Zebra finches are an accessible model organism for studying how upper motor neurons control a rapid and precise learned behavior. Their song consists of bouts of repeated motifs made up of multiple syllables, each containing distinct features that change on a rapid timescale (Leonardo and Fee, 2005; Sturdy et al., 1999; Yazaki-Sugiyama et al., 2015). In sharp contrast with mammals, which possess a six layered neocortex, songbirds orchestrate song behavior with a circuitry consisting of pallial nuclei, which nonetheless have connectivity analogous to mammalian cortical microcircuits (Jarvis, 2019; Karten, 2015). Projection neurons within the robust nucleus of the arcopallium (RAPNs) represent the main forebrain output of the vocal motor system of songbirds. They share several molecular markers with mammalian layer 5 pyramidal neurons (L5PNs) (Dugas-Ford et al., 2012; Nevue et al., 2020; Pfenning et al., 2014; Stacho et al., 2020). During song production, RAPNs exhibit robust burst-pause firing with high temporal precision (~0.2 ms variance in the first spike latency; Chi and Margoliash, 2001). They are thus well poised to orchestrate the rapid movements of the syringeal muscles (~4 ms to peak force of muscle twitch; Adam and Elemans, 2020).

We have recently shown that zebra finch RAPNs share many electrophysiological properties with mammalian L5PNs, including a hyperpolarization-activated current (I_h), a persistent Na⁺ current, and a large transient Na⁺ current (I_NaT) with a short onset latency (Zemel et al., 2021). These properties facilitate the minimally adapting, regular spiking of APs (Almog et al., 2018; McCormick et al., 1985). A major difference, however, is that RAPNs exhibit an ultranarrow AP half-width (Zemel et al., 2021), a property also found in primate Betz cells (Lemon et al., 2021; Vigneswaran et al., 2011). Not found in rodents (Lacey et al., 2014; Soares et al., 2017), these cells are sparsely distributed across layer 5 of the motor cortex in primates and cats (Chen et al., 1996; Rivara et al., 2003; Tomasevic et al., 2022), often terminate directly onto lower motor neurons and are thought to facilitate highly refined aspects of motor control (Lemon and Kraskov, 2019). The unique AP half-width of Betz cells is associated with high expression of the voltage-gated potassium channel Kv3.1 subunit (Bakken et al., 2021; Ichinohe et al., 2004; Soares et al., 2017). The high-voltage, fast activation and fast deactivation of these channels have been shown to significantly narrow the AP waveform, thus facilitating high-frequency firing (Hong et al., 2016; Kaczmarek and Zhang, 2017; Rudy and McBain, 2001).

Similar to mammalian Betz cells, RAPNs in adult male finches also exhibit high expression of KCNC1 (Kv3.1; Lovell et al., 2013). Interestingly, this expression is significantly lower in the adjacent dorsal intermediate arcopallium (AId) (Nevue et al., 2020), an area thought to be involved in non-vocal somatic motor functions (Feenders et al., 2008; Mandelblat-Cerf et al., 2014; Yuan and Bottjer, 2020) that have different temporal requirements than song (e.g., ~10 ms to peak force of twitch for pectoral wing muscles Bahlman et al., 2020). Whereas the excitable properties of RAPNs have been examined in detail (Adret and Margoliash, 2002; Garst-Orozco et al., 2014; Liao et al., 2011; Spiro et al., 1999; Zemel et al., 2021), little is known about (1) the excitability of AId neurons and (2) the molecular basis shaping the AP waveform in either brain region.

A comparison of excitable features between RAPNs and AId neurons may reveal molecular specializations that evolved to specifically support the execution of complex, learned vocalizations. Here, we show that compared to RAPNs, AId neurons have broader APs and spike at lower frequencies during current injections. We found that these differences are due, in part, to the differential activity of Shaw-related K⁺ channels (Kv3.1–3.4), as Kv3 channel blockers disproportionately broadened APs and decreased firing rates in RAPNs compared to AId neurons. Furthermore, a novel Kv3.1/3.2 positive modulator, AUT5, narrowed the AP waveform and increased the steady-state firing frequency of RAPNs, but not of AId neurons. Moreover, KCNC1 had significantly higher expression in RA compared to AId, while KCNC2–4 (Kv3.2–3.4) genes were non-differential in expression. Notably, our analysis identified zebra finch KCNC3 (Kv3.3), a gene previously thought to be absent in birds. Morphological analysis revealed higher dendritic complexity and spine density but smaller spines in AId neurons compared to RAPNs, which had larger spines, like Betz cells (Kaiserman-Abramof and Peters, 1972). We propose that the shared molecular and electrophysiological properties that promote ultranarrow spikes in songbird RAPNs and primate Betz cells likely originated from a convergent evolutionary process that allowed these neurons to operate as fast and precise signaling devices for fine motor control.

Understanding the neuronal basis of specific behaviors requires determining the cellular properties of the upper motor neurons involved in those behaviors. RAPNs and AId neurons are thought to control vocal and non-vocal somatic functions respectively via descending projections out of the finch telencephalon toward lower motor centers (Bottjer et al., 2000; Feenders et al., 2008; Mandelblat-Cerf et al., 2014; Nottebohm et al., 1976; Paton et al., 1981; Wild, 1993b; Yuan and Bottjer, 2020; Mello et al., 2019; Figure 1A). Contrasting the properties of RAPNs and AId neurons may reveal specific features of vocal motor neurons (RAPNs) that have not been previously identified. RAPNs and AId neurons are known to differ in their molecular profiles, including higher expression of the voltage-gated potassium channel KCNC1/Kv3.1 in RAPNs (Nevue et al., 2020). Our goal here was to contrast the excitable properties of RAPNs and AId neurons in order to (1) identify and (2) determine the role of molecular correlates of excitability that differ between these neuronal populations.

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Morphological features of RAPNs and AId neurons

We started with an examination of the morphology of principal neuronal cells in RA and AId, whose close proximity in the arcopallium can be easily observed in frontal sections (Figure 1B–C; Figure 2A–B). Whereas many morphological characteristics of RAPNs have been described (Hayase et al., 2018; Kittelberger and Mooney, 1999; Miller et al., 2017; Spiro et al., 1999), those of AId neurons have not been previously examined. Intracellular biocytin fills in frontal slices revealed that recorded AId neurons exhibit several morphological characteristics similar to those of RAPNs, including a large soma, a large diameter axon initial segment with extensively branched thin, aspinous axonal collaterals, and an extensive dendritic arborization, with individual dendrites exhibiting numerous spines (Figure 1D–F). There were however some important differences. A Sholl analysis (Sholl, 1956a) revealed the extent of dendritic complexity for AId neurons to be significantly greater than that of RAPNs, although dendrites of AId neurons were restricted to ~200 µm from the cell body, as has been previously reported for RAPNs (Figure 1G). AId neurons also had approximately twice the number of spines compared to RAPNs as measured from a 30 µm segment of the tertiary branch of the filled cells (mean ± SE: 0.9±0.07 vs 0.4±0.05 spines/µm; Figure 1H). Additionally, whereas RAPN spines consistently presented with a mushroom-type shape, those in AId neurons exhibited a mix of mushroom, thin and filopodic structures (Figure 1D–E, right; for a review on spine shapes see Pchitskaya and Bezprozvanny, 2020).

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To gain further insights into the morphology of RAPNs and AId neurons, we next analyzed our highest quality images (three RAPNs and two AId neurons) using ShuTu software designed for digital 3D reconstructions (Figure 1—figure supplement 1A–B; Jin et al., 2019). We were able to confirm the approximately twofold larger spine density when pooling all branch segments together (Figure 1—figure supplement 1C; Figure 1, Supplementary file 1). The distribution of these spines as a function of distance from the soma was unimodal in both groups, with an increase in spines occurring after the initial, mostly aspinous primary dendrite, followed by a decrease toward more distal branches (Figure 1—figure supplement 1E). Upon manually tracing >1000 individual spines for each group we found that AId neurons display a larger proportion of spines with smaller 2D surface areas compared to RAPNs (Figure 1—figure supplement 1D). The total surface area of the soma and dendrites of RAPNs and AId neurons is shown in Figure 1, Supplementary file 1. The average surface area for different compartments were (in µm²) soma: 879.7 vs 727; dendrites: 5047.7 vs 5548; spines: 638.7 and 937, for RAPN and AId neurons, respectively (axons not included; Figure 1, Supplementary file 1). While we acknowledge the limited data set and the caveat that some dendrites are cut off by the slicing procedure, the results suggest that AId neurons may receive more numerous, perhaps diverse, synaptic inputs that are differentially filtered compared to RAPNs. Finally, we calculated the surface to volume ratio. For RAPNs we find 1.5–2.3 µm^–1 and for AId neurons 2.5–2.9 µm^–1 (Figure 1, Supplementary file 1). These values are similar to those found using EM 3D reconstructions in mouse cortical neurons (1.63 µm^–1) but lower than found in astrocytes (4.4 µm^–1 Calì et al., 2019), which may have metabolic energy consequences for RA nuclei, which stain heavily for metabolic markers (Adret and Margoliash, 2002).

