Department of Molecular and Cell Biology, Division of Neurobiology, University of California, Berkeley, California 94720
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ABSTRACT |
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Ohl, Frank W., H. Scheich, and Walter J. Freeman. Topographic Analysis of Epidural Pure-Tone-Evoked Potentials in Gerbil Auditory Cortex. J. Neurophysiol. 83: 3123-3132, 2000. This study investigated the tonotopic organization of pure-tone-evoked middle latency auditory evoked potentials (MAEPs) recorded at the auditory cortical surface in unanesthetized gerbils. Multielectrode array recording and multiple linear regression analysis of the MAEP demonstrated different degrees of tonotopic organization of early and late MAEP components. The early MAEP components P1 and N1 showed focal topography and clear dependence in location and size of cortical area covered on pure-tone frequency. The later components P2 and N2 showed a widespread topography which was largely unaffected in location and size of cortical area covered by pure-tone frequency. These results allow delimitation of the neural generators of the early and late MAEP components in terms of the spectral properties of functionally defined neural populations.
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INTRODUCTION |
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Auditory events (e.g., acoustic clicks,
pure-tones, or more complex and natural sounds) evoke characteristic
temporal patterns of electrical potential recordable from various
locations both within the brain and from its surface or from the scalp.
Usually a series of short poststimulus latency (<10 ms), small
amplitude (up to a few tens of µV) positive and negative deflections
of electrical potential called the brain stem auditory evoked potential (BAEP), is distinguished from a series of longer latency (>10 ms),
high-amplitude (tens to hundreds of µV) deflections, called the
middle latency auditory evoked potential (MAEP). Whereas the BAEP is
extensively studied and thought to reflect in its series of potential
deflections a sequence of neuronal activations in separate nuclei of
the auditory brain stem, the neurogenesis of the MAEP is only partly
understood, despite the clinical relevance of this signal
(Ichiki et al. 1998; Kraus and McGee
1992
) and its possible relevance for our understanding of
central auditory processing of sound (Bullock 1981
;
Kraus and McGee 1995
).
Investigation of the MAEP has been impeded mostly by the circumstance that these potentials are unlikely to reflect a serial activation of separate auditory nuclei but may confound a number of different neuronal processes in separate but partially overlapping neuronal populations. As most approaches aimed at unraveling the different contributions of presumed generator populations evoked MAEPs by auditory clicks, which exhibit a spectrally broad energy distribution, a most salient feature of auditory neurons, viz., their tuning to characteristic confined frequency intervals of the auditory spectrum, has remained largely unexploited.
Within the last decade, understanding the neurogenesis of the MAEP has
been advanced by spatial analysis of the MAEP (Barth and Di
1990, 1991
; Kraus et al. 1985
, 1988
;
Simpson and Knight 1993a
,b
; Steinschneider et al.
1992
). This understanding was made possible by the combination
of high-resolution recording using multielectrode arrays, depth
recording through cortical laminae with microelectrodes, and
multivariate analysis of the linear models of the MAEP and its
component peaks (Barth and Di 1990
, 1991
; Di and
Barth 1992
, 1993
). From these studies it was concluded that the
peaks of the click-evoked MAEP recorded from the surface of the rat
auditory cortex are generated by distinguishable but partially
overlapping neuronal populations which are asynchronously activated by
acoustic input. Specifically, the earlier MAEP components (called P1
and N1 to reflect their polarity and sequence of occurrence in the MAEP
complex) were thought to be primarily caused by extracellular currents
associated with thalamocortical activation of supragranular and,
respectively, supra- and infragranular pyramidal cells in primary
auditory cortex. The later components (P2 and N2) however, were
presumed to involve contributions from corticocortical activity (Barth and Di 1991
) but were shown to mainly reflect
input from a second, more diffuse, thalamocortical projection system,
probably originating in the medial part of the medial geniculate body
(Barth and Di 1993
).
