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date: 22 January 2019

The Nuclei of the Lateral Lemniscus

Abstract and Keywords

Parallel processing streams guide ascending auditory information through the processing hierarchy of the auditory brainstem. Many of these processing streams converge in the lateral lemnisucus, the fiber bundle that connects the cochlear nuclei and superior olivary complex with the inferior colliculus. The neuronal populations within the lateral lemniscus can be segregated according to their gross structure-function relationships into three distinct nuclei. These nuclei are termed ventral, intermedial, and dorsal nucleus, according to their position within the lemniscal fiber bundle. The complexity of their input pattern increases in an ascending fashion. The three nuclei employ different neurotransmitters and exhibit distinct synaptic and biophysical features. Yet they all share a large heterogeneity. Functionally, the ventral nucleus of the lateral lemniscus has been hypothesized to reduce spectral splatter by generating a rapid, temporally precise feedforward onset inhibition in the inferior colliculus. In the intermedial nucleus of the lateral lemniscus a cross-frequency integration has been observed. The hallmark of the dorsal nucleus of the lateral lemniscus is the generation of a long-lasting inhibition in its contralateral counterpart and the inferior colliculus. This inhibition is proposed to generate a suppression of sound sources during reverberations and could act as a temporal filter capable of removing spurious interaural time differences. While great advances have been made in understanding the role that these nuclei play in auditory processing, the functional diversity of the individual neuronal responsiveness within each nucleus remains largely unsolved.

Keywords: nuclei of the lateral lemniscus, auditory brainstem, structure-function relationship, tonotopy, synaptic integration, supra-threshold spike pattern, spectral filter, temporal filter

In this chapter, we summarize and discuss the current literature concerning the auditory brainstem nuclei located in the lateral lemniscus (LL). In line with classical neuroscience research, we relate structure to function in order to elucidate the processing mechanisms of these auditory brainstem nuclei. We first look at the structure of the auditory nuclei, which are embedded within this fiber bundle. We summarize the different types of transmitters, specific expression patterns, specialized morphologies, and how the tonotopy is arranged. We continue to review the biophysical properties of the different cell types within the LL. These properties include action potential generation and firing behavior, as well as synaptic input properties. Furthermore, we discuss functional data showing how sound information is integrated in the nuclei of the LL. These considerations will guide us to form a hypothesis regarding their functional significance. Finally, by bringing these different aspects together, we seek to obtain a glimpse of the processing power of the auditory nuclei that are immersed in the fiber bundle of the LL.

The Structure and Connectivity of the Auditory Nuclei within the Lateral Lemniscus

The LL is formed by a thick fiber bundle, which connects the auditory brainstem with the auditory midbrain (Figure 1). Auditory information travels from the cochlear nucleus, the superior olivary complex (SOC), and the neurons within the LL to the inferior colliculus (IC). Within this thick axonal bundle, several nuclei are intermingled, the nuclei of the LL.

The Nuclei of the Lateral LemniscusClick to view larger

Figure 1. Simplified input output pattern of the nuclei of the lateral lemniscus (NLL). The ventral nucleus receives inputs from the anterior and posterior ventral cochlear nucleus (AVCN and PVCN) and the medial and lateral nucleus of the trapezoid body (MNTB and LNTB) from the superior olivary complex (SOC). In addition, ventral nucleus of the lateral lemniscus (VNLL) neurons themselves are indicated to generate collaterals within the VNLL while their ascending projections target the intermedial nucleus of the lateral lemniscus (INLL), dorsal nucleus of the lateral lemniscus (DNLL), and inferior colliculus (IC). The INLL receives also input from the ventral cochlear nuclei (CN) and the SOC. Input from the SOC is derived from medial and lateral superior olive neurons (MSO and LSO) the MNTB, and the superior paraolivary nucleus (SPN). INLL input projects the DNLL and IC. DNLL neurons receive inputs from the CN, SOC, and the LL nuclei. The output structures of the DNLL are the ipsilateral IC and the contralateral IC and DNLL via the commissure of Probst (CP). All nuclei of the LL receive cholinergic modulator inputs. Descending inputs from cortical structure appear in all LL nuclei, in the DNLL with a tonotopic arrangement.

Separation into Nuclei

The neuronal populations in the LL can be separated. The most distinct part of the LL is the dorsal part that makes up the dorsal nucleus of the lateral lemniscus (DNLL). This structure is well defined as a roundish nucleus at the junction of the LL and commissure of Probst, ventral to the border of the IC. DNLL neurons are separated by those that follow ventrally in the LL. In bats, a region of the intermedial nucleus of the lateral lemniscus (INLL) is well defined. In rodents, this region merges more continuously into the elongated ventral nucleus of the lateral lemniscus (VNLL). Thus, the border between INLL/VNLL is difficult to define in some species. The boarders of the VNLL are best defined at lateral and ventral edge.

Ventral nucleus of the lateral lemniscus.

The overall organization of the VNLL seems complex and is species dependent. In general, the VNLL consists of a heterogeneous group of various cell types. This heterogeneity is obvious in the echolocating bat Eptesicus fuscus, where a subset of globular cells is aggregated to form the columnar region (Covey & Casseday, 1986), while the rest of the VNLL contains other cell types. These other cell types are dominated by multipolar neurons (Covey & Casseday, 1986). In rodents, this organization is absent, but the ventral and dorsal VNLL parts still hold differences in the neuronal population. In the gerbil VNLL globular cells are more prominent in the ventral aspect compared to the dorsal part (Mylius, Brosch, Scheich, & Budinger, 2013). In the same species multipolar and elongated cells are present in the entire VNLL with a bias toward the dorsal part (Mylius et al., 2013). This distribution of neuronal morphologies appears to match with that of guinea pig (Schofield & Cant, 1997), rat (Merchan & Berbel, 1996; Zhao & Wu, 2001), cat (Adams, 1979), and humans (Adams, 1997). Thus, as a general emerging picture, the VNLL is composed of a morphologically heterogeneous cell population, with biased localizations for most mammals: globular cells being located in the ventral region, while elongated and multipolar cells are more frequent in the dorsal part.

