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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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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