As shortest latency thalamocortical input is mediated by a projection
from the ventral part of the medial geniculate body to the primary
auditory cortex, the above interpretation allows formulation of two
hypotheses amenable to experimental testing. The first hypothesis is
that direct electrical stimulation of the ventral part of the medial
geniculate body should evoke epicortical potentials similar in
field-specific localization, topography, and timing to the P1 and N1
components evoked by acoustic stimulation. This hypothesis was
experimentally verified by Di and Barth (1992) in the
rat. As the projection from the ventral medial geniculate to the
primary auditory cortex is tonotopically organized in the rat
(Brett et al. 1994
; Winer et al. 1999
),
as well as in other species (Winer 1992
), a second
hypothesis can be formulated on the topography of epicortical MAEPs: if
the early, but not the later, components of the epicortical MAEP
predominately reflect thalamocortical input from the ventral medial
geniculate, then given a suitable spectrally defined acoustic input,
the functional architecture of this projection into the primary
auditory cortex should be visible in the topography of early MAEP
components and should be less obvious or absent in later MAEP components.
The main objective of this study is to test this hypothesis by studying
the surface topography of separate components of the MAEP evoked by
pure-tones. Pure-tones, in contrast to acoustic clicks, activate the
thalamocortical input into the auditory cortex in a frequency-dependent
and systematic (i.e., tonotopic) manner. The frequency dependence of
the surface topography of the pure-tone-evoked MAEP should allow
evaluation of the above hypothesis. We have chosen the lissencephalic
rodent species Mongolian gerbil (Meriones unguiculatus) as
the experimental animal because its auditory cortex has been
extensively investigated (Ryan et al. 1982;
Scheich 1991
; Scheich et al. 1993b
, 1997
)
and the tonotopy of its primary field AI and of the anterior auditory
field AAF are thoroughly described (Hess and Scheich
1996
; Scheich et al. 1993a
; Sugimoto et
al. 1997
; Thomas et al. 1993
).
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METHODS |
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Multielectrode arrays
For high resolution multichannel recordings two types of
multielectrode arrays were configured from epoxy-insulated stainless steel microwires (100 µm diam) (Barrie et al. 1996). A
rectangular 3 × 6 electrode array (interelectrode distance: 600 µm) and a linear 16 electrode array (interelectrode distance: 300 µm) were designed after optimizing interelectrode distances by
spatial spectral analysis of recorded potentials (Freeman and
Baird 1987
) (Fig. 1A).
Just before implantation (see Surgical preparation) the surface of the arrays were filed to concave shape matching the
convexity of the cortical surface.
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Surgical preparation
Six adult (aged 6 mo) male Mongolian gerbils weighing 85-100 g
were chronically implanted with the multielectrode arrays (4 animals
with rectangular arrays and 2 animals with linear arrays) under deep
ketamine anesthesia (xylazine, 2 mg/100 g body wt ip; ketamine, 20 mg/100 g body wt ip). An array was positioned onto the dura exposed by
craniotomy over the region of primary auditory cortical field AI
(rectangular arrays) or covering both cortical core fields AI and AAF
(linear arrays; see Fig. 1A). The positioning of the arrays
was guided by visual inspection of the vascularization pattern
(Ohl and Scheich 1997a,b
; Sugimoto et al.
1997
) and established by stereotactic coordinates relative to
stereotactic landmarks (Ohl and Scheich 1996
;
Thomas et al. 1993
). Both types of arrays were
positioned with their length axes rostrally inclined into the ventral
direction ~10° from the horizontal plane (Fig. 1A) to
achieve orientation parallel to the tonotopic gradient in AI (Thomas et al. 1993
) and fixed with dental acrylic.
After the operation, animals were allowed to recover for 3 days before
recording sessions began.
Acoustic stimulation
Pure-tone bursts (duration: 250 ms, including 5 ms linearly
ramped rise/fall times) of frequencies varying from 0.25 to 8.0 kHz in
5 octave steps were free-field delivered over a calibrated loudspeaker
at a rate of 0.2 Hz. This frequency range was selected because of its
high spatial resolution in the tonotopic maps of fields AI and AAF in
the gerbil (Scheich et al. 1993a; Thomas et al.
