binaural auditory processing in multiple sclerosis subjects

Hearing Research, 68 (1993159-72

0 1993 Elsevier Science Publishers B.V. All rights reserved 0378-5955/93/$06.00 SY

HEARES 01931

Binaural auditory processing in multiple sclerosis subjects *

R.A. Levine a.h-c, J.C. Gardner a.d, S.M. Stufflebeam a-C, B.C. Fullerton ‘I.‘, E.W. Carlisle ‘I, M. Furst a,e, B.R. Rosen b,c and N.Y.S. Kiang a,h,c.d

* Massachusetts Eye and Ear Infirmary, ’ Massachusetts General Hospital. ’ Harc,ard Medical School, Boston. ‘I Muvsachusrtts Institute of Technology, Cambridge, Massachusrtts, USA and ’ Tel Al,il, Uniwrsity, Tel AGc, 69Y78x I.srarl

(Received 13 June 1992; Revision received 27 January 1993; Accepted 3 February lY931

In order to relate human auditory processing to physiological and anatamical experimental animal data, we have examined the interrelation-

ships between behavioral, electrophysiological and anatomical data obtained from human subjects with focal brainstem lesions. Thirty-eight

subjects with multiple sclerosis were studied with tests of interaural time and level discrimination (just noticeable differences or jndsl, brainstem

auditory evoked potentials and magnetic resonance (MR) imaging Interaural testing used two types of stimuli, high-pass t > 4000 HL) and

low-pass ( < 1000 Hz) noise bursts. Ahnormal time jnds (Tjndl were far more common than abnormal level jnds (70” < vs 1 1’7 ); especially for the

high-pass (Hpl noise (70% abnormal vs 40% abnormal for low-pass (Lpi noise). The HpTjnd could be abnormal with no other abnormalities;

however, whenever the BAEPs. LpTjnd and/or level jnds were abnormal HpTjnd was always abnormal. Ahnormal wave III amplitude was

associated with abnormalities in both time jnds, but abnormal wave III latency with only abnormal HpTjnds. Abnormal wave V amplitude. when

unilateral, was associated with a major HpTjnd abnormality, and. when bilateral. with both HpTjnd and LpTjnd major abnormalities.

Sixteen of the subjects had their MR scans obtained with a uniform protocol and could he analyzed with objective criteria. In all four subjects

with lesions involving the pontine auditory pathway, the BAEPs and both time jnds were abnormal. Of the twelve subjects with no lesions

involving the pontine auditory pathway, all had normal BAEPs and level jnds. ten had normal LpTjnds. but only five had normal HpTjnds.

We conclude that interaural time discrimination is closely related to the BAEPs and is dependent upon the stimulus spectrum. Redundant

encoding of low-frequency sounds in the discharge patterns of auditory neurons, may explain why the HpTjnd is a better indicator of neural

desynchrony than the LpTjnd. Encroachment of MS lesions upon the pontine auditory pathway always is associated with ahnormal BAEPs and

abnormal interaural time discrimination hut may have normal interaural level discrimination. Our data provide one of the most direct

demonstrations in humans of relationships among auditory performance. evoked potentials and anatomy. We present a model showing that many

of these interrelationships can he readily interpreted using ideas developed from work on animals, even though these relationships could not

have been predicted with confidence beforehand. This work provides a clear advance in our understanding of human auditon, processing and

should serve as a basis for future studies.

Brainstem auditory evoked potentials: Sound lateralization; Multiple sclerosis; Magnetic resonance imaging; Interaural discrimination

Introduction

In an earlier study, Hausler and Levine (1980) found that deficits in binaural timing discrimination were related to abnormalities in brainstem auditory evoked potentials (BAEPs) for a group of patients with multiple sclerosis (MS). MS is a common neurologic disorder, characterized by multifocal lesions of the nervous system. It is thought to be an immune-mediated in- flammatory disease directed toward the myelin of the oligodendroglia in the central nervous system. The

effect upon central nervous system dysfunction is

Correspondenw to: Robert A. Levine, Eaton-Peabody Laboratory,

Massachusettss Eye and Ear Infirmary, 243 Charles Street, Boston,

MA 02114. Fax: (6171 720-4408.

* This investigation has been performed in accordance with the

principles of the Declaration of Helsinki.

thought to relate principally to the effect upon myelin, which provides the electrical insulation between the nodes of an axon that enables saltatory conduction along the axon (Waxman and Bennett, 1972). It has been observed clinically, that functional losses can be followed by recovery within a few days. This suggests that, besides demyelination, more acute factors such as edema may sometimes play a role in the dysfunction of MS (Newcombe et al., 1991). Slower recovery from an attack may result from remyelination (Prineas et al., 1984). Finally, neuropathologic studies reveal that in

long standing lesions, axonal loss may occur with associated Wallerian degeneration (Lumsden et al.. 1970).

Because MS lesions can occur virtually anywhere in the white matter of the central nervous system, the specific behavioral symptoms will depend upon the sites of lesions. Thus, it is possible to find patients with focal lesions encroaching upon all parts of the auditory pathways. In 1980 it was not feasible to correlate lesion

sites with psychophysical and electrophysiological data, because the lesions could not be located directly in living subjects. Since then MS lesions have become identifiable through magnetic resonance (MR) imaging (Young et al., 19811, so we decided to revisit the study of human auditory information processing in MS subjects. Among the issues we wanted to explore were: 1) How BAEP waveforms are related to psychophysical performance with more rigorous definitions of abnormality; 2) Whether the apparent dissociation between performance on interaural level tests from performance on interaural timing tests holds for both high- and low- frequency stimuli; 3) How locations of MS lesions correlate with both BAEPs and with psychophysical test results, and 4) How brainstem activity interacts with mechanisms at higher levels of the brain to determine performance on the psychophysical tests.

Methods

MR scans, psychophysical testing, and electrophysiological testing were obtained on thirty-eight subjects (33 females, 5 males; ages from 25 to 57) with the clinical diagnosis of multiple sclerosis. Subjects were recruited from MS patients of the Massachusetts Gen- eral Hospital and from a local MS self-help group. Most of the subjects have had this diagnosis for several years and were taking no medications. No subjects were recruited who reported having a significant hearing loss.

Thirty neurologically normal adults served as controls for the MR scans. Seventeen neurologically and audiometrically normal adults served as control subjects for the psychophysical testing and thirteen for the electrophysiological testing. Eight of the normal subjects participated in all three tests.

