| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
The Journal of Neurophysiology Vol. 79 No. 5 May 1998, pp. 2629-2642
Copyright ©1998 by the American Physiological Society
Georgetown University Medical Center, Georgetown Institute for Cognitive and Computational Sciences, Washington, DC 20007
 |
ABSTRACT |
|---|
 Abstract
 Introduction
Methods
Results
Discussion
References
|
|---|
Tian, Biao and Josef P. Rauschecker. Processing of frequency-modulated sounds in the cat's posterior auditory field. J. Neurophysiol. 79: 2629-2642, 1998. Single-neuron activity was recorded from the posterior auditory field (PAF) in the cortex of gas-anesthetized cats. Tone bursts and broadband complex sounds were used for auditory stimulation. Responses to frequency-modulated (FM) sounds, in particular, were studied systematically. Linear FM sweeps were centered around the best frequency (BF) of a neuron and had an excursion large enough to cover its whole frequency tuning range. Rate and direction of change of the FM sweeps were varied. In the majority of PAF neurons (75%) the FM response seemed not to be linear, i.e., their best instantaneous frequency (BIF) varied by more than one octave at different FM rates (FMR). When the difference between BIF and BF at each FMR was used as a measure of linearity, it was within one-third octave only at five or fewer FMR in most PAF neurons (74%). The majority of PAF neurons (70%) preferred moderate FM rates (<200 Hz/ms). Fifty-four percent of all neurons in this area showed band-pass behavior with a clear preference in the middle range of FM rates in at least one direction. Overall, neurons with high-pass behavior in both directions made up only a minor portion (22%) of PAF neurons. When both directions of an FM sweep (low-to-high and high-to-low frequency) were tested, 50% of the neurons were clearly selective for one direction, i.e., the response to one FM direction was at least twice as large as that to the other direction. This selectivity was not necessarily present at the preferred FM rate. In general, FM direction selectivity was equally distributed over FM rates tested. The selectivity of PAF neurons for the rate and direction of FM sounds makes these neurons suitable for the detection and analysis of communication sounds, which often contain FM components with a moderate sweep rate in a particular direction.
Several auditory cortical areas have been identified on the basis of their tonotopic organization and their thalamocortical connections both in cats (Imig and Reale 1980 Animals and surgery
The experimental procedures were generally the same as in our previous study on the AAF (Tian and Rauschecker 1994 Acoustic stimulation
STIMULUS GENERATION.
Pure-tone (PT) stimuli were generated with a stimulus generator (Wavetek 148A). The tone bursts were gated by a control unit (HI-MED, HG 300G) to 50 ms duration with 5-ms rise/fall time. The amplitude was monitored on an oscilloscope.
STIMULUS CALIBRATION AND SOUND FIELD.
The stimulus delivery system was calibrated with the same B&K equipment (Fig. 1). Between 0.4 and 24 kHz, the output varied by ±6 dB. Above and below this range a rolloff existed, partially because the signal was outside the measuring range of the microphone. The fidelity of the system in producing rapid FM sweeps was also tested, and near free-field conditions were ensured. Details of calibration were reported in a previous paper (Tian and Rauschecker 1994 Electrophysiological recording
For extracellular recording of neuronal spike activity, a lacquer-coated tungsten electrode (F. Haer, impedance ~1 M) was advanced vertically into the brain by a hydraulic micropositioner with remote controlled stepping motor (model 650, David Kopf). The signals were band-pass filtered (0.3-20 kHz) and amplified in two stages (model 1800, A-M Systems preamplifier; AM 502, Tektronix). A "slicer" module was used to set the threshold for filtering out background noise. The output of the slicer was monitored with an audio monitor (AM 8, Grass Instruments), and a window discriminator was used to reliably separate spikes with different amplitudes and to convert the isolated spikes into transistor-transistor logic (TTL) signals. In addition, the signal at each step was monitored on an oscilloscope (5113 dual beam storage, Tektronix), so that we are quite confident that only isolated single-unit activity was recorded. The TTL signals were then registered on an IBM AT-386 PC with a data collection program (HIST, Spikes Systems), which produced peristimulus time histograms (PSTH) and raster displays with a binwidth of 1 ms for on- or off-line evaluation.
Data analysis
To quantify the response to stimulation with tone bursts and FM sweeps in the posterior areas, the same "peak firing rate" was determined from the PSTHs as described in a previous paper (Tian and Rauschecker 1994 Histology
At the end of an experiment, the animal was deeply anesthetized with pentobarbital sodium (Nembutal, 60 mg/kg iv) and perfused transcardially with 0.9% saline followed by 10% Formalin in 0.9% saline. The brain was removed from the skull, blocked stereotaxically, and stored in fixative at 4°C. The part of the brain containing the auditory cortex was cut in 50-µm-thick frontal sections on a freezing microtome (Jung) at A total of 275 auditory cortical units from seven cats were studied with extracellular single-unit recording. Of these, 147 were located with certainty in PAF. Among the 147 PAF cells, 132 were analyzed with FM sweeps. For comparison, data recorded in AAF and A1 in a previous study (Tian and Rauschecker 1994 Recording sites
Vertical or near-vertical electrode penetrations were made through the posterior ectosylvian gyrus (PEG). Figure 2 shows examples of recording tracks through one cat brain in frontal sections (9C978, left hemisphere). Penetrations were made at 1-mm distances along the anteroposterior axis (Fig. 2A). Sometimes, more than one penetration was made in the same frontal plane (Fig. 2B). Lateral distances between two parallel penetrations were 0.5-1 mm.
