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Sound localization
Sound localization
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Sound localization is a listener's ability to identify the location or origin of a detected sound in direction and distance.

The sound localization mechanisms of the mammalian auditory system have been extensively studied. The auditory system uses several cues for sound source localization, including time difference and level difference (or intensity difference) between the ears, and spectral information. Other animals, such as birds and reptiles, also use them but they may use them differently, and some also have localization cues which are absent in the human auditory system, such as the effects of ear movements. Animals with the ability to localize sound have a clear evolutionary advantage.

How sound reaches the brain

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Sound is the perceptual result of mechanical vibrations traveling through a medium such as air or water. Through the mechanisms of compression and rarefaction, sound waves travel through the air, bounce off the pinna and concha of the exterior ear, and enter the ear canal. In mammals, the sound waves vibrate the tympanic membrane (ear drum), causing the three bones of the middle ear to vibrate, which then sends the energy through the oval window and into the cochlea where it is changed into a chemical signal by hair cells in the organ of Corti, which synapse onto spiral ganglion fibers that travel through the cochlear nerve into the brain.

Neural interactions

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In vertebrates, interaural time differences are known to be calculated in the superior olivary nucleus of the brainstem. According to Jeffress,[1] this calculation relies on delay lines: neurons in the superior olive which accept innervation from each ear with different connecting axon lengths. Some cells are more directly connected to one ear than the other, thus they are specific for a particular interaural time difference. This theory is equivalent to the mathematical procedure of cross-correlation. However, because Jeffress's theory is unable to account for the precedence effect, in which only the first of multiple identical sounds is used to determine the sounds' location (thus avoiding confusion caused by echoes), it cannot be entirely used to explain the response. Furthermore, a number of recent physiological observations made in the midbrain and brainstem of small mammals have shed considerable doubt on the validity of Jeffress's original ideas.[2]

Neurons sensitive to interaural level differences (ILDs) are excited by stimulation of one ear and inhibited by stimulation of the other ear, such that the response magnitude of the cell depends on the relative strengths of the two inputs, which in turn, depends on the sound intensities at the ears.

In the auditory midbrain nucleus, the inferior colliculus (IC), many ILD sensitive neurons have response functions that decline steeply from maximum to zero spikes as a function of ILD. However, there are also many neurons with much more shallow response functions that do not decline to zero spikes.

Human auditory system

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Sound localization is the process of determining the location of a sound source. The brain utilizes subtle differences in intensity, spectral, and timing cues to localize sound sources.[3][4][5]

Localization can be described in terms of three-dimensional position: the azimuth or horizontal angle, the elevation or vertical angle, and the distance (for static sounds) or velocity (for moving sounds).[6]

The azimuth of a sound is signaled by the difference in arrival times between the ears, by the relative amplitude of high-frequency sounds (the shadow effect), and by the asymmetrical spectral reflections from various parts of our bodies, including torso, shoulders, and pinnae.[6]

The distance cues are the loss of amplitude, the loss of high frequencies, and the ratio of the direct signal to the reverberated signal.[6]

Depending on where the source is located, our head acts as a barrier to change the timbre, intensity, and spectral qualities of the sound, helping the brain orient where the sound emanated from.[5] These minute differences between the two ears are known as interaural cues.[5]

Lower frequencies, with longer wavelengths, diffract the sound around the head forcing the brain to focus only on the phasing cues from the source.[5]

Helmut Haas discovered that we can discern the sound source despite additional reflections at 10 decibels louder than the original wave front, using the earliest arriving wave front.[5] This principle is known as the Haas effect, a specific version of the precedence effect.[5] Haas measured down to even a 1 millisecond difference in timing between the original sound and reflected sound increased the spaciousness, allowing the brain to discern the true location of the original sound. The nervous system combines all early reflections into a single perceptual whole allowing the brain to process multiple different sounds at once.[7] The nervous system will combine reflections that are within about 35 milliseconds of each other and that have a similar intensity.[7]

Duplex theory

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To determine the lateral input direction (left, front, right), the auditory system analyzes the following ear signal information:

In 1907, Lord Rayleigh utilized tuning forks to generate monophonic excitation and studied the lateral sound localization theory on a human head model without auricle. He first presented the interaural clue difference based sound localization theory, which is known as Duplex Theory.[8] Human ears are on different sides of the head, and thus have different coordinates in space. As shown in the duplex theory figure, since the distances between the acoustic source and ears are different, there are time difference and intensity difference between the sound signals of two ears. We call those kinds of differences as Interaural Time Difference (ITD) and Interaural Intensity Difference (IID) respectively.

Duplex theory
Interaural time difference (ITD) between left ear (top) and right ear (bottom).
[sound source: 100 ms white noise from right]
Interaural level difference (ILD) between left ear (left) and right ear (right).
[sound source: a sweep from right]

From the duplex theory figure we can see that for source B1 or source B2, there will be a propagation delay between two ears, which will generate the ITD.[tone] Simultaneously, human head and ears may have a shadowing effect on high-frequency signals, which will generate IID.

  • Interaural time difference (ITD) – Sound from the right side reaches the right ear earlier than the left ear. The auditory system evaluates interaural time differences from: (a) Phase delays at low frequencies and (b) group delays at high frequencies.
  • Theory and experiments show that ITD relates to the signal frequency . Suppose the angular position of the acoustic source is , the head radius is and the acoustic velocity is , the function of ITD is given by: [9] [citation not found] . In above closed form, we assumed that the 0 degree is in the right ahead of the head and counter-clockwise is positive.
  • Interaural intensity difference (IID) or interaural level difference (ILD) – Sound from the right side has a higher level at the right ear than at the left ear, because the head shadows the left ear. These level differences are highly frequency dependent and they increase with increasing frequency. Massive theoretical researches demonstrate that IID relates to the signal frequency and the angular position of the acoustic source . The function of IID is given by: [9] [citation not found]
  • For frequencies below 1000 Hz, mainly ITDs are evaluated (phase delays), for frequencies above 1500 Hz mainly IIDs are evaluated. Between 1000 Hz and 1500 Hz there is a transition zone, where both mechanisms play a role.
  • Localization accuracy is 1 degree for sources in front of the listener and 15 degrees for sources to the sides. Humans can discern interaural time differences of 10 microseconds or less.[10][11]

For frequencies below 800 Hz, the dimensions of the head (ear distance 21.5 cm, corresponding to an interaural time delay of 626 μs) are smaller than the half wavelength of the sound waves. So the auditory system can determine phase delays between both ears without confusion. Interaural level differences are very low in this frequency range, especially below about 200 Hz, so a precise evaluation of the input direction is nearly impossible on the basis of level differences alone. As the frequency drops below 80 Hz it becomes difficult or impossible to use either time difference or level difference to determine a sound's lateral source, because the phase difference between the ears becomes too small for a directional evaluation.[12]

For frequencies above 1600 Hz the dimensions of the head are greater than the length of the sound waves. An unambiguous determination of the input direction based on interaural phase alone is not possible at these frequencies. However, the interaural level differences become larger, and these level differences are evaluated by the auditory system. Also, delays between the ears can still be detected via some combination of phase differences and group delays, which are more pronounced at higher frequencies; that is, if there is a sound onset, the delay of this onset between the ears can be used to determine the input direction of the corresponding sound source. This mechanism becomes especially important in reverberant environments. After a sound onset there is a short time frame where the direct sound reaches the ears, but not yet the reflected sound. The auditory system uses this short time frame for evaluating the sound source direction, and keeps this detected direction as long as reflections and reverberation prevent an unambiguous direction estimation.[13] The mechanisms described above cannot be used to differentiate between a sound source ahead of the hearer or behind the hearer; therefore additional cues have to be evaluated.[14]