Psychophysical testing The psychophysical and electrophysiological tests

were usually done in that order during the same session and typically within three weeks of the MR scan (longest interval 45 days). All testing was done in a ‘sound-proofed’ electrically shielded chamber. First, audiograms were obtained for each ear using TDH-39 earphones. For binaural testing, the ability to make interaural time and level discriminations was measured with respect to a centered (diotic) reference. Tests were run for two spectrally different stimuli, since the responses of auditory nerve fibers phase-lock to the envelope and fine-structure of low-frequency sounds but only to the envelope of high-frequency sounds. The subjects were tested using a low-frequency sound (low- pass filtered noise bursts (20-1000 Hz, 100 dB per

octave cut-offs)) as well as a high-frequency sound (high-pass filtered noise bursts (4000-20000 Hz)). The noise bursts, delivered by Sennheiser HD424 head- phones, were 275 ms long, with a 10 ms rise-fall time and a cos’ envelope.

A computer-controlled, two-alternative, two-interval, forced-choice tracking paradigm was used to determine an interaural time jnd. A single trial consisted of two pairs of noise bursts. The first pair was the reference stimulus (65 dB HL) and the second pair the test stimulus. The two noise bursts of each pair were separated by 275 ms, while 800 ms separated the two pairs of noise bursts. The first pair of reference noise bursts were always presented identically at the two earphones. The second pair of test noise bursts were identical at the two ears except that the time of arrival of the noise bursts at one of the earphones was delayed (range lo-1280 ps.1. Both the envelope and fine structure of the noise burst were delayed. The subject’s task was to press a button to indicate whether the test stimulus appeared to be displaced toward the right or left of the reference. Feedback (a colored light) was provided to indicate whether the response was correct or not for each trial. The ear receiving the delayed noise bursts was randomized with each trial. For each interaural time difference four trials were presented. If all four were correct, the time difference for the next trial was made smaller. If two or more were incorrect, the time difference was made larger. If one of the four was incorrect, four more trials were presented with the same time difference. If one of four was still incorrect, then the time difference was made larger. A turn- around was defined as changing the direction of the time differences from becoming smaller to becoming larger or larger to smaller. Testing was stopped after the sixth turn-around. The jnd was defined as the mean of all the time differences tested after the first turn- around. Initially, the interaural time difference was set at 1280 pus and was decreased by 50%; after the first turn-around, interaural time differences were changed by 20%.

Interaural level jnds were measured in a similar way. For level jnds, only the level at one ear was either increased or decreased (range 0.25 to 10 dB). The ear having the level changed from 65 dB HL was randomized with each trial, as was the direction of the level change. The initial level difference was 10 dB. At the start, interaural level differences were decreased by 50%; after the first turn-around, interaural level differences were changed by 25%.

The order of measuring the four jnds was as follows: high-pass level jnd (HpL jnd), low-pass level jnd (LpL jnd), low-pass time jnd (LpT jnd), and high-pass time jnd (HpT jnd). This order was chosen because the level jnds could be done by all MS subjects, whereas for some MS subjects, the interaural time discrimination

tasks could not be performed above a chance level even at the maximum interaural delay our system could generate (1280 ps>. The inabihty of some subjects to do an interaural time discrimination task could not be attributed to their inability to use the testing method, because they had already performed above a chance level on the interaural level discrimination tests using the same testing paradigm. The mean jnds of normal control subjects for both high and low pass stimuli were computed and values greater than three standard deviations from these means were considered abnormal.

The written instructions to each subject were as follows: ‘You will be hearing four sounds. The first two will be exactly the same and the last two will be exactly the same. The first pair will sound like it is coming from somewhere near the middle of your head. The second pair will sound like it is coming from the side of the first. Your task is to indicate whether the second pair is coming from the right or left of the first pair. If you think the second pair is coming from the right of the first pair, then press the red button in your right hand. If you think the second pair is coming from the left of the first pair, then press the black button in your left hand. At first you should find the task relatively easy. Later on the task will become more difficult. At some point you will probably feel like you are guessing. In all cases you must respond with an answer even if you feel you are guessing. If your answer is correct the green light will flash; if your answer is wrong the red light will flash. If you have any questions at any time, just speak up and I will answer you. Do you have any questions now? If not, we will start’.

Electrophysiological testing The electrophysiological tests were always done im-

mediately following the psychophysical tests at the same session. The recording and analysis techniques for obtaining the brainstem auditory evoked potentials (BAEPs) have been previously described in detail (Fullerton et al., 1987). In brief, subjects lie supine with surface electrodes attached to each earlobe, the vertex, nape of the neck, and forehead (ground). Recordings were made from three pairs of electrodes: vertex{+ I- nape( - 1, vertex( + )-right earlobe( - ), and vertex{ + )- left earlobe( - ). The recording system bandwidth was l-3000 Hz (-3 dB cutoffs). Movement artifact rejection was employed. Responses were averaged over a 20 ms interval (8 ms prestimulus and 12 ms poststimulus), with a total of 256 sampling intervals of 80 ps duration each. The stimuli were 65 dB HL rarefaction clicks generated by ten per second, 30 pus pulses delivered to Sennheiser HD424 earphones. Typically, the responses to 5120 click presentations were averaged. The con- traiateral ear was masked with broad-band noise at 50 dB HL.

For amplitude and latency measurements, waveforms were factored off-line into high-pass (360-900 Hz, - 3 dB cutoffs) and Iow-pass components (20-190 Hz) by zero phase-shift digita filtering. A computer paradigm identified ‘significant’ peaks in the poststimulus period. A peak was ‘significant’ if it had a baseline-to-peak amplitude or peak-to-peak slope that was at least three standard deviations from the mean of the corresponding measure in the prestimutus interval, From a parabolic fit to the peak and its two neighbor- ing data points, the baseline-to-peak amplitude and latency of the peak was determined (Furst et al., 1985). Jewett and Williston’s convention (1971) will be used to refer to the waves of the high-pass BAEPs. The large vertex-positive peak of the low-pass BAEPs, that occurs at about the same time as wave V in normal subjects (Fullerton et al., 19871, will be referred to as L. Because waves II, IV, and VI may be undetectable in normal subjects (Levine et al., 1993), we have re- stricted our analysis to waves I, III, V, and L. Based on the fact that BAEP amplitudes and latencies are normally distributed (Thornton, 197S), parametric statistical measures were used to define normality of a peak. A positive peak latency or interpeak interval from an MS subject’s waveform was considered abnormal if its value exceeded the mean value from the control subjects by more than three standard deviations for at least two of the three recording electrode configurations. For the one subject (No. 607, right ear) with a prolonged wave I, only interpeak intervals and not absolute latencies were used in evaluating the timing of the later waves. The amplitude of wave III, V, or L was considered abnormal if its typical waveform could not be readily identified or its baseline to positive peak amplitude was more than two standard deviations below the mean of our control subjects for at least two of the three recording electrode configurations *.