Responses to pure tones and tonotopic organization in the PAF
PAF units generally responded to tone bursts. The BF and the frequency tuning range could be determined for the majority (112/135 = 83%) of the neurons with BFs represented in every part of the spectrum. However, 23 of 135 units (17%) tested with tone bursts could not be driven at any amplitude level tested (up to 95 dB SPL). Therefore their BF and tuning range remained undefined. Among these units, only three did not show responses to FM stimuli. Inhibitory responses were not explored in any of the neurons.
Minimum latency
The minimum latency was estimated for each neuron in PAF. The distribution of minimum latency is shown in Fig. 4A. For comparison, data from AAF and A1 (unpublished observations) are also shown here (Fig. 4, B and C, respectively). The minimum latency of PAF neurons varied from 10 to 141 ms. From 10 to 50 ms, the distribution was almost even. The mean and SD for PAF neurons was 42 ± 29 ms. In contrast, neurons in AAF (19 ± 11 ms) and A1 (23 ± 12 ms) had much shorter latencies than those in PAF (Mann-Whitney U-test, P < 0.001). Only a few of AAF and A1 neurons exceeded 50 ms in latency.
Response to FM sounds
GENERAL PROPERTIES.
When stimulated with linear FM sweeps, 125 of 132 PAF neurons (95%) responded in at least one FM direction (Fig. 5). Only in seven units (5%) a response was not detectable at any tested FMR in either direction. The PSTHs in response to FM were transformed into rate-frequency curves of IF by substituting frequency for time, and the locations of local and global maxima in these curves were determined. Both procedures are described in detail in METHODS.
COMPARISON BETWEEN FM AND PURE-TONE RESPONSE.
In 102 of 125 PAF neurons, it was possible to determine the BF with tone bursts, and thus a direct comparison between BF and BIF could be performed. In the examples shown in Fig. 6, BIFs were close to BF at some FMRs (Fig. 6A, both in upward and downward direction; B, in upward direction; and C, in downward direction), but not at others. When the difference between BIF and BF at each FMR was used as a measure for response linearity, it was within 1/3 octave only in 1 of 102 neurons (1%) at all 12 different FMRs for both upward and downward sweeps (Fig. 7A). In most neurons (75/102 = 74%) it was the case only at five or fewer FMRs. Furthermore, it was not within 1/3 octave in 19 neurons (19%) at any of the FMRs.
TUNING TO FM RATE.
Neurons in the posterior areas showed great sensitivity to changes in the rate (or speed) of FM. Four different examples of FMR tuning curves are illustrated in Fig. 8. The unit in Fig. 8A responded with a higher firing rate to higher FMRs in the upward direction, whereas neurons such as the unit in Fig. 8C showed a more vigorous response at lower FMRs. For other units, the optimal FMR was in the middle of the test range (Fig. 8B); some units did not prefer any particular FMR, yet some other units had two optimal FMRs separated by FMRs that yielded low responses. Additional examples of FMR tuning curves are shown in Fig. 9, where the responses at different FMRs were normalized to the maximum response. As defined in METHODS, FMR tuning was categorized as HP (Fig. 9A), LP (Fig. 9C), BP (Fig. 9B), AP (Fig. 9D), or BR (Fig. 9E) behavior.
SELECTIVITY FOR FM DIRECTION.
Another distinct property of PAF neurons in response to FM stimuli is their selectivity to the direction of an FM sweep. The four examples in Fig. 8, besides demonstrating FM rate selectivity, also show FM direction selectivity.
Tonotopic organization and extent of PAF
When stimulated with tone bursts, the BF of neurons in the posterior ectosylvian region first decreased, then increased along a rostrocaudal axis. In the same penetration, BF decreased in the dorsal part of the PEG. In the posterior bank of PES, BF first increased, then decreased, when the electrode advanced into the ventral part of the cortex. These results confirm those of previous studies, namely, that PAF shares its low-frequency border with A1, and that there is a smooth transition between PAF and VPAF (Reale and Imig 1980 Responses to FM sweeps
In a previous report, we had studied responses of AAF neurons to FM stimuli (Tian and Rauschecker 1994 RATE SELECTIVITY.
When stimulated with linear FM sweeps, the vast majority of PAF neurons showed some selectivity for the rate (or speed) of the frequency change. Unlike AAF neurons that comprised a high proportion of HP neurons (Tian and Rauschecker 1994
FM DIRECTION SELECTIVITY.
