Speech planning is an important part of human communication and the inability to plan speech is manifest in disorders such as apraxia. But to what extent is targeted vocal planning an entirely human ability? Many animals are capable of volitional control of vocalizations (Brecht et al., 2019; Veit et al., 2021), but are they also capable of planning to selectively adapt their vocalizations toward a target, such as when striving to reduce the pitch mismatch of a note in a song? Target-specific vocal planning is a cognitive ability that requires extracting or recalling a sensory target and forming or selecting the required motor actions to reach the target. Such planning can be covert or overt. Evidence for covert planning is manifest when a targeted motor change is executed without intermittent practice (Costalunga et al., 2023), for example, when we instantly imitate a word upon first hearing. Overt planning, by contrast, includes practice, but without access to the sensory experience from which target mismatch could be computed, for example, when we practice a piano piece by tapping on a table.

The vocal planning abilities in animals and their dependence on sensory experience remain poorly explored. Motor learning has been mostly studied in tasks where a skilled behavioral response must be produced on the spot, such as when a visual target must be hit by a saccade or by an arm reaching movement (Brashers-Krug et al., 1996; Galea et al., 2011; Shmuelof et al., 2012; Krakauer et al., 2005). In this context, motor planning has been shown to enhance motor flexibility as it allows separation of motor memories when there are conflicting perturbations (Sheahan et al., 2016). However, for developmental behaviors such as speech or birdsong that rely on hearing a target early in life (Konishi, 1985; Immelmann, 1969), the roles of practice and of sensory feedback for flexible vocal control and for target-directed adaptation are unknown.

Recovery of a once-learned vocal skill could be instantaneous (covert) or it might require practice (overt). In support of the former, many motor memories are long-lasting (Park et al., 2013), for example, we can recall the happy-birthday song for years without practice. Some memories are even hard to get rid of such as accents in a foreign language. By contrast, practice-dependent, but feedback-independent recovery is argued for by arm reaching movements during use-dependent forgetting: following adaptation to biasing visual feedback, arm movements recover when the bias is either removed or the visual error is artificially clamped to zero (Galea et al., 2011; Shmuelof et al., 2012). One explanation put forward is that motor adaptation is volatile and has forgetting built-in (Krakauer et al., 2005; Smith et al., 2006), leading to practice-dependent reappearance of the original motor program even without informative feedback (Smith et al., 2006). Given these possibilities, we set out to probe songbirds’ skills of recovering their developmental song target when deprived of either singing practice (to probe covert planning) or of sensory feedback (to probe overt planning).

Adult vocal performances in songbirds can be altered by applying external reinforcers such as WN stimuli (Tumer and Brainard, 2007; Andalman and Fee, 2009). When the reinforcer is withdrawn, birds recover their original song within hundreds of song attempts (Tumer and Brainard, 2007; Canopoli et al., 2014; Warren et al., 2011; Hoffmann et al., 2016). We argued that these attempts may be unnecessary and birds could recover their original performance by recalling either (1) the original motor program (Aronov et al., 2008; Nottebohm et al., 1976; Prather et al., 2009) or (2) its sensory representation (Yazaki-Sugiyama and Mooney, 2004; Kojima and Doupe, 2007; Yanagihara and Yazaki-Sugiyama, 2016) plus the mapping required for translating that into the original program (Canopoli et al., 2014; Warren et al., 2011; Figure 1A). These options might not need sensory feedback, which is argued for by birds’ large perceptual song memory capacity (Yu et al., 2020). That is, birds’ song practice may be mainly expression of deliberate playfulness (Riters et al., 2019), conferring the skill of vocal flexibility rather than serving to reach a target, evidenced by young birds that explore vocal spaces close to orthogonal to the song-learning direction (Kollmorgen et al., 2020) and that are already surprisingly capable of adult-like singing when appropriately stimulated (Kojima and Doupe, 2011).

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To test whether birds can covertly recover a song syllable without practice, we first reinforced the pitch of a song syllable away from baseline and then we suppressed birds’ singing capacity for a few days by muting their vocal output. We then unmuted birds and tested whether the song has covertly reverted back to the original target. We used syllable pitch as the targeted song feature because we found that birds did not reliably recover syllable duration in experiments in which we induced them to shorten or lengthen syllable duration (Figure 1—figure supplement 1).