Locating MS lesions MR scans were obtained either on a Technicare 0.6

tesla unit or on a GE Signa 1.5 tesla unit with T2 weighted, spin-echo pulse sequences. The procedure was optimized with the earlier MS subjects so that only with the later 18 MS subjects was a relatively uniform protocol used. To achieve high spatial resolution we initially used a relatively small field of view (14 cm), with a short interpulse interval (TR = 1500 ms) and 4 averages. Later, to obtain better contrast of MS lesions and to improve the signal to noise, we increased both

* The amplitude criterion was chosen as 2 standard deviations

because for larger multiples of the standard deviation, such as 2.5

standard deviations, the cut-off level for a positive peak fell below zero. In nearly all cases this 2 standard deviation cut-off level was

below the observed range of the normals.

h?

the field of view and the TR (to 2500 ms). For consis- tency, the TR of scans in the sagittal plane was kept at 1500 ms.

The later 18 MS subjects and 14 normal control subjects were scanned on the same Signa unit with the following (or similar) protocol. The standard Signa headcoil was used. Scout scans were obtained in the scanner’s standard sagittal and coronal planes with a 20 cm field of view, TR of 600 ms, and an echo time (TE) of 20 ms. The data were then collected from three orthogonal planes of the brainstem: axial (perpendicular to the long axis of the bra~nstem), coronal (parallel to the plane of the floor of the fourth ventricle), and sagittal (perpendicular to the plane of the floor of the fourth ventricle and in the plane of the long axis of the brainstem). A typical protocol collected data at four spin-echo times: 25, 50, 75, and 100 ms, and used 2 averages with an 18 cm field of view. The resulting images contained 128 X 256 pixels (each 1.4 x 0.7 mm). Sections were acquired contiguously, without a gap. The other parameters varied with the scanning plane as follows:

Plane Sagittal Axial Corona1

TR (ms> Section thickness 1500 5mm 2500 6mm 2500 5mm

To identify regions of high signal on an objective basis, a semi-automatic algorithm was developed for the pons (quadrigeminal plate to pontomedullary junc-

, tion). Since it is well-known that MS lesions have increased signal on n-weighted scans (Young et al., 1980, the algorithm uses a TZweighted scan. The TE50 ms spin echo image was chosen as the T2- weighted scan, because, of the four spin-echo images, it appeared to have the greatest contrast between the regions of high signal and the overall background. Areas of abnormally increased signal in MR scans of MS subjects are also known to be characterized by abnormally long T2 values (Rumbach et al., 1991). Therefore, to improve our confidence that a region has unusual signal characteristics, the algorithm also uses a second brainstem image, the T2 map, which is derived from the four spin-echo images. Ultimately, we require that a high signal region have high signal on both the TE50 ms spin-echo image and the TZ image. The T2 map is computed on a pixel by pixel basis by determin- ing the slope of the best fit line relating the log of the signal intensity to the echo times. The T2 is the absolute value of the inverse of that slope. This T2 mapping technique eliminates contamination from other contrast effects.

Using an intensity-based segmentation procedure (Kennedy, 1986) the pons was outlined and a histogram

of all the pixel values within the ports was generated for each of these two images. To assure that only regions of elevated values would he detected by this algorithm, as opposed to single pixels ithat could be widely separated), each image was then smoothed with a digital filter (3 X 3 running box-car average). A high- signal region must have pixel values that exceed the mode of the histogram of the TE50 ms spin-echo image by one criterion value and the mode of the histogram of the the T2 map by another criterion value. From observing the effect of varying these criterion levels on scans of normal subjects, criterion levels of 4 grcy level units for the TE50 ms spin-echo image and 5 ms for the T2 map were chosen. In normal subjects less than 4% of the total area exceeded these criteria. Unlike with lower criterion values, with these choices no areas of high signal on more than one of the three orthogonal planes were detected in any of the scans of four- teen normal subjects, except for the rostra1 periventricular regions. For this reason, the rostra1 periventricular regions cannot be evaluated with this algorithm (the region includes the inferior colliculi for all planes of section, and the lateral lemnisci for the sagitta1 plane of section). For these subjects, we define a lesion as a region of high signal that is caudal to the inferior colliculus with at least some part of it detected on two or more of the orthogonal planes. The border of a lesion is taken as the maximum distribution of the lesion in any plane. For the earlier subjects the objective criteria cannot be applied, so subjective criteria were used, namely, visual inspection of the MR scans with detection of overlapping high signal regions in at least two orthogonal planes.

Of the 18 subjects with MR scans done with a uniform protocol, No. 601’s scan was partly unsatisfac- tory, because the subject’s bra~nstem was in an inho- mogenious part of the magnetic field. Subject No. 579 had high signal throughout the majority of her brainstem, so that our objective algorithm could not be meaningfully applied. For the remaining 16 subjects, the relationship of the sites of lesions detected by objective criteria to the auditory pathway was esti- mated by applying a computer-based model of the human brainstem to each experimental brainstem as described below. For the other subjects the identifica- tion and registration of lesions was done subjectively.

An anatomical model was constructed from a seri- ally-sectioned (in the transverse plane), adult human brainstem. The sections (from rostra1 medulla to mid- inferior colliculus) were 40 microns thick and stained with cresyl violet and hematoxylin. Under light mi- croscopy, edges of the brainstem, auditory nuclei, and fiber tracts were manually traced in sections occurring at intervals of approximately one half millimeter. A total of 97 tracings were then digitized and entered into our computer-aided anatomy system. Using this

system the three-dimensional atlas could be resec-

tioned in any plane and with any thickness to corre- spond to a particular MR section.

Matching an MR section to a corresponding slice from the anatomical atlas involved a number of steps.

First, an outline of the brainstem was obtained from the MR section using the segmentation programs. The grey level selected for the edge detection algorithm was based on the intensity of grey levels of pixels along a line joining two points on either side of the ventral

border of the pons. The value chosen was approximately the midpoint between the minimum (outside

the brainstem) and maximum (inside the brainstem) values occurring along this line segment. Using this

value, the edge detection algorithm placed a boundary around the outer edge of the brainstem, which was then manually closed by the operator at levels chosen to approximate the rostra1 and caudal extents of our

anatomical model. Caudally, this point was a few mil- limeters below the pontomedullary junction, rostrally it was about halfway through the inferior colliculus.

The second step was to obtain slices from the brainstem atlas that corresponded to a particular MR section. For each plane of section, the location of an MR

section, as indicated on the ‘planner scan’, was related to the coordinate system of the brainstem atlas. With a sagittal planner, for example, we used two reference points, the junction of the base of the pons with the

medulla and the junction of the base of the pons with the midbrain. These points were assigned the value of the corresponding points in the coordinate system of the brainstem atlas, and the MR slice thickness was expressed as a fraction of the distance between the two points. Given these values, the center of each slice was determined and a section of the anatomical model was taken centered at this point and with the same thickness as the MR section.

