hillenbrand physiology

Auditory Physiology

The primary aim of this chapter will be to review the physiological mechanisms that are

involved in two basic and extraordinarily important functions of the auditory system: (1)

conversion of the vibratory energy that reaches the ear drum into a series of neural impulses on

the auditory nerve (this is called transduction), and (2) the spectrum analysis function of the

auditory system; that is, the ability of the auditory system to break a complex sound wave into its

individual frequency components.

Before getting into the details, it might be useful to consider some of the fundamental

capabilities of the auditory system which, from any point of view, are nothing short of awe

inspiring. A brief and by no means exhaustive list appears below.

The faintest sound that can be detected by the human ear is so weak that it moves the ear

drum a distance that is equivalent to one-tenth the diameter of a hydrogen molecule. If the

ear were slightly more sensitive we would hear the random particle oscillations known as

Brownian motion.

The most intense sound that can be heard without causing pain is approximately 140 dB

more intense than a barely detectable sound. This means that that the dynamic range of the

ear – the ratio of the most intense sound that can be heard without pain to the intensity of a

barely audible sound – is an astounding 100 trillion to 1.

The frequency range of human hearing runs from approximately 20 Hz to 20,000 Hz, a

range of about 10 octaves.

For signal levels approximating conversational speech, the ear can detect frequency

differences that are on the order of 0.1%, or approximately 1 Hz for a 1,000 Hz test signal

(Wier, Jestaedt, & Green, 1977).

Later in the chapter we will see that the auditory system utilizes an elegant mechanism that

delivers sounds of different frequencies to different physical locations along the cochlea;

i.e., a sound of one frequency will produce the greatest neural activity at one physical

location while a sound of a slightly different frequency will activate a different location.

The difference in frequency that a listener can barely detect corresponds to a difference in

physical location along the cochlea of about 10 microns (1 micron = one millionth of a

meter, or one thousandth of a millimeter). This distance, in turn, is approximately the width

of a single auditory receptor cell (Davis and Silverman, 1970).

Under ideal conditions listeners can detect intensity differences as small as 0.6 dB (Gulick,

Gescheider, and Frisina, 1989).

Listeners can locate the source of a sound based on differences in the time of arrival

between the two ears that are as small as 10 s (i.e., 10 millionths of a second).

Auditory Physiology 2

Further, the anatomy that supports this processing is a miracle of miniaturization. For example,

the middle ear cavity is approximately 3 mm in width and approximately 15 mm in the vertical

dimension (Zemlin, 1968), with roughly the volume of a sugar cube. The cochlea, which

contains the auditory receptors, is even smaller, at approximately 5 mm in height and

approximately 9 mm in diameter at its widest point (Gelfand, 1990).

Overview of the Auditory System

The auditory system can be divided into three major functional subsystems: the conductive

mechanism, the sensorineural mechanism, and the central auditory system (see Figure 4-1).

In terms of anatomical structures, the conductive mechanism consists of the pinna, the ear canal

(also known as the external auditory meatus), the ear drum (also known as the tympanic

membrane), and the middle ear, which contains three very small bones called the auditory

ossicles. The primary function of the conductive mechanism is to transmit the vibrations that are

picked up at the tympanic membrane to the structures of the inner ear, a fluid-filled structure

which contains the auditory receptors. However, as we shall see, the middle ear also

accomplishes a pressure amplification trick which significantly enhances the sensitivity of the

ear.

The sensorineural mechanism consists of the structures of the cochlea and the auditory

nerve, also known as the 8th cranial nerve. The auditory nerve conveys neural impulses

between the cochlea and the brain stem, which is part of the central auditory system. The inner

ear contains specialized sensory receptor cells called hair cells. These cells are responsible for

converting the vibratory energy that enters the auditory system into nerve impulses that are

transmitted to the central nervous system via the auditory nerve. In addition to the conversion of

vibratory energy into neural impulses, the cochlea also carries out a spectrum analysis in which

the low frequency components of the signal are directed to one end of the cochlea and the high-

frequency components are directed to the other end. As will be seen later in this chapter, the

precise role that is played by this frequency analysis is only partially understood.

Figure 4-1. The three functional subdivisions of the auditory system. Reprinted from

Deutsch and Richards (1979).


The electrical signals that are generated by the hair cells in the inner ear are carried by the

auditory nerve to central auditory system, which consists of structures in the brain stem and

auditory cortex. It is often said that the central auditory system is responsible for higher level

functions of auditory analysis, such as the "... recognition, interpretation, and integration of

auditory information ..." (Deutsch & Richards, 1979). There is little question that the central

auditory system is, in fact, heavily involved in higher level functions such as speech recognition

and the ability to recognize familiar voices and familiar melodies. However, the central auditory

system also plays a very important role in relatively low-level aspects of auditory analysis, such

as sound localization, pitch perception and, quite possibly, spectrum analysis.

The Conductive Mechanism

The Outer Ear

The outermost portion of the conductive mechanism is a cartilaginous structure called the

pinna, also known as the auricle (see Figure 4-2). While the approximately funnel shape of the

auricle might lead one to believe that the structure may play some role in sound gathering, this

appears not to be the case (von Bekesy & Rosenblith, 1958). A prominent visual characteristic of

the auricle is the rather convoluted shape consisting of a number of ridges, grooves, and

depressions. It appears that this complex topography, along with other factors, plays some role in

sound localization (von Bekesy & Rosenblith, 1958; Batteau, 1967; Freedman & Fisher, 1968).

Sound is conducted to the tympanic membrane through the external auditory meatus, also

known as the ear canal. The lateral two-thirds of the ear canal is cartilaginous and the medial

third is bone. The general shape of the ear canal

approximates that of a uniform tube, open at the

lateral end and closed medially by the tympanic

membrane. The tube averages approximately 2.3 cm

in length (Wiener & Ross, 1946). Recall that the

resonant frequency pattern of a uniform tube which

is closed at one end (by the ear drum in this case)

can be determined if its length is known. Using the

formula from Chapter 3, the lowest resonant

frequency of the ear canal should be approximately

3800 Hz (F1 = 35,000/(4 . 2.3) = 35,000/9.2 = 3804

Hz). This figure agrees well with experimental data

(Wiener & Ross, 1946; Fleming, 1939), although

estimates vary. This resonance is partially

responsible for the heightened sensitivity of the auditory system to frequencies in the middle

portion of the spectrum, which will be discussed later .

The sound wave that enters the ear canal sets the tympanic membrane into vibration. When

instantaneous air pressure is relatively high (compression), the membrane will be forced inward,

and when instantaneous air pressure is relatively low (rarefaction), the membrane will be forced

outward. Consequently, the inward and outward movements of the tympanic membrane mirror

Figure 4-2. The pinna or auricle. (Reprinted

from Zemlin, 1968)


those of the sound wave that is driving it; for example, if the tympanic membrane is excited by a

500 Hz sinusoid, the tympanic membrane will move inward and outward sinusoidally at 500 Hz.

In general, the instant-to-instant displacements of the tympanic membrane will mirror the

instantaneous air pressure waveform that is driving the membrane.

The Middle Ear

The middle ear or tympanic cavity is an air-filled chamber whose volume approximates

that of a sugar cube (see Figure 4-3). The middle ear communicates with the nasopharynx via the

Eustachian tube. This tube is approximately 35 mm in length in adults and angles downward

and forward to connect the anterior wall of the tympanic cavity with the nasopharynx. The tube

is normally closed, but opens during yawning and swallowing. When the tube opens, air can

travel either into or out of the middle ear to create an equilibrium between the air pressure inside

the tympanic cavity and that of the outside air. The Eustachian tube also plays an important role

in allowing fluids to drain from the middle ear into the nasopharynx.

In terms of the broad overview presented here, the most important structures in the

tympanic cavity are the three ossicles, a series of very small bones referred to collectively as the

ossicular chain (see Figure 4-4). The largest of the ossicles is the malleus, which attaches

directly to the tympanic membrane. The head of the malleus articulates with the incus, which in

turn connects to a very small stirrup-shaped bone called the stapes. The stapes ends in an oval

plate called the footplate. The stapes footplate attaches to an opening into the labyrinth called

the oval window. The labyrinth is a fluid-filled structure that contains the cochlea and the

vestibular system, which is responsible for our sense of balance. The stapes footplate is attached

to the oval window via a circular ligament called the annular ligament. Directly below the oval

Figure 4-3. The ear canal and middle ear cavity. Reprinted from Denes and Pinson, The

Speech Chain, 1993, W.H. Freeman & Co.


window is a second opening into the labyrinth

called the round window. The round window is

covered by a very small membrane called the

internal tympanic membrane.

A reasonable question to ask about the

auditory system is why we have a tympanic

membrane and ossicular chain at all. Since a

primary effect of these structures is to transmit

vibrations to the fluid-filled structures of the inner

ear, then why isn't the oval window simply

covered with a flexible membrane that is driven

directly by the sound wave? Aquatic animals, in

fact, make use of a "direct-drive" system with no

middle ear. A system of this kind would work in

land animals as well, but for reasons that are

explained below, a substantial loss of energy

would result. The key to understanding the role

that is played by the tympanic membrane and ossicular chain is to appreciate the energy loss that

occurs when a sound wave is transmitted from the air medium in which the sound is initially

generated to the fluid medium that exists inside the inner ear.

