantify the cortical sound-evoked responses, we used adeno-associated virus (AAV) driven by the synapsin promoter to express the genetically-encoded calcium indicator GCaMP6s in auditory cortical neurons (AAV-Syn-GCaMP6s, (Chen et al., 2013); Materials and methods). Eleven to 24 days following stereotaxic viral injections into the posterior temporal cortex, we performed in vivo calcium imaging in head-fixed unanesthetized mice (Materials and methods). To locate the primary auditory cortex (A1), we presented low frequency tones (5 or 6 kHz, 40–60 dB SPL) and imaged the sound-evoked changes in transcranial GCaMP6s fluorescence (Figure 1a, Materials and methods). Due to the mirror-like reversal of tonotopic gradients between A1 and the anterior auditory field (AAF) (Guo et al., 2012; Joshi et al., 2015), these sounds activated two discrete regions of the auditory cortex corresponding to the low frequency regions of A1 and the AAF (Figure 1a bottom). These results are consistent with previous studies mapping auditory cortical fields in the mouse (Issa et al., 2014; Kato et al., 2015; Guo et al., 2012).

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After locating A1, we performed a small craniotomy adjacent to A1 and inserted a thin glass micropipette containing the extracellular, high-affinity, fast, zinc-specific chelator ZX1 (Pan et al., 2011; Anderson et al., 2015) (Figure 1a top right, Materials and methods). Then, we quantified the sound-evoked responses of A1 neuronal populations to 400 msec long, 12 kHz tones of 30–80 dB SPL – an intensity span that encompasses sounds ranging from a quiet room to a busy city street. To assess the effect of zinc on A1 responses, we infused ZX1 in the auditory cortex and verified the intracortical diffusion of the chelator into A1 by visualizing the spread of the extracellular red fluorescent dye Alexa-594, co-infused with ZX1 (Figure 1—figure supplement 1a–c). We observed that the response to an 80 dB SPL tone was significantly enhanced after ZX1 application (Figure 1b,c); whereas, the response to a 50 dB SPL tone was not affected (Figure 1d,e). Overall, ZX1, but not vehicle containing ACSF and Alexa-594, enhanced the amplitude of the fluorescence response for sounds of ≥70 dB SPL (Figure 1f and Figure 1—figure supplement 1d,e). These results indicate that endogenous extracellular zinc inhibits the gain of sound-evoked A1 responses.

Does zinc scale by division or shift by subtraction the gain of sound-evoked A1 responses? To answer this question, we plotted the normalized evoked responses before vs. after ZX1 infusion. By fitting a regression line to this function, we found a slope steeper than unity and no change in the y-intercept (Figure 1g–i), indicating that extracellular zinc signaling exerts divisive gain control of sound-evoked A1 responses.

To track the origin of the extracellular zinc modulating A1 gain control, we performed similar experiments in ZnT3 KO mice, which lack the vesicular zinc transporter ZnT3 and synaptic zinc (Cole et al., 1999). Compared to WT mice, ZnT3 KO mice showed larger responses to sounds of 80 dB SPL (Figure 1—figure supplement 1f), suggesting that synaptic zinc inhibits the gain of A1 responses. Moreover, zinc chelation in KO mice had no effect on the gain of A1 responses (Figure 1j–m, Materials and methods), suggesting that, in WT mice, ZX1 enhances A1 gain via chelation of extracellular, ZnT3-dependent zinc. Consistent with the high selectivity of ZX1 over calcium and other biologically relevant metal ions such as magnesium (Pan et al., 2011), the lack of ZX1 effects on the sound-evoked responses in ZnT3 KO mice further validate that the observed effects of ZX1 on the sound evoked responses of WT mice are due to the chelation of synaptic zinc – and not to the potential non-specific effects of ZX1 on calcium or other metal ions. Finally, because extracellular tonic, not synaptically-evoked, zinc levels in brain slices are ZnT3-independent (Anderson et al., 2015), our results suggest that synaptically released zinc modulates the gain of sound-evoked responses in A1.

We next investigated how synaptic zinc affects the gain of populations of specific classes of auditory cortical neurons. We recorded transcranial sound-evoked responses from populations of principal excitatory neurons, by utilizing an AAV driven by the calcium/calmodulin-dependent protein kinase 2 (CaMKII) promoter to express GCaMP6f in principal neurons (Figure 2a–c and Figure 2—figure supplement 1a; AAV-CaMKII-GCaMP6f, [Pakan et al., 2016]). ZX1 reduced the amplitude of sound-evoked responses of principal neurons to sounds of 60–80 dB SPL (Figure 2a,b). Linear regression analysis showed that the ZX1-induced reduction in the gain was due to a slope shallower than unity (Figure 2c), indicating that extracellular zinc signaling exerts multiplicative gain control of the sound-evoked A1 responses in principal neurons. In contrast to the enhancing effects of ZX1 on responses to sounds of 70–80 dB SPL in all neurons (Figure 1f), the divisive effect of ZX1 on responses to sounds of 60–80 dB SPL in principal neurons suggests that the effects of synaptic zinc are intensity- and cell type-specific.

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To track the origin of the extracellular zinc increasing the gain of principal neurons, we studied the effects of ZX1 in ZnT3 KO mice, which had been injected with AAV-CaMKII-GCaMP6f. ZX1 had no effect on the sound-evoked responses of principal neurons in ZnT3 KO mice, indicating that synaptic zinc increases the gain of principal neurons (Figure 2—figure supplement 1b,c).

Whereas synaptic zinc is, mostly, an inhibitor of glutamatergic neurotransmission (Perez-Rosello et al., 2013; Vergnano et al., 2014; Anderson et al., 2015; Kalappa et al., 2015), zinc chelation decreased the sound-evoked activity of principal neurons. To explain this result, we hypothesized that the effects of zinc chelation are circuit-dependent. Since the sound-evoked responses of principal neurons in A1 are suppressed by inhibitory inputs from parvalbumin-expressing interneurons (PV neurons; Li et al., 2013; Seybold et al., 2015; Phillips and Hasenstaub, 2016; Resnik and Polley, 2017), a ZX1-induced increase of the sound-evoked responses of PV neurons would be consistent with the ZX1-induced decrease of the sound-evoked responses observed in principal neurons.

