Neuron Types, Intrinsic Circuits, and Plasticity in the Inferior Colliculus
Abstract and Keywords
The inferior colliculus is a critical auditory center in the midbrain which virtually acts as a hub of all ascending and descending auditory information flows. Wide variety of neuronal responses to sound is found in the IC, and this variety emerges not only from the wide range of extrinsic afferent inputs, but also from the complex features of the local circuits in the IC, for example, the mosaic pattern of extrinsic fiber termination, the various neuronal types each of which compose different patterns of local connection, and the unique forms of synaptic plasticity de novo. This chapter reviews the recent progress in understanding these features, and identifies the key issues for future research.
Neurons, intrinsic circuits and plasticity in the inferior colliculus (IC) are best discussed within the framework of the overall structure of the auditory midbrain. The IC contains a central nucleus (ICC) that is surrounded by a cortex. The ICC is the primary terminus and integration center for the lateral lemniscus and the dorsal acoustic stria, the ascending inputs from the lower auditory brainstem (see chapter by Cant in this volume), and it is easily identified by prominent cytochrome oxidase staining. The ICC contains subregions where some inputs are more prevalent than others. ICC is the primary source of ascending projections to the portions of the medial geniculate body that supply the core auditory cortex.
In contrast, the cortex of the IC differs in its structure, which consists of layers that parallel the surface of the IC laterally, dorsally, caudally, and in some species rostrally. In general, the cortex has prominent staining with nicotinamide adenine dinucleotide phosphate (NADPH) diaphorase. The lateral cortex of IC is the main structure through which the tectothalamic and corticotectal pathways exit and enter the IC. However, its neuronal structure indicates that it is more than just a gateway, and the inputs and outputs of these lateral cortex neurons are distinct from those in the ICC. The dorsal cortex of the IC contains layers that parallel the dorsal surface of the IC. These layers are typically thicker than the lateral cortex layers, and their size is correlated with the size of the auditory cortex that provides its major input. The neuronal types, local, afferent, and efferent connections also differ from that of ICC. The caudal cortex is thin and superficial, while the rostral cortex is complex and merges with the intercollicular tegmentum.
IC neurons are subdivided into several categories according to criteria such as dendritic morphology, molecular profiles, synaptic organization, intrinsic membrane properties, or response types to sound. Unfortunately, with some exceptions, no definite agreement of correspondence of categories defined by different criteria.
Neurons in the IC exhibit various morphology. Even with simple Nissl staining, neuronal types can be distinguished by the size and shape of the neuron bodies. Dendritic morphology was described by Golgi-impregnation (Malmierca, Blackstad, Osen, Karagulle, & Molowny, 1993; Oliver & Morest, 1984), intra- or juxtacellular staining (Oliver, Kuwada, Yin, Haberly, & Henkel, 1991; Wallace, Shackleton, & Palmer, 2012), or virally introduced labeling (Ito & Oliver, 2014) methods. Neurons also show variety in cytoplasmic features that can be studied with electron microscopy and correlate with dendritic morphology (Paloff, Usunoff, & Hinova-Palova, 1992).
In the ICC, Golgi impregnated materials revealed that several distinctive neuron types can be identified based on the arborization of the dendritic tree. Neuron types in the ICC are well-studied. In the cat, disc-shaped neurons and stellate neurons were identified based on the orientation of the dendritic trees (Oliver & Morest, 1984). Disc-shaped neurons have flat dendritic trees roughly 70 µm wide that are parallel to each other and the major lemniscal afferent fibers and form the characteristic fibrodendritic laminae of the ICC. Stellate neurons have dendritic trees that are either un-oriented or oriented orthogonal to the fibrodendritic laminae. In Nissl stained sections, disc-shaped neurons are seen as flattened neuron bodies that align with the fibrodendritic laminae. In rats, two neuron types, flat and less-flat, were identified by 3D reconstruction and quantitative analyses (Malmierca et al., 1993). Flat neurons are likely to correspond with disc-shaped neurons, and the thickness of dendritic arbor is 50–70 µm. Unlike stellate neurons, dendritic trees of less-flat neurons in the rat are “oriented” to the axis of fibrodendritic laminae, although the dendritic trees are thicker than those of flat neurons and the thickness is about 100 µm. When recordings of the characteristic frequency (CF) of ICC neurons are made in an orientation orthogonal to the fibrodendritic laminae, every 150–180 microns there is a step in the CF of about 0.24 to 0.33 octave (Malmierca et al., 2008; Schreiner & Langner, 1997). This is roughly the same size as the diameter of an axonal lamina and suggests that two or three flat, disc-shaped neurons, side by side, form the functional unit of the fibrodendritic lamina in ICC (Malmierca et al., 2008).
