Abstract
The role of granule cells in olfactory processing is surrounded by several enigmatic observations, such as the purpose of reciprocal spines and the mechanisms for GABA release, the apparently low firing activity and recurrent inhibitory drive of granule cells, the missing proof for functional reciprocal connectivity, and the apparently negligible contribution to lateral inhibition. Here, we summarize recent results with regard to both the mechanisms of GABA release and the behavioral relevance of granule cell activity during odor discrimination. We outline a novel hypothesis that has the potential to resolve most of these enigmas and allows further predictions on the function of granule cells in odor processing. Briefly, recent findings imply that GABA release from the reciprocal spine requires a local spine action potential and the cooperative action of NMDA receptors and high voltage-activated Ca2+ channels. Thus, lateral inhibition is conditional on activity in the principal neurons connected to a granule cell and tightly intertwined with recurrent inhibition. This notion allows us to infer that lateral inhibition between principal neurons occurs “on demand,” i.e., selectively on coactive mitral and tufted cells, and thus can provide directed, dynamically switched lateral inhibition in a sensory system with 1000 input channels organized in glomerular columns. The mechanistic underpinnings of this hypothesis concur with findings from odor discrimination behavior in mice with synaptic proteins deleted in granule cells. In summary, our hypothesis explains the unusual microcircuit of the granule cell reciprocal spine as a means of olfactory combinatorial coding.
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Introduction
The role of granule cells in olfactory processing is surrounded by several enigmatic findings (Shepherd et al. 2007; Burton 2017). Here, we present recent results and outline a novel hypothesis that has the potential to resolve most of these enigmas and allows further predictions on the function of granule cells in odor processing. Our focus is the synaptic interaction of mitral cells and granule cells via the reciprocal synapse, the mechanisms of signal processing in granule cells with an emphasis on their spines/gemmules, and the network consequences of these functions and mechanisms, especially with regard to odor discrimination. Plasticity at this synapse, adult neurogenesis of granule cells and higher order processing beyond the olfactory bulb are not within the scope of our review.
As described in previous chapters (cross references to be added in proof) in more detail, odorant molecules bind to olfactory receptor neurons in the nasal epithelium. The axons of these receptor neurons terminate in glomeruli of the olfactory bulb (OB) where they interact with local interneurons and the apical dendritic tufts of the bulbar projection neurons, the mitral and tufted cells (MTC), which in turn send their axons mostly to olfactory cortical areas (Igarashi et al. 2012; Nagayama et al. 2014). A single glomerulus usually receives convergent input from olfactory sensory neurons that all express the very same olfactory receptor (Belluscio et al. 2002). Activation of a given olfactory receptor will in turn activate its associated glomerular unit and the neurons belonging to the respective glomerular column. This unit could be considered an input channel that carries and further processes information as defined by the properties of the olfactory receptor generating the initial signal. Any given olfactory receptor is usually sensitive to a set of similar molecular structural elements with varying affinity (Malnic et al. 1999). Thus, even a single odorant can activate multiple glomerular units. Since the odor space consists of an enormous, nearly infinite number of possible odorants, olfactory processing needs to provide extensive inherent flexibility, which is in part covered by combinatorial coding: Odors are encoded as specific combinations of wide-spread glomerular activities. Due to the large number of olfactory receptors (~ 1000 in rodents (Mombaerts 1999)), this combinatorial principle allows to accommodate vast numbers of different stimuli. However, the problem arises of how to synthesize an “odor image” out of this highly distributed activity. This synthesis has been suggested to happen downstream of the bulb, in pyramidal cells of the olfactory cortex that integrate inputs from active MTCs of the entire bulb (Franks and Isaacson 2006; Apicella et al. 2010; Ghosh et al. 2011; Igarashi et al. 2012).
Inhibition both within and across glomerular columns is a key element of OB computations, as reflected in the extraordinarily large fraction of inhibitory interneurons. In the OB, the ratio of the inhibitory versus the excitatory neuron numbers amounts to roughly 80% versus 20% of the total population, which is the inverse of ratios in vertebrate cortex and hippocampus (Shepherd et al. 2004). The inhibitory interactions take place within a two-stage network (Aungst et al. 2003) of local and long-range connections, (1) within the glomerular layer, where a highly diverse set of inhibitory neurons forms synapses with the terminals of the receptor neurons and the apical dendritic tufts of MTCs and (2) in the external plexiform layer (EPL), where the long lateral MTC dendrites engage in reciprocal dendrodendritic interactions with granule cells (GC) and other inhibitory neurons, most prominently parvalbumin (PV+) neurons. These interactions are the subject of several excellent recent detailed reviews (Nagayama et al. 2014; Burton 2017) and represent a fundamental processing step in forming the odor representation on the level of the OB.
Aside from presynaptic inhibition of olfactory receptor neuron terminals, there are two main forms of inhibition of the principal neurons: (1) recurrent inhibition, which refers to interneuron feedback onto an exciting MTC, and (2) lateral inhibition, which refers to interneuron feedforward onto MTCs other than the exciting MTC. GCs, the most numerous neuron population of the OB, participate in both recurrent and lateral inhibition of MTCs at the level of the EPL, where they receive glutamatergic synaptic input from MTC lateral dendrites which they provide with reciprocal GABAergic output. Axonless GCs feature basal dendrites and an apical dendrite, both spinous, with the apical dendrite extending from the granule cell layer (GCL) into the EPL and contacting MTC lateral dendrites via large spines that house the reciprocal synapses (Fig. 1a). Historically, GC-mediated recurrent inhibition of MTCs has been suggested to provide substantial gain control for the massively convergent excitatory input onto MTCs, and GC-mediated lateral inhibition has been proposed to play a key role in contrast enhancement analogous to the visual system (Yokoi et al. 1995; Shepherd et al. 2007). However, a general chemotopic, continuous representation of molecular receptive ranges (i.e., map) could not be confirmed in the OB (e.g., Murthy 2011). Nevertheless, non-topographical representations may also use lateral inhibition for decorrelation of similar odorant representations (Cleland and Sethupathy 2006). Both the nature of olfactory mapping and the specific role of GCs in it are still unclear, in part due to several enigmatic or confounding observations.