We first drove pitch away from baseline by at least 1 standard deviation using a WN stimulus delivered whenever the pitch within a 16 ms time window locked to the targeted syllable was above or below a manually set threshold (Figure 1B and C, see ‘Materials and methods’). We muted these WNm (WN reinforced and muted) birds by implanting a bypass cannula into the abdominal air sac (see ‘Materials and methods’). While muted, air is leaking from the abdominal air sac and as a result, sub-syringeal air pressure does not build up to exceed the threshold level required for the self-sustained syringeal oscillations (Elemans et al., 2015) that underlie singing. Physical absence of such oscillations essentially strips muted birds from all pitch experience. In some cases, the bypass cannula got clogged during the muted period and birds were spontaneously unmuted, allowing them to produce a few songs before we reopened the cannula (Figure 1C–G).

We quantified recovery in terms of normalized residual pitch (NRP) to discount for differences in the amount of initial pitch shift where NRP = 0% corresponds to complete recovery and NRP = 100% corresponds pitch values before withdrawal of reinforcement ($R$) and thus no recovery. After spending 5.1 ± 1.6 days (range 3–8 days, N = 8) in the muted state and upon unmuting, WNm birds displayed an average NRP of 89%, which was far from baseline (p=6.2 · 10^–8, tstat = -23.6, N = 8 birds, two-sided t-test of H0: NRP = 0%, songs analyzed in 2 hr time window – early ($E$), see ‘Materials and methods’, Figure 1), suggesting that in the muted state, birds are unable to recover their pre-reinforced songs. The average NRP in WNm birds was comparable to that of unmanipulated control (WNC) birds within the first 2 hr after withdrawal of the reinforcer (average NRP = 91%, p=3.7 · 10^–11, tstat = 14.8, two-sided t-test for NRP = 0%, N = 18 WNC birds). Indeed, during 5 days without song practice, birds recovered no more pitch distance than birds normally do within the first 2 hr of release from reinforcement (p=0.82, tstat = -0.23, N = 8 WNm and N = 18 WNC birds, two-sided t-test). In WNm birds, there was no correlation between the NRP in the early window and the time since the muting surgery (correlation coefficient R=0.26, p=0.53), suggesting that the lack of pitch recovery while muted was not due to a lingering burden of the muting surgery. These findings did not sensitively depend on the size of the analysis window — we also tested windows of 4 and of 24 hr.

Subsequently, after 4 days of unmuted singing experience (roughly 9 days after withdrawal of WN), WNm birds displayed an average NRP of 30%, which was significantly different from the average NRP within the first 2 hr after unmuting (p=3 · 10^–4, tstat = 4.83, N = 8 birds, two-tailed t-test early ($E$) vs. late ($L$) time window) but still significantly different from zero (p=0.04, tstat = 2.59, N = 8 birds, two-tailed t-test, late ($L$) time window). The amount of recovery was neither correlated with the number of renditions sung between early and late windows (R=0.03, p=0.95), nor with the duration the birds were muted (R=–0.50, p=0.20), nor with the time since they last sung the target song before reinforcement (R=–0.43, p=0.29), suggesting the limiting factor for recovery was neither the amount of song practice nor the recovery time from the muting surgery (although for the latter there was a trend). Overall, these findings rule out covert planning in muted birds and suggest that motor practice is necessary for recovery of baseline song.

Next, we tested whether motor experience but not sensory experience is necessary for overt recovery, similar to arm reaching movements that can be restored without guiding feedback (Galea et al., 2011; Galea et al., 2015). In a second group of birds, we provided slightly more singing experience (Figure 2). Instead of muting, WNd birds were deafened through bilateral cochlea removal immediately after the end of WN reinforcement. This latter manipulation does not suppress the act of singing as does muting, but it eliminates auditory feedback from singing. Deaf birds could gain access to some pitch information via somatosensory stretch and vibration receptors and/or air pressure sensing (Suthers et al., 2002). Our aim was to test whether such putative pitch correlates are sufficient for recovery of baseline pitch (Figure 2A). However, in the deaf state, WNd birds did not recover baseline pitch even after 4 days of song practice: on the fifth day (late, $L$) after deafening, their average NRP was still 50%, which was different from zero (p=0.03, tstat = 2.73, two-tailed t-test of H0: NRP = 0%, N = 10, Figure 2D) and significantly larger than the average NRP of WNC birds on the fifth day since withdrawal of reinforcement (difference in NRP = 49%, p=0.003, tstat = 3.34, df = 26, N = 10 WNd and N = 18 WNC birds, two-tailed t-test).