In the lateral cortex of IC, there are three layers (Faye-Lund & Osen, 1985; Loftus, Malmierca, Bishop, & Oliver, 2008). Layer 1 contains small, flattened neurons that extend dendrites parallel to the surface of the IC (T. Ito, unpublished observation). Layer 2 is densely packed with small and medium-sized neurons. Many of layer 2 neurons are GABAergic (Ono, Yanagawa, & Koyano, 2005) and likely to extend the dendritic trees within the layer. Layer 2 GABAergic neurons make distinct dense clusters (Chernock, Larue, & Winer, 2004; Lesicko, Hristova, Maigler, & Llano, 2016) that are called GABA modules. Some of layer 2 neurons are densely covered with dendritic spines (Malmierca, Blackstad, & Osen, 2011). Layer 1 and 2 of the lateral cortex continue medially to the same layers in the dorsal cortex, and rostrally to brachium and brachial nucleus of the IC, respectively. Layer 3 of the lateral cortex receives banded lemniscal axons which are orthogonal to the fibrodendritic laminae in the ICC (Saldana & Merchan, 1992). In layer 3, several neuron types are identified and their dendritic arbor is related to the layering of the ascending axons as well as layered structure of the cortex (Malmierca et al., 2011). Pyramidal-like neurons (Figure 1D) are spiny neurons and resemble pyramidal neurons in neocortex, as they have thick tufted apical dendrites that extend to layer 1, as well as basal dendrites. The basal dendrites may receive inputs from layered lemniscal axons in layer 3, while the tips of basal dendrites intermingle with the lateral-most fibrodendritic laminae of the ICC. Bitufted neurons have a spindle-shaped, middle to large soma with two or three dendritic trees that extend in opposite directions, parallel to apical dendrites of pyramidal-like neurons. Chandelier neurons have 3 or more dendrites that are sharply branched and oriented toward the surface of the IC. The different layers of lateral cortex receive inputs from different sources, that is, visual inputs to layer 1 (Paloff, Usunoff, Hinova-Palova, & Ivanov, 1985), somatosensory inputs to layer 2 (Lesicko et al., 2016), and auditory inputs to layer 3 (Loftus et al., 2008), and differential neuromodulatory inputs to layers (Henderson & Sherriff, 1991; Klepper & Herbert, 1991). Since all three neuron types have dendrites directed to the surface to the lateral cortex, it suggests these neurons participate in multimodal integration. As these neurons have dendritic spines, they may control synaptic strength independently, and this may contribute to plasticity in this region.
The dorsal cortex contains three to four layers depending on the species (Faye-Lund & Osen, 1985; Morest & Oliver, 1984). Layer 1 is mostly free of neurons except for small cells whose dendrites parallel the surface of IC. Layers 2 and 3 have successively larger neurons in the rat. Dorsal cortex is more extensive in the cat and other species that exhibit a more elaborately developed cerebral cortex. The largest cells are in layer 4 (Morest & Oliver, 1984). In the deep layers of dorsal cortex, ascending axons are found that are the continuum of fibers that compose the fibrodendritic lamina of the ICC (Saldana & Merchan, 1992). Some neurons have dendritic trees that parallel the fibrodendritic laminae like flat neurons in the ICC (Malmierca et al., 2011; Oliver et al., 1991). In the same region, many large multipolar neurons are present whose dendrites extend orthogonal to the orientation of the lamina in ICC (Morest & Oliver, 1984; Oliver & Morest, 1984).
In the rostral cortex, there is no sign of lamination, and most neurons are classified as multipolar that do not have dendritic trees with a specific orientation (Malmierca et al., 2011; Morest & Oliver, 1984). Small multipolar neurons tend to have medium number of spines, while larger neurons tend to have fewer spines. Although inputs to the rostral cortex have not been well described, it is likely the region receives converged inputs from cerebral cortex, brainstem somatosensory nuclei, and ICC (Lesicko, Hristova, Maigler, & Llano, 2016).
Neurotransmitter Type or Other Molecular Markers
Inferior colliculus expresses wide variety of neurotransmitters or other molecular markers, which can be examined on a database (http://mouse.brain-map.org/). It appears that almost all IC neurons contain either glutamate or GABA as a neurotransmitter (Fujimoto, Konno, Watanabe, & Jinno, 2017), that is, excitatory or inhibitory, respectively. IC neurons are unlikely to use glycine as a neurotransmitter because GLYT2, a key molecule for a glycinergic phenotype (Aubrey et al., 2007), is not expressed by neurons in the IC (Tanaka & Ezure, 2004). GLYT2 is found in lemniscal axons from the auditory brainstem that terminate in ICC (Choy Buentello, Bishop, & Oliver, 2015). GABAergic neurons express glutamic acid decarboxylase 65 and 67 (GAD65 and GAD67). IC glutamatergic neurons express vesicular glutamate transporter 2 (VGLUT2) but not VGLUT1 or VGLUT3 (Ito, Bishop, & Oliver, 2009).