Enigmatic features of granule cells
Purpose of the reciprocal spine as a unique circuit motif
Dendrodendritic, reciprocal excitatory-inhibitory synapses are rare on a brain-wide scale, but common to occur between principal neurons and local interneurons of the olfactory bulb (Crespo et al. 2013). Here, they are mostly formed not only between MTCs and GCs but also between MTCs and other inhibitory neurons of the glomerular and external plexiform layers. Uniquely, the MTC-GC reciprocal synapse forms on spines that consist of a rather large spine head connected by a thin elongated neck to the GC dendrite, a structure also referred to as gemmule (Fig. 1a, b) (Rall et al. 1966). The resulting dedicated anatomical compartment could enable an isolated reciprocal microcircuit. This observation has led us to propose the idea of the spine as a mini-neuron that can release GABA independently from the level of activity of its mother GC (Egger and Urban 2006). However, similar, functionally independent local processors are known to also exist in smooth dendrites (e.g., A17 amacrine cells of the retina (Egger and Diamond 2020)). What then is functionally particular about the gemmule architecture?
Mechanisms for recurrent GABA release
Early in vitro studies of recurrent inhibition in individual MTCs delivered contradictory results based on using very strong stimulation paradigms in the absence of extracellular Mg2+: the extended release of large amounts of glutamate from MTC dendrites caused massive Ca2+ entry and slow IPSCs lasting for seconds. Some groups identified NMDA receptors as the main effector of recurrent GABA release, whereas others implied high-voltage activated Ca2+ channels (HVACCs), but did not provide data for an involvement of voltage-gated Na+ (NaV) channels as in “classical” axonal release (Schoppa et al. 1998; Isaacson and Strowbridge 1998; Chen et al. 2000; Halabisky et al. 2000; Isaacson 2001). Moreover, the recurrent inhibition detected in these paradigms is not necessarily originating from GCs but might also be exerted by other EPL interneurons such as PV+ cells. PV+ cells, however, do not feature a substantial NMDAR current, and NMDA receptor antagonists are currently used to separate GC-mediated inhibition from that exerted by other glomerular interneurons and possibly also PV+ neurons (Najac et al. 2011; Geramita and Urban 2017). Hence, what exactly are the mechanisms of recurrent GABA release?
Lack of proof for functional reciprocal connectivity from individual GCs onto MTCs
Despite the aforementioned functional demonstrations of recurrent inhibition and solid ultrastructural evidence for the reciprocity of most GC spines within the EPL, functional connectivity from individually identified GCs to MCs has not yet been observed: several groups including ourselves (e.g., Egger et al. 2003; Schoppa 2006a) have been unable to find connected GC → MC pairs in the first place and even paired recordings of coupled MC → GC pairs have never shown a reciprocal connection so far (Isaacson 2001; Kato et al. 2013; Pressler and Strowbridge 2017). While this issue might to some extent be explained by the short electrotonic length of the thick MC dendrite, the complete lack of such observations is surprising in view of the many recordings of recurrent IPSCs and high density of GABAergic synapses on the MC lateral dendrites, most of which indeed originate from GCs (Bartel et al. 2015; Sailor et al. 2016; Matsuno et al. 2017). Yet, does functional reciprocal connectivity exist?
Sparse global GC spiking
Although axonless, GCs are capable of firing full-blown APs and at the same time feature a rather hyperpolarized resting membrane potential (Egger and Urban 2006). Indeed, early studies found sparse spontaneous spiking activity and low odor-evoked excitability in GCs in vivo under anesthesia (Wellis and Scott 1990; Cang and Isaacson 2003), yet higher activities were found in awake mice (Kato et al. 2012; Cazakoff et al. 2014, Wienisch and Murthy 2016). Still, spike rates appear considerably lower than those of MCs. Can global APs thus power substantial GC-mediated lateral inhibition? Moreover, it is unclear whether GC spiking is predominantly driven by MTC dendritic and/or axonal input or other excitatory input sources, such as centrifugal projections (Kishi et al. 1984; Schoppa 2006a; Pressler and Strowbridge 2017).
Little inhibitory drive
In spite of the high density of reciprocal synapses, GCs are unlikely to provide substantial inhibitory drive, because their silencing had little effect on mitral cell spiking rate in vivo (Fukunaga et al. 2014). Rather, they influence the relative timing of MC spiking, thus reinforcing older findings on a role in the generation of gamma oscillations at the reciprocal synapses (reviewed in Kay 2015). Other interneuron subtypes, both in the glomerular layer and in the EPL, are by now known to fill this gap, allowing for gain control of the highly convergent excitatory input onto MTCs. In the EPL, the aforementioned PV+ neurons have been shown to provide efficient and broad, long-range lateral inhibition between MTCs via reciprocal interactions with their large smooth dendritic arbors that extends horizontally within the EPL. PV+ neurons are broadly tuned for odors and suppression of their activity in vivo results in a general increase in MTC activity (Kato et al. 2013; Miyamichi et al. 2013). Do GC finally make only a minor contribution to recurrent MTC inhibition?
Apparently missing contribution to lateral inhibition
Yet more strikingly, in the aforementioned in vivo recordings from MCs by Fukunaga et al (2014), a subset of MCs responded exclusively with inhibition to odor activation, presumably via lateral inhibition—but optogenetic silencing specifically of GCs had no effect on this lateral inhibition both in anesthetized and in awake animals, whereas silencing of glomerular inhibitory neurons did. Thus, GCs dominate neither recurrent nor lateral inhibition in terms of magnitude, i.e., total charge transfer, as also supported by other recent studies (Geramita and Urban 2017). On these grounds, Burton (2017) has rightfully challenged the central role that GCs were thought to play in olfactory processing. What then is the function of GC-mediated inhibition? Does it exist at all?
Reciprocal GC output relevant for odor discrimination behavior
In spite of the results described above, deletion of glutamate receptors in GC changed the time mice required to discriminate highly similar odors (Abraham et al. 2010). Because of the activation of substantial numbers of glomerular input channels and highly similar activation patterns, in particular, lateral inhibition would be expected to be crucial for efficient discrimination. Yet, owing to technical limitations, only recurrent inhibition could be assessed in glutamate receptor-deleted mice. Removal of the GluA2 subunit increased recurrent inhibition and accelerated discrimination time, while removal of the GluN1 subunit showed the opposite effect (Abraham et al. 2010). While the viral expression of Cre recombinase used in this study is OB layer-specific, but not cell type-specific, it can be ruled out that PV+ interneurons of the external plexiform layer mediated these effects, because they mostly express AMPA receptors lacking the GluA2 subunit and negligible amounts of NMDA receptors (Kato et al. 2013; Miyamichi et al. 2013). Thus, molecular GC perturbations have a behaviorally relevant effect. How does this align with the above mentioned enigmas?
