Brain Topography, Volume 15, Number 2, Winter 2002 (© 2002)
69
Intracerebral Sources of Human Auditory Steady-State
Responses
Anthony T. Herdman*, Otavio Lins+, Patricia Van Roon^, David R. Stapells*, Michael Scherg~,
and Terence W. Picton^
Summary: The objective of this study was to localize the intracerebral generators for auditory steady-state responses. The stimulus was a continuous
1000-Hz tone presented to the right or left ear at 70 dB SPL. The tone was sinusoidally amplitude-modulated to a depth of 100% at 12, 39, or 88 Hz. Responses recorded from 47 electrodes on the head were transformed into the frequency domain. Brain electrical source analysis treated the real and
imaginary components of the response in the frequency domain as independent samples. The latency of the source activity was estimated from the
phase of the source waveform. The main source model contained a midline brainstem generator with two components (one vertical and lateral) and
cortical sources in the left and right supratemporal plane, each containing tangential and radial components. At 88 Hz, the largest activity occurred in
the brainstem and subsequent cortical activity was minor. At 39 Hz, the initial brainstem component remained and significant activity also occurred in
the cortical sources, with the tangential activity being larger than the radial. The 12-Hz responses were small, but suggested combined activation of
both brainstem and cortical sources. Estimated latencies decreased for all source waveforms as modulation frequency increased and were shorter for
the brainstem compared to cortical sources. These results suggest that the whole auditory nervous system is activated by modulated tones, with the
cortex being more sensitive to slower modulation frequencies.
Key words: Auditory evoked potentials; Intracereberal generators; Frequency-analysis; Source analysis.
Introduction
Steady-state responses evoked by regularly repeating auditory stimuli can be recorded from the human
scalp. Determining the intracerebral sources of these responses should increase our understanding of the processes underlying normal human hearing and may help
to localize the level of a hearing impairment when the responses are abnormal or absent.
* School of Audiology and Speech Sciences, University of British
Columbia, Vancouver, BC, Canada.
+ Laboratórios Integrados de Neurofisiologia e Sono, Rua Manoel
de Almeida, 172 - CEP 52011-140, Graças Recife-PE, Brasil.
^ Rotman Research Institute, Baycrest Centre for Geriatric Care,
University of Toronto, ON, Canada.
~ MEGIS Software GmbH, Wessobrunner Str. 10,D-82166
Gräfelfing, Munich, Germany .
Accepted for publication: August 28, 2002.
This research was supported by the Canadian Institutes of Health
Research. The authors also thank James Knowles and the Baycrest
Foundation for additional support. Some of these results were presented at the International Evoked Response Audiometry Study Group
meeting in Vancouver, British Columbia, Canada, July 2001.
Correspondence and reprint requests should be addressed to Anthony T. Herdman, Rotman Research Institute, Baycrest Centre for Geriatric Care, 3560 Bathurst Street, Toronto, Ontario, M6A 2E1, Canada.
Fax: (416) 785-2862
E-mail: aherdman@rotman-baycrest.on.ca
Copyright © 2002 Human Sciences Press, Inc.
Sources for the electrically recorded auditory
steady-state responses (ASSRs) have not been extensively
studied. Johnson et al. (1988) performed a 21-channel mapping study and demonstrated clear polarity-inversions of
the response to 40-Hz brief tones over the mid-temporal regions in some of their subjects. Mauer and Döring (1999) reported in an abstract that the both brainstem and cortical
(temporal lobe) sources are active during the amplitude
modulation following response (using modulation frequencies between 24 and 120 Hz). However, the size of the
cortical activity decreased with increasing modulation frequency, and the brainstem was the dominant source at
modulation rates of greater than 50 Hz.
Several magnetoencephalographic (MEG) studies
have identified generators for the ASSRs to 40-Hz stimuli
within the supratemporal gyrus of the auditory cortex
(Hari et al. 1989; Mäkelä and Hari 1987; Pantev et al. 1993;
Pantev et al. 1996; Gutschalk et al. 1999). These sources
are similarly located to those for the transient middle-latency responses (MLRs)(Pantev et al. 1993; Yvert et
al. 2001). MEG studies have difficulty in recognizing
sources that are tangential and sources that are deeply located in the brain. Gutschalk et al. (1999) identified two
overlapping sources for the ASSRs in the supratemporal
plane. The more lateral of these might have represented a
source that was partially radial in its orientation. Electric
recordings might help to disentangle these components.
70
Animal and human intracranial recordings have led
to some controversy regarding the neural substrates of the
MLRs. Several human studies have suggested that these
are primarily generated within the auditory cortex
(Pelizzone et al. 1987; Jacobson et al. 1990; LiégeoisChauvel et al. 1994; Hashimoto et al. 1995; Kuriki et al.
1995). Animal studies indicate that both the primary auditory cortex (Arezzo et al. 1975; Kraus et al. 1982; Knight
and Brailowsky 1990) and brainstem (Fischer et al. 1995;
Kraus et al. 1988; Littman et al. 1992; Smith and Kraus
1988) are involved in generating the scalp recorded responses. The 40-Hz response might, therefore, represent
overlapping fields from both the cortex and the thalamus.
Deep-seated sources are difficult to see with MEG but
might be recognizable in electric recordings.
Galambos et al. (1981) suggested that the 40-Hz response represents the superimposition of individual
MLRs. Because the main waves of the MLRs have peak
latencies separated by approximately 25 ms between adjacent waves of the same polarity, the overlapping of the
responses will enhance the response when the stimulus
rate is 40 Hz. This idea has been supported by evidence
showing a close correspondence of superimposed transient MLRs and 40-Hz ASSR (Galambos et al. 1981; Hari
et al. 1989; Plourde et al. 1991; Stapells et al. 1988;
Gutshalk et al. 1999). Another hypothesis proposes that
neural units have an intrinsic rhythm of firing that best
resonates with a stimulus when it is presented at 40 Hz
(Azzena et al. 1995; Basar et al. 1987; Santarelli et al. 1995).
There are discrepancies between the recorded
steady-state response and waveforms modelled by adding together transient responses, particularly at rates not
equal to 40 Hz. It is difficult to be sure whether these effects are related to resonance effects or to refractory effects on different components of the MLRs (see
discussion in Gutshalk et al. 1999).