1993
) to facilitate detection of the hypothesized tonotopic organization of MAEP components. Calibration was to equal a sound pressure level of 70 dB as measured by a condenser microphone at a
distance of 22 cm from the speaker.
Recording
Single presentation MAEPs were recorded (ISO 4/8 differential amplifiers, World Precision Instruments; amplification: 10K; band-pass filtering between 3dB cutoff frequencies of 0.1 and 100 Hz) from all electrodes of the array monopolarly against the reference electrode. Data from 2 s prestimulus and 2 s poststimulus were sampled at 1 kHz sampling frequency and stored to disk for offline analysis. All data were obtained from fully awake unanesthetized animals that were sitting in a small compartment (18 × 16 × 22 cm) during acoustic stimulation through the calibrated loudspeaker mounted 22 cm over the compartment floor.
Postmortem examination
After the experiments, animals were killed by pentobarbital sodium overdose (12 mg/100 g body wt). The recording array was surgically removed and the underlying tissue was examined for any signs of damage, necrosis or regrowth of connective tissue.
Data analysis
For each pure-tone stimulus of given frequency single
presentation MAEPs were averaged (n = 100). The average
MAEP was DC corrected for interelectrode variability by subtracting the
mean of the 2 s prestimulus average for each electrode channel.
Analysis of spatiotemporal patterns of the MAEP and their linear
modeling from spatial patterns obtained at the latencies of the four
identified peaks P1, N1, P2, and N2 was performed by multivariate
linear regression analysis (Dillon and Goldstein 1984)
as introduced for this purpose by Barth and Di (1990)
.
The multivariate linear regression yielded for each spatial pattern
associated with one of the four peaks a standard partial regression
coefficient (often referred to as "beta weights" or "regression
weights") as a function of time. These coefficients are a measure of
the contribution of the spatial pattern of epicortical potential at the
latency of a given peak to the total spatial contribution under the
assumption of a linear model.
On the basis of the high-resolution data obtained with the linear arrays in two animals, tonotopic gradients for MAEP components could be determined by log-linear regression of the pure-tone frequency shifts to spatial coordinates of the local component maxima: a model of pure-tone octave shifts as a linear function of spatial coordinate was fitted to the data by minimizing the residual sum of squares between data and model. The fit was quantified by calculating the coefficient of determination R2 and its goodness was evaluated statistically by comparing with a fit of a simpler model involving only a constant term. Analysis of variance (ANOVA), F ratios, and attainable significance levels are presented in Table 1. Note, that the determined P value corresponds to the significance level of t-testing the hypothesis of a tonotopic gradient unequal to zero. Only when this test yielded significant results was a tonotopic gradient determined.
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All procedures were conducted according to protocol approved by the University of California at Berkeley Animal Care and Use committee with veterinary supervision by the Office of Laboratory Animal Care.
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RESULTS |
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Figure 1A shows a lateral view of the brain of a
Mongolian gerbil with the positioning of both a rectangular 3 × 6 epidural electrode array (interelectrode distances: 600 µm) and a
linear 16 electrode array (interelectrode distances: 300 µm)
schematically indicated over the right temporal cortex. The rectangular
arrays covered an area of 3.0 × 1.2 mm2 of
cortical surface and were used to record two-dimensional potential distributions over the primary cortical field AI in four animals; the
linear arrays covered a length of 4.5 mm and were positioned to record
a one-dimensional spatial potential profile over a cortical region
spanning both the field AI and the anterior auditory cortical field AAF
in two other animals. Both fields show a clear topographic organization
with tonotopic gradients from low- to high-frequency running from
caudal to rostral in field AI and from rostral to caudal in field AAF
so that both fields share a common border of high-frequency
representation (Scheich et al. 1993a; Thomas et
al. 1993
). Figure 1B shows a typical recording of
the MAEP from the epidural surface over field AI. The basic wave forms of the MAEP evoked by pure-tones of frequencies from 0.5 to 8.0 kHz
corresponded to those of click-evoked responses recorded from other
species. They invariably consisted of two subsequent positive/negative deflections, termed P1/N1 and P2/N2, and often a third
positive/negative complex P3/N3 (see example in Fig. 1B).
