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7
The Superior Olivary Complex
Shigeyuki Kuwada and Tom C. T. Yin
Learning Objectives
n The reader will be able to describe the
anatomic divisions of the superior olivary
complex (SOC).
n The reader will be able to describe the
binaural cues and neural circuitry used by
neurons in the SOC to localize sounds
n The reader will be able to describe the
anatomic pathways linking the SOC to
the cochlear nuclei, lateral lemniscus, and
inferior colliculus.
n The reader will be able to describe the
frequency bias of the medial superior olive
and the lateral superior olive.
Key Words. Superior olivary complex, lateral superior olive, medial superior olive, medial nucleus
of the trapezoid body, periolivary nuclei, medial
olivocochlear system, lateral olivocochlear system,
interaural time differences, interaural intensity differences, sound localization
Functional Anatomy of the
Superior Olivary Complex
The superior olivary complex (SOC) is an important
relay center for ascending auditory information as
it receives projections from the cochlear nucleus,
which in turn is the destination of all auditory nerve
fibers from the cochlea. Since both cochlear nuclei
impinge upon cells in the SOC, it represents the initial site of binaural interaction. The SOC is so named
because anatomically it is in a superior position relative to the inferior olivary complex. The term olivary is based on the olive-shaped protuberance on
the ventral lateral surface of the medulla created by
the underlying inferior olivary complex. The SOC
extends from the rostral medulla to the caudal pons
and is called a complex because it represents many
nuclear groups. The SOC can be functionally divided
into a feedback system to the cochlea (olivocochlear
system), an inhibitory periolivary system and a
sound-localization system. Anatomically, there is
considerable overlap between these systems. The
SOC varies in size and composition among species
(Figure 7–1). The main nuclei, the lateral (LSO) and
medial (MSO, Figure 7–1, green filled) superior olivary nuclei can usually be identified in most species,
but the nuclei that surround the LSO and MSO, viz.,
the periolivary nuclei (Figure 7–1, gray filled), take
many forms. The tuning of neurons in LSO is biased
towards high frequencies, whereas those in the
MSO are biased towards low frequencies (Guinan
et al., 1972). Thus, the relative size of the LSO and
MSO reflect the animal’s frequency range of hearing (Glendenning & Masterton, 1998). So, animals
with a hearing bias towards high frequency sounds
(e.g., mice and rats) have a large LSO and a small
MSO. Animals with good low and high frequency
hearing (e.g., cats) have a prominent LSO and MSO.
Humans have a hearing bias towards low frequency
sounds so the most prominent nucleus is the MSO.
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(SPON) although they are not entirely equivalent in
their inputs and outputs. The MNTB is classically
considered a main nucleus but we include it with
the periolivary group because it logically fits with
this group. The trapezoid body (aka, ventral acoustic
stria) is a thick band of axons bounded ventrally by
the ventral border of the brainstem and the pyramidal tract and the approximate position of the dorsal
border is shown in Figure 7–2B. The trapezoid body
is primarily made up of axons of cochlear nucleus
(CN) neurons projecting to the SOC, axons from
SOC nuclei to other SOC nuclei, and axons from SOC
nuclei projecting to higher structures. The trapezoid
body is so named because the descending axons
from the abducens (cranial nerve VI) nucleus create
an image of a trapeze with the descending abducens
nerve fibers being the ropes of the trapeze and the
crossing axons the seat or body of the trapeze.
Feedback System to the Cochlea
(olivocochlear system)
Figure 7–1. The superior olivary complex in different species. Lateral superior olive (LSO), medial superior olive
(MSO), medial nucleus of the trapezoid body (MNTB).
Based on Schwartz, 1992. Mouse and rat provided by Tetsufumi Ito.
The LSO in humans is difficult to identify and even
more difficult is the medial nucleus of the trapezoid
body (MNTB), a periolivary nucleus that has strong
projections to the LSO in most mammals (Bazwinsky
et al., 2003).
Figure 7–2 shows the organization of the SOC in
the cat from its caudal (Figure 7–2A) to rostral (Figure 7–2D) extent. The main nuclei of the SOC, the
MSO and LSO, are depicted as green and the periolivary nuclei as gray. The periolivary nuclei surround
the main nuclei and are named according to position:
medial (MNTB), ventral (VNTB), and lateral (LNTB)
nuclei of the trapezoid body and the anterior lateral
(ALPO), dorsal lateral (DLPO), and dorsal medial
(DMPO) periolivary nuclei. In rodents the DMPO
nucleus is called the superior paraolivary nucleus
Our treatment of this system is brief because it
will be comprehensively discussed by Guinan (see
Chapter 11). This is a feedback system where neurons in the SOC project their axons to the hair cells
of the cochlea, hence the name olivocochlear system.
A major role of this system is to actively alter the
mechanical tuning of the basilar membrane by affecting the motility of the outer hair cells (OHCs). This
system is often referred to as a cochlear amplifier.
Figure 7–2 shows the locations of olivocochlear
neurons that were stained by injecting a retrograde
tracer, into the left cochlea of a cat (Vetter et al., 1991;
Warr et al., 2002). Two populations of neurons can be
seen, those located medial and those located lateral
to the MSO and are appropriately named the medial
(MOC) and lateral (LOC) olivocochlear neurons.
The LOC neurons can be further divided into those
that are in close proximity to the margins of the LSO
(marginal LOC) and those located more distally to
the LSO (para-LOC). The olivocochlear neurons
project bilaterally, however, MOC neurons project
predominantly to the contralateral cochlea whereas
those in the LOC project primarily to the ipsilateral
cochlea.