There are limited data regarding neural generators
for ASSRs to amplitude modulated (AM) tones modulated at rates between 70-110 Hz. Animal recordings
have shown units and fields in the brainstem that respond at these rates (Batra et al. 1989; Creutzfeldt et al.
1980; Frisina et al. 1990; Rees and Møller 1983). Kuwada
et al. (2002) reviewed their own animal studies and concluded that the surface-recorded amplitude modulation
following response is a composite response from multiple brain generators, with the responses to high and low
frequencies reflecting strong contributions from
subcortical and cortical sources, respectively. Hari et al..
(1989) reported dipole activity within the auditory cortex
for MEG responses to clicks presented at 70 Hz. Using dipole source analysis, Mauer and Döring (1999) suggested
that both brainstem and cortical generators are responsible for the ASSRs to stimuli modulated at low rates (20-40
Hz), whereas the brainstem is primarily responsible
Herdman et al.
when stimuli are modulated at higher rates (70-100 Hz).
Roß et al. (2000) studied the MEG ASSRs concentrating
on modulation frequencies near 40 Hz. However, they
also reported a secondary response maximum at stimulus rates near 80 Hz with an apparent latency of 26 ms for
these responses. The sources for these responses were
found in the superior temporal plane. Schoonhoven et al.
(2001) also found similar sources for both 40 Hz and 80
Hz responses. These results indicate the cortex is activated by the rapid modulations. However, because MEG
does not easily pick up deep sources, these studies do not
rule out concomitant activity in the brainstem.
The intent of this study was to identify the neural anatomical substrates for ASSRs to tones amplitude-modulated at frequencies of 12, 39 and 88 Hz. The
responses were mainly analyzed in the frequency domain. Brain electric source analysis (BESA) (Scherg 1990;
Scherg and Picton 1991) was used to model the location
and orientation of the neural generators of these ASSRs.
Methods
Subjects
Ten right-handed subjects (5 females) with an average age of 30 (range 17 to 50) years participated in this
study. Data were missing for some conditions for three
subjects (see below). Subjects were screened for normal
hearing at 1000 Hz at 20 dB HL. All subjects provided informed consent.
Recordings
EEG data were collected from 46 tin electrodes
mounted in an electrode cap and placed on the scalp. The
cap electrodes were Fp1, Fp2, AF3, AFz, AF4, F7, F3, Fz,
F4, F8, FC5, FC1, FC2, FC6, T7, C3, Cz, C4, T8, CP5, CP1,
CP2, CP6, P3, P7, Pz, P4, P8, PO3, PO4, Oz, O1, O2, Cb1,
Cb2 and Iz. Three additional electrodes were placed on
the left and right mastoids and on the back of the neck at a
distance of 10% of the nasion-inion distance below the Iz
electrode. Five electrodes were placed on the face to
monitor eye movements. These electrodes were placed
at the nasion, just inferior to the eye (IO1, IO2) and at the
outer canthus of the eye (LO1, LO2). Inter-electrode impedances were maintained below 10 kOhms at 10 Hz. All
electrodes were referenced to Cz electrode for the online
recording. EEG potentials were collected at a sampling
rate of 2000 Hz, amplified 2500 times (0.034 µV/bit resolution, 16 bit resolution), and bandpass filtered (slope 12
dB/octave) between 1 and 200 Hz. Artifacts, such as eye
movements or muscle activity, with potentials greater
than ±200 µV in any channel, were automatically rejected
prior to averaging (between 0 and 9% of the sweeps). For
Sources for Auditory Steady-State Responses
each stimulus condition, average ASSRs were obtained
by averaging 200 EEG epochs of 1023 ms. The average responses were then recalculated relative to an average reference and the Cz waveform added to give a 47-channel
recording for source analysis.
71
to the equivalent of two cycles of the stimulus. Because
this was not an integer factor of the available 2048 points,
we initially spline-fit the full sweep with a set of data containing an integer number of points per two-cycle period.
We also splined the 12-Hz responses to obtain a single cycle of the response.
Stimuli
The stimuli were produced by digitally modulating a
sine wave by another sine wave to obtain a 1000-Hz waveform with 100% amplitude modulation. The digital waveform was then converted into analog form with a 12-bit
resolution digital-to-analog converter running at a rate of
10 kHz. The stimulus was amplified to a calibration level
then attenuated to 70 dB SPL or approximately 60 dB nHL
(Herdman and Stapells 2001) and presented to the subject
through Eartone 3A insert earphones. Stimulus artefacts
were ruled out by control recordings with the transducers
removed from the ears and the canals plugged.
The stimulus was constructed and presented using a
program that continuously recycled a buffer containing
10240 values. The frequency of both carrier and modulation signals were adjusted to give an integer number of
cycles in the buffer. This ensured that no acoustic artifacts occurred as the buffer was recycled, and that the frequency analysis could measure responses at exactly the
modulation frequency. Three frequencies of modulation
were used: 11.72, 39.06 and 87.89 Hz (equivalent to 12, 39
and 90 cycles per sweep).
The Fast Fourier Transform (FFT) also required that
the number of points in the response waveform was a
power of two and that the response was exactly triggered
by the onset of the stimulus buffer. These criteria are reviewed more extensively in John and Picton (2000). We
synchronized the stimulus computer and the Neuroscan
amplifiers using the Neuroscan clock. The Neuroscan
provide a sweep of 2048 addresses.
Experimental Protocol
EEG recordings were obtained in a two-hour session. During this time, subjects relaxed quietly in a comfortable chair, and maintained a wakeful state of
alertness by reading novels or magazines. The presentation of the AM tones was randomized for the different
modulation frequencies (12, 39, and 88 Hz) and for the
two ears. For each frequency of modulation and ear of
stimulation, we obtained responses from two separate
recording sessions (each containing 200 epochs and lasting about four minutes).
Scalp Waveforms
In order to look at the actual temporal waveforms of
the response, we collapsed the 1.024-second sweep down
Frequency Analysis
Each averaged sweep was analyzed at each of the 47
electrodes using a Fast Fourier Transform (FFT). The real
and imaginary values at the frequency of stimulation
were then plotted using vector diagrams (with the real
values on the x-axis and the imaginary values on the
y-axis) and stored for evaluation in the source analysis
programs.