RAPNs fire ultranarrow spikes at higher frequencies than AId neurons

RAPNs produce remarkably narrow APs (half-width = ~0.2 ms at 40°C; Zemel et al., 2021), making them well suited for orchestrating rapid movements of the syringeal and respiratory muscles required for song production. Upon examining properties of spontaneous APs, we found that RAPNs and AId neurons shared similar threshold, amplitude, peak, and after-hyperpolarization at both temperatures examined (Figure 2C; Table 1). However, AId neurons had an AP half-width that was twice as broad as the RAPN APs (Figure 2C–D , and F–G; Table 1). The shorter half-width of RAPNs could be due to either a faster AP depolarization and/or repolarization rate. To determine which phase of the AP was responsible for this difference, we derived phase plane plots from averaged spontaneous APs and compared the maximum rates of depolarization and repolarization. At room temperature, the maximum rate of repolarization was 76% larger in RAPNs compared to AId neurons (mean ± SEM in V/s: 181.9±7.8 vs 64.5±3.7, respectively; Figure 2E; Table 1), whereas the maximum rate of depolarization was only 29% larger in RAPNs compared to AId neurons (mean ± SEM in V/s: 658.4±26.5 vs 477.1±24.6, respectively; Table 1). At 40°C the difference in the maximum depolarization rate was not significant, while the maximum repolarization rate was still 37% greater in RAPNs (mean ± SEM in V/s: 764.7±92.4 vs 482.3±52.8, respectively; Figure 2H; Table 1). While the similar maximum rate of depolarization at 40°C may result from limitations on temporal resolution (Oláh et al., 2021), taken together with the room temperature recordings these findings indicate that RAPN APs are narrower than those of AId neurons, with larger differences in the maximum repolarization rate compared to the depolarization rate.

We next examined the evoked firing properties by delivering increasing, step-wise 1 s current injections to RAPNs and AId neurons (Figure 3A and C, examples at +500 pA). As expected, a higher firing rate was observed in both brain regions at physiological temperature compared to room temperature. In the absence of injected current, both RAPNs and AId neurons fired spontaneous APs (spontaneous APs in RAPNs also observed in extracellular slice recordings; Wood et al., 2011), however, RAPNs exhibited significantly higher firing rates than AId neurons at high temperatures (Figure 3B and D; Table 1). Moreover, we consistently observed lower firing rates in AId neurons (Figure 3B and D), with lower instantaneous (frequency of the first two spikes) and steady-state (frequency of the last two spikes) firing frequencies at all levels of current injected (Figure 3A and C, top of each AP train). These results suggest that compared to RAPNs, the slower repolarization rate of AId neurons is likely a limiting factor for high-frequency repetitive spiking.

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Spikes are more sensitive to Kv3 blockers in RAPNs than in AId neurons

Kv3 channels (Kv3.1–3.4) are part of the Shaw-related family of voltage-gated K⁺ channels, which are characterized by rapid activation and deactivation kinetics at depolarized membrane potentials (Kaczmarek and Zhang, 2017; Rudy and McBain, 2001). These properties enable the rapid repolarization of APs, which in turn facilitates voltage-gated Na⁺ (Nav) channel recovery from inactivation during repetitive firing (Bean, 2007; Leão et al., 2005). Kv3.1, in particular, has been implicated in narrowing the AP waveform in a number of cell types, including Betz cells (Ichinohe et al., 2004; Soares et al., 2017). Interestingly, KCNC1 (Kv3.1) mRNA is expressed within RA (Lovell et al., 2013). Moreover, RA shows much higher expression of KCNC1 than AId (Nevue et al., 2020). We thus asked whether Kv3.1 channels are regulators of the AP half-width in RAPNs and AId neurons. Although there are no commercially available Kv3.1-specific inhibitors, previous studies have established pharmacological protocols to confirm the presence of Kv3.x currents in excitable cells (Liu et al., 2017; Muqeem et al., 2018). APs from Kv3.x-expressing neurons, including Betz cells (Spain et al., 1991), are typically broadened by sub-millimolar concentrations of the Kv channel inhibitors tetraethylammonium (TEA) and 4-aminopyridine (4-AP) (Rettig et al., 1992). If the differences in AP half-width and maximum repolarization rate between RAPNs and AId neurons are due to the expression of Kv3.1, we would expect a more significant AP broadening upon exposure to either of these compounds in RAPNs than in AId neurons.

To test this prediction, we recorded spontaneous APs from RAPNs and AId neurons in frontal slices before and after exposure to 500 µM TEA (Figure 4A–B) and 100 µM 4-AP (Figure 4E–F), respectively. We performed these experiments at room temperature, as this allowed for more stable recordings that lasted for longer time periods. In response to TEA, spontaneous APs in RAPNs showed significantly more broadening (Figure 4C; mean ± SEM [ms]: 0.53±0.01–0.92±0.04 [77% change] and 1.24±0.06–1.71±0.15 [36% change] for RAPNs and AId neurons, respectively; for individual measurements in RAPNs and AId neurons, see Figure 4—figure supplement 1A–B, left) and decreases in the maximum repolarization rate (Figure 4D; mean ± SEM [ms]: 196.8±7.7–101.8±8.0 [49% change] and 51.6±2.5–39.5±5.1 [24% change] for RAPNs and AId neurons, respectively; for separate measurements in RAPNs and AId neurons, see Figure 4—figure supplement 1A–B, right). In response to 4-AP, spontaneous APs in RAPNs also showed significantly more broadening (Figure 4G; mean ± SEM [ms]: 0.53±0.04–0.98±0.04 [93% change] and 1.10±0.05–1.49±0.13 [36% change] for RAPNs and AId neurons, respectively; for individual measurements in RAPNs and AId neurons, see Figure 4—figure supplement 1C–D, left) and decreases in the maximum repolarization rate (Figure 4H; mean ± SEM [ms]: 185.9±21.7–109.9±3.4 [35% change] and 66.3±3.3–61.9±7.0 [8% change] for RAPNs and AId neurons, respectively; for individual measurements in RAPNs and AId neurons, see Figure 4—figure supplement 1C–D, right).

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Evoked AP firing was also more affected by TEA and 4-AP in RAPNs than in AId neurons. Upon exposure to TEA, RAPNs showed significant decreases in the evoked firing rate (Figure 5A; 35 ± 4.1% decrease in spikes/s, 29.3 ± 10.4% decrease in instantaneous firing, and 33.7 ± 3.8% decrease in steady-state firing frequency upon the +500 pA current injection), whereas trends, but no significant effects, were seen in AId (Figure 5B). Upon exposure to 4-AP, RAPNs also showed significant decreases in the evoked firing rate (Figure 5C; 36.8 ± 10.9% decrease in spikes/s, 63.7 ± 4.8% decrease in instantaneous firing frequency, and 36.5 ± 12.9% decrease in steady-state firing frequency upon the +500 pA current injection), whereas trends, but no significant effects, were seen in AId (Figure 5D).

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In order to confirm that the results obtained with TEA and 4-AP were not an artifact of time spent in the whole-cell current-clamp configuration, we performed washout experiments (Figure 5—figure supplement 1). We observed a washout of the effects of TEA within 3 min, both on the AP half-width (Figure 5—figure supplement 1A–B; 82% recovery) and the spikes per second during a +300 pA current injection (Figure 5—figure supplement 1C; 98% recovery). We additionally observed a trend for recovery from the effects of 4-AP on the AP half-width (Figure 5—figure supplement 1D–E) and spikes per second (Figure 5—figure supplement 1F) on a longer timescale than TEA. This was not surprising as 4-AP displays prolonged residency within cells by crossing of the plasma membrane (Molgó et al., 1980). These results confirm the stability of our recordings and the reversibility of TEA and 4-AP effects in our experiments.

Our results with TEA and 4-AP alone, however, could not rule out the possible contributions of other K⁺ channels that are also sensitive to either TEA (Kv1, Kv7, and large-conductance Ca²⁺ -activated K⁺ [BK] channels; Al Sabi et al., 2010; Shen et al., 1994; Wang et al., 1998) or 4-AP (Kv1; Shu et al., 2007; Storm, 1988; Wu and Barish, 1992). Thus, we next tested the effects α-dendrotoxin (DTX), XE991, and iberiotoxin (IbTX), which are highly selective antagonists of Kv1.1/1.2/1.6, Kv7, and BK channels, respectively. Upon exposing RAPNs and AId neurons to these antagonists, we observed no significant effects on spontaneous AP half-width or maximum repolarization rate (Figure 4—figure supplement 2A–F) in contrast to the effects of TEA and 4-AP. We also observed little to no effects on spontaneous and evoked firing frequency in RAPNs or AId neurons (Figure 5—figure supplement 2A–F). Importantly, we anticipate these compounds would produce significant effects if the indicated channels were expressed as we note high homology between the mammalian and avian amino acid sequences for these channels (sequence conservation ranged from 77% to 98% with ≥97% conservation between the first and last transmembrane segments for all channels), with previous studies demonstrating effects of both DTX (Rathouz and Trussell, 1998) and IbTX (Moonen et al., 2010) in avian species. Thus, we conclude that Kv3.x subunits are the predominant TEA- and 4-AP-sensitive channels in the recorded arcopallial cells.