Pinna filtering effect

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HRTF

Duplex theory shows that ITD and IID play significant roles in sound localization, but they can only deal with lateral localization problems. For example, if two acoustic sources are placed symmetrically at the front and back of the right side of the human head, they will generate equal ITDs and IIDs, in what is called the cone model effect. However, human ears can still distinguish between these sources. Besides that, in natural sense of hearing, one ear alone, without any ITD or IID, can distinguish between them with high accuracy. Due to the disadvantages of duplex theory, researchers proposed the pinna filtering effect theory.[15][16] The shape of the human pinna is concave with complex folds and asymmetrical both horizontally and vertically. Reflected and direct waves generate a frequency spectrum on the eardrum, relating to the acoustic sources. Then auditory nerves localize the sources using this frequency spectrum.[17]

HRTF binaural synthesis

These spectrum clues generated by the pinna filtering effect can be presented as a head-related transfer function (HRTF). The corresponding time domain expressions are called the head-related impulse response (HRIR). The HRTF is also described as the transfer function from the free field to a specific point in the ear canal. HRTFs are usually recognized as LTI systems:[9]

where L and R represent the left ear and right ear respectively, and represent the amplitude of the sound pressure at the entrances to the left and right ear canals, and is the amplitude of sound pressure at the center of the head coordinate when listener does not exist. In general, an HRTF's and are functions of source angular position , elevation angle , the distance between the source and the center of the head , the angular velocity and the equivalent dimension of the head .

At present, the main institutes that work on measuring HRTF database include CIPIC[18] International Lab, MIT Media Lab, the Graduate School in Psychoacoustics at the University of Oldenburg, the Neurophysiology Lab at the University of Wisconsin–Madison and Ames Lab of NASA. Databases of HRIRs from humans with normal and impaired hearing and from animals are publicly available.

Other cues

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The human outer ear, i.e. the structures of the pinna and the external ear canal, form direction-selective filters. Depending on the sound input direction, different filter resonances become active. These resonances implant direction-specific patterns into the frequency responses of the ears, which can be evaluated by the auditory system for sound localization. Together with other direction-selective reflections at the head, shoulders and torso, they form the outer ear transfer functions. These patterns in the ear's frequency responses are highly individual, depending on the shape and size of the outer ear. If sound is presented through headphones, and has been recorded via another head with different-shaped outer ear surfaces, the directional patterns differ from the listener's own, and problems will appear when trying to evaluate directions in the median plane with these foreign ears. As a consequence, front–back permutations or inside-the-head-localization can appear when listening to dummy head recordings, or otherwise referred to as binaural recordings. It has been shown that human subjects can monaurally localize high frequency sound but not low frequency sound. Binaural localization, however, was possible with lower frequencies. This is likely due to the pinna being small enough to only interact with sound waves of high frequency.[19] It seems that people can only accurately localize the elevation of sounds that are complex and include frequencies above 7,000 Hz, and a pinna must be present.[20]

When the head is stationary, the binaural cues for lateral sound localization (interaural time difference and interaural level difference) do not give information about the location of a sound in the median plane. Identical ITDs and ILDs can be produced by sounds at eye level or at any elevation, as long as the lateral direction is constant. However, if the head is rotated, the ITD and ILD change dynamically, and those changes are different for sounds at different elevations. For example, if an eye-level sound source is straight ahead and the head turns to the left, the sound becomes louder (and arrives sooner) at the right ear than at the left. But if the sound source is directly overhead, there will be no change in the ITD and ILD as the head turns. Intermediate elevations will produce intermediate degrees of change, and if the presentation of binaural cues to the two ears during head movement is reversed, the sound will be heard behind the listener.[14][21] Hans Wallach[22] artificially altered a sound's binaural cues during movements of the head. Although the sound was objectively placed at eye level, the dynamic changes to ITD and ILD as the head rotated were those that would be produced if the sound source had been elevated. In this situation, the sound was heard at the synthesized elevation. The fact that the sound sources objectively remained at eye level prevented monaural cues from specifying the elevation, showing that it was the dynamic change in the binaural cues during head movement that allowed the sound to be correctly localized in the vertical dimension. The head movements need not be actively produced; accurate vertical localization occurred in a similar setup when the head rotation was produced passively, by seating the blindfolded subject in a rotating chair. As long as the dynamic changes in binaural cues accompanied a perceived head rotation, the synthesized elevation was perceived.[14]

In the 1960s Batteau showed the pinna also enhances horizontal localization.[23][24]

Distance of the sound source

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[citation needed]

The human auditory system has only limited possibilities to determine the distance of a sound source. In the close-up-range there are some indications for distance determination, such as extreme level differences (e.g. when whispering into one ear) or specific pinna (the visible part of the ear) resonances in the close-up range.

The auditory system uses these clues to estimate the distance to a sound source:

  • Direct/ Reflection ratio: In enclosed rooms, two types of sound are arriving at a listener: The direct sound arrives at the listener's ears without being reflected at a wall. Reflected sound has been reflected at least one time at a wall before arriving at the listener. The ratio between direct sound and reflected sound can give an indication about the distance of the sound source.
  • Loudness: Distant sound sources have a lower loudness than close ones. This aspect can be evaluated especially for well-known sound sources.
  • Sound spectrum: High frequencies are more quickly damped by the air than low frequencies. Therefore, a distant sound source sounds more muffled than a close one, because the high frequencies are attenuated. For sound with a known spectrum (e.g. speech) the distance can be estimated roughly with the help of the perceived sound.
  • ITDG: The Initial Time Delay Gap describes the time difference between arrival of the direct wave and first strong reflection at the listener. Nearby sources create a relatively large ITDG, with the first reflections having a longer path to take, possibly many times longer. When the source is far away, the direct and the reflected sound waves have similar path lengths.
  • Movement: Similar to the visual system there is also the phenomenon of motion parallax in acoustical perception. For a moving listener nearby sound sources are passing faster than distant sound sources.
  • Level Difference: Very close sound sources cause a different level between the ears.

Signal processing

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Sound processing of the human auditory system is performed in so-called critical bands. The hearing range is segmented into 24 critical bands, each with a width of 1 Bark or 100 Mel. For a directional analysis the signals inside the critical band are analyzed together.

The auditory system can extract the sound of a desired sound source out of interfering noise. This allows the listener to concentrate on only one speaker if other speakers are also talking (the cocktail party effect). With the help of the cocktail party effect sound from interfering directions is perceived attenuated compared to the sound from the desired direction. The auditory system can increase the signal-to-noise ratio by up to 15 dB, which means that interfering sound is perceived to be attenuated to half (or less) of its actual loudness. [citation needed]

In enclosed rooms not only the direct sound from a sound source is arriving at the listener's ears, but also sound which has been reflected at the walls. The auditory system analyses only the direct sound,[13] which is arriving first, for sound localization, but not the reflected sound, which is arriving later (law of the first wave front). So sound localization remains possible even in an echoic environment. This echo cancellation occurs in the Dorsal Nucleus of the Lateral Lemniscus (DNLL).[25]

In order to determine the time periods, where the direct sound prevails and which can be used for directional evaluation, the auditory system analyzes loudness changes in different critical bands and also the stability of the perceived direction. If there is a strong attack of the loudness in several critical bands and if the perceived direction is stable, this attack is in all probability caused by the direct sound of a sound source, which is entering newly or which is changing its signal characteristics. This short time period is used by the auditory system for directional and loudness analysis of this sound. When reflections arrive a little bit later, they do not enhance the loudness inside the critical bands in such a strong way, but the directional cues become unstable, because there is a mix of sound of several reflection directions. As a result, no new directional analysis is triggered by the auditory system.