Phase Topography
The vector data from the FFT can be portrayed over
the scalp using a graphical convention similar to that used
in meteorology to portray the strength and direction of the
wind. However, contour-mapping two-dimensional data
over the scalp is not simple. One cannot just map the amplitude since this would miss the fact that some responses
have inverted polarity from others (i.e., are 180° out of
phase). Separate amplitude- and phase-maps are not easy
to understand. The techniques described by Lehmann
and Michel (1989, 1990) to project the activity onto a dominant phase axis and then map the projected activity can
miss the complexity of the response which can change in
topography over each cycle of the response. BESA 2000 allows one to construct a series of "phase maps" at successive phase angles θ by using spherical splines to map the
values at each electrode calculated as
x ef cos(θ) + y ef sin(θ)
where xef and yef are the real and imaginary components
at electrode e for frequency f (Scherg et al. 2002). This
looks at the changing topography at different times during a cycle of the response, with the time measured in
terms of degrees. A change of topography in consecutive
maps indicates multiple underlying processes. If there is
no shift in topography with phase, a single generator
process may be assumed (although this is much more
difficult to prove).
Brain Electric Source Analysis (BESA)
Source analysis was carried out using BESA 3.0. This
analysis was carried out using a four-shell head model
with relative conductivities (relative to brain) of 1.0, 3.0,
0.0125 and 1.0 for the brain, cerebrospinal fluid, skull and
scalp, and radii of 71, 72, 79 and 85 mm (Berg and Scherg
72
1994). The source analysis used two points in the frequency domain (real and imaginary) per electrode to
evaluate dipole sources.
A brainstem source was fit using the 88-Hz
grand-mean data. We were able to fit separate sources for
the responses to left- and right-ear stimulation with each
source being at the same level, a little to the side of stimulation and oriented to the contralateral side. However, these
sources were close together and we could not use them simultaneously if the data for left and right ears were analyzed together. We therefore decided to use one midline
source (1) and to allow it to fit its orientation only in the
mid-sagittal plane. Once this was fit, we added a second
dipole source (2) at the location of the first and oriented it
laterally to the right. This would pick up the main differences between the left and right-ear responses.
In order to fit the 39-Hz grand-mean data, we added
two symmetrical sources (3 and 4) to the two brainstem
sources (1 and 2) and fit their location and orientation using all the 39-Hz data. Additional radial dipoles (5 and 6)
were added at the location of dipoles 3 and 4, because activity in the auditory cortex has radial as well as tangential components (Scherg and von Cramon 1986; Scherg et
al. 1989). Then dipoles 3 and 4 were refit. This resulted in
an "overall" model that was based on the grand-mean responses at both 88 and 39 Hz. This model was then used
to model both the grand-mean data and each subject’s
data at all three rates of stimulation
Using the data obtained from individual subjects, two
3-factor repeated-measures analyses of variance (ANOVA)
compared the amount of activity and the estimated latencies at each of the six sources across the three different conditions and the two ears (i.e., 6 sources × 3 modulation
frequencies × 2 ears) . Three of the ten subjects had data
missing for left- and right-ear stimulation of 12 Hz (subject
5 and 6) or 88 Hz (subject 4 and 5). Thus, repeated-measures
ANOVAs compared results from seven subjects with complete datasets. For ease of interpreting the ANOVAs, the
sources were reclassified to a vertically-oriented brainstem
source (S1), laterally-oriented brainstem source (S2), tangentially-oriented ipsilateral cortical sources (S3 for left ear
and S4 for right ear), tangentially-oriented contralateral
cortical sources (S4 for the left ear and S3 for the right ear),
radially-oriented ipsilateral cortical sources (S5 for left ear
and S6 for right ear), and radially-oriented contralateral
cortical sources (S6 for the left ear and S5 for the right ear).
Results of the ANOVAs were considered significant if
p<.01. Greenhouse-Geisser epsilon correction factors for
degrees of freedom were used when appropriate.
Newman-Keuls post hoc comparisons were performed
only for significant main effects and interactions. Results of
the post hoc tests were considered significant if p<.05.
In addition to interpreting each subject’s responses
according to the overall model, we also separately fit di-
Herdman et al.
poles to each subject’s data using a simpler model with a
single midline source and two symmetric hemispheric
dipoles. The brainstem dipole was fit to the 88-Hz data
and the cortical dipoles then added and fit to the 39-Hz
data. This allowed us to estimate the inter-subject variability in estimating the source-locations. The signal-to-noise levels of the individual subject’s data did not
allow us to fit more than these three dipole sources.
Latency of Source Activity
Each source "waveform" consisted of two components, in the real and imaginary dimensions of the frequency domain. From these components we could derive
a phase, calculated as the cosine onset phase. This value
(θ) was adjusted to give a phase delay Φ using the equation 360-θ-90, with the final term compensating for the fact
that the stimulus modulation used a sine rather than a cosine function. The latency of the source activity was estimated from the phase delay. Unfortunately, the phase of a
steady-state response cannot be directly converted into latency because it is impossible to know how many cycles
intervened between the stimulus and the recorded cycle
of the response. We calculated the latency in seconds as
Φ/(360f)+N/f where Φ is the phase delay in degrees, N is
the number of preceding modulation cycles, and f is the
modulation frequency in Hz. For the 12-Hz and 39-Hz
data, we arbitrarily set N to 0 and 1 for brainstem and cortical sources, respectively. For the 88-Hz data, N was set to
1 and 2 for brainstem and cortical sources, respectively.
This provided reasonable latencies that fit with the approximate travel-time delays between the cochlea and
brainstem, and between the brainstem and cortex. An additional cycle was added to some of the data to make the
relations between the cortical sources more consistent.