To image and quantify the sound-evoked responses of PV neurons, we injected AAV expressing Cre-dependent GCaMP6f (AAV-Flex-GCaMP6f, Materials and methods) into the auditory cortex of PV-Cre mice (Figure 2—figure supplement 1a, Materials and methods). ZX1 increased the sound-evoked responses of PV neurons to all tested sound intensities (30–80 dB SPL, Figure 2d,e). Linear regression analysis showed that the ZX1-induced increase in response gain was due to a slope steeper than unity (Figure 2f), indicating that extracellular zinc exerts divisive gain control of sound-evoked responses in PV neurons.

In PV neurons, the enhancing effect of ZX1 on sound-evoked responses was largest for sounds of 60–80 dB SPL (Figure 2—figure supplement 1d) – the intensities where principal neurons showed a ZX1-induced reduction in their responses (Figure 2b). Although our approach involving the bulk application of ZX1 is not conclusive for distinguishing cell- (direct) vs. circuit-dependent effects (see Discussion for details), this coupling between the ZX1-induced enhancement in the gain of PV neurons (Figure 2ef) and the ZX1-induced reduction in the gain of principal neurons (Figure 2bc) is consistent with the notion that synaptic zinc increases, at least in part, the gain of principal neurons by decreasing the gain of PV neurons.

We next focused on the effect of zinc chelation on the somatostatin-expressing interneurons (SOM neurons), which inhibit PV neurons (Harris and Shepherd, 2015; Tremblay et al., 2016). We selectively expressed GCaMP6f in SOM neurons by injecting AAV-Flex-GCaMP6f into SOM-Cre mice (Figure 2—figure supplement 1a, Methods). ZX1 increased the sound-evoked responses of SOM neurons to sounds of lower intensities (30–60 dB SPL, Figure 2gh, Figure 2—figure supplement 1d), and increased the gain of these neurons through a positive shift in the y-intercept (Figure 2i). These results support that extracellular zinc exerts subtractive gain control of sound-evoked A1 responses in SOM neurons.

The smaller ZX1-induced enhancement of the sound-evoked responses of PV neurons to lower intensity sounds (30–40 dB SPL) is consistent with the ZX1-induced increases of the sound-evoked responses of SOM neurons to the same sound intensities (Figure 2—figure supplement 1d). Together, our results from SOM, PV and principal neurons are consistent with a scheme where the zinc-mediated inhibition of the sound-evoked responses in SOM neurons contributes to the sound intensity dependence of the zinc-mediated inhibition in PV neurons, which, in turn, contributes to the zinc-mediated increase in the sound-evoked responses of principal neurons (see Discussion for more details).

We next investigated the effect of zinc chelation on the vasoactive intestinal polypeptide-expressing interneurons (VIP neurons), which inhibit SOM and PV neurons (Harris and Shepherd, 2015; Tremblay et al., 2016; Pi et al., 2013). We selectively expressed GCaMP6f in VIP neurons by injecting AAV-Flex-GCaMP6f into VIP-Cre mice (Figure 2—figure supplement 1a, Materials and methods). ZX1 increased the responses of VIP neurons to sounds of 60–80 dB SPL but did not affect their overall response gain (Figure 2j–l). The ZX1-induced enhancements of the responses of VIP neurons to sounds of 60–80 dB SPL are consistent with the lack of ZX1 effects on the responses of SOM neurons to sounds of the same intensity (Figure 2—figure supplement 1d). Although the lack of ZX1 effects on the gain of VIP neurons may reflect either a circuit-based cancellation of opposing effects or no direct effect (see Discussion for more details), together, our results show that synaptic zinc is a novel modulator of cortical sound processing – a modulator that increases the gain of principal neurons, but reduces the gain of PV and SOM neurons.

We next focused on the molecular targets (i.e., zinc-interacting proteins) that contribute to the effects of synaptic zinc on cortical sound-evoked activity. Because nanomolar levels of zinc inhibit NMDA receptors (NMDARs; Paoletti et al., 1997; Hansen et al., 2014), we tested whether NMDARs contribute to the observed zinc-mediated gain modulation in A1. To answer this question, we measured the effects of ZX1 on the neuronal sound-evoked responses after pharmacological blockade of NMDARs with a selective NMDAR antagonist (D-2-Amino-5-phosphonopentanoic acid, APV, infusion, Materials and methods). In the presence of APV (control), ZX1 increased the responses of principal neurons to sounds of 70–80 dB SPL (Figure 3ab), which is a reversal of the observed ZX1-induced reduction in the sound-evoked responses in the absence of APV (Figure 2ab). Moreover, APV enhanced the sound-evoked responses of principal neurons (Figure 3—figure supplement 1ab), suggesting that APV disinhibits principal neurons. This disinhibition may also disrupt the coupling between the ZX1-induced enhancement in the gain of PV neurons (Figure 2e,f) and the ZX1-induced reduction in the gain of principal neurons (Figure 2b,c). Consistent with this hypothesis, in the presence of APV, zinc chelation caused an increase in the sound-evoked responses of PV neurons to sound intensities of 30–80 dB SPL (Figure 3a,c). These results suggest that the disinhibition of principal neurons, in the presence of APV, unmasked the NMDAR-independent inhibitory effects of zinc on the sound-evoked responses of principal neurons, which are likely direct and non-circuit-dependent. However, similarly to ZX1 application, our approach involving the bulk application of APV is not conclusive for distinguishing cell autonomous vs. circuit-dependent effects (see Discussion for more details).

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The ZX1-induced increases in the sound-evoked responses of PV neurons in the presence of APV (Figure 3c) were not different from the increases observed in the absence of APV (Figure 2f), suggesting that the effects of zinc on the responses of PV neurons are, at least in part, NMDAR-independent.

Next, we investigated whether NMDARs contribute to the effects of synaptic zinc on the sound-evoked responses of SOM neurons. APV reduced the sound-evoked responses of SOM neurons (Figure 3—figure supplement 1ef) and abolished the effects of zinc chelation on the sound-evoked responses of SOM neurons (Figure 3d,e). Although potential circuit effects due to NMDAR-dependent and NMDAR-independent effects that cancel each other out can’t be ruled out (see Discussion for more details), our results are consistent with the notion that the effects of synaptic zinc on the sound-evoked responses of SOM neurons are NMDAR-dependent.