In the next step, the linear transformation is found for matching the borders of the section from the anatomical atlas to the borders of the MR section. Due to the 5 or 6 mm thickness of the sections, the border of the anatomical model often varied considerably within a section. Therefore, we used a thin section from the center of the anatomical model section for finding the linear transformation that registers the anatomical section to the MR section. This matching of the borders of the thin atlas section to the borders of the MR section involves (a) a translation to align the centers of mass of the two sections, (b) a uniform scaling to equate the areas enclosed by the two sections, and (c) a rotation about the centers of mass to align the principal axes of the two sections. In the final step, this linear transformation was applied to the complete atlas section, thereby registering our estimate of the location of the auditory pathway on the MR section.

Results

Our normal control subjects had little difficulty with the psychophysical tasks (Fig. 1). In addition, their BAEP waveforms all showed the classically identifiable

low- and high-pass waves. Waves I, III, V, and L were identified for all subjects, while waves II, IV, and VI

were sometimes not clear (Levine et al., 1993). No normal subject had regions anywhere in their brain MR scans consistent with an MS pathology. Thus, it is possible to define an objective measure of abnormality

for any of these variables by using data from normal control subjects as references.

Fig. 2 summarizes the psychophysical and electro-

physiological data for 38 MS patients. With our exper- omental system the maximum possible interaural time difference that could be measured was 1280 ps, a value

so large that subjects unable to perform above chance level for this interaural difference essentially could not

Normal Control Subjects

Subject #

2 11

200 425 459 490 508 510 512 522 526 527 588 593 600 603 608 621 623

mean

std. dev.

mean + 3 (std. de\

F Psychophysics

C

LPL

0.45 1.96 0.97 0.50 1.10 0.81 0.65 0.90 1.38 0.65 0.90 0.59 -

0.58 -

jr HPL

0.41 1.81 0.86 0.25 0.39 0.25 0.71 0.67 1.33 0.50 0.70 0.56 -

0.69 -

2.07 0.61 0.89 0.52 1.08 0.64 0.94 0.70

0.97 0.68

0.46 0.38

2.35 1.82

i _DT

10 40 10 10 IO 10 17 IO 45 34 15 16 -

26

HPT

95 119 49 32 39 60 55 57 61 83 79 36 -

66 - _

19 59 19 63 40 42

10 45

20 61

12.: 23

57 130

ll- E !AEPs MRIS

*

* * *

* * * * * * * *

*

* * * * * * *

*

*

*

*

* -

-I Fig. 1. Summary of data available for normal control subjects. The

binaural tests with noise bursts generated psychophysical data given

as just noticeable differences (jnds) for low-pass time (LpT), high-pass

time (HpT). low-pass le\J*’ ‘-_pL) and high-pass level (HpL). Time

jnds are in microseconds. Level jnds are in dB. Asterisks in the other

two columns indicate whether brainstem auditory-evoked responses

or magnetic-resonance images, respectively. were obtained. For the

psychophysical data, the means, standard deviations, and mean plus

3 standard deviation values are given below each column.

do the task. The maximum possible interaural level difference that could be measured was 10 dB. Since it is impractical to show all the waveforms for the BAEPs, a code has been adopted to indicate the type of abnormality. [In the accompanying paper (Levine et al., 1993) several waveforms are shown.] For two subjects, the recordings were too noisy, either from movement artifact (No. 539) or equipment failure (No. 620) to meet the standards for a waveform reliable enough to make judgements on all waves.

Audiograms for both ears were normal ( < 20 dB HL at all six standard frequencies) for 25 of the 38 MS subjects (Fig. 2). For eleven subjects audiometric thresholds were elevated to between 25 and 35 dB HL at 4 or 8 kHz for one or both ears; for two subjects bilaterally symmetric threshold elevations of 5.5 dB were present at 8 kHz.

PSYCHOPHYE MONAURAL BAEPs

Subi AL&XI LDL HDL HpT High-Pass Low-Pass . _.

*- abnomml Jnd _______----- BREPr: O- IlamPl U - amplltuds abnl

n - interpeak interval abnl 4 - alrIp1 D 1st abIll a - lat. abnl 7 - unmco~nlzable

Fig. 2. Summary of data for 38 MS patients arranged by subject

number. Audiometric data is summarized in the second column.

Blanks indicate that the audiograms for both ears were normal;

otherwise, the poorest threshold of either ear in dB HL is given. The psychophysical data are shown as in Fig. 1; data exceeding the mean

plus 3 standard deviations of the normal controls are marked with

asterisks. > 1280 indicates that the task could not be performed

above chance level for our maximum time delay (1280 ps). The four

columns listing BAEP data show whether the high and low-passed

waveforms were normal or not for monaural clicks presented to the

right or left ear. If abnormal, the type of abnormality is indicated.

The key to symbols is given at the bottom of this table.

F 0 normal 0 abnormal - unavailable

:---- Subject # -IPL _pT ipT ---

536 0 0 0 563 0 0 0 567 0 0 0 569 0 0 0 582 0 0 0 590 0 0 0 596 0 0 0 599 0 0 0 604 0 0 0 613 0 0 0 203 0 0 0

69 0 0 0 539 0 0 0 566 0 0 0 587 0 0 0 589 0 0 0 616 0 0 0 620 0 0 0 538 0 0 0 602 0 0 0 572 0 0 0 585 0 0 0 610 0 l l 551 0 0 0 575 0 0 0 537 0 0 0 540 0 0 a 543 0 0 0 576 0 0 0 577 0 0 0 578 0 0 0 579 0 0 0 581 0 0 0 583 0 l l 601 0 l 0 607 0 0 0 163 0 0 0 521 0 0 0

--- -l

Fig. 3. Psychophysical and physiological data from Fig. 2 classified

as normal (open circles) or abnormal (filled circles). The ordering

of the subjects has been rearranged to facilitate appreciation of

interrelationships.

LPL

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

-

0 0 0 0 0 0 0 0 0 0 0 0 -

0 0 0 0 -

0 0 0 0 0 l 0 0 l 0 0 0 0 0 0 a 0 0 0 0

Psychophysics

inds lr B

-__

AEPs

The psychophysical data on all 38 MS subjects (Figs. 2 and 3) indicate that many more subjects had abnormal time jnds than had abnormal level jnds. AIL subjects could easily perform above chance level on the level jnds (i.e. all level jnds were less than 10 dB), but 16% of subjects could not perform above chance level on the HpTjnd and 3% on the LpTjnd (i.e. this group of subjects could not perform any better than chance for the 1280 ps limit of our system). The most sensitive indicator of auditory dysfunction is the high-pass time jnd. Seventy percent of all MS subjects performed abnormally on this test, as compared to forty percent for the LpTjnd, the behavioral test with the next high- est sensitivity. Abnormal performance on any of the other psychophysical tests was always associated with an abnormal HpTjnd, but the converse was not true. Of the 27 subjects with some psychophysical abnormal-

TIME jnds and BAEPs of MULTIPLE SCLEROSIS SUBJECTS

HIGH-Pass Noise LOW-Pass Noise

10 1

Fig. 4. Type of BAEP abnormality plotted against high-pass and

low-pass time jnds for each MS subjects. The symbol plotted indi-

cates the type of wave abnormality (key at bottom of figure). If both

amplitude and latency abnormalities were present, the amplitude

symbol was used. Jnds within shaded regions are abnormal. > 1280

indicates that the subject could not perform above chance for the

largest (1280 KS) interaural time difference that could be presented.

ity, almost half had a high HpTjnd as their only psychophysical dysfunction. The functional tests with the least sensitivity were the level jnds (11% for LpLjnd and 8% for HpLjnd) which never occurred as an iso- lated abnormality. Of the five subjects with abnormal high- or low-pass level jnds, all had abnormal high-pass time jnds and four of the five had abnormal low-pass time jnds as well.