In the following, we review own recent findings that offer a clue to resolve these issues.
Recent findings 1: recurrent inhibition by the reciprocal spine and role of GC action potentials
Via high-resolution two-photon imaging and two-photon uncaging of glutamate, we have recently gathered evidence that upon unitary glutamatergic input the reciprocal spines fire local action potentials (“spine spikes”) that in turn activate HVACCs. This mechanism relies on the tight electrical isolation of the spine head by the high spine neck resistance, boosting the AMPAR-mediated EPSP (Bywalez et al. 2015). Next, we found that mouse GC spines express clusters of the NaV1.2 subunits, and by knocking down NaV1.2 in GCs, we showed that upon eliciting action potentials (AP) in MTCs, the recurrent rIPSPs were strongly reduced. These results demonstrated that an AP was required for GABA release at the reciprocal synapse, just like neurotransmitter release from regular axonal presynaptic terminals (Nunes and Kuner 2018). Finally, by recording from mitral cells while activating single reciprocal spines with two-photon uncaging, we have been able to detect recurrent GABA release with a low release probability of approximately Pr_GABA = 0.3. This GABA release was indeed dependent on the local spine spike and HVACC activation, consistent with the mini-neuron hypothesis (Lage-Rupprecht et al. 2020).
Interestingly, recurrent GABA release was also dependent on NMDAR activation, pointing towards a cooperative mechanism for which we obtained further evidence via ultrastructural demonstration of NMDARs within the GABAergic active zone of the spine (Fig. 1b; Lage-Rupprecht et al. 2020). This opens the possibility of cooperative overlapping Ca2+ domains between NMDARs and HVACCs within the GABAergic active zone and, in particular, may establish a close distance between NMDARs and the release sensor at the readily releasable vesicles. Both HVACC- and NMDAR-mediated Ca2+ currents may overlap if the spine spike causes a NMDAR-mediated Ca2+ spikelet via fast, transient additional relief of the Mg2+ block, as illustrated by our simulations (Aghvami et al. 2019; see Fig. 6 in Lage-Rupprecht et al. 2020). However, because of the very slow activation kinetics of NMDARs (12–13 ms (Monyer et al. 1992; Wyllie et al. 1998)), this mechanism will unfold its full potential if NMDARs are still activated from a previous episode of glutamate release. Yet even when newly activated, Ca2+ can enter also at this early phase, although at a reduced amount. This may explain the low release probability of 0.3 reported in Lage-Rupprecht et al. (2020).
In summary, a cooperative action of Ca2+ entering through HVACC and NMDAR will maximize the release probability for GABA at the active zone and hence provides a conditional mechanism for GABA release. Neither of the two Ca2+ sources can achieve this in isolation. Importantly, the spine AP is instrumental to boost Ca2+ entry through both NMDAR and HVACC: (1) a rapid relief of Mg2+ block (Kampa et al. 2004) already during the upstroke of the AP permits nearly instantaneous Ca2+ entry through already gated NMDARs, and (2) during the repolarization phase of the AP, the driving force for Ca2+ entry through HVACCs will strongly increase (“tail current”; see Nunes and Kuner 2018) while NMDARs are getting blocked again by Mg2+.
An important consequence of this cooperativity is that there will be only little AP-mediated release from a reciprocal spine without concurrent synaptic input onto this spine. As to the generation and spread of APs within the axonless granule cells, the preferred site for spike generation is likely to be located on the proximal apical dendrite (Pressler and Strowbridge 2019), consistent with the strong difference in Nav1.2 channel density between the soma and the proximal apical dendrite of the GC (Nunes and Kuner 2018). Within the dendritic domain, NaV1.2 is rather homogenously distributed, yet forming local clusters (Nunes and Kuner 2018). As argued by this study, a certain density of Nav channels within the clusters may facilitate AP generation. An AP will propagate along the GC apical dendrite and into its reciprocal spines perfectly well, as demonstrated by Ca2+ imaging and Nav channel blockade, notwithstanding the electrical isolation from spine head to the dendrite (Egger et al. 2003; Pressler and Strowbridge 2019). The ensuing spine depolarization Vm(t)SPINE will closely resemble that of the spine spike (see also Aghvami et al. 2019), which on its own, in the absence of glutamate at the spine, has only a low probability to trigger GABA release, as we have argued above. Therefore, any AP that propagates within the GC has a low probability of causing lateral inhibition by releasing GABA. Only those spines containing NMDARs activated within a time window of a few milliseconds to a few hundreds of milliseconds (depending on the NMDAR subtype (Monyer et al. 1992; Wyllie et al. 1998)), preceding the AP of the GC, will release GABA.
Taken together, the NMDAR provides a short-term memory of activity present in the respective MTC in a time window of a few ms to a few hundred milliseconds. We predict that the cooperative action of NMDAR and HVACC at the GABAergic active zone then allows for GABA release in three modes, with increasing probability: (1) unitary release upon single MTC input; (2) the same spine was already activated within the NMDAR memory time window and the subsequent glutamate release generates recurrent inhibition as described above, e.g., during a theta burst of an MTC; (3) the GC fires an action potential that enters all spines (or a subset, see below), but GABA is only released from those spines that were activated during the NMDAR memory time window, thereby generating lateral inhibition. In essence, short MTC bursts will facilitate recurrent inhibition and lateral inhibition will mostly affect MTCs that are currently active or were active very recently.
Notably, extracellular stimulation of the GC layer can evoke MC inhibition (e.g., Chen et al. 2000; Egger et al. 2003; Arevian et al. 2008). Perhaps some small Pr_GABA from spiking GCs remains in the absence of glutamate, which is then amplified by the large number of stimulated GCs. Alternatively, the stimulation activates other, yet unknown inhibitory inputs to MCs, e.g., from deep short-axon cells or axons of EPL interneurons (Nagayama et al. 2014, Burton 2017). In any case, for weak sensory input, the functional setup of the reciprocal GC spines allows for segregated recurrent inhibitory interactions of a given GC with several glomerular columns. Because we observed that plastic changes in response to sniff-like stimulation are likely to also occur independently in each spine (Chatterjee et al. 2016), spine-specific and perhaps column-specific synaptic plasticity might exist.
