Sequence Sensitivity of Neurons in Cat Primary Auditory Cortex

Michael Brosch1 and Christoph E. Schreiner

Coleman Laboratory, W.M. Keck Center for Integrative Neuroscience, University of California at San Francisco, San Francisco, CA 94143-0732, USA, 1 Current address: Leibniz-Institut für Neurobiologie, Box 1860, 39008 Magdeburg, Germany


    Abstract
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Notes
 References
 
Properties of sequence-sensitive neurons in primary auditory cortex of cats were explored in detail. Stimuli were sequences of two tones, in which the frequency and intensity of the first tone and the temporal separation between the first and second, or probe, tone were parametrically varied. After presentation of the first tone, the responses of 32 single units and 48 multiunits to the probe tone were found to be enhanced up to 140–5270% (median 340%) above the response obtained in the single-tone condition. Probe tone enhancement was induced from a considerable number of sequence conditions and depended on the frequency and intensity of the first tone and on the temporal separation between the onsets of the first and the probe tone. On average, the maximally enhanced response occurred when the first tone was 1 octave below or above the probe tone and its intensity was 14 dB louder than the probe tone. The most effective temporal separation of the tones for an enhancement effect was ~100 ms. The range of enhancing tones was largely outside the excitatory tuning curve of a neuron. Results extend previous findings of properties of sequence-sensitive neurons in the auditory cortex of echolocating bats and non-echolocating mammals, and suggest that sequence-sensitive neurons are quite common and involved in the cortical representation of spectrotemporal patterns of acoustic signals.


    Introduction
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Notes
 References
 
It has been hypothesized that sequence-sensitive neurons are involved in the processing of spectro-temporal sound patterns (Suga et al., 1978Go; Newman and Symmes, 1979Go). There is a large body of evidence for this hypothesis from studies of sonar sounds in echolocating bats. In the FM–FM area and other cortical fields of the bat auditory cortex, many neurons respond more strongly to specific combinations of pulse–echo pairs than to the individual components of the pulse–echo pair. The tuning range of these combination-sensitive neurons overlaps the features that a bat encounters while emitting echolocation sounds and listening to the echoes from the targets.

For non-echolocating mammals there have been only a few reports showing examples of cortical neurons responding more strongly to sequences of tones than to the individual tones of the sequence (McKenna et al., 1989Go; Riquimaroux, 1994Go; Brosch and Schreiner, 1997Go). Rather, most studies in non-echolocating mammals have found that the temporal stimulus context has an inhibitory or suppressive influence on the responses to individual segments of acoustic signals. This suggests that the cortical representation of spectrotemporal sound patterns is largely determined by inhibitory neuronal mechanisms (Creutzfeldt et al., 1980Go; Steinschneider et al., 1982Go, 1998Go; Schreiner and Urbas, 1986Go, 1988Go; Eggermont, 1991Go, 1994Go, 1999Go; Calford and Semple, 1995Go; Brosch and Schreiner, 1997Go; Brosch et al., 1998Go). Recently, however, a systematic study, performed in monkey auditory cortex, has revealed neurons exhibiting enhanced responses to tone sequences that closely match some common features of complex sounds, like speech, animal vocalizations and music (Brosch et al., 1999Go). Specifically, enhanced responses to appropriate sequences of two pure tones were observed in 67% of the multiunits and 43% of the single units, recorded in the primary auditory cortex (AI) and in caudomedial belt areas. The enhancement effect of the first tone in the sequence started after the initial onset response to the following tone and lasted for a period of ~50 ms. Enhanced responses occurred for stimulus onset asynchronies (SOAs) between the two tones ranging from 100 to several hundreds of milliseconds. They were strongest at the shortest tested SOA and decreased with increasing SOA. In the spectral dimension, response enhancement occurred for a wide range of frequency intervals between the two tones, and it was maximal when the first tone was ~1 octave below or above the second tone.

Several issues regarding the temporal and spectral parameters of the sequence sensitivity of cortical neurons remained unresolved in the study of Brosch and colleagues, due to a limited number of tone sequences that were used (Brosch et al., 1999Go). First, enhanced responses were maximal in most neurons at the shortest used SOA of 