A morphological specialty of ventral, globular VNLL neurons is their large glutamatergic input that is targeted toward their soma. This endbulb type synapse was found in cats (Adams, 1997; Smith, Massie, & Joris, 2005; Stotler, 1953), guinea pig (Schofield & Cant, 1997), mice (Caspari, Baumann, Garcia-Pino, & Koch, 2015), gerbils (Berger, Meyer, Ammer, & Felmy, 2014), rats (Friauf & Ostwald, 1988), bats (Covey & Casseday, 1986; Vater, Covey, & Casseday, 1997), and humans (Adams, 1997). Globular VNLL neurons therefore form a similar synaptic input-output structure as has been found in the MNTB (calyx of Held) and the anterior ventral cochlear nucleus (endbulb of Held).

The heterogeneity of VNLL cells is also given in the expression of the diverse transmitter types. In the VNLL, glycinergic and GABergic cells are present (Moore & Trussell, 2017; Riquelme, Saldana, Osen, Ottersen, & Merchan, 2001; Saint Marie, Shneiderman, & Stanforth, 1997; Ueyama et al., 1999; Vater, Kossl, & Horn, 1992). The lack of glutamatergic neurons in the VNLL is further documented by in-situ hybridizations that showed only expression of vesicular inhibitory amino acid transporter (T. Ito, Bishop, & Oliver, 2011). Interestingly, it was recently demonstrated that glycine and γ-aminobutyric acid (GABA) are co-released simultaneously from a subset of VNLL neurons in the IC (Moore & Trussell, 2017). Besides GABAergic and glycinergic cells, a population of neurons in the VNLL stains for neither (Riquelme et al., 2001; Saint Marie et al., 1997), indicating a small portion of neurons with an unresolved transmitter type. With respect to calcium binding proteins, VNLL neurons have been shown to be parvalbuminergic (Caicedo, d'Aldin, Puel, & Eybalin, 1996; Lohmann & Friauf, 1996). In guinea pigs, VNLL neurons are also positive for calbindin (Caicedo et al., 1996), while in bats and in rats calretinin positive staining is observed (Lohmann & Friauf, 1996; Vater & Braun, 1994). Ion channel labelling showed that VNLL neurons in bats express Kv1.1. This labelling was most prominent in the columnar region (Rosenberger, Fremouw, Casseday, & Covey, 2003). In rodents, HCN1 staining is more prominent in the dorsal part, while HCN2 staining is present throughout the VNLL (Caspari et al., 2015; Koch, Braun, Kapfer, & Grothe, 2004). GABAB receptors have been described in the VNLL with a stronger density in the dorsal aspect (Jamal, Zhang, Finlayson, Porter, & Zhang, 2011). GABAA receptors appear to differ in subunit composition between the dorsal and the ventral VNLL (Campos, de Cabo, Wisden, Juiz, & Merlo, 2001). Finally, nicotinic acetylcholine (ACH) receptors have been detected throughout the VNLL (Happe & Morley, 2004). Taken together, neurons in the VNLL form a heterogeneous population based on morphology and protein expression patterns. Since globular cells receive a specific type of synaptic input and are located mainly in the ventral aspect of the VNLL, they constitute a rather distinct population of specialized neurons. It is expected that overall the VNNL cell populations show different biophysical adaptations as indicated by the antibody staining for membrane channels.

The tonotopic organization of the VNLL is less clear cut compared to other auditory brainstem nuclei. In vivo recordings and tracing studies suggest that the tonotopic organization is complex in the VNLL (Covey & Casseday, 1986, 1991; Kelly, Liscum, van Adel, & Ito, 1998; Malmierca, Leergaard, Bajo, Bjaalie, & Merchan, 1998; Merchan & Berbel, 1996). In rats, it has been shown that the most lateral neurons of the VNLL represent largely low frequencies and more central neurons high frequencies (Kelly, Liscum, et al., 1998; Merchan & Berbel, 1996). In the cat, frequency domains are originally reported to be organized in a dorso-ventral order (Aitkin, Anderson, & Brugge, 1970), but have since been shown to be organized in a patchy way (Malmierca et al., 1998). Only in the bat columnar region, the tonotopy is well defined and follows a high- to low-frequency gradient along the ventro-dorsal axis (Covey & Casseday, 1986, 1991).

VNLL neurons receive inputs mainly from the cochlear nuclei and the medial nucleus of the trapezoid body (Glendenning, Brunso-Bechtold, Thompson, & Masterton, 1981; Huffman & Covey, 1995; Kelly, van Adel, & Ito, 2009; Spangler, Warr, & Henkel, 1985; Zook & Casseday, 1987). In bats, evidence for a small projection from the lateral nucleus of the trapezoid body was presented (Huffman & Covey, 1995). The large somatic endbulb synapses on globular VNLL neurons originates from neurons in the posterior ventral cochlear nuclei most likely from octopus cells (Adams, 1997; Friauf & Ostwald, 1988; Schofield & Cant, 1997; Smith et al., 2005). In addition bushy cells innervate the region of the VNLL (Friauf & Ostwald, 1988; Huffman & Covey, 1995; Smith, Joris, Carney, & Yin, 1991; Smith, Joris, & Yin, 1993), most likely without the restriction towards globular VNLL neurons. Also axons originating in the core of the posterior cochlear nucleus innervate the overall VNLL (Thompson, 1998; Warr, 1969). Inhibitory inputs to the VNLL originate from the medial nucleus of the trapezoid body or stem from internal collaterals. Thus, both excitatory and inhibitory inputs to VNLL neurons are fast and precisely timed. The main projection of VNLL neurons is to the IC (Kelly et al., 2009; Moore & Trussell, 2017; Tanaka, Otani, Tokunaga, & Sugita, 1985; Willard & Martin, 1983; Zook & Casseday, 1982, 1987). Besides these direct projections, axons of VNLL neurons are thought to terminate on INLL and the DNLL neurons (Kelly et al., 2009) and within the VNLL itself, where globular neurons might feedforward inhibition to other VNLL neurons (Nayagam, Clarey, & Paolini, 2005). In addition, VNLL neurons receive cholinergic inputs, most likely in form of volume transmission. This follows from the presence of nicotinic (Happe & Morley, 2004) and metabotropic (Franzen et al., 2015) ACH receptors. Where these cholinergic fibers might originate from is so far not fully clarified.

Intermedial nucleus of the lateral lemniscus

As some authors define a short segment of the lateral lemniscus dorsal to the VNLL and ventral to the DNLL as INLL, we will discuss the anatomical and morphological properties of these neurons. This region appears morphologically better defined in bats compared to other mammals.