Recent findings 2: dendritic integration and coincidence detection on the level of the entire GC
For stronger sensory input, activity from many spines will become summated and result in regional and global signaling via Ca2+ spikes and Na+ spikes (Egger et al. 2003, 2005; Pinato and Midtgaard 2003; Zelles et al. 2006) that will then possibly translate into lateral inhibition. Recently, we have characterized the properties of dendritic integration in GCs, with special focus on the transition between local/purely reciprocal signaling and global spike signaling. To this end, we have established a holographic uncaging system that allows for simultaneous multi-site stimulation, thereby preventing the inactivation of voltage-dependent conductances expected during sequential uncaging (Go et al. 2019). We find that even though GCs show a rather hyperpolarized membrane potential, a quite small number of coactivated spines on their apical dendrite is sufficient to trigger non-local, dendritic Ca2+ and Na+ spikes, and even global Na+ spikes require no more than ~ 9 simultaneous apical inputs (Mueller and Egger 2020). Thus, the threshold for lateral inhibition is low. Moreover, lateral inhibition may often occur in a restricted manner within a branch or small portion of the GC dendritic tree, due to the dendritic spikes that may not invade the entire apical dendrite or not propagate fully to the soma, as has also been observed in vivo (Wienisch and Murthy 2016, Wallace et al. 2017).
The coincidence of local input and global spiking within a spine substantially increased Ca2+ entry up to threefold, indicating that the low Pr_GABA observed upon unitary activation might be substantially enhanced by additional spike invasion. Even though the summation of Ca2+ signals is spike timing-dependent and might be even sublinear in the case of |∆t| < 10 ms, because of the local inactivation of voltage-dependent conductances (NaVs and CaVs, ∆t: time interval between the local and global spike (Aghvami et al. 2019)).
Recent findings 3: behavioral evidence for a central role for granule cell–mediated GABA release in olfactory processing
To assess the relevance of physiological and network mechanisms of OB computations, it is ultimately necessary to link these mechanisms to odor discrimination behavior. A commonly used behavioral test to investigate odor discrimination in rodents is the go/no-go task (e.g., Bodyak and Slotnick 1999), designed for mice to learn to associate an odor with a reward (Fig. 1c). After about 300–600 trials mice can discriminate even highly similar stimuli such as binary 60:40 versus 40:60 mixtures with accuracies exceeding 90% (Abraham et al. 2004). In addition to the learning curve and discrimination accuracy, the time required to discriminate two odors is a parameter tightly linked to the mechanisms of computations performed by the OB network and, hence, changes in synaptic processing and network function will have a high chance to affect odor discrimination time. The amount of time required by the OB network to discriminate two odors is governed by the similarity and strength of glomerular activity patterns and is independent of sampling behavior (Bhattacharjee et al. 2019). Hence, discrimination of two monomolecular odorants with different glomerular representations requires less time than discrimination of a binary mixture of these odors (Abraham et al. 2004). In a next step, odor discrimination time can be linked to recurrent inhibition, a parameter that can be readily determined by recordings from MTC.
As already discussed above, deletion of the GluA2 subunit from GCs, a manipulation that renders AMPA receptors Ca2+ permeable and strengthens recurrent inhibition, resulted in a gain of function phenotype accelerating discrimination time by 54 ms (Abraham et al. 2010). Conversely, deletion of the GluN1 subunit, causing a complete loss of NMDAR expression, decreased recurrent inhibition and slowed odor discrimination by 62 ms (Abraham et al. 2010). Addressing the role of NaV channels in GABA release at the reciprocal synapse as discussed in detail above, NaV1.2 was identified as the sole NaV channel alpha subunit expressed in mouse GCs (Nunes and Kuner 2018). NaV1.2 was found to be expressed in GC spines and knockdown of it prevented the GC from generating action potentials. Recurrent inhibition recorded in MTC was strongly reduced and discrimination of binary mixtures took 95 ms longer (Nunes and Kuner 2018). Finally, to probe the role of GABAergic inputs that modulate GC function, the GABAA receptor β3 subunit was deleted from GCs, a perturbation that removes all GABAergic input to GCs (Nunes and Kuner 2015). This disinhibition of GC function increased recurrent inhibition and accelerated odor discrimination by 33 ms. When taking together these four molecular perturbations of GCs, performed over a time period of almost 10 years, the strength of recurrent inhibition perfectly well predicts the difference in discrimination time (Fig. 1c), demonstrating a simple generalizable relationship in olfactory bulb processing: more recurrent inhibition accelerates discrimination of similar stimuli and less recurrent inhibition slows it down. While these experiments only assessed recurrent inhibition, it is likely that also lateral inhibition scales according to this principle.
Integration of findings into an emerging hypothesis on lateral inhibition
Two main prerequisites are needed for lateral inhibition via GCs to occur:
(1) The involved GCs have to be excited sufficiently to generate a non-local spike (i.e., a spike that invades a larger dendritic compartment and its spines) or global spike. Evidence for global GC spiking upon uniglomerular activation in vitro has been observed by several groups, including our own (e.g., Schoppa et al. 1998; Egger 2008; Stroh et al. 2012; Burton and Urban 2015); as described above, rather low numbers of coactivated spines on GC apical dendrites (< 10) are sufficient to elicit global spiking and even less to elicit non-local, dendritic spiking (Mueller and Egger 2020). If a given GC can be fired via the activation of the MTCs associated with a particular glomerular column, it belongs to this column. Based on multiwire glomerular stimulation experiments (e.g., Chatterjee et al. 2016), we found that GCs can be fired from more than one glomerular channel independently (perhaps involving not only reciprocal synapses but also axonal MTC inputs). Thus, an individual GC may belong to more than one column, although the respective ensemble of columns will most likely be tightly spaced. In the classical picture (Fig. 2a), GABA release will happen not only recurrently at the reciprocal synapses that have received input from an active glomerulus, but also at other spines invaded by the spike that connect to MCs from other glomerular columns, exerting lateral inhibition. The spatial structure of this lateral inhibition depends on anatomical connectivity and network dynamics and has been proposed to be either isotropic, consistent with a center-surround field as in the retina or rather patchy (reviewed in Murthy 2011; see also Chae et al. 2019). Note, however, that most of the involved studies did not investigate specifically GC-mediated lateral inhibition. In any case, the columnar GC spines (i.e., those that receive synaptic input from the active column) will experience coincident local spine spikes and global spikes and therewith are likely to increase Pr_GABA at their GABA release sites.