We know from everyday experience that we do not hear airborne sound very well when we

are underwater. The primary reason for this is that there exists an impedance mismatch between

the air medium in which the airborne sound is initially generated and the fluid medium into

which the vibratory distrubance must be transmitted in order for our underwater listener to hear

the sound. Impedance is the total opposition to the flow of energy,1 and the mismatch results

from the fact that air is a low-impedance medium while water (and other similar fluids) is a high-

impedance medium. These differences in impedance can be demonstrated simply by running a

cupped hand through air and water. There is a general rule that states that energy is reflected

back toward the source when a signal reaches the boundary between two media whose

impedances do not match. In the case of air and fluid, the impedance mismatch is quite large, and

when the signal reaches the air-fluid boundary, only 1/1,000th of the energy is absorbed into the

fluid medium, with the remainder being reflected back toward the source. Represented on a

decibel scale, the loss of signal intensity is 30 dB. In the formula below, the signal intensity on

the airborne side of the air-fluid boundary serves as the reference intensity, and the signal

intensity on the fluid side of the boundary serves as the measured intensity.

1

Impedance consists of three distinct components: resistance, capacitive reactance (also known as compliant reactance), and mass

reactance (also known as inductive reactance or inertive reactance). Resistance is simply the dissipation of energy due to friction. When the

head of a thumb tack is rubbed back and forth on the surface of a table, the tack heats up because of the friction of the two surfaces. Capacitive

reactance is opposition that is offered due to the elastic properties of an object. For example, when you push against a spring, compressing it beyond its resting state, the spring generates a force that opposes the applied force. The same kind of opposition to an applied force occurs when

a spring is stretched beyond its resting state. Mass reactance is opposition due to the inertial properties of objects; that is, the tendency of a resting

object to remain at rest, and the tendency of a moving object to remain in motion. Impedance is the vector sum of resistance, capacitive reactance,

and mass reactance, with vector sum simply indicating that these three quantities need to be added using the Pythagorean theorem.

Figure 4-4. The auditory ossicles. (From Yost and

Nielson, 1985).


dB = 10 log10

Im/Ir

= 10 log10

1/1,000

= 10 (-3)

= -30 dB

The negative sign here simply means that the signal will be 30 dB weaker on the fluid side of the

boundary. Consequently, if the airborne sound wave were to directly drive a simple membrane

covering the oval window, a 30 dB loss in signal intensity would occur at the air-fluid boundary.

This is not a minor loss of energy. As we will see in the chapter on auditory perception, a 10 dB

decrease in intensity corresponds to a decrease of approximately one-half in our subjective

impression of loudness. This means that a 50 dB signal, for example, sounds only one-eighth as

loud as an 80 dB signal.

One of the primary functions of the middle ear is to amplify pressure so as to overcome a

large portion of this energy loss. This is accomplished in two ways: (1) an increase in pressure

that occurs when the vibrations that are picked up on the relatively large surface area of the

tympanic membrane are focused on the very small surface area of the stapes footplate, and (2) an

increase in force (and therefore pressure as well) that occurs as a result of the mechanical lever

action of the ossicular chain. The "area trick," known as the condensation effect, is by far the

more important of the two effects. Recall from Chapter 2 that there is an important distinction

between force and pressure: force is the amount of push or pull on an object, and is the product

of mass and acceleration; pressure, on the other hand, is force per unit area. A major implication

of this relationship is that pressure can be amplified without a change in force simply by

decreasing the area over which the force is delivered. This is the design principle underlying

thumb tacks and knives with sharp cutting edges, and exactly this principle is at work in the

middle ear as the energy that is delivered to the relatively large area of the tympanic membrane

is focused on the very small area at the stapes footplate. The amount of pressure amplification

that results from this concentration of force is proportional to the ratio of the two areas that are

involved. The effective area of the tympanic membrane is approximately 0.594 cm2, while the

area of the stapes footplate is approximately 0.032 cm2 (Durrant & Lovrinic, 1984).

Consequently, pressure at the stapes footplate will be approximately 18.6 times greater than

pressure at the tympanic membrane (0.594/0.032 = 18.6). This pressure amplification can be

represented on a decibel scale. Since we are talking about an increase in pressure, the pressure

version of the decibel formula is needed:

dB = 20 log10

(0.594/0.032)

= 20 log10

(18.6)

= 20 (1.27)

= 25.4 dB

Consequently, of the 30 dB that would be lost at the air-fluid boundary, the condensation effect

makes up for roughly 25 dB.

A small amount of additional amplification results from the lever action of the ossicular

chain. The basic idea is that the ossicular chain is suspended by ligaments in such a way as to


form a lever system, with the fulcrum on

the body of the incus. One arm of the

lever system consists of the malleus

while the other arm consists of the incus

(see Figure 4-5). The malleus lever arm

is approximately 30% longer than the

incus lever arm, producing a lever ratio

of 1.3:1. Since the force amplification

that occurs in any lever system is

proportional to the ratio of the lengths of

the two lever arms, force will be

amplified by a factor of 1.3. Pressure is

the force per unit area, so this increase in

force means that pressure will also be

amplified by a factor of 1.3. Represented

on a decibel scale, this amounts to:

dB = 20 log10

(1.3)

= 20 (0.11)

= 2.3 dB

(Notice that the pressure version of the decibel formula is being used here rather than the

intensity version. That is because the lever advantage produces an increase in force and,

therefore, pressure.) If this 2.3 dB pressure amplification is added to the 25.4 dB that is produced

by the condensation effect, we find that the combined action of the middle ear system results in a

pressure amplification of 25.4+2.3 = 27.7 dB, nearly all of the 30 dB that would otherwise be

lost at the air-fluid boundary.

The Sensorineural Mechanism

The two major auditory structures of the sensorineural mechanism are the cochlea and the

auditory nerve. The cochlea is one portion of a larger structure called the labyrinth. As noted

earlier, the labyrinth contains both the cochlea (the organ of hearing) and the vestibular system

(the organ of balance). The three major divisions of the labyrinth are shown in Figure 4-6. The

snail-shaped portion of the labyrinth is the cochlea, which contains the hair cells and many other

structures that are important for hearing. The upper portion of the labyrinth contains three

structures called the semicircular canals, which are part of the vestibular system. The middle

portion of the labyrinth is called the vestibule. The oval window and round window are openings

into the vestibule.

The portion of the labyrinth that is shown in panel a of Figure 4-7 is a hollowed-out and

fluid-filled bony shell called the bony or osseous labyrinth. Fully contained within the bony

labyrinth is a fluid-filled structure called the membranous labyrinth, which can be thought of

as something like a convoluted water balloon that fits inside the bony labyrinth (see panel b of

Figure 4-7). The fluid that courses through the membranous labyrinth is called endolymph and

the fluid outside the membranous labyrinth is called perilymph. Two bulges in the membranous

Figure 4-5. The mechanical lever advantage of the ossicular

chain. Adapted from Denes and Pinson, The Speech Chain,

1993, W.H. Freeman & Co.


labyrinth called the utricle and saccule are part of the vestibular system. The portion of the

membranous labyrinth that is contained within the cochlea is called the cochlear duct. The end

of the cochlea that is closest to the vestibule is called the base or basal end, and the end that is

furthest from the vestibule is called the apex or apical end. The cochlea is divided into three

canals or scalae: the scala vestibuli, which lies above the cochlear duct, the scala tympani,

which lies below the cochlear duct, and the cochlear duct itself, which is also known as the scala

media. The three canals are shown in highly schematic form in a partially unrolled cochlea in

Figure 4-8. A small gap at the apical end of the cochlea called the helicotrema allows the

perilymph in the scala vestibuli and the scala tympani to communicate.

Anatomy of the Cochlea

Some of the views that are shown of the cochlea can be a bit difficult to interpret simply

because of the coiled shape. Since the coiling is strictly a space-saving feature that has

essentially no effect on cochlear physiology, the cochlea is often shown in unrolled form. Panels

a and b of Figure 4-9 show views that result from two kinds of cuts through an unrolled cochlea.

Panel c shows a highly schematic picture of what the view would look like if a cut were made

through the cochlea in its coiled-up form.

A more detailed picture of the view in panel c can be seen in Figure 4-10. Shown in this

figure are the basal, medial, and apical turns of the cochlea, which are wrapped around a bony

core called the modiolus. We can imagine building a structure similar to the cochlear portion of

Figure 4-6. The labyrinth. From Zemlin (1968).

Figure 4-7. The bony labyrinth (panel a) and the

membranous labyrinth (the unshaded portion of panel b).