We next tested whether NMDARs contribute to the effects of synaptic zinc on the sound-evoked responses of VIP neurons. APV enhanced the sound-evoked responses of VIP neurons (Figure 3—figure supplement 1gh) and abolished the effects of ZX1 on the sound-evoked responses of VIP neurons (Figure 3df), suggesting that synaptic zinc inhibits the sound-evoked responses of VIP neurons, likely, via NMDAR-dependent mechanisms. However, similarly to the limitations in the interpretation of our results in SOM neurons due to potential circuit-based cancelation, NMDAR-independent mechanisms can’t be excluded. Overall, our results highlight that synaptic zinc modulates non-NMDAR targets to inhibit the gain of sound-evoked responses of principal and PV neurons; and suggest that NMDAR-mediated signaling is involved in the zinc-mediated gain control of SOM and VIP neurons.

Transcranial imaging reflects a sound-evoked population fluorescent signal arising from neurons residing in different cortical layers, as well as from different neuronal compartments (e.g. somata vs. dendrites). To explore the layer and sub-cellular specificity of the zinc-mediated effects on gain control, we next performed two-photon imaging of individual A1 L2/3 neurons in awake mice. In these experiments, we investigated the effects of ZX1 on the sound evoked responses from individual L2/3 neuronal somata (Methods). We began these experiments by injecting AAV-CaMKII-GCaMP6f into A1 to record responses from principal neurons (Materials and methods). After locating A1 as shown in Figure 1, we performed a craniotomy and subsequent two-photon imaging to obtain sound-evoked responses from the somata of individual principal neurons (Figure 4a, Materials and methods). We then infused ZX1 and were able to locate the same group of neurons to remeasure their sound-evoked responses (Figure 4a). ZX1 reduced the responses to sounds of 70 dB SPL (Figure 4b,c), and linear regression analysis showed that this reduction in gain was divisive (Figure 4d), which is consistent with our results obtained with transcranial imaging (Figure 2c). These results show that synaptic zinc exerts multiplicative gain control of sound-evoked responses in individual L2/3 principal neurons.

Figure 4

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We next measured the effects of ZX1 on the responses of individual L2/3 PV neurons. We injected AAV-Flex-GCaMP6f into PV-Cre mice and performed 2-photon imaging (Figure 4e). We measured the sound-evoked responses from the somata of individual L2/3 PV neurons, infused ZX1, and remeasured the responses of the same neurons (Figure 4e). PV neurons showed increased sound-evoked responses to sounds of 50 and 70 dB SPL (Figure 4f,g) and a multiplicative increase in their gain (Figure 4h), suggesting that synaptic zinc exerts divisive gain control of sound-evoked responses in individual L2/3 PV neurons.

In individual L2/3 PV neurons, in contrast to our transcranial measurements, we did not observe any increases in their somatic responses to sounds of 30 dB SPL. Since calcium transients in neuronal dendrites can be tuned to different stimulus features compared to somata (Chen et al., 2013), and can generate action potentials independently from the soma (Golding and Spruston, 1998), this discrepancy may reflect the differential zinc modulation of sound-evoked responses in dendritic vs. somatic domains of L2/3 PV neurons. It could also indicate that the sound-evoked responses of non-L2/3 PV neurons may contribute to the effects synaptic zinc to sounds of 30 dB SPL observed with transcranial imaging. Together, these results show that synaptic zinc signaling decreases the gain of sound-evoked responses of individual L2/3 PV neurons in A1.

We performed similar two-photon experiments in individual L2/3 SOM and VIP neurons (Figure 5) and the results we obtained were, overall, consistent with the results we observed with transcranial imaging: ZX1 caused an additive gain increase in L2/3 SOM neurons (Figure 5a–d) and no significant changes in the gain of L2/3 VIP neurons (Figure 5e–h). Whereas with transcranial imaging we observed ZX1-induced increases in the responses of VIP neurons to sounds of 70 dB SPL, we did not observe such an increase in individual L2/3 VIP neurons. This discrepancy may reflect the differential zinc modulation of sound-evoked responses in dendritic vs. somatic domains of L2/3 VIP neurons and/or may suggest that non-L2/3 VIP neurons are responsible for the enhancement we observed with transcranial imaging. Together, our two-photon experiments on individual L2/3 neurons support the cell-specific effect of synaptic zinc on A1 neurons: synaptic zinc increases the gain of principal neurons, but decreases the gain of PV and SOM interneurons.

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Our results show that synaptic zinc modulates the gain of sound-evoked auditory cortical responses. In the auditory system, as sound statistics of the auditory environment change, auditory neurons adjust their gain – the dynamic range of their responses – to match the stimulus statistics. In the auditory nerve, inferior colliculus, and auditory cortex, neurons adapt their responses to match the mean sound intensity levels (Wen et al., 2012; Dean et al., 2005; Watkins and Barbour, 2008). In addition to adaptation to the mean sound intensity levels, auditory cortical response gain is modulated by higher-level stimulus statistics, such as spectrotemporal contrast, reflecting tone distributions with identical mean intensity but different widths, and stimulus temporal correlation (Rabinowitz et al., 2011; Natan et al., 2017). Moreover, increases in cortical gain restore sound-evoked responses following near complete cochlear denervation, thus providing central compensation to peripheral damage (Chambers et al., 2016). Therefore, gain modulation provides a mechanism for generating sensory representations that are robust to noise, thus maximizing sensitivity to changes in stimulus intensity across variable auditory contexts. Moreover, gain modulation maintains the robustness of central responses after peripheral damage. We propose, although not addressed in this manuscript, that sound-dependent changes in zinc signaling may contribute to these mechanisms. But, is there any evidence for activity-dependent changes in cortical zinc signaling?