(2) Moreover, because of the necessary activation of the NMDARs in the GABAergic active zone, there will be only little GC-mediated lateral inhibition upon activation of a single column because there is no glutamate provided at the lateral spines (Fig. 2b). Instead, we predict that GC-mediated lateral inhibition will happen specifically across coactive columns, such that a local synaptic input originating from a lateral active column will coincide with a global (or regional) columnar spike, resulting in enhanced inhibition of the lateral coactive column (Fig. 2c). The enhancing mechanism is the same as for the coincidence detection described above for recurrent inhibition within an active column. Provided that there are mutually interconnecting GCs in both columns, lateral inhibition will be symmetric. Interestingly, simulations have shown that columnar arrays of GCs may be particularly effective in mediating synchronization for symmetric lateral connectivity (McTavish et al. 2012), in line with our hypothesis.
Therefore, GC-mediated lateral inhibition acts non-topographically (i.e., not isotropically) to enhance recurrent inhibition. Non-topographical lateral interactions in the bulb have been proposed already previously by others based on functional evidence and simulations (e.g., Shepherd et al. 2007; Fantana et al. 2008; Urban and Arevian 2009). While non-topographical lateral inhibition may also happen within the glomerular layer via dedicated connections (e.g., Economo et al. 2016), GC-mediated non-topographical lateral inhibition does not require a specific, pre-established anatomical connectivity. Rather, it is a property of the outlined activity-dependent spine specificity of GABA release, by which functional lateral connectivity is dynamically restricted to coactive columns and thus matched to glomerular activation patterns.
This mechanism will allow GC-mediated lateral inhibition to participate in synthesizing the olfactory percept already at the level of the bulb from the individual glomerular columns, most likely via synchronization in the gamma band which is a widely accepted idea (e.g., Laurent et al. 1996; Kashiwadani et al. 1999; Schoppa 2006b; Brea et al. 2009; McTavish et al. 2012; Peace et al. 2017), while at the same time preventing unwanted energy expenditure and inhibition of other glomerular columns (i.e., if GABA would be released from all spines of an activated GC). Thus, inactive columns are not inhibited and therefore will remain sensitive for new stimuli or changing components.
In other words, the discovered mechanism allows GCs to perform lateral inhibition “on demand,” selectively on coactive mitral cells, and thus can provide directed, dynamically switched lateral inhibition in a sensory system with 1000 receptor channels, therefore explaining the unusual microcircuit of the GC spine/mini-neuron as a means of olfactory combinatorial coding.
Activity-dependent lateral inhibition was already observed earlier in vitro between pairs of mitral cells (MC) by Arevian et al. (2008); one “sending” cell was induced to fire at a high frequency, whereas the other “receiving” cell was either not activated at all or also subjected to evoked spike trains with increasing frequency. The receiving MC showed effects of lateral inhibition by the sending MC within a certain range of its own firing, but never for low or no own firing. The authors argue that the activity-dependent effect is due to increased recruitment of firing interconnected GCs with increased activity, because of the summation of inputs from both sending and receiving MC. While such summation can certainly contribute, our results further clarify the reason for a complete lack of lateral inhibition of silent receiving MCs.
Activity dependence is also reflected in the labeling of glomerular columns spanning all layers of the bulb by markers of neuronal activity (Kauer and Cinelli 1993). More recently, retrograde transsynaptic tracing studies using pseudorabies virus injections have further confirmed this concept, by labeling subsets of glomerular columns dispersed across the bulb, which very frequently contained a substantial fraction of GCs (Willhite et al. 2006; Kim et al. 2011). The authors already speculated that this patchy labeling could be explained by activity-dependent transsynaptic crossing from MC lateral dendrites, i.e., specifically to active GC spines, which matches with the powered release of GABA within activated columns as implied by the results discussed here.
Summary: enigmas lifted
Purpose of reciprocal spines as a unique circuit motif
The isolated spine is required to generate the localized spine spike via locally expressed NaV channels and therewith the localized fast and cooperative activation of both HVACCs and presynaptic NMDARs situated in the GABAergic active zone. Thus, the design of the GC gemmule provides a local coincidence detection circuit, which is essential for OB function and at this point unique within the brain.
Mechanisms for recurrent GABA release
The cooperation of HVACCs and NMDARs explains apparently contradictory early observations. Both require a local action potential to flux Ca2+ ions: HVACCs for activation and generation of the tail current and NMDARs for rapid relief of Mg2+ block. The interplay between NMDARs and HVACCs also could allow to render lateral inhibition conditional on activity within a time window of a few to hundreds of milliseconds in the connected MTC.
Lack of proof for functional reciprocal connectivity from GCs to MTCs
The requirement of NMDAR activation explains why GC APs alone have a very low likelihood of triggering MTC inhibition. Hence, when testing functional connectivity by eliciting APs in the putative presynaptic cell, in this case the GC, the lack of connected MTCs is to be expected.
Sparse global GC spiking
Most of the MTC-induced GC spiking activity will be limited to the gemmules (“mini-neurons”) of the apical dendrite or involve local dendritic spikes and will therefore not be visible to recordings from the GC soma. Furthermore, this spiking activity may also remain undetected in field potential recordings, because the limited space within which currents will flow might not suffice to generate sources and sinks far enough apart to be detected. In our view, global spikes mostly serve to enhance (but not trigger) a GC’s output across coactive columns.
Little inhibitory drive
GCs do not prevent MC spiking but influence MC spiking frequency and therewith could contribute to the synchronization of coactive columns. In this scenario, recurrent inhibition is inherently linked to lateral inhibition.
Apparently missing contribution to lateral inhibition
According to the model proposed here, lateral inhibition does exist, but predominantly between coactive columns and always in combination with recurrent inhibition, making it easy to miss experimentally.
Reciprocal GC output relevant for odor discrimination behavior
Manipulations of essential components of the reciprocal microcircuit, i.e., deletion of the glutamate receptor subunits GluA2 or GluN1 and knockdown of the sodium channel NaV1.2 subunit in mouse GCs, consistently affected odor discrimination time, such that manipulations that both should reduce GABA release (NaV KO, GluN1 KO) result in decreased recurrent inhibition and a slowed odor discrimination. Conversely, the GluA2 KO manipulation should increase GABA release (as well as the GABAAβ3 manipulation that lowers the general inhibitory tone of GCs) and indeed increased recurrent inhibition and accelerated odor discrimination. Since according to our hypothesis lateral inhibition is tightly related to recurrent inhibition, it is likely to be affected in a similar manner. Hence, our framework is further closing the loop from molecules to synapses, networks, and behavior in olfactory bulb function.