PAF neurons also showed selectivity for FM direction, but the proportion of such neurons was actually somewhat smaller than in AAF (Fig. 13). In PAF, one-half of the neurons showed selectivity for one particular direction, whereas in AAF this proportion was about two-thirds. Like in AAF, we found that a majority of FM direction-selective neurons preferred upward sweeps. One reason could be the presence of low-frequency masking noise in the recording room. However, when neurons with higher BF ( FM RESPONSE AND PURE-TONE BF.
PAF neurons responded to FM stimuli with a single peak. Multiple maxima like in the FM tuning curves of AAF neurons were not found in PAF neurons. Unlike in AAF neurons, the BIF at different FMRs was not always the same: BIF varied by more than one octave in a large majority (75%) of the PAF neurons, and even by more than two octaves in 60%. This is also demonstrated by the distribution of the mean difference between BIF and BF and its SD (Fig. 7). The majority of PAF neurons had a mean difference and SD larger than one-third octave. By contrast, the variation of BIF was within one octave in a large majority of the AAF neurons, and even within one-third of an octave in about one-third of the neurons. Only in a minority of AAF neurons, the mean difference between BIF and BF and the SD were larger than one-third octave (Fig. 7). One possible explanation for the larger variation of BIF in PAF neurons is that they have a larger bandwidth. However, AAF neurons, especially those with multiple maxima, also have relatively large bandwidths, but they still have their BIF close to the BF. The bimodal distribution of mean BIF-BF in PAF neurons indicates that BIF cannot be related to FM direction, whereas BIF clearly depends on FM direction in AAF neurons (Fig. 7). This indicates that, in contrast to AAF and A1, a linear model (Heil et al. 1992a Parallel processing in the auditory cortex?
Laminar analysis of corticocortical connections in the cat has demonstrated that AAF and A1 are on the same processing level, whereas the posterior auditory areas are hierarchically "higher" than A1 (Rouiller et al. 1991
INTRODUCTION
Abstract
Introduction
Methods
Results
Discussion
References
; Imig et al. 1982; Knight 1977; Merzenich et al. 1975; Morel and Imig 1987; Reale and Imig 1980) and in monkeys (Merzenich and Brugge 1973; Morel et al. 1993; Rauschecker et al. 1995, 1997). However, little progress has been made to date in terms of characterizing any functional differences between these areas. Using tone bursts, other parameters, such as sharpness of frequency tuning, response latency, level sensitivity, minimum threshold, sensitivity to different rise/fall times, and binaural interactions, have been analyzed. However, most of these studies have concentrated on primary auditory cortex (A1) (e.g., Imig and Adrian 1977; Merzenich et al. 1975; Phillips and Irvine 1981; Phillips et al. 1994; Schreiner and Cynader 1984; Schreiner and Mendelson 1990; Sutter and Schreiner 1991, 1995). Only few attempts have been made to go beyond A1, such as the anterior auditory field (AAF) (Knight 1977; Phillips and Irvine 1982) or the posterior auditory field (PAF) (Phillips and Orman 1984; Phillips et al. 1995). AAF was found to be very similar to A1, although there was some indication that neurons in AAF may be more broadly tuned than those in A1, and neurons with multiple peaks were found there (Knight 1977; Tian and Rauschecker 1994). In ferrets, the excitatory bandwidth in AAF neurons is twice as large as in A1 (Kowalski et al. 1995). Most recently, a higher proportion of nonmonotonic cells was found in PAF than in A1 (Phillips et al. 1995). Nevertheless, none of these parameters have been sufficient to clearly differentiate the various areas functionally. So far, the only known physiological parameter reliably delineating different areas in cat auditory cortex from one another remains tonotopic organization.
, 1992). These studies have demonstrated that it is not sufficient to use tone bursts to explore nonprimary auditory cortex. Rather, it appears advantageous to use complex stimuli with behavioral relevance to the species under study. Unfortunately, most work in higher mammals that has employed complex stimuli, such as species-specific calls (Newman and Symmes 1974; Ploog 1981; Symmes 1981; Wang et al. 1995; Winter and Funkenstein 1973; Wollberg and Newman 1972), or potential prey vocalizations (Sovijärvi 1975), has again concentrated on primary auditory cortex (A1).
; Erulkar et al. 1968; Heil et al. 1992a,b; Mendelson and Cynader 1985; Mendelson et al. 1993; Mendelson and Grasse 1992; Phillips et al. 1985; Schreiner and Urbas 1986; Whitfield and Evans 1965), ferrets (Kowalski et al. 1995; Shamma et al. 1993), and squirrel monkeys (Bieser and Müller-Preuss 1996). Again, however, few attempts have been made to explore nonprimary auditory areas: AM sounds have been tested in AAF, PAF, and ventroposterior auditory field (VPAF) of the cat (Schreiner and Urbas 1986, 1988); FM sounds have only been used in AAF of cats (Tian and Rauschecker 1994) and ferrets (Kowalski et al. 1995). The latter is particularly surprising because FM sounds are highly relevant for two reasons: 1) they occur ubiquitously in many different kinds of communication sounds (Brown et al. 1978; Capranica 1972; Leppelsack 1983), including human speech (Liberman et al. 1967), and 2) they can be seen as analogous to moving light stimuli (Mendelson and Cynader 1985; Tian and Rauschecker 1994), which are very effective in driving neurons of extrastriate visual cortex (Hubel and Wiesel 1959).