Figure 7–2. Transverse sections depicting the caudal (A) to rostral (D) extent of the SOC. Also depicted in the center is a line drawing of the whole brainstem at that level of the SOC. The main nuclei, medial superior olive (MSO)
and lateral superior olive (LSO) are colored green. The periolivary nuclei, medial (MNTB), ventral (VNTB) and lateral (LNTB) nuclei of the trapezoid body and the anterior lateral (ALPO), dorsal lateral (DLPO), and dorsal medial
(DMPO) periolivary nuclei are colored gray. Also shown at the rostral extreme is the ventral nucleus of the lateral lemniscus (VNLL). Adapted from Warr et al., 2002, with permission by the Association for Research in Otolaryngology.
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Figure 7–3 provides a schematic of the olivocochlear system. The MOC neurons are myelinated and
innervate the base of OHCs using acetylcholine as its
transmitter (Vetter et al., 1991), although a small proportion may use GABA as a transmitter (Whitlon &
Sobkowicz, 1989). About two-thirds of the neurons
project to the contralateral cochlea and one-third to
the ipsilateral cochlea. In the cat, the MOC neurons
almost exclusively reside in three periolivary nuclei,
VNTB, MNTB, and DMPO. These neurons show
Figure 7–3. Schematic of olivocochlear system. medial olivocochlear (MOC), lateral olivocochlear (LOC), outer hair cell
(OHC), inner hair cell (IHC), tectoral membrane (TH), pyramidal tract (PT). Adapted from Warr et al., 2002, with permission by the Association for Research in Otolaryngology.
The Superior Olivary Complex
sharp frequency tuning and project to many hair
cells located above and below the frequency tuning
of the MOC neuron (Liberman & Brown, 1986). The
marginal cell region of the anteroventral cochlear
nucleus (AVCN) project bilaterally to MOC neurons.
It is hypothesized that the marginal cells provide
information about sound intensity as part of a feedback gain control system comprising the cochlea,
cochlear neurons, CN, MOC neurons, and cochlear
OHCs (Ghoshal & Kim, 1997; Ye et al., 2000).
The function of the LOC neurons is not well
understood because their small size and unmyelinated axons make recordings difficult. In cat, cell bodies of LOC neurons are preferentially distributed in
the low frequency region (lateral limb) of the LSO.
They project to the inner hair cells (IHCs) where they
synapse on the afferent terminals of auditory nerve
fibers (Liberman, 1980). This projection appears tonotopic, because injections of anterograde tracers at
progressively more medial regions of the LSO label
terminals near IHCs at progressively more basal
locations in the ipsilateral cochlea (Guinan et al.,
1984). LOC neurons use acetylcholine as a transmitter, but other neuroactive substances (enkephalin,
Altschuler et al., 1984); dynorphin, Abou-Madi et al.,
1987); calicitonin gene-related peptide, Vetter et al.,
1991) are found to colocalize with acetylcholine. The
LOC neurons receive inputs from the ipsilateral,
posteroventral cochlear nucleus (PVCN: Warr, 1982).
Inhibitory, Periolivary System
This system does not appear to have a unitary function and is, as a whole, the least understood group
of nuclei of the SOC. A common feature is that most
periolivary neurons are immunoreactive for glycine
and GABA. Thus, these neurons provide inhibitory
inputs to the CN (Figure 7–4) as well as to other
nuclei of the SOC. In general, the role of inhibition
in sensory systems is to sharpen receptive fields,
enhance contrast and improve frequency tuning.
Also shown in Figure 7–4 is the projection of MOC
neurons to the contralateral VCN. As described (see
Figures 7–2 and 7–3), these neurons use acetylcholine as a transmitter. The periolivary nuclei, except
for the MNTB, show dense immunoreactive labeling for serotoninergic fibers (Figure 7–5). Serotonin
is considered a neuromodulator and is produced in
the Raphe nucleus, a structure that runs the length of
the brainstem. Serotonin levels are low during sleep
Figure 7–4. Outputs of periolivary nuclei to cochlear nuclei. Adapted from Helfert and
Aschoff, 1997, with permission by the Oxford University Press, Inc.
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and high during vigilant states. A local injection of
serotonin usually usually depresses responses and
increases neural response latencies to sound in neu-
Figure 7–5. Distribution of immunoreactive serotonergic
fibers in the SOC of the cat. Reprinted from (Thompson and
Schofield, 2000), with permission by Microscopy Research
Techniques (John Wiley & Sons).
rons of the inferior colliculus, though the effect can
be stimulus dependent (Hurley & Pollak, 1999).
Another common feature is that the periolivary nuclei receive their excitatory input from the
CN (Figure 7–6). These inputs are from specific cell
types (octopus, globular bushy and stellate cells) in
the VCN. The collateral branches in the schematic of
Figure 7–6 are not necessarily meant to indicate that
the same cell in the CN innervates different periolivary nuclei, though most cells do innervate more
than one target, but instead that the same cell type
can innervate more than one periolivary nucleus.
The MNTB and VMPO receive inputs from the contralateral VCN, the DLPO, and LNTB from the ipsilateral VCN, and the DMPO and VNTB from both
VCNs (see review by Helfert & Aschoff, 1997).
In addition to the inputs to the SOC from the
cochlear nuclei, higher-order structures also provide
inputs to the SOC. Figure 7–7 shows these descending
inputs. The heaviest projections are from the thalamus
and inferior colliculus (IC), with a lighter projection
from the auditory cortex (Thompson & Schofield, 2000).