Elongated cells sending their dendrites orthogonal to the ascending fibers are the hallmark of the INLL, as described in bats (Covey & Casseday, 1986) and gerbils (Mylius et al., 2013). In addition, the presence of globular cells and multipolar cells has been described in bats (Covey & Casseday, 1986) and gerbils respectively (Mylius et al., 2013). In cats, elongated and multipolar neurons are also located in this region (Adams, 1979; Glendenning et al., 1981). Thus, the common denominator of neuron types in the INLL across species appears to be elongated, bipolar morphologies.

The neuronal population assigned to the INLL expresses predominantly parvalbumin (Caicedo et al., 1996; Lohmann & Friauf, 1996; Vater & Braun, 1994). Some of these neurons are GABAergic in bats (Vater et al., 1992), but in cats, rats and mice most neurons are non-GABAergic and non-glycinergic (T. Ito et al., 2011; Riquelme et al., 2001; Saint Marie et al., 1997; Ueyama et al., 1999). Using in-situ hybridizations T. Ito et al. (2011) observed only vesicular glutamate expressing cells in the INLL of rats and mice. Thus, the interface between the VNLL and the DNLL is generated by a population of glutamatergic, excitatory neurons. As in the VNLL, the INLL region expresses nicotinic ACH receptors (Happe & Morley, 2004). In INLL Kv1.1 was only expressed in a third of all INLL neurons (Rosenberger et al., 2003).

For the tonotopy of the INLL, the best frequencies of neurons decrease along a ventro-dorso axis, along the ascending fibers in bats (Covey & Casseday, 1991; Yavuzoglu, Schofield, & Wenstrup, 2010). In rats, however, a specific tonotopic organization of this INLL region seems not apparent at a first glance (Kelly, Buckthought, & Kidd, 1998). Neurons of the INLL receive inputs from the major nuclei of the superior olivary complex and the cochlear nuclei (Kelly et al., 2009; Thompson, 1998) and send their axons to the inferior colliculus (Kelly et al., 2009; Zook & Casseday, 1982).

Dorsal nucleus of the lateral lemniscus

The crossing of two fiber bundles is an excellent landmark of the DNLL. Here, the fibers of the lateral lemniscus and the commissure of Probst generate a T-junction. The commissure of Probst is a fiber bundle that connects the DNLL hemispheres with each other. The neurons at this fiber crossing represent the first cluster of neurons ventral to the IC border. Thus, the DNLL is one of the “simplest to spot” nuclei in the LL. However, lateral to the DNLL, a small cell population resides that has been attributed to a different nucleus called the sagulum nucleus, a neuronal population that will not be addressed here further.

Neurons in the DNLL come in different shapes. In one study, the axial diameters of the soma were quantified and subsequently separated based on their shape. Nine types of neurons could be identified (Kane & Barone, 1980), categorized into round ovoid and elongated, each with three different sizes. Other studies defined multipolar, bipolar, round and elongated cell types ( Adams, 1979; Bajo, Merchan, Lopez, & Rouiller, 1993; Iwahori, 1986; Mylius et al., 2013; Wu & Kelly, 1995). Importantly, all of the different morphological cell types exhibited the same action potential firing properties (Wu & Kelly, 1995). Therefore, the morphological differentiation seems not to segregate DNLL neurons into biophysically distinct neurons. The dendrites of DNLL neurons have received little attention regarding their extent and orientation. Morphologically, these dendrites are relatively thin and without spiny protrusions. Overall, the heterogeneity of DNLL neurons might rather reflect a large continuum of morphological variability than clearly defined subsets of neurons. Whether such a large morphological variability supports a specific function remains unresolved.

Despite this morphological heterogeneity at least 80% of DNLL neurons were shown to be GABAergic (Riquelme et al., 2001; Saint Marie et al., 1997; Ueyama et al., 1999; Vater et al., 1992). The remaining 20% of neurons were also negative for glycine (Saint Marie et al., 1997). It remains unclear whether this cell population contains glutamatergic or neuro-modulatory transmitters and how it is inter-connected within the auditory brainstem pathways. Expression patterns have been determined by immunohistochemistry showing that DNLL neurons preferentially express the slow calcium buffer parvalbumin (Ammer, Grothe, & Felmy, 2012; Caicedo et al., 1996; Lohmann & Friauf, 1996; Seto-Ohshima, Aoki, Semba, Emson, & Heizmann, 1990; Vater & Braun, 1994). Interestingly, 20% of DNLL neurons are calbindinergic (Ammer et al., 2012; Caicedo et al., 1996; Lohmann & Friauf, 1996). Whether this calbindinergic subset matches with the non-GABAergic neurons is not known. Other functional markers whose expression has been demonstrated are Kv1.1 (Rosenberger et al., 2003), HCN2 but not HCN1 (Koch et al., 2004), GABAA receptors (Campos et al., 2001), low amounts of GABAB2 receptors (Jamal et al., 2011), and VGlut2 (Di Bonito et al., 2013).

Like many other auditory brainstem nuclei, the DNLL is tonotopically organized. The tonotopic organization has been evaluated either by activity markers or by synaptic connectivity with respect to other well-known topographic maps. In gerbils, early studies suggested that low frequencies are represented in the dorso-medial portion, while high frequencies are present in the ventro-medial part (Ryan, Woolf, & Sharp, 1982). This dorso-medial tonotopical arrangement was also described by retrograde labeling of the IC (Bajo, Merchan, Malmierca, Nodal, & Bjaalie, 1999; Shneiderman, Stanforth, Henkel, & Saint Marie, 1999) and anterograde labeling of the SOC (Shneiderman, Oliver, & Henkel, 1988; Shneiderman et al., 1999). Moreover, the dorso-ventral tonotopic axis is in agreement with in vivo studies performed in bats (Covey, 1993; Markovitz & Pollak, 1994). In rats, however, two studies indicated that the tonotopy follows a concentric arrangement. Here, low frequencies are represented in the center, while high frequencies are present in the outer shell of the DNLL (Kelly, Liscum, et al., 1998; Merchan, Saldana, & Plaza, 1994).