Sensory experience alters synaptic zinc levels in primary somatosensory and visual cortex (Brown and Dyck, 2002; Dyck et al., 2003); however, the physiological roles of this plasticity in sensory processing remain unknown. Based on our results, we propose that sound-dependent changes in zinc signaling, which have been demonstrated in the dorsal cochlear nucleus (Kalappa et al., 2015), may contribute to the activity-dependent changes in cortical gain. Such a contribution, which will be the focus of future experiments, would provide a role for zinc signaling in the adaptation of neuronal input-output functions to changing sound statistics, as well as in the preservation of central responses after peripheral damage.

Synaptic zinc is present in many cortical areas (Danscher and Stoltenberg, 2005) and dynamic gain modulation is a fundamental mechanism across many brain regions affecting sensory computations, attention, multisensory integration and value estimation (Somers et al., 1995; Reynolds and Heeger, 2009; Ohshiro et al., 2011; Louie et al., 2013). We therefore propose, although not addressed in this manuscript, that activity-dependent modification of synaptic zinc signaling may be a fundamental mechanism capable of mediating dynamic gain modulation in response to context, history, training, or injury across sensory modalities.

Gain modulation is mediated by selective increases or decreases in cortical inhibition (Li et al., 2013; Olsen et al., 2012; Wilson et al., 2012; Phillips and Hasenstaub, 2016). Recent studies, including optogenetic approaches to increase the activity of PV and SOM neurons, have suggested that PV neurons provide multiplicative/divisive gain control of principal neurons, whereas SOM neurons provide additive/subtractive gain control of principal neurons (Atallah et al., 2012; Li et al., 2014; Wilson et al., 2012; Moore and Wehr, 2013). However, activation and inactivation of PV and SOM neurons revealed asymmetric effects on neuronal gain in auditory cortex (Phillips and Hasenstaub, 2016). Here, we observed that zinc caused a multiplication in the gain of principal neurons, which is consistent with the observed zinc-mediated division in the gain of PV neurons. Therefore, our results are consistent with the role of PV neurons in providing dynamic gain control in A1 and add zinc as a player in the gain control of L2/3 cortical circuits.

The lack of ZX1 effects on the A1 neuronal responses to specific sound intensities may reflect circuit-based cancelation of opposing ZX1 effects. Although the bulk application of ZX1 limits our ability to distinguish cell- from circuit-specific effects, the lack of ZX1 effect on the sound-evoked responses of principal and VIP neurons to lower sound intensities (30–50 dB SPL), and on the responses of SOM neurons to higher intensities (70–80 dB SPL) suggests that the disruption of extracellular zinc signaling does not affect the balance of excitation and inhibition in these cases (Wehr and Zador, 2003). In principal neurons, it is interesting that this balance begins to break at sound intensities of ≥60 dB SPL, which is the intensity range where we observed the ZX1-induced increases in the sound-evoked responses of VIP neurons. Since VIP neurons provide inhibition to both SOM and PV neurons (Pi et al., 2013; Harris and Shepherd, 2015), these findings suggest that synaptic zinc modulates the VIP-mediated disinhibition of SOM and PV neurons, which, in turn, shape the gain of principal neurons. This scheme, and our previously stated suggestions on the hierarchical contribution of the zinc-mediated effects on SOM, PV and principal neuronal responses to sound (Results), are consistent with the overall sequential hodology of the three main inhibitory cortical cell classes (Harris and Shepherd, 2015). Importantly, the effects of ZX1 over a wide range of sound intensities (30–80 dB SPL) reflect the ethological relevance of synaptic zinc signaling in modulating cortical responses to sound.

Blockade of NMDARs with APV reduced the sound-evoked responses of PV neurons (Figure 3—figure supplement 1cd) and increased the sound-evoked responses of principal neurons (Figure 3—figure supplement 1ab). Similarly, in the prefrontal cortex pharmacological blockade of NMDARs reduced the spontaneous firing rates of PV neurons and increased the spontaneous firing rates of principal neurons (Homayoun and Moghaddam, 2007). Moreover, genetic deletion of NMDARs selectively from PV neurons increased the spontaneous firing rates of principal neurons (Carlén et al., 2012), suggesting that NMDA receptors expressed by PV-neurons contribute to PV neuron-mediated inhibition of principal neurons. Finally, PV neurons show high expression of GluN2A containing NMDAR subunits (Xi et al., 2009), which are exceptionally sensitive to low nanomolar zinc levels (Paoletti et al., 1997; Hansen et al., 2014), thus rendering excitatory inputs to PV neurons very zinc-sensitive. Together, these results are consistent with the view that NMDAR signaling and its modulation by zinc support and modulate the ability of PV neurons to inhibit principal neurons. However, it is unclear whether NMDARs expressed by PV neurons are responsible for these effects, for previous studies showed relatively weak NMDA receptor-mediated excitation of PV neurons (Goldberg et al., 2003; Rotaru et al., 2011), suggesting that NMDARs are not a strong source of excitation for PV neurons. In this context, it is interesting that blockade of NMDARs increased the sound-evoked responses of VIP neurons (Figure 3—figure supplement 1gh), which provide inhibition to PV neurons (Tremblay et al., 2016). This suggests that NMDAR signaling may serve to increase the sound evoked-responses of PV neurons via a combination of direct excitation of PV neurons and reduced VIP-mediated sound-evoked inhibition to these cells. Future studies will be required to explore these possibilities.

The responses of PV neurons to sound are the most sensitive to zinc modulation, both in amplitude and sound intensity span (Figure 2 and Figure 2—figure supplement 1d). It is interesting to note that plasticity in auditory cortex PV neurons during the first days following auditory nerve damage predicts the eventual recovery of cortical sound processing, which is achieved via increased A1 gain modulation weeks later (Resnik and Polley, 2017). The mechanisms of this PV neuronal plasticity remain unknown; however, activity-dependent changes in zinc levels may contribute to this plasticity – future experiments will be needed to test this hypothesis.