Interestingly, the DMPO and VNTB are the major recipients of these inputs and they are the only periolivary
nuclei that receive input from both CN (see Figure 7–6).
Figure 7–6. Cochlear nucleus inputs to periolivary nuclei. Adapted from Helfert and
Aschoff, 1997, with permission by the Oxford University Press, Inc.
The VNTB houses many MOC neurons and
many of these neurons are excited by binaural
sound stimulation, consistent with the inputs from
both CN. MOC neurons exhibit a slow chopping
firing pattern that persists for the duration of the
sound (Liberman & Brown, 1986). In contrast, the
predominant response of DMPO/SPON neurons
is suppression to sound stimulation followed by a
robust off-response when the sound is turned off
(Kulesza et al., 2003; Kuwada & Batra, 1999). These
neurons have a strong preference to sounds presented to the contralateral ear. As described above,
DMPO/SPON neurons receive an excitatory input
from octopus cell in the contralateral CN as well as
a weak input from stellate cells in the ipsilateral CN.
This structure also receives a strong projection from
the ipsilateral MNTB that uses the inhibitory transmitter, glycine. So, the suppression seen to contralateral sound stimulation is most likely created by
the MNTB input, and release from inhibition, that
is, at sound offset, creates an off response through a
rebound mechanism (Kuwada & Batra, 1999). Examples of off-responses recorded in or near the vicinity
of the DMPO in the unanesthetized rabbit is shown
Figure 7–7. Schematic of major descending projections
to the SOC. Adapted from Thompson and Schofield (2000),
with permission by Microscopy Research Techniques (John
Wiley and Sons).
The Superior Olivary Complex
in Figure 7–8. Both of the neurons display suppression to a 50-msec tone burst at high and low sound
levels, followed by a punctuate but long-lasting off
response. The rate-level function of these two neurons (panels C & F) indicates that the off-response is
monotonic over a wide intensity range (~60 to 70 dB).
Humans are sensitive to even a wider range, but the
range seen in these off neurons is 2 to 3 times greater
than that seen in the auditory nerve. Although the
response to tones is suppressive, periodic sinusoidal amplitude modulated (SAM) tone can entrain
the off-response to create a time-locked response to
the modulation frequency. Figure 7–9 (left column)
shows the response of a SOC neuron in the form of
Figure 7–8. Examples of SOC neurons that show an off
response to tone bursts and their rate-level functions to the
off response. Adapted from Kuwada and Batra (1999), with
permission by the Society for Neuroscience via Copyright
Clearance Center.
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Figure 7–9. Response of an off-neuron to SAM tones. Left column: post-stimulus time histograms to modulation frequencies between 25 and 800 Hz. Right column: corresponding cycle histograms binned over a cycle
of the modulation frequency. Carrier frequency = 6 kHz, intensity = 42 dB SPL. Adapted from Kuwada and
Batra (1999), with permission by the Society for Neuroscience via Copyright Clearance Center.
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poststimulus time histograms to different modulation frequencies. At 800 Hz, there is a weak sustained
response during the 1100 msec SAM tone followed
by a robust off-response. However, at progressively lower modulation frequencies, the sustained
response becomes more robust and the off response
at the lowest modulation frequencies (50 and 25 Hz)
blends completely with the sustained response. The
cycle histograms created by averaging the response
over one cycle of the modulation frequency (right
column) only over the stimulus duration indicate
that the spike timing is highly locked to the modu-
The Superior Olivary Complex
lation frequency, even at the highest modulation
frequency where the sustained response is weak.
Careful analysis of the phase indicates that the sustained response is due to the entrainment of the neuron’s off response (Kuwada & Batra, 1999). As shown
in Figure 7–9, this off response is present over a wide
range of modulation frequencies, and is also responsive over a wide range of sound levels and modulation depths. An example is shown in Figure 7–10.
When synchrony is measured, the modulation transfer function to sound intensity (Figure 7–10A) and to
modulation depth (Figure 7–10C) both show primarily
Figure 7–10. Modulation transfer functions (MTFs) of an off-neuron as a function of sound level and modulation depth.
MTFs based on synchrony (A) and spike rate (B) at different sound levels. MTFs based on synchrony (C) and spike rate (D)
at different modulation depths measured at 50 dB SPL. E. Synchrony as a function of level and modulation depth measured
at 100 Hz modulation. F. Spike rate as a function of level and modulation depth measured at 100 Hz modulation. Adapted
from Kuwada and Batra (1999), with permission by the Society for Neuroscience via Copyright Clearance Center.
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a low-pass shape. When measured as a function of
intensity or modulation depth (at 100 Hz modulation) synchrony becomes asymptotic (Figure 7–10E).
In contrast, the spike rate modulation transfer functions to intensity and depth is primarily band pass in
shape. The spike rate is non-monotonic with sound
level and monotonic with modulation depth (Figure
7–10F). A common view of the role of inhibition is
that it attenuates or suppresses post-synaptic neural activity. Although this is true for off neurons, the
robust discharge when inhibition is released adds
a new dimension. For simple sounds, (e.g., tones),
the off response can code a wide range of sound
levels (see Figure 7–8). For complex sounds, the off
response becomes entrained to each modulation,
resulting in precise temporal coding of the envelope
(see Figures 7–9 and 7–10)
Off responses in the SOC of rats are almost
exclusively found in the SPON (Kulesza et al., 2003).