Ascending projections arrive at the DNLL from the nuclei of the SOC, and information is then forwarded from the DNLL to the IC. Inputs arise mainly from the medial and lateral superior olive (Glendenning et al., 1981; Henkel, 1997; Huffman & Covey, 1995; Kelly et al., 2009; Shneiderman et al., 1999; Siveke, Pecka, Seidl, Baudoux, & Grothe, 2006). Besides these inputs, it has been indicated that some axons originate in the superior para-olivary nuclei (Kelly et al., 2009) and the medial nucleus of the trapezoid body (Siveke et al., 2006; Spangler et al., 1985). For rats (Kelly et al., 2009) and bats (Covey & Casseday, 1986; Huffman & Covey, 1995; Yang, Liu, & Pollak, 1996; Zook & Casseday, 1985) connections from the VNLL and INLL and in cats (Glendenning et al., 1981) also minor collaterals from the cochlear nucleus to DNLL neurons have been described. Also inputs from the cochlear nucleus to the DNLL have been observed (Thompson, 1998; Warr, 1969). Besides this ascending input, a small number of descending inputs from higher brain areas enter and likely terminate in the DNLL in a tonotopic fashion (Budinger, Brosch, Scheich, & Mylius, 2013). Thus, feedback from cortical structures might be able to influence auditory processing at the stage of the DNLL. The DNLL in turn projects only to two nuclei. One nucleus is the contralateral DNLL; the other nuclei are the both IC hemispheres. Retrograde labeling from the IC stains the DNLL (Gonzalez-Hernandez, Mantolan-Sarmiento, Gonzalez-Gonzalez, & Perez-Gonzalez, 1996; Kelly et al., 2009; Shneiderman et al., 1999; Tanaka et al., 1985; Willard & Martin, 1983; Zook & Casseday, 1982). Retrograde tracing of the DNLL labels its contralateral counterpart (Glendenning et al., 1981; Huffman & Covey, 1995; Oliver & Shneiderman, 1989), and anterograde labeling of the DNLL output yields staining in the contralateral DNLL and the IC (Bajo et al., 1993).

Taken together, the DNLL receives tonotopically organized excitatory inputs from the medial superior olive, the lateral superior olive and, to a smaller extent, from the cochlear nucleus. Glycinergic inhibitory inputs are provided by the VNLL, the medial nucleus of the trapezoid body, and the lateral superior olive, while GABAergic inputs originate predominantly from the contralateral DNLL and from the superior para-olivary nuclei. The tonotopically organized output of the DNLL is GABAergic and projects to the contralateral DNLL and both IC hemispheres. Thus, the DNLL integrates information from a large number of lower auditory brainstem areas. This connectivity suggests that the DNLL functions as an inhibitory gate for the IC by using highly processed auditory information from various sources.

Cellular Features of Neurons in the Auditory Nuclei of the Lateral Lemniscus

In the following section the synaptic and biophysical properties of neurons in the LL are discussed. The data for this section is largely based on single cell recordings in vitro obtained from rodents.

Ventral Nucleus of the Lateral Lemniscus

Similar to their morphological heterogeneity, VNLL neurons show a wide range of firing behaviors when recorded in vitro (Zhao & Wu, 2001). Neurons located in the dorsal part exhibit sustained firing with very rapid onset and strong hyperpolarizing current (Ih) (Caspari et al., 2015). In the ventral region, firing patterns are characterized by a single rapid onset action potential (Caspari et al., 2015; Franzen et al., 2015). For globular cells in the ventral part of the VNLL, the onset firing pattern emerges during development (Franzen et al., 2015). Interestingly, during late postnatal refinement, the input resistance and membrane time constant decrease (Franzen et al., 2015), resulting in a decreased cell capacitance (Baumann & Koch, 2017; Franzen et al., 2015). Thus, smaller and leakier neurons with large somatic excitation are generated during late postnatal development. This process generates neurons suited for rapid voltage signaling with very short latencies (Franzen et al., 2015). Furthermore, globular VNLL neurons display membrane resonance properties. These intrinsic membrane dynamics are thought to facilitate action potential generation at a certain input frequency. For globular VNLL neurons, the resonance frequencies are low compared to neurons of the medial and lateral superior olive, despite exhibiting similar onset firing patterns in vitro (Fischer, Leibold, & Felmy, 2018). This difference is due to a larger input resistance compared to the extremely leaky neurons in the SOC (Fischer et al., 2018). The resonance frequency in the VNLL ranges between 10 and 100 Hz and therefore promotes matching input rates. Thus, based on their intrinsic biophysical properties, VNLL neurons are ideally suited to respond rapidly and with high precision to sounds whose amplitude is modulated at 10 to 100 Hz.

VNLL neurons receive inhibitory and excitatory inputs (Baumann & Koch, 2017; Irfan, Zhang, & Wu, 2005; Zhao & Wu, 2001). Individual neurons receive inhibitory input via GABAA receptors only or via both GABAA and glycine-receptors, while excitation is mediated by non-NMDA and NMDA-receptors (Irfan et al., 2005). Where the GABAergic input originates is not fully understood. It may originate from a possible GABA-positive subpopulation of neurons of the lateral nucleus of the trapezoid body, which in bats is connected to the VNLL (Huffman & Covey, 1995). Excitatory inputs appear to be distributed through the VNLL in a size-dependent manner—the excitatory post-synaptic current (EPSC) of a single fiber being the fastest and largest in the ventral aspect of the VNLL (Caspari et al., 2015). This distinct distribution of input size appears not be present for the inhibitory inputs (Caspari et al., 2015). The strong excitation delivered by a single somatic fiber in juvenile gerbil ventral VNLL neurons is unable to drive supra-threshold output reliably (Berger et al., 2014), thus indicating that integration is required. During late postnatal development, these large inputs increase even more in size (Baumann & Koch, 2017); F. Felmy, unpublished results). This increase in synaptic current and an increase in excitability are probably sufficient to generate a faithful one-to-one transmission in fully matured VNLL neurons. This is consistent with in vivo on-cell recordings that show a pre-potential followed by the large postsynaptic spike (Adams, 1997). Contrary, however to the situation in the medial nucleus of the trapezoid body, it seems that more than one large somatic synapse targets a single globular VNLL neuron (Berger et al., 2014), possibly generating additional safety-factors for synaptic transmission during periods of high activity.