RAPNs have a faster, larger, high threshold TEA-sensitive I_K+ than AId neurons

To confirm that the regional differences in our current-clamp recordings were indeed due to differences in the outward voltage-gated K⁺ current (I_K+), we performed voltage-clamp recordings. We note that our recordings are performed in frontal slices that transect RAPN axons near the soma. To further minimize space and voltage-clamp issues, we (1) decreased the slice thickness from 180 µm to 150 µm to eliminate more neuronal processes, (2) lowered intracellular K⁺ from 142.5 mM to 75 mM to decrease the magnitude of I_K, and (3) compensated the series resistance electronically to 1  MΩ. We have previously shown that while these conditions do not offer complete space and voltage-clamp control, they significantly improve these parameters (see Zemel et al., 2021). After pharmacologically isolating I_K+, we delivered sequential 200 ms test pulses to –30 mV and 0 mV, from a 5 s holding potential at –80 mV, to preferentially activate low threshold I_K+ or both low and high threshold I_K+ respectively. Both RAPNs and AId neurons produced outward currents during both depolarizing steps (Figure 6A). Consistent with a difference in expression of a high threshold, non-inactivating I_K+ RAPNs produced significantly larger peak outward currents 200 ms (I_200ms) after stepping to 0 mV (Figure 6A–B; mean ± SE: 12.2±1.2 nA vs. 4.8±0.7 nA for RAPNs and AId neurons, respectively), whereas outward currents were indistinguishable between RA and AId during the –30 mV step (Figure 6B; mean ± SE: 0.8±0.1 nA vs. 0.4±0.04 nA for RAPNs and AId neurons, respectively). We also noted an initial A-type current waveform component in both RAPNs and AId neurons that preceded the larger delayed rectifier component during the 0 mV step (Figure 6A, red shaded area of the current at the 0 mV test pulse). Interestingly, the time to this peak was shorter in RAPNs than in AId neurons (Figure 6C; mean ± SE: 4.7±0.4 ms vs. 6.2±0.3 ms for RAPNs and AId neurons, respectively), even though the I_K+ size was much larger in the RAPNs.

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Informed by our current-clamp pharmacology experiments, we next tested the prediction that I_K+ would be more attenuated by sub-millimolar concentrations of TEA in RAPNs than in AId neurons. Upon washing in 500 µM TEA onto slices we saw decreases in the peak current from neurons in both brain regions (Figure 6D), with RAPNs showing a larger fold change in both the peak of the A-type current component (Figure 6E; mean ± SE: 55.7±4.4% vs 22.0 ± 4.9% decrease for RAPNs and AId neurons, respectively) and in the peak current at I_200ms (Figure 6F; mean ± SE: 41.2±5.2% vs 22.2 ± 7.0% decrease for RAPNs and AId neurons, respectively). We then extracted the TEA-sensitive I_K+ by subtracting the post-TEA traces from the pre-TEA traces. Like the pre-TEA currents obtained at 0 mV, the TEA-sensitive current in both RAPNs and AId neurons had A-type and delayed rectifier components (Figure 6G). By dividing the current 8 ms after the initial A-type peak by the peak A-type current, we found that the degree of inactivation was indistinguishable between RAPNs and AId neurons (Figure 6—figure supplement 1). Notably, the time to peak of the A-type component was preserved (mean ± SE: 4.5±0.4 ms vs. mean ± SE: 5.8±0.4 ms for RAPNs and AId neurons, respectively), with RAPNs maintaining a trend toward smaller values (Figure 6H). Importantly, whether measuring the A-type current peak (Figure 6I; mean ± SE: 4.7±0.4 nA vs. 1.1±0.3 nA for RAPNs and AId neurons, respectively) or the I_200ms peak (Figure 6J; mean ± SE: 5.0±0.7 nA vs. 1.3±0.5 nA for RAPNs and AId neurons, respectively), RAPNs had a significantly larger TEA-sensitive I_K+ than AId neurons. In sum, our voltage-clamp results show a higher proportion of a fast-activating, TEA-sensitive current in RAPNs compared to AId neurons, consistent with the presence of a larger Kv3 current in RAPNs.

Differential mRNA expression of the TEA-sensitive ion channel subunit Kv3.1 in RAPNs vs. AId neurons

The evidence presented thus far is consistent with the ultra-fast APs unique to RAPNs being related to higher expression of Kv3.1 in RA compared to AId. However, Kv3.1 is only one of four members of the Shaw-related channel family (Kv3.1–3.4) in vertebrates (Kaczmarek and Zhang, 2017; Rudy and McBain, 2001). To further examine a link between RAPN properties and Kv3.1, it was important to examine other Kv3.x family members. As a start, through close assessments of reciprocal alignments and synteny we confirmed that the locus named KCNC1 (100144433; located on chromosome 5) is the zebra finch ortholog of mammalian KCNC1, noting the conserved synteny across major vertebrate groups (Figure 7—figure supplement 1A). Importantly, the predicted zebra finch Kv3.1 protein (Kv3.1b isoform) is remarkably conserved (96.5% residue identity) with human (Figure 7—figure supplement 2) and is thus predicted to have similar pharmacology as in mammals, which is supported by our recordings from RAPNs. Additionally, we confirmed the correct identification of the zebra finch orthologs of mammalian KCNC2/Kv3.2 and KCNC4/Kv3.4, as previously reported (Lovell et al., 2013).

Previous investigations of the zebra finch genome (taeGut1, Warren et al., 2010) reported that zebra finches lacked a KCNC3/Kv3.3 ortholog (Lovell et al., 2013). Recent long-read sequencing technology, however, has facilitated a more complete assembly of genomes (Rhie et al., 2021), elucidating the presence of some genes previously thought to be absent. Using RefSeq release 106 (GCF_003957565.2 assembly), we observed a locus (LOC115491734) described as similar to member 1 of the KCNC family on the newly assembled zebra finch chromosome 37, one of the smallest and hardest to sequence avian microchromosomes. LOC115491734, however, exhibited the highest alignment scores and conserved upstream synteny with KCNC3/Kv3.3 in humans and various vertebrate lineages, noting that NAPSA in zebra finch and other songbirds is misannotated as cathepsin D-like (LOC121468878) (Figure 7—figure supplement 1C). We conclude that LOC115491734 is the zebra finch ortholog of mammalian KCNC3, previously thought to be missing in birds (Lovell et al., 2013), and not KCNC1. We have also identified an avian KCNC3 locus in a few other songbird and non-songbird species, noting that in most cases the gene is incorrectly annotated in NCBI as KCNC1 or KCNC1-like, whereas conversely, a large set of avian genes in this family are incorrectly annotated as KCNC3-like (Figure 7—figure supplement 1B–C). Also notably, a KCNC3 locus (XM_009582050.1) previously described as the ortholog of KCNC3 in two seabirds (De Paoli-Iseppi et al., 2017) was misidentified in that study and most likely represents KCNC4 in those species. Interestingly, the downstream immediate synteny is not conserved across vertebrate lineages, with the ancestral condition in tetrapods likely being TBC1D17 downstream of KCNC3. The predicted zebra finch KCNC3 protein showed only moderate conservation with human (68.32% residue identity), some domains including the BTB/POZ and transmembrane domain being fairly conserved, but spans of residues on the N-terminal and C-terminal regions being highly divergent. Notably, based on the genomic sequence, the N-terminal inactivation domain (Rudy and McBain, 2001) is absent in the predicted zebra finch KCNC3 protein (Figure 7—figure supplement 3).

We next performed in situ hybridization for all identified KCNC/Kv3.x family members in adjacent frontal brain sections from adult male zebra finches. We replicated our previous finding that KCNC1/Kv3.1 expression is higher in RA than in AId (Nevue et al., 2020; Figure 7A, top left), whereas expression of both Kv3.2 (Figure 7A, top right) and Kv3.4 (Figure 7A, bottom right) was non-differential between RA and AId. Unlike the graded Kv3.1 expression that matches a tonotopic distribution found in avian (Parameshwaran et al., 2001) and mammalian (Li et al., 2001) auditory brainstem, Kv3.1 expression was uniformly distributed across RA. Kv3.2-expressing cells were sparse, strongly labeled, and reminiscent of the GABAergic cell distribution (Pinaud and Mello, 2007), while Kv3.4 expression was uniformly weak throughout both brain regions (Figure 7A). We also found that Kv3.3, while more strongly expressed in both brain regions compared to the surrounding arcopallium, is non-differentially expressed between RA and AId (Figure 7A, bottom left). Importantly, we found strong Kv3.3 expression in the Purkinje cell layer of the cerebellum (Figure 7A, bottom left), consistent with findings in mammals (Akemann and Knöpfel, 2006). Furthermore, other TEA-sensitive potassium channel subunits examined, namely members of the Kv1 (KCNA), BK (KCNMA), and Kv7 (KCNQ) families, had similar expression in RA and AId, with the exception of KCNQ2, which had a lower proportion of labeled cells in RA than in AId (Figure 7B and C). These results indicate that compared to the other TEA-sensitive channels, KCNC1/Kv3.1 is the only TEA-sensitive subunit we examined that was more highly expressed in RA compared to AId, providing supporting evidence for a stronger contribution of Kv3.1 in shaping the ultranarrow AP of RAPNs compared to AId neurons.

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Intriguingly, while curating avian KCNC3s, we discovered a previously undescribed KCNC family member in the genomes of several bird species, but notably absent in songbirds (Figure 7—figure supplement 1B), a finding that cannot be explained by gaps in genomic sequence in the latter. This gene most closely resembled KCNC1 in predicted domains and amino acid conservation, thus we named this KCNC1 paralog as KCNC1-like (KCNC1L). We also observed KCNC1L in non-avian sauropsids including lizards and snakes, where the locus seems to be duplicated. It was not present in humans/mammals, nor in amphibian or fish outgroups. This suggests this paralog possibly arose after the split between mammals and sauropsids, with a subsequent loss in songbirds. Overall, while our comparative analysis helps to further link the differential expression of KCNC1/Kv3.1 to physiological differences between RA and AId, it also brings new insights into the evolution of this key family of neuronal excitability regulators. How the newly identified avian KCNC3 and non-oscine KCNC1L contribute to avian neuronal physiology are intriguing questions for future studies.