Unlike the robust off response seen in the unanesthetized rabbit (e.g., see Figure 7–8), the off responses in
the anesthetized rat often constitutes a single action
potential. Neurons in the DMPO and SPON project
to the ipsilateral IC using GABA as a transmitter
(Saldana & Berrebi, 2000). The role of this projection
is unclear but would serve to modulate AM sensitivity or be a source of AM processing in the midbrain.
Kadner and Berrebi (2008) have suggested that off
neurons may play a role in gap detection.
Question 1
Are there diseases known to result in disordered processing in the human SOC?
Answer 1
Diseases like multiple sclerosis do target
myelinated fibers and the SOC receives
inputs from large myelinated axons. However, this disease has wide spread effects
and would not specifically target the SOC.
Vascular strokes in this area of the brainstem
are often fatal so again deficiencies specific
to the SOC would not be reported.
Sound Localization System
The ability to localize sounds in space is accomplished by comparing the signals at the two ears.
The comparison can be in the difference in the time
of arrival of the signals at the two ears, viz., interaural time differences (ITDs), or in the difference in
sound pressure level of the signals at the two ears,
viz., interaural level differences (ILDs). The SOC is
considered to be the initial site where these binaural
comparisons are made. Chapter 14 discusses binaural hearing, and specifically sound localization,
in more detail). Figure 7–11 displays these binaural
cues measured with miniature microphones placed
deep in the rabbit’s ears to a broad band sound from
5 locations along the horizontal plane in an anechoic
chamber. The traces in the upper panel for each location display the time waveforms recorded at each
ear, whereas the lower panel displays the response
in the frequency domain. For any source off the midline, the sound will reach the closer ear first, creating
an ITD. Because the head is an obstacle to sound,
the sound at the closer ear will also be louder than
that to the distal ear, creating an ILD. The degree to
which a sound is attenuated by striking an object,
like a head, depends upon the wavelength of the
sound relative to the size of the object. If the wavelength is long with respect to the size of the head,
then there is minimal attenuation and therefore
small ILD. If the wavelength is short (i.e., high frequency) relative to head size, then there is large
attenuation and large ILD. This dependence of ILD
on frequency can be clearly seen in the frequency
response traces of Figure 7–11, that show increasing
divergence of the left and right ear traces as a function of frequency. It follows that ILDs are an important cue to localize high-frequency sound sources. In
contrast, ITDs are an important cue to localize low
frequency sound sources because the neural timing information needed to convey ITDs is present
in auditory nerve fibers, only for frequencies below
~2 kHz. This dichotomy between the mechanisms
for localizing low- and high-frequency signals was
formulated long ago (Rayleigh, 1907) and is often
referred to as the Duplex theory. Interestingly, the
main nuclei of the SOC, the LSO and MSO, can be
The Superior Olivary Complex
Figure 7–11. Acoustic recordings made in the ear canals of a rabbit to a broad band sound from 5 different spatial locations along the horizontal meridian. Upper panels depict the time waveform from the left (blue) and right (red) ear and
corresponding lower panels depict the power spectrum.
viewed as the structural basis for the Duplex theory: ITDs are encoded in the MSO whereas ILDs are
encoded in the LSO.
The frequency dichotomy expressed in the
Duplex theory is reflected in the distribution of best
frequencies in the MSO and LSO. As can be seen in
Figure 7–12, both the LSO and the MNTB have a
disproportionate number of neurons tuned to high
frequencies in accord with the role of the LSO for
encoding ILDs (Guinan et al., 1972). On the other
hand, there is the opposite bias in the MSO with a
disproportionate representation of low frequencies
and neurons sensitive to ITDs.
The inputs to the MSO and LSO are illustrated
in Figure 7–13. The MSO receives excitatory (glutamatergic) inputs from spherical bushy cells in the
VCN of both sides (see Figure 7–13A). In addition it
also receives inhibitory (glycinergic) inputs from the
ipsilateral LNTB and MNTB that may be the source
of ipsilateral- and contralateral-induced inhibition,
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dreau & Tsuchitani, 1970). As expected, the receptive fields of LSO cells are such that they respond to
stimuli in the ipsilateral sound field and are turned
off by sounds in the contralateral sound field.
Processing of ITDs
Figure 7–12. Tonotopic organization of the LSO, MSO, and
MNTB in the cat. Based on Guinan et al. (1972) and Boudreau and Tsuchitani (1970).
respectively, since globular bushy cells provide excitatory input to the ipsilateral LNTB and contralateral
MNTB (Smith et al., 1991; Cant & Hyson, 1992).
The LSO receives excitatory input from spherical bushy cells in the ipsilateral cochlear nucleus (see
Figure 7–13B). The input from the contralateral CN
originates from globular bushy cells whose axons
cross the midline and synapse onto principal cells in
the MNTB with one of the most remarkable synapses
in the brain: the giant calyces of Held (Tolbert et al.,
1982). In turn, the axons of the principal cells in the
MNTB make inhibitory glycinergic (Moore & Caspary, 1983) synapses onto LSO neurons of the same
side (Spangler et al., 1985). In rat, another source of
inhibitory input to the LSO is from the contralateral
VNTB (Warr & Beck, 1996). Planar multipolar cells
in the DCN may also project to the ipsilateral LSO in
the rat (Doucet & Ryugo, 2003). The result of these
inputs is that LSO cells are excited by stimulation of
the ipsilateral ear and inhibited by stimulation of the
contralateral ear, so-called IE cells, thereby making
them sensitive to the ILD between the two ears (Bou-
In order for a neuron to encode ITDs, the inputs from
each ear must reflect the temporal structure of the
sound waveforms at each ear. For tonal sounds, this
feature is called phase-locking. Phase-locking begins
to roll off around 1 kHz in most species. The exception is the barn owl where phase-locking is seen to
~9 kHz. The frequency limits of phase-locking dictates the frequency limit for ITD sensitivity. So, for
most mammals with low frequency hearing, the
bulk of the neurons prefer ITD at frequencies below
~1.5 kHz, but can extend to 2 to 3 kHz in the cat. The
barn owl can show ITD sensitivity to about 10 kHz.