We observed both NMDAR-dependent and NMDAR-independent zinc-mediated effects on A1 responses to sound. This is consistent with in vitro studies showing that synaptic zinc inhibits, albeit at different concentrations, NMDARs (Paoletti et al., 1997; Hansen et al., 2014), AMPA receptors (Kalappa et al., 2015; Kalappa and Tzounopoulos, 2017), and reduces vesicular release probability via endocannabinoid signaling (Perez-Rosello et al., 2013; Kalappa and Tzounopoulos, 2017). Although previous studies have reported potentiation, inhibition and no effects of zinc on AMPARs (McAllister and Dyck, 2017), the vast majority of these did not employ ZX1, which, due to its improved kinetic and zinc binding properties, is the most appropriate chelator for investigating the effects of fast, transient elevations of synaptic zinc on synaptic targets (Pan et al., 2011; Anderson et al., 2015; Kalappa et al., 2015). However, ZX1 had no effects on synaptic AMPA currents in mossy fiber-CA3 synapses, suggesting that the effects of zinc on synaptic AMPA responses are subunit- and/or synapse-specific. Together, our results suggest that synaptic zinc shapes the gain of L2/3 neurons via multiple zinc-interacting targets, including NMDARs.

In the presence of APV, the lack of ZX1 effects on the sound-evoked responses of SOM and VIP neurons may be due to potential circuit- or to direct but multiple target-based cancelation of ZX1 effects, and it therefore does not necessarily support total NMDAR-dependence. Despite these limitations in the interpretation of the APV experiments showing negative results, our APV experiments showing enhancing effects of ZX1 on the sound-evoked responses of principal and PV neurons, suggest that synaptic zinc exerts its effects on these neurons, at least partially, in an NMDAR-independent manner. Nonetheless, future experiments investigating the effect of sound-evoked zinc on subthreshold conductances mediating the sound-evoked response of different types of neurons in A1; in vitro experiments on the effect of synaptic zinc on NMDAR and AMPAR EPSCs in A1 synapses; as well as the use of optogenetic approaches are needed to further resolve the detailed molecular mechanisms via which synaptic zinc shapes the sound-evoked responses of A1 L2/3 neurons.

Our findings are mostly specific to cells and circuits in L2/3. In the neocortex, synaptic zinc containing terminals are found predominantly in L1, 2/3 and 5, with moderate presence in L6 and light presence in L4 (McAllister and Dyck, 2017). This distribution together with the differential distribution of the different classes of interneurons – with VIP neurons more predominant in the superficial layers, SOM neurons more predominant in the deeper layers, and PV neurons present throughout the cortex (Tremblay et al., 2016) – make it unclear whether our findings apply to the deeper layers of cortex. Future studies will be required to address the effects of synaptic zinc on the gain of neurons and circuits located outside of L2/3.

Together, our results and previous findings on the role of zinc in modulating glutamatergic neurotransmission demonstrate that synaptic zinc fine-tunes excitatory synaptic transmission and sensory processing. Although this fine-tuning does not impair baseline neurotransmission or basic sensory and sensorimotor functions, such as hearing thresholds and prepulse inhibition (Cole et al., 2001; Thackray et al., 2017), it has profound consequences on synaptic plasticity (Pan et al., 2011), sound-evoked cortical processing and more intricate, yet ethologically crucial sensory processing tasks, such as gain modulation. We propose that zinc is a novel ‘knob’ in the brain that tunes cortical gain.

1. 1. Anderson CT
   2. Radford RJ
   3. Zastrow ML
   4. Zhang DY
   5. Apfel UP
   6. Lippard SJ
   7. Tzounopoulos T

   (2015) Modulation of extrasynaptic NMDA receptors by synaptic and tonic zinc

   PNAS 112:E2705–E2714.

   https://doi.org/10.1073/pnas.1503348112

   • PubMed
   • Google Scholar
2. 1. Atallah BV
   2. Bruns W
   3. Carandini M
   4. Scanziani M

   (2012) Parvalbumin-expressing interneurons linearly transform cortical responses to visual stimuli

   Neuron 73:159–170.

   https://doi.org/10.1016/j.neuron.2011.12.013

   • PubMed
   • Google Scholar
3. 1. Brown CE
   2. Dyck RH

   (2002)

   Rapid, experience-dependent changes in levels of synaptic zinc in primary somatosensory cortex of the adult mouse

   Journal of Neuroscience 22:2617–2625.

   • PubMed
   • Google Scholar
4. 1. Carlén M
   2. Meletis K
   3. Siegle JH
   4. Cardin JA
   5. Futai K
   6. Vierling-Claassen D
   7. Rühlmann C
   8. Jones SR
   9. Deisseroth K
   10. Sheng M
   11. Moore CI
   12. Tsai LH

   (2012) A critical role for NMDA receptors in parvalbumin interneurons for gamma rhythm induction and behavior

   Molecular Psychiatry 17:537–548.

   https://doi.org/10.1038/mp.2011.31

   • PubMed
   • Google Scholar
5. 1. Chambers AR
   2. Resnik J
   3. Yuan Y
   4. Whitton JP
   5. Edge AS
   6. Liberman MC
   7. Polley DB

   (2016) Central gain restores auditory processing following near-complete cochlear denervation

   Neuron 89:867–879.

   https://doi.org/10.1016/j.neuron.2015.12.041

   • PubMed
   • Google Scholar
6. 1. Chen TW
   2. Wardill TJ
   3. Sun Y
   4. Pulver SR
   5. Renninger SL
   6. Baohan A
   7. Schreiter ER
   8. Kerr RA
   9. Orger MB
   10. Jayaraman V
   11. Looger LL
   12. Svoboda K
   13. Kim DS

   (2013) Ultrasensitive fluorescent proteins for imaging neuronal activity

   Nature 499:295–300.

   https://doi.org/10.1038/nature12354

   • PubMed
   • Google Scholar
7. 1. Cole TB
   2. Wenzel HJ
   3. Kafer KE
   4. Schwartzkroin PA
   5. Palmiter RD

   (1999) Elimination of zinc from synaptic vesicles in the intact mouse brain by disruption of the ZnT3 gene

   PNAS 96:1716–1721.

   https://doi.org/10.1073/pnas.96.4.1716

   • PubMed
   • Google Scholar
8. 1. Cole TB
   2. Martyanova A
   3. Palmiter RD

   (2001) Removing zinc from synaptic vesicles does not impair spatial learning, memory, or sensorimotor functions in the mouse