AUT5 narrows the AP half-width and increases the firing rate of RAPNs

Whereas pharmacological inhibitors provided strong evidence of a major role for Kv3.x channels in RAPNs compared to AId neurons (Figures 4—6), they notably lack the specificity for Kv3.x subunits. In contrast, the specific (Covarrubias et al., 2023), novel positive Kv3.1/3.2 modulator, AUT5, potentiates Kv3.1 currents by speeding up activation kinetics (Taskin et al., 2015) and leftward shifting the voltage dependence of activation (Taskin et al., 2015; Covarrubias et al., 2023). To examine AUT5 effects, we recorded both spontaneous (Figure 8A and C, left) and evoked (Figure 8B and D, left) APs from RAPNs and AId neurons in the whole-cell current-clamp configuration, before and during exposure to 1 µM AUT5 (EC₅₀ = 1.3 µM, Taskin et al., 2015). Compared to pre-drug measurements, RAPNs showed a significant narrowing of the AP waveform (mean ± SE: 6.5 ± 2.1% decrease; Figure 8A, middle) and an increase of the maximum repolarization rate (mean ± SE: 12.2 ± 4.3% increase; Figure 8A, right) but not of the maximum depolarization rate (paired t-test, t_stat = 1.04, p=0.3), whereas no significant effects were seen in AId neurons (Figure 8C, middle and right). Spontaneous APs from RAPNs also displayed significant depolarizations in the peak (mean ± SE: 35.1±1.1 mV to 38.9±1.2 mV, paired t-test, t_stat = 2.72, p=0.03), threshold (mean ± SE: –58.9±1.8 mV to –57.0±1.6 mV, paired t-test, t_stat = 3.542, p=0.01), with a non-significant trend observed for the peak after-hyperpolarization (mean ± SE: –72.0±0.7 mV to –71.1±0.7 mV, paired t-test, t_stat = 2.3, p=0.06). We note, that the depolarization in the AP peak could in turn further recruit Kv channel-mediated AP repolarization. In comparison AId only showed a modest change in the after-hyperpolarization (–69.6±1.1 to –67.3±0.6, paired t-test, t_stat = 2.874, p=0.03). These changes in the spike waveform correlated with a significant increase in evoked spikes produced in RAPNs that was not seen in AId neurons (Figure 8B and D; mean ± SE: 25.7% ± 6.1% for RAPNs during the 1 s + 500 pA current injection). This effect is consistent with AUT5 effects observed in the Kv3.1 expressing hippocampal GABAergic interneurons of rats (Boddum et al., 2017). Interestingly, whereas AUT5 had no effects on the instantaneous firing frequency in RAPNs, the steady-state firing frequency (as measured for the last two spikes recorded during the 1 s + 500 pA current injection) increased substantially (mean ± SE: 24.3 ± 8.2% increase). We did not observe significant washout with AUT5. This result was not surprising as previous studies indicate limited capacity for washout of this compound, even within cell lines (Taskin et al., 2015). Taken together, these results are again consistent with the finding of higher Kv3.1 expression in RAPNs than in AId neurons, and further support the role for Kv3.1 in the specialized fast firing properties of RAPNs compared to AId neurons.

Figure 8

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Our results demonstrate that RAPNs and AId neurons share several properties, including spontaneous firing, minimally adapting firing during current injections and similar expression profiles of KCNC2–4 (Kv3.2–3.4) subunits. However, they differ greatly in AP spike half-width and capacity for high-frequency firing. We show that these unique RAPN properties, which are reminiscent of the large Betz cells in layer 5 of primate M1 cortex, are associated with higher expression of KCNC1 (Kv3.1) in RA than in AId. In contrast, the properties of AId neurons, which are involved in non-vocal somatic motor function in birds, are more similar to those of canonical mammalian L5PNs. We propose that RAPNs are highly specialized neurons for song production, sharing with primate Betz cells some unique physiological and molecular properties that allow both cell types to reliably fire ultranarrow spikes at high frequencies.

A source Excel data file is included with the manuscript and a raw data file has been uploaded to the DRYAD data base (DOI https://doi.org/10.5061/dryad.1zcrjdfvs).

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Decision letter after peer review:

Thank you for submitting your article "Cortical Betz cells analogue in songbirds utilizes Kv3.1 to generate ultranarrow spikes" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by John Huguenard as the Senior Editor. The following individual involved in the review of your submission has agreed to reveal their identity: Ian D Forsythe (Reviewer #1).

The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.

Essential revisions:

1) The correspondence between RA cells and cortical Betz cells is a stretch.

This seems more of a discussion point than an essential part of the title, abstract, or introduction.

2) The evidence of a specific role for Kv3.1 is not conclusive and relevant claims should be moderated.

3) A valuable pharmacological approach is used. Evidence of stability of responses and reversibility of drug effects should be provided for each of the major findings.

Reviewer #1 (Recommendations for the authors):

This is an extensive piece of work and it contains some good quality data, but the great breadth of the article means that many elements of the results are too superficial and/or lack sufficient detail to deal with certain aspects and complexities of Kv3 physiology. There are also some problems in the interpretation of the voltage-clamp data which together weaken the overall findings.

1). Page 1. The first paragraph of the introduction over-emphasises a link to mammalian Betz cells; this would seem better justified as a discussion point. Perhaps you feel the need to justify the avian system to mammalian-biased readers, but the lack of transgenic zebrafinch models undermines the strength of your arguments for doing this work in the bird.

2) Page 3. Morphology. While the detail and work conducted in contrasting the morphology of RA and AId neurons are appreciated, your cell numbers are low (only 2 AId neurons) and this reduces the confidence in the observed differences. Also, many of the parameters are presented as % differences – this would be better presented as different absolute values (these are often only shown on the figure graph and are difficult to estimate). It is not clear how the observed differences relate to the Kv3 question, other than in establishing some convergence with mouse cortical neurons. This could be a distinct study in itself but is not a good fit for this manuscript.

3) Page 4 ln 179. Electrophysiology. The data is usefully presented in absolute terms in Table 1, but the differences should be described in the same terms, not as % (as in ln192) nor as qualitative comments (as in lns 198 – 203).

4) Page 5, ln 208-217. This is a methodological aside and is not relevant except to demonstrate the care that the authors have taken to exclude inhibitory neurons from their data set.

5) Page 5, ln 230-254. The data is consistent with a larger effect of TEA and 4-AP on RA repolarization. Again, absolute measures of duration rather than % change should be quoted and compared for the data in figure 4. This will be important if anyone were to model these conductances and neuronal properties in the future. APs in the Ald neurons are already longer, so a similar effect of TEA or 4AP might be expected to be proportionally smaller (if presented as %).

Figure 4 clearly shows that TEA and 4-AP have direct effects on the AP of RA cells, but less so on Aid cells. But you can only infer that this is mediated by an action on Kv3 channels. The data is very difficult to interpret as all the numerical graphs are presented in fold change in AP halfwidth. How long were the drugs applied, and was recovery data collected to demonstrate washout? It is a pedantic point, but have you checked that the pharmacological evidence cited (from mammals) applies to birds? Since you show no effect in Supl Figure 4, a key issue would be: does α-DTx or iberiotoxin block Kv1 and BK channels (respectively) in the bird; have you positive controls or can you provide citations of such (or at least checked for precise homology at the respective toxin binding sites)?

6) The effect of TEA and 4AP differs in figure 5 (first AP) from figure 4 (AP train). The effect on the half-width of the 1st AP seems smaller than on subsequent APs in the train – particularly noticeable in 5A and 5B. What is the explanation for this (see point 8 below)?

7) The AP duration is also changing during the trains in Supl Figure 5. There are a few minor inconsistencies here. For example, XE991 has a significant effect in the lowest current injections in S5c. The control peak firing rates (spikes/sec) in S5E are lower (~70 vs ~100) than in S5A and S5C.

8) Page 6 and figure 6. Voltage-clamp data is well presented and clearly shows larger outward currents in the RA neurons, with little or no 'low-voltage-activated' (steps to -30 mV; potential DTx-sensitive current) in either neuron type. The 'high-voltage activated' currents are very slow activating… And so would be hardly activated during a single fast AP lasting less than a ms….. This undermines your arguments that this is Kv3 on two counts: it is too slow to activate (taking over 100ms) and only differs by around 25% between RA and AId neurons. The key current for the AP repolarization, especially for the first AP in a train, is most likely to be the fast inactivating current. From the evidence in figure 6, it is not clear that this is a classic A-current (Kv4), because no estimation of steady-state inactivation has been conducted.

Although this undermines your current hypothesis that this is a Kv3.1 current, the possibility that the Kv3 current is fast inactivating (i.e. a Kv3.3 or Kv3.4-like current) is very interesting. In Figure 6G, you appear to show that both the inactivating and slow-activating outward currents are TEA-sensitive. Because the activation of the slow outward current overlaps with the decay of the fast transient outward current, any estimation of one will be contaminated by the other. Ideally, you could steady-state inactivate the transient current so you can measure the slow-activating current. This would then allow you to estimate the 'contamination' of one current by the other.

9) P7 ln 335. Another paper has described kcnc3/Kv3.3 in a seabird (De Paoli-Iseppi et al. PLOS One 12: e0189181, 2017).