Reprinted from Minifie, Hixon, and Williams (1973).


the labyrinth by coiling a length of garden hose approximately 2 3/4 turns around wet plaster,

and then allowing the plaster to dry. The plaster is analogous to the modiolus, and the garden

hose is the cochlea. Entering through a tunnel in the modiolus is the cochlear branch of the

auditory nerve. The vestibular branch of the 8th cranial nerve, which is not shown in this figure,

Figure 4-8. Schematic of a partially unrolled cochlea

showing the scala vestibuli, the scala media, and the scala

tympani. Adapted from Zemlin (1968).

Figure 4-9 Cuts through an unrolled (panels a and b) and

rolled (panel c) cochlea. Reprinted from Deutsch and

Richards (1979).

Figure 4-10. The cochlea, modiolus, and auditory nerve.

Reprinted from Deutsch and Richards (1979).

Figure 4-11. A cross-section of the cochlea. Reprinted from

Stevens (1951).


innervates sensory receptors in the vestibular system. Figure 4-11 shows a detailed view of a

single cross-section through the cochlea, corresponding to the cut shown in panel b of Figure 4-

9. Fibers from the auditory nerve enter the cochlear duct through a tunnel in a thin shelf of bone

called the spiral lamina. The opening in the spiral lamina through which the auditory nerve

fibers enter is called the habenula perforata. The spiral lamina is covered with a layer of

fibrous tissue called the limbus. As Figure 4-10 shows, the cochlear duct is a triangular-shaped

partition of the cochlea that is formed by two membranes: Reisner's membrane, which

separates the cochlear duct from the scala vestibuli, and the basilar membrane, which separates

the cochlear duct from the scala tympani. The basilar membrane is held in place by the spiral

ligament. Covering the spiral ligament in the scala media is a layer of endolymph-secreting

vascular tissue called the stria vascularis.

The set of structures that are resting on the basilar membrane are referred to collectively as

the organ of Corti. A more detailed look at the organ of Corti is shown in Figure 4-12.

Emerging from the limbus and lying immediately above the hair cells is a gelatinous membrane

called the tectorial membrane. The hair cells are arranged in rows consisting of a single inner

hair cell (IHC) and either three or four outer hair cells (OHC), with three OHCs being more

common. The hair-like structures emerging from the tops of the hair cells are called cilia. The

structure and function of hair cells will be discussed later in this chapter. The human cochlea

contains approximately 3,000 - 3,500 arrangements such as those shown in Figure 4-12,

consisting of approximately 3,000 - 3,500 IHCs and approximately 10,000 - 12,000 OHCs. In

later discussions we will refer to this unit consisting of one IHC and three or four OHCs as a

channel. The hair cells are innervated by approximately 30,000 auditory nerve fibers (Spoendlin,

1989), which connect to the base of the hair cells. The overwhelming majority (~98%) of these

auditory nerve fibers are afferent, i.e., conveying neural impulses away from the hair cells in the

direction of the central nervous system. In turn, the overwhelming majority (~95%) of these

afferent fibers are connected to the IHCs as opposed to the OHCs, meaning that it is almost

exclusively the IHCs that are responsible for conveying sensory information to the central

nervous system (Spoendlin, 1974). A rough estimate is that there are approximately 10 auditory

nerve fibers connected to each IHC. Individual auditory nerve fibers that innervate IHCs

typically supply a single IHC, rather than sprouting branches to many other IHCs. Exactly the

opposite is true of fibers that innervate OHCs, where a single nerve fiber branches to innervate

many OHCs. These differences in innervation patterns are shown in Figure 4-13.

As will be seen below, the hair cells generate an electrical signal in response to the

traveling wave motion of the basilar membrane. These electrical disturbances in turn cause

depolarization of the auditory nerve fibers that are attached at the base of the hair cells. The

physiology of nerve fibers and the precise meaning of the term depolarization will be explained

later in this chapter. For the time being, it is necessary only to understand that the ultimate result

of action of the organ of Corti is the generation of an electrical spike on the auditory nerve fibers

that innervate the hair cells. The nature of the basilar membrane traveling wave and the

mechanisms that are thought to be involved in the generation of the electrical disturbance in the

hair cells will be described below.


Figure 4-12. A cross-section of the cochlea. Reprinted from

Stevens (1951).

Figure 4-13. Innervation patterns for inner and outer hair cells.

Note that a single IHC is typically innervated by many nerve

fibers, while individual nerve fibers innervating OHCs typically

branch to supply several receptor cells. After Spoendlin (1979).

[check this citation]

Figure 4-15. The basilar membrane varies continuously in

stiffness from base to apex. The greater stiffness of the

membrane at the base makes the basal end respond better to

high frequencies than low frequencies, while the opposite is true

of the apical end. After von Bekesy (1960), Rhode (1973), and

Durrant & Lovrinic (1984).

Figure 4-14. The cochlear duct is formed by two membranes:

Reisner's membrane above, and the basilar membrane below. In

this simplified drawing the duct is represented as a single

structure called the cochlear partition. Inward movement of

the stapes causes a downward deflection of the cochlear

partition, and the fluid pressure is resolved by an outward

deformation at the round window. Outward motion of the stapes

has the opposite effect: the partition is deflected upward, and

the fluid pressure is resolved by an inward deformation at the

round window. Based on von Bekesy (1960) and reprinted from

Durrant and Lovrinic (1984).


The Traveling Wave

Figure 4-14 shows a simplified view of an uncoiled cochlea. The cochlear duct in this

figure has been greatly simplified and is represented as though it were a single membrane,

attached on either side and running from the base to the helicotrema. We know, of course, that

the cochlear duct is formed by two membranes: Reisner's membrane above and the basilar

membrane below. These two membranes are often referred to collectively as the cochlear

partition, and for the purposes of understanding the movement dynamics of this system we can

consider the partition as consisting of just a single membrane. Further it is primarily the

mechanical properties of the basilar membrane that control the most important movement

characteristics of the cochlear partition. The single most important fact about the basilar

membrane is that its stiffness varies systematically from the base to the apex (see Figure 4-15).

Specifically, the basilar membrane is stiffer at the base than the apex. Recall from our discussion

of spring-and-mass systems in chapter 3 that natural vibrating frequency varies in direct

proportion to stiffness; i.e., as stiffness increases, natural vibrating frequency increases. This

means that the basal end of the basilar membrane, which is stiff, will respond best to high

frequencies, and the apical end, which less stiff, will respond best to low frequencies.

When an acoustic stimulus is delivered to the ear, the vibratory pattern is picked up at the

tympanic membrane and transmitted through the ossicles, resulting in inward and outward

movements at the stapes footplate. As shown in Figure 4-14, the inward pressure of the stapes on

the incompressible cochlear fluid causes the cochlear partition to deflect in the direction of the

scala tympani. This fluid pressure is resolved by an outward deflection of the internal tympanic

membrane, which covers the round window. Similarly, during a rarefaction phase the outward

motion of the stapes will cause the cochlear partition to deflect in the direction of the scala

vestibuli, pulling the internal tympanic membrane inward. These upward and downward

Figure 4-16. The basilar membrane traveling wave. Panel a shows a sequence of snapshots of the traveling

wave (reprinted from Ranke, 1942). Panel b shows a single snapshot of the traveling wave (reprinted from

Tonndorf, 1960).


deflections of the cochlear partition result in the generation of a displacement pattern with a

highly specific shape called a traveling wave. The basilar membrane traveling wave was

discovered in a series of ingenious experiments by Georg von Bekesy, which earned him the

Nobel Prize for Physiology and Medicine. As shown in Figure 4-16, the traveling wave moves

from the base toward the apex, with the amplitude rising rather gradually to a peak, and then

decaying rather suddenly after reaching a peak. Panel a shows what a sequence of snapshots of

the traveling wave might look like. The smooth curve in panel a is the envelope or amplitude

envelope of the traveling wave. A more detailed view of a single snapshot of the traveling wave

pattern is shown in panel b of Figure 4-16. As shown in Figure 4-15, the point along the basilar

membrane where the traveling wave reaches its maximum amplitude will be strongly affected by

the frequency of the input signal: high frequency signals will reach peak amplitude near the

basal end of the cochlea, where the basilar membrane is stiffer, while low frequency signals will

reach peak amplitude near the apical end of the cochlea, where the basilar membrane is less

stiff. What this means is that low-frequency signals will be directed toward the apical end of the

basilar membrane, high- frequency signals will be directed toward the basal end of the basilar

membrane, and mid-frequency signals will be directed toward an appropriate place in the middle

of the basilar membrane. As will be seen below, this frequency-dependent behavior of the basilar

membrane traveling wave will be reflected in the pattern of 8th-nerve electrical activity; that is,

for low-frequency signals, 8th-nerve electrical activity will be greatest for fibers connected to

hair cells at the apical end of the cochlea, while for high-frequency signals, 8th-nerve electrical

activity will be greatest for fibers connected to hair cells at the basal end of the cochlea. This

relationship between the frequency of the input signal and the point of maximum basilar

membrane motion is one of the most important properties of cochlear analysis, and it is the key

to understanding what has been called the place theory or the rate-place model of auditory

spectrum analysis, which will be discussed later in this chapter.