References
Abraham NM, Egger V, Shimshek DR et al (2010) Synaptic inhibition in the olfactory bulb accelerates odor discrimination in mice. 65:399–411. https://doi.org/10.1016/j.neuron.2010.01.009
Abraham NM, Spors H, Carleton A et al (2004) Maintaining accuracy at the expense of speed: stimulus similarity defines odor discrimination time in mice. Neuron 44:865–876. https://doi.org/10.1016/j.neuron.2004.11.017
Aghvami SS, Müller M, Araabi BN, Egger V (2019) Coincidence detection within the excitable rat olfactory bulb granule cell spines. J Neurosci 39:584–595. https://doi.org/10.1523/jneurosci.1798-18.2018
Apicella A, Yuan Q, Scanziani M, Isaacson JS (2010) Pyramidal cells in piriform cortex receive convergent input from distinct olfactory bulb glomeruli. J Neurosci 30:14255–14260. https://doi.org/10.1523/jneurosci.2747-10.2010
Arevian AC, Kapoor V, Urban NN (2008) Activity-dependent gating of lateral inhibition in the mouse olfactory bulb. Nat Neurosci 11:80–87. https://doi.org/10.1038/nn2030
Aungst JL, Heyward PM, Puche AC et al (2003) Centre–surround inhibition among olfactory bulb glomeruli. Nature 426:623–629. https://doi.org/10.1038/nature02185
Bartel DL, Rela L, Hsieh L, Greer CA (2015) Dendrodendritic synapses in the mouse olfactory bulb external plexiform layer. J Comp Neurol 523:1145–1161. https://doi.org/10.1002/cne.23714
Belluscio L, Lodovichi C, Feinstein P et al (2002) Odorant receptors instruct functional circuitry in the mouse olfactory bulb. Nature 419:296–300. https://doi.org/10.1038/nature01001
Bhattacharjee AS, Konakamchi S, Turaev D et al (2019) Similarity and strength of glomerular odor representations define a neural metric of sniff-invariant discrimination time. Cell Reports 28:2966-2978.e5. https://doi.org/10.1016/j.celrep.2019.08.015
Bodyak N, Slotnick B (1999) Performance of mice in an automated olfactometer: odor detection, discrimination and odor memory. Chem Senses 24:637–645. https://doi.org/10.1093/chemse/24.6.637
Brea JN, Kay LM, Kopell NJ (2009) Biophysical model for gamma rhythms in the olfactory bulb via subthreshold oscillations. Proc National Acad Sci 106:21954–21959. https://doi.org/10.1073/pnas.0910964106
Burton SD (2017) Inhibitory circuits of the mammalian main olfactory bulb. J Neurophysiol 118:2034–2051. https://doi.org/10.1152/jn.00109.2017
Burton SD, Urban NN (2015) Rapid feedforward inhibition and asynchronous excitation regulate granule cell activity in the mammalian main olfactory bulb. J Neurosci 35:14103–14122. https://doi.org/10.1523/jneurosci.0746-15.2015
Bywalez WG, Patirniche D, Rupprecht V et al (2015) Local postsynaptic voltage-gated sodium channel activation in dendritic spines of olfactory bulb granule cells. Neuron. https://doi.org/10.1016/j.neuron.2014.12.051
Cang J, Isaacson JS (2003) In vivo whole-cell recording of odor-evoked synaptic transmission in the rat olfactory bulb. 23:4108–4116
Cazakoff BN, Lau BYB, Crump KL et al (2014) Broadly tuned and respiration-independent inhibition in the olfactory bulb of awake mice. Nat Neurosci 17:569–576. https://doi.org/10.1038/nn.3669
Chae H, Kepple DR, Bast WG et al (2019) Mosaic representations of odors in the input and output layers of the mouse olfactory bulb. Nat Neurosci 22:1306–1317. https://doi.org/10.1038/s41593-019-0442-z
Chatterjee M, de Pallares FP, los C, Loebel A, et al (2016) Sniff-like patterned input results in long-term plasticity at the rat olfactory bulb mitral and tufted cell to granule cell synapse. Neural Plast 2016:1–16. https://doi.org/10.1155/2016/9124986
Chen WR, Xiong W, Shepherd GM (2000) Analysis of relations between NMDA receptors and GABA release at olfactory bulb reciprocal synapses. Neuron 25:625–633
Cleland TA, Sethupathy P (2006) Non-topographical contrast enhancement in the olfactory bulb. Bmc Neurosci 7:7. https://doi.org/10.1186/1471-2202-7-7
Crespo C, Liberia T, Blasco-Ibáñez JM et al (2013) The circuits of the olfactory bulb. The exception as a rule. Anatomical Rec 296:1401–1412. https://doi.org/10.1002/ar.22732
Economo MN, Hansen KR, Wachowiak M (2016) Control of mitral/tufted cell output by selective inhibition among olfactory bulb glomeruli. Neuron 91:397–411. https://doi.org/10.1016/j.neuron.2016.06.001
Egger V (2008) Synaptic sodium spikes trigger long-lasting depolarizations and slow calcium entry in rat olfactory bulb granule cells. Eur J Neurosci 27:2066–2075. https://doi.org/10.1111/j.1460-9568.2008.06170.x
Egger V, Diamond JS (2020) A17 amacrine cells and olfactory granule cells: parallel processors of early sensory information. Front Cell Neurosci. 2020 Nov 5;14:600537. https://doi.org/10.3389/fncel.2020.600537. eCollection 2020
Egger V, Svoboda K, Mainen ZF (2003) Mechanisms of lateral inhibition in the olfactory bulb: efficiency and modulation of spike-evoked calcium influx into granule cells. J Neurosci 23:7551–7558. https://doi.org/10.1523/jneurosci.23-20-07551.2003
Egger V, Svoboda K, Mainen ZF (2005) 25:3521. https://doi.org/10.1523/jneurosci.4746-04.2005
Egger V, Urban NN (2006) Dynamic connectivity in the mitral cell–granule cell microcircuit. Semin Cell Dev Biol 17:424–432. https://doi.org/10.1016/j.semcdb.2006.04.006
Fantana AL, Soucy ER, Meister M (2008) Rat olfactory bulb mitral cells receive sparse glomerular inputs. Neuron 59:802–814. https://doi.org/10.1016/j.neuron.2008.07.039