Approximately 20–30% of IC neurons are GABAergic (Merchan, Aguilar, Lopez-Poveda, & Malmierca, 2005; Oliver, Winer, Beckius, & Saint Marie, 1994). In the central nucleus, the density of GABAergic neurons is higher than in the dorsal, caudal, and rostral cortical areas. GABAergic neurons within the GABA modules in lateral cortex also are densely clustered. GABAergic neurons are subdivided into at least 2 populations, large and small GABAergic (LG and SG) neurons (Ito et al., 2009; Ito & Oliver, 2012): LG neurons receive dense VGLUT2-positive axosomatic synapses while SG or glutamatergic neurons not. The somatic size of SG and glutamatergic neurons are similar, and LG neurons have the largest cell bodies in the IC. The LG and SG neurons have a different synaptic organization and different projection targets (described in Synaptic Organization and Morphology of Local Circuit). The functional classification of IC GABAergic neurons is further subdivided into 4 categories by the presence of axosomatic VGLUT2-positive excitatory terminals and an extracellular matrix structure, the perineuronal net (Beebe, Young, Mellott, & Schofield, 2016; Foster, Mellott, & Schofield, 2014). The perineuronal nets are found mainly around large neurons and are on most but not all LG neurons. Since perineuronal nets may stabilize synapses on dendrites and inhibit structural plasticity (Corvetti & Rossi, 2005), the GABAergic LG neurons with perineuronal nets may have reduced plasticity relative to other IC neurons.
Many IC neurons appear to co-release neuromodulators together with classical neurotransmitters such as glutamate and GABA. Neuromodulators, such as nitric oxide, enkephalin, neuropeptide-Y, somatostatin, substance P, and cholecystokinin are prevalent in the IC cortex but not in the ICC (Coote & Rees, 2008; Nakagawa et al., 1995; Tongjaroenbuangam et al., 2006; Wynne, Harvey, Robertson, & Sirinathsinghji, 1995; Wynne & Robertson, 1997). In the lateral cortex, the labeling density of neuromodulators appeared to be layer-specific, suggesting that they control the gain of multimodal inputs. Since GABAergic neurons of all sizes may or may not express nitric oxide synthase (Fujimoto et al., 2017), the expression of nitric oxide is not likely related to the LG/SG classification.
In addition to neuromodulators, IC neurons express other molecular markers. For example, calcium binding proteins like parvalbumin (PV), calretinin, and calbindin are expressed in the IC (Friauf, 1994; Lohmann & Friauf, 1996). The expression of calcium binding protein is also layer- and subdivision-specific. PV is strongly expressed in the ICC and in the GABA modules of layer 2 lateral cortex (Chernock et al., 2004). Calretinin and calbindin is rich in layer 1 of the IC cortex and appears to be almost absent in GABA modules (Friauf, 1994; Lohmann & Friauf, 1996). In many brain regions, PV is used as a marker of GABAergic neurons, and in the IC, almost all GABAergic neurons are positive for PV (Fujimoto et al., 2017). However, a substantial number of GAD67-negative neurons also express PV (Fujimoto et al., 2017), so PV cannot be used as a marker of GABAergic neurons in the IC. Expression patterns of calcium binding proteins change during development (Friauf, 1994; Fujimoto et al., 2017; Lohmann & Friauf, 1996).
IC receives ascending inputs from all auditory brainstem nuclei (Adams, 1979), descending inputs from the auditory cortex (Winer, 2005) and several non-lemniscal thalamic nuclei (Winer, Chernock, Larue, & Cheung, 2002), as well as neuromodulatory inputs from dopaminergic (Nevue, Elde, Perkel, & Portfors, 2015), noradrenergic, serotoninergic (Klepper & Herbert, 1991), and cholinergic (Motts & Schofield, 2009) neurons, and multisensory inputs (Lesicko et al., 2016). Axons from each input source tend to terminate in specific subregions in the IC, some of which are smaller than the obvious anatomical subdivisions (Oliver, 2005). One example is layer 2 of the lateral cortex where somatosensory inputs terminate within the GABA modules and auditory cortex inputs terminate outside the modules (Lesicko et al., 2016). Even within the ICC, there are subregions which differ in terms of the specific combination of inputs from extrinsic sources (Cant & Benson, 2007; Loftus, Bishop, & Oliver, 2010). This “synaptic domain” organization limits the variety of synaptic inputs available to neurons in different parts of the IC (Oliver, 2005). Within the ICC, this concept extends down to the level of the fibrodendritic laminae where adjacent laminae may contain axons from different sources (Loftus, Bishop, Saint Marie, & Oliver, 2004; Shneiderman & Henkel, 1987). A flat, disc-shaped neuron may have both its cell body and dendritic tree confined to one fibrodendritic lamina and receive only one set of synaptic inputs. In contrast, an adjacent large stellate neuron may have dendrites that extend into two or three adjacent laminae and receive inputs from several sets of inputs. Thus, adjacent neurons in the ICC may have very different patterns of synaptic input and receive excitatory or inhibitory synaptic inputs from different sources.
Since the patterns of synaptic distribution on LG, SG, and glutamatergic neurons are very different (Ito et al., 2009), studies about the synaptic organization should account for the type of postsynaptic neuron. The identification of inputs to the dendrites of identified neurons is technically challenging, thus our current knowledge is limited (Oliver, Ostapoff, & Beckius, 1999), and future studies must generate the details about axodendritic synapses on identified neuron types. In the following, the patterns of axosomatic synapses are described.