This first detected direction from the direct sound is taken as the found sound source direction, until other strong loudness attacks, combined with stable directional information, indicate that a new directional analysis is possible. (see Franssen effect)

Specific techniques with applications

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Auditory transmission stereo system

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This kind of sound localization technique provides us the real virtual stereo system.[26] It utilizes "smart" manikins, such as KEMAR, to glean signals or use DSP methods to simulate the transmission process from sources to ears. After amplifying, recording and transmitting, the two channels of received signals will be reproduced through earphones or speakers. This localization approach uses electroacoustic methods to obtain the spatial information of the original sound field by transferring the listener's auditory apparatus to the original sound field. The most considerable advantages of it would be that its acoustic images are lively and natural. Also, it only needs two independent transmitted signals to reproduce the acoustic image of a 3D system.

Sound localization with manikin

3D para-virtualization stereo system

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The representatives of this kind of system are SRS Audio Sandbox, Spatializer Audio Lab and Qsound Qxpander.[26] They use HRTF to simulate the received acoustic signals at the ears from different directions with common binary-channel stereo reproduction. Therefore, they can simulate reflected sound waves and improve subjective sense of space and envelopment. Since they are para-virtualization stereo systems, the major goal of them is to simulate stereo sound information. Traditional stereo systems use sensors that are quite different from human ears. Although those sensors can receive the acoustic information from different directions, they do not have the same frequency response of human auditory system. Therefore, when binary-channel mode is applied, human auditory systems still cannot feel the 3D sound effect field. However, the 3D para-virtualization stereo system overcome such disadvantages. It uses HRTF principles to glean acoustic information from the original sound field then produce a lively 3D sound field through common earphones or speakers.

Multichannel stereo virtual reproduction

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Since the multichannel stereo systems require many reproduction channels, some researchers adopted the HRTF simulation technologies to reduce the number of reproduction channels.[26] They use only two speakers to simulate multiple speakers in a multichannel system. This process is called as virtual reproduction. Essentially, such approach uses both interaural difference principle and pinna filtering effect theory. Unfortunately, this kind of approach cannot perfectly substitute the traditional multichannel stereo system, such as 5.1/7.1 surround sound system. That is because when the listening zone is relatively larger, simulation reproduction through HRTFs may cause invert acoustic images at symmetric positions.

Animals

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Since most animals have two ears, many of the effects of the human auditory system can also be found in other animals. Therefore, interaural time differences (interaural phase differences) and interaural level differences play a role for the hearing of many animals. But the influences on localization of these effects are dependent on head sizes, ear distances, the ear positions and the orientation of the ears. Smaller animals like insects use different techniques as the separation of the ears are too small.[27] For the process of animals emitting sound to improve localization, a biological form of active sonar, see animal echolocation.

Lateral information (left, ahead, right)

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If the ears are located at the side of the head, similar lateral localization cues as for the human auditory system can be used. This means: evaluation of interaural time differences (interaural phase differences) for lower frequencies and evaluation of interaural level differences for higher frequencies. The evaluation of interaural phase differences is useful, as long as it gives unambiguous results. This is the case, as long as ear distance is smaller than half the length (maximal one wavelength) of the sound waves. For animals with a larger head than humans the evaluation range for interaural phase differences is shifted towards lower frequencies, for animals with a smaller head, this range is shifted towards higher frequencies.

The lowest frequency which can be localized depends on the ear distance. Animals with a greater ear distance can localize lower frequencies than humans can. For animals with a smaller ear distance the lowest localizable frequency is higher than for humans.

If the ears are located at the side of the head, interaural level differences appear for higher frequencies and can be evaluated for localization tasks. For animals with ears at the top of the head, no shadowing by the head will appear and therefore there will be much less interaural level differences which could be evaluated. Many of these animals can move their ears, and these ear movements can be used as a lateral localization cue.

In the median plane (front, above, back, below)

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For many mammals there are also pronounced structures in the pinna near the entry of the ear canal. As a consequence, direction-dependent resonances can appear, which could be used as an additional localization cue, similar to the localization in the median plane in the human auditory system. There are additional localization cues which are also used by animals.

Head tilting

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For sound localization in the median plane (elevation of the sound) also two detectors can be used, which are positioned at different heights. In animals, however, rough elevation information is gained simply by tilting the head, provided that the sound lasts long enough to complete the movement. This explains the innate behavior of[vague] cocking the head to one side when trying to localize a sound precisely. To get instantaneous localization in more than two dimensions from time-difference or amplitude-difference cues requires more than two detectors.

Localization with coupled ears (flies)

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The tiny parasitic fly Ormia ochracea has become a model organism in sound localization experiments because of its unique ear. The animal is too small for the time difference of sound arriving at the two ears to be calculated in the usual way, yet it can determine the direction of sound sources with exquisite precision. The tympanic membranes of opposite ears are directly connected mechanically, allowing resolution of sub-microsecond time differences[28][29] and requiring a new neural coding strategy.[30] Ho[31] showed that the coupled-eardrum system in frogs can produce increased interaural vibration disparities when only small arrival time and sound level differences were available to the animal's head. Efforts to build directional microphones based on the coupled-eardrum structure are underway.

Bi-coordinate sound localization (owls)

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Most owls are nocturnal or crepuscular birds of prey. Because they hunt at night, they must rely on non-visual senses. Experiments by Roger Payne[32] have shown that owls are sensitive to the sounds made by their prey, not the heat or the smell. In fact, the sound cues are both necessary and sufficient for localization of mice from a distant location where they are perched. For this to work, the owls must be able to accurately localize both the azimuth and the elevation of the sound source.

Dolphins

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Dolphins (and other odontocetes) rely on echolocation to aid in detecting, identifying, localizing, and capturing prey. Dolphin sonar signals are well suited for localizing multiple, small targets in a three-dimensional aquatic environment by utilizing highly directional (3 dB beamwidth of about 10 deg), broadband (3 dB bandwidth typically of about 40 kHz; peak frequencies between 40 kHz and 120 kHz), short duration clicks (about 40 μs). Dolphins can localize sounds both passively and actively (echolocation) with a resolution of about 1 deg. Cross-modal matching (between vision and echolocation) suggests dolphins perceive the spatial structure of complex objects interrogated through echolocation, a feat that likely requires spatially resolving individual object features and integration into a holistic representation of object shape. Although dolphins are sensitive to small, binaural intensity and time differences, mounting evidence suggests dolphins employ position-dependent spectral cues derived from well-developed head-related transfer functions, for sound localization in both the horizontal and vertical planes. A very small temporal integration time (264 μs) allows localization of multiple targets at varying distances. Localization adaptations include pronounced asymmetry of the skull, nasal sacks, and specialized lipid structures in the forehead and jaws, as well as acoustically isolated middle and inner ears.

The role of Prestin in sound localization:

In the realm of mammalian sound localization, the Prestin gene has emerged as a pivotal player, particularly in the fascinating arena of echolocation employed by bats and dolphins. Discovered just over a decade ago, Prestin encodes a protein located in the inner ear's hair cells, facilitating rapid contractions and expansions. This intricate mechanism operates akin to an antique phonograph horn, amplifying sound waves within the cochlea and elevating the overall sensitivity of hearing.

In 2014 Liu and others delved into the evolutionary adaptations of Prestin, unveiling its critical role in the ultrasonic hearing range essential for animal sonar, specifically in the context of echolocation. This adaptation proves instrumental for dolphins navigating through turbid waters and bats seeking sustenance in nocturnal darkness.[33]

Noteworthy is the emission of high-frequency echolocation calls by toothed whales and echolocating bats, showcasing diversity in shape, duration, and amplitude. However, it is their high-frequency hearing that becomes paramount, as it enables the reception and analysis of echoes bouncing off objects in their environment. A meticulous dissection of Prestin protein function in sonar-guided bats and bottlenose dolphins, juxtaposed with nonsonar mammals, sheds light on the intricacies of this process.