10) Figure 7 and Page 7/8. The heading on ln 319 states, that Kv3.1 is the TEA-sensitive ion channel subunit… But this seems a rather weak point and could be disputed, as you have measured mRNA, not protein (and the interpretation of the current is ambiguous). The in situ hybridisation for each of the Kv3 genes is interesting, but the quantification is insufficient. The lack of absolute values (or at least relative to some 'housekeeping' gene) for the mRNA expression is a serious weakness. The ratios expressed here between two nuclei in Figure 7 hide/obscure important information and have contributed to the misinterpretation of the physiology. For example, one could argue on the basis of Fig7A that all Kv3 genes are present and that kcnc3 is most striking in that it highlights the two nuclei of interest, is present in both and you have the positive control of Purkinje neurons. Fig7B and 7C are best omitted… The expression ratio of RA to Ald has little or no relevance to a measurable parameter in your study. Perhaps you could argue some relevance if you had done a more quantitative measure and/or western blotting, but this has not been done. Your own evidence clearly indicates that multiple Kv3 subunits are present (Figure 7A), but you have no measure of the efficacy with which the mRNA is translated into protein (it is also hard to know what constitutes a 'background' value for any of the mRNA probes).

11. AUT5. This is not a well-designed experiment, since you apply a dose that is half-maximal (1uM when the EC50 is 1.3uM: ln 391), so you would be unlikely to observe more than half of the potential effect. For most readers, this comes across as a rather minor point and I think they will wonder why they need to know this information, certainly it is a weak figure with which to finish. Perhaps if AUT5 was shown to change the finch song or other behaviour in the opposite way to blocking the channel it would be interesting. AUT5 effects have also been noted previously in other publications:

2015. Biophysical characterization of KV3.1 potassium channel activating compounds. Taskin B, von Schoubye NL, Sheykhzade M, Bastlund JF, Grunnet M, Jespersen T.

Eur J Pharmacol. 2758:164-70.

2017. Kv3.1/Kv3.2 channel positive modulators enable faster activating kinetics and increase firing frequency in fast-spiking GABAergic interneurons. Boddum K, Hougaard C, Xiao-Ying Lin J, von Schoubye NL, Jensen HS, Grunnet M, Jespersen T. Neuropharmacology, 118:102-112.

Reviewer #3 (Recommendations for the authors):

This paper was a pleasure to read and goes through a logical sequence of experiments to pinpoint the role of Kv3(.1?) in the fast-spiking of RAPN neurons. There are large replicate numbers for almost all findings, and admirably, there is confirmation of the main result at physiological temperature. The phase plots in Figure 4 make clear that 4AP and TEA, at the concentrations used, have little effect on Ald neurons, but strong effects on RAPNs in both current clamp and voltage clamp. The methods developed to improve voltage clamp compliance are to be commended.

1) The paper has an unclear focus. In some ways, it focuses on the properties of RAPN neurons and how they might generate fast APs. Yet in other contexts, the paper seems to center on the description of a previously uncharacterized cell type, the neurons of Ald.

2) The pharmacological analysis of repetitive spike firing is lacking. For example, the traces in Figure 5B and 5D, and 8B and 8D, DO in fact show effects of 4AP/TEA/AUT5 on Ald neurons. This raised two issues. A) Repeated measures, such as a paired t-test I (before and after the drug, on a per cell basis) are arguably more appropriate than group averages at each current injection strength. B) Some effort should be dedicated to reversibility. While it can be technically challenging to hold a cell for the total time required to completely wash out the drug, at least a few examples should be provided to confirm that "drug" effects are not due to time-dependent changes in cell physiology.

3) For fast repolarization, it would likely be better to focus mainly on the early current, highlight with the red bars in figure 6, rather than on the current persisting until 200 ms.

4) There is a bit of circular logic regarding the description of the effects of AUT5 on spike depolarization (Figure 8A). If RA affects the maximum depolarization, then this could secondarily increase the recruitment of K channels and in turn produce a faster rate of repolarization.

5) While voltage clamp compliance is likely much improved by the approaches taken, it will still not be perfect, and there will remain issues of non-isopotentiality. This should be discussed.

6) The correspondence to Betz cells is oversold and should be removed from the title and abstract. There are many differences, as the authors note. A) The RA cells are not necessarily larger than other motor output neurons as with Betz cells, B) They have presumably developed along a unique evolutionary path, C) Other central features of Betz cells (conduction velocities, myelination, axon fiber diameter) are not reported.

Essential revisions:

1) The correspondence between RA cells and cortical Betz cells is a stretch.

This seems more of a discussion point than an essential part of the title, abstract, or introduction.

We agree with this request, as we may have initially overemphasized the analogy between RA projection neurons and Betz cells. We have now (1) removed the comparison with Betz cells from the Title, (2) tempered our language in the Abstract, where we now clarify that RA projection neurons and Betz cells share some physiological and molecular properties, and (3) removed the opening paragraph in the Introduction that discusses mammalian Betz cells, in favor of the second paragraph introducing the zebra finch model to study aspects of fine, fast motor control. As also suggested by the reviewer, we expand the comparison between RA projection neurons and Betz cells in the Discussion, noting that we also disclose several differences between these cell types.

2) The evidence of a specific role for Kv3.1 is not conclusive and relevant claims should be moderated.

We agree that we cannot conclude from our data that Kv3.1 is the sole voltage-gated K⁺ channel responsible for AP repolarization in RA projection neurons. Our title has changed now to mention “Kv3 subunits”. However, we have found marked contrasts in excitable properties (e.g. spike half-width, maximum repolarization rate) between upper motor neurons in RA and AId, and thus identified physiological specializations characteristic of just RA projection neurons (RAPNs). The molecular data also give clear indication that Kv3.1 is differentially expressed between RAPNs and AId neurons, in contrast to the other TEA-sensitive Kv3 family members, which are not differentially expressed between RA and AId. Coupled with the data from the Kv3.1/Kv3.2 specific agonist, AUT5, we argue that Kv3.1 is the most likely subunit to explain the difference in spike properties between these two regions. Importantly, our paper shows the presence of Kv3.3 in RA and AId and also possible functional evidence of Kv3.4, since we show that a component of the K currents inactivates very quickly (see Figure 6A and 6G).

To address this important issue, we have changed the wording throughout the manuscript to moderate our claims about a unique role of Kv3.1 in RA. This includes changes in the Title (line 1), Abstract (line 31-35), Results (line 395-399, 409-410, 446), Figure Legends (line 1592, 1624) and Discussion (line 546, 551-553). We have also added a new paragraph at the beginning of Results (lines 105-116) to clarify the rationale for our regional comparative approach.

3) A valuable pharmacological approach is used. Evidence of stability of responses and reversibility of drug effects should be provided for each of the major findings.

We show evidence of stability and reversibility of drug effects in an added new figure (Figure 5—figure supplement 1), and describe the washout of TEA, 4-AP and AUT5 in a related passage of Results (lines 262-271, 442-444), and provide further details in Methods (lines 894-897). We note that the opposing effects of AUT5 versus 4-AP and TEA, as well as the stability of recordings during administration of iberiotoxin already provide an indication of stable recordings that can be differentially affected depending on the types of compounds applied to our slices, but we agree that the additional requested data help to solidify the study.

Reviewer #1 (Recommendations for the authors):

This is an extensive piece of work and it contains some good quality data, but the great breadth of the article means that many elements of the results are too superficial and/or lack sufficient detail to deal with certain aspects and complexities of Kv3 physiology. There are also some problems in the interpretation of the voltage-clamp data which together weaken the overall findings.

1) Page 1. The first paragraph of the introduction over-emphasises a link to mammalian Betz cells; this would seem better justified as a discussion point. Perhaps you feel the need to justify the avian system to mammalian-biased readers, but the lack of transgenic zebrafinch models undermines the strength of your arguments for doing this work in the bird.

We thank the reviewer for the detailed and helpful comments. We agree with the assessment that we overemphasized the similarities to mammalian Betz cells, and have now eliminated the opening paragraph of the Introduction, while reserving that topic for the Discussion. The Introduction now starts with the paragraph where we introduce zebra finches as a useful model for studying regulation of intrinsic neuronal excitability in the context of refined, fast motor control. In that regard, we note that more traditional genetic models like mice lack the equivalent of a cortical vocal nucleus like RA and its specialized projection neurons, as well as the vocal learning behavior this nucleus subserves. Thus, in spite of the current limitations in applying transgenic methods to these birds, their use provides a unique opportunity to study features of fine motor control systems that are uniquely shared with primates and not apparent in rodents.

2) Page 3. Morphology. While the detail and work conducted in contrasting the morphology of RA and AId neurons are appreciated, your cell numbers are low (only 2 AId neurons) and this reduces the confidence in the observed differences. Also, many of the parameters are presented as % differences – this would be better presented as different absolute values (these are often only shown on the figure graph and are difficult to estimate). It is not clear how the observed differences relate to the Kv3 question, other than in establishing some convergence with mouse cortical neurons. This could be a distinct study in itself but is not a good fit for this manuscript.

The reviewer brings up relevant points about the cell morphology analysis. While we agree that the cell morphology analyses we presented do not directly relate to the Kv3-related experiments, ours is a first characterization of neuronal morphology in AId, and how it compares to RAPN morphology. Importantly, while the N of the elaborate ShuTu analysis was small, it was meant to complement the findings from our more extensive FIJI analysis (N=6 per cell-type). The ShuTu analysis confirmed, using a different approach, the findings of cell type differences in spine density and dendrite area. To fully address the reviewer’s request, we now also present our ShuTu measurements as average absolute values of the surface area of different neuronal compartments for both cell types, besides % differences (lines 149-150). We also note that we refer to the limitations of these datasets in Results (lines 151-152) and state in the Discussion that they lay the groundwork for future more detailed morphological studies (lines 487-490, 502-503).