In humans, the limit is about 1.1 kHz.
The type of ITD sensitivity is dependent on
whether the inputs from each ear are excitatory
or inhibitory. Figure 7–14 represents the predicted
response of a MSO (see Figures 7–15A and 7–15B)
or LSO (see Figures 7–14C and 7–14D) neuron to
low frequency tonal stimulation that arrive in-phase
(Figures 7–14A and 7–14C) or out-of-phase (Figures
7–14B and 7–14D) between the ears. The inputs to
these neurons have action potentials that are temporally locked to the tonal waveform and this feature
is referred to as phase-locking (Joris et al., 1994). The
MSO neuron receives phase-locked excitatory inputs
(see Figure 7–14, column 2) from either ear and the
LSO neuron (see Figures 7–14C and 7–14D) receives
excitatory input from the ipsilateral ear and inhibitory input from the contralateral ear (re: to the side of
the LSO cell). Shown for both the MSO and LSO are
cases when the ITD is such that the inputs from each
ear arrive coincident in time (in-phase, see Figures
7–14A and 7–14C) or when they arrive maximally
discordant in time (out-of-phase, see Figures 7–14B
and 7–14D). For the model MSO neuron, the phaselocked, action potentials from each ear evoke phaselocked, excitatory postsynaptic potentials (EPSPs,
see Figure 7–14, column 3). In contrast, for the LSO
neuron, the phase-locked, action potentials from the
The Superior Olivary Complex
Figure 7–13. Schematic of the medial superior olive (MSO) circuit (A) and the lateral
superior olive (LSO) circuit (B). Abbreviations: dorsal (DCN) and ventral (VCN) cochlear
nucleus, spinal trigeminal tract (STT), medial (MNTB), ventral (VNTB), and lateral (LNTB)
nuclei of the trapezoid body (TB), dorsal lateral (DLPO) and dorsal medial (DMPO) periolivary nuclei, pyramidal tract (PT).
contralateral ear evokes phase-locked, inhibitory
post synaptic potentials (IPSPs) and those to ipsilateral stimulation evoke phase-locked EPSPs. For the
MSO neuron, when the inputs arrive coincident in
time (see Figure 7–14A), the EPSPs from each side
optimally sum, creating suprathreshold EPSPs (see
Figure 7–14A, column 4) and a maximal discharge
of action potentials (see Figure 7–14A, column 5).
Under the same conditions for the model LSO neuron (see Figure 7–14C), the EPSPs and IPSPs cancel
each other and no action potentials are discharged.
In the case where the inputs arrive discordant in
time, the model MSO neuron is minimally excited
(see Figure 7–14B) whereas the model LSO neuron
is maximally activated (see Figure 7–14D, column 4
and 5). When the ITD is systematically varied, the
ITD functions for the model MSO and LSO show a
cyclic function at the period of the stimulating frequency (see Figure 7–14, column 6). At maximum
coincidence (0 ITD) the MSO neuron fires maximally
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Figure 7–14. A neural schema of ITD processing for model MSO and LSO neurons. The MSO neuron (A and B) receives
excitatory (+) inputs from each side, and the LSO neuron (C and D) receives excitatory inputs from the ipsilateral side and
inhibitory inputs (-) from the contralateral side. Column 1: 5 cycles of a low frequency tone delivered to the contralateral
(blue trace) and ipsilateral (red trace) ear either in-phase (A & C) or out-of-phase (B & D). Column 2. Schematic of action
potentials (spikes) phase locked to the stimulating tone that synapse onto a MSO (A & B) or LSO (C & D) neuron. Column 3.
Postsynaptic potentials evoked by the contralateral and ipsilateral phase locked spikes. Column 4. Summed postsynaptic
responses to binaural stimulation. Threshold for action potentials is indicated by arrows and is lower in the LSO cell (C &
D) than for the MSO cell (A & B). Column 5. Schematic of the spike output as a result of the summed postsynaptic potentials exceeding action potential threshold. Column 6. Schematic of the ITD functions for the model MSO and LSO when
the ITD is systematically varied.
whereas the LSO neuron fires minimally. Note that
at maximal activation the MSO neuron exceeds its
monaural inputs whereas the maximum response of
the LSO neuron does not exceed its ipsilateral input.
As the ITD function is cyclic when the ITD of a
tone is varied (see Figure 7–14, column 6), it is not
possible to determine whether coincidence evokes
maximum excitation or suppression using a single
tonal stimulus. If the mechanism proposed in Figure 7–14 is operating, then the ITD functions across
multiple frequencies should show alignment of the
maximum discharge (peak) for MSO neurons and
alignment of the minimal discharge (trough) for LSO
neurons. This prediction is illustrated in Figure 7–15.
For the model MSO neuron (Figure 7–15A ), the ITD
functions at different stimulating frequencies (500
to 1500 Hz) show a peak discharge that align at a
common ITD, in this case, when the ipsilateral tone
is delayed by 150 µsec relative to the contralateral
tone. In contrast to the model MSO neuron, the
The Superior Olivary Complex
Figure 7–15. Schematic of a peak (A–C) and a trough (D–F) type neuron. A and D. ITD functions across frequency for
a peak and trough type neuron, respectively. B and E. Composite curve derived from averaging the functions in A and D.