). In addition, a prevalence of spatially tuned neurons has been reported for the anterior ectosylvian (AE) region, including AAF (Henning et al. 1995; Korte and Rauschecker 1993; Rauschecker and Korte 1993; Rauschecker et al. 1993). These findings, as well as other recent data (Middlebrooks et al. 1994), have led to the hypothesis that the AE region may be specialized for the analysis of sound location. By analogy with the visual system (Ungerleider and Mishkin 1982), one could argue further that separate streams may exist in the central auditory system for the processing of space and pattern information. Neurons involved in the processing of auditory "patterns" both in the spectral and temporal domain, especially those used in acoustic communication, might be expected to be selective for slower changes of frequency, because they occur in these sounds. A good candidate structure for such an analysis appeared to be area PAF and the surrounding areas in the posterior ectosylvian cortex. PAF has recently been found to contain a high proportion of amplitude-tuned neurons (Phillips et al. 1995), which may also be indicative of pattern-related processing. In the present study, we therefore extended the same approach that we used for AAF to the posterior auditory areas by testing neurons with FM sweeps of different rate and direction.
).
METHODS
Abstract
Introduction
Methods
Results
Discussion
References
). In brief, seven adult cats with no signs of middle ear infections were used. A total of 275 cells was collected from the posterior auditory areas.
1 s. Each stimulus was repeated 20 times for each neuron.
View larger version (12K):
[in a new window]
FIG. 1.
Calibration curve of the sound delivery system. The sound pressure level (SPL) of standard stimuli was at ~70-80 dB. Dashed line represents the sound pressure level of the background noise. Between 0.4 and 24 kHz, the output varied by about ±6 dB. Below and about this range, there was a roll-off.
).
). In brief, a 10-ms window was slid at 1-ms steps across the PSTH, the number of spikes in this 10-ms interval was counted at each step until the maximum was found, and the average firing rate in the peak interval was calculated after subtracting spontaneous activity. The so obtained rate-frequency curves were smoothed with a three-point smoothing routine. Sometimes several local maxima were detected in these rate-frequency curves. A secondary or tertiary peak was defined if the firing rate between two local maxima dropped by 50% compared with either maximum.
). The preferred FMR (PFMR) was defined as the FMR at which the response was maximal in a given FM direction. For statistical evaluation, the PFMR in the preferred direction was used if the neuron was FM direction-selective (see below); otherwise, the PFMR at which the response was maximal was used.
in which RU and RD are the responses to upward and downward FM sweeps at a particular FMR, respectively (Heil et al. 1992a
,b; Mendelson and Cynader 1985; Phillips et al. 1985; Shamma et al. 1993; Tian and Rauschecker 1994).
18°C. The sections were mounted on slides and stained with cresyl violet or thionin. Electrolytic microlesions were identified under a microscope (Wild) and the sections drawn with a camera lucida (Leitz). The lesion sites were compared with the stereotaxic measurements taken during the recording session to verify the location of the recording sites.
RESULTS
Abstract
Introduction
Methods
Results
Discussion
References
) were also reanalyzed with the same methods.
View larger version (35K):
[in a new window]
FIG. 2.
Location of posterior, ventroposterior, and dorsoposterior auditory fields (PAF, VPAF, and DPAF, respectively) and position of recording tracks (1-7) in left cerebral hemisphere. A: lateral view of a cat brain and location of auditory cortical areas (after Imig et al. 1982 ). The PAFs are darkly shaded, whereas all other auditory areas are lightly shaded. A1, primary auditory field; A2, "secondary" auditory field; AAF, anterior auditory field; VAF, ventral auditory field; aes, anterior ectosylvian sulcus; pes, posterior ectosylvian sulcus; sss, suprasylvian sulcus. B: reconstruction of electrode tracks through the posterior ectosylvian gyrus, shown in a series of anterior to posterior frontal sections separated by ~1 mm (1-7). Numbers next to each recording site indicate the best frequency (BF) in kHz found with pure-tone stimuli.
). Anteriorly, PAF shares a common low-frequency border with A1. Because a reversal of the frequency representations occurs along this border, neurons with a higher BF than those in the next posterior penetration were counted as A1 neurons. Ventral to PAF, the VPAF shares common isofrequency lines in the middle and high-frequency range (>6 kHz) with PAF, whereas the lowest BFs in VPAF are situated near the ventral end of PES (Reale and Imig 1980). Dorsal and posterior to A1, an area was found with BFs that were not consistent with the tonotopic organization of A1. This field had been termed previously as dorsoposterior auditory field (DPAF) (Reale and Imig 1980).
).
View larger version (18K):
[in a new window]
FIG. 3.