The regularly occurring components P1, N1, P2, and N2 peaked at
characteristic latencies of 16.4 ± 3.1 (SD), 29.7 ± 2.9, 58.0 ± 5.1, and 115 ± 8.9 ms, respectively.
The description of the spatial distribution of potential amplitudes of
the four identified peaks was based on a multiple regression analysis
of the MAEP as introduced for the analysis of the spatiotemporal organization of click-evoked potentials by Barth and Di
(1990). MAEP components P3 and N3 were not included in this
analysis because they were not reliably recordable as their occurrence
seemed to be dependent on the behavioral state of the animal. Figure
2A shows typical isopotential
distributions of a 2 kHz pure-tone-evoked MAEP of one animal
(gerbil 1) at latencies corresponding to the four identified
MAEP peaks. Components P1 and N1 showed similarly focal potential
distributions with nearly identical location of the potential maxima in
the rostral half of the recording area corresponding to central AI and
similarly steep potential gradients. Components P2 and N2 had more
widespread potential distributions and shallower potential gradients in
comparison to P1 and N1. The potential maxima were located caudally
with respect to the P1 and N1 foci near the border between caudal AI
and rostral parts of the caudal auditory fields dorsoposterior field
(DP) and ventroposterior field (VP) (see Scheich et al.
1993a
; Thomas et al. 1993
).
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The same general pattern was found for the components of MAEPs evoked
by pure-tones of other frequencies from 0.25 to 8.0 kHz. Figure
2B shows standard partial regression coefficients of the
MAEP regressed onto the spatial patterns of potential distributions recorded at the four latencies corresponding to the MAEP peaks P1, N1,
P2, and N2 as a function of time. The four regression weights are a
measure of the contribution of a spatial pattern of potential
distribution at these four specified latencies to the overall MAEP. The
amplitudes were predictably maximal at the latencies of the respective
peaks. However, the regression weights of all peaks showed substantial
contribution to the overall MAEP at other latencies as well. This was
especially apparent for the N1 regression weights which contributed to
the overall MAEP at latencies corresponding to peak P1 as evident in a
clearly discernible downward peak at the P1 latency. The P2 component
showed a contribution to the overall MAEP at the N1 latency; similarly,
but to a lesser degree, did component N2. Figure 2C shows
spatiotemporal maps of potential reconstructed by multiplication of the
isopotential distribution with the regression weight time series. The
sum of these maps is a linear prediction of the spatiotemporal map of the overall MAEP and explained 98% of the variance across
measurements. In the other three animals implanted with rectangular
arrays multiple regression analysis yielded variance explanation of 94, 97, and 97%, respectively. The potentials showed a sharp fall-off in
amplitude at the caudal border (Fig. 2C, left) of
the array corresponding to locations near the caudal border of the
primary auditory cortex (see Scheich et al. 1993a;
Thomas et al. 1993
).
The other three animals implanted with rectangular electrode arrays showed very similar patterns of isopotential maps, regression weights, and reconstructed spatiotemporal maps. Figure 3 depicts the 50% isopotential contours of the 2-kHz pure-tone-evoked MAEP at the latencies of the four identified peaks for all four animals plotted superimposed on each other (Fig. 3A) and the corresponding partial regression coefficients (Fig. 3B). Despite considerable variance across individuals the following features were invariant. The isopotential distributions of the early components P1 and N1 were similar in location and shape to each other and much more focal than those of the later components P2 and N2. The locations of the earlier peaks were more consistent across animals than those of the later peaks. The isopotential distributions of P2 and N2 tended to overlap those of the earlier peaks whereas their foci were shifted toward the caudal boundary of primary field AI; this was especially manifest for peak N2. The variance in the regression weights across individuals was higher for the later peaks. For all four peaks, regression weights were maximal at their corresponding latencies but also indicated contribution of their spatial potential patterns to the overall MAEP at other latencies: component N1 contributed to the overall MAEP at latencies of P1 and component P2 contributed to the MAEP at N1 latencies. In those cases where the component N3 was measurable, a contribution of the N2 component to the MAEP at N3 latencies was found (Fig. 3B).