C and F. Linear fit of mean interaural phase versus stimulus frequency for a peak and trough type neuron. Characteristic
phase (CP) is the phase intercept at 0 Hz and the characteristic delay (CD) is the slope of the linear fit.
ITD functions for the model LSO neuron display a
minimum (trough) at a common ITD, in this case,
when the ipsilateral stimulus is delayed by 150 µsec
(Figure 7–15D). The middle panels (Figures 7–15B
and 7–15E) show the composite curves derived by
averaging the ITD functions in the corresponding
panels. The composite curve for the MSO neuron
has a peak at 150 µsec whereas that for the LSO
neuron has a trough at 150 µsec. The alignment of
the peaks or troughs of the ITD functions was first
observed in the IC by Rose et al. (1966), and the ITD
where this alignment occurred was called the “characteristic delay” (CD). They hypothesized that the
CD reflected a difference in the anatomical delays
required to activate the binaural cell. By offsetting
the difference in anatomical delays with an ITD, the
inputs from each ear would arrive simultaneously at
the binaural neuron and maximally excite or inhibit
it. The quantitative analysis of CDs was developed
later by Yin and Kuwada (1983) and is illustrated
in the right panels (see Figures 7–15C and 7–15F).
The mean interaural phase for maximal discharge
for each ITD curve is plotted as a function of stimulating frequency and fitted with a linear regression
line. The slope of the regression line represents the
CD, and the y-intercept at 0 Hz is the characteristic
175
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Translational Perspectives in Auditory Neuroscience: Normal Aspects of Hearing
phase (CP). For the model MSO neuron, a CP of 0 or
equivalently 1 cycle indicates that the CD occurred
at maximal discharge (see Figure 7–15C), while for a
model LSO neuron a CP of 0.5 cycles indicates that
the CD occurred at minimal discharge (see Figure
7–15F). Note that for these idealized neurons, the
best delay measured from the composite curves (see
Figures 7–15B and 7–15E) matches the CD.
The ITD sensitivity of actual MSO and LSO neurons are remarkably similar to the idealized model
neurons depicted in Figures 7–14 and 7–15. Figure
7–16 displays the ITD properties of a MSO and LSO
neuron recorded in the cat (Tollin & Yin, 2005; Yin &
Chan, 1990). Like the model neurons, the peak of the
ITD functions across frequency align at the same ITD
for the MSO neuron, whereas the trough of the ITD
functions across frequency align at the same ITD for
the LSO neuron. Also, like the model neurons, the
CP for the MSO neuron is near 0 cycles whereas that
for the LSO neuron is near 0.5 cycles, and in both
cases the CD is similar to the best delay.
The representation of ITDs and the neural code
for locating a low frequency sound source along the
azimuth is a subject of considerable debate (Joris
Figure 7–16. Responses of a MSO, peak-type (A–C) and a LSO, trough-type (D–F) neuron. A and D. ITD functions across
frequency for the MSO peak and MSO neuron, respectively. B and E. Composite curve derived from averaging the functions in A and D. C and F. Linear fit of mean interaural phase versus stimulus frequency for the MSO and LSO neuron.
Characteristic phase (CP) is the phase intercept at 0 Hz and the characteristic delay (CD) is the slope of the linear fit. Panel
A adapted from Yin and Chan (1990), with permission of The American Physiological Society.
& Yin, 2007). The classic view proposed in 1948 by
Lloyd Jeffress (1948) postulated an array of coincidence detectors (e.g., MSO neurons) each with its
own set of neural delay lines from each ear that offset the acoustic delays created between the ears from
a sound source along the azimuthal plane. In this
way an ITD code could be transformed into a place
code for sound localization. Many of the anatomic
(Beckius et al., 1999; Smith et al., 1993) and physiologic features of the MSO and its inputs have been
found to be consistent with the Jeffress model (Batra
et al., 1997; Goldberg & Brown, 1969; Spitzer & Semple, 1995; Yin & Chan, 1990; ). However, the finding
that the best ITD of a neuron was related to its best
frequency and that the peaks of the ITD functions
for small-headed animals were often outside of the
range that such animals would normally encounter (McAlpine et al., 2001) led to a resurrection of
the count comparison model first proposed by von
Békésy (1930) and van Bergeijk (1962) that sound
localization could be achieved by comparing activity in a structure on one side of the brain with the
activity of the equivalent structure on the other side.
McAlpine et al.(2001) noted that the medial slope
of the ITD functions, independent of the neuron’s
best frequency, fell within the physiological range
of small-headed animals and changes in ITD would
create rapid changes in response rate (also see Skottun et al., 2001). Brand et al. (2002) and Pecka et al.
(2008) provided evidence in the MSO of gerbils that
inhibitory mechanisms could shift the peaks of the
ITD functions outward so that the steep part of this
function is always within the physiologic range of
the animal.