Figure 4-17. The upward and downward movement of the basilar membrane produces a shearing force on

the hair cell cilia, causing them to pivot at their base. Reprinted from Ryan and Davis (1976).


Figure 4-18. A hair cell. Note that the cilia are arranged

according to height and interconnected by fine filaments

called transduction links. Adapted from Hudspeth (1994).

Figure 4-19. Transmission electron micrograph of a longitudinal

section of outer hair cells. Reprinted from Kimura (1966).

There is one additional fact about basilar membrane motion that is necessary for

understanding how the sensorineural system converts vibration into neural impulses. As shown

in Figure 4-17, the upward and downward movement of the basilar membrane produces

something called a shearing force on the hair cell cilia that results in the side-to-side movement

of the cilia. In other words, as the basilar membrane vibrates up and down, the cilia are

alternately forced away from and then toward the spiral lamina.2 As explained below, it is this

movement of the cilia that produces excitation of the hair cells which, in turn, results in the

depolarization of the auditory nerve fibers that innervate the hair cells.

Hair-Cell Transduction

All sensory receptors are examples of a general class of device called transducers. In all

cases the function of a transducer is to convert energy of one form into energy of a different

form. Common examples of transducers include microphones, which convert acoustic energy

2

The mechanism of cilia motion that is shown in Figure 4-17 is the most widely accepted view. As simple and intuitive as this model might

seem, it may well be incorrect. The motion pattern shown in Figure 4-17 will have to suffice for the relatively cursory review presented here. For

our purposes the important point is that movement of the hair cell cilia occurs as a direct result of the movement of the basilar membrane. This

much is well established, although the detailed mechanism is not well understood. See Gelfand (1990) and Zwislocki (1984, 1985, 1986) for a discussion of the potential problems with the view presented in Figure 4-17.


into electrical energy, and loudspeakers, which perform precisely the opposite type of

transduction, converting the electrical energy coming from an amplifier into acoustic energy. In

the case of sensory receptors, the job is to convert stimulation of various sorts into an electro-

chemical code consisting of a sequence of neural impulses. In the visual system the incoming

optical stimulus is converted by the rods and cones of the retina into a series of neural impulses

on the optic nerve that are interpreted by the brain as a visual image. In the auditory system, the

type of transduction that takes place involves the conversion of the mechanical vibration that

reaches the basilar membrane into a series of impulses on the auditory nerve.

While there are many aspects of auditory transduction that remain poorly understood, there

is complete agreement that the site of transduction is the hair cell, which generates an electrical

potential that stimulates impulses in the 8th-nerve fibers that are connected to its base. The chain

of events, which will be described below, includes the following: (1) the vibration of the basilar

membrane causes the hair-cell cilia to bend at their base, (2) this "shearing" of the cilia results in

the flow of electrical current through the hair cell that is called the receptor current, (3) the

receptor current stimulates the release by the hair cell of neurotransmitter chemicals, and (4)

uptake of this neurotransmitter substance by dendrites in an 8th fiber connected to the base of the

hair cell stimulates an all-or-none action potential in the nerve fiber.

A schematic drawing of a single hair cell is shown in Figure 4-18. In close proximity to the

base of the hair cell are auditory nerve fibers.3 The cilia projecting from the top of the hair cell

serve a crucial function in transduction. Note that the cilia are arranged according to height, with

the shortest cilia being closest to the spiral lamina. This feature can be seen clearly in the

electron micrograph shown in Figure 4-19. Also shown in the schematic drawing in Figure 4-18

is a series of very thin filaments called transduction links that serve to attach the adjacent cilia

of differing heights. The cilia themselves are exceedingly stiff and are effectively hinged at their

base. As a result, the application of a force to the hair bundle causes the cilia to pivot at their

base rather than bow. Figure 4-21 shows the position of the cilia at rest (panel a), and after the

application of a force either in the direction of the tall cilia (panel b), or in the direction of the

short cilia (panel c). For reasons that are explained below, it is the cilia motion pattern shown in

panel b, in response to the movement of the basilar membrane, which is ultimately responsible

for the stimulation of the 8th nerve fiber.

To see how the transduction process occurs it is necessary to understand two important

electrical potentials that exist within the cochlea. An electrode inserted into the body of the hair

cell will record a negative voltage of approximately -60 millivolts (mV), while an electrode

inserted into the endolymphatic fluid in the scala media (which is electrically separated from the

hair cell body) will record a positive voltage of approximately +80 mV. Consequently, the

difference in electrical potential between the hair cell body and the endolymphatic fluid that lies

outside of the cell body is approximately 140 mV. As will be seen below, this difference in

electrical potential serves as a biological battery that supplies the energy source for the

generation of the receptor current.

3

The single afferent fiber and single efferent fiber that are shown in Figure 4-18 should not be taken too seriously. Recall that: (a) the typical

IHC is innervated by several afferent fibers, (b) the great majority of afferent fibers innervate IHCs rather than OHCs, and (c) only about 2% of all fibers innervating hair cells are efferent.


Figure 4-21. Hair cell cilia: (a) at rest, (b) being displaced in the

direction of the tall hairs (i.e., away from the modiolus), and (c)

being displaced in the direction of the short hairs (i.e., toward the

modiolus).

Figure 4-23. Model of hair cell transduction proposed by

Pickles (1984) and Hudspeth (1985). Adapted from

Hudspeth (1994).

Figure 4-22. Davis' model of hair cell function. Reprinted

from Davis (1965).

Figure 4-20. A simple electrical circuit consisting of a

battery in series with a variable resistor and a current meter.


The theory of hair cell function that has enjoyed the widest acceptance is a surprisingly

straightforward model (at least in broad strokes) that was proposed a number of years ago by

Davis (1965), although many important details of hair cell transduction have only been

uncovered within the last few years. To understand how the Davis model works, consider the

simple electrical circuit in Figure 4-20. The circuit consists of a battery connected in series with

a device called a variable resistor (also known as a rheostat). The meter has been placed in the

circuit simply to record how much electrical current is flowing. A variable resistor is simply an

electrical resistor whose resistance value can be varied. Volume control dials on devices such as

televisions and radios are variable resistors, as are the dimmer dials that are often found in dining

rooms. Turning the volume down is a matter of setting the dial on the variable resistor to a high

resistance position, limiting the flow of electrical current to a small value. In our simple circuit,

this high resistance value would be reflected by a very small deflection on the current meter. On

the other hand, turning the volume up involves setting the dial on the variable resistor to a low

resistance position, resulting in a large flow of electrical current and, consequently, the current

meter would show a large deflection. The battery in this simple circuit corresponds to the

roughly 140 mV difference in electrical potential between the hair cell body and the endolymph.

According to Davis, the hair cell cilia behave like variable resistors whose resistance values

change as they pivot at their base. These changes in electrical resistance modulate the flow of

ions between the endolymphatic fluid and the hair cell. (An ion is an atom with either a surplus

of electrons, giving it a negative charge, or a deficit of electrons, giving it a positive charge.) A

drop in resistance is accompanied by the flow of electrical current, and this current flow is the

receptor current.

It is now known that the specific type of cilia motion that produces the required resistance

drop is movement in the direction of the taller cilia; that is, the kind of motion that is depicted in

panel b of Figure 4-20. Electrical resistance offered by the cilia when they are standing straight

up (Figure 4-20, panel a) is very high and becomes even higher when the cilia are sheared in the

direction of the shorter cilia (Figure 4-20 panel c), resulting in inhibition of the receptor current

rather than excitation. A more complex version of the electrical circuit envisioned by Davis is

shown in Figure 4-22.

A theory proposed by Pickles et al. (1984) and Hudspeth (1985) attempts to explain why

this change in electrical resistance occurs when the hair bundle pivots in the direction of the

taller cilia. A schematic of the model is shown in Figure 4-23. Recall that very fine filaments

called transduction links connect adjacent cilia of different heights. According to this "gate-

spring" model, movement of the hair bundle in the direction of the taller cilia has the effect of

stretching these transduction links, while movement of the hair bundle in the direction of the

shorter cilia has the effect of compressing the transduction links (see Figure 4-23). As seen in the

figure, stretching the spring-like transduction links has the effect of opening a pore or "molecular

gate," allowing ions to flow. On the other hand, movement in the direction of the shorter cilia,

which compresses transduction links, has the effect of squeezing the molecular gate closed,

inhibiting the flow of ions. As a result, the receptor current tends to be generated primarily

during that half of each cycle of vibration that results in movement of the hair bundle in the

direction of the taller cilia.


To complete the transduction story, it is necessary to note that the receptor current (i.e., the

electrical current that flows through the hair cell) stimulates the release by the hair cell of

neurotransmitter chemicals which, in turn, stimulates the depolarization of the auditory nerve

fiber. Although the causal link between these two events is well established, the precise

mechanism that relates the generation of the receptor to the release of neurotransmitter substance

is currently not well understood.