Both excitatory and inhibitory axosomatic synapses are present in the IC. In an electron microscopic study (Paloff, Usunoff, Hinova-Palova, & Ivanov, 1989), inhibitory axosomatic synapses were common for most neuron types, while excitatory axosomatic synapses were found mainly on large neurons. The large neurons in that study appear to be the GABAergic LG neurons as they share the same ultrastructural features (Ito et al., 2009; Ito & Oliver, 2014). The number of excitatory axosomatic terminals is positively correlated with the somatic size of the LG but not SG neurons (Ito et al., 2009), and this suggests that the density of the axosomatic terminals is kept constant on LG neurons to maintain excitability. The sources of fibers that make VGLUT2-positive excitatory axosomatic contacts on LG neurons include the IC itself, dorsal cochlear nucleus, superior olivary complex, and intermediate nucleus of the lateral lemniscus. Auditory cortex and ventral cochlear nuclei are not likely sources because projection neurons in these regions express VGLUT1 (Ito, Bishop, & Oliver, 2011; Ito & Oliver, 2010), which is not expressed in axosomatic terminals on LG neurons (Ito et al., 2009). Quantitative analysis of the axosomatic contacts from single VGLUT2-expressing axons revealed that a single excitatory axon makes 1–7 axosomatic contacts, so this suggests that an LG neuron receives axosomatic inputs from hundreds of excitatory neurons (Ito et al., 2015; Ito & Oliver, 2014). Furthermore, a single LG neuron receives inputs from both lemniscal fibers and local neurons which indicates a convergence of inputs from many sources (Ito et al., 2015). Since each lower brainstem auditory nucleus encodes different auditory information, LG neurons are likely to integrate auditory information analyzed in parallel in lower brainstem nuclei.
The spatial origins of excitatory and inhibitory local inputs to single IC neurons were revealed in experiments that combined whole-neuron recording with the uncaging of glutamate (Sturm, Zhang-Hooks, Roos, Nguyen, & Kandler, 2017; Sturm, Nguyen, & Kandler, 2014). Because synaptic responses caused by focal glutamate uncaging indicate the presence of presynaptic neurons in the stimulation sites, maps of regions with neurons which make inputs on recorded neurons can be revealed. Inhibitory and excitatory inputs were isolated by holding membrane voltage at the reversal potentials of chloride and glutamate receptors, respectively. Furthermore, the inputs specific to glutamatergic and GABAergic neurons were identified in recordings from VGLUT2-Cre-dT-loxP and VGAT-Cre-dT-loxP mice, respectively. In glutamatergic neurons in the normal condition, the map of inputs from GABAergic neurons was larger than the map of inputs from glutamatergic neurons (Figure 2A). This suggests that excitatory inputs originate in a spatially restricted region, fibrodendritic lamina, while the origin of inhibitory inputs was not restricted in the same lamina. In contrast, the GABAergic neurons were subdivided into 2 groups based on the shape of the map. Type 1 GABAergic neurons received an inhibitory input area from a larger area than the excitatory one. Type 2 neurons received predominantly excitatory inputs with very few or no inhibitory inputs. The amplitude of the excitatory inputs was larger in type 2 neurons than in type 1. The authors suggested that type 1 and type 2 GABAergic neurons correspond to the SG and LG neurons, respectively. Interestingly, noise trauma altered the input maps and synaptic electrical charges to glutamatergic and type 1 GABAergic neurons, but not to type 2 GABAergic neurons. The lack of plasticity in type 2 GABAergic, presumably LG neurons, is also suggested by the fact that most of LG neurons possess perineuronal nets, which may inhibit structural plastic changes (see Neurotransmitter Type or Other Molecular Markers).
The IC consists of the neurons with diverse intrinsic membrane properties, and this results in different firing patterns in response to depolarization (Geis & Borst, 2013; Moore & Trussell, 2017; Ono et al., 2005; Peruzzi, Sivaramakrishnan, & Oliver, 2000; Sivaramakrishnan & Oliver, 2001; Tan & Borst, 2007). The majority of the IC neurons showed the repetitive firing during the depolarization evoked by square current injection, while the others showed transient firing only at the onset of the depolarization (Moore & Trussell, 2017; Peruzzi et al., 2000; Sivaramakrishnan & Oliver, 2001; Tan & Borst, 2007). The neurons with repetitive firing were subdivided by the temporal pattern of the firing: regular sustained, adapting, build-up, pauser, and so forth. The diversity in the firing is shaped by the different potassium currents (Sivaramakrishnan & Oliver, 2001). In addition to the firing pattern to depolarization, IC neurons were subdivided based on the presence of rebound firing to hyperpolarization. This rebound firing was shown to involve the T-type calcium current and the hyperpolarization-activated current (Ih) (Koch & Grothe, 2003; Ono et al., 2005), but the Ih does not determine the firing properties by itself (Koch & Grothe, 2003).