Figure 2

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We speculated that the lack of pitch recovery in WNd birds could be attributable to the sudden deafening experience, which might be too overwhelming to uphold the plan to recover the original pitch target. WN deaf birds did not sing for an average of 2.3 ± 1.1 days (range 1–4 days) after the deafening surgery, which is a strong indication of an acute stressor (Yamahachi et al., 2020). We thus inspected a third group of birds (dLO, Figure 3) taken from Zai et al., 2020a that learned to shift pitch while deaf and that underwent no invasive treatment between the pitch reinforcing experience and the test period of song recovery.

Figure 3

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dLO birds were first deafened, and after they produced stable baseline song for several days, their target syllable pitch was reinforced using pitch-contingent light-off (LO) stimuli, during which the light in the sound recording chamber was briefly turned off upon high- or low-pitch syllable renditions (Zai et al., 2020b). dLO birds displayed an average NRP of 112% on the fifth day since release from LO, which was significantly different from zero (p=3.7 · 10^–8, tstat = 25.4, N = 8 birds, two-tailed t-test of H0: NRP = 0) and was larger than the NRP in WNC birds on the fifth day since release (p=1.3 · 10^–13, tstat = 14.9, df = 24, N = 8 dLO and N = 18 WNC birds, two-sided t-test). Thus, dLO birds were unable to recover baseline pitch, suggesting that song recovery requires undiminished sensory experience, which includes auditory feedback.

Deaf birds' decreased singing rate could not explain their lack of pitch recovery. Deaf birds sang less during the first 2 hr since release of reinforcement (early) than control birds: 87 ± 59 motif renditions for WNd and 410 ± 330 renditions for dLO compared to 616 ± 272 renditions for WNC birds. Also, WNd birds sang only 4,300 ± 2,300 motif renditions between the early and late period compared to the average of 11,000 ± 3,400 renditions that hearing WNC birds produced in the same time period. However, despite these differences, when we inspected WNd birds’ behavior 9 days after the early window, when they sung on average 12,000 ± 6,000 renditions, their NRP was still significantly different from zero (NRP = 0.37, p = 0.007, tstat = 3.47, df = 9). Thus, even after producing more practice songs than control birds, deaf birds did not recover baseline pitch and so the number of songs alone cannot explain why deaf birds do not fully recover pitch. We conclude that auditory experience seems to be necessary to recover song.

That song practice and sensory experience are required for full recovery of song does not imply that without experience, birds are incapable of making any targeted changes to their songs at all. We therefore inspected birds’ fine-grained vocal output and whether they changed their song in the direction of baseline when deprived of sensory experience. We hypothesized (Figure 4A) that when birds experience a target mismatch during reinforcement (i.e., they hear that their song deviates from the target), they plan to recover the pitch target, and a portion of this plan they can execute without feedback. If, by contrast, they have no mismatch experience before deafening, they will make no corresponding plan. Hence, we predicted that WNd birds that experienced a pitch mismatch during reinforcement and before deafening would slightly revert their song toward baseline even in the absence of auditory feedback. By contrast, dLO birds that did not experience a mismatch because they did not hear their song while it was reinforced would not revert toward the target (Figure 4A).

Figure 4

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Indeed, WNd birds changed their pitch significantly toward baseline already in the first 2 hr of their singing since release from reinforcement (relative to the pitch from the last 2 hr during reinforcement). We quantified local pitch changes in terms of the d' sensitivity of signal detection theory (which is independent of shift magnitude) and found d' = -0.60 (p = 0.03, tstat = -2.19, df = 9, N = 10 WNd birds, one-sided t-test of H0: d' = 0). A significant reversion toward pitch baseline was still evident after 4 days of practice (d' = -1.27, p = 0.02, tstat = -2.35, N = 10 WNd birds, one-sided t-test, Figure 4B, D and F), showing that pitch reversion in deaf birds is persistent. Because the average pitch shift in WNd birds was on the order of one standard deviation (d'${\displaystyle \simeq }$ 1), we conclude that without auditory experience, birds are able to perform target-directed pitch shifts of about the same magnitude as their current exploratory range (i.e., the denominator of the d' measure).