   Brain Research 891:253–265.

   https://doi.org/10.1016/S0006-8993(00)03220-0

   • PubMed
   • Google Scholar
9. 1. Danscher G
   2. Stoltenberg M

   (2005) Zinc-specific autometallographic in vivo selenium methods: tracing of zinc-enriched (ZEN) terminals, ZEN pathways, and pools of zinc ions in a multitude of other ZEN cells

   Journal of Histochemistry & Cytochemistry 53:141–153.

   https://doi.org/10.1369/jhc.4R6460.2005

   • PubMed
   • Google Scholar
10. 1. Dean I
    2. Harper NS
    3. McAlpine D

    (2005) Neural population coding of sound level adapts to stimulus statistics

    Nature Neuroscience 8:1684–1689.

    https://doi.org/10.1038/nn1541

    • PubMed
    • Google Scholar
11. 1. Dyck RH
    2. Chaudhuri A
    3. Cynader MS

    (2003) Experience-dependent regulation of the zincergic innervation of visual cortex in adult monkeys

    Cerebral Cortex 13:1094–1109.

    https://doi.org/10.1093/cercor/13.10.1094

    • PubMed
    • Google Scholar
12. 1. Frederickson CJ
    2. Koh JY
    3. Bush AI

    (2005) The neurobiology of zinc in health and disease

    Nature Reviews Neuroscience 6:449–462.

    https://doi.org/10.1038/nrn1671

    • PubMed
    • Google Scholar
13. 1. Goldberg JH
    2. Yuste R
    3. Tamas G

    (2003) Ca2+ imaging of mouse neocortical interneurone dendrites: contribution of Ca2+-permeable AMPA and NMDA receptors to subthreshold Ca2+dynamics

    The Journal of Physiology 551:67–78.

    https://doi.org/10.1113/jphysiol.2003.042598

    • PubMed
    • Google Scholar
14. 1. Golding NL
    2. Spruston N

    (1998) Dendritic sodium spikes are variable triggers of axonal action potentials in hippocampal CA1 pyramidal neurons

    Neuron 21:1189–1200.

    https://doi.org/10.1016/S0896-6273(00)80635-2

    • PubMed
    • Google Scholar
15. 1. Guo W
    2. Chambers AR
    3. Darrow KN
    4. Hancock KE
    5. Shinn-Cunningham BG
    6. Polley DB

    (2012) Robustness of cortical topography across fields, laminae, anesthetic states, and neurophysiological signal types

    Journal of Neuroscience 32:9159–9172.

    https://doi.org/10.1523/JNEUROSCI.0065-12.2012

    • PubMed
    • Google Scholar
16. 1. Hansen KB
    2. Ogden KK
    3. Yuan H
    4. Traynelis SF

    (2014) Distinct functional and pharmacological properties of Triheteromeric GluN1/GluN2A/GluN2B NMDA receptors

    Neuron 81:1084–1096.

    https://doi.org/10.1016/j.neuron.2014.01.035

    • PubMed
    • Google Scholar
17. 1. Harris KD
    2. Shepherd GM

    (2015) The neocortical circuit: themes and variations

    Nature Neuroscience 18:170–181.

    https://doi.org/10.1038/nn.3917

    • PubMed
    • Google Scholar
18. 1. Homayoun H
    2. Moghaddam B

    (2007) NMDA receptor hypofunction produces opposite effects on prefrontal cortex interneurons and pyramidal neurons

    Journal of Neuroscience 27:11496–11500.

    https://doi.org/10.1523/JNEUROSCI.2213-07.2007

    • PubMed
    • Google Scholar
19. 1. Issa JB
    2. Haeffele BD
    3. Agarwal A
    4. Bergles DE
    5. Young ED
    6. Yue DT

    (2014) Multiscale optical Ca2+ imaging of tonal organization in mouse auditory cortex

    Neuron 83:944–959.

    https://doi.org/10.1016/j.neuron.2014.07.009

    • PubMed
    • Google Scholar
20. 1. Joshi A
    2. Middleton JW
    3. Anderson CT
    4. Borges K
    5. Suter BA
    6. Shepherd GM
    7. Tzounopoulos T

    (2015) Cell-specific activity-dependent fractionation of layer 2/3→5B excitatory signaling in mouse auditory cortex

    Journal of Neuroscience 35:3112–3123.

    https://doi.org/10.1523/JNEUROSCI.0836-14.2015

    • PubMed
    • Google Scholar
21. 1. Kalappa BI
    2. Anderson CT
    3. Goldberg JM
    4. Lippard SJ
    5. Tzounopoulos T

    (2015) AMPA receptor inhibition by synaptically released zinc

    PNAS 112:15749–15754.

    https://doi.org/10.1073/pnas.1512296112

    • PubMed
    • Google Scholar
22. 1. Kalappa BI
    2. Tzounopoulos T

    (2017) Context-dependent modulation of excitatory synaptic strength by synaptically released zinc

    Eneuro 4:ENEURO.0011-17.2017.

    https://doi.org/10.1523/ENEURO.0011-17.2017

    • PubMed
    • Google Scholar
23. 1. Kato HK
    2. Gillet SN
    3. Isaacson JS

    (2015) Flexible sensory representations in auditory cortex driven by behavioral relevance

    Neuron 88:1027–1039.

    https://doi.org/10.1016/j.neuron.2015.10.024

    • PubMed
    • Google Scholar
24. 1. Kelleher SL
    2. McCormick NH
    3. Velasquez V
    4. Lopez V

    (2011) Zinc in specialized secretory tissues: roles in the pancreas, prostate, and mammary gland

    Advances in Nutrition: An International Review Journal 2:101–111.

    https://doi.org/10.3945/an.110.000232

    • PubMed
    • Google Scholar
25. 1. Li LY
    2. Li YT
    3. Zhou M
    4. Tao HW
    5. Zhang LI

    (2013) Intracortical multiplication of thalamocortical signals in mouse auditory cortex

    Nature Neuroscience 16:1179–1181.

    https://doi.org/10.1038/nn.3493

    • PubMed
    • Google Scholar
26. 1. Li LY
    2. Ji XY
    3. Liang F
    4. Li YT
    5. Xiao Z
    6. Tao HW
    7. Zhang LI