The IC neurons with different firing patterns were not related to specific morphological types (Peruzzi et al., 2000). Moreover, they were not spatially organized in the IC, but it is possible that the neurons with different firing properties are distributed in a mosaic pattern. Both glutamatergic and GABAergic neurons were heterogeneous in terms of their firing patterns, although the patterns in glutamatergic neurons were more diverse than GABAergic neurons (Ono et al., 2005). Consequently, to date, the different firing patterns have not been related to other characteristics of cell types in the IC with a few exceptions. One exception is the GABAergic neurons in the GABA module in the lateral cortex region (Ono et al., 2005). These neurons are a homogenous group with transient firing to depolarization and rebound firing to hyperpolarization. In the dorsal cortex, all the large GABAergic neurons had lower membrane resistance than other types of neurons (Geis & Borst, 2013) despite not being a single firing type. In the future, additional neuronal classifiers will be necessary to associate the firing properties with specific neuron types, and this will help dissect the design of the neural circuits in the IC.
Response Properties to Sound
It is well known that IC neurons have diverse responses to sound. In the response to pure tones, they vary in their frequency response areas (Palmer, Shackleton, Sumner, Zobay, & Rees, 2013), post-stimulus time histograms (PSTH) patterns (Rees, Sarbaz, Malmierca, & Le Beau, 1997), and the degree of temporal adaptation (Perez-Gonzalez & Malmierca, 2014). They also have diverse responses to binaural, amplitude-modulated (AM) (Joris, Schreiner, & Rees, 2004), and frequency-modulated (FM) sounds (Williams & Fuzessery, 2012). This diversity in the IC partly reflects the processing in the neural circuits of the brainstem. In many cases, the responses of the IC neurons reflect their inputs from the neurons in the brainstem. This diversity of inputs was demonstrated directly in recent in vivo whole-cell studies that revealed the synaptic currents evoked by sound in IC neurons (Ono & Oliver, 2014a, 2014b). However, the IC is not merely a relay station. It can integrate information from multiple sources in the brainstem. An anatomical study combined with electrophysiological recordings showed that IC neurons that differed in their responses to binaural stimuli received inputs from different combinations of nuclei in the brainstem (Loftus et al., 2010). In that case, inputs from the different sources were related to neural circuits with distinct roles in binaural processing (or the absence of binaural processing). In some cases, neurons in the IC have complex responses to binaural sound that are likely due to convergence of inputs from at least two of the binaural circuits (Batra, Kuwada, & Stanford, 1993; Li, Gittelman, & Pollak, 2010; McAlpine, Jiang, Shackleton, & Palmer, 1998). The results of these studies strongly suggest that the convergence of afferent inputs generates de novo responses to sound in the IC.
Consistent with these observations, virtually all IC neurons were shown to receive both excitatory and inhibitory synaptic inputs, and this is critical in shaping the response properties of IC neurons. Among the properties shaped by the interaction of the excitatory and inhibitory inputs are: threshold (Ono & Oliver, 2014a), frequency tuning (Xie, Gittelman, & Pollak, 2007), PSTH pattern (Ono & Oliver, 2014a), binaural responses (Li et al., 2010; Ono & Oliver, 2014b; Xiong et al., 2013), FM direction selectivity (Gittelman, Li, & Pollak, 2009; Kuo & Wu, 2012) and others. While all the excitatory synaptic inputs are glutamatergic in the IC, the inhibitory inputs are both GABAergic and glycinergic, and this may lead to a diversity of function. The GABAergic and glycinergic inhibitory currents are known to have distinct kinetics (Moore & Trussell, 2017). Since GABAergic and glycinergic terminals are distributed differentially in the IC (Choy Buentello et al., 2015), it raises the possibility of a segregation of function related to different inputs using these two inhibitory transmitters.
Interestingly, combination-sensitive neurons in the bat appear to depend exclusively on glycinergic inputs and are independent of GABAergic inputs (Nataraj & Wenstrup, 2005; Sanchez, Gans, & Wenstrup, 2008; Wenstrup, Nataraj, & Sanchez, 2012). In addition, FM-rate selectivity in the bat was reported to depend exclusively on glycinergic inputs (Williams & Fuzessery, 2011). Thus, in some cases, the GABAergic and glycinergic inputs are likely to have different functions and terminate on different neurons. However, in other IC neurons, GABAergic and glycinergic inputs may work cooperatively instead of having distinct roles in processing. Previous pharmacological studies have shown that sound-evoked responses of many IC neurons were modulated by blocking either GABAergic or glycinergic inputs. In support of this view, a recent in vitro study showed that some ascending fibers from ventral nucleus of the lateral lemniscus co-released GABA and glycine (Moore & Trussell, 2017). This may be the ultimate form of cooperation between GABAergic and glycinergic in the IC.
In IC neurons, it was reported that there was no one-to-one correspondence between the sound-evoked responses and morphology (Wallace et al., 2012) or intrinsic firing properties (Tan, Theeuwes, Feenstra, & Borst, 2007). The morphology of a neuron is often an important factor in the neuronal response. Morphology largely affects the spread of passive currents within the neuron and constrains the spatial distribution of the synaptic terminals. It is likely that the orientation and length of the dendritic tree affect the combination of the synaptic inputs on the IC neuron since the IC has a tonotopic structure as well as synaptic domains which are created by the different termination zones of different subcortical nuclei. One would expect that neurons with the largest dendritic fields would have the most diverse responses. However, a study using the juxtacellular labeling technique failed to find an explicit relationship between the dendritic morphology and the responses to sound (Wallace et al., 2012). In addition to the morphology, the intrinsic firing properties are expected to influence the neural responses strongly. Again, a study using in vivo whole-cell recording showed that the temporal pattern of the responses of IC neurons to sound did not always match that of firing during the depolarization evoked by square current injection (Tan et al., 2007). In both the case of morphology and intrinsic properties, the lack of correspondence between response pattern and cell morphology is likely due to the diversity in the afferent inputs. Neurons with the same morphology and intrinsic membrane properties may have different responses to sound if the sources of the afferents are different. Further studies will be required to understand the contribution of these cellular properties to sound processing in the IC.