A schema comparing the Jeffress place code
model with slope, count comparison model is presented in Figure 7–17. The upper panel depicts an
array of ITD-sensitive neurons, each tuned to a particular ITD. Also shown at the top is the range of
ITDs encountered by animals with different head
sizes. For animals with a small head size (e.g., gerbil,
±125 µsec), the array is limited and only the medial
slopes (heavy blue and red lines) fall within the
natural range. In this case, the ITD created by a
sound source, depending on its location, would create activity on one side of the brain that could be
compared with the activity on the opposite side of
the brain. In this example, the Jeffress place code
The Superior Olivary Complex
would be inoperative due to the sparseness of the
ITD array. In contrast, for a medium (e.g., cat, ±400
µsec) or large size head (e.g., human, ±825 µsec), the
medial slope only constitute a small part of the natural ITD range. So, a Jeffress-type place code would
be optimal and ITD created by a sound source would
create focused neural activity in the ITD/azimuthal
plane. In the middle panel of Figure 7–17, the width
of the ITD functions have been broadened. This situation allows the count comparison model to operate
for both small and medium head size and a sparse
array for animals with a large head size. In the bottom panel, the width of the ITD functions have been
broadened even more and here the count comparison model operates over a broad range of head sizes.
In summary, when the ITD functions are narrow and
dense (see Figure 7–17, upper panel), the count comparison model only operates for small head sizes. As
the ITD functions broaden and become sparse, the
count comparison model can encompass large and
larger head sizes. However, the amount of broadening needed to make the count comparison model
work for all head sizes and all frequencies exceeds
the physiological evidence (Palmer & Kuwada,
2005). Harper and McAlpine, (2004) concluded that
a count comparison mechanism may operate for
small-headed animals and a Jeffress place model for
large-headed animals.
Processing of ILDs
While the data presented above argue for a weak
role of LSO cells in coding ITDs of complex stimuli,
the basic IE response property of LSO cells has traditionally been considered to convey a role in ILD processing (Boudreau & Tsuchitani, 1970). As discussed
above, LSO cells receive excitatory inputs from the
ipsilateral CN and inhibitory inputs relayed by glycinergic neurons of the MNTB that are in turn excited
by the calyces of Held synapses from globular bushy
cells of the contralateral CN. The end result is that
LSO cells are excited by stimulation of the ipsilateral ear and inhibited by stimulation of the contralateral ear. In this way they are sensitive to the ILD
at the two ears. Usually, this has been studied using
dichotic stimuli so that the inputs to each ear can be
precisely specified.
177
Figure 7–17. Schematic of two models of sound localization. Displayed is an array of ITD-sensitive neurons, each tuned
to a particular ITD. The extent of the array depends on the size of the head and in our schematic is shown for ±100 µsec
(e.g., gerbil), ±400 µsec (e.g., cat) and ±800 µsec (e.g., humans). The heavy lines centered about an ITD of 0 µsec are the functions used in a slope, count comparison model whereas the entire array are the functions used in a peak-picking or Jeffress
model. Top panel: Half-width of ITD functions is 200 µsec; for the middle panel, 800 µsec; and for the bottom panel, 1600 µsec.
178
Figure 7–18 shows responses of an LSO cell
illustrating its sensitivity to ILDs. Figures 7–18A
through 7–18D show the dot rasters and associated
histograms of responses to 300 ms duration best frequency tones (16 kHz) with the ipsilateral excitatory
tone held at 30 dB SPL while the contralateral tone
is raised from 5 dB SPL (see Figure 7–18A) to 45 dB
SPL (see Figure 7–18D). By holding the excitatory
ipsilateral stimulus constant, the inhibitory effect of
the contralateral input is clearly seen as it is raised
in level. The spike count is plotted as a function of
ILD (defined as the contralateral level in dB minus
the ipsilateral level) in Figure 7–18E. Negative ILDs
correspond to higher levels to the ipsilateral ear. ILD
sensitivity can be quantified by the half-maximal
ILD, which designates the ILD at which the response
is half-maximal, and the slope of the function. In Figure 7–18E the half-maximal ILD is about -6 dB. In
general, different cells will have different half-maximal ILDs, thereby covering the range of possible
ILDs occurring in natural conditions. There are a
few reports of systematic topographical representation of half-maximal ILDs across one dimension of a
nucleus: cells in the deep and intermediate layers of
the superior colliculus (Wise & Irvine, 1985) and in
the 60 kHz region of the bat IC (Park & Pollak, 1994).
Surprisingly, there are no reports of the receptive
field properties of LSO using free-field stimuli. Tollin
and Yin ( 2002a) studied the receptive field properties
of LSO using virtual space techniques by delivering
the stimuli dichotically but filtering the broad band
noise by the HRTFs of the cat to simulate sounds at
different spatial locations. As expected from the IE
binaural property of LSO cells, the spatial receptive
fields of LSO neurons had peaks in the ipsilateral
sound field where the excitatory ipsilateral input
would be dominant and decreased responses in the
contralateral field. That the response in the contralateral sound field arose from the inhibition from the
contralateral ear was demonstrated by turning off the
input to the contralateral ear (Figure 7–19D), a trivial
procedure using virtual space stimuli but much more
difficult to do in free field.
Because ILDs are an inherent component of
free-field sound stimuli, vary in a systematic fashion
for stimuli in different spatial locations (see Figure
7–11), and strongly modulate the responses of LSO
neurons (see Figure 7–18), it is natural to think that
The Superior Olivary Complex
the shape of the receptive field is determined by the
cell’s ILD sensitivity. Taking advantage of the virtual
space technique, Tollin and Yin ( 2002b) systematically manipulated the three spatial localization cues
of ITDs, ILDs and spectral cues to see which cue was
most important in the shape of the receptive field.