Evolutionary analyses of Prestin protein sequences brought forth a compelling observation – a singular amino acid shift from threonine (Thr or T) in sonar mammals to asparagine (Asn or N) in nonsonar mammals. This specific alteration, subject to parallel evolution, emerges as a linchpin in the mammalian echolocation narrative.[33]

Subsequent experiments lent credence to this hypothesis, identifying four key amino acid distinctions in sonar mammals that likely contribute to their distinctive echolocation features. The confluence of evolutionary analyses and empirical findings provides robust evidence, marking a significant juncture in comprehending the Prestin gene's role in the evolutionary trajectory of mammalian echolocation systems. This research underscores the adaptability and evolutionary significance of Prestin, offering valuable insights into the genetic foundations of sound localization in bats and dolphins, particularly within the sophisticated realm of echolocation.[33]

History

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The term 'binaural' literally signifies 'to hear with two ears', and was introduced in 1859 to signify the practice of listening to the same sound through both ears, or to two discrete sounds, one through each ear. It was not until 1916 that Carl Stumpf (1848–1936), a German philosopher and psychologist, distinguished between dichotic listening, which refers to the stimulation of each ear with a different stimulus, and diotic listening, the simultaneous stimulation of both ears with the same stimulus.[34]

Later, it would become apparent that binaural hearing, whether dichotic or diotic, is the means by which sound localization occurs.[34][35][page needed]

Scientific consideration of binaural hearing began before the phenomenon was so named, with speculations published in 1792 by William Charles Wells (1757–1817) based on his research into binocular vision.[36] Giovanni Battista Venturi (1746–1822) conducted and described experiments in which people tried to localize a sound using both ears, or one ear blocked with a finger. This work was not followed up on, and was only recovered after others had worked out how human sound localization works.[34][36] Lord Rayleigh (1842–1919) would do these same experiments and come to the results, without knowing Venturi had first done them, almost seventy-five years later.[36]

Charles Wheatstone (1802–1875) did work on optics and color mixing, and also explored hearing. He invented a device he called a "microphone" that involved a metal plate over each ear, each connected to metal rods; he used this device to amplify sound. He also did experiments holding tuning forks to both ears at the same time, or separately, trying to work out how sense of hearing works, that he published in 1827.[36] Ernst Heinrich Weber (1795–1878) and August Seebeck (1805–1849) and William Charles Wells also attempted to compare and contrast what would become known as binaural hearing with the principles of binocular integration generally.[36]

Understanding how the differences in sound signals between two ears contributes to auditory processing in such a way as to enable sound localization and direction was considerably advanced after the invention of the stethophone by Somerville Scott Alison in 1859, who coined the term 'binaural'. Alison based the stethophone on the stethoscope, which had been invented by René Théophile Hyacinthe Laennec (1781–1826); the stethophone had two separate "pickups", allowing the user to hear and compare sounds derived from two discrete locations.[36]

See also

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References

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Revisions and contributorsEdit on WikipediaRead on Wikipedia
from Grokipedia
Sound localization is the ability of the to determine the spatial position of a source in three-dimensional space, a fundamental perceptual process essential for survival, communication, and interaction with the environment in mammals including humans. This capability relies on the integration of acoustic cues arising from the interaction of sound waves with the head, external ears (pinnae), and , enabling precise of direction with angular resolutions as fine as 1–2° in the horizontal () plane and 4–5° in the vertical () plane under optimal listening conditions. The primary mechanisms of sound localization involve binaural cues, which exploit the separation between the two ears, and monaural cues, which depend on the filtering effects of the listener's on a single ear. Binaural cues include interaural time differences (ITDs), where sounds arrive at the ears with timing disparities of up to about 700 μs for azimuthal positions (most effective for frequencies below 1.5 kHz), and interaural level differences (ILDs), where head shadowing creates intensity disparities of up to 20 dB (most effective for frequencies above 4 kHz). Monaural cues, such as those encoded in the (HRTF), provide spectral shaping by the pinnae and head, which is crucial for resolving elevation and front-back ambiguities, particularly through frequency-dependent notches and peaks in the sound spectrum. Additional factors like sound source are inferred from cues such as direct-to-reverberant ratios, though humans tend to overestimate distances below 1 m and underestimate them beyond. At the neural level, sound localization is computed through specialized circuits that process these cues in parallel pathways. ITDs are primarily encoded via coincidence detection neurons in the medial superior olive (MSO), which fire maximally when excitatory inputs from both ears align temporally, while ILDs are processed through excitatory-inhibitory interactions in the lateral superior olive (LSO). Spectral cues are analyzed in the dorsal cochlear nucleus and further refined in the , with integration across these structures enabling a unified spatial percept in the . Performance can vary with factors like sound frequency bandwidth, listener age, and acoustic environment, with broadband noise yielding the highest accuracy, and illusions such as the influencing perceived location in reverberant spaces. These mechanisms not only underpin natural auditory behavior but also inform applications in audio, hearing aids, and devices for the hearing impaired.

Fundamentals

Definition and perceptual importance

Sound localization refers to the perceptual process by which the determines the position of a sound source in , utilizing auditory cues to estimate direction and . This ability enables listeners to construct a spatial of their acoustic environment, distinguishing sounds from multiple sources and enhancing overall auditory scene analysis. The perceptual importance of sound localization lies in its contribution to spatial awareness and everyday functioning, such as identifying the direction of a speaker during conversations or orienting toward unexpected noises for . It supports critical survival mechanisms, including predator detection and prey tracking in natural settings, while also facilitating with vision to refine spatial perceptions and improve reaction times to events. From an evolutionary perspective, sound localization provided adaptive advantages to early mammals, particularly nocturnal species, by allowing precise orientation toward opportunities or threats in low-visibility environments, thereby increasing survival rates. A notable perceptual illusion illustrating this capability is the , where the brain suppresses echoes following a direct sound, enabling accurate localization of the despite reverberant conditions.

Acoustic principles and cues

Sound waves propagate through air as pressure variations that create alternating regions of compression and , enabling the transmission of acoustic energy from a source to a listener. When a sound source is off to one side, the acts as an obstacle, producing a head shadow effect that and the wave, particularly for higher frequencies where wavelengths are shorter than the head's diameter (approximately 18-22 cm). This obstruction reduces the intensity of the sound reaching the contralateral , with attenuation increasing for frequencies above 1500 Hz, as the head blocks direct paths and limits diffraction around its curvature. The torso and shoulders further influence propagation by reflecting and scattering lower-frequency waves, altering the overall acoustic field before the sound reaches the ears. The head-related transfer function (HRTF) quantifies these filtering effects, representing the acoustic transfer from a free-field sound source to a point in the ear canal as a function of source direction and distance. HRTFs incorporate frequency-dependent , where the head, pinnae, and selectively amplify or suppress spectral components—for instance, creating notches and peaks that vary with and due to constructive and destructive interference. Additionally, HRTFs introduce phase shifts, which manifest as time delays in the arrival at each ear, contributing to spatial encoding without assuming biological processing. Acoustic cues for localization fall into two broad categories: interaural cues, which arise from differences between the two ears, and monaural cues, which rely on spectral shaping at a single ear. Interaural cues include the interaural time difference (ITD), the microsecond-scale delay in sound onset between ears due to the ~21 cm interaural distance (maximum ITD ≈ 650 μs for azimuthal angles), effective primarily for low frequencies below 1500 Hz where phase ambiguities are minimal; and the interaural level difference (ILD), an intensity disparity (up to 20 dB for high frequencies) stemming from head shadowing, dominant for frequencies above 1500 Hz. Monaural cues, embedded in the HRTF, involve direction-specific spectral alterations, such as pinna-induced resonances that provide elevation information through frequency notches varying by angle. In real-world environments, acoustic reflections from surfaces introduce reverberation, which complicates localization by superimposing delayed echoes onto the direct sound path, thereby smearing ITD and ILD cues over time. This degradation is most pronounced beyond the initial 0-50 ms after sound onset, where direct sound dominates, leading to reduced directional accuracy compared to anechoic conditions that eliminate reflections for pristine cue isolation. Reverberation's diffuse energy buildup compresses spatial sensitivity, though early-arriving reflections can sometimes enhance perceived source position via precedence effects in moderate rooms.