Frequency tuning in PAF neurons after pure-tone stimulation. Three examples of neurons are shown, whose unit numbers are given on top. A-C: threshold tuning curves: the sensitivity of the neuron for different frequencies is measured by determining the threshold amplitude at which a neuronal response can be elicited by a tone burst. D-F: "rate-frequency" or "iso-intensity" curves corresponding to A-C, respectively: the peak firing rate of the neuron at each frequency was measured from peristimulus time histograms (PSTHs). Dashed line depicts baseline activity of each neuron. Sound pressure level was 55 dB ( 
) or 75 dB (
). Good correspondence was found for all 3 neurons between BFs and tuning widths determined with either procedure.
View larger version (21K):
[in a new window]
FIG. 4.
Distribution of minimum latency in PAF (A), AAF (B), and A1 (C). Binwidth was 5 ms. Means and SD for PAF, AAF, and A1 neurons are given with each distribution.
View larger version (23K):
[in a new window]
FIG. 5.
Comparison of rate-frequency curves in one neuron for pure-tone stimulation (A) and in response to frequency-modulated (FM) sweeps (B and C) of different rate and direction. Curves in B and C are derived from PSTH responses by the conversion process described in METHODS: net firing rate is plotted as a function of instantaneous frequency (IF). The number above each peak indicates the frequency at the peak center. In all cases, stimulus amplitude was 75 dB SPL. A: tone-burst response. B: responses to upward FM sweep at 6 different FM rates (FMRs; decreasing from top left to bottom right panel: 600, 300, 150, 75, 37.5, and 18.75 Hz/ms, indicated in italics in the top left corner of each plot). C: responses to downward FM sweeps at different FMRs in the same sequence as for upward sweep. Peaks in the FM response are at an IF that varied at different FMRs.
View larger version (23K):
[in a new window]
FIG. 6.
Examples of best instantaneous frequency (BIF) plotted against FMR. , upward sweeps; , downward sweeps. Dashed line indicates the BF for each neuron.
View larger version (43K):
[in a new window]
FIG. 7.
Distribution of deviations of BIF from BF in PAF neurons ( 
). For comparison, data from AAF are also shown here (
). A: percentage of neurons whose BIF deviates from BF at different FMR in < 1/3 octave. B: percentage of neurons whose BIF differs from BF at different FMR in >1 octave. C and D: distribution of averaged difference between BIF and BF and its SD for upward sweeps. E and F: distribution for downward sweeps. Vertical dashed lines indicate the border at 1/3 octave.
2 test,df = 11, P < 0.0001).
View larger version (21K):
[in a new window]
FIG. 8.
Neuronal activity as a function of FMR and FM direction selectivity in PAF neurons. Firing rate (top panels) and direction selectivity (DS) index (bottom panels) at different FMRs are plotted for 4 neurons (A and E to D and H). In the top panel, open circles symbolize the responses to upward FM sweeps, filled circles to downward sweeps. In the bottom panel, dashed lines at a DS index of ±0.33 indicate the criterion for DS applied to an FM sweep (cf. Mendelson and Cynader 1985 ). Values beyond these limits indicate that the response to one FM direction is <50% of that in the other direction. Thus the neuron is direction selective at this particular FMR. Positive and negative values refer to upward and downward preference, respectively. A and E: neuron with high preferred FMR [PFMR; high-pass (HP) neuron] but no DS. B and F: neuron with a preference for moderate FMR [band-pass (BP) neuron) and direction preference for upward sweep at lower FMRs. C and G: neuron with low PFMRs [low-pass (LP) neuron] and direction preference for downward FM sweep at moderate FMRs. D and H: neuron with a preference for lower FMRs (LP neuron) and direction preference for upward FM sweep at lower FMRs.
View larger version (28K):
[in a new window]
FIG. 9.
Examples of FMR tuning curves in 5 different categories. A: HP neurons. B: BP neurons. C: LP neurons. D: all-pass (AP) neurons. E: band-rejection (BR) neurons. Each diagram depicts several examples for each of the 4 categories. Responses are normalized to the maximum response (100%) for each neuron. Dashed line marks 75% of the maximal response, which was used as the criterion to categorize the neurons. Note that the FMR tuning curves cover the whole range of FMRs tested.
View larger version (39K):
[in a new window]
FIG. 10.
Distribution of cells in PAF in FMR tuning categories. Cells in AAF are displayed for comparison. All the possible combinations of responses in 2 FM directions are shown here. Up, upward sweep; Down, downward sweeps; HP, high-pass behavior; BP, band-pass behavior; LP, low-pass behavior; AP, all-pass behavior; BR, band-rejection behavior. N refers to number of animals, n to number of neurons.
2 kHz), 10 units (8.0%) preferred higher FMRs (100 Hz/ms). The BR neurons were not included in the evaluation, because they had more than one PFMR.
View larger version (33K):
[in a new window]
FIG. 11.
Distribution of PFMRs for all cells (open bars) and BP cells only (stippled bars) in PAF. Top panel: data for upward sweeps. Bottom panel: downward sweeps. Preference for FMR was distributed over the whole range tested. For BP cells, the PFMRs were in the midrange. Binwidth of the graphs is 1/2 octave, i.e., 20.5k (k = 1, 2, . . . , 18) in Hz/ms.
View larger version (24K):
[in a new window]
FIG. 12.