The development of large synaptic inputs to globular, ventral VNLL neurons is modulated by acetylcholine. Treating mice with nicotine during development leads to smaller excitatory inputs (Baumann & Koch, 2017). This treatment appears selective for the synaptic inputs as membrane properties were unchanged. The effect was driven by nicotinic ACH-Rs, some of which are calcium permeable and thereby able to modulate gene expression. Besides this influence of nACH-Rs on development, mACH-Rs can be activated on globular VNLL neurons (Franzen et al., 2015). These receptors reduce the action potential current threshold, which leads to changes in firing behavior in juvenile neurons. Thus, acetylcholine influences VNLL neurons on various levels at least during late postnatal development.

Intermedial Nucleus of the Lateral Lemniscus

The cellular features of the INLL have not been quantified. Since it is difficult to distinguish between the dorsal part of the VNLL and the INLL in rodents and both nuclei contain elongated cells, it is likely that INLL cell properties match those reported for dorsal VNLL neurons.

Dorsal Nucleus of the Lateral Lemniscus

The biophysical properties of DNLL neurons have been studied in various species and age groups. The membrane properties of DNLL neurons change during late postnatal development (Ahuja & Wu, 2000; Ammer et al., 2012). As in many other brainstem nuclei, input resistance and time constant become smaller during development, while the resting potential remains stable. Overall, the variability of membrane properties at rest is high for DNLL neurons. In mature neurons, for example, the membrane resistance can vary by a factor of 10, ranging from 20 to 200 MOhm. Despite their strong heterogeneity, it is difficult to assign firing properties to specific neuronal morphologies (Wu & Kelly, 1995). Neurons in the DNLL generate large action potentials when challenged with current injections or synaptic stimulations. During long-lasting current injections, these neurons fire sustained action potentials with little adaptation (Ahuja & Wu, 2000; Ammer et al., 2012; Porres, Meyer, Grothe, & Felmy, 2011; Wu & Kelly, 1995). In general, DNLL neurons appear highly excitable and the high-input resistance allows incoming EPSCs to have a strong impact on voltage signaling. During late postnatal development, the somatic action potential size increases and the half-width decreases (Ahuja & Wu, 2000; Ammer et al., 2012). Mature DNLL neurons exhibit a small Ih that activates at low membrane potentials (Fu, Brezden, & Wu, 1997). In gerbils this Ih current hardly becomes activated upon strong inhibition (Ammer, Siveke, & Felmy, 2015). Whether activation kinetics of this channel change during heavy synaptic inputs in an NO dependent manner, like in the MNTB (Steinert et al., 2008), and thereby increase its impact on voltage signaling, remains unknown. The presence of high-voltage-gated and A-type potassium currents has been described (Fu, Wu, Brezden, & Kelly, 1996). It should be noted that DNLL neurons express hardly any low–voltage-gated potassium currents (Fu et al., 1996), consistent with the expression analysis in bats (Rosenberger et al., 2003). In addition, somatic action potentials were shown to activate calcium influx through voltage-gated calcium channels (Porres et al., 2011).

Neurons in the DNLL receive all three major synaptic inputs: GABA, glycine, and glutamate. Inhibitory inputs are hyperpolarizing, since the chloride reversal is negative in respect to the resting potential (Ammer et al., 2015). GABAergic inputs are driven by ionotropic GABAA receptors (Pecka et al., 2007). These inputs show a frequency-dependent buildup (Ammer et al., 2015). In addition, spillover and asynchronous release prolong the decay of the synaptic GABAergic conductance in a frequency-dependent manner (Ammer et al., 2015). Since little Ih or low-voltage-activated potassium current (KLT) are activated between maximal hyperpolarization and action potential threshold, the GABAergic inhibition is integrated passively. Passive integration enhances the time course of the GABAergic IPSP (Ammer et al., 2015). Thus, strong activity in the GABAergic inputs prolongs the time courses of IPSPs and generates long-lasting inhibitory action. The pattern and synaptic parameters of the glycinergic inhibition remain unclear. Some of our initial recordings indicate that glycinergic inputs show asynchronous release during and after high-frequency stimulation similar to GABAergic inputs.

Postsynaptic glutamatergic currents are mediated by α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) and N-methyl-D-aspartate acid (NMDA) receptors (Ammer et al., 2012; Fu, Brezden, Kelly, & Wu, 1997; Kelly & Kidd, 2000; Porres et al., 2011; Siveke et al., 2018; Wu & Kelly, 1996). Consistent with the strong heterogeneity of morphological, passive, and active membrane parameters, glutamatergic inputs to the DNLL show a large variability. This variability applies to the time constants, the size, the short-term plasticity, and the NMDA/AMPA ratio of glutamatergic inputs (Ammer et al., 2012; Porres et al., 2011). Importantly, action potential generation is supported by NMDA receptors even under normal extracellular Mg2+ concentrations (Ammer et al., 2012; Fu, Brezden, Kelly et al., 1997; Kelly & Kidd, 2000; Porres et al., 2011; Siveke et al., 2018). Thus, NMDA currents enhance the output firing rate and thereby the information content of DNLL neurons (Ammer et al., 2012; Porres et al., 2011; Siveke et al., 2018). This NMDA action is also interesting because, first, the NMDA dependent increase in sensory information content in the DNLL might be a blueprint for other auditory brainstem nuclei. NMDA receptor activation and electrogenic signaling has also been documented in the IC (Sanchez, Gans, & Wenstrup, 2007; Sivaramakrishnan & Oliver, 2006; Wu, Ma, & Kelly, 2004), the AVCN (Pliss, Yang, & Xu-Friedman, 2009), and in the VNLL. This NMDA receptor-mediated increased information content matches the increase in sensory information that has been described along the ascending auditory brainstem pathways before (Kuwada, Fitzpatrick, Batra, & Ostapoff, 2006; Pecka, Siveke, Grothe, & Lesica, 2010). Second, the addition of NMDA conductances will help overcome the strong GABAergic long-lasting inhibition generated by contralateral DNLL neurons. At the same time, NMDA receptor amplified excitation will lead to an even greater inhibition on the contralateral counterpart. Thus, the push-pull mechanism between the DNLL hemispheres is strongly dependent on NMDA currents.

DNLL neurons exhibit basic similarities, yet with a large parameter range. The function of this variability is obscure and might simply reflect the nuclear organization or adaptations to the various input nuclei. Alternatively, the variability might indicate that DNLL neurons can use a large set of cellular features to adjust their function to the specific sound-processing tasks.