A.Audit0r-y brainstem lesions

Subject #

t

576 577 563 607

The BAEPs were a less sensitive indicator of audi-

tory dysfunction than the HpTjnds; 42 percent of all

subjects had abnormal BAEPs as compared to 70 percent with abnormal HpTjnds. What is remarkable is that without exception every subject with abnormal

BAEPs had an abnormal HpTjnd. More detailed analysis is even more intriguing (Figs. 2 and 4). All seven

subjects who were unable to perform above chance level on the high pass time task had either (i) a unilaterally or bilaterally abnormal wave III or (ii) at

least one wave V that was undetectable. For one subject the BAEPs were normal on one side with

prolonged latencies in waves III, V, and L on the other side. Of the remaining subjects with HpTjnds greater than 500 ps, four of five had abnormally small wave V amplitude for at least one side. Thus, a profound

impairment on the high-pass interaural time test is nearly always associated with a wave III abnormality involving either latency or amplitude, or a wave V abnormality involving amplitude.

The number of subjects with abnormal BAEPs was nearly the same as the number with abnormal LpTjnds

and the overlap between these two groups of subjects was high, with three-quarters of all those with abnormal BAEPs having abnormal LpTjnds. As shown in Fig. 4, the congruity between the performance on these two tests may be even stronger if we consider that the performance was ‘slightly’ abnormal for the subjects who were classified as normal on one test and abnormal on the other. Notice that (a) all three subjects (No. 572, No. 585, and No. 6101 with abnormal LPTjnds and no BAEP abnormality had barely abnormal LpTjnds (62, 65 and 71 ~LS) and (b), of the three subjects (No. 537, No. 551, and No. 575) with normal LpTjnds and

Subjects with MRI Scans Evaluated by OBJECTIVE Criteria

B. Non-auditory brainstem lesions C. All lesions outside of brainstem

0 normal

0 abnormal

r

Fig. 5. Psychophysical, physiological and MR data for the 16 MS subjects whose MR scans were evaluated using objective criteria. Data are

represented as in Fig. 3. (A) shows the data for subjects whose lesions did encroach upon the pontine auditory pathway. (B) the data for the

subject with brainstem lesions that did not encroach upon the pontine auditory pathway. In (CJ the data for subjects whose lesions were not

detected in the pons.

hh

abnormal BAEPs, the BAEPs had only latency abnor- stem by objective criteria; all of these subjects had malities and no amplitude abnormalities or unrecogniz- normal BAEPs. More than half of these subjects had able waves. In general, latency abnormalities were not abnormally elevated time jnds for the high pass stimuli, associated with major dysfunction on the low-pass tim- while one had a just barely abnormal time jnd (65 ~5) ing task, but amplitude abnormalities were, whenever for the low pass stimuli. Thus, in general it appears they involved wave III (unilaterally or bilaterally) or that abnormal BAEPs (particularly with unrecogniz- wave V bilaterally. A unilateral wave V abnormality able waves or amplitude abnormalities) may be diag- alone, even if wave V were unrecognizable, was never nostic for auditory brainstem lesions. Similarly ‘sub- associated with major abnormalities of the low-pass stantially’ abnormal LpTjnds (> 100 ps) may also be timing task. diagnostic for auditory brainstem lesions.

Let us now examine the psychophysical and electrophysiological results in relationship to their MR scans. For technical reasons, MR data are not available for subjects 69 and 163. The other 36 subjects all had regions of high grey scale levels detected somewhere in the brain consistent with the diagnosis of multiple sclerosis (Young et al., 1981). Because our most valid MR evaluations are probably on the sixteen MS subjects whose scans were done with a uniform protocol and evaluated by objective criteria, we shall begin by considering the data from these subjects (Fig. 5). All four subjects with lesions encroaching upon brainstem (pontine) auditory pathways (these lesions will be more completely described in the following paper) had major abnormalities of their HpTjnds (Fig. 5A). One subject also had a slightly abnormal low pass level jnd. What is striking is that all four patients had very abnormal LpTjnds as well as highly abnormal BAEPs involving amplitudes as well as latencies. Some waves were not even recognizable. In a case for which lesions were found in the brainstem but not involving the auditory pathways (Fig. 5B), we note that the BAEPs were normal, the LpTjnd nearly normal (71 ps), but the HpTjnd solidly abnormal (331 ps). In addition to the brainstem lesions this patient also had diffuse lesions throughout the cortex. Fig. 5C shows data for the patients who had no discernible lesions in the brain-

Finally the data from 20 patients with MR data evaluated subjectively (Fig. 6) are consistent with those from the groups with lesions defined objectively. Sub- jects with lesions involving the pontine auditory pathway always had abnormal HpTjnds and included three of the four cases with abnormal level jnds. All subjects with unrecognizable waves or amplitude abnormalities of the BAEPs had lesions involving the pontine auditory system, as did all but one subject with substantially abnormal LpTjnds (> 100 ps). However, the converse was not always true. Two subjects who appeared to have pontine auditory involvement by subjective criteria had normal LpTjnds; the BAEPs of one were normal and the BAEPs of the other had only prolonged latencies.

Discussion

The empirical data from this study show certain orderly relationships between the location of lesions, psychophysical performance on several binaural tests and electrophysiological responses to clicks. All subjects diagnosed as having MS had lesions demonstrable in MR scans, whereas no normal subject had such lesions. About half of the MS subjects had brainstem lesions and, in about two-thirds of these,

Subjects with MRI Scans Evaluated by SUBJECTIVE Criteria

A. Auditory brainstem lesions

I II ihds II I

B. Non-auditory brainatem lesions C. All lesions outside of bra&tern

0 rormal 0 abnormal

Fig. 6. Psychophysical, physiological and MR data for the 20 MS subjects whose MR scans were evaluated using subjective criteria. Conventions as in Fig. 5.