Results
Scalp Recorded Responses
Figure 1 shows how the scalp-recorded responses
were analysed using of the grand-mean response to
left-ear stimulation at 39 Hz as an example. Figure 1A
shows the average time-domain response to 2-cycles of
stimulation. As can be seen the response inverted in polarity between the fronto-central regions of the scalp and
the posterior neck. The inversion occurred over a curved
line running through the mid-temporal and mid-parietal
regions. Figure 1B shows the polar plots of the responses
derived from the FFTs of the full 1.024 second sweep
rather than the 2-cycle sweep. The phase is the cosine onset phase, measured in a counter-clockwise direction
from the right-sided horizontal axis. The cosine onset
phase of the response was approximately 250° at the ver-
Sources for Auditory Steady-State Responses
73
Figure 1. (A) Time-domain waveforms for grand-mean auditory steady-state responses recorded in response to a 1000-Hz
tone amplitude-modulated at 39 Hz and presented at 70 dB SPL to the left ear. Waveforms representing the responses to
2-cycles of the stimulus were recorded from 47 scalp electrodes. These are plotted at the equivalent electrode position
when looking at the scalp from above with the nose at the top of the figure. The ellipse represents the "equator" of the
head running through electrodes T7, T8 and Oz. Electrodes below the equator are plotted beyond the ellipse. (B) Scalp
distribution of polar plots representing the amplitude and phase of the grand-mean auditory steady-state responses
shown in (A). These frequency-based measurements were based on 1.024 seconds rather than the 2-cycle period shown
in (A). The magnitude of the vector in a polar plot represents the amplitude of the response and the angle between the
vector and the horizontal axis measured counter-clockwise represents the cosine onset phase.
74
tex electrode and 60° at the neck electrode. These phases
can also be estimated from the time-waveforms in figure
1A. For example, at the vertex the time-waveform approximates a sine wave beginning with a phase of about
-20°. This would be equivalent to a cosine wave beginning
at -110° (or +250°). The phases on the polar plots also
agree with the approximate inversion in polarity (a phase
shift of 180°) seen between vertex and neck. Here the vectors are aligned along a similar directional axis for the vertex (center of the ellipse) and the neck (most inferior plot),
but go in opposite directions along this axes (down and to
the left for the vertex and up and to the right for the neck).
The response recorded at the mid-temporal electrodes
(on the right and left most extrema of the ellipse) showed
a different phase from responses recorded at posterior
neck electrodes. This is most clearly seen in the polar representation in figure 1B where the vector points up and to
the left for the mid-temporal locations (larger on the right)
and up and to the right for the neck.
The response to the right ear stimulation was very
similar to that recorded to left ear stimulation. The overall amplitudes and phases of the responses at the different electrode locations were similar for the different ears
of stimulation, except that the responses over the mastoid and neck ipsilateral to stimulation were larger than
over the contralateral region.
The responses to the 88-Hz stimuli were smaller than
those recorded at 39 Hz and more variable from subject to
subject. Figure 2A shows the grand-mean temporal
waveform for the 88-Hz response to left-ear stimulation.
As well as being smaller than the response at 39 Hz, the responses showed a greater asymmetry in the mastoid regions, again being larger ipsilateral to stimulation.
The time-domain waveforms for the 12-Hz stimuli
were clearly not sinusoidal at the frequency of stimulation.
A single cycle of the grand-mean response to left-ear stimulation is shown in figure 2B. The vertex response showed
a prominent positive wave peaking at 21 ms after the onset
of the sweep (which occurs at 0° on the sinusoidal modulation waveform - the half-amplitude point). The frequency
spectrum of the response at the vertex contained as much
activity at the second and third harmonics as at the modulation frequency. Interestingly, the amplitude-spectrum
varied across the scalp and at the mid-temporal electrode
the dominant activity was at the modulation frequency.
Figure 3 compares the spectra for the responses at the three
different modulation frequencies.
Phase Topography
The topography of the 39 Hz response changed significantly when examined at different locations during
the cycle (figure 4). The topography with the largest
global field power occurred at phases near 120° and 300°.
Herdman et al.
This topography had maxima/minima at the mid-frontal
region of the scalp and the posterior neck electrodes. A
strikingly different topography with maxima/minima at
the lateral temporal electrodes and anterior frontal electrodes is seen at 30° and 210°. This was larger over the
right hemisphere than the left. The response to right ear
stimulation showed a similar pattern (with the laterally-oriented topography again larger over the right than
over the left). Phase topography of the 88 Hz responses
showed a consistent pattern over the cycle with maxima/minima at the mid-frontal and neck locations. Evaluation of the phase topography of the 12 Hz responses
was difficult because of the low signal levels at the stimulus frequency. The results for these responses at the second harmonic of 24 Hz showed lateral patterns but these
were again small and difficult to evaluate.
Source Analyses
Figure 5 represents the model used to analyse the
scalp-recorded data in the frequency domain. For each
frequency of stimulation, the analysis is shown for
left-ear stimulation. The analysis for the mean data is
shown by the thick line with a closed circle, and the analysis for the individual subjects by the thin lines. For the
39- and 88-Hz responses, data from the individual subjects showed similar phases to the mean responses. For
the 12-Hz responses, the phases were quite variable between subjects (figure 5). Table I shows the residual variance for fitting the scalp-recorded grand-mean and
individual responses using the overall model.
When dipoles were fit to the individual subjects’
data, the locations were quite variable because certain
subjects show unusual waveforms at some electrode locations, particularly the neck, mastoid and facial electrodes. Examining the scalp-recorded waveforms shows
that this was related to increased noise or unusually large
responses at specific electrodes that the analysis was attempting to fit. Nevertheless, the mean locations of the
three sources used in this analysis were similar to those
obtained by fitting the grand-mean data (table II).
Table III presents the amplitudes and estimated latencies of the source waveform from the grand-mean
data. For 12-Hz modulation, the sources showed low
level activity and there was little difference in amplitudes between source waveforms. Conversely, at a modulation frequency of 39 Hz the vertically-oriented
brainstem source (source 1) and the two tangential cortical sources (sources 3 and 4) were larger in amplitude
than the other sources. For the 88-Hz modulation, the
vertically-oriented brainstem source was larger than all
other sources. Latencies increased with decreasing modulation frequency, and were shorter for the brainstem
sources than for the cortical sources.
Sources for Auditory Steady-State Responses
75
Figure 2. (A) Time-domain waveforms for grand-mean auditory steady-state responses in response to 2-cycles of a 1000-Hz
tone amplitude-modulated at 88 Hz and presented at 70 dB SPL to the left ear. (B) Time-domain waveforms for
grand-mean auditory steady-state responses to 1-cycle of a 1000-Hz tone amplitude-modulated at 12 Hz and presented
at 70 dB SPL to the left ear.