Functional Aspects of the Auditory Nuclei in the Lateral Lemniscus

After reviewing the cellular features of neurons of the LL we turn to discuss functional apsects of each nucleus. These considerations are largely based on in vivo recordings. In this section finally we aim to identify some functional tasks that these neurons perform during the processing of auditory information to support the generation of the wonderfull auditory space which we perceive in our everyday life.

Ventral Nucleus of the Lateral Lemniscus

VNLL neurons are predominantly driven by monaural sounds; however, binaurality has also been documented in cats, rats, and rabbits (Batra & Fitzpatrick, 1999; Guinan, Norris, & Guinan, 1972; Recio-Spinoso & Joris, 2014; Zhang & Kelly, 2006b), but little binaurality exists in bats (Covey & Casseday, 1991). Sound-evoked responses can be segregated in different classes amongst VNLL neurons. Covey and Casseday (1991) found that neurons in the columnar region of the VNLL in bats fire predominantly with a very rapid onset response. Neurons in the rest of the VNLL could be classified into the main groups of onset, onset-sustained, sustained, and chopping-response types (Covey & Casseday, 1991; Huffman, Argeles, & Covey, 1998; Metzner & Radtke-Schuller, 1987). These types of neurons were also described in other mammals. In cats, rats, mice, and rabbits, onset and onset-sustained cells with various forms of adaptations predominate in the VNLL (Adams, 1997; Batra & Fitzpatrick, 1999; Liu, Huang, & Wang, 2014; Recio-Spinoso & Joris, 2014; Zhang & Kelly, 2006b). One hallmark of the columnar neurons in the bat VNLL is that they have a very short latency and this latency is invariant to the increase in sound intensity (Covey & Casseday, 1991; Haplea, Covey, & Casseday, 1994). Such constant latency neurons are also found in cats (Recio-Spinoso & Joris, 2014), mice (Liu et al., 2014), and rats (Zhang & Kelly, 2006b). Thus, within the VNLL, a subset of neurons shows a very high temporal precision to sound transients that is barely affected by intensity. As these neurons are located in the columnar region in bats, they are known to be innervated with a large somatic synapse arising from the octopus cell area. Thus, the constant latency might arise from strong synaptic inputs integrated by small round neurons. Frequency tuning of VNLL neurons to sound is heterogeneous and, in bats, it seemed to segregate again into neurons that show a rapid temporal precise onset and neurons that fire more sustained to brief tone stimulations. In the bat’s columnar neurons, broad frequency tuning is dominant (Covey & Casseday, 1991; Haplea et al., 1994). However, in mice and cats, the width of the frequency tuning seemed not to correlate with the firing pattern of sustained or onset response type (Liu et al., 2014; Recio-Spinoso & Joris, 2014). Here, tuning curves correlate with the characteristic frequency of the neuron (Liu et al., 2014; Recio-Spinoso & Joris, 2014), with wider tunings in lower frequencies. These tuning characteristics are consistent with in vivo data from the octopus cell area recorded in cats (Rhode & Smith, 1986). Thus, overall frequency tuning in the VNLL might be inherited from its input structure. Taken together, rapid onset neurons generate fast, temporally precise inhibition in the ascending pathways targeting the dorsal VNLL and, importantly, the IC. Such fast-onset inhibitions have been indeed observed in VNLL and IC neurons (Nayagam et al., 2005; Spencer et al., 2015; Xie, Gittelman, Li, & Pollak, 2008; Xie, Gittelman, & Pollak, 2007). This inhibition covers a broad frequency range, extending the frequency range that triggers excitation in the same neuron. Thus, based on the frequency range and temporal precision, the onset inhibition is considered to originate in the ventral VNLL. This inhibitory signaling can be interpreted as a “shut up and listen” input. Such an onset inhibition might enhance the contrast of excitatory inputs and may generate ideal spike triggers due to the relief of sodium channel inactivation. Functionally, fast-onset inhibition was shown to reduce spectral splatter (Spencer et al., 2015). Spectral splatter emerges during sharp onset activation and consists of the resultant noise generated in the frequency domain. This function arises from its ability to suppress onset information over a broad frequency range. A spectral filter is thereby generated that suppresses spurious sound frequencies when integrated in the IC.

Furthermore, the modulation transfer-functions of VNLL neurons show that these neurons do not follow very high-input frequencies (Zhang & Kelly, 2006a). This finding is consistent with their intrinsic resonance (Fischer et al., 2018), which is tuned to low frequencies. Therefore, one might argue that VNLL neurons are designed to transmit especially loud low-frequency-modulated sounds. As low-frequency modulation of sound is one feature of salient sounds, including natural alarm sounds (Arnal, Flinker, Kleinschmidt, Giraud, & Poeppel, 2015), the octopus-VNLL circuit might be designed to process such auditory features initially. The rapid feedforward inhibition from VNLL to IC might furthermore enhance contrast and modulate gain for the processing of such salient-sounds features. Interestingly, contrast enhancement is supposed to be one possible mechanism mediating saliency (Huang & Elhilali, 2017; Itti & Koch, 2001). Thus, this circuit holds the requirements for early processing of the salient-sounds feature.

Intermedial Nucleus of the Lateral Lemniscus

In vivo recordings selectively performed in the INLL are sparse, with most data being collected in bats and rats. As in the VNLL, the response characteristics in the INLL are fairly heterogeneous. INLL neurons responded to sounds with sustained, onset, or onset-sustained patterns in some cases with chopping behavior (Huffman et al., 1998; Kelly, Buckthought, et al., 1998; Xie, Meitzen, & Pollak, 2005). All frequencies an animal can hear are represented in the INLL (Covey & Casseday, 1991; Kelly, Buckthought, et al., 1998). Another response feature that received attention in INLL neurons is spike latency. This feature is particular interesting, as it might segregate VNLL from INLL neurons. INLL first-spike latencies were longer compared to columnar neurons but not to other VNLL neurons (Covey & Casseday, 1991). Overall, VNLL and INLL latencies were shown to present a continuum, with the shortest being in the columnar VNLL and the longest in INLL neurons (Covey & Casseday, 1991). Compared to DNLL neurons, INLL neurons showed shorter latencies in rats (Kelly, Buckthought, et al., 1998).