67

some of the brainstem lesions involved the pontine

auditory system. Nearly half the MS subjects had abnormal brainstem

auditory evoked responses. About three-quarters of the MS subjects had abnormal time-jnds for high-pass noise bursts; of these more than half also had abnormal time-jnds for the low-pass noise bursts. All subjects with abnormal LpTjnds had abnormal HpTjnds. About one out of every six MS subjects could not do the HpTjnd for our maximal delay.

Only about an eighth of the MS subjects had abnormal level-jnds for either high or low pass noise bursts. All subjects could do both level jnds for interaural differences well below our maximal difference. All subjects

with abnormal level jnds had abnormal time jnds for high pass noise. Eighty percent also had abnormal time

jnds for low-pass noise. All MS subjects with abnormal evoked responses had abnormal high pass time-jnds. Two-thirds of those with abnormal evoked responses had abnormal low pass time-jnds. All subjects with an amplitude abnormality in the evoked potentials had an abnormal LpTjnd. All subjects with abnormal level jnds had abnormal evoked responses. All subjects with ‘substantially’ abnormal low pass time jnds (> 100 KS) had abnormal

evoked responses. Of the subjects with major abnormalities of the Lp- Tjnds, none had only BAEP latency abnormalities. Of the subjects with major abnormalities of the HpTjnds, BAEP latency abnormalities did occur but only for wave III. Abnormal BAEP wave amplitudes were associated with major time jnd abnormalities: for unilateral wave III, high- and low-pass time jnds; for wave V when unilateral, HpTjnd; and for wave V when bilateral, LpTjnd. Our rigorously defined protocol for evaluating MR. data detected auditory brainstem lesions in every MS subject with abnormally small evoked responses. Nearly two-thirds of all our MS subjects with one or more abnormal psychophysical indicators had no detectable lesions of the pontine auditory pathway and about half have no detectable lesions in the brainstem.

Relationship to Multiple Sclerosis

A well known clinical observation in MS patients is that there may often be pathologically widespread disease and yet little neurological dysfunction (‘silent le-

sions’ (McDonald, 1986)). This observation has also been made more recently with MR scanning (Harris et al., 1991). This apparent paradox may be partially explained by our finding that it is the auditory behavior most dependent upon precise timing that is compromised in MS subjects. One of the major pathophysio- logical effects of MS is a slowing of spike conduction along individual axons when there is demyelination.

Nerve impulses will propagate but the temporal rela-

tionship of impulses to the stimulus may be abnormal.

Such changes should affect only those neural functions that depend upon precise timing relationships between the stimulus and the neural impulse. Of all neural

systems the auditory system probably has the most stringent neural timing requirements (on the order of microseconds for auditory tasks such as lateralization), and may be the most sensitive of all neural systems to the effects of multiple sclerosis lesions. Most neural

mechanisms, including ot!rer auditory mechanisms, that do not require precise timing (e.g., interaural level discrimination and pure tone thresholds) are largely

left intact by the disease process. Thus, if decreased axonal speed of conduction in individual fibers is the main pathophysiologic effect of MS. then despite evidence for widespread disease by neuropathologic or

MR study, there may be little in the way of symptoms. In fact, none of our subjects complained about their hearing or reported difficulties with sound localization. Presumably, those unable to use interaural timing cues could still use interaural level cues or spectral cues. However, in our study, we found no ‘silent lesions’; every lesion involving the brainstem auditory pathway was associated with some abnormalities (Figs. 5 and 6)

on our tests requiring microsecond accuracy in neural timing.

Another aspect of the pathology of multiple sclerosis relates to a more generalized abnormality of myelin (Allen and McKeown, 1979). MR studies suggest that, in regions of white matter without focal disease, the white matter has abnormal physical-chemical properties (Rumbach et al., 1991). Physiological studies have reported abnormalities in conduction properties of peripheral nerves in patients with MS (Hopf and Eysh- oldt,197X), including the peripheral portion of the auditory nerve (Hopf and Maurer, 1983; Parving et al., 1981; Fischer et al., 1985). Just as in one of our subjects (No. 607) we found wave I (the compound action potential of the auditory nerve) delayed, some of the latency abnormalities in the later parts of the BAEPs may be related to the more diffuse myelin disorder rather than to the classical focal disorder of MS. Consequently we may not find that every BAEP latency abnormality or psychophysical abnormality can be accounted for by a focal MS lesion on the MR scan.

In fact, if the distribution of the HpTjnds for all MS subjects is examined closely, it is striking that the HpTjnd for all 38 subjects is above the mean of the normal control group (Fig. 4). This suggests that the HpTjnd for some of the MS subjects, whose HpTjnd still falls within 3 standard deviations from the mean of the normal controls, is elevated from the level it would have been had they not contracted the disease. Some of these slight elevations may be due to this diffuse myelin disorder.

Relationship to Preuious Studies

The present study can be compared with previous reports. Overall, the results are consistent with those of Hausler and Levine (1980), in effect, replicating and expanding that study. Again we find that interaural time (but not level) jnds are closely related to monaural brainstem potentials: normal brainstem potentials were associated with normal time jnds and abnormal potentials with abnormal time jnds. A major method- ological difference in the present study is that high- and low-pass noise bursts were used rather than broadband noise bursts. We found that the performance on the two spectrally different stimuli were often diver- gent, with abnormal HpTjnds coupled with normal LpTjnds. One subject (No. 551) with such jnds was retested 8 weeks after the first testing (Fig. 21. Her results were again very similar (LpTjnds: 35 vs. 37 ps; HpTjnds: > 1280 vs 1162 ps). We then tried a broadband noise burst and her jnd was normal (48 11s). This result suggests that some of the subjects who performed normally on the time jnd of the Hlusler and Levine (1980) study which used broadband noise bursts would have had abnormal HpTjnds. In fact, in that study, there were two subjects who had abnormalities in their BAEPs but normal time jnds. In the light of present results, it appears that those subjects were probably using the low frequency components of the broadband noise to lateralize the stimulus; had those two subjects been tested by our present methods, we would predict that their performances would have been normal for LpTjnd and abnormal for HpTjnd.

Other studies have used clicks, another type of broad band stimulus, and obtained results seemingly different from ours. While Van der Poe1 et al. (1988) also found that about three-quarters of their MS subjects performed abnormally on their test of interaural time discrimination, they found that some MS patients’ performances on their test of interaural time discrimination were normal despite abnormal wave Vs. Be- cause their stimulus was broadband, it may be that these subjects would have performed abnormally on a test of interaural time discrimination whose spectrum was limited to the high frequencies. Furst et al. (1990) also reported subjects with normal time jnds and abnormal monaural BAEPs; spectral considerations may account for these results as well. However, the reason for their finding of normal BAEPs in MS subjects with abnormal time jnds requires another explanation. While it may relate to factors such as the choice of criteria for classifying the BAEPs as abnormal, a possible factor is that the shorter duration of the stimulus used for behavioral measurements makes the judgments harder to make and therefore more sensitive to any disruption, even those not severe enough to make the BAEPs abnormal (Jenkins and Merzenich,l984). Furst et al.