76
Herdman et al.
Figure 3. Amplitude spectra at electrodes Cz (vertex) and T8 (right mid-temporal) for responses to tones amplitude-modulated modulated at 12, 39, and 88 Hz. Arrows designate responses and their harmonics.
Table IV compares the amplitudes for the different
sources at different modulation frequencies (12, 39, and
88 Hz) and for the left- and right-ear stimulation. Post hoc
tests of the main effect of sources revealed that tangentially-oriented cortical sources were significantly larger,
averaged across modulation frequency and ear stimulation, than radially-oriented cortical sources (F = 19.8; df =
5, 30; p<.0001). Furthermore, post hoc tests of the interaction between sources and modulation frequency showed
that tangentially-oriented cortical sources were significantly larger at 39 Hz than at 88 or 12 Hz (F = 4.98; df = 10,
60; p<.0001). This was also true for the vertically-oriented
brainstem sources, which were larger for 39 Hz than the
other modulation frequencies. Mean amplitudes for leftand right-ear stimulation, averaged across modulation
frequency and sources, were not considerably different
from one another (means = 1.69 and 1.45, respectively).
There was no evidence that the contralateral cortical responses were larger than the ipsilateral.
Table V presents the mean estimated latencies of the
source waveforms from the individual data. As modulation frequency decreased from 88 Hz to 12 Hz, latencies
became significantly prolonged (F=478.4; df=2,12;
p<.0001). Latencies for the brainstem sources were statistically shorter than for the cortical sources, as revealed by
post hoc tests of the main effect of sources (F=76.4,
df=5,30; p<.0001). Interactions between modulation frequencies and sources, revealed no significant differences
between ipsilateral and contralateral cortices, for any of
the modulation frequencies. Furthermore, there were no
differences between latencies for tangential and radial
components. However, post hoc tests of the interaction
between sources and modulation frequency revealed
that tangentially-oriented cortical (ipsi and contra lateral
Sources for Auditory Steady-State Responses
77
Figure 4. Phase topography of the response to left-ear stimulation with a tone modulated at 39 Hz (shown in figure 1 in the
time domain and in the polar plots). Negative voltages are represented by dashed lines and positive voltages by solid
lines. The topographies are plotted at different locations (every 30°) during a single cycle of the response. The topography
changes with the phase showing a vertically-oriented dipolar pattern with maxima/minima in the mid-frontal and posterior neck (at 120 and 300°) and a pattern with maxima/minima in the mid-temporal regions (30 and 210°).
combined) activity was significantly prolonged for 39 Hz
than for 88 Hz (F=24.8; df=10,60; p<.0001).
Figure 6 shows the source waveforms when the
model was used to examine the 2-cycle time waveforms
for 88 and 39 Hz responses. The time-domain data were
the same as those shown (for the left ear) in figures 1 and
2, and the source model was the same as used for the
analyses in figure 5. The source waveforms for the 88-Hz
response showed the dominant activity in source 1 with
source 2 showing smaller activity that inverted between
the ears of stimulation. Effectively, each ear activates a
response that is oriented between the ipsilateral ear and
the fronto-central regions. Source 2 was designed to pick
up this asymmetry, since it was not possible to model simultaneously two sources in the left and right brainstem.
There was some low-level activity at sources 3 and 4 in
response to the 88-Hz stimulus. This activity occurred
about 120° before (or more likely 240° after) the
brainstem response. The 240° after translates to the 7-8
ms differences between the brainstem vertical source
and the tangential cortex sources in table III.
The source waveforms for the 39 Hz responses (right
side of figure 6) show dominant activity at sources 1, 3 and
4. The cosine onset phase of the waveform at source 1 is
78
Herdman et al.
Figure 5. Polar plots for source activity underlying the responses to the 12-, 39-, and 88-Hz AM tones. The magnitude of a
vector in a polar plot represents the amplitude of the source activity and the angle between the vector and horizontal axis
when measured counter-clockwise, represents the onset phase. Mean vector results are designated by thick lines with a
filled circle, while vectors for each subject are designated by thin lines. The diagram of the head at the bottom of the figure
shows the location and orientation of the dipole sources.
about -140° and at sources 3 and 4 is about -90°. These
phases were related in a similar way to the phases of the
surface-recorded responses at the vertex (-125°) and the Fz
(-110°) electrodes, respectively, in figure 1. Both sources
contributed to the waveforms at both electrodes, with
source 1 contributing more to the vertex waveform and
sources 3 and 4 contributing more to the Fz waveform.
The difference in phase (310°) translates to the 22-27 ms la-
tency difference between the brainstem and the tangential
cortical sources in table III. Sources 5 and 6 were active but
the phase of this activity varied with the ear and the
source. The phase topography shown in figure 4 can be
followed in terms of the source waveforms for the left ear
(dashed line) in the right column of figure 6. At 30° into the
response (first hash mark onthe horizontal axis for the 39
Hz response in figure 6), the activity for source 1 was close
Sources for Auditory Steady-State Responses
79
Table I. Model Fitting. Residual variances (%) for source models fitting grand-mean data and mean residual variances and
standard deviations for fitting source models to individual data. Numbers of subjects are given within parentheses.
Ear
Left
Right
Modulation Frequency
Grand Mean
From Individual Subjects
12 Hz
12.2
22.8 ± 16.4
(8)
39 Hz
3.3
12.2 ± 7.4
(10)
88 Hz
9.6
30.6 ± 14.0
(8)
12 Hz
11.3
21.0 ± 8.0
(8)
39 Hz
3.0
11.8 ± 9.2
(10)
88 Hz
6.8
32.8 ± 18.1
(8)
to zero, there was some positive activity from sources 3
and 4 which would explain the frontal positivity and there
was maximum negative activity from source 6 which
would explain the temporal negativity. Source 6 was able
to show up on the phase topography since it was active
when other sources (such as source 1) were inactive.
Discussion
tently active at all rates of stimulation whereas the
cortical sources are more active at slower rates (particularly at 39 Hz). This general idea is consistent with animal recordings showing that the cortex does not respond
as well as the brainstem auditory nuclei at rapid rates
(Creutzfeldt et al. 1980; Rees and Møller 1983; Fastl et al.