Figure 7–19 shows an example of the manipulations in one LSO neuron. The idea is to vary only
one of the cues while holding the other two cues
constant. For example, Figure 7–19A shows results
that explore the potency of the ITD cue. The curve
labeled “Normal” shows the receptive field of the
neuron when all three cues are varied naturally, that
is, it shows the receptive field of the cell. The curves
labeled Δ-ITD shows responses when the other two
cues were held constant at values corresponding to
the point straight ahead (ILD = 0 and spectral cues
of the straight-ahead position) but ITDs were varied from those values corresponding to -90 deg in
the ipsilateral field to +90 deg in the contralateral
field. The nearly flat line suggests that ITDs by themselves do not modulate the cell’s response. This is
reinforced by the responses in the “0-ITD” condition, where the ITDs were held at 0 and the ILDs and
spectral cues varied normally. The close correspondence of the “Normal” and “0-ITD” curves again
suggest that ITDs are not important parameters in
determining the receptive field response.
Figure 7–19B shows analogous manipulations
of the spectral cues and the responses are similar to
those in Figure 7–19A. These suggest that spectral
cues are also not critical in the normal receptive field
sensitivity of the cell.
Figure 7–19C shows contrasting results when
ILDs are studied. In this case the “Normal” and
“Δ-ILD” responses are nearly identical, suggesting
that ILDs are the key determinant in the normal
receptive field response. This is confirmed by the flat
response in the “0-ILD” curve which shows that the
cell is not modulated by normal variations in ITDs
and spectral cues when ILDs are held at 0. While different LSO cells showed different degrees of modulation with the cue manipulation paradigms shown
in Figure 7–19, for the most part similar responses
were found for all 24 LSO neurons studied. Thus, in
accordance with the classical view, ILDs are by far
the most important factor in shaping the receptive
field profile for most LSO neurons.
179
180
Figure 7–18. Responses of an LSO cell to variations in the ILD of a CF tone. A through D, Dot rasters and PST histograms in response to a 300-msec ipsilateral
tone at 30 dB SPL as a function of the level of a tone at the contralateral ear, as shown in the top right of each panel. The inset in A shows the first 40 msec of the
response to short tone pips at CF presented monaurally to the ipsilateral ear only, demonstrating the characteristic chopping response exhibited by most of our cells
(bin width, 400 μsec and the top tic on the ordinate, 150 spikes). E. Mean discharge rate ±1 SEM versus ILD (in decibels: SPL). (In this and all subsequent figures,
where the error bars are not present, the SEM is less than the height of the data point.) The top abscissa indicates the level of the tone at the contralateral ear, and
the right ordinate shows the rate normalized to the maximum. The dashed horizontal line shows the spontaneous rate of the unit. Reproduced from Tollin and Yin
(2002a) with permission by the Society for Neuroscience via Copyright Clearance Center.
The Superior Olivary Complex
Figure 7–19. Spatial receptive fields in azimuth for an LSO cell (CF = 7.8 kHz) to cue manipulations
of the HRTFs. In all graphs the “Normal” (filled circles) response is that recorded with all localization
cues varied naturally. A. ITD manipulations. Responses obtained when the ITD cue was varied normally
(∆-ITD) while ILD and spectra were kept constant are shown by filled squares, where as responses when
the ITD cue was held constant (0-ITD) are shown by open circles. B. Spectral manipulations. Analogous
manipulations as in A except the spectral cue was manipulated. C. ILD manipulations. Same as in A
except ILD was manipulated. D. Comparison of the “normal” and ipsilateral stimulus alone responses.
Reproduced from Tollin and Yin (2002b) with permission by the Society for Neuroscience via Copyright
Clearance Center.
As LSO is involved in processing predominantly high-frequency sounds and the human auditory system is chiefly low frequency, a legitimate
question is the relative role of the LSO for human
hearing. Anatomical, post-mortem studies of the
human SOC have generally acknowledged the existence of an LSO though diminished relative to the
size of the MSO (Bazwinsky et al., 2003; Moore, 1987;
Strominger, 1978). On the other hand, the existence
of the MNTB has been controversial (Bazwinsky
et al., 2003; Moore, 2000; Richter et al., 1983), which
casts doubt on the importance of the ILD circuit in
the human system (Schwartz, 1992).
Question 2
Is it known how the SOC encodes sound
when a patient wears a cochlear implant or
brainstem implant?
181
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Translational Perspectives in Auditory Neuroscience: Normal Aspects of Hearing
Answer 2
There are no studies examining the response
of SOC neurons to cochlear implant stimulation. However, there are numerous studies
that have recorded from the auditory nerve,
cochlear nucleus, and inferior colliculus to
cochlear implant stimulation. One reason for
the lack of studies in the SOC is that, in general, it is a very difficult site to make singleunit recordings.
On a different note, there is growing
literature in which patients who receive
bilateral cochlear implants are tested with
one vs. two devices, and it looks like most
patients perform significantly better with
two implants than with one. As the SOC is
the first site where the inputs from each ear
converge, it is likely that this effect is mediated through the SOC.
Summary
We have provided a brief summary of the anatomy
and physiology of the cell groups in the SOC. While
most previous studies of the SOC have concentrated
on the binaural processing which is thought to
involve sound localization, the SOC also provides
important feedback pathways to the cochlea by the
olivocochlear systems as well as intrinsic inhibitory
processing networks in the periolivary nuclei.
Further Readings
Irvine, D. R. F. (1986). The auditory brainstem. In D. Ottoson
(Ed.), Progress in sensory physiology (Vol. 7). Berlin, Germany: Springer-Verlag.
Yin, T. C. T. (2002). Neural mechanisms of encoding binaural
localization cues in the auditory brainstem. In D. Oertel,
A. N. Popper, & Fay R. R. (Eds.), Integrative functions in the
mammalian auditory pathway (pp. 99–159). New York. NY:
Springer-Verlag.
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