A crucial fact about the nerve-stimulating electrical disturbance that is generated by the

hair cell is that it is a graded signal. This means that the instantaneous amplitude of the hair cell

current varies continuously depending on the instantaneous amplitude of the shearing force that

is applied to the hair bundle (which, in turn, varies continuously depending on the amplitude of

the basilar membrane traveling wave). To say that the receptor current varies continuously with

the amplitude of the shearing force simply means that when the shearing force is low the receptor

current will be low, when the shearing force is large the receptor current will be high, and when

the shearing force is intermediate in size the receptor current will be intermediate. Figure 4-24 is

an idealized representation showing how the receptor current varies over time for two input

signals. The main point to be made about this figure is that the changes over time in receptor

current faithfully model the shape of the input signal, with one critical exception: since the hair

cell is stimulated to generate a receptor by shearing of the cilia in one direction only, the "bottom

half" of the signal is missing. The name that is given to this process in which only one polarity of

a signal is preserved is halfwave rectification. The main point, then, is that the hair cell receptor

faithfully models a halfwave rectified version of the input signal (though with some restrictions,

which will not be discussed here).

The graded nature of the receptor stands in contrast to the all-or-none nature of the

electrical potential that is generated by the auditory nerve fiber. As will be seen, this graded,

continuously varying receptor current will be translated by the auditory nerve into a sequence of

Input Signal

Receptor Current

Input Signal

Receptor Current

Figure 4-24. Relationship between the receptor potential generated by the hair cells and the input signal.

The receptor potential is a graded response that preserves the shape of the input signal, except that it is

halfwave rectified.


discrete on-off pulses called action potentials. The mechanism involved in the generation of

these action potentials on the auditory nerve will be described below.

Nerve Impulses

Neurons are highly specialized cells that form the basic building blocks of the nervous

system. The human brain contains approximately 10 billion neurons. Neurons can vary

considerably in their detailed structure, but all neurons share a common architecture, which is

illustrated in Figure 4-25. The portion of the neuron containing the nucleus is called the cell

body. The long projection extending from the cell body, called the axon, carries electrochemical

information away from the cell body. Axons terminate in branch-like endings called nerve

endings. Axon lengths can vary considerably from one neuron to the next, with the longest

axons extending a meter or more. The bushy endings on the other side of the cell body are called

dendrites; these extensions convey electrochemical information in the direction of the cell body.

The microscopic spaces that exist between the nerve endings of an axon and the dendrites of an

adjacent neuron are called synapses.

Effector Cells and Receptor Cells

Neurons communicate not only with other neurons, but also with two other kinds of

specialized cells: effector cells and receptor cells. A common example of an effector cell is a

muscle fiber, which receives its stimulus to contract from a neuron. Receptor cells, on the other

hand, receive sensory information from stimuli such as light, sound, and touch, and convey this

information to adjacent sensory neurons. In the auditory system, hair cells serve as receptor cells,

and the neurons that convey information from the hair cells to the central nervous system are

auditory nerve fibers.

Figure 4-25. The dendrites of one neuron synapsing with the axon of an adjacent neuron . Reprinted from

Denes and Pinson, The Speech Chain, 1993, W.H. Freeman & Co.


Generation of an Action Potential

The electrochemical signal that is generated by a neuron is called an action potential. The

energy source that supplies the power for the generation of an action potential is a difference in

electrical charge between the cytoplasm inside the neuron and the extracellular fluid that lies

outside of the cell membrane. If one electrode is placed inside the cell membrane of a neuron in

its resting state and a second electrode is placed in the extracellular fluid just outside of the cell

membrane, a voltmeter will show an electrical potential of about -50 mV, with the cell body

being negative with respect to the extracellular fluid (see Figure 4-26, panel a). The difference in

charge exists because of unequal concentrations of positively and negatively charged ions within

the cell as compared to the extracellular fluid. The neuron in this state is said to be polarized,

and the difference in charge can be thought of as constituting a biological battery in the same

sense as the electrical potential that serves as the energy source for the generation of the receptor

potential in the Davis hair cell model.

There are several different kinds of events that can stimulate the depolarization of a neuron,

resulting in the propagation of an action potential along the axon. The most important of these

events is the uptake of neurotransmitter chemicals by the dendrites of the neuron. These

neurotransmitter chemicals are released either by an adjacent neuron or an adjacent receptor cell,

such as a hair cell. Depolarization of the neuron begins with an increase in the permeability of

the cell membrane, allowing positively charged ions to enter the cell and negatively charged ions

to exit. The result is a very rapid change in the electrical potential of the cell. Panel b of Figure 4-

26 shows the electrical state of a neuron at a particular location where the depolarization

disturbance has reached.

An imperfect but useful analogy can be drawn between the propagation of an action

potential on an axon and the combustion that propagates along the length of a fuse. The analogy

is useful in making three important points about the propagation of an action potential. First, the

event is a self-sustaining chain reaction. In the case of the fuse, the combustion in one local area

Figure 4-26. Propagation of an action potential along a nerve fiber.


of the fuse causes an adjacent area to burn, and in the case of the action potential, it is the local

electrochemical disturbance that spreads to adjoining regions of the axon. Second, the energy

that supports the propagation of the action potential comes from the fiber itself, and not the

stimulating event, just as the energy that is responsible for the propagation of combustion along a

fuse comes from the fuse and not the match that was used to light the fuse. Finally, combustion

along a fuse is an all-or-none event, meaning that the fuse will either burn or fail to burn, and the

amount of heat that is generated along the fuse will not be graded depending on the size of the

match that was used to light it. This all-or-none law is one of the most fundamental and

important properties of neural coding: the neuron either depolarizes or it does not, and the

amplitude of the action potential is not graded according to the amplitude of the stimulating

event. In relation to the transduction process. This means that the graded receptor potential

generated by the hair cell will be translated not into a correspondingly graded neural event, but

into a discrete, all-or-none action potential on the auditory nerve.

Figure 4-27 shows what a typical action potential looks like. Action potentials are measured

by placing a very small recording electrode inside the membrane of an axon. Consequently, the

graph shows the changes that occur over time in the electrical potential within the cell at one

particular location on the axon. The same pattern is repeated at different points in time as the

disturbance propagates along the axon. The graph begins at the approximately -50 mV resting

potential of the neuron. The very rapid swing to about +40 mV occurs when the cell membrane

permeability increases, allowing positive ions to enter. This rapid swing from about -50 mV to

about +40 mV occurs over a brief interval of approximately 0.5 ms, and this portion of the action

potential is called the spike potential. An active process within the cell rapidly repolarizes the

neuron by pumping positive ions out through the cell membrane and, if the neuron remains

undisturbed, the electrical potential eventually returns to the resting potential of about -50 mV.

Figure 4-27. Changes in voltage over time in an action potential.


Absolute and Relative Refractory Periods

There is one crucial aspect of the fuse analogy that does not apply to neurons: once a fuse

burns it cannot be relit. Neurons, on the other hand, repolarize shortly after generating an action

potential and can be stimulated to fire again. However, if the stimulating event occurs less than

about 1 ms after the generation of a spike potential, the fiber will not fire, no matter how strong

the stimulus. This interval of approximately 1 ms is called the absolute refractory period, and it

simply means that spike potentials cannot occur more frequently than about once every

millisecond. This corresponds to a frequency of 1/1,000 s = 1,000 spikes per second, or 1,000

Hz. Following the absolute refractory interval is a longer interval of about 1-10 ms that is called

the relative refractory period. A neuron can fire during the relative refractory period, but the

threshold for stimulating the neuron is elevated. For example, at 2 ms following a neural spike

the neuron is capable of firing again since the absolute refractory period has been exceeded;

however, since the threshold is elevated a relatively strong stimulus is required. It is important to

appreciate that the firing of neurons is a probabilistic event, meaning that it has a random rather

than deterministic character. The probability of a second firing increases with either: (a)

increases in the amplitude of the stimulating event (i.e., the neuron is more likely to fire when

strongly stimulated), and (b) increases in the time that elapses since the previous spike potential

(i.e., the neuron is more likely to fire if a long interval has elapsed since the previous spike

potential). As we will see later in this chapter, the concepts of refractory periods and the

probabilistic nature of neural firing patterns have important implications for neural coding of

sound.

Excitation versus Inhibition

When a neural spike arrives at a nerve ending, neurotransmitters are released into the

synaptic space where they are taken up by the dendrites of adjoining neurons. To this point we

have been speaking as though the release of neurotransmitters at synaptic junctures always had

the effect of stimulating an action potential. However, synaptic junctures may be either

excitatory – increasing the likelihood of an action potential in an adjoining neuron, or

inhibitory –- decreasing the likelihood of an action potential in an adjoining neuron. These

inhibitory connections are quite important and play a central role in a class of contrast-enhancing

phenomena called lateral suppression or lateral inhibition, which we will not be discussing in

this text. [Omit this? if not, at least give a citation]

Signal Coding on the Auditory Nerve

Sensory Nerves as Encoders

We have seen that the receptor potential that is generated by the hair cells is a graded or

continuously varying signal that is a faithful model of the input signal, with the important

exception that it is halfwave rectified; that is, the "bottom half" of the signal is not represented

since the hair cells are excited by cilia shearing in one direction only (see Figure 4-24). In fact,

the signal exists in graded or continuous form at all points up to and including the hair cell

potential: (a) as continuous variations in instantaneous air pressure over time prior to the

tympanic membrane, (b) as continuous variations in instantaneous displacement over time all the


way from the tympanic membrane to the basilar membrane, and (c) as continuous variations in

instantaneous voltage over time at the hair cell. The electrical signals on the auditory nerve,

however, have a very different character since auditory nerve fibers carry a sequence of all-or-

none on-off pulses. [a figure is needed here - see parkins-houde paper]

The importance of this difference between the graded receptor potential and the discrete

on-off pulses on the auditory nerve can not be overestimated. What this means is that the

auditory nerve cannot represent the input signal in a completely straightforward way; for

example, the all-or-none law means that the auditory nerve cannot simply generate weak pulses

when the receptor potential is weak and strong pulses when the receptor potential is strong. The

auditory nerve must find some way to encode the receptor potentials generated at various places

along the basilar membrane that can be carried out with on-off pulses.