1986; Batra et al. 1989; Frisina et al. 1990; Kiren et al. 1994).
12 Hz
Sources
The model that we used to fit the scalp-recorded
data contains brainstem sources and bilateral cortical
sources localized near the supratemporal plane. This
model suggests that both the brainstem and the auditory
cortex are active during the processing of sinusoidally
AM tones. For our responses, the brainstem is consis-
The responses to the 12-Hz stimulus did not show
much energy at the frequency of modulation. Picton et
al. (1987) found that the responses at these modulation
frequencies are often difficult to distinguish from the
background EEG noise. The spectrum of the response
showed significant activity at higher harmonics. This is
the pattern that one gets from a repeating transient response. This response, recorded in the time domain (fig-
Table II. Source Locations. Location-coordinates are in mm relative to the center of the sphere used to analyze sources for
the overall model and sources fitted from individual subjects. The x dimension is from left (-) to right (+), the y-dimension
from back (-) to front (+), and the z dimension form below (-) to above (+). The left cortical source is located symmetrically
to the right (i.e. has a negative x coordinate).
Source
Brainstem
Cortical (right)
Coordinate
Overall Model
From Individual Subjects
x
0
0
y
1
-1 ± 15
z
-4
-8 ± 11
x
54
43 ± 20
y
6
-1 ± 16
z
15
3 ± 10
80
Herdman et al.
Table III. Source Activity. Amplitudes (nAmp) and estimated latencies (ms; in parentheses) for source waveforms fit using
the grand-mean data. Source results are compared between ear stimulation (left and right) and modulation frequency
(fm: 12, 39, and 88 Hz).
Ear
fm
Brainstem
Vertical
Brainstem
Lateral
Ipsilateral Cortex
Tangential
Contralateral Cortex
Tangential
Ipsilateral Cortex
Radial
Contralateral
Cortex Radial
12 Hz
1.16
(21)
2.03
(58)
1.30
(154)
2.36
(166)
0.96
(165)
1.37
(168)
39 Hz
3.39
(29)
0.95
(26)
1.75
(48)
2.58
(50)
0.71
(52)
0.83
(59)
88 Hz
1.40
(18)
0.64
(17)
0.45
(26)
0.40
(26)
0.24
(27)
0.35
(35)
12 Hz
0.88
(63)
0.78
(90)
0.93
(186)
0.98
(181)
0.67
(176)
0.36
(171)
Right 39 Hz
3.98
(27)
0.29
(18)
2.33
(49)
1.65
(48)
0.87
(57)
0.64
(53)
88 Hz
1.75
(18)
0.49
(24)
0.52
(26)
0.27
(25)
0.17
(33)
0.50
(25)
Left
ure 2), is likely triggered by the beginning of the rise in
the tonal amplitude in each cycle of the modulation.
Since we used a sinusoidal modulation envelope, the onset of the rise in amplitude would occur one-quarter cycle before the onset of the recording sweep. This would
give the vertex positive wave a peak latency of 42 ms
from the onset of the rise in amplitude (the measured
peak latency of 21 ms plus one quarter of the 85.3 ms cycle duration). The wave is, therefore, likely homologous
to the Pa wave of the transient response, which occurs
with a peak-latency of about 30-35 ms (Picton et al. 1974).
One would estimate the latency to be delayed by the longer rise time of the modulated stimulus (Brinkmann and
Scherg 1979). We had expected to see radial and tangential components of the response related to the compo-
nents underlying the P1, N1, and P2 waves of the transient response (Wood and Wolpaw 1982; Scherg et al.
1989). However, the responses were too small to provide
reliable radial source components.
39 Hz
Our scalp-recorded data for the 39-Hz response are
similar to those reported by Johnson et al. (1988). On the
basis of the polarity inversion over the mid-temporal regions, they suggest that the response is partially generated in the auditory cortices on the upper surface of the
temporal lobe. They also suggest that thalamic activity
and thalamo-cortical circuits might be involved in the response. Our analyses suggest that both the cortex and
Table IV. Source Asymmetries. Mean and standard deviations for amplitudes (nAmp) of the six sources included in the
ANOVA comparing across ear stimulation (left and right) and modulation frequency (fm: 12, 39, 88 Hz). Data are averaged
over seven subjects.
Ear
Left
fm
Brainstem
Vertical
Brainstem
Lateral
Ipsilateral Cortex
Tangential
Contralateral Cortex Ipsilateral Cortex
Tangential
Radial
Contralateral
Cortex Radial
12 Hz
3.56 ± 2.38
2.03 ± 0.84
1.30 ± 0.93
2.36 ± 1.69
0.96 ± 0.83
1.37 ± 0.73
39 Hz
4.95 ± 1.71
1.27 ± 1.26
2.32 ± 1.28
3.36 ± 1.42
0.99 ± 0.54
1.40 ± 0.92
88 Hz
1.77 ± 0.62
0.82 ± 0.38
0.58 ± 0.40
0.63 ± 0.37
0.31 ± 0.22
0.42 ± 0.24
12 Hz
1.98 ± 1.66
0.95 ± 0.82
1.41 ± 0.94
1.50 ± 1.03
0.46 ± 0.22
0.89 ± 0.66
Right 39 Hz
5.22 ± 2.75
0.96 ± 0.41
3.02 ± 1.27
2.49 ± 0.90
1.21 ± 0.79
0.94 ± 0.47
88 Hz
2.14 ± 0.91
0.71 ± 0.36
0.74 ± 0.24
0.57 ± 0.26
0.38 ± 0.20
0.50 ± 0.41
Sources for Auditory Steady-State Responses
81
Table V. Latencies. Mean and standard deviations for estimated latencies (ms) for the six sources included in the ANOVA
comparing across ear stimulation (left and right) and modulation frequency (fm:12, 39, 88 Hz). Latencies are averages for
seven subjects.