In contrast, dLO birds showed no signs of reverting pitch, neither in the first 2 hr since release of reinforcement (d' = -0.13, p = 0.36, tstat = -0.37, df = 7, N = 8 birds, one-sided t-test), nor after 4 days of practice (d' = -0.08, p = 0.43, tstat = -0.18, df = 7, N = 8 birds, one-tailed t-test, Figure 4C, E and F).

The singing rate does not explain why deaf birds with mismatch experience partially revert their song toward baseline, unlike deaf birds without mismatch experience. WNd birds sang less during the first 2 hr after reinforcement (early) than both control birds (p=2.3 · 10^–6, tstat = 6.02, df = 26, N = 10 WNd and N = 18 WNC birds, two-sided t-test) and dLO birds (p=0.008, tstat = 3.06, df = 16, N = 8 dLO birds, two-sided t-test), unlike dLO birds that sang similar amounts as WNC birds (p = 0.11, tstat = 1.67, df = 24, two-sided t-test). If the number of songs were to determine the rate of recovery, we would have seen the opposite effect (dLO birds should recover similar amounts as WNC birds and significantly more than WNd birds). In conclusion, singing rate does not explain the difference between WNd and dLO birds.

To discount for the effect of time elapsed since deafening and quantify the change in pitch specifically due to reinforcement, we bootstrapped the difference in d' between dLO/WNd birds and a new group of dC birds that were deafened but experienced no prior reinforcement (see ‘Materials and methods’). To discount for possible influences of circadian pitch trends, we assessed early and late pitch changes in reinforced birds and in dC birds in 2 hr time windows separated by multiples of 24 hr (and again flipped pitch changes in birds that were reinforced to decrease pitch, see ‘Materials and methods’). In agreement with the findings above, we found that significant reversion toward baseline was only seen in WNd birds and very consistently so (Figure 4G, Supplementary file 1), showing that prior experience of a target mismatch is necessary for pitch reversion independent of auditory feedback.

We further validated our finding using a linear mixed effect model on the combined NRP data of all groups (see ‘Materials and methods’), which confirmed our previous findings: we did not find a significant effect of the time without practice between ${\displaystyle R}$ and ${\displaystyle E}$ windows on the NRP in the ${\displaystyle E}$ window (fixed effect –0.04, p = 0.2), confirming that birds do not recover without practice. Neither deafening nor muting had a significant effect by itself but the interaction between deafening and time (late) was associated with an NRP increase of 0.67 (fixed effect, p = 2 · 10^–6), demonstrating that deaf birds are significantly further away from baseline (NRP = 0) than hearing birds in late windows, thereby confirming that birds require auditory feedback to recover a distant pitch target. Importantly, we found that mismatch experience was associated with a significant fixed effect of –0.37 on the NRP (fixed effect toward the target, p = 0.006), supporting our finding that limited vocal plasticity is possible even in the absence of auditory feedback.

Our results thus argue for a model of song maintenance in which birds extract from target mismatch experience a plan of reducing the mismatch. Without practice and auditory experience, birds cannot reach a distant motor target (Figure 5A). With practice and without auditory experience, they can make small changes toward a target, which we refer to as the planning range. Auditory experience allows them to consolidate the small changes such that step-by-step they can reach even a distant target (Figure 5B).

Figure 5

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Our work shows that recent auditory experience can drive motor plasticity even while an individual is deprived of such experience, that is, zebra finches are capable of overt vocal planning. But to reach a distant vocal target beyond the pitch range they have recently produced necessitates auditory feedback, which sets a limit to zebra finches’ overt planning ability.

Our insights were gained in deaf birds, and we cannot rule out that deaf birds could gain access to pitch information via somatosensory-proprioceptive sensory modalities. However, such information, even if available, cannot explain the difference between the ‘mismatch experience’ (WNd) and the ‘no mismatch experience’ (dLO) groups, which strengthens our claim that the pitch reversion we observe is a planned change and not merely a rigid motor response (as in simple use-dependent forgetting; Galea et al., 2011; Shmuelof et al., 2012). Also, it is unlikely that dLO birds’ inability to recover baseline pitch is somehow due to our use of a reinforcer of a non-auditory (visual) modality since somatosensory stimuli do not prevent reliable target pitch recovery in hearing birds (Sober and Brainard, 2009). Thus, the overt planning ability is an active experience-dependent process.