The sharpness of frequency tuning in the INLL is very variable, covering a large range of QdB values (Covey & Casseday, 1991; Xie et al., 2005). There is evidence that for some cells, tuning is acuminated by side band inhibition (Xie et al., 2005). This side band inhibition is mediated by either GABAergic or both GABAergic and glycinergic inputs. The mixed input is intriguing, as VNLL neurons were shown to release both GABA and glycine simultaneously (Moore & Trussell, 2017). Thus, ascending VNLL axons might be sending of collaterals into the INLL on their way to the IC, thereby sharpening the tuning of INLL neurons.

The physiological features of INLL neurons described so far are based on monaural activation. However, some INLL neurons were shown to receive binaural inputs. Despite the fact that most INLL neurons respond similarly to monaural and binaural sounds, a fraction showed increased responsiveness to stimulation of both ears, while others showed lower responsiveness when stimulated binaurally (Covey & Casseday, 1991; Kelly, Buckthought, et al., 1998; Xie et al., 2005). Thus, for both the VNLL and the INLL a fraction of neurons integrate binaural information.

A physiological hallmark that was recently assigned to INLL neurons, and possibly to some VNLL neurons, is their ability to integrate information across different sound frequencies. Thus, these neurons pool information between different frequency channels. In some neurons, low-frequency sounds can suppress the response rate to higher-frequency tones even at best frequency (Peterson, Nataraj, & Wenstrup, 2009). In other neurons facilitation of neuronal response rates was observed upon cross-frequency integration (Mittmann & Wenstrup, 1995). This integration was sensitive to glycine but not GABA antagonists. The glycinergic inputs mediating this response were traced to originate mainly in the medial and lateral nucleus of the trapezoid body and to a minor extend in the VNLL (Yavuzoglu et al., 2010; Yavuzoglu, Schofield, & Wenstrup, 2011). Thus, ascending inhibition sharpens well-defined cross-frequency integration in the INLL.

Dorsal Nucleus of the Lateral Lemniscus

In the DNLL the frequency tuning is narrower compared to the VNLL (Bajo, Villa, de Ribaupierre, & Rouiller, 1998; Covey, 1993; Kelly, Buckthought, et al., 1998; Markovitz & Pollak, 1994) and is directly inherited from the ascending pathways, as no side band glycinergic or GABAergic inhibition was observed (Xie et al., 2005). Sound-evoked response patterns recorded at best frequency can be categorized into onset, sustained, on-off, and off responses (Bajo et al., 1998; Covey, 1993; Kelly, Buckthought, et al., 1998; Kuwada et al., 2006; Markovitz & Pollak, 1994; Metzner & Radtke-Schuller, 1987). On-neurons encode time more faithfully as they follow higher modulation frequencies in sinusoidal amplitude modulated paradigms, compared to sustained firing cells (Yang & Pollak, 1997). Overall, specific sound-evoked response patterns vary significantly. It has not fully been elucidated whether these variations are related to tonotopy, location, or input structures within the DNLL. Nevertheless, this functional heterogeneity matches well with the heterogeneity of the membrane and synaptic parameters described in the DNLL part of the section about the cellular features. Functionally, these diverse responses do not underlie a detection of distinct con-specific calls, as in bats DNLL neurons were not selective for a specific call, but responded to any call well (Bauer, Klug, & Pollak, 2002). In addition, sound-evoked response latencies vary considerably in the DNLL (Covey, 1993; Markovitz & Pollak, 1994) and clearly depend on sound intensity (Markovitz & Pollak, 1994). Spontaneous activity recorded in the DNLL was subdivided into modes of bursting or regular spiking (Bajo et al., 1998), again implicating different cellular categories. The presence of spontaneous activity matches the notion that DNLL neurons appear highly excitable in in vitro recordings. Moreover, in vivo recordings additionally demonstrated that DNLL neurons are sensitive to excitatory non-NMDA- and NMDA-receptor antagonists (Kelly & Kidd, 2000; Siveke et al., 2018). Inhibitory inputs to DNLL neurons can be blocked by antagonists of GABA and glycine receptors (Yang & Pollak, 1994a, 1994b).

It follows from the inputs of the binaural coincidence detectors located in the SOC that DNLL neurons are sensitive to interaural time differences (ITDs) and interaural level differences (ILDs) (Covey, 1993; Kelly, Buckthought, et al., 1998; Kuwada et al., 2006; Siveke et al., 2006). That ITD and ILD coding is inherited from the SOC is also indicated by the observed peak and trough type ITDs (Kuwada et al., 2006; Siveke et al., 2006). The binaural accuracy or the information content of ITDs is higher in the DNLL compared to the SOC (Kuwada et al., 2006; Pecka et al., 2010). Such an enhancement could be mediated on the circuit level by integrating over a large range of inputs. Alternatively, the increase could be mediated by postsynaptic amplification mechanisms. Porres et al. (2011) have shown that NMDA receptors are ideally suited to amplify the output rates of DNLL neurons. That the sensory information content is indeed enhanced in an NMDA-dependent manner was recently demonstrated in vivo (Siveke et al., 2018). This NMDA-dependent mechanism might be a blueprint for increasing the information contents in the ascending auditory pathways as glutamatergic synapses drive NMDA-receptors at least in DNLL and IC neurons (Sanchez et al., 2007; Sivaramakrishnan & Oliver, 2006; Wu et al., 2004). Furthermore, as will be described, the NMDA-receptor dependent amplification of DNLL outputs might be crucial to adjust long-lasting GABAergic inhibition in both the DNLL and the IC (Bauer, Klug, & Pollak, 2000; Porres et al., 2011; Yang & Pollak, 1994b).

Besides the processing of binaural information that is inherited from the SOC, DNLL neurons have the potential to interact via the commissure of Probst with their contralateral counterparts to generate additional binaural interactions. In agreement with the GABAergic nature of DNLL neurons, this hemispherical interaction is dominated by GABA. GABAergic, but not glycinergic, blockers reduce the long-lasting inhibition generated in the DNLL from its contralateral counterpart (Yang & Pollak, 1994b). The GABAergic action is mediated by ionotropic GABA receptors. This contralaterally initiated inhibition can outlast sound presentations by tens of milliseconds (Burger & Pollak, 2001; Pecka et al., 2007; Siveke et al., 2018; Yang & Pollak, 1994b, 1998). The time course of this GABAergic inhibition depends first on the firing rate of the presynaptic DNLL neuron (Ammer et al., 2015). Higher output rates lead to a frequency-dependent buildup of GABAergic transmitter in the synaptic cleft and to asynchronous release from presynaptic terminals, thereby prolonging activation of postsynaptic GABA receptors. Second, passive postsynaptic integration of hyperpolarizing inhibition prolongs the GABAergic action (Ammer et al., 2015). These mechanisms together are suitable and sufficient to explain the long-lasting suppression of activity in the DNLL (Ammer et al., 2015). Whether similar biophysical properties on the pre- and postsynaptic site are the basis of the long-lasting inhibition observed in the IC (Bauer et al., 2000) has not been elucidated.