3) Page 4 ln 179. Electrophysiology. The data is usefully presented in absolute terms in Table 1, but the differences should be described in the same terms, not as % (as in ln192) nor as qualitative comments (as in lns 198 – 203).

We agree with the reviewer’s request and now also present the differences in various parameters in terms of absolute average values, not only percentages (line 189-194). We have also eliminated the related qualitative comments that were originally at the end of the paragraph.

4) Page 5, ln 208-217. This is a methodological aside and is not relevant except to demonstrate the care that the authors have taken to exclude inhibitory neurons from their data set.

In agreement with the reviewer’s comment, we have now moved this section to Methods.

5) Page 5, ln 230-254. The data is consistent with a larger effect of TEA and 4-AP on RA repolarization. Again, absolute measures of duration rather than % change should be quoted and compared for the data in figure 4. This will be important if anyone were to model these conductances and neuronal properties in the future. APs in the Ald neurons are already longer, so a similar effect of TEA or 4AP might be expected to be proportionally smaller (if presented as %).

We thank the reviewer for this suggestion, as we are also interested in future modeling of these neuronal properties. We now present the absolute average measures with standard errors in addition to the % change in the description of the data shown in Figure 4 (lines 237-248). We also note that the individual paired data are shown in Figure 4—figure supplement 1.

Figure 4 clearly shows that TEA and 4-AP have direct effects on the AP of RA cells, but less so on Aid cells. But you can only infer that this is mediated by an action on Kv3 channels. The data is very difficult to interpret as all the numerical graphs are presented in fold change in AP halfwidth. How long were the drugs applied, and was recovery data collected to demonstrate washout? It is a pedantic point, but have you checked that the pharmacological evidence cited (from mammals) applies to birds? Since you show no effect in Supl Figure 4, a key issue would be: does α-DTx or iberiotoxin block Kv1 and BK channels (respectively) in the bird; have you positive controls or can you provide citations of such (or at least checked for precise homology at the respective toxin binding sites)?

As discussed above, we now present the absolute values in the text. We also include information on drug application times in the Methods (lines 894-897). Additionally, we now show wash out experiments with TEA, 4-AP and AUT5. The effects of TEA were almost completely reversed within 3 minutes of washout. We also observed a significant, but not complete washout with 4-AP on a significantly slower timescale than TEA. We did not observe a significant reversal of the effects of AUT5. This was not surprising, as a previous publication (Taskin et al., Eur. J. Pharmacol., 2015) has indicated that this compound does not washout readily. Nevertheless, these results confirm the stability of our recordings throughout the duration of our experiments. These data are now described in a new Figure 5—figure supplement 1, the figure legend, and the Results section (see lines 262-271, 442-444).

With regard to the effects of DTX and BK channels on neuronal excitability in birds, we note that both of these compounds have previously been shown to affect cellular properties in avian species. For example, administration of DTX in the nucleus magnocellularis in the chicken inhibits low threshold potassium currents (Rathouz and Trussell, J. Neurophysiol., 1998). Additionally, iberiotoxin inhibits a ca²⁺-dependent potassium current in the chicken ductus arteriosis (Moonen et al., Neonatology, 2010). We additionally performed amino acid sequence alignments for Kv1.1, Kv1.2, Kv7.2, Kv7.3 and BK channels between humans and zebra finches. We found that the percent identity was 93%, 98%, 77%, 84% and 92% respectively. Kv1.1 and 1.2 both contained high conservation (>95%) in the region between S5 and S6 implicated in the binding of α-DTX (Hurst et al., Mol. Phamacol. 1991, Tytgat et al., J. Biol. Chem., 1995). We additionally note a near 100% conservation of the S1-S6 region of Kv7.2 (97% identity) and Kv7.3 (99% identity) between zebra finches and humans. We also note that the BK channel showed remarkable conservation with 98% identity of the S0-S6 domains. Lastly, we note that there were detectable effects on evoked AP firing in RAPNs from administration of DTX. These effects appeared to be restricted to inter-spike periods and not the AP waveform, as shown in Figure 4—figure supplement 2A and Figure 5—figure supplement 2A. Thus, while this drug can exert detectable effects on finch RAPNs, we did not observe significant effects on their AP halfwidth. We now comment on these important aspects in lines 282-288.

6) The effect of TEA and 4AP differs in figure 5 (first AP) from figure 4 (AP train). The effect on the half-width of the 1st AP seems smaller than on subsequent APs in the train – particularly noticeable in 5A and 5B. What is the explanation for this (see point 8 below)?

We appreciate the reviewer’s comments. Regarding the first sentence, the examples shown in Figure 4 are spontaneous APs which were recorded with no current being injected. Figure 5 shows a train of APs evoked by a +500 pA current injection. Both RAPNs and AId neurons display broader APs, including the first AP, with the administration of TEA and 4-AP. The APs being shown in Figures 4 & 5 are on very different timescales, making visual comparisons of the halfwidth changes in these APs difficult to assess.

Regarding the second point, the increase in width of the subsequent APs in Figure 5 may be due to the accumulation of voltage-gated Na⁺ channels and/or A-type potassium channels in inactivated states. The decrease in Nav and/or Kv channel availability may add to the increase in the width of the subsequent APs in the train due to a relatively slower depolarization and/or repolarization rate. We note that this adaptation is described in our previous publication (Zemel et al., Nat. Commun., 2021), in which we show the first AP in a train (at +500 pA) is narrower, with significantly greater rates of depolarization and repolarization than subsequent APs. In order to acknowledge this adaption, we have changed our reference to RAPN and AId neuron firing as non-adapting to minimally adapting in the text (Lines 452,518).

7) The AP duration is also changing during the trains in Supl Figure 5. There are a few minor inconsistencies here. For example, XE991 has a significant effect in the lowest current injections in S5c. The control peak firing rates (spikes/sec) in S5E are lower (~70 vs ~100) than in S5A and S5C.

We appreciate again the reviewer’s comments, and refer the reviewer to the response to the previous comment to address the first sentence.

Regarding the second sentence, we acknowledge that there were indeed some changes in the evoked firing rates on APs in RAPNs in response to XE991. The statistical differences were shown in the legend of Figure 5—figure supplement 2. These findings in fact provide further supportive evidence that these drugs were exerting effects on neuronal cell excitability in finches, and suggest that Kv7 may contribute to the spike rates of RAPNs. Importantly, however, XE991 exerted no detectable effects on AP halfwidth or maximum rate of repolarization, as evidenced from the data from spontaneously firing APs in Figure 4—figure supplement 2. The difference in spontaneous firing rates of RAPNs exposed to XE991, while modest, may reflect the relative weight of the Kv7 conductance when cells are sparsely firing versus at more depolarized voltages during positive constant current injections, when additional voltage dependent conductances are more heavily recruited.

Regarding the third sentence, we acknowledge that on average the control peak firing rates are lower in Figure 5—figure supplement 2E compared to 2A and 2C. But these differences are very small, within the standard error for half of the current injection levels. Specifically, the averages for the controls in 2A and 2E were 35.2 ± 2.2 vs. 39.7 ± 4.3 at +100 pA, 53.8 ± 3.1 vs. 54.3 ± 5.6 at +200pA and 68.3 ± 4.1 vs. 64.5 ± 6.2 at +300pA. While the values for current injections above +300 pA were indeed lower the variability of the data in 2E was clearly greater, as indicated by the standard error. Taken together, while we cannot be certain as to what caused the decreased averages and higher variability in the two data points in Figure 5—figure supplement 2E, we do show that the RAPN evoked firing properties are remarkably consistent across experimental conditions (Figure 5, Figure 8, Figure 5—figure supplement 2).

8) Page 6 and figure 6. Voltage-clamp data is well presented and clearly shows larger outward currents in the RA neurons, with little or no 'low-voltage-activated' (steps to -30 mV; potential DTx-sensitive current) in either neuron type. The 'high-voltage activated' currents are very slow activating… And so would be hardly activated during a single fast AP lasting less than a ms….. This undermines your arguments that this is Kv3 on two counts: it is too slow to activate (taking over 100ms) and only differs by around 25% between RA and AId neurons. The key current for the AP repolarization, especially for the first AP in a train, is most likely to be the fast inactivating current. From the evidence in figure 6, it is not clear that this is a classic A-current (Kv4), because no estimation of steady-state inactivation has been conducted.

Although this undermines your current hypothesis that this is a Kv3.1 current, the possibility that the Kv3 current is fast inactivating (i.e. a Kv3.3 or Kv3.4-like current) is very interesting. In Figure 6G, you appear to show that both the inactivating and slow-activating outward currents are TEA-sensitive. Because the activation of the slow outward current overlaps with the decay of the fast transient outward current, any estimation of one will be contaminated by the other. Ideally, you could steady-state inactivate the transient current so you can measure the slow-activating current. This would then allow you to estimate the 'contamination' of one current by the other.