Preferred FMRs as a function of BF for each PAF unit in one FM direction. Preferred FMR and BF of the neurons showed a weak positive correlation (top graph: total, r = 0.27, n = 115; bottom graph: BP only r = 0.20, n = 69). Inset histogram at the bottom of each graph displays the distribution of BFs in the sample. Binwidth of the graphs is 1/2 octave, i.e., 20.5k (k = 4, 3, . . . , 10) in kHz.
). This corresponds to an absolute value of the DS index of 0.33. Of 125 units, 71 units fulfilled the criterion and were classified as direction selective (Fig. 13). Among them, in eight units (6.4% of all 125 cells) direction preference depended on FMR, i.e., these cells preferred one direction at one FMR but the opposite direction at another. Of the remaining 63 neurons, 42 (33% of all 125 cells in the sample) preferred upward and 21 (17%) downward sweeps. Thus a majority of the cells with a clearly defined direction preference (42/63 = 67%) preferred upward motion. The remaining 54 units (43%) did not meet the criterion and responded about equally to upward and downward direction at all FMRs. No significant differences were found between animals.
View larger version (18K):
[in a new window]
FIG. 13.
Distribution of PAF neurons with different types of FM direction selectivity (top panel). Units from all animals are combined; error bar indicates SD in each category. For comparison, AAF data are replotted from Tian and Rauschecker (1994) (bottom panel). Up, Down: neurons that responded better to an upward or downward FM sweep, respectively, at all FMRs. Up/down: neurons that responded better to one FM direction at some FMRs, but better to the other direction at other FMRs. None: no difference between both FM directions at any FMR.
View larger version (54K):
[in a new window]
FIG. 14.
Distribution of FMRs at which PAF neurons were selective for the direction of an FM sweep. The binwidth of the graph is 1 octave, i.e., 2k (k = 2, 3, . . . , 9). Only neurons with single-peaked responses were included in this analysis. In PAF, FM-direction selectivity is almost equally distributed over the whole range of FMRs tested.
DISCUSSION
Abstract
Introduction
Methods
Results
Discussion
References
). Because besides pure tone responses little had been known about the physiological properties of neurons in the posterior areas, we used those same responses to delimit the areas from each other. At the anterior end of PAF, the BF reversal was taken as the border of PAF with A1. On the ventral side of PAF, the reversal point of BF was taken as the border between PAF and VPAF. Dorsal to PAF, there appeared to be another BF reversal in the rostrocaudal axis. Thus this dorsal area was identified as DPAF (Reale and Imig 1980). In a study of the posterior areas with AM stimuli, Schreiner and Urbas (1988) also used BF gradients in conjunction with sulcal pattern landmarks to identify different areas.
). In the present study, we have applied the same approach to neurons in PAF. We will try to compare the response in PAF with those in AAF.
), neurons with HP-HP tuning only made up 22% of the PAF neurons that responded to FM stimuli. By contrast, the proportions of BP-BP (22%) and LP-LP neurons (10%) were higher in PAF than in AAF. This is also reflected in the PFMR. In general, the PFMR of PAF neurons was significantly lower than that of AAF neurons (Mann-Whitney U-test, P < 0.02). This indicates that PAF neurons have a preference for slower temporal changes.
; Härtel 1975). The FM rate ranges from below 1 Hz/ms in a standard "meow" up to around 100 Hz/ms in communication calls of young kittens or mothers (Table 1). As for potential prey, FM components with a large range of FM rates are also found in mouse squeaks (20-100 Hz/ms) and bird songs (see Table 2 in Tian and Rauschecker 1994).
View this table:
TABLE 1.
Range of FMRs in cat communication calls
3 kHz) were examined, which were unlikely affected by the low-frequency background noise, the same biased ratio toward upward sweeps persisted. It would be interesting to see whether there is a genuine difference between PAF and A1, since two-thirds of A1 neurons prefer downward sweeps (Heil et al. 1992a; Mendelson and Cynader 1985). In contrast to neurons in AAF, which show FM direction selectivity only for low FMRs and lose it at high FMRs (Tian and Rauschecker 1994), the selectivity of PAF neurons for FM direction was almost equally distributed over the whole FMR range tested (Fig. 14). This indicates that FM direction information is preserved in PAF regardless of FMR, whereas AAF neurons display a general preference for fast transient sounds.
,b; Kowalski et al. 1995, 1996a,b; Shamma and Versnel 1995; Shamma et al. 1995; Suga 1968; Tian and Rauschecker 1994) can no longer predict the response in PAF neurons to FM (or other complex sounds). Instead, nonlinear effects, such as facilitation or suppression from temporal interactions between combinations of frequencies, may be responsible for this effect (Suga 1988, 1992). This kind of processing requires convergent inputs from lower stages. Thus PAF can be considered as a higher-order stage in FM processing, which is consistent with neuroanatomic findings on the connectional hierarchy within auditory cortex (Rouiller et al. 1991) and the longer minimum latency in our data.