The importance of the DNLL in binaural processing has been demonstrated by a series of behavioral and elegant in vivo pharmacological experiments. By cutting the commissure of Probst, M. Ito, van Adel, and Kelly (1996) demonstrated that the minimal audible angle increased dramatically. Along the same lines, Kelly, Li, and van Adel (1996) used unilateral and bilateral kainic acid induced lesions of the DNLL to show that its loss led to an increase in minimal audible angle. To demonstrate binaural processing in vivo, the approach was to change the activity in one DNLL and recorded in the contralateral counterpart or the IC. Li and Kelly (1992) demonstrated that by silencing the DNLL, the ILD functions of contralateral IC neurons lost tuning, a finding corroborated by Burger and Pollak (2001). Additionally, these authors could link the long-lasting GABAergic effect toward the change in ILD function in the IC. Silencing DNLL neurons either by GABA agonists or non-NMDA-receptor and NMDA-receptor antagonists shows the suppressive effect of DNLL neurons in the IC (Faingold, Anderson, & Randall, 1993; Kelly & Kidd, 2000). These authors thereby demonstrate that the GABAergic reciprocal inhibition between the DNLL hemispheres is crucial for binaural responsiveness in the IC. Conversely, electrically evoked activity of the DNLL was able to suppress IC activity to contralateral sound stimulation in a manner that matched binaural activation (Faingold et al., 1993). Together these data demonstrate that based on synaptic integration of AMPA, NMDA, and GABA receptors, binaural activity in the DNLL shapes ITD and ILD coding, and hence the space representation, in the IC.

The function of long-lasting GABAergic inhibition in the DNLL was proposed to generate suppression of location information of sound source during reverberations (Pecka et al., 2007). Mechanistically, rapid alterations in the location of sound sources could generate relief of GABAergic suppression (disinhibition) in one IC hemisphere. In this model (Pecka et al., 2007), a preceding sound blocks the activity of the sound source ipsilateral DNLL via the commissure of Probst. Therefore, the suppression of this DNLL leads to a disinhibition of the IC that is contralateral to the sound. Since the inhibition of the DNLL is supposed to be longer-lasting than the sound itself, the suppression of the ipsilateral DNLL by the preceding sound will persist into the activity generated by a rapidly occurring second sound. When the second sound comes from the opposite direction while the disinhibition in the IC is still present, the second sound will be represented in both IC hemispheres. Thus, for the time of the long-lasting inhibition an ambiguous representation of the second sound is generated that might suppress the accurate detection of its localization. Such an ambiguous sound representation might suppress the localization without quenching the sensory evoked activation. Since the IC is activated on both hemispheres during the second sound we can speculate that this second sound can be detected but not accurately localized. That a second sound can be detected but not localized is observed in human listeners during an echo, or lead lag detection paradigm (Litovsky, Colburn, Yost, & Guzman, 1999; Pecka et al., 2007). A key element for this GABAergic dis-inhibition is thereby the reciprocal inhibition between the DNLL/IC hemispheres. Such reciprocal inhibitory connections were indicated to be ideally suited to underlie context-dependent sensory processing (Mysore & Knudsen, 2012). A more overarching scenario for DNLL function could be a possible role as a selective filter. As we have seen, the long-lasting inhibition creates a time window that quenches unambiguous localizations. Evidence was presented that during rapid sound fluctuations, the DNLL circuit might suppress the presence of acoustically generated spurious sound information (Meffin & Grothe, 2009). The properties of the DNLL circuit were shown to match the temporal structure of a filter that suppresses a frequency of spuriously generated ITDs larger than 100 Hz. Thus, ITDs and ILDs that are stable and do not fluctuate between the different locations in space rapidly will be allowed to be processed further. This selective filtering is consistent with the idea of a long-lasting suppression that might be involved in the suppression of space information during reverberations, and with the finding that DNLL neurons process con-specific sounds irrespective of the call type (Bauer et al., 2002). Thus, the DNLL might represent a filter specifically tuned for slower temporal aspects that acts in a context dependent manner. Data from our group indeed supports this idea of a context-dependent filter, as the time course of the long-lasting suppression evoked in the contralateral DNLL depends on the overall sound intensity. Thus, the temporal properties of this filter are dynamically adjusted to sound intensities.

The Nuclei of the Lateral LemniscusClick to view larger

Figure 2. Three main nuclei can be delineated in the fiber bundle of the lateral lemniscus (LL) that connects lower auditory brainstem nuclei with the inferior colliculus (IC). The glycinergic/GABAergic ventral nucleus of the lateral lemniscus (VNLL) is considered temporally precise and generates a rapid feed-forward inhibition. One functional feature might be the suppression of spectral splatter, spurious frequencies that are generated by the onset of a rapid sound transient. A subregion (dotted circle) is temporally most precise and receives a large glutamatergic somatic input. The glutamatergic neurons of the intermediate nuclei of the lateral lemniscus (INLL) are likely to be involved in cross-frequency integration. The GABAergic dorsal nucleus of the lateral lemniscus (DNLL) is reciprocally connected via the commissure of Probst (CP). It acts as a binaural filter suppressing spurious interaural information and is implicated in the suppression of sound source localization during reverberations.

We can put together a scenario in which the VNLL and DNLL act as specific filters (Figure 2). The function of the VNLL and the DNLL might be to filter out spurious frequencies and space information, respectively. We put forward that these nuclei cut out perturbing material and enhance the remaining information. In doing so, the LL enhances sound representation in the IC by increasing signal to noise. Based on their filter properties, sound processing in the IC becomes focused. In light of these properties, the LL might be regarded as a gate keeper for the IC.

Acknowledgments

I grateful to Dr. Elisabeth M.M. Meyer who for her comments and help with the manuscript. I thank Sönke von den Berg for help with the figure. Our current work on the LL is supported by DFG789/6-1 and DFG789/7-1

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