(1990) felt that ‘there is no obvious relationship between monaural BAEPs and click lateralization’; this conclusion contrasts with Matathias et al. (1985>, who also used click stimuli for measuring time and level jnds, and found significant correlations between both types of jnds and the BAEP latencies. Our findings are more consonant with the latter study.

Relationship to Experimental Models

Our empirical findings provide a rich set of constraints for physiological models of how humans process auditory information. We have adopted a model, the main outline of which was proposed by Jeffress in 1948. This model is now supported by anatomical and physiological studies in animals and not only accounts for the findings described here, but makes predictions that are testable in future work.

Fig. 7 shows the most simplified version of the model. A group of brainstem neurons (open circles, diagram A) is innervated symmetrically by inputs from both ears through axons with cell bodies in the cochlear nuclei. Each brainstem neuron behaves as a probabilis- tic coincidence detector such that, when action potentials arrive nearly simultaneously from the two sides, their effects sum and greatly increase the probability of an output spike. These brainstem neurons are frequency selective, each receiving inputs representing local regions in the two cochleas that have the same characteristic frequency (CF). High CF neurons receive inputs from the base of the cochlea, low CF neurons, from the apex of the cochlea. In fact, in the human there is a brainstem nucleus, the medial superior olive (MSO), that has such an innervation pattern (Ramon y Cajal, 1909; Stotler, 1953). There are two MSOs, one on each side and their output fibers ascend in the ipsilateral lateral lemnisci (van Noort, 1969; Stotler, 1953; Adams, 1979).

To a wideband transient sound, high CF auditory- nerve fibers tend to respond at the same time (group synchrony), but low CF units tend to respond at different times depending upon their CFs (Kiang et al., 1965). This type of group synchrony from the high CF neurons is presumably also responsible for the distinct waves in the BAEPs (Don and Eggermont, 1978) and we assume that it will be carried through to the brainstem auditory nucleus represented in Fig. 7.

For a normal subject, the same sound delivered to both ears creates the perception of a midline oriented sound source. Either amplitude or time differences in the same sound delivered to the two ears can produce the perception of a sound source off to the side of the midline and, thus, can be distinguishable from the symmetrically presented sound stimuli. In diagrams B and C, one sees the effects of an MS lesion encroaching on the input fibers to the brainstem nucleus. In B

High CF High CF

Low CF Low CF

E3

High CF

Low CF

c l---l Higher.Levei PKO3S90~

High CF

Low CF

BAEPs (right)

LpL HpL LpT HpT

JNDs 0 0 0 0

Lpi HpL LpT HpT

JNDs 0 0 . l

LpL HpL LpT HpT

JNDs 0 0 0 .

High CF

Low CF

L$rL HpL LpT HpT

JNDs 0 0 0 .

Left Right

Fig. 7. Schematic depiction of a theoretical model to account for the data in this paper. In diagrams A, B, C, and D, the brainstem processor (vertical rectangle) is seen as a collection of neurons (open circles) that receive symmetric inputs from corresponding regions of the cochlea through the cochlear nuclei. The stimulus is a wideband acoustic transient presented identically at the two ears. For simplicity, only one spike per fiber is represented. The position of the spikes indicate relative times of arrival of single unit discharges at the brainstem processor, with time of arrival increasing for spikes which are further away from the brainstem processor. Dashed vertical lines are symmetrically placed on either side of the brainstem processor to serve as reference. Each brainstem neuron is a binaural spike-pattern comparator that sends its output to a higher-level processor (horizontal rectangle). To the right of each model is a depiction of how the BAEPs (to clicks to the left ear) and the jnds (open circles, normal; filled circles, abnormal) might appear in each case. Diagram A is the case of a normal subject. In diagram B, a multiple sclerosis iesion, affecting the fibers from the left side (stippled oval), is seen as altering the conduction times of input neurons by varying amounts in different fibers; in one there is no spike due to conduction block. In this case many of the brainstem neurons would have a very different output than they do in diagram A. The functions of the higher-level processor that depend upon comparing the exact time of arrival of spikes to each brainstem neuron and integrating over the entire array of brainstem outputs would be disrupted as reflected by the abnormal high- and low-pass time jnds. The loss of group synchrony of the input fibers would also be reflected in the absence of recognizable waves following wave II of the BAEPs. Functions that require only measuring the number of spikes coming from both sides within some time period might still be normal as reflected in the normal level jnds. In diagram C, an MS lesion also alters some fiber conduction times, but uniformly so that group synchrony of the high CF fibers remains. Thereby, the later BAEPs are recognizable but delayed. Only the high-pass time jnd is abnormal. In diagram D, the brainstem auditory apparatus is intact, but MS lesions involve the higher-level processor (stippled area). This situation could occur in MS

subjects that performed abnormally on the high-passed time jnds and had normal BAEPs.

70

the group synchrony of high CF fibers is disrupted, so that from the side with the lesion there is no group of high CF input neurons that all discharge at the same time, as shown for the top 3 fibers in diagram A. This loss of group synchrony would also remove the type of synchrony that is essential for coherent waves in the BAEPs (Goldstein and Kiang, 1958). If, as shown in Fig. 7C, the MS lesion causes many fibers to have equivalent slowing of conduction, then the group synchrony would still be maintained and the BAEP waves would remain detectable but the latencies of the later BAEP waves would have a longer latency. In case B, C, or some combination of the two, disruption of timing from one side will disrupt the input to the brainstem neurons acting as coincidence detectors. Thus it is easy to see how the time jnds and the BAEP amplitudes or latencies could be correlated.

High CF neurons respond to low frequency stimuli at higher stimulus levels, while low CF neurons do not respond to high frequency stimuli at any stimulus levels (Kiang and Moxon, 1974). For low-pass stimuli, then, there can be cues for binaural processing not only in the response of low CF neurons but also in the response of high CF neurons, whereas for high-pass stimuli only high CF neurons will respond. Further- more, nerve fiber responses are time-locked to both the envelope and fine structure of low frequency sounds, while they are time-locked to only the envelope of high-frequency sounds (Javel, 1980; Joris and Yin, 1991). Thus, it can be appreciated that low-pass time information, particularly at higher stimulus levels, is redundantly represented in the discharge patterns of high as well as low CF neurons. Consequently, low-pass time discriminations may be less vulnerable than high- pass time discriminations for MS lesions.