The key word here is encode, and to understand the nature of this encoding process and, in

fact, the basic structure of all encoding operations, it might be helpful to consider the kind of

encoding that occurs in the transmission of messages using Morse Code. In Morse Code the units

that must be encoded are letters and a few control characters such as STOP. This is accomplished

by assigning a code to each character consisting of a unique sequence of long and short electrical

pulses. Imagine a device consisting of an optical scanner, software that would recognize the

characters on a page of text, and an encoding circuit that would produce the appropriate sequence

of long and short electrical pulses for each character. The main point is that the device has done

more than simply convert from optical energy to electrical energy; it has translated or encoded

the message into an entirely different kind of language; that is, from the language of letter shapes

to the language of pulse widths.

In the case of the auditory system, the "message" that needs to be encoded is the sound

wave arriving at the tympanic membrane or, alternatively, its spectrum. The signal is preserved

in halfwave rectified form in the hair cell receptor potential that drives the auditory nerve. The

kind of translation that is occurring is from a graded, continuous signal to a sequence of on-off

pulses. The question, then, is how might this continuous signal (or its spectrum) be coded on the

Figure 4-28. The basilar membrane displacement patterns for two sinusoids differing in frequency

(top panels) and the auditory nerve firing rate patterns that would likely be associated with each of

these signals (bottom panels). When the amplitude of basilar membrane movement is high,

auditory nerve firing rate is high.


auditory nerve using on-off pulses? Since the pulses do not vary appreciably in amplitude, the

number of dimensions that might be exploited is fairly limited. Three characteristics of auditory

nerve firing patterns that might be exploited in this coding scheme are: (1) the time of occurrence

of the pulse, (2) the rate at which the neurons fire (i.e., whether a large or small number of

spikes occur in a given time interval), and (3) the physical location of the nerve fiber (i.e.,

whether the nerve fiber is connected to a hair cell on the basal end of the cochlea, the apical end,

or somewhere in between). These dimensions need not be treated separately. For example, it is

possible to examine the rate of neural activity for fibers connected at various positions along the

basilar membrane, which combines the firing rate parameter with the physical position

parameter. This is the essence of "place coding" or "rate-place coding," described below.

Rate-Place Coding

To understand rate-place coding, it is necessary to recall that the basal end of the basilar

membrane, which is stiffer than the apical end, responds better to high frequencies than low

frequencies, while the opposite is true of the apical end of the basilar membrane. Consequently,

higher frequency pure tones will produce the largest basilar membrane movement amplitude

toward the base, while lower frequency pure tones will produce the largest basilar membrane

movement amplitude toward the apex (see Figures 4-15 and 4-16). The same basic principle

applies to complex signals consisting of many frequency components: the lower frequency

components of the input signal will be directed toward the apical end of the basilar membrane,

and the higher frequency components will be directed toward the basal end. The basic idea of

rate-place coding is that this spatial separation of frequency components will be reflected in the

pattern of auditory nerve activity. As shown in Figure 4-28, two signals differing in frequency

will show different patterns of 8th nerve electrical activity, with lower frequency signals showing

more activity at the apical end and higher frequency signals showing more activity at the basal

end. "Amount of neural activity" here is simply firing rate: the number of spikes per unit time in

neurons connected at various places along the cochlea. The basic idea, then, is that auditory

nerve activity toward the base codes high frequency, while auditory nerve activity at the apex

codes low frequency. The representation in Figure 4-28 can be viewed as a spectrum of sorts,

broadly analogous to a Fourier amplitude spectrum, with two differences: (1) the frequency scale

is backwards, since low frequencies are on the right and high frequencies are on the left, and (2)

the spectrum is quite coarse relative to the kind of spectrum that can be obtained by Fourier

analysis; that is, the pure tone produces activity over a rather wide area of the cochlea. The first

point is not relevant since Mother Nature has no bias toward reading from left to right, but the

second point may have considerable relevance. This issue will be discussed below.

The data shown in Figure 4-28 are hypothetical, and no such pattern has ever been directly

observed. The reason is that collection of this kind of data would require the simultaneous

recording of auditory nerve firing patterns in a large number of fibers at various positions.

Current methods do not exist for making these kinds of recordings simultaneously from a large

number of spatially separated neurons. Rate-place coding, however, can be inferred from two

techniques that make use of recordings from single auditory nerve fibers. One technique involves

the measurement of neural tuning curves from single neurons, and the other technique involves

measurement of frequency response curves, also from single neurons.


Neural Tuning Curves

Neural tuning curves are measured by placing an electrode into a neuron and determining

the threshold of the fiber over a wide range of signal frequencies. The threshold is simply the

signal intensity that is required to obtain a measurable response from the neuron. Neural tuning

curves for three different neurons are shown in Figure 4-29. Measuring the threshold of a neuron

is not simply a matter of increasing the signal intensity until the neuron fires. This is because

neurons will fire periodically even in the absence of an acoustic stimulus. The rate at which a

neuron will fire in relative quiet is called the spontaneous rate of the neuron. The threshold of a

neuron, then, is the intensity required for a neuron to fire at rates that are measurably above its

spontaneous rate.

The main point to be noted about the tuning curves in Figure 4-29 is that each neuron has a

much lower threshold at some frequencies than others. The sharp dip in each tuning curve

represents the lowest threshold and therefore the frequency at which the neuron is most sensitive.

This is called the characteristic frequency (CF) or best frequency (BF) of the neuron. The

terms characteristic frequency and best frequency need to be interpreted carefully. Finding that a

given neuron has a CF of 12,000 Hz, for example, does not reveal anything about the structural

properties of the neuron that cause it to "resonate" at 12,000 Hz; rather, the CF of 12,000 Hz

Figure 4-29. Neural tuning curves for auditory nerve fibers with three different characteristic

frequencies (CF). Data from Kiang and Moxon (1974).

Figure 4-29. Neural tuning curves for auditory nerve fibers with three different characteristic

frequencies (CF). The threshold of the fiber is the lowest (i.e., sensitivity is greatest) at the

characteristic frequency of the fiber. Data from Kiang and Moxon (1974).


means that the neuron is connected to a hair cell that is located at the high frequency (basal) end

of the basilar membrane. In other words, the "best frequency" of a neuron is determined not by

its internal properties but by its location along the basilar membrane. If a neuron has a CF of

12,000 Hz it is because it is innervating a hair cell that is located at a point along the length of

the cochlea where the basilar membrane responds best to a frequency of 12,000 Hz. If this

12,000 Hz CF neuron were "unplugged" from its hair cell near the basal end of the cochlea and

attached to a hair cell located at the apical end, the CF would shift to a lower frequency since it

would then be driven by the movement of a portion of basilar membrane that is maximally

sensitive to lower frequencies. Consequently, although CF is measured by recording the

electrical activity of a nerve fiber, the best frequency of the fiber is actually controlled by the

mechanical properties of the basilar membrane.

Notice also that the tuning curves are asymmetrical; that is, the slopes are much sharper on

the high frequency side than the low frequency side. This asymmetry is a direct result of the

asymmetry in the envelope of the basilar membrane traveling wave. This point will be addressed

in the section below on auditory nerve frequency response curves. The relationship that exists

on the auditory nerve between CF and the physical location of the nerve fiber along the basilar

membrane is called tonotopic organization. As will be seen later in this chapter, tonotopic

organization is a fundamental architectural property of the auditory system. Tonotopic

organization is preserved not only on the auditory nerve but throughout the entire auditory

system, up to and including the auditory cortex.

Figure 4-30. Frequency response curves for two neurons with different characteristic frequencies.

The figure shows the firing rate of the two nerve fibers to sinusoids whose amplitude is always the

same, but whose frequency varies. Data from Rose et al. (1971).


Frequency Response Curves of Auditory Nerve Fibers

Another way to observe rate-place coding on the auditory nerve is to measure frequency

response curves of individual fibers. For reasons that are explained below, this method is more

revealing in some respects of the kind of frequency analysis that is carried out by the cochlea.