    (2014) A feedforward inhibitory circuit mediates lateral refinement of sensory representation in upper layer 2/3 of mouse primary auditory cortex

    Journal of Neuroscience 34:13670–13683.

    https://doi.org/10.1523/JNEUROSCI.1516-14.2014

    • PubMed
    • Google Scholar
27. 1. Louie K
    2. Khaw MW
    3. Glimcher PW

    (2013) Normalization is a general neural mechanism for context-dependent decision making

    PNAS 110:6139–6144.

    https://doi.org/10.1073/pnas.1217854110

    • PubMed
    • Google Scholar
28. 1. McAllister BB
    2. Dyck RH

    (2017) Zinc transporter 3 (ZnT3) and vesicular zinc in central nervous system function

    Neuroscience & Biobehavioral Reviews 80:329–350.

    https://doi.org/10.1016/j.neubiorev.2017.06.006

    • PubMed
    • Google Scholar
29. 1. Moore AK
    2. Wehr M

    (2013) Parvalbumin-expressing inhibitory interneurons in auditory cortex are well-tuned for frequency

    Journal of Neuroscience 33:13713–13723.

    https://doi.org/10.1523/JNEUROSCI.0663-13.2013

    • PubMed
    • Google Scholar
30. 1. Natan RG
    2. Carruthers IM
    3. Mwilambwe-Tshilobo L
    4. Geffen MN

    (2017) Gain Control in the Auditory Cortex Evoked by Changing Temporal Correlation of Sounds

    Cerebral Cortex 27:2385–2402.

    https://doi.org/10.1093/cercor/bhw083

    • PubMed
    • Google Scholar
31. 1. Ohshiro T
    2. Angelaki DE
    3. DeAngelis GC

    (2011) A normalization model of multisensory integration

    Nature Neuroscience 14:775–782.

    https://doi.org/10.1038/nn.2815

    • PubMed
    • Google Scholar
32. 1. Olsen SR
    2. Bortone DS
    3. Adesnik H
    4. Scanziani M

    (2012) Gain control by layer six in cortical circuits of vision

    Nature 483:47–52.

    https://doi.org/10.1038/nature10835

    • PubMed
    • Google Scholar
33. 1. Pakan JM
    2. Lowe SC
    3. Dylda E
    4. Keemink SW
    5. Currie SP
    6. Coutts CA
    7. Rochefort NL

    (2016) Behavioral-state modulation of inhibition is context-dependent and cell type specific in mouse visual cortex

    eLife 5:e14985.

    https://doi.org/10.7554/eLife.14985

    • PubMed
    • Google Scholar
34. 1. Pan E
    2. Zhang XA
    3. Huang Z
    4. Krezel A
    5. Zhao M
    6. Tinberg CE
    7. Lippard SJ
    8. McNamara JO

    (2011) Vesicular zinc promotes presynaptic and inhibits postsynaptic long-term potentiation of mossy fiber-CA3 synapse

    Neuron 71:1116–1126.

    https://doi.org/10.1016/j.neuron.2011.07.019

    • PubMed
    • Google Scholar
35. 1. Paoletti P
    2. Ascher P
    3. Neyton J

    (1997)

    High-affinity zinc inhibition of NMDA NR1-NR2A receptors

    Journal of Neuroscience 17:5711–5725.

    • PubMed
    • Google Scholar
36. 1. Patel TP
    2. Man K
    3. Firestein BL
    4. Meaney DF

    (2015) Automated quantification of neuronal networks and single-cell calcium dynamics using calcium imaging

    Journal of Neuroscience Methods 243:26–38.

    https://doi.org/10.1016/j.jneumeth.2015.01.020

    • PubMed
    • Google Scholar
37. 1. Perez-Rosello T
    2. Anderson CT
    3. Schopfer FJ
    4. Zhao Y
    5. Gilad D
    6. Salvatore SR
    7. Freeman BA
    8. Hershfinkel M
    9. Aizenman E
    10. Tzounopoulos T

    (2013) Synaptic Zn2+ inhibits neurotransmitter release by promoting endocannabinoid synthesis

    Journal of Neuroscience 33:9259–9272.

    https://doi.org/10.1523/JNEUROSCI.0237-13.2013

    • PubMed
    • Google Scholar
38. 1. Phillips EA
    2. Hasenstaub AR

    (2016) Asymmetric effects of activating and inactivating cortical interneurons

    eLife 5:e18383.

    https://doi.org/10.7554/eLife.18383

    • PubMed
    • Google Scholar
39. 1. Pi HJ
    2. Hangya B
    3. Kvitsiani D
    4. Sanders JI
    5. Huang ZJ
    6. Kepecs A

    (2013) Cortical interneurons that specialize in disinhibitory control

    Nature 503:521–524.

    https://doi.org/10.1038/nature12676

    • PubMed
    • Google Scholar
40. 1. Pologruto TA
    2. Sabatini BL
    3. Svoboda K

    (2003) ScanImage: flexible software for operating laser scanning microscopes

    Biomedical Engineering Online 2:13.

    https://doi.org/10.1186/1475-925X-2-13

    • PubMed
    • Google Scholar
41. 1. Rabinowitz NC
    2. Willmore BD
    3. Schnupp JW
    4. King AJ

    (2011) Contrast gain control in auditory cortex

    Neuron 70:1178–1191.

    https://doi.org/10.1016/j.neuron.2011.04.030

    • PubMed
    • Google Scholar
42. 1. Resnik J
    2. Polley DB

    (2017) Fast-spiking GABA circuit dynamics in the auditory cortex predict recovery of sensory processing following peripheral nerve damage

    eLife 6:e21452.

    https://doi.org/10.7554/eLife.21452

    • PubMed
    • Google Scholar
43. 1. Reynolds JH
    2. Heeger DJ

    (2009) The normalization model of attention

    Neuron 61:168–185.

    https://doi.org/10.1016/j.neuron.2009.01.002

    • PubMed
    • Google Scholar
44. 1. Rotaru DC
    2. Yoshino H
    3. Lewis DA
    4. Ermentrout GB
    5. Gonzalez-Burgos G