A third factor that is operative (whether or not a neuron is responding to the fine structure of the stimulus) may also be contributing to the robustness of the interaural discrimination for wide-band low-frequency noise. This factor is related to the envelope of the correlation function and how the rate of decay of this envelope depends on the bandwidth of the effective stimulus. To understand the effects of abnormal delays, it is helpful to extend our model to include two dimensions, the characteristic frequency dimension and a ‘characteristic-delay’ dimension that spans a range of interaural delays of about 1 millisecond in each direction. Further, it is useful to think of the activity of these cells along the delay dimension as an estimate of the cross-correlation functions for filtered versions of the stimulus waveforms. The correlation function for a narrowband-filtered noise waveform is an amplitude- modulated sinusoid in which the frequency of the fine structure is equal to the center frequency of the noise and the envelope is determined by the bandwidth of the filter. The activity pattern will shift when the

stimulus interaural time delay changes. and the process of discriminating time delays corresponds to distin- guishing the corresponding internal patterns. We now consider additional interaural delays imposed on the inputs to the neural model as in Fig. 7B or 7c‘, due to MS induced disruption of timing. When these delays are small (< 1 ms) they will be ‘naturally’ accommodated for within the network by a simple shift of which characteristic delay neurons are active. On the other hand, large delays (relative to the characteristic delays within the model) cannot be compensated by shifts in which cells are activated in the delay network; and sensitivity to delay in this case depends on the fact that the waveform is similar to itself delayed according to its correlation function. The ability to represent time delays larger than 1 ms within the delay network depends on the envelope of the correlation function, which is determined by the filter shape, particularly by the bandwidth. Filter bandwidths for low-frequency noise are smaller in Hertz (not in octaves) than bandwidths for higher frequency noise, so the larger delays could be better accommodated by low-frequency cells *. Hence, this may be another reason why the LpTjnd is more resistant than the HpTjnd to the effects of MS.

Fig. 7D indicates that even when the brainstem is free from lesions, psychophysical performance can be compromised by lesions at some higher level. When this occurs, the BAEPs would not need to be affected. Another possibility is that MS lesions involve the output neurons of the brainstem nuclei acting as coincidence detectors, in which case later components of the evoked potentials could well be affected.

The relative rarity of level discrimination abnormalities follows easily from the fact that spikes are not necessarily blocked by the MS lesions, only their conduction velocities are affected by demyelination. If level comparisons depend on counting spike numbers in comparable channels over some short integration time (e.g., by summed ipsilateral excitation and con- tralateral inhibition such as in LSO neurons (Caird and Klinke, 1983; Yin and Chan, 1988)), then the interaural time discriminator would be unaffected by small desyn- chronizations. However, for some lesions, conduction may actually be blocked so level discriminations can be abnormal. Nonetheless, the interaural level comparison machinery is unlikely to be independent of the interau-

* Note that this is not an issue related to the temporal fine structure

of the correlation functions. The fine structure, which is deter-

mined by the center frequency of the filter, is sharper for higher

frequencies (as long as the frequency is low enough that the neurons respond to the fine structure), but the set of internal

delays (the distribution of the characteristic delays) is able to

compensate for fine structure delays anyway because they are

always effectively smaller than a period.

71

ral time comparison machinery because abnormal level

jnds never seem to occur in the absence of abnormal

time jnds, at least in these MS patients. Based on a more detailed analysis (presented in the

accompanying paper) relating the MR scan lesions to

the BAEPs, it is reasonable to propose that wave III represents the gross potential corresponding to the high CF inputs to the coincidence detector brainstem nucleus and wave V its output. If we now view the model in light of these assumptions, then the details of the relationship between the type of BAEP abnormality and the major time jnd abnormalities may also be understood. An increased latency could occur from either (1) a ‘group’ conduction delay of the high CF

fibers or (2) a desynchronization (or blockage) of only the high CF fibers so that the fibers with lower CFs are generating the delayed wave (Don and Eggermont, 1978). In either case the brainstem binaural coinci-

dence detector is receiving the low frequency information through the lower CF units with little change. Consequently latency changes in wave III do not result in major LpTjnd abnormalities, but could result in major disruption of HpTjnds, since high pass information is carried only in the high CF fibers, which are either desynchronized or delayed.

A reduced amplitude (Fig. 7B) in a wave suggests a

group desynchronization (or blockage) of both high and low CF fibers, Consequently, if wave III is reduced

in amplitude then both high and low CF fibers would be supplying incorrect signals to the brainstem nucleus about both high-pass and low-pass noise. As a result the HpTjnd and LpTjnd would be abnormal.

Finally, if wave V represents the output of this brainstem nucleus, then the fact that a unilateral reduced amplitude of wave V disrupts HpTjnd in a major way suggests that the later stages of HpTjnd processing requires input from both the right and left brainstem

coincidence detectors. The fact that a major disruption of LpTjnd (referenced to a midline stimulus) requires a bilateral reduction in wave V amplitude suggests that the later stages of LpTjnd can be processed with the inputs from just one side of the brainstem.

Thus, there is a theoretical picture, consistent with

known anatomy and physiology of brainstem single neurons studies, that can be used to account for all the data of this study. This picture naturally generates a number of possible directions for future work. Among these are simple improvements in technical matters which might settle certain issues. For example, surface coils and pulse sequences specially designed for imaging the brainstem will improve the contrast to noise ratios so that lesions not seen now may be detected and spatial resolution improved. This may resolve whether the results on subjects with abnormal BAEPs or jnds, but normal MR scans of the brainstem, are explainable in terms of small undetected brainstem

lesions. It is also possible to reexamine the criteria for

abnormality in both the BAEPs and the psychophysical

tests. Recordings from other electrode montages, ex- amining BAEPs for low and high frequency stimuli, examination of binaural interaction waveforms, or new and different psychophysical tests could be used to test present ideas on how neurons in human brains process binaural information.

Our data provide clear confirmation that the ideas embodied in this model, which were derived principally from experiments on animals, hold for humans. Fur- thermore, although the ideas were derived by integrating knowledge from a multiplicity of sources, little, if any, of this previous work provided direct evidence

which ties psychophysical performance to anatomical structures. Our observations (e.g., that high-pass-noise time jnds are much more sensitive to the disruptions of MS than low-pass-noise time jnds) can be readily inter-

preted in terms of existing knowledge, but could not. with confidence, have been predicted. These observations can now serve as constraints on future models of auditory processing.

Acknowledgements

This work was supported by NIH grant PO1 DC001 19 and BSF grant 89-00460. J.C. Gardner was supported by NIH grant T32 DC00006. We are indebted to the MS subjects who made this study possible; we particularly thank the Association to Overcome MS. We thank J. Sundsten of the University of Washington for mak- ing available to us his human brain sections, L. Yaffe for writing the matching paradigm, D. Kennedy for his segmentation software, and R. McKinstry for the T2 map software. H.S. Colburn gave us valuable advice about psychophysical issues. P. Cuneo provided techni-

cal assistance.

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