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Figure 4 shows the dependence of the location of the pure-tone-evoked MAEP on pure-tone frequency (color-coded) separately for the four components P1, N1, P2, and N3. The spatial location of the P1 and N1 components showed a clear tonotopic shift from caudal to rostral across field AI with increasing pure-tone frequency from 250 Hz to 8 kHz in 5 octave steps (Fig. 4, top two rows). The 50% isopotential contours of components P1 and N1 of the MAEP evoked by a tone of a given frequency were similar in size, shape and localization of covered surface area within an individual. The change in size of the 50% isopotential contour with varying frequency presented at identical absolute sound pressure levels in a given individual was similar in the other individuals. Sizes were maximal for the frequencies between 1 and 4 kHz. The later components P2 and N2 did not show a clear tonotopic organization. P2 and N2 component isopotentials in a given individual showed lesser similarity compared with P1 and N1, especially with respect to localization (see gerbils 2 and 3). The fact of more widespread potential distributions in later MAEP components compared with earlier components was evident for middle range and high pure-tone frequencies but less evident for the 0.25 kHz stimuli. Across individuals a greater variation of isopotential contours for the later components was also detectable in comparison to the early components, especially with respect to size and shape.
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To obtain a more quantitative determination of the tonotopic shift of MAEP component localization, two additional gerbils were implanted with linear electrode arrays of doubled spatial resolution (interelectrode distance: 300 µm) oriented along the tonotopic gradients in fields AI and AAF. Both fields have a clear topographic organization with tonotopic gradients running approximately in the rostrocaudal direction and isofrequency dorsoventrally oriented isofrequency contours running approximately parallel to their common border (see Fig. 1A) where high frequencies are represented in both fields. Figure 5 shows the spatial profiles of MAEP component amplitudes in one animal across a linear 16-electrode array spanning both cortical fields AI and AAF. In each panel, numbers at the nearly horizontal abscissae index the electrodes from caudal positions over AI to rostral positions over AAF; the other abscissae specify the frequency of the pure-tones (0.25-8.0 kHz in 5 octave steps) used to evoke the MAEPs. The vertical ordinates specify the component amplitudes. For better comparison all amplitudes were plotted upward as absolute values. Across MAEP components amplitudes were of comparable absolute value (0.27 ± 0.18 mV) with higher values (>0.4 mV) found for the P1 and N1 component evoked by higher range frequencies, 2.0, 4.0, and 8.0 kHz. Components P1 and N1 showed more peaked spatial profiles of potential amplitude than components P2, N2, P3, and N3 did. The amplitudes were minimal at the edges of the recording line and in the center around electrode index 9 corresponding to the border between AI and AAF. The local maxima of the spatial profiles over fields AI (electrode indices 1-9) and AAF (electrode indices 10-16) are emphasized in the figure by black tops of the corresponding columns. A tonotopic shift of the local maxima was observed for both components P1 and N1: with increasing pure-tone frequency local maxima moved from caudal to rostral positions in AI with shallower tonotopic gradient and from rostral to caudal positions in AAF, toward the common high-frequency boundary between both fields. The later components did not show a tonotopic organization: components P2 and N2 showed reduced activity at the AI/AAF border (between electrode indices 9 and 10) similarly to P1 and N1 but a markedly less peaked spatial profile with positions of local maxima not systematically changing with pure-tone frequency. The spatial profiles of components P3 and N3 were basically flat and remained unchanged with pure-tone frequency.
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The other animal implanted with the linear 16-electrode array showed
very similar results. We used the data from both animals to determine
the tonotopic gradients of the MAEP components P1 and N1 by log-linear
regression of the frequency shifts produced by varying pure-tone
frequency onto the spatial rostrocaudal coordinates of the local maxima
in the MAEP profiles. Figure 6 shows the
spatial coordinates of the local profile maxima of components P1
(top) and N1 (bottom) measured in the two animals
plotted against the octave shift from 0 octaves (corresponding to 250 Hz) to 5 octaves (8.0 kHz). The regression lines are also depicted for
both animals and both cortical fields AI and AAF. Table 1 gives the
numerical results of the regression. Only MAEP components P1 and N1
showed a clear tonotopic organization in fields AI and AAF (Fig. 6)
which can be fitted to the model of a linear relationship between
octave shift and spatial position (Table 1). The steeper tonotopic
gradients in field AAF compared with field AI are a result of the
smaller spatial extent of AAF (see Fig. 5 and Scheich et al.