    (2011) Glutamate receptor subtypes mediating synaptic activation of prefrontal cortex neurons: relevance for schizophrenia

    Journal of Neuroscience 31:142–156.

    https://doi.org/10.1523/JNEUROSCI.1970-10.2011

    • PubMed
    • Google Scholar
45. 1. Seybold BA
    2. Phillips EA
    3. Schreiner CE
    4. Hasenstaub AR

    (2015) Inhibitory actions unified by network integration

    Neuron 87:1181–1192.

    https://doi.org/10.1016/j.neuron.2015.09.013

    • PubMed
    • Google Scholar
46. 1. Sindreu CB
    2. Varoqui H
    3. Erickson JD
    4. Pérez-Clausell J

    (2003) Boutons containing vesicular zinc define a subpopulation of synapses with low AMPAR content in rat hippocampus

    Cerebral Cortex 13:823–829.

    https://doi.org/10.1093/cercor/13.8.823

    • PubMed
    • Google Scholar
47. 1. Somers DC
    2. Nelson SB
    3. Sur M

    (1995)

    An emergent model of orientation selectivity in cat visual cortical simple cells

    Journal of Neuroscience 15:5448–5465.

    • PubMed
    • Google Scholar
48. 1. Suter BA
    2. O'Connor T
    3. Iyer V
    4. Petreanu LT
    5. Hooks BM
    6. Kiritani T
    7. Svoboda K
    8. Shepherd GM

    (2010) Ephus: multipurpose data acquisition software for neuroscience experiments

    Frontiers in Neural Circuits 4:100.

    https://doi.org/10.3389/fncir.2010.00100

    • PubMed
    • Google Scholar
49. 1. Thackray SE
    2. McAllister BB
    3. Dyck RH

    (2017) Behavioral characterization of female zinc transporter 3 (ZnT3) knockout mice

    Behavioural Brain Research 321:36–49.

    https://doi.org/10.1016/j.bbr.2016.12.028

    • PubMed
    • Google Scholar
50. 1. Tremblay R
    2. Lee S
    3. Rudy B

    (2016) GABAergic interneurons in the neocortex: from cellular properties to circuits

    Neuron 91:260–292.

    https://doi.org/10.1016/j.neuron.2016.06.033

    • PubMed
    • Google Scholar
51. 1. Vallee BL

    (1988)

    Zinc: biochemistry, physiology, toxicology and clinical pathology

    BioFactors 1:31–36.

    • PubMed
    • Google Scholar
52. 1. Vergnano AM
    2. Rebola N
    3. Savtchenko LP
    4. Pinheiro PS
    5. Casado M
    6. Kieffer BL
    7. Rusakov DA
    8. Mulle C
    9. Paoletti P

    (2014) Zinc dynamics and action at excitatory synapses

    Neuron 82:1101–1114.

    https://doi.org/10.1016/j.neuron.2014.04.034

    • PubMed
    • Google Scholar
53. 1. Vogt K
    2. Mellor J
    3. Tong G
    4. Nicoll R

    (2000) The actions of synaptically released zinc at hippocampal mossy fiber synapses

    Neuron 26:187–196.

    https://doi.org/10.1016/S0896-6273(00)81149-6

    • PubMed
    • Google Scholar
54. 1. Watkins PV
    2. Barbour DL

    (2008) Specialized neuronal adaptation for preserving input sensitivity

    Nature Neuroscience 11:1259–1261.

    https://doi.org/10.1038/nn.2201

    • PubMed
    • Google Scholar
55. 1. Wehr M
    2. Zador AM

    (2003) Balanced inhibition underlies tuning and sharpens spike timing in auditory cortex

    Nature 426:442–446.

    https://doi.org/10.1038/nature02116

    • PubMed
    • Google Scholar
56. 1. Wen B
    2. Wang GI
    3. Dean I
    4. Delgutte B

    (2012) Time course of dynamic range adaptation in the auditory nerve

    Journal of Neurophysiology 108:69–82.

    https://doi.org/10.1152/jn.00055.2012

    • PubMed
    • Google Scholar
57. 1. Wilson NR
    2. Runyan CA
    3. Wang FL
    4. Sur M

    (2012) Division and subtraction by distinct cortical inhibitory networks in vivo

    Nature 488:343–348.

    https://doi.org/10.1038/nature11347

    • PubMed
    • Google Scholar
58. 1. Xi D
    2. Keeler B
    3. Zhang W
    4. Houle JD
    5. Gao WJ

    (2009) NMDA receptor subunit expression in GABAergic interneurons in the prefrontal cortex: application of laser microdissection technique

    Journal of Neuroscience Methods 176:172–181.

    https://doi.org/10.1016/j.jneumeth.2008.09.013

    • PubMed
    • Google Scholar

Author details

1. Charles T Anderson

   Department of Otolaryngology, University of Pittsburgh, Pittsburgh, United States

   Present address

   Department of Physiology, Pharmacology, and Neuroscience, Blanchette Rockefeller Neurosciences Institute, Sensory Neuroscience Research Center, West Virginia University School of Medicine, Morgantown, United States

   Contribution

   Conceptualization, Formal analysis, Supervision, Investigation, Methodology, Writing—original draft, Writing—review and editing

   Contributed equally with

   Manoj Kumar

   For correspondence

   charles.anderson@hsc.wvu.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-3353-0182

2. Manoj Kumar

   Department of Otolaryngology, University of Pittsburgh, Pittsburgh, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing—review and editing

   Contributed equally with

   Charles T Anderson

   Competing interests

   No competing interests declared

3. Shanshan Xiong

   1. Department of Otolaryngology, University of Pittsburgh, Pittsburgh, United States
   2. The Third Xiangya Hospital, Central South University, Changsha, China

   Contribution

   Data curation, Formal analysis, Investigation, Methodology

   Competing interests

   No competing interests declared

4. Thanos Tzounopoulos

   Department of Otolaryngology, University of Pittsburgh, Pittsburgh, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Supervision, Funding acquisition, Writing—original draft, Project administration, Writing—review and editing

   For correspondence

   thanos@pitt.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-4583-145X

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