Ear
Left
fm
Brainstem
Vertical
Brainstem
Lateral
Ipsilateral Cortex
Tangential
Contralateral Cortex Ipsilateral Cortex
Tangential
Radial
Contralateral
Cortex Radial
12 Hz
67 ± 28
57 ± 11
155 ± 24
146 ± 25
138 ± 30
146 ± 32
39 Hz
22 ± 10
23 ± 7
47 ± 3
49 ± 3
51 ± 3
39 ± 8
88 Hz
19 ± 2
17 ± 1
29 ± 5
31 ± 5
28 ± 4
32 ± 4
12 Hz
63 ± 26
68 ± 25
150 ± 32
160 ± 29
158 ± 27
149 ± 28
Right 39 Hz
25 ± 9
19 ± 6
47 ± 4
48 ± 3
47 ± 8
40 ± 10
88 Hz
19 ± 1
21 ± 4
31 ± 4
28 ± 4
25 ± 0
33 ± 3
brainstem are simultaneously active and that the
scalp-recorded fields result from overlapping fields from
multiple generators. This is similar to the interpretation
of Mauer and Döring (1999). The brainstem responses at
39 Hz are activated at shorter latencies, but the latency
difference between the activation at brainstem and the
tangential cortical dipoles (table III - 22-27 ms) is roughly
equivalent to one cycle of the stimulus and thus, the responses add together in the overlap.
The laterally-oriented sources 5 and 6 are active in response to the 39 Hz response. These show up clearly in the
analysis of phase topography (figure 4). When the other
sources are less active during the stimulus cycle, the effects
of the laterally-oriented sources becomes evident (e.g. at 30
and 120°). In the evaluation of transient MLRs, there are radial sources that are activated a few milliseconds after the
tangential sources (Scherg and von Crammon 1986) differences were not apparent in our data, perhaps because of
higher noise levels in the recordings.
Spydell et al. (1985) reported that the auditory 40-Hz
response is reduced in patients with brainstem or thalamic
lesions, but not in patients with unilateral lesions of the
temporal lobe. The 40-Hz response is usually absent in comatose patients and in patients with brain death, in keeping with a crucial role for the upper brainstem in
generating this response (Firsching et al. 1987). The absence of effects of unilateral temporal lobe lesions may be
related to the remaining temporal lobe generating a response that can be recorded from the vertex.
88 Hz
Our data suggest that the 88-Hz ASSRs are mainly
generated in the auditory pathways of the brainstem.
There is limited data regarding generators for the 80-Hz
ASSR. Inferences from intercellular recordings within the
cochlear nucleus and inferior colliculus to sinusoidally AM
tones predominantly suggest subcortical origins (Batra et
al. 1989; Creutzfeldt et al. 1980; Frisina et al. 1990; Rees and
Møller 1983). Neurons within the cochlear nucleus respond best to modulation rates above 80 Hz (Frisina et al.
1990; Møller 1976); while those in the inferior colliculus respond best to rates between 20 to 40 Hz (Batra et al. 1989).
This implies that possible generation of the 40- and 80-Hz
ASSR arise from the inferior colliculus and cochlear nucleus, respectively. Kiren and associates (1994) ruled out
the cortex as a possible generator of the 80-Hz auditory
steady-state response by bilaterally aspirating the auditory
cortices in cats. They revealed no change in 80-Hz response
phase, thus providing evidence for non-cortical generators. Within this same study, they demonstrated significant phase changes in ASSRs for both ipsilateral and
contralateral lesions to the inferior colliculus. The inferior
colliculus may play an important role in the generation of
80-Hz responses. Species differences may make it difficult
to translate these findings to humans. However, our results do confirm that, in humans, the brainstem is the primary source of the scalp-recorded responses to AM tones
modulated at fast rates (i.e., 88 Hz).
Latency Estimations
Estimating the latency of steady-state responses can
be problematic (John and Picton 2000). One does not
know how many cycles have intervened between the
stimulus and the response that one is recording. This
was a particular problem for the individual data (table V)
which were more variable than the mean data, particularly for the small radial sources 5 and 6. Furthermore,
one does not know whether the modulation waveform
evokes a similar response waveform or one inverted in
polarity and, therefore, a 180° difference in phase. Our
calculations arbitrarily assumed intervening cycles and
similar response and stimulus waveforms (i.e., that the
82
Herdman et al.
Figure 6. Time domain waveforms for the source activity underlying the responses at 88 and 39 Hz. The responses to left-ear
stimulation are shown with dotted lines and the responses to right-ear stimulation with continuous lines. The time axis is
equivalent to 2 cycles of the stimulus. In order to facilitate comparison to figure 4, the time scale is divided into 30° sections
(12 per cycle). The main activity underlying the 88-Hz response is at source 1 with a time waveform similar to that recorded
from the vertex or mid-frontal regions (see figure 2). The activity underlying the 39-Hz response occurs at sources 1, 3 and 4.
The waveforms at these source locations differ in onset phase by about 80°. The response waveform recorded at the vertex (see figure 1) has a phase close to that of the source 1 activity and the response recorded from the mid-frontal regions
is more like the waveforms of sources 3 and 4. Low-level activity also occurs at sources 5 and 6 with an onset-phase similar
to the surface waveform recorded at the mid-temporal electrodes (figure 1).
peak of the modulation envelope evoked a positive wave
at the vertex). Calculating apparent latencies can obviate
some of these problems (Regan 1989). In order to make
such calculations one needs to record responses at different modulation frequencies within each frequency region, and this was not done in the present study.
Although we cannot conclusively determine the latency for our source waveforms, our estimated latencies
agree with the apparent latencies previously reported for
ASSRs (Rickards and Clark 1984; Stapells et al. 1984; Linden et al. 1985; Kuwada et al. 1986; Picton et al. 1987;
Stapells et al. 1987; Cohen et al. 1991). A limited number
of investigations of ASSR to AM tones modulated at low
rates (i.e., <25 Hz) have reported apparent latencies between 75 and 153 ms (Rickards and Clark 1984; Stapells et
al. 1987). Our estimated latency results for cortical
Sources for Auditory Steady-State Responses
sources are similar. However, there is considerable variability in onset phase between subjects (see figure 5), and
the results should be interpreted with caution. Our data
(table III) show latencies around 140 ms which is likely
related to the latency of the P1-P2 waves of the transient
response. At rapid stimulus rates (e.g., figure 1 of Alain
et al. 1994; figure 5 of Roß et al. 2002) the N1 wave of the
response decreases in amplitude and the P1 and P2
waves meld into one wave, or the P1 increases in latency
to between the normal P1 and P2 response.