), the variation of BIFs at different FMRs could be attributed to the inaccurate estimation of minimum latency. If the neuron is linear, it will start responding once the IF of an FM sweep enters the excitatory response area of the neuron; the response will reach its peak when the IF is close to the BF of the neuron. Both is indeed the case for A1 (Heil et al. 1992a; Phillips et al. 1985) and AAF neurons (Tian and Rauschecker 1994). In this case, the time at which the peak response occurs depends on the inherent latency and the FMR. If, however, the inherent latency is assessed incorrectly, then the calculated BIFs at different FMRs would deviate from the correct values. Because we kept the frequency range constant and changed the FM duration to vary the FMR, it would mean that if the inherent latency was assessed too short, the BIF would decrease with increasing FM duration for upward FM sweeps, but increase for downward FM sweeps, converging at a value close to BF. Conversely, if the inherent latency was assessed too long, then the BIF would increase for upward sweeps, but decrease for downward sweeps, when the FM duration increased. However, this kind of behavior was only observed in four neurons, but also with some reservations. For example, the neuron in Fig. 6C showed this behavior, with an exception at an FMR of 100 Hz/ms for downward sweep. At this point, the BIF was 0.2 kHz. Because the frequency range of the FM sweeps was 0.1-10.1 kHz, this means that the peak response occurred almost at the end of the downward FM sweep. On the other hand, the BIFs at higher FMRs for upward sweeps were also very low, i.e., the peak responses occurred at the very beginning of the upward sweeps. Therefore the latency had to be compromised to cover both the peaks for upward and downward sweeps. In other neurons, the BIFs were rather scattered over a large range (Fig. 6D).
). Multiple maxima were also found in A1 neurons (Heil et al. 1992a). This suggests that some of the A1 and AAF neurons might act as logical "or"-gates, because input in each of the several channels alone can elicit a response from these neurons. By contrast, neurons in PAF act as "and"-gates, because input in more than one channel is needed to excite the neuron (Suga 1988, 1992). In other words, PAF neurons have higher thresholds, or more input is needed to elicit a response from them.
). The tonotopic organization of PAF, as revealed with pure-tone stimuli (Imig and Reale 1980; Reale and Imig 1980), suggests that the area is still at a fairly low level in the hierarchy. On the other hand, use of AM sounds has shown that the posterior areas have a lower temporal resolution than AAF (Schreiner and Urbas 1988), which could be due to temporal integration. Our present observations are consistent with the view of PAF being at a more advanced stage of processing. When tested with FM sweeps, PAF neurons clearly display more complex response properties and a greater degree of nonlinear behavior than neurons in AAF or A1. The fact that FM direction selectivity in PAF neurons is equally distributed over the whole FMR range tested can be seen in the same light, namely, that PAF neurons are at a higher processing stage because they can process FM direction over the whole range.
), in much the same way as areas A1 and R are wired in parallel in the rhesus monkey (Rauschecker et al. 1997). Paradoxically, monkey area R shares its low-frequency border with A1, whereas AAF borders A1 at its high-frequency end. Nevertheless, we have speculated in either case that the parallel scheme could give rise to dual pathways specialized for the processing of auditory space and pattern information. In the cat, AAF with its preference for easily localizable transient sounds and with its spatially tuned neurons may be the beginning of the spatial stream (Henning et al. 1995; Rauschecker et al. 1993). In the monkey, the "lateral belt" areas seem to be the next processing stage in the auditory pattern stream, because neurons there integrate spectral information and respond to monkey vocalizations (Rauschecker et al. 1995). Although the present results from cats as well as those of another recent study (Phillips et al. 1995) are consistent with a role for PAF in auditory pattern processing, it remains to be seen whether the posterior ectosylvian areas in general are analogous to the lateral belt in monkeys. This question could be tested further by using sounds of even higher complexity.
| |
ACKNOWLEDGEMENTS |
|---|
We thank R. Gelhard for technical assistance. P. Henning, M. Korte, and J. Olsen participated in some of the recording experiments.
This study was supported by Grant R01-DC-03489 from National Institute of Deafness and Other Communication Disorders to J. P. Rauschecker and DOD Grant DAMD17-93-V-3018 from Department of Defense to Georgetown University.
| |
FOOTNOTES |
|---|
Address for reprint requests: B. Tian, Georgetown University Medical Center, Georgetown Institute for Cognitive and Computational Sciences, The Research Building WP24B, 3970 Reservoir Rd., NW, Washington, DC 20007.