We appreciate the thoughtful comments from the reviewer. We acknowledge that there is indeed a discrepancy between the time to the peak outward K⁺ current and the AP duration measured in RAPNs and AId neurons. There are a number of technical reasons that could explain this: (1) While we have identified conditions that maximize our ability to obtain high quality voltage-clamp recordings from RAPNs (see Zemel et al., Nat. Commun., 2021), we note that our cells likely retain some complex processes consisting of dendrites and local axon collaterals. This non-spherical geometry likely limits isopotentiality in our recordings, limiting our ability to accurately measure the speed of the onset of these currents. (2) While we successfully eliminated the vast majority of the Nav currents during our experiments using TTX, we note that our previous estimates of the Na⁺ current during the AP upstroke was ~65 nA (Zemel et al., Nat. Commun., 2021). We thus posit that a residual Na⁺ current that might remain even after administration of 1 µM TTX could limit our ability to fully isolate and measure the onset of the K⁺ current. (3) Under physiological conditions the outward K⁺ currents were too large to measure accurately. As stated in Methods, we lowered our intracellular K⁺ concentration by half in an attempt to limit the size of the outward current. This in turn reduces the current size, even at very early timepoints.

Nevertheless, we were able to reliably obtain outward K⁺ currents under the same experimental conditions from RAPNs and AId neurons. We note that the larger currents with shorter time to peak in RAPNs compared to AId neurons are consistent with a differential expression of Kv currents in these brain regions. Taken together with the differential expression of Kv3.1, but not other TEA-sensitive Kvs, our voltage clamp data provides further indication that Kv3.1 likely contributes to this difference between RAPNs and AId neurons.

We also agree with the reviewer that the overlap of any delayed rectifier current with the decay of the fast, transient outward current obscures any measurement of either of these components individually. The TEA sensitivity of these currents does suggest that Kv3 channels likely exist as heteromultimeric complexes, that include Kv3.4. This point is discussed in lines (584-588). While further studies on the components of the K⁺ current are of great interest to us, the data are consistent with a differential expression of a high-threshold, TEA-sensitive Kv channel between RAPNs and AId neurons.

9) P7 ln 335. Another paper has described kcnc3/Kv3.3 in a seabird (De Paoli-Iseppi et al. PLOS One 12: e0189181, 2017).

We thank the reviewer for pointing out this reference, which had previously escaped us. Contrary to the conclusions by De Paoli-Iseppi et al., however, we stand by our assertion that ours is the first description of the KCNC3/Kv3.3 in a bird. The basis for this statement is several-fold:

1) The locus identified in De Paoli-Iseppi et al. as the presumed fulmar KCNC3 ortholog turns out to be the fulmar KCNC4 ortholog, not KCNC3, as in fact acknowledged in their own S1 File, Table K. The accession number the authors provided (XM_009582050.1) is described in NCBI’s Refseq as Fulmarus glacialis potassium voltage-gated channel, Shaw-related subfamily, member 4 (KCNC4), transcript variant X1, mRNA. BLAST alignments of this transcript indeed reveal high hits only to KCNC4 in birds, sauropsids and mammals, including humans, thus this is clearly KCNC4, not KCNC3.

2) BLAST alignments of the primers (File S1, Table A in De Paoli-Iseppi et al) used to amplify the presumed CpG region of KCNC3 in the fulmar fully align to a scaffold (NW_009228155.1) that contains no trace of KCNC3, KCNC4, or any other voltage-gated ion channel, so the claim that these primers amplify a regulatory region of these genes cannot be verified;

3) Our study is the first to describe the KCNC3 genomic locus, including its synteny. Notably, the locus is on zebra finch chromosome 37, whose equivalent has not been assembled in either the fulmar or the shearwater, as well as in most other bird species. This hard to characterize microchromosome has only been completed in very few avian species, requiring the latest advances in long-read sequencing and assembling technologies (Rhie et al., 2021), which helps to explain why this remains an undefined locus in the majority of bird species.

4) There are no significant hits to a KCNC3-like locus in fulmar or shearwater in our unbiased BLAST searches of genomic databases using as queries the identified KCNC3 in zebra finch, gyrfalcon and kakapo. Altogether, we conclude that the locus mentioned as KCNC3 was erroneously identified as KCNC3 and most likely is KCNC4. We have added an explanatory comment with regard to this misannotation in the Results. We also provide further details of our curation/annotation efforts in Methods, as well as include in the legend of Figure 7—figure supplement 1 the loci numbers for all avian genes that were misannotated in NCBI and that we have reannotated as part of our curation effort.

10) Figure 7 and Page 7/8. The heading on ln 319 states, that Kv3.1 is the TEA-sensitive ion channel subunit… But this seems a rather weak point and could be disputed, as you have measured mRNA, not protein (and the interpretation of the current is ambiguous). The in situ hybridisation for each of the Kv3 genes is interesting, but the quantification is insufficient. The lack of absolute values (or at least relative to some 'housekeeping' gene) for the mRNA expression is a serious weakness. The ratios expressed here between two nuclei in Figure 7 hide/obscure important information and have contributed to the misinterpretation of the physiology. For example, one could argue on the basis of Fig7A that all Kv3 genes are present and that kcnc3 is most striking in that it highlights the two nuclei of interest, is present in both and you have the positive control of Purkinje neurons. Fig7B and 7C are best omitted… The expression ratio of RA to Ald has little or no relevance to a measurable parameter in your study. Perhaps you could argue some relevance if you had done a more quantitative measure and/or western blotting, but this has not been done. Your own evidence clearly indicates that multiple Kv3 subunits are present (Figure 7A), but you have no measure of the efficacy with which the mRNA is translated into protein (it is also hard to know what constitutes a 'background' value for any of the mRNA probes).

The reviewer brings up important points with regard to mRNA expression of Kv3 subunits. In retrospect, we agree that the heading of that section may have been somewhat misleading, and have adjusted it accordingly. It was not our intention to claim that Kv3.1 is the sole channel in this family that is expressed in RAPNs, or that it is the sole determinant of RAPN properties, nor was our intention to disprove the possible contributions of other Kv3 family subunits to RAPN properties. Our goal was to demonstrate that Kv3.1 differential expression in RAPNs vs AId neurons in a pattern consistent with the regional differences in their electrophysiological properties, thus indicative of Kv3.1 playing a larger role in RAPNs compared to AId neurons. In that regard, we disagree that our analysis is misleading or irrelevant. We do show that other Kv3s are expressed in RAPNs, but we are saying that their mRNA expression patterns are inconsistent with the differences seen between RAPNs and AId spikes. Thus, these other family members are less likely to contribute to the differences in electrophysiological properties seen between RAPNs and AId neurons. We agree that the Kv3.3 pattern is interesting, suggesting a prominent role of this subunit in both RAPNs and AId neurons, but the high Kv3.3 expression in both areas is inconsistent with the differential electrophysiological properties seen between these two regions. We have modified the relevant passages of the text to make these points more clearly (see lines 85-87, 105-116, 395-399, 409-410, 446, 546, 551-553, 1592, 1624).

To further address the reviewer’s concerns, and for disclosure and completeness, we note that the absolute values of our densitometric analysis that were used to generate the ratios are provided in the corresponding tab 7B and 7C of the Source Data file that accompanies the manuscript, as is also done for electrophysiological parameters. We also note that the in situ signal is sensitive to differences in probe length, hybridization strength and stringency conditions, and does not involve counts of mRNA molecules, thus the values do not allow us to conclude which specific subunit is most highly expressed in RAPNs, which again was not our goal. We closely examine probe specificity through genomic alignment of probe sequences, and our in situs are run under optimized hybridization conditions that result in no detectable signal upon omission of probe or anti-dig antibody. Background levels as measured in tissue areas devoid of cells are well below the cellular levels measured for each of the probes used, as attested in the Source Data file. Furthermore, the large number of probes in Figures 7B/C that show no differences between regions essentially play a normalizing role (similar to the request for “housekeeping” gene data), showing that transcript of various lengths and sequences are not differential between RAPNs and AId neurons, and further helping to establish the specificity of the differential expression of Kv3.1 between RAPNs and AId. Lastly, we agree that we cannot directly infer protein levels from mRNA expression, and note that there is currently no published use of Kv3.1 antibodies in the zebra finch. However, based on parsimony, we think it is reasonable to infer that the Kv3.1 mRNA pattern correlates better with the electrophysiological differences between RAPNs and AId neurons than any of the other subunits examined. We have edited several passages in Methods and Results to address these important points.

11. AUT5. This is not a well-designed experiment, since you apply a dose that is half-maximal (1uM when the EC50 is 1.3uM: ln 391), so you would be unlikely to observe more than half of the potential effect. For most readers, this comes across as a rather minor point and I think they will wonder why they need to know this information, certainly it is a weak figure with which to finish. Perhaps if AUT5 was shown to change the finch song or other behaviour in the opposite way to blocking the channel it would be interesting. AUT5 effects have also been noted previously in other publications:

2015. Biophysical characterization of KV3.1 potassium channel activating compounds. Taskin B, von Schoubye NL, Sheykhzade M, Bastlund JF, Grunnet M, Jespersen T.

Eur J Pharmacol. 2758:164-70.

2017. Kv3.1/Kv3.2 channel positive modulators enable faster activating kinetics and increase firing frequency in fast-spiking GABAergic interneurons. Boddum K, Hougaard C, Xiao-Ying Lin J, von Schoubye NL, Jensen HS, Grunnet M, Jespersen T. Neuropharmacology, 118:102-112.