As described in Neurotransmitter Type or Other Molecular Markers, the IC contains both glutamatergic and GABAergic neurons. A recent study elucidated the response properties of glutamatergic and GABAergic IC neurons to sound using transgenic mice that express channelrhodopsin-2 (ChR2) exclusively in the inhibitory neurons. The glutamatergic and GABAergic neurons could not be distinguished in vivo by their spike shapes (Ono, Bishop, & Oliver, 2017) unlike in the neocortex or the hippocampus. Overall, the sound-evoked responses in both classes of neurons were similar, although glutamatergic neurons responded better to amplitude modulations at high rate. However, the responses of both classes were affected by their locations (Ono et al., 2017). These results suggest that the location of the neuron in a specific synaptic domain (described in Synaptic Organization) might be the dominant influence on the response to sound regardless of the cell types. However, the caveat here is that both glutamatergic and GABAergic neurons have subtypes (see Morphology, and Neurotransmitter Type or Other Molecular Markers). It is possible that one subtype might have distinct sound-evoked responses. Today, the development of optogenetics will allow specific cell types in IC to be identified and studied in vivo and in vitro. With this approach, it will be possible to characterize the function of all the neuronal types in the IC and investigate their role in the circuitry of the auditory midbrain.
IC neurons receive inputs not only from extrinsic fibers but also from other IC neurons, making complex local circuitry. The complex local circuitry produces variety and similarity of response patterns among nearby neurons and emerges various forms of plasticity.
Morphology of Local Circuits
The IC has a complex local circuitry. Most neurons with axons that project out of the IC also have a local axonal plexus (Oliver et al., 1991). Single neuron labeling studies showed with intracellular or juxtacellular dye injection or recombinant viral tracers that most IC neurons possessed axons with local collaterals (Ito & Oliver, 2014; Oliver et al., 1991; Wallace et al., 2012). Although the presence of true interneurons is under debate, neurons with well-developed local axons without collaterals entering the brachium of the IC have been observed (Ito & Oliver, 2014; Wallace et al., 2012).
The morphology of the local circuit in the ICC is best viewed in relationship to the fibrodendritic laminae. In cats, disc-shaped neurons have flattened local collaterals that are parallel to the dendritic field of the neuron and extend within the same fibrodendritic laminae as the dendritic field. In contrast, stellate neurons with dendritic trees that are unoriented or orthogonal to the laminae have axonal collaterals that enter multiple fibrodendritic laminae (Oliver et al., 1991). The former circuit may enhance or suppress many neurons within a lamina that share similar tuning, while the latter pattern suggests a circuitry with broad spectral sensitivity used to connect many neurons with different frequency tuning. In rodents, neurons with a laminar axonal plexus can originate from both flat neurons and moderately-oriented, less-flat neurons (Ito & Oliver, 2014; Wallace et al., 2012). Although, most neurons had single local plexuses in the same laminae as the dendritic trees, a few neurons had plexuses in different laminae. These results suggest that the local axons can influence the IC circuitry in various ways. Mapping of local connections with uncaging glutamate in slices showed that IC neurons receive local excitatory as well as inhibitory inputs along the fibrodendritic laminae in which they reside (J. J. Sturm, Nguyen, & Kandler, 2016). This is in line with the anatomical studies (Ito & Oliver, 2014; Wallace et al., 2012) and further shows that the organization of local excitatory and inhibitory circuits is similarity organized. Some ICC neurons also send their local axons into the cortex of the IC, and these neurons are likely to convey auditory information to the multimodal regions of IC.
Since the local IC circuit contains subtypes of both excitatory and inhibitory neurons, identifying the circuitry between specific neuron types is important. Little is known about this topic except for a recent study where three GAD67-negative, putative glutamatergic neurons without visible projection axons were reconstructed, and the apposition of axonal terminals on GABAergic neuron bodies was examined (Ito & Oliver, 2014) (Figure 1). Two ICC neurons had well-developed local axonal plexuses, and the axons made contact on 20 and 30 LG somata. The LG somata receiving contacts were well-aligned on a plane, and this suggested that local glutamatergic neurons innervate many LG neurons in the same fibrodendritic laminae. In the lateral cortex, one pyramidal-like neuron had a poorly developed axon within layer 3, but this axon made contacts with 9 LG somata.