The method is conceptually identical to the one described in Chapter 3 for measuring the

frequency response of a filter. The method described earlier involves driving the filter with pure

tones of constant amplitude at various frequencies, from the lowest frequency of interest to the

highest frequency of interest. The frequency response curve is the amplitude of the signal at the

output of the filter as a function of the frequency of a constant amplitude input signal. The shape

of the frequency response curve tells us what frequencies will be allowed to pass through the

filter and what frequencies will be attenuated.

To measure the frequency response curve of an auditory nerve fiber, a recording electrode

is placed in the nerve fiber and its firing rate is measured as pure tones are delivered at a variety

of input frequencies; the amplitude of the input signal is held constant. The frequency response

curve of the fiber shows firing rate on the y axis and the frequency of a constant amplitude input

signal on the x axis. The firing rate measure is equivalent to the output amplitude measure that

was described in Chapter 3 for determining the frequency response curve of a filter.

Figure 4-30 shows frequency response curves for two neurons with different CFs. The

measurements were made by Rose et al. (1971) from a squirrel monkey using a rather low

presentation level of 45 dBSPL. (The low presentation level is quite important, as will be

discussed below.) One fiber has a CF of 900 Hz and the other fiber has a CF of 1,700 Hz. Note

that the two frequency response curves resemble bandpass filters; that is, the fibers respond with

maximum output at their CF, with fairly sharp drops on either side. Again, the tendency of these

fibers to respond with high firing rates at their CF does not reveal anything about the fibers

except that the 1,700 Hz CF fiber innervates a hair cell that is closer to the basal end of the

basilar membrane than the 900 Hz CF fiber. The filtering effect, then, can be attributed to the

frequency selective behavior of the basilar membrane and not the nerve fiber or the hair cell.

Findings such as those presented in Figure 4-30 have given rise to a view of the cochlea as

a filter bank; that is, a bank of some 3,000-3,500 overlapping bandpass filters of the kind shown

in Figure 4-30. This range of 3,000-3,500 comes from the approximate number of hair cell

channels in the cochlea, with each channel consisting of 1 IHC and 3-4 OHCs.4 Each of these

channels can be thought of as analogous to the bandpass filter that is used on a radio tuner: each

channel allows a band of energy through, while attenuating signal components of higher or lower

frequency. By measuring the output of each of these channels (i.e., the firing rate), a spectrum

could be reconstructed. Since each channel is maximally sensitive to signal components at the

fiber CF, the firing rate at each CF reflects the amount of signal energy at that frequency. This is

the essence of what is meant by rate-place coding: the firing rate at each channel codes the

amount of signal energy at the CF corresponding to that channel.

4

In terms of the signals that are generated on the auditory nerve, a channel can essentially be considered to be a single IHC since the great

majority of afferent auditory nerve fibers innervate IHCs rather than OHCs.


Problems with Rate-Place Coding

There is no doubt that filtering of the general type that is shown in Figure 4-30 takes place

in the cochlea, but does the auditory system actually derive a spectrum using rate-place coding?

Opinions on this question have been divided for many years. One of the main questions is

whether the bandpass filters that make up the cochlear filter bank are sufficiently selective to

account for what is known about the frequency discrimination abilities of listeners. The term

"selective" here simply means narrow; that is, a selective or narrow band filter passes a narrow

band of frequencies, with sharp slopes on either side. If frequency discrimination ability can be

explained on the basis of the cochlear filter bank, then the bandpass filters need to be very

narrow since frequency discrimination abilities are stunningly good: in the middle portion of the

spectrum, one just noticeable difference in frequency corresponds to a distance along the basilar

membrane of approximately 10 microns, or roughly the diameter of a single inner hair cell

(Davis and Silverman, 1970). Consequently, in order for rate-place coding to work, the

bandwidths of the filters at each channel would have to be sufficiently narrow that relatively

little energy is allowed to "spill" into an adjacent channel.

There is some reason to believe that the cochlear filter bank is too broadly tuned to explain

frequency discrimination abilities. Although frequency response curves tend to be fairly narrow

when signal intensities are low, there is very good evidence that filter bandwidths become quite

broad at even moderate signal intensities. Figure 4-31 shows a family of frequency response

curves for an individual auditory nerve fiber from a squirrel monkey from a study by Rose et al.

(1971). This particular auditory nerve fiber has a CF of 1,700 Hz. The eight separate curves

represent the frequency response curve measured at eight different signal levels, every 10 dB

from 25 dBSPL to 95 dBSPL. Notice first of all that the frequency response curves reveal a certain

Figure 4-31. Frequency response curves for a single auditory nerve fiber at eight different signal

intensities. Note that the frequency response curves are relatively narrow at low presentation levels

but become very broad at intensities that are typical of speech. Data from Rose et al. (1971).


amount of frequency selectivity; that is, the fiber responds better to frequencies at or near the

1,700 Hz CF than at other frequencies, despite the fact that the intensity of the input signal is

held constant for each of the individual curves. However, notice that the degree of frequency

selectivity is strongly affected by signal level. Specifically, the frequency response curves

become much more broad (i.e., less frequency selective) at higher signal intensities. For

example, at 35-45 dBSPL the shapes of the frequency response curves resemble a bandpass filter,

with fairly sharp drops in firing rate on either side of the CF. However, at levels that are more

typical of speech (e.g., 65-85 dBSPL), the filter shapes become considerably broader. This is

especially true on the low frequency side of the frequency response curves; that is, the fibers

show considerable activity at frequencies that are much lower than the CF. In fact, at the higher

presentation levels the filter shapes begin to resemble lowpass filters more than bandpass filters.

What this means is that the relationship between place and frequency -- which is the essence of

place coding -- is not nearly as strong at typical speech levels as it is at very low stimulus levels.

Some theorists have argued that the frequency selectivity that is shown in these frequency

response curves is far too coarse to account for the excellent frequency discrimination ability of

human listeners.

The final point that needs to be discussed regarding the frequency response curves in

Figure 4-31 is the asymmetry. The slopes of the frequency response curves are considerably

sharper on the high frequency side (~100-500 dB/octave) than on the low frequency side (~8-12

dB/octave). This is the same kind of asymmetry that was seen earlier in the neural tuning curve

data, and both effects are due to the asymmetry in the envelope of the basilar membrane

traveling wave. This may seem counterintuitive since the traveling wave envelope has a sharper

slope on the low frequency (apical) side than the high frequency (basal) side. To understand why

this does, in fact, make sense, suppose that we were to measure the frequency response of a fiber

with a CF of 1,000 Hz. In measuring the frequency response curve of the fiber, we begin with

low frequency pure tones and move to higher frequencies, each time holding the intensity

constant and measuring the firing rate of the neuron. Since we are progressing from low

frequencies to high frequencies, the point of maximum amplitude in the basilar membrane

traveling wave moves systematically from the apex to the base. Figure 4-32 shows what the

traveling wave envelope would look like for three sinusoids: (1) a pure tone at the CF of the fiber

(1,000 Hz), (2) a pure tone that is lower in frequency than the CF, and (3) a pure tone that is

higher in frequency than the CF. The arrow in roughly the center of the figure shows the

approximate location of the 1,000 Hz CF fiber that is being recorded. The firing rate at this

location will be strongly correlated with the amplitude of the traveling wave at this position on

the cochlea. The main point to notice is that the pure tone that is lower than the CF would be

expected to cause much more activity in the 1,000 CF fiber than the pure tone that is higher in

frequency than the CF due to the asymmetry in the traveling wave envelope. This is why the

slopes of the frequency response curves in Figure 4-31 tend to be much sharper on the high

frequency side than the low frequency side.

Summary of Rate-Place Coding

In summary, the essence of rate-place coding is that the vibratory characteristics of the

basilar membrane are such that high frequency signals tend to cause greater neural activity in

auditory nerve fibers connected at the base than the apex, while the opposite is true of low


frequency signals. This relationship between the characteristic frequency or best frequency of an

auditory nerve fiber and spatial location along the basilar membrane is called tonotopic

organization. Tonotopic organization may be observed experimentally by recording the threshold

of individual nerve fibers at different frequencies, resulting in a neural tuning curve. It can also

be observed by measuring the frequency response curves of individual nerve fibers.

Experimental findings using these two techniques have given rise to the view of the cochlea as a

filter bank, with each of some 3,000-3,500 channels passing a band of frequencies. An auditory

spectrum might be coded as variations in the firing rate at the output of each of these channels.

However, there is some uncertainty about whether the filter bank provides enough frequency

resolution to account for the excellent frequency discrimination that is shown by listeners.

Synchrony Coding

The basic idea behind synchrony coding is that the period of the input signal will be

preserved in the period that elapses between successive spikes on the auditory nerve fibers. For

example, if the input signal has a period of 10 ms (f = 100 Hz), the pulse train produced on the

auditory nerve will tend to have an interspike interval of 10 ms. This type of coding, then,

exploits the time of occurrence parameter in neural firing patterns. The basic idea behind

synchrony coding is shown in a highly simplified form in Figure 4-33. The basic idea is quite

straightforward: a 100 Hz signal will produce a 100 Hz pulse train on the auditory nerve or,

stated differently, the interspike interval will match the period of the input signal. According to

synchrony coding, the auditory spectrum is assumed to be derived not by the filtering action of

the cochlea, but by the measurement of interspike intervals in the central nervous system, where

neural firing patterns are analyzed.