Franks KM, Isaacson JS (2006) Strong single-fiber sensory inputs to olfactory cortex: implications for olfactory coding. Neuron 49:357–363. https://doi.org/10.1016/j.neuron.2005.12.026
Fukunaga I, Herb JT, Kollo M et al (2014) Independent control of gamma and theta activity by distinct interneuron networks in the olfactory bulb. Nat Neurosci 17:1208–1216. https://doi.org/10.1038/nn.3760
Geramita M, Urban NN (2017) Differences in glomerular-layer-mediated feedforward inhibition onto mitral and tufted cells lead to distinct modes of intensity coding. J Neurosci 37:1428–1438. https://doi.org/10.1523/jneurosci.2245-16.2016
Ghosh S, Larson SD, Hefzi H et al (2011) Sensory maps in the olfactory cortex defined by long-range viral tracing of single neurons. Nature 472:217–220. https://doi.org/10.1038/nature09945
Go MA, Mueller M, Castañares ML et al (2019) A compact holographic projector module for high-resolution 3D multi-site two-photon photostimulation. Plos One 14:e0210564. https://doi.org/10.1371/journal.pone.0210564
Halabisky B, Friedman D, Radojicic M, Strowbridge BW (2000) Calcium influx through NMDA receptors directly evokes GABA release in olfactory bulb granule cells. J Neurosci : the official journal of the Society for Neuroscience 20:5124–5134
Igarashi KM, Ieki N, An M et al (2012) Parallel mitral and tufted cell pathways route distinct odor information to different targets in the olfactory cortex. 32:7970–7985. https://doi.org/10.1523/jneurosci.0154-12.2012
Isaacson JS (2001) Mechanisms governing dendritic γ-aminobutyric acid (GABA) release in the rat olfactory bulb. Proc National Acad Sci 98:337–342. https://doi.org/10.1073/pnas.98.1.337
Isaacson JS, Strowbridge BW (1998) Olfactory reciprocal synapses: dendritic signaling in the CNS. Neuron 20:749–761
Kampa BM, Clements J, Jonas P, Stuart GJ (2004) Kinetics of Mg2+ unblock of NMDA receptors: implications for spike-timing dependent synaptic plasticity. J Physiology 556:337–345. https://doi.org/10.1113/jphysiol.2003.058842
Kashiwadani H, Sasaki YF, Uchida N, Mori K (1999) Synchronized oscillatory discharges of mitral/tufted cells with different molecular receptive ranges in the rabbit olfactory bulb. J Neurophysiol 82:1786–1792. https://doi.org/10.1152/jn.1999.82.4.1786
Kato HK, Chu MW, Isaacson JS, Komiyama T (2012) Dynamic sensory representations in the olfactory bulb: modulation by wakefulness and experience. Neuron 76:962–975. https://doi.org/10.1016/j.neuron.2012.09.037
Kato HK, Gillet SN, Peters AJ et al (2013) Parvalbumin-Expressing Interneurons Linearly Control Olfactory Bulb Output. 80:1218–1231. https://doi.org/10.1016/j.neuron.2013.08.036
Kauer JS, Cinelli AR (1993) Are there structural and functional modules in the vertebrate olfactory bulb? Microsc Res Techniq 24:157–167. https://doi.org/10.1002/jemt.1070240207
Kay LM (2015) Olfactory system oscillations across phyla. Curr Opin Neurobiol 31:141–147. https://doi.org/10.1016/j.conb.2014.10.004
Kim DH, Phillips ME, Chang AY et al (2011) Lateral connectivity in the olfactory bulb is sparse and segregated. Front Neural Circuit 5:5. https://doi.org/10.3389/fncir.2011.00005
Kishi K, Mori K, Ojima H (1984) Distribution of local axon collaterals of mitral, displaced mitral, and tufted cells in the rabbit olfactory bulb. J Comp Neurol 225:511–526. https://doi.org/10.1002/cne.902250404
Lage-Rupprecht V, Zhou L, Bianchini G et al (2020) Presynaptic NMDA receptors cooperate with local action potentials to implement activity-dependent GABA release from the reciprocal olfactory bulb granule cell spine. eLife 2020;9:e63737 https://doi.org/10.7554/eLife.63737
Laurent G, Wehr M, Davidowitz H (1996) Temporal representations of odors in an olfactory network. J Neurosci 16:3837–3847. https://doi.org/10.1523/jneurosci.16-12-03837.1996
Malnic B, Hirono J, Sato T, Buck LB (1999) Combinatorial receptor codes for odors. Cell 96:713–723. https://doi.org/10.1016/s0092-8674(00)80581-4
Matsuno T, Kiyokage E, Toida K (2017) Synaptic distribution of individually labeled mitral cells in the external plexiform layer of the mouse olfactory bulb. J Comp Neurol 525:1633–1648. https://doi.org/10.1002/cne.24148
McTavish TS, Migliore M, Shepherd GM, Hines ML (2012) Mitral cell spike synchrony modulated by dendrodendritic synapse location. Front Comput Neurosc 6:3. https://doi.org/10.3389/fncom.2012.00003
Miyamichi K, Shlomai-Fuchs Y, Shu M et al (2013) Dissecting local circuits: parvalbumin interneurons underlie broad feedback control of olfactory bulb output. Neuron 80:1232–1245. https://doi.org/10.1016/j.neuron.2013.08.027
Mombaerts P (1999) Seven-transmembrane proteins as odorant and chemosensory receptors. Science 286:707–711. https://doi.org/10.1126/science.286.5440.707
Monyer H, Sprengel R, Schoepfer R et al (1992) Heteromeric NMDA receptors: molecular and functional distinction of subtypes. Science 256:1217–1221. https://doi.org/10.1126/science.256.5060.1217
Mueller M, Egger V (2020) Dendritic integration in olfactory bulb granule cells upon simultaneous multispine activation: low thresholds for nonlocal spiking activity. Plos Biol 18:e3000873. https://doi.org/10.1371/journal.pbio.3000873
Murthy VN (2011) Olfactory maps in the brain. Neuroscience 34:233–258. https://doi.org/10.1146/annurev-neuro-061010-113738
Nagayama S, Igarashi KM, Manabe H, Mori K (2014) The olfactory system, from odor molecules to motivational behaviors. 133–160. https://doi.org/10.1007/978-4-431-54376-3_7