1993a; Thomas et al. 1993
). MAEP components P2
and N2 show a focal organization over field AI and over field AAF, but
no systematic relationship of octave shift with spatial position (Table
1). MAEP components P3 and N2 showed smaller amplitude variation over
the recording array for a given pure-tone frequency than did P1, N1,
P2, and N2 (Fig. 5) and no systematic relationship of the local
amplitude maximum to the ocatave shift (Table 1).
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DISCUSSION |
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The purpose of this study was to test the hypothesis that
successive components of the MAEPs as recorded epidurally over the auditory cortex mainly result from activity in differing but partially overlapping neuronal populations in auditory cortex. Specifically our
objective was to exploit the different degree of tonotopic organization
in separate thalamocortical projection systems to delineate their
different contributions to the MAEP. Based on earlier work on
click-evoked MAEPs from the rat auditory cortex (Barth and Di
1990, 1991
; Di and Barth 1992
), we hypothesized that the early but not the later components of the MAEP should exhibit
tonotopic organization of their surface topography. Thus we evoked the
middle latency responses by pure-tones rather than clicks and studied
their surface topography with multiple regression analysis. The
discussion first addresses methodological issues relevant for the
interpretation of our present experimental approach and then places the
present results into the functional context from earlier work.
Methodological considerations
We evoked MAEPs in unanaesthetized animals by pure-tones from a
loudspeaker in the free field. A general problem with free-field stimulation is a reduced control of stimulus levels compared with closed-field stimulation (speakers inserted into the meatus). However,
such a preparation is incompatible with recording from fully awake
unsedated animals which was mandatory for this study because of known
differential drug effects on the tonotopic and nontonotopic
thalamocortical projection systems (Herz et al. 1967). A
further problem with acoustic stimulation of the freely moving animals
is the uncontrollable variance in binaural input which affects precise
timing of MAEP components (Di and Barth 1993
) thereby
possibly disguising shoulder structures in MAEP peaks (Simpson
and Knight 1993a
). However, given the random orientations of
the constantly moving animal relative to the loudspeaker during the
recording periods and the averaging over large number of repetitions (n = 100) these differences cannot have systematically
biased our results, although they excluded the possibility to further investigate possible subcomponents of P1 in the gerbil. In summary, the
free field stimulation imposed no constraints on our data analysis as
the latter was based not on single condition observations but on
comparisons between experiments (different pure-tone stimuli) the
intertrial variance each of which was similarly affected by the chosen
experimental situation.
This study focused on the anatomic gerbil auditory cortical field AI
and the rostrally adjacent anterior auditory field AAF. Both fields can
be considered "core cortex" and "primary" (Patterson 1977) on the basis of their shared cyto- and myeloarchitecture, characterized by increased cellular density within layer IV and characteristic high-density of myelinated fibers in granular and infragranular layers (Budinger and Scheich 2000a
), the
dominating input from the ventral part of the medial geniculate nucleus
(Budinger and Scheich 2000b
), their precise tonotopic
organization (Scheich et al. 1993a
; Thomas et al.
1993
), and their indistiguishable electrophysiological
characteristics of single units to pure-tone stimuli (Schulze et
al. 1997
; Thomas et al. 1993
) and linear
frequency-modulated tones (Schulze et al. 1997
). Our
method of localizing auditory cortical fields AI and AAF has proved to
be useful in previous studies (Ohl and Scheich 1997
;
Ohl et al. 1999
) and could be posthoc verified by these results.