Human Mechanisms

Binaural cues

Binaural cues exploit the differences in timing and intensity between the sound signals received at the two ears to enable localization primarily in the horizontal plane. The foundational duplex theory, formulated by Lord Rayleigh in 1907, explains this process by distinguishing between low-frequency sounds, where interaural time differences (ITD) predominate, and high-frequency sounds, where interaural level differences (ILD) become the primary cue. This model highlights how the human auditory system leverages these interaural disparities to estimate azimuth angles, with ITD effective below approximately 1.5 kHz and ILD above that threshold. The ITD represents the delay in sound arrival between the ears due to the path length difference caused by the head's separation. For a sound source at an azimuth angle θ relative to the head's midline, the ITD τ is calculated as τ=dsinθc,\tau = \frac{d \sin \theta}{c}, where d is the interaural (approximately 21 cm in humans) and c is the (343 m/s at standard conditions). This yields a maximum ITD of roughly 610 μs for a lateral source at θ = 90°, allowing discrimination of angular positions with thresholds as fine as 10 μs. At low frequencies, where wavelengths exceed the head diameter, ITDs manifest as interaural phase differences, but these introduce phase ambiguity since a given phase shift could correspond to multiple actual time delays differing by the signal's period. detection in binaural neurons resolves this by comparing ongoing phase-locked inputs from both ears to identify the true ITD. ILD arises from the acoustic shadowing effect of the head, which obstructs and diffracts sound waves more effectively at higher frequencies, reducing intensity at the far (contralateral) ear. For frequencies above 1.5 kHz, this attenuation can produce ILDs up to 20 dB for azimuths near 90°, with the difference increasing with frequency due to poorer diffraction around the head. Listeners can detect ILDs as small as 1 dB, enabling reliable horizontal localization where ITD sensitivity diminishes. Despite their efficacy in the horizontal plane, binaural cues have inherent limitations. They generate identical ITDs and ILDs for sound sources along the cone of confusion—a conical surface extending from the head where positions at different elevations but similar azimuths produce equivalent interaural differences. Additionally, front-back ambiguity persists because sources 180° apart in azimuth yield the same magnitude of ITD and ILD, though reversed in sign, requiring supplementary cues for disambiguation.

Monaural cues

Monaural cues in sound localization arise from the filtering effects of the head, pinna, and on incoming waves, providing directional information to a single without relying on interaural comparisons. These cues are particularly crucial for resolving and front-back ambiguities in the vertical plane. The pinna plays a central role by acting as a directional filter, introducing modifications that vary with sound source position. The pinna's filtering effect creates unique spectral notches and peaks in the (HRTF), which characterizes the acoustic path from a sound source to the . For , these notches typically occur in the 5–10 kHz range, with the center frequency shifting systematically: for instance, around 6.5 kHz at -40° and increasing to about 10 kHz at +60° , while bandwidth varies from ~1 kHz at lower angles to ~4 kHz near horizontal. These high-frequency features enable the to discriminate vertical positions, as broadband sounds filtered by the pinna produce elevation-specific spectra that listeners match against internalized templates. reflections and effects contribute additional monaural cues, particularly at lower frequencies below 1 kHz, by diffracting and reflecting sound waves to alter the overall spectral shape and enhance sensitivity in the . HRTFs exhibit significant individual variations due to anatomical differences, especially in pinna shape, which directly influences the position and depth of spectral notches. For example, listeners with larger or differently shaped pinnae show distinct HRTF spectra, leading to localization errors of up to 28° in when using non-personalized HRTFs, compared to ~15° accuracy with individualized ones. These variations necessitate personalization in audio technologies, such as systems, where mismatched HRTFs cause front-back confusions and reduced vertical precision, emphasizing the need for subject-specific measurements or modeling based on anthropometric data.

Distance and environmental cues

Sound localization relies on several acoustic cues to estimate the distance of a sound source, beyond directional information. One primary cue is the intensity of the , which decreases with according to the , where sound intensity II is proportional to 1/r21/r^2 (with rr as the from the source), resulting in approximately a 6 dB reduction per doubling of in free-field conditions. This cue is relative, as listeners adjust for the expected of familiar sources, such as speech or footsteps, enabling discrimination thresholds of 5-25% of the reference , though accuracy diminishes without prior knowledge of source intensity. Temporal cues further refine distance estimation through the direct-to-reverberant (DRR), the energy ratio of the direct path to the reverberant reflections from room surfaces. As increases, the direct sound attenuates more rapidly (6 dB per doubling) compared to the relatively stable reverberant , lowering the DRR and signaling greater separation; this provides an absolute indicator, particularly indoors. Human sensitivity to DRR changes yields just-noticeable differences (JNDs) of 2-8 dB, with optimal performance when combined with intensity cues, though discrimination is poorest at low DRR values corresponding to far . High-frequency attenuation due to air absorption serves as another distance cue, disproportionately affecting components above 8 kHz over distances exceeding 15 m, where molecular relaxation and viscosity cause greater energy loss in higher frequencies than in lower ones. This spectral filtering alters the sound's , making distant sources appear duller and thus farther away, even at shorter ranges if the source inherently lacks high frequencies; experimental evidence shows listeners perceive low-pass filtered sounds as more remote, enhancing judgments in open environments. Environmental factors, such as room acoustics, modulate these cues and overall localization accuracy. Reverberation time (T60, the time for sound to decay by 60 dB) influences perceived distance, with longer times (e.g., 2 s) causing underestimation of near sources and overestimation of far ones due to increased reflection overlap, while shorter times (e.g., 1 s) preserve cue clarity. Room size affects DRR similarly, as larger spaces dilute direct energy relative to reflections, elevating localization errors by up to 20-30% in highly reverberant settings; the Haas effect (or ) mitigates this by suppressing echoes arriving within 5-35 ms of the direct sound, prioritizing the first for source positioning and reducing confusion from . These factors highlight how enclosed environments can both aid (via DRR) and hinder (via distortion) precise depth estimation.

Neural Processing

Auditory pathway to the brain

The peripheral begins with waves entering the through the pinna and external auditory canal, which direct them to the tympanic membrane. Vibrations of the tympanic membrane are transmitted via the —the , , and —to the oval window of the , amplifying the mechanical energy by approximately 20-30 times to overcome impedance mismatch between air and cochlear fluid. In the , these vibrations create traveling waves along the basilar membrane within the scala media, where inner and outer hair cells in the transduce mechanical stimuli into electrical signals through deflection, releasing neurotransmitters onto neurons. These neurons form the (cranial nerve VIII), conveying action potentials from the to the . The auditory nerve fibers project ipsilaterally to the in the dorsal and ventral pons-medulla junction, the first central relay station, where neurons segregate into pathways preserving timing and spectral information. From the , axons ascend via the trapezoid body and dorsal acoustic stria to the (SOC) in the caudal , enabling initial binaural comparisons such as interaural time and level differences for sound localization. SOC efferents, along with direct projections from the , form the , which synapses in the of the , a key integration hub for ascending auditory inputs from both ears. The sends fibers through the brachium of the to the (MGN) in the , the principal thalamic relay for auditory signals, which organizes inputs into parallel ventral and dorsal divisions for spectral and temporal processing, respectively. projections terminate in the primary (A1) within Heschl's gyrus of the superior , where higher-order analysis occurs. Throughout this pathway, tonotopic organization is preserved, reflecting the cochlea's frequency-specific mapping: high frequencies activate the basal turn near the oval window, while low frequencies stimulate the apical turn, a maintained in the auditory nerve, nuclei, MGN, and A1 as spatially segregated bands. This ensures efficient representation of spectra, foundational for localization cues like interaural differences.