We appreciate the reviewer’s comments and note that we have cited both of these studies within our manuscript. We additionally note that the half maximal dose of AUT5 yielded significant effects on RAPNs, but not on AId neurons. These results are consistent with the difference in expression of Kv3.1 between RAPNs and AId neurons. We believe that the AUT5 data is critical in: (1) Narrowing down to Kv3.1/Kv3.2 as the most likely contributing channels for the differences between RAPNs and AId neurons; and (2) Showing that by positively modulating Kv3.1 channel activity we can demonstrate opposite effects of blockade by TEA or 4-AP. With regard to delivering AUT5 to RA during song production, it would require various elaborate controls and the exact predictions are unclear, as one might see opposing effects due to AUT5’s possible actions on Kv3.1/2 expressed in both RAPNs and GABAergic interneurons. Thus, while we agree this is a tantalizing experiment, we believe it is beyond the scope of the present study.

Reviewer #3 (Recommendations for the authors):

This paper was a pleasure to read and goes through a logical sequence of experiments to pinpoint the role of Kv3(.1?) in the fast-spiking of RAPN neurons. There are large replicate numbers for almost all findings, and admirably, there is confirmation of the main result at physiological temperature. The phase plots in Figure 4 make clear that 4AP and TEA, at the concentrations used, have little effect on Ald neurons, but strong effects on RAPNs in both current clamp and voltage clamp. The methods developed to improve voltage clamp compliance are to be commended.

1) The paper has an unclear focus. In some ways, it focuses on the properties of RAPN neurons and how they might generate fast APs. Yet in other contexts, the paper seems to center on the description of a previously uncharacterized cell type, the neurons of Ald.

We appreciate the reviewer’s concern. Our main goal has been to characterize the excitable properties of RAPNs, which are upper motor neurons with a specialized role in vocal-motor control. However, we also discovered that the excitable properties of RAPNs differ in significant ways from those of neurons in the adjacent AId, which are thought to control non-vocal somatic motor function (Mandelblat-Cerf, eLife, 2014; Yaun and Bottjer, eNeuro, 2020; Feenders et al., PLoS One, 2008). We then realized that an important way to highlight the unique properties of RAPNs would be to contrast them with those of AId neurons. Whereas there is literature describing the excitable properties of RAPNs, no studies to date have described the intrinsic excitable properties of AId neurons (using whole-cell patch clamp), nor contrasted the neuronal excitable properties of these two regions. Examination of the differences between RAPNs and AId neurons provided key insights into specializations that may be associated with vocal production. To clarify this important point, we now make the goals and general strategy of our study more explicit in the beginning of the Results section (see lines 105-116).

2) The pharmacological analysis of repetitive spike firing is lacking. For example, the traces in Figure 5B and 5D, and 8B and 8D, DO in fact show effects of 4AP/TEA/AUT5 on Ald neurons. This raised two issues. A) Repeated measures, such as a paired t-test I (before and after the drug, on a per cell basis) are arguably more appropriate than group averages at each current injection strength. B) Some effort should be dedicated to reversibility. While it can be technically challenging to hold a cell for the total time required to completely wash out the drug, at least a few examples should be provided to confirm that "drug" effects are not due to time-dependent changes in cell physiology.

We appreciate the comment about the need for statistical rigor and drug reversibility experiments. With regard to the first point, we did run repeated measures statistics. In our experimental design we measured spikes per second at multiple levels of positive current injections before and after drug administration. Based on this experimental design, we conducted a Repeated Measures Two-way ANOVA to determine any effects on the spikes per second of the recorded cells, which is statistically more appropriate than running multiple t-tests. For datasets in which the ANOVA detected a significant effect, we followed up with post-hoc tests to determine significance for individual comparisons that could explain our results. While we note the trends in the data for AId neuron responses to 4-AP and TEA (see lines 252-260), no significant effect was detected by the ANOVA. To our knowledge we used an appropriate and rigorous statistical treatment of the data given the experimental design.

Per the reviewers’ suggestion (see also Reviewer 1) we performed washout experiment with TEA, 4-AP and AUT5. These data are now described in Results (lines 262-271, 442-444) and presented in the new Figure 5—figure supplement 1.

3) For fast repolarization, it would likely be better to focus mainly on the early current, highlight with the red bars in figure 6, rather than on the current persisting until 200 ms.

We agree that the early current indeed plays a more important role in AP repolarization. While we analyzed the currents at 200 ms, we gave equal attention to analysis of the initial inactivating current observed. We have now added a sentence to the discussion focusing on the early current and its putative effects on the repolarization of APs in RAPNs and AId neurons. See lines (588-589).

4) There is a bit of circular logic regarding the description of the effects of AUT5 on spike depolarization (Figure 8A). If RA affects the maximum depolarization, then this could secondarily increase the recruitment of K channels and in turn produce a faster rate of repolarization.

The reviewer comments here on another important point. We note, however, that there was no change in the maximum rate of spike depolarization in RAPNs in response to AUT5 (stats in lines 425-426). While we agree that Kv channel recruitment could result from a more depolarized spike peak, as far as we are aware there is no data to suggest effects of AUT5 on Nav channels, that could cause this increased peak. Previously published literature (Boddum et al., Neuropharmacol., 2017; Taskin et al., Eur. J. Pharmacol., 2015) and personal communications with Autifony Therapeutics describe AUT5 as being a highly selective positive modulator for Kv3.1 and Kv3.2. We acknowledge that the exact explanation for the effects of AUT5 on spike shape may be complicated, with indirect effects on the availability of other voltage gated ion channels during spiking as a result of voltage-dependent shifts, activation changes and deactivation changes of Kv3.1 channels in response to 1 µM AUT5. Nonetheless, coupled with the other AUT5-induced changes that were seen in RAPNs, but not in AId neurons, we believe that the most parsimonious explanation for our data is that the changes seen in RAPNs with AUT5 are due to the positive modulation of the Kv3.1 subunit.

We have now included a statement regarding the potential increase in recruitment of Kv’s as a result of the depolarized peak of the AP (See lines 432-433).

5) While voltage clamp compliance is likely much improved by the approaches taken, it will still not be perfect, and there will remain issues of non-isopotentiality. This should be discussed.

We appreciate the reviewer’s comments and revised text in Results to address issues of isopotentiality. See lines 295-301.

6) The correspondence to Betz cells is oversold and should be removed from the title and abstract. There are many differences, as the authors note. A) The RA cells are not necessarily larger than other motor output neurons as with Betz cells, B) They have presumably developed along a unique evolutionary path, C) Other central features of Betz cells (conduction velocities, myelination, axon fiber diameter) are not reported.

We appreciate the reviewer’s comments and have removed the reference to Betz cells from the title. We have additionally modified the Abstract and significantly changed the Introduction (eliminating the first paragraph) to de-emphasize the comparison with Betz cells. While we also agree that future studies are indeed required (i.e. looking at myelination, axon fiber diameter and conduction velocities) for thorough comparisons, we nonetheless believe it is worth discussing the similarities to Betz cells in the paper. In particular, the presence of Kv3.1b in Betz cells (but not in other Layer 5 motor cortex pyramidal neurons) has been highlighted by researchers working with primates, so we find it most intriguing that this important feature is also present in the RA cells. Nevertheless, the comparison with Betz cells is now mostly detailed in the Discussion section.

Author details

1. Benjamin M Zemel

   Vollum Institute, Oregon Health and Science University, Portland, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review and editing, designed electrophysiology and morphology experiments

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-6701-0647

2. Alexander A Nevue

   Department of Behavioral Neuroscience, Oregon Health and Science University, Portland, United States

   Contribution

   Conceptualization, Formal analysis, Investigation, Methodology, Resources, Visualization, Writing – review and editing, designed molecular biology experiments and genomic analysis

   Competing interests

   No competing interests declared

3. Leonardo ES Tavares

   1. Vollum Institute, Oregon Health and Science University, Portland, United States
   2. Department of Physics, Pennsylvania State University, University Park, United States

   Contribution

   Conceptualization, Software, Formal analysis, Investigation, Visualization, Methodology, Writing – review and editing, designed and carried out morphometric analyses using the ShuTu software package

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-8642-5186

4. Andre Dagostin

   Vollum Institute, Oregon Health and Science University, Portland, United States

   Contribution

   Investigation, Visualization, Methodology, acquired electrophysiology data and performed biocytin fills

   Competing interests

   No competing interests declared

5. Peter V Lovell

   Department of Behavioral Neuroscience, Oregon Health and Science University, Portland, United States

   Contribution

   Conceptualization, Funding acquisition, integrated molecular and electrophysiological data

   Competing interests

   No competing interests declared

6. Dezhe Z Jin

   Department of Physics, Pennsylvania State University, University Park, United States

   Contribution

   Conceptualization, Resources, Software, Formal analysis, Supervision, Investigation, Visualization, Methodology, Writing – review and editing, designed and managed morphometric analyses using the ShuTu software package

   Competing interests

   No competing interests declared

7. Claudio V Mello

   Department of Behavioral Neuroscience, Oregon Health and Science University, Portland, United States

   Contribution

   Conceptualization, Resources, Formal analysis, Supervision, Funding acquisition, Investigation, Visualization, Methodology, Project administration, Writing – review and editing, designed molecular biology experiments and genomic analysis

   For correspondence

   melloc@ohsu.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-9826-8421

8. Henrique von Gersdorff

   1. Vollum Institute, Oregon Health and Science University, Portland, United States
   2. Oregon Hearing Research Center, Oregon Health and Science University, Portland, United States

   Contribution

   Conceptualization, Resources, Formal analysis, Supervision, Funding acquisition, Visualization, Methodology, Project administration, Writing – review and editing, designed electrophysiology and morphology experiments

   For correspondence

   vongersd@ohsu.edu

   Competing interests

   Reviewing editor, eLife

   "This ORCID iD identifies the author of this article:" 0000-0002-4404-3307

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