In our two-stage model, recovery of a developmentally learned vocal target is controlled by two nested processes, a highly flexible process with limited scope (d'${\displaystyle \simeq }$ 1, Figures 4 and 5), and a dependent process enabled by experience of the former. Such motor learning based on separate processes for acquisition and retention is usually referred to as motor consolidation (Brashers-Krug et al., 1996; Fenn et al., 2003; Karni and Sagi, 1993). Accordingly, the flexible process of acquisition or planning as we find is independent of immediate sensory experience, but the dependent process (consolidation of the flexible process) requires experience. Perhaps then, it is the sensory experience itself that is consolidated, and therefore, consolidation of sensory experience may be a prerequisite for extensive planning.

We cannot distinguish the overt planning we find from a more complex use-and-experience-dependent forgetting since we only probed for recovery of pitch and did not attempt to push birds into planning pitch shifts further away from baseline. Evidence for more flexible planning is provided by the pitch matching skills of nightingales (Costalunga et al., 2023). Interestingly, although nightingales can reach without practice even distant pitch targets, the targets in Costalunga et al., 2023 were also located within the extent of nightingale’s recent song practice, so also satisfied d' ${\displaystyle \simeq }$ 1. Perhaps then, our two-stage model of song plasticity of planning and consolidation in Figure 5 applies more broadly in songbirds and not just in zebra finches.

Consolidation in motor learning generally emerges from anatomically separated substrates for learning and retention (Galea et al., 2011). Such separation also applies to songbirds. Both reinforcement learning of pitch and recovery of the original pitch baseline depend on the anterior forebrain pathway and its output, the lateral magnocellular nucleus of the anterior nidopallium (LMAN) (Warren et al., 2011). LMAN generates a pitch bias that lets birds escape negative pitch reinforcers and recover baseline pitch when reinforcement is withdrawn (Andalman and Fee, 2009), thus is likely involved in planning. This pitch bias is consolidated outside of LMAN (Warren et al., 2011; Tian and Brainard, 2017) in a nonlinear process that is triggered when the bias exceeds a certain magnitude (Tachibana et al., 2022). This threshold magnitude is roughly identical to the planning limit we find (d' ${\displaystyle \simeq }$ 1), suggesting that birds’ planning limit arises from the consolidation of LMAN-mediated motor plasticity. Although it remains to be seen whether LMAN is capable of executing motor plans without sensory feedback, our work provides a new perspective on the neural basis of birdsong learning and consolidation in and around LMAN.

The formation of a planned motor change may not require LMAN itself because pharmacological suppression of LMAN sets the bias to zero, but upon removal of output suppression, the pitch of the song syllable that was targeted by reinforcement jumps by about 1% away from the reinforced pitch zone (Charlesworth et al., 2012), which corresponds to about d' = 1, about the planning limit we find. Originally, this jump was interpreted as evidence of functional connectivity or an efference copy between the anterior forebrain pathway of which LMAN is part of and some other unspecified variability-generating motor area. However, in our view, a simpler explanation requiring neither functional connectivity nor efference copy is that LMAN is involved in putting a plan into action, which in that case is to produce syllable variants that are unaffected by WN.

Zebra finches’ ability to plan directed song changes could hinge on song memories that feed into LMAN and that could drive neurons there to produce diverse perceptual song variants. LMAN neurons are selective for the bird’s own song but not the target song (Yazaki-Sugiyama and Mooney, 2004; Kojima and Doupe, 2007), which makes them well suited for executing song plans within the range of recent experience (i.e., if the song is outside recent experience, it elicits no LMAN response and so does not gain access to planning circuits). Furthermore, LMAN neurons show mirrored activity, that is, similar activity when a zebra finch produces a vocal gesture and when it hears the same gesture played through a loudspeaker (Hanuschkin et al., 2013; Oztop et al., 2013). This mirrored activity has been argued to be involved in translating an auditory target into the corresponding motor command, also known as an inverse model (Giret et al., 2014). Mirroring in LMAN was observed across the song variability generated over a period of several hours, which is about the same as the experience-dependent pitch planning limit we find. Zebra finches could thus transform a desired pitch change into the corresponding motor plan via LMAN’s aligned sensory and motor representations of recent vocal output.