Binaural integration and neural mechanisms

Binaural integration begins in the of the auditory , where neurons process interaural time differences (ITDs) and interaural level differences (ILDs) to encode sound azimuth. The medial superior olive (MSO) primarily handles ITD computation for low-frequency sounds, employing a network of coincidence-detecting neurons that fire when inputs from both ears arrive synchronously. This mechanism aligns with the duplex theory, which posits ITDs as dominant cues for low frequencies below approximately 1.5 kHz. The foundational Jeffress model proposes that MSO neurons act as coincidence detectors, receiving inputs via axonal delay lines that compensate for varying ITDs, creating a topographic map of sound location where the most active neuron indicates the sound's azimuthal position. Experimental evidence from mammals, including cats and gerbils, supports this, showing MSO neurons tuned to specific ITDs through precise temporal summation of excitatory inputs from the cochlear nuclei, with best frequencies typically under 2 kHz. Delay lines are implemented via axonal branching and synaptic delays, enabling sensitivity to microsecond-scale disparities up to the mammalian head width limit of about 600 μs. In parallel, the lateral superior olive (LSO) encodes ILDs, particularly for higher frequencies where phase ambiguity limits ITD utility. LSO principal neurons receive excitatory input from the ipsilateral and glycinergic inhibitory input from the contralateral side via the medial nucleus of the trapezoid body, forming an excitation-inhibition (E-I) balance that enhances sensitivity to level disparities. For instance, when is greater at the ipsilateral , excitation dominates, increasing firing rates, while contralateral precedence suppresses activity; this yields ILD tuning curves peaking at 5-20 dB, sufficient for localizing sources up to 90° . Such E-I interactions sharpen spatial selectivity, with LSO neurons showing rate-level functions that shift systematically with ILD magnitude. Higher-level integration occurs in the , where neurons construct spatial representations through a place code, with population activity patterns mapping sound locations across and . In the core auditory fields, such as A1, neurons exhibit spatial receptive fields tuned via convergence of subcortical inputs, often modulated by during active localization tasks, which narrows tuning widths by up to 30%. The (STS) facilitates , combining auditory spatial cues with visual inputs to refine perceived location, as evidenced by enhanced BOLD responses to congruent audiovisual stimuli and single-unit recordings showing bimodal neurons with reduced variance in spatial estimates. This cortical place code emerges from distributed activity, where decoding algorithms applied to neural populations achieve localization accuracies comparable to psychophysical thresholds of 1-5°. Neural interactions further shape binaural processing, with mechanisms in MSO neurons computing ITDs by integrating spike timings over short windows (5-10 ms), akin to a normalized cross-correlation function that maximizes at the perceived delay. This process underlies the Jeffress-like encoding but incorporates synaptic integration for robustness against noise. effects, however, modulate sensitivity; prolonged exposure to fixed ITDs causes a 20-50% reduction in MSO and LSO response rates over seconds to minutes, shifting best ITDs and potentially aiding in dynamic environments by preventing to static sources, though it temporarily impairs fine discrimination.

Comparative Biology

Localization in mammals

Mammals primarily rely on binaural cues such as interaural time differences (ITD) and interaural level differences (ILD) for azimuthal sound localization, similar to the duplex theory in humans but adapted to variations in head size and auditory ecology. In species with smaller heads, such as cats, the maximum ITD is limited to approximately 400 μs compared to 700 μs in humans, constraining the use of low-frequency ITD cues and shifting reliance toward higher-frequency ILD processing. This adaptation aligns with the duplex strategy but emphasizes ILD for smaller mammals, where ITD effectiveness diminishes below 1-2 kHz due to reduced interaural distances. Behavioral studies reveal variations in localization acuity across mammals, with rodents demonstrating errors around 12° in Norway rats, reflecting their dependence on ILD and spectral cues from small heads that limit ITD utility. In contrast, larger mammals like cats achieve finer acuity of about 5°, benefiting from moderately larger heads that enhance both ITD and ILD resolution near the midline. These differences underscore how head size influences the balance of cues, with smaller species compensating through heightened sensitivity to high frequencies above 50 kHz in some . Specialized adaptations appear in echolocating bats, which integrate Doppler shifts from echo returns to achieve precise localization beyond passive binaural cues. For instance, horseshoe bats (Rhinolophus ferrumequinum) use rapid pinna movements at speeds up to 2.2 m/s to generate Doppler shifts exceeding 300 Hz, encoding target direction into distinct time-frequency signatures that resolve up to a million potential directions. This active sensing complements ITD and ILD, enabling bats to detect fluttering prey with sub-degree accuracy in cluttered environments. Evolutionary trade-offs in pinna structure affect monaural spectral cues, with reduced mobility or size in subterranean mammals like blind mole rats leading to diminished elevation and front-back discrimination. These exhibit localization errors up to 180° and loss of high-frequency hearing (>3 kHz), prioritizing seismic detection over aerial sound localization in dark, enclosed habitats. In contrast, surface-dwelling mammals with mobile pinnae, such as cats, dynamically adjust spectral notches for enhanced vertical plane cues, illustrating adaptations tied to ecological demands.

Localization in birds and reptiles

Birds, particularly , exhibit sophisticated sound localization capabilities that rely on specialized anatomical and neural adaptations to process binaural cues in three-dimensional space. In the barn owl (Tyto alba), a model for avian auditory research, sound localization employs a bi-coordinate system where interaural time differences (ITDs) and interaural level differences (ILDs) are independently mapped to azimuthal and elevational coordinates. ITDs, which encode primarily the horizontal (azimuthal) position of a sound source, are processed in the medial superior olive (MSO), while ILDs, which primarily signal vertical (elevational) position, are computed in the lateral superior olive (LSO). These parallel pathways converge in the , forming topographic maps of auditory space that enable precise orienting responses. The barn owl's asymmetrical ears further enhance elevational localization by generating vertical disparities that contribute to both ITD and ILD cues. The left ear opening is positioned higher and directed downward, while the right ear is lower and directed upward, creating a vertical offset and differential acoustic filtering. This produces ITDs sensitive to , as sounds from above or below arrive at the ears with temporal offsets due to the height difference, supplementing the primary ILD-based elevational coding. Behavioral experiments demonstrate that these cues allow barn owls to localize sounds with errors as small as 2° in both and , far surpassing many other vertebrates. In contrast, reptilian sound localization is generally simpler and more limited, with a reliance on ILD cues and reduced binaural integration. Snakes, for instance, lack external ears and tympanic membranes, detecting airborne sounds primarily through , which constrains their ability to generate robust ITDs. Their auditory features a well-developed nucleus angularis (NA), associated with intensity processing and ILD computation, but proportionally small nucleus magnocellularis (NM) and nucleus laminaris (NL), indicating minimal central processing of temporal disparities. As a result, snakes exhibit ILD-dominant localization for substrate vibrations and airborne cues, with behavioral accuracy limited to broad directional rather than precise spatial mapping. Many birds, including , employ dynamic head tilting behaviors to resolve ambiguities in the median plane, where monaural cues alone are insufficient. By tilting the head during sound presentation, birds enhance binaural disparities, particularly ILDs from the facial ruff or head shape, allowing disambiguation of front-rear or elevational confusions. In barn owls, such movements align the asymmetrical ears optimally, amplifying cue reliability and improving localization accuracy in the vertical midline by up to 50% in simulated conditions. This behavioral strategy complements static anatomical cues, enabling effective hunting in low-light environments.