The very simple kind of synchrony coding that is shown in Figure 4-33 is a very old idea

that dates back to Rutherford (1886). When the theory was first proposed the limits imposed on

maximum firing rates by neural refractory periods were not known, and it was thought that an

Figure 4-32. Basilar membrane traveling wave envelopes for signals at three different frequencies.

If a signal with a 1,000 Hz CF is being recorded, the lower frequency signal will produce more

activity in the 1,000 Hz CF fiber than the higher frequency signal. This is why tuning curves and

frequency response curves have sharper slopes on the high frequency side than the low frequency

side.


individual nerve fiber could fire at the very high rates that prevail at the high end of the human

frequency range (~20 kHz). Recall that the absolute refractory period is approximately 1 ms,

meaning that a neuron cannot fire at a rate exceeding about 1,000 Hz. An individual nerve fiber,

in fact, can sustain this 1,000 Hz top rate only for very brief bursts. For sustained signals, the

relative refractory period must also be taken into account. The relative refractory period is a

longer interval ranging from about 1-10 ms, and when this interval is taken into account, a

maximum sustained firing rate that might average perhaps 300-400 Hz or less might be achieved

by an individual fiber.

Figure 4-34. The volley principle. Adapted from Wever (1949).


One implication of these firing rate limits would seem to be that the synchrony principle

could accurately code signal frequencies only for very low frequencies of perhaps 300 Hz or

lower. However, a rather simple elaboration of synchrony coding called the volley principle

allows this low frequency limit to be greatly exceeded. The basic idea behind the volley

principle, which was proposed by Wever (1949), is shown in Figure 4-34. The assumption made

by Wever is that, while each individual neuron may not be able to fire fast enough to produce

one pulse for every cycle of the waveform, the sum of the activity of several neurons will show a

train of pulses whose interspike interval matches the period of the input signal.5 According to

this view, then, the interspike interval, which codes the period of the input signal, must be

measured not from individual nerve fiber, but from the summed output of a group of nerve

fibers.

5

Figure 4-34, which has been widely reproduced in many texts in auditory physiology, does a rather good job of capturing the basic idea

behind Wever's volley principle. However, the figure is misleading in one respect. The figure shows an unrealistically orderly firing pattern for

the individual neurons, where each neuron fires, misses exactly four cycles, fires again, and so on. The adjacent neurons are also shown to be

offset from one another by exactly one pulse. Such orderly behavior is not actually obtained experimentally, but the basic principle of measuring the interspike interval from a group of neurons does not depend on this unrealistically orderly behavior.

Figure 4-35. An illustration of Poisson coding. The figure shows the instantaneous probability of a pulse

on an individual auditory nerve fiber (i.e., the number of spikes occurring in a given time interval) as a

function of time. Superimposed on the pulse probability function, which is plotted as a bar graph, is the

input signal. The main lesson of this figure is that instantaneous pulse probability is high when

instantaneous signal amplitude is high, and vice versa. Consequently, the pulse probability function

preserves the shape of the input waveform, except that the function, like the receptor potential, is halfwave

rectified. Data are from the Rose et al. (1971) measurements of 8th nerve firing patterns in the squirrel

monkey. [replace w/ scan of Rose puretone and complex data??]


This coding scheme does not depend on individual nerve fibers firing at the same

frequency as the input signal, but it does depend on the ability of nerve fibers to remain

synchronized to the input waveform. In other words, the neuron may fire for one cycle, miss

several cycles, fire on another cycle, miss several more, and so on. However, for the coding

scheme to work, the spikes that do occur need to remain in synchrony with the input waveform.

Remaining in synchrony means that the fiber tends to fire at roughly the same point in the cycle.

For example, a fiber out of synchrony might fire once at the positive peak, next at zero crossing,

again at a negative peak, and so on. Auditory nerve fibers appear to be able to maintain

synchrony for signal frequencies up to approximately 4,000-5,000 Hz, although there is no sharp

cutoff. Consequently, synchrony coding, along with the summing-across-fibers assumption

provided by the volley principle, appears to be capable of coding frequency up to about 4,000-

5,000 Hz.

Place-Synchrony Coding

Rate-place coding and synchrony coding are both very old ideas with long and complex

histories. The earliest well formulated version of place theory was proposed by von Helmholtz

(1857) more than a century ago, and later significantly modified and extended in the Nobel-

Prize-winning work of von Bekesy (1960) that culminated in the traveling wave theory that has

been discussed at great length in this chapter. Synchrony coding has a nearly equally long

history, dating back to the first well formulated version described by Rutherford (1886). For

many years the principal debate in auditory physiology centered around the question of which of

these two divergent approaches was correct. A view that has become rather common is that these

two coding schemes are not incompatible. A compromise view called place-synchrony coding

or place-volley theory holds that frequency is coded both by rate-place mechanisms and by

synchrony mechanisms. In the low frequencies, where synchrony is well maintained, synchrony

coding is thought to be dominant, while in the higher frequencies where synchrony is not well

maintained, place coding is dominant. There is assumed to be no abrupt shift between synchrony

coding and place coding, and for a rather broad range of frequencies in the middle of the

spectrum, perhaps from 1,500-5,000 Hz, both kinds of coding schemes are assumed to contribute

to frequency analysis.

Poisson Coding

There is one additional coding scheme that may play an important role in auditory analysis.

The scheme is called Poisson (pwah-SOAN) coding, and it typically receives little or no

attention in introductory discussions in auditory physiology and, in the view of the authors, has

perhaps received too little attention among professional scientists. While the coding scheme has

an unfamiliar sounding name, the basic principle is not complicated. The basic idea behind

Poisson coding is shown in Figure 4-35, which displays a slightly simplified version of data from

a study by Rose et al. (1971). In this study recordings were made from single auditory nerve

fibers from a squirrel monkey. Each of these figures shows pulse probability as a function of

time; that is, the probability that a pulse will occur at any given point in time. (Note that this

scheme, like synchrony coding, exploits the time of occurrence parameter of auditory nerve

firing patterns.) Superimposed on each of these figures is the signal that is being presented to the

animal. The signal is the smooth curve, and pulse probability is shown as a bar graph. Pulse


probability is simply the number of spikes that occur in a given small interval of time. The

similarity between the shape of the pulse probability function and the shape of the input signal is

striking. What the Rose et al. data show is that the instantaneous probability of an auditory nerve

pulse is directly and linearly proportional to the instantaneous amplitude of the signal that is

being coded. In other words, if the signal amplitude at a given instant is high, the fiber is very

likely to fire and, conversely, if the signal amplitude at a given instant is low, the fiber is not very

likely to fire. Engineers refer to this coding scheme as a Poisson point process or a Poisson

code. The origin of the name is unimportant; what is important is the stunning similarity between

the pulse probability code and the input waveform. The pulse probability function can be seen as

a very direct coding of the graded receptor potential which, in turn, is a faithful representation of

the input signal.6 (Note that both the receptor potential and the pulse probability function are

halfwave rectified. Again, this is because hair cells are stimulated to generate a receptor potential

as a result of cilia shearing in one direction only. Since it is the receptor potential that stimulates

the generation of action potentials in neurons, spike probability is near zero in one half of each

cycle.)

What is the Poisson code good for? Unfortunately, as with many aspects of auditory

analysis, it is not currently known. In very general terms, one possibility is that the primary

function of the cochlea is simply to preserve the detailed shape of the input signal (in halfwave

rectified form), and the auditory nerve serves to code this signal with on-off pulses using the

Poisson pulse-probability code. The Poisson coded signal is then passed on to the central nervous

system for analysis. According to this view, the "heavy lifting" of spectrum analysis is carried

out not by the cochlea but by purely neural mechanisms in the central nervous system. The

neural mechanisms that might be involved in carrying out this spectrum analysis at central levels

-- if they exist at all -- are currently not known. Neural circuits that are capable of deriving

something equivalent to a Fourier amplitude spectrum from the Poisson coded signal have been

hypothesized, but it is not currently known if these circuits exist (see Houde & Hillenbrand,

1997).

***********************

CHAPTER NOT QUITE FINISHED. STILL NEEDED ARE: (1) A QUICK TOUR OF

CENTRAL AUDITORY PATHWAY AND (2) A SUMMARY.

6

A point worth noting about the Rose et al. data is that the pulse probability functions were derived by summing the activity of an individual

fiber over many hundreds of cycles of the input waveform. Being a probabilistic process, the Poisson code will be very ragged looking on any individual fiber for a single presentation of a stimulus. Since a listener perceives sound quality in real time based on single presentations of

stimuli, it must be the case that the Poisson code is derived not on a single nerve fiber but by summing pulse probabilities over many nerve fibers.

Some rough calculations suggest that the Poisson code is accumulated by summing the activity of something on the order of 1,000 fibers (Houde and Hillenbrand, 1996).


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