In a broader context of motor recovery, birds’ failure to recover baseline pitch without guiding sensory feedback agrees with reports that binary reinforcement (as we used) slows down or prevents forgetting of the adapted behavior (Shmuelof et al., 2012). However, whereas forgetting is fast when sensory errors affect arm movements (Shmuelof et al., 2012), the contrary applies to birdsong, where pitch learning from artificial sensory errors is slower and less forgotten (Sober and Brainard, 2009) than is pitch learning from binary reinforcement (Tumer and Brainard, 2007; Canopoli et al., 2014). Hence, the commonality of short-term visuo-motor adaptation and of birdsong maintenance is that slow learning leads to slow forgetting, regardless of whether it is due to sensory errors or reinforcement. Such conclusion also agrees with observations that zebra finch song does not recover to pre-manipulated forms, both after restoring auditory feedback after long-term (>5 months) deprivation (Zevin et al., 2004) and after restoring normal syrinx function after long-term (16 weeks) manipulation with beads (Hough and Volman, 2002), suggesting that song can spontaneously recover only within some limited time since it was manipulated.

Our observations in zebra finches could be relevant to other species including humans. The planning abilities we find bear resemblance to human motor imagery for movement learning, which is most effective when subjects already show some competence for the movements to be learned (Mulder et al., 2004), suggesting a recall-dependent process. Naively, human vocal flexibility seems superior to that of zebra finches since we can flexibly change sound features such as loudness, pitch, and duration to convey emotional state or to comply with the tonal and rhythmical requirements of a musical piece (Dichter et al., 2018; Belyk and Brown, 2016), whereas zebra finches produce more subtle modulations of their songs, for example, when directing them to a female (Stepanek and Doupe, 2010). Nevertheless, a limit of human vocal flexibility is revealed by non-native accents in foreign languages, which are nearly impossible to get rid of in adulthood. Thus, a seeming analogous task to feedback-dependent learning of zebra finch song, in humans, is to modify developmentally learned speech patterns.

Our findings help elucidate the meaning of song signals in songbirds and the evolutionary pressures of singing. Because zebra finches seem incapable of large jumps in performance without practice, their current song variants are indicative of the recent song history, implying that song is an honest signal that zebra finches cannot adapt at will to deceive a receiver of this signal. Hence, if high pitch has either an attractive or repelling effect on another bird, a singer must commit to being attractive or repulsive for some time. In extension, we speculate that limited vocal flexibility increases the level of commitment to a group and thereby strengthens social cohesion.

All experimental procedures were in accordance with the Veterinary Office of the Canton of Zurich (licenses 123/2010 and 207/2013) or by the French Ministry of Research and the ethical committee Paris-Sud and Centre (CEEA no. 59, project 2017-12).

Pitch and duration values used for the analysis together with the MATLAB scripts to reproduce the analysis and figures are available at the ETH Research Collection at: https://doi.org/10.3929/ethz-b-000670443. Due to the considerable volume of the raw audio data associated with the pitch measurements (approximately 1TB), this dataset is not available for direct download. However, interested researchers can request access by contacting the corresponding author via email to coordinate the data transfer.

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Author details

1. Anja T Zai

   1. Neuroscience Center Zurich (ZNZ), University of Zurich and ETH Zurich, Zurich, Switzerland
   2. Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland

   Contribution

   Conceptualization, Data curation, Software, Formal analysis, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing

   For correspondence

   zaia@ethz.ch

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0460-0850

2. Anna E Stepien

   1. Neuroscience Center Zurich (ZNZ), University of Zurich and ETH Zurich, Zurich, Switzerland
   2. Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland

   Contribution

   Conceptualization, Data curation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-6398-6255

3. Nicolas Giret

   Institut des Neurosciences Paris-Saclay, UMR 9197 CNRS, Université Paris-Saclay, Saclay, France

   Contribution

   Supervision, Funding acquisition, Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-7139-6231

4. Richard HR Hahnloser

   1. Neuroscience Center Zurich (ZNZ), University of Zurich and ETH Zurich, Zurich, Switzerland
   2. Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland

   Contribution

   Conceptualization, Formal analysis, Supervision, Funding acquisition, Visualization, Writing - original draft, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4039-7773

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