Localization in insects and aquatic animals

Insects have evolved specialized auditory systems to overcome the limitations of their small size, which restricts traditional binaural cues like interaural time differences (ITDs). Many species, particularly flies and moths, utilize internally coupled ears connected via tracheal tubes to enhance sensitivity to pressure differences between the ears. In the parasitoid fly Ormia ochracea, the tympanal membranes are mechanically coupled through a flexible cuticular , amplifying ITDs from an acoustic value of about 1.45 µs to 50–60 µs at frequencies near 5 kHz, corresponding to the calls of host crickets. This coupling allows the fly to detect and localize low-frequency sounds with directional precision despite its tiny interaural distance of less than 1 mm. Moths, conversely, employ similar interaural coupling via acoustic tracheae to achieve pressure-difference sensitivity for higher frequencies, enabling evasion of bat predation. In species like the pyralid moth Achroia grisella, the tracheal system connects the ears indirectly, creating asymmetric pressure gradients that peak in sensitivity at contralateral angles, tuned to frequencies of 70–130 kHz with optimal response around 100 kHz. This mechanism supports monaural directional cues, allowing moths to track or avoid sources by comparing internal pressure imbalances rather than relying solely on intensity differences up to 40 dB. Neural integration of these cues occurs in specialized auditory , though the primary processing emphasizes mechanical amplification over neural computation. Aquatic animals face unique challenges in sound localization due to the medium's properties, where sound travels faster (about 1500 m/s in water versus 343 m/s in air), minimizing ITDs even for larger heads. In dolphins, the head width of approximately 20 cm yields negligible ITDs (on the order of microseconds or less), limiting binaural processing and shifting reliance to monaural amplitude cues derived from head-related transfer functions (HRTFs). To compensate, dolphins transmit wideband echolocation clicks (centroid frequencies ~68–80 kHz, bandwidth ~38 kHz) via the melon, receiving echoes through jaw conduction where elastic waves propagate along the mandible to the inner ears, providing directional information from waveform distortions and reverberations. This biosonar system achieves resolutions of 0.9 cm for object discrimination at 0.7 m and detects spheres over 100 m, with minimum audible angles as fine as 0.7° in the median plane. Fish, lacking external ears, primarily detect the particle motion component of sound using inner ear otoliths and the lateral line system, which senses near-field vibrations over distances up to one body length. The otolithic organs act as vector detectors, comparing particle motion phases to localize far-field sounds via pressure gradients reradiated by the swim bladder, enabling directional responses like startle away from sources. In near-field scenarios, the lateral line neuromasts detect oscillatory flows and particle displacements, aiding short-range localization during behaviors such as nest guarding in species like the plainfin midshipman, though ablation studies indicate it refines rather than drives overall phonotaxis. Swim bladder inflation is crucial for pressure sensitivity, with deflated bladders reducing localization success to near zero in experimental trials.

Applications

Audio engineering and reproduction

In stereo audio systems, sound localization is primarily simulated using interaural time differences (ITD) and interaural level differences (ILD) through panning techniques, where the same is distributed between left and right channels with varying intensities to create virtual sound sources. These methods rely on panning laws, such as the sine/cosine law, which adjust gain levels according to sinusoidal functions to maintain perceived and positional accuracy across the horizontal plane; for instance, a source panned to 45 degrees might use gains proportional to sin(45°) and cos(45°) for the respective channels. This approach approximates natural binaural cues but is limited to frontal localization, with accuracy diminishing at extreme angles due to unequal distances from the listener. Binaural recording techniques enhance localization fidelity by capturing spatial audio using dummy head , which mimic human head and acoustics to record head-related transfer functions (HRTF). These artificial heads, equipped with at positions, preserve ITD, ILD, and spectral cues during recording, allowing playback over to deliver immersive 3D soundscapes as if the listener were present at the original scene. Developed since the late and refined in the with models like the KU 100, this method excels in headphone reproduction but requires precise head tracking for head movements to avoid front-back confusion. Multichannel audio formats, such as 5.1 and , extend localization to broader spatial coverage using vector-based amplitude panning (VBAP), a technique that positions virtual sources by solving gain vectors across multiple . In VBAP, the direction of a virtual source is decomposed into basis vectors from positions, enabling precise placement in 2D or 3D spaces without discrete channel assignments; for example, in a 5.1 setup, gains are calculated to balance contributions from front, surround, and channels for stable imaging. This method improves upon basic stereo panning by supporting arbitrary arrays, though it assumes equal distances and can introduce errors in non-ideal room acoustics. Ambisonics represents sound fields using spherical harmonics decomposition, encoding 3D audio as a set of signals that capture directional components up to a specified order for reproduction over arbitrary loudspeaker configurations. First-order Ambisonics provides basic horizontal and vertical localization, while higher-order variants (e.g., third or fourth order) increase spatial resolution and accuracy by incorporating more harmonics, reducing localization errors to under 10 degrees in perceptual tests. This approach excels in flexible decoding for immersive environments, prioritizing wavefront reconstruction over point-source simulation, and has been validated for superior sweet-spot performance compared to discrete multichannel systems.

Assistive technologies and virtual environments

Assistive technologies leverage sound localization principles to enhance spatial awareness for users with hearing impairments and to create immersive experiences in virtual and augmented environments. In virtual reality (VR) systems, head-tracked head-related transfer function (HRTF) rendering is employed to simulate three-dimensional audio by convolving sounds with individualized or generic HRTFs, allowing dynamic updates based on head orientation to produce realistic spatial cues. This approach significantly reduces front-back confusions, which can reach up to 30% in static binaural rendering, by incorporating interaural time differences (ITD) and level differences (ILD) that adjust with listener movement, thereby improving overall localization accuracy to levels approaching natural hearing. Studies demonstrate that such head-tracked systems enhance externalization and elevation perception, making virtual sound sources feel positioned in external space rather than inside the head. Hearing aids incorporate advanced to restore or amplify binaural cues for improved sound localization. microphones in bilateral hearing aids use directional arrays to enhance ITD and ILD by focusing on the signal from the intended direction while suppressing noise from other azimuths, achieving improvements of up to 10 dB without fully distorting spatial information. Bilateral fittings preserve natural binaural processing by sharing microphone signals across devices via links, enabling consistent ITD cues across frequencies and supporting better front-back discrimination compared to monaural aids. These techniques, often combined with adaptive , allow users to benefit from head movements for cue disambiguation, mimicking normal auditory behavior. In (AR), spatial audio overlays integrate virtual sound sources with real-world visuals to create cohesive multimodal experiences. These systems position audio relative to visual anchors using head-tracking and environmental mapping, ensuring sounds align with augmented objects for intuitive interaction. (WFS) is utilized in AR setups with loudspeaker arrays to reconstruct wavefronts that produce stable spatial images over extended areas, allowing multiple users to perceive localized audio without . This method supports dynamic overlays, such as navigational cues or interactive elements, by synthesizing ILD, ITD, and spectral cues that remain consistent as users move through mixed reality spaces. Hearing-impaired individuals often face reduced sound localization acuity due to high-frequency , which impairs spectral shape cues essential for and front-back discrimination, leading to errors up to 20-30 degrees larger than in normal-hearing listeners. High-frequency loss particularly affects ILD cues above 1.5 kHz, exacerbating performance in noisy or reverberant environments. Solutions like frequency transposition or lowering in hearing aids shift inaudible high-frequency components to lower, audible bands, potentially restoring access to these cues for better localization without introducing significant . Clinical evaluations indicate that such may provide benefits for localization in some users with severe high-frequency thresholds, though benefits vary with individual audiograms and require fine-tuning to avoid overlap with native low-frequency signals.