Pure-tone-evoked versus click-evoked MAEPs
We found pure-tone-evoked MAEPs to share the basic wave form and
overall topography with click-evoked MAEPs characterized by steep
fall-off in amplitude beyond the region of auditory cortex. We have
focused on the first four major deflections recorded over the region of
the primary auditory cortex, termed P1, N1, P2, and N2, adopting the
nomenclature from Shaw (1988) to facilitate comparison
with these studies and with those of Barth and coworkers (Barth
and Di 1990
, 1991
; Di and Barth 1992
).
Simpson and Knight (1993a)
have described multiple
subcomponents of P1 in click-evoked MAEPs occurring at latencies
earlier and later than the main component. In this study it was not our
aim to resolve any subcomponents of the classical ones. Kraus
and coworkers had earlier described a similar MAEP recorded from the
auditory cortical surface of the guinea pig (Kraus and McGee
1995
; Kraus et al. 1985
, 1987
, 1988
). The
comparable latencies and corresponding polarities suggest that their
components A, B, and C correspond to P1, N1, and P2, respectively.
Later components like P3 and N3 were not regularly observed in this
study and seemed to be dependent on nonstimulus-related parameters like
the vigilance and state of attention of the experimental animals.
Whereas these later components tend to be reduced or absent in
anesthetized animals (Borbély and Hall 1970
;
Kiang et al. 1961
; Pradhan and Galambos
1963
; Schwender et al. 1996
; Simpson and
Knight 1993b
), their dependence on behavioral state has been
described already in the early studies of both awake animals with
chronic electrodes (e.g., Teas and Kiang 1964
) and humans (Picton and Hillyard 1974
).
Our results on the general spatial localization of the four major
components of the pure-tone evoked MAEP are in basic agreement with
comparable studies on click-evoked potentials in the rat auditory
cortex (Barth and Di 1990, 1991
; Brett et al.
1996
; Di and Barth 1992
; Sukov and Barth
1998
). All studies reported a more focal and spatially confined
localization of the components P1 and N1 compared with P2 and N2. Given
that AAF must be considered a primary field in the gerbil the present
data support the general notion of confinement of these peaks over
primary auditory cortex. Similar, but in their latencies
distinguishable MAEP components were measured over the surface of the
secondary auditory cortex in the rat (Barth and Di 1991
;
Di and Barth 1992
). A difference in the results using
click-evoked potentials in rat auditory cortex is the very similar size
of areas encircled by corresponding isopotential contours of the P1 and
N1 components. In the rat, N1 consistently covered an area
approximately twice as large as P1. As the current source/sink pattern
giving rise to the surface N1 component was hypothesized (Barth
and Di 1990
) to be mediated by ascending collateral fibers from
the supragranular cells (Jones 1984
, 1985
) this
difference could be a result of slightly different collateral circuitry
patterns being less divergent in the gerbil compared with the rat. The closer similarity of the N1 spatial activity pattern to the P1 pattern
in the gerbil compared with the rat is also evident in the very marked
peak of the N1 regression weight at the P1 latency in the gerbil (Figs.
2 and 3) not regularly reported in the rat (e.g., Barth and Di
1990
).
Tonotopic organization of pure-tone-evoked MAEPs
Few studies so far have addressed the question of MAEP tonotopy
(e.g., Kraus and McGee 1988; Scheel 1988
;
Woods et al. 1995
). In a recent study on MAEPs recorded
from the human scalp no tonotopic effects on MAEP topography were found
after probing with loudness-matched 250 Hz and 4 kHz pure-tones mixed
with continuous broadband masking noise (Woods et al.
1995
). From these results the authors were careful to not
conclude that there was a lack of tonotopic organization in the MAEP
generators but also considered the possibility of an unfavorable
orientation of neural generators impeding detection of tonotopic
organization (Bertrand et al. 1991
).
The input into the primary auditory cortex (fields AI and AAF in the
gerbil) is predominantly from the ventral division of the medial
geniculate body (Budinger and Scheich 2000b), similar to
conditions in other species (for review see Winer 1992
;
for a discussion of species differences in certain anatomic details see
Winer et al. 1999
). At least one other thalamocortical
projection system into primary auditory cortex originates from the
medial division of the medial geniculate body. Whereas the first
projection system is generally thought to be tonotopically organized,
the latter is assumed to be more unspecific with respect to frequency (Masterson and Glendenning 1978
) because the ventral
part of the medial geniculate nucleus itself is precisely tonotopically
organized (cat: Imig and Morel 1985
; rat: Winer
et al. 1999
) and the medial part is not (cat: Rouiller
et al. 1989
; rat: Winer et al. 1999
).