Physiological Properties of Nearby Neurons
It is likely that the local circuit of the IC contains subtypes of neurons with different intrinsic membrane properties, but these neurons receive similar synaptic inputs, as synaptic domain hypothesis suggests. As described in Intrinsic Properties, a spatial organization in the IC has not been reported that could segregate neurons with different firing properties, except for the neurons in the GABA modules. Consistent with this, the expression of voltage sensitive ion channels also appears to lack any specific spatial distribution in IC.
How then are the responses properties to sound organized in the local circuits of the IC? Although few, several studies have reported the relationship of the nearby neurons in the IC, using different recording techniques [single microelectrode; (Ono et al., 2017; Syka, Radionova, & Popelar, 1981), tetrode; (Chen, Rodriguez, Read, & Escabi, 2012; Seshagiri & Delgutte, 2007), multichannel silicon probe; (Atencio, Shen, & Schreiner, 2016)]. In all the studies, the characteristic (CF) or best frequency (BF) were the parameters of the sound-evoked responses that were most highly correlated among the nearby neurons. In three studies, the bandwidths of the frequency response area were also well correlated in the nearby neurons although less so than CF and BF (Atencio et al., 2016; Chen et al., 2012; Ono et al., 2017). However, in another study (Seshagiri & Delgutte, 2007), the bandwidths of the frequency response areas were not significantly correlated. When pairs of identified GABAergic and glutamatergic neurons or pairs of glutamatergic neurons were compared, the pairs shared similar frequency tuning (Ono et al., 2017). This suggests that within a lamina both classes of neurons share inputs with similar frequency tuning, but adjacent laminae could have differences in spectral sensitivity depending on whether the same inputs are present in the adjacent laminae.
The temporal properties of neurons within a local circuit may be less well correlated. The PSTH to pure tones may be highly variable among the nearby neurons (Atencio et al., 2016; Ono et al., 2017; Seshagiri & Delgutte, 2007). This may be true for both GABAergic-glutamatergic and glutamatergic-glutamatergic neuronal pairs (Ono et al., 2017). This could be a function of local neurons with similar inputs but different intrinsic membrane properties. When an array of tetrodes is used, the neurons near one tetrode recording site had spectro-temporal response patterns that were more similar to each other than the neurons at other recording sites (Chen et al., 2012). However, the temporal response patterns to a dynamic moving ripple sound were less well correlated at different sites than the spectral responses. The nature of temporal processing within the local IC circuit and the mechanisms that create the response diversity in the local IC circuit remain unresolved.
Plasticity is ubiquitous and plays a critical role in the organization of functional neural circuits in the CNS. In the IC, it is well known that the corticofugal projection to IC can induce plastic changes in the responses of IC neurons to sound. This top-down plasticity is likely to be critical in the learning of the auditory tasks (Bajo, Nodal, Moore, & King, 2010; Slee & David, 2015). A series of studies by Suga’s group (Suga, 2012; Xiao & Suga, 2005; Zhang & Suga, 1997) showed that the activation or inactivation of the primary auditory cortex changes the response properties of the IC neurons to sound. The plasticity induced by the cortex affects the response properties in the frequency, temporal and intensity domains (reviewed in Suga, 2012). Acoustic fear conditioning induced dramatic frequency changes in the IC via corticofugal projection (Gao & Suga, 1998).
The plastic changes in the IC may not be solely due to changes in the IC local circuit. Corticofugal activity is known to affect multiple levels in the auditory pathway: medial geniculate body, IC, superior olivary nuclei, cochlear nuclei, and cochlea. However, local changes in the IC are likely since because local application of atropine, an acetylcholine blocker, can block the BF changes in IC induced by the acoustic fear conditioning (Ji, Gao, & Suga, 2001). The cholinergic inputs driven by corticofugal projection is likely from pontomesencephalic tegmentum (Schofield, Motts, & Mellott, 2011), but the relationships of these cholinergic inputs to the auditory corticofugal system remains unclear.
In addition to the top-down plasticity, some forms of bottom-up plasticity have been reported in the IC. Stimulus specific adaptation (SSA) is a plastic neuronal processing that is not found caudal to the IC (Ayala, Perez-Gonzalez, Duque, Nelken, & Malmierca, 2013; Carbajal & Malmierca, 2018; Perez-Gonzalez & Malmierca, 2014) (see also chapter by Malmierca et al., in this volume). Given a series of repetitive tones, the neurons with SSA show reduced responses to a common sound, while they respond well to a tone that is rarely presented. SSA was considered to be relevant to novelty detection in the acoustic environment and was first discovered in the auditory cortex (Ulanovsky, Las, & Nelken, 2003). The neurons with SSA are located in the cortices of the IC (Ayala et al., 2015; Carbajal & Malmierca, 2018; Malmierca, Cristaudo, Perez-Gonzalez, & Covey, 2009) that are heavily innervated by the corticofugal projections from auditory cortex. In line with this observation, it was shown that the deactivation of the auditory cortex modified the responses of the neurons with SSA in the IC (Anderson & Malmierca, 2013). However, cortical deactivation did not affect half of the neurons with SSA and did not completely eliminate the SSA in the majority of neurons with decreased SSA after cortical deactivation. Thus, local processing in the IC must contribute to the SSA in the IC neurons. Synaptic depression is likely the major determinant of SSA. Indeed, some IC neurons showed synaptic depression in sound evoked EPSCs when the sound interval was longer than 1 s (Ono & Oliver, 2014a), which is much longer than the 2–8 Hz repetition rate used in SSA experiments suggesting that synaptic depression is even more likely during stimulus presentations in SSA. The highly depressive synaptic inputs might be from IC intrinsic connections because the SSA neuron were shown to receive minimal inputs from brainstem in comparison to non-SSA neurons (Ayala et al., 2015). Further, pharmacological studies have shown that inhibition (Ayala & Malmierca, 2018) and neuromodulators (Ayala & Malmierca, 2015; Valdes-Baizabal, Parras, Ayala, & Malmierca, 2017) modified the SSA in the IC, and this suggests that the SSA in the IC is likely to be shaped by complex neuronal processing.