Received 4 March 1997; accepted in final form 2 February 1998.
| |
REFERENCES |
|---|
|
Abstract
Introduction
Methods
Results
Discussion
References
|
|---|
This article has been cited by other articles:
|
|
 |
|
  T. A. Brown and R. V. Harrison Responses of Neurons in Chinchilla Auditory Cortex to Frequency-Modulated Tones J Neurophysiol, April 1, 2009; 101(4): 2017 - 2029. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. D. Washington and J. S. Kanwal DSCF Neurons Within the Primary Auditory Cortex of the Mustached Bat Process Frequency Modulations Present Within Social Calls J Neurophysiol, December 1, 2008; 100(6): 3285 - 3304. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
L. Qin, J. Wang, and Y. Sato Heterogeneous Neuronal Responses to Frequency-Modulated Tones in the Primary Auditory Cortex of Awake Cats J Neurophysiol, September 1, 2008; 100(3): 1622 - 1634. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. Malhotra, G. C. Stecker, J. C. Middlebrooks, and S. G. Lomber Sound Localization Deficits During Reversible Deactivation of Primary Auditory Cortex and/or the Dorsal Zone J Neurophysiol, April 1, 2008; 99(4): 1628 - 1642. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 P. K. Pandya, D. L. Rathbun, R. Moucha, N. D. Engineer, and M. P. Kilgard Spectral and Temporal Processing in Rat Posterior Auditory Cortex Cereb Cortex, February 1, 2008; 18(2): 301 - 314. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. F. Altmann, O. Doehrmann, and J. Kaiser Selectivity for Animal Vocalizations in the Human Auditory Cortex Cereb Cortex, November 1, 2007; 17(11): 2601 - 2608. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. A. Atencio, D. T. Blake, F. Strata, S. W. Cheung, M. M. Merzenich, and C. E. Schreiner Frequency-Modulation Encoding in the Primary Auditory Cortex of the Awake Owl Monkey J Neurophysiol, October 1, 2007; 98(4): 2182 - 2195. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. G. Lomber, S. Malhotra, and J. M. Sprague Restoration of Acoustic Orienting Into a Cortically Deaf Hemifield by Reversible Deactivation of the Contralesional Superior Colliculus: The Acoustic "Sprague Effect" J Neurophysiol, February 1, 2007; 97(2): 979 - 993. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. Malhotra and S. G. Lomber Sound Localization During Homotopic and Heterotopic Bilateral Cooling Deactivation of Primary and Nonprimary Auditory Cortical Areas in the Cat J Neurophysiol, January 1, 2007; 97(1): 26 - 43. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
B. Gourevitch and J. J. Eggermont Spatial Representation of Neural Responses to Natural and Altered Conspecific Vocalizations in Cat Auditory Cortex J Neurophysiol, January 1, 2007; 97(1): 144 - 158. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
K. N. O'Connor, C. I. Petkov, and M. L. Sutter Adaptive Stimulus Optimization for Auditory Cortical Neurons J Neurophysiol, December 1, 2005; 94(6): 4051 - 4067. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. K. Bizley, F. R. Nodal, I. Nelken, and A. J. King Functional Organization of Ferret Auditory Cortex Cereb Cortex, October 1, 2005; 15(10): 1637 - 1653. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. Brechmann and H. Scheich Hemispheric shifts of sound representation in auditory cortex with conceptual listening Cereb Cortex, May 1, 2005; 15(5): 578 - 587. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
B. Tian and J. P. Rauschecker Processing of Frequency-Modulated Sounds in the Lateral Auditory Belt Cortex of the Rhesus Monkey J Neurophysiol, November 1, 2004; 92(5): 2993 - 3013. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. P. Rauschecker and B. Tian Processing of Band-Passed Noise in the Lateral Auditory Belt Cortex of the Rhesus Monkey J Neurophysiol, June 1, 2004; 91(6): 2578 - 2589. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. Fishbach, Y. Yeshurun, and I. Nelken Neural Model for Physiological Responses to Frequency and Amplitude Transitions Uncovers Topographical Order in the Auditory Cortex J Neurophysiol, December 1, 2003; 90(6): 3663 - 3678. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. F. Linden, R. C. Liu, M. Sahani, C. E. Schreiner, and M. M. Merzenich Spectrotemporal Structure of Receptive Fields in Areas AI and AAF of Mouse Auditory Cortex J Neurophysiol, October 1, 2003; 90(4): 2660 - 2675. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
D. A Hall, I. S Johnsrude, M. P Haggard, A. R Palmer, M. A Akeroyd, and A. Q. Summerfield Spectral and Temporal Processing in Human Auditory Cortex Cereb Cortex, February 1, 2002; 12(2): 140 - 149. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. Brechmann, F. Baumgart, and H. Scheich Sound-Level-Dependent Representation of Frequency Modulations in Human Auditory Cortex: A Low-Noise fMRI Study J Neurophysiol, January 1, 2002; 87(1): 423 - 433. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
W. C. Loftus and M. L. Sutter Spectrotemporal Organization of Excitatory and Inhibitory Receptive Fields of Cat Posterior Auditory Field Neurons J Neurophysiol, July 1, 2001; 86(1): 475 - 491. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 B. Tian, D. Reser, A. Durham, A. Kustov, and J. P. Rauschecker Functional Specialization in Rhesus Monkey Auditory Cortex Science, April 13, 2001; 292(5515): 290 - 293. [Abstract] [Full Text]
|
|
|
|
|
|
J.R. Binder, J.A. Frost, T.A. Hammeke, P.S.F. Bellgowan, J.A. Springer, J.N. Kaufman, and E.T. Possing Human Temporal Lobe Activation by Speech and Nonspeech Sounds Cereb Cortex, May 1, 2000; 10(5): 512 - 528. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| Visit Other APS Journals Online |