Our estimated latency of 48 ms for ASSR cortical
source waveforms to the 1000-Hz AM tones modulated
at 39 Hz are later than the apparent latencies (25 to 41 ms)
previously reported (34 ms from Stapells et al. 1984; 32
ms from Kuwada et al. 1986; 36 ms from Linden et al.
1985; 38 ms from Picton et al. 1987; 41 ms from Stapells et
al. 1987; 25 ms from Cohen et al. 1991). Our latencies may
be prolonged due to different stimulus and recording parameters, such as the alertness of the participants or the
intensity of the stimuli. As pointed out by Rickards and
Clark (1984), latencies for 40-Hz modulation rates are
similar to those of the transient MLRs (Picton et al. 1974).
Magnetically recorded 40-Hz ASSRs have been shown to
have comparable latencies to those for their transient
middle-latency counterparts (Hari et al. 1989; Roß et al.
2000). Our estimated latencies and source locations are in
agreement to those reported for these magnetically recorded ASSRs. Such similarities may further indicate
that ASSRs have cortical generators comparable to those
for transient MLRs (Scherg and von Cramon 1986;
Gutschalk et al. 1999).
We estimated a one-cycle difference between the
brainstem and cortical sources, although the latency differences could have been longer or shorter than the estimated 25 ms. However, for the 39-Hz modulation rate,
the approximate latency difference of 25 ms between
brainstem and cortical sources (see table V) suggests
some type of 40-Hz oscillatory behavior between these
generators (Ribary et al. 1991).
The latencies for the brainstem sources are more delayed at 12- and 39-Hz as compared to 88-Hz. This may
be a result of the slower modulation envelopes of the 12and 39-Hz AM tones as compared to the 88-Hz.
For ASSRs evoked by AM tones modulated at 88 Hz,
the small amplitude cortical sources had shorter latencies
than for the 39-Hz modulation rate. Nevertheless, they
are still near the latencies for the transient middle latency
response. From the present study, the large amplitude
brainstem source activity for the 88-Hz modulation rate
has an estimated latency of 19 ms that is comparable to
the 19 ms and 13 ms apparent latencies reported by John
and Picton (2000) and by Cohen et al. (1991), respectively.
The shorter latencies from Cohen et al. (1991) may be the
result of basing the latency estimates on a range of modu-
83
lation frequencies that extended higher than the range
used by John and Picton (2000).
Some Caveats
Source modeling for these responses are limited by
the amount of data available for each response: two values (real and imaginary) at each electrode location. This
approach increases the signal-to-noise ratio of the recordings, because only data that is exactly time locked to
the stimulus would be evaluated in the frequency bin of
the FFT that equals the modulation frequency. However,
it does limit the amount of data that is submitted to the
source analysis. The analysis is, therefore, performed using many constraints: fixing the brainstem sources to the
midline and making the cortical sources symmetric. The
modeling is more confirmatory than analytic. We show
that the data could be reasonably interpreted using the
combination of brainstem and cortical dipoles, but these
dipoles are derived as much from our hypotheses as
from our data.
The scalp-recorded waveforms of the 39-Hz responses are about five times larger than the 88-Hz responses. Although the noise levels near 88 Hz are less than
those near 39 Hz, this difference is not sufficient to counteract the differences in response amplitudes and the signal-to-noise ratio was lower for the 88-Hz responses.
Because responses recorded with slower rates are larger in
wakefulness than in sleep (Linden et al. 1985; Dobie and
Wilson 1998), we decided to have our subjects awake for all
recordings. However, one generally records the 80-100 Hz
ASSRs from sleeping subjects because this reduces the
background noise at these frequencies (mainly from muscle activity) without significantly affecting the response
(Cohen et al. 1991). In retrospect, it might have been better
to record the 88-Hz response in sleeping subjects and the
39-Hz responses in waking subjects.
Repeating sound patterns can evoke reflexes in the
scalp muscles and these can affect the recordings in unpredictable ways. These reflexes are usually evoked by
high intensity sounds and are usually bilateral. However, they may be asymmetric and variable in location
from one subject to another (Picton et al. 1974; Gibson
1979). These may have contributed to our scalp recorded
responses. Recent work has shown that the postauricular
muscle reflex may be quite asymmetrical if the eyes look
in one direction (Patuzzi and Thomson 2000). Looking
toward the stimulated ear might have increased the size
of the postauricular muscle response on the mastoid near
the stimulated ear. This may, in some subjects, have accentuated the asymmetry for the 88 Hz response, since
the muscle reflex has a negative wave peaking at about
12 ms after the stimulus. This negativity could add with
the inverse of the vertex recorded positive wave.
84
Clinical Significance
Because ASSRs are becoming an alternate means of
objectively evaluating hearing thresholds in hard-to-test
patients, there is a need for clinicians to understand the
level of the auditory system being evaluated. Testing patients using ASSRs to AM tones modulated between
70-110 Hz would suggest normal auditory function (i.e.,
hearing sensitivity) up to the level of the brainstem. Dysfunction further along the auditory pathway may not be
resolved unless slower rates (i.e., 40-Hz) are used.
Slowing the rate of modulation may only be useful in
adults or young children because 40-Hz responses are
not reliably recorded in infants (Aoyagi et al. 1993;
Maurizi et al. 1990; Stapells et al. 1988; Suzuki and
Kobayashi 1984).
To date, there are limited data to suggest what the effects of auditory dysfunctions, such as auditory neuropathy or central auditory lesions, would have on ASSRs.
Because ASSRs require synchronous activity (see John
and Picton 2000), the desynchronization due to auditory
neuropathy (Starr et al. 1996) may disrupt the recording
of the ASSRs, particularly at faster rates of stimulation.
Upper brainstem lesions have been reported to produce
abnormal 40-Hz ASSRs (Rei and Fu 1988; Spydell et al.
1985); however, unilateral cortical lesions did not alter
the phase of the 40-Hz response (Spydell et al. 1985). This
could be a result of the contralateral (non-lesioned) cortex generating a stable 40-Hz response.
Our results suggest that central abnormalities may
be identified using ASSRs modulated at several different
rates. Rates around 80-Hz may provide a means of identifying brainstem abnormalities, whereas rates near 40-Hz
may help to locate cortical lesions. However, the effects
of lesions within the auditory system require further investigation.
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