Our results have shown that the early components P1 and N1 of the
pure-tone-evoked MAEP have a clear tonotopic organization. In the two
cases of the animals implanted with the narrowly spaced linear
electrode configuration the spatial resolution was high enough to
determine the tonotopic gradients to 3.3 and 4.2 octaves/mm in AI and
AAF, respectively, for component P1 and to 3.0 and
5.5 octaves/mm in
AI and AAF, respectively, for component N1. These values agree with the
tonotopic gradients estimated from multiunit mapping (Thomas et
al. 1993
) and 2-deoxyglucose mapping (Scheich et al.
1993a
) of pure-tone representations in these two fields. These
results provide strong support for the hypothesis that these components
result from depolarization of primary cortical pyramidal cells by
thalamocortical input from the tonotopically organized medial
geniculate body as was concluded on the basis of a current source
density analysis of laminar recordings of click-evoked potentials
(Barth and Di 1990
) and analysis of cortical activity patterns after electrical stimulation of the ventral medial geniculate body (Di and Barth 1992
).
Corresponding isopotential contours of P1 and N1 obtained for the
different pure-tone frequencies differed not only in tonotopic location
but also in size. P1 and N1 isopotential contours obtained for
frequencies between 1.0 and 4.0 kHz consistently covered larger areas
than those evoked by lower and higher frequencies. Because the sound
delivery system was calibrated to equal absolute intensities for all
stimuli this result most likely reflects the representational geometry
of isointensity input intrinsic to field AI which is characterized by a
spatial "over-representation" of these frequencies reflecting the frequency dependence of pure-tone hearing
threshold (Ryan 1976) as was demonstrated with
electrophysiological mapping (Thomas et al. 1993
),
2-deoxyglucose mapping (Scheich et al. 1993a
), and
mapping of intrinsic optical signals (Hess et al. 1996
).
Because 2-deoxyglucose accumulation is predominately a measure of
dendritic input activity (Scheich 1990
), which in AI
results primarily from the ventral medial geniculate (Budinger and
Scheich, 2000b
), this is another independent argument in favor
of the above hypothesis of the neural generators of the MAEP components
P1 and N1.
Our approach, taking advantage of spectrally confined stimuli rather
than clicks, sheds some light onto the question whether the later MAEP
components are of a thalamocortical or rather corticocortical origin.
Based on their finding in the rat, that P2 can be elicited even in the
absence of the P1/N1 complex, Di and Barth (1993) have
already concluded that P2 cannot solely reflect corticocortical activity induced by the P1/N1 response but has to be caused by activity
of a second, albeit more diffuse, thalamocortical projection. Although
a corticocortical contribution cannot be ruled out its possible
relevance is further deemphasized by the finding that the P2/N2 shows
almost no signs of tonotopy. Given that intracortical connections in
gerbil auditory cortex are highly tonotopic (Budinger and Scheich,
2000a
), a higher level of tonotopic organization of the P2/N2
response would have been expected if the organization was to a large
degree the result of the P1/N1 complex.
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ACKNOWLEDGMENTS |
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We thank B. Burke, D. Labra Cardero (Berkeley), and K. Buckisch (Magdeburg) for skillful technical assistance during experiments and manuscript preparation.
Part of this research was supported by the Deutsche Forschungsgemeinschaft (We2104/2-1).
Present address of H. Scheich: Leibniz Institute for Neurobiology, D-39118 Magdeburg, Germany.
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FOOTNOTES |
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Present address and address for reprint requests: F. W. Ohl, Leibniz Institute for Neurobiology, Brenneckest. 6, D-39118 Magdeburg, Germany.
The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Received 18 August 1999; accepted in final form 4 January 2000.
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REFERENCES |
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