Clinical and research tools

Clinical and research tools for assessing sound localization encompass a range of psychophysical tests and techniques designed to quantify spatial hearing abilities and underlying neural processes. These tools are essential for diagnosing impairments and advancing research on auditory spatial processing. One primary method for evaluating localization acuity is the minimum audible angle (MAA) task, which measures the smallest angular separation between two sound sources that a listener can reliably discriminate. In MAA experiments, broadband noise bursts are presented from speakers separated by varying azimuths, typically in the horizontal plane, with thresholds often ranging from 1° to 3° for normal-hearing adults under optimal conditions. This task isolates directional sensitivity and has been adapted for clinical settings to detect deficits in patients with hearing impairments. Virtual acoustic spaces (VAS) further enhance these assessments by simulating free-field sounds over , allowing precise isolation of binaural cues like interaural time differences (ITDs) and interaural level differences (ILDs) without environmental confounds. VAS rendering uses individualized head-related transfer functions (HRTFs) to convolve stimuli, enabling controlled manipulation of spectral or temporal cues for targeted evaluation of cue-specific contributions to localization. Binaural hearing loss significantly degrades spatial hearing, as it disrupts the integration of ITDs and ILDs necessary for precise discrimination. Individuals with bilateral exhibit elevated MAA thresholds, often exceeding 10°, and reduced spatial release from masking, impairing speech intelligibility in noisy environments. Unilateral similarly compromises localization, forcing reliance on monaural cues, which results in errors biased toward the intact ear and overall accuracy dropping to around 20-30% in horizontal-plane tasks. These disorders highlight the brain's dependence on balanced binaural input, with long-term unilateral deprivation leading to weakened contralateral neural representations that persist even after auditory restoration. In neuroscience research, functional magnetic resonance imaging (fMRI) reveals cortical activation patterns during sound localization tasks, showing heightened activity in the posterior superior temporal gyrus and planum temporale for processing azimuthal cues. Active localization paradigms, where participants point to or vocalize sound positions, sharpen spatial tuning in primary auditory cortex, with BOLD signals correlating to behavioral accuracy. Animal models complement these human studies through neural ablation techniques, such as targeted lesions in the inferior colliculus of barn owls or ferrets, which disrupt space-specific maps and confirm the role of midbrain nuclei in cue integration. For instance, electrolytic lesions in the owl's external nucleus of the inferior colliculus abolish topographic auditory responses, demonstrating causal links between subcortical structures and localization behavior. Recent advances since 2020 have leveraged for AI-based HRTF personalization, improving the fidelity of virtual simulations in both clinical diagnostics and research. Neural networks trained on anthropometric , such as ear shape and head dimensions, predict individualized HRTFs with notable reductions in spectral errors compared to generic models, enhancing localization accuracy in VAS tasks. Techniques like deep convolutional networks or transformers upsample sparse measurements to full-azimuth HRTFs, enabling scalable personalization for diverse populations and facilitating studies on cue variability in impaired listeners. As of 2024, approaches such as spherical neural processes have further reduced interpolation errors by up to 3 dB relative to prior methods.

Historical Development

Early theories and experiments

Early observations of sound directionality date back to philosophers, who expressed interest in how sounds propagate and are perceived in space, laying philosophical groundwork for later scientific inquiry. In the , conducted pioneering binaural experiments to explore sound localization. Using a device with adjustable speaking tubes connected to each ear, Wheatstone demonstrated that interaural time differences (ITDs) allow listeners to perceive the direction of a sound source. By introducing small delays—on the order of milliseconds—between the sounds reaching each ear, he showed that participants could accurately localize the apparent position of the sound, establishing ITD as a key cue for azimuthal localization in the horizontal plane. Lord Rayleigh formalized these ideas in his 1907 duplex of sound localization, proposing that the human relies on two primary cues depending on : phase (or time) differences for low frequencies and intensity differences for high frequencies. He formulated the as follows: at low pitches (below approximately 256 Hz), localization is achieved through interaural phase differences, while at high pitches (above 512 Hz), it depends on interaural intensity differences arising from the head's . Rayleigh validated this through experiments using tuning forks at specific frequencies, such as 128 Hz and 256 Hz for low-pitch tests and higher ones up to 768 Hz for intensity cues. In outdoor setups with eyes closed, participants easily discriminated right-left positions for low-frequency forks mounted at varying azimuths; indoor tests with paired forks confirmed that phase opposition produced a sensation of at the back of the head, while agreement localized it forward, supporting the 's predictions. In the mid-20th century, S.S. Stevens and E.B. Newman extended these foundations with empirical studies on localization accuracy in free-field conditions. Their 1936 experiments measured listeners' ability to localize pure tones across frequencies, revealing that performance was poorest around 2-3 kHz, where neither ITD nor interaural level difference (ILD) cues are optimally effective. They quantified ILD sensitivity indirectly through localization errors, finding that detectable ILDs were on the order of 1-2 dB for high frequencies above 5 kHz, confirming Rayleigh's intensity-based mechanism and establishing thresholds that informed subsequent models of binaural hearing.

Modern computational models

Refinements to the Jeffress model, originally proposed in 1948, have extended its applicability to more complex acoustic scenarios beyond narrowband tones, incorporating mechanisms for wideband signals through multiple interaural time difference (ITD) maps and stochastic processing. In avian systems, such as chickens, the nucleus laminaris processes wideband signals via a single tonotopically organized ITD map with axonal delays tuned to different frequency bands, enabling robust localization across spectral ranges. Similarly, in barn owls, specialized neurons in the nucleus laminaris form multiple ITD maps along a dorsoventral axis, with sparse distributions optimizing sensitivity for wideband stimuli. In mammals like gerbils, stochastic implementations incorporate rate-based slope coding in the medial superior olive, where average spike rates influenced by probabilistic synaptic inputs detect ITDs without strict place coding, improving reliability in noisy environments. These extensions, developed from the 1980s onward, address limitations of the original model for broadband sounds by integrating probabilistic coincidence detection and frequency-specific delays. Computational models of head-related transfer functions (HRTFs) have advanced sound localization simulations by numerically modeling acoustic interactions with the head and torso, particularly through finite element methods that account for head . Finite element approaches reconstruct personalized 3D head models from photographic data using structure-from-motion techniques, then simulate sound propagation via adaptive rectangular decomposition and Kirchhoff surface integrals to compute HRTFs efficiently, reducing processing time to about 20 minutes on standard hardware while capturing scattering effects from pinnae and shoulders. This enables accurate replication of spectral cues like interaural level differences (ILDs) and pinna notches, essential for elevation perception. such as the CIPIC HRTF database, containing measurements for 45 subjects across 1250 directions with corresponding anthropometric data, facilitate personalization by correlating physical traits (e.g., head width, pinna shape) with HRTF variations, such as ITD ranges from 635 to 755 µs. These resources support model training for individualized virtual auditory displays, minimizing localization errors in applications like . Machine learning approaches since the 2010s have integrated neural networks to predict sound localization from binaural audio features, effectively handling individual variability in HRTFs without exhaustive measurements. Deep neural networks (DNNs) trained on virtual environments with simulated human ears achieve high localization accuracy by learning ITD and ILD patterns from raw waveforms, outperforming traditional models in reverberant conditions with errors below 10° . For , convolutional neural networks (CNNs) use anthropometric inputs alongside generic HRTFs to generate subject-specific transfer functions, reducing spectral mismatch and improving localization by up to 20% compared to non-individualized models. These methods address variability through and clustering of binaural features, enabling robust predictions across diverse head shapes as seen in databases like CIPIC. Recent multi-stage models combine sparse coding with DNNs to mimic processing, further enhancing precision in dynamic scenes. More recent advances from 2020 to 2025 have built on these foundations with biologically inspired that incorporate tonotopic organization and synaptic connections to simulate human-like ITD detection, achieving accuracies rivaling biological systems in noisy environments. Multi-stage computational models emulate the auditory pathway for binaural localization, integrating low-level feature extraction with higher-order integration for improved performance in reverberant settings. Additionally, techniques like SoundLoc3D enable invisible 3D sound source localization using on RGB-D data, demonstrating robustness in real-world scenarios as of 2025.

References

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