Another example of bottom-up plasticity is long-lasting sound-evoked after-discharge (Ono, Bishop, & Oliver, 2016). Most neurons in the auditory pathway as well as IC neurons usually respond to sound during its presentation and cease spike discharges at the sound termination. However, when presented a long duration sound (more than 30 s) or repetitive sequential sounds over a long duration, a subpopulation of IC neurons continued to fire for several tens of seconds to a few minutes after the sound termination (after-discharge). Both glutamatergic and GABAergic neurons could exhibit the long-duration sound-evoked after-discharge (LSA). The neurons with LSA were distributed broadly in the ICC, however most were located in the ventral ICC, the area tuned to high sound frequencies (Ono et al., 2016). Although the cellular mechanism that generates LSA remains unknown, it is likely to be shaped in the IC because most neurons in lower brainstem nuclei show a suppression of activity after long-lasting sound stimuli. The functional significance of LSA is also unknown, but it might be a neuronal gain control mechanism dependent on the input strength, and it might be relevant to tinnitus as an abnormal gain enhancement in the auditory pathway (Auerbach, Rodrigues, & Salvi, 2014).
To elucidate the mechanism of these plastic changes in vivo, it is necessary to learn the cellular properties of the neural circuit. In vitro brain slice preparations are helpful in this regard. Most IC neurons show long-term potentiation or long-term depression with tetanic stimulation in the brain slice (Wu, Ma, Sivaramakrishnan, & Oliver, 2002; Zhang & Wu, 2000). Moreover, a plateau potential is seen in the IC in response to electrical stimulation of axons in the lateral lemniscus (Sivaramakrishnan & Oliver, 2006). A sustained depolarization might be relevant to potentiation, depression or LSA. However, studies using IC slice preparations are still limited, and further in vitro investigations of the neural circuits of the IC would promote our understanding of the plastic responses in response to sound.
Finally, the responses of IC neurons can be altered by auditory experiences (Irvine, 2017), for example, partial hearing loss (Chambers et al., 2016; Popescu & Polley, 2010) or specific sound-rearing (Yu, Sanes, Aristizabal, Wadghiri, & Turnbull, 2007). In vitro slice recordings have also shown that hearing loss can modify synaptic strength in the IC neural circuit (J. J. Sturm et al., 2017; Vale, Juiz, Moore, & Sanes, 2004; Vale & Sanes, 2000, 2002). These changes may be a product of a large-scale reorganization within the auditory pathway and interactions between the different structures including the IC. Examples include the application of atropine to the IC of fear-conditioned animals which abolishes the plastic changes in the IC and also reduces the changes in the auditory cortex (Ji et al., 2001). Thus, it might be possible to reduce the symptoms induced by maladaptive plasticity in the auditory pathway (leading to tinnitus) by manipulating the neural activity in the IC.
Key Issues to Address in the Future
To better understand the functional organization of the IC, we need to identify and manipulate specific cell types which are involved in a particular functional unit inside the IC local circuit. Followings are our proposal for the future research direction.
Molecular Markers for Specific Neuronal Types
At this point, we do not have molecular markers that identify subtypes of glutamatergic or GABAergic neurons. For example, it is likely that subtypes of GABAergic neurons (LG, SG, or neurons with perineuronal nets) have different projection patterns and serve different functions. With single molecular markers to define neuronal subtypes, one may create transgenic mice that target specific types of IC neurons to label or modify specific components of the neural circuitry.
Identification of Functional Circuits through the IC and Specific Microcircuits within the IC
Since the IC consists of neuron subtypes, which have different patterns of circuit connectivity, their roles in auditory processing are likely to be different. On the other hand, synaptic domains in the IC suggest the wiring of microcircuit is different between regions. The former implies neuron-type-specific functional organization, while latter implies microdomain-based or map-based functional organization in the IC. Future study may determine which is the case in the IC. It is also possible that dual modes of coding, that is, both neuron-type-based and map-based, are present in the IC. Neuron type identification using molecular markers and recording from large number of neurons will help to clarify this issue. Neighboring neurons with different dendritic arborizations may receive different combination of inputs even their neuron bodies are in the same synaptic domain. Therefore, in future studies of the synaptic organization, the composition of inputs should be related to the neuron type as well as the location of the cell body.
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