Najac M, Jan DDS, Reguero L et al (2011) Monosynaptic and polysynaptic feed-forward inputs to mitral cells from olfactory sensory neurons. J Neurosci 31:8722–8729. https://doi.org/10.1523/jneurosci.0527-11.2011
Nunes D, Kuner T (2018) Axonal sodium channel NaV1.2 drives granule cell dendritic GABA release and rapid odor discrimination. PLoS biology 16:e2003816. https://doi.org/10.1371/journal.pbio.2003816
Nunes D, Kuner T (2015) Disinhibition of olfactory bulb granule cells accelerates odour discrimination in mice. Nat Commun 6:8950. https://doi.org/10.1038/ncomms9950
Peace ST, Johnson BC, Li G et al (2017) Coherent olfactory bulb gamma oscillations arise from coupling independent columnar oscillators. Biorxiv 213827. https://doi.org/10.1101/213827
Pinato G, Midtgaard J (2003) Regulation of granule cell excitability by a low-threshold calcium spike in turtle olfactory bulb. J Neurophysiol 90:3341–3351. https://doi.org/10.1152/jn.00560.2003
Pressler RT, Strowbridge BW (2017) Direct recording of dendrodendritic excitation in the olfactory bulb: divergent properties of local and external glutamatergic inputs govern synaptic integration in granule cells. J Neurosci 37:11774–11788. https://doi.org/10.1523/jneurosci.2033-17.2017
Pressler RT, Strowbridge BW (2019) Functional specialization of interneuron dendrites: identification of action potential initiation zone in axonless olfactory bulb granule cells. J Neurosci 39:9674–9688. https://doi.org/10.1523/jneurosci.1763-19.2019
Rall W, Shepherd GM, Reese TS, Brightman MW (1966) Dendrodendritic synaptic pathway for inhibition in the olfactory bulb. Exp Neurol 14:44–56. https://doi.org/10.1016/0014-4886(66)90023-9
Sailor KA, Valley MT, Wiechert MT et al (2016) Persistent structural plasticity optimizes sensory information processing in the olfactory bulb. Neuron 91:384–396. https://doi.org/10.1016/j.neuron.2016.06.004
Schoppa NE (2006a) AMPA/kainate receptors drive rapid output and precise synchrony in olfactory bulb granule cells. The Journal of neuroscience : the official journal of the Society for Neuroscience 26:12996–13006. https://doi.org/10.1523/jneurosci.3503-06.2006
Schoppa NE (2006b) Synchronization of olfactory bulb mitral cells by precisely timed inhibitory inputs. Neuron 49:271–283. https://doi.org/10.1016/j.neuron.2005.11.038
Schoppa NE, Kinzie JM, Sahara Y et al (1998) Dendrodendritic inhibition in the olfactory bulb is driven by NMDA receptors. J Neurosci 18:6790–6802. https://doi.org/10.1523/jneurosci.18-17-06790.1998
Shepherd GM, Chen WR, Greer CA (2004) The synaptic organization of the brain. 165–216. https://doi.org/10.1093/acprof:oso/9780195159561.003.0005
Shepherd GM, Chen WR, Willhite D et al (2007) The olfactory granule cell: from classical enigma to central role in olfactory processing. Brain Res Rev 55:373–382. https://doi.org/10.1016/j.brainresrev.2007.03.005
Stroh O, Freichel M, Kretz O et al (2012) NMDA Receptor-dependent synaptic activation of TRPC channels in olfactory bulb granule cells. J Neurosci 32:5737–5746. https://doi.org/10.1523/jneurosci.3753-11.2012
Urban NN, Arevian AC (2009) Computing with dendrodendritic synapses in the olfactory bulb. Annals of the New York Academy of Sciences 1170:264–269. https://doi.org/10.1111/j.1749-6632.2009.03899.x
Wallace JL, Wienisch M, Murthy VN (2017) Development and refinement of functional properties of adult-born neurons. Neuron 96(4):883-896.e887. https://doi.org/10.1016/j.neuron.2017.09.039
Wellis DP, Scott JW (1990) Intracellular responses of identified rat olfactory bulb interneurons to electrical and odor stimulation. J Neurophysiol 64:932–947. https://doi.org/10.1152/jn.1990.64.3.932
Wienisch M, Murthy VN (2016) Population imaging at subcellular resolution supports specific and local inhibition by granule cells in the olfactory bulb. Sci Rep 6:29308. https://doi.org/10.1038/srep29308
Willhite DC, Nguyen KT, Masurkar AV et al (2006) Viral tracing identifies distributed columnar organization in the olfactory bulb. Proc Nat Acad Sci 103:12592–12597. https://doi.org/10.1073/pnas.0602032103
Wyllie DJA, Béhé P, Colquhoun D (1998) Single-channel activations and concentration jumps: comparison of recombinant NR1a/NR2A and NR1a/NR2D NMDA receptors. J Physiology 510:1–18. https://doi.org/10.1111/j.1469-7793.1998.001bz.x
Yokoi M, Mori K, Nakanishi S (1995) Refinement of odor molecule tuning by dendrodendritic synaptic inhibition in the olfactory bulb. Proc National Acad Sci 92:3371–3375. https://doi.org/10.1073/pnas.92.8.3371
Zelles T, Boyd JD, Hardy AB, Delaney KR (2006) Branch-specific Ca2+ influx from Na+-dependent dendritic spikes in olfactory granule cells. The Journal of neuroscience : the official journal of the Society for Neuroscience 26:30–40. https://doi.org/10.1523/jneurosci.1419-05.2006
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Open Access funding enabled and organized by Projekt DEAL. Both authors received funding by the SPP 1392 “Integrative Analysis of Olfaction.” VE has received major funding from the BMBF (FKZ 01GQ1104/1502).
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Egger, V., Kuner, T. Olfactory bulb granule cells: specialized to link coactive glomerular columns for percept generation and discrimination of odors. Cell Tissue Res 383, 495–506 (2021). https://doi.org/10.1007/s00441-020-03402-7
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DOI: https://doi.org/10.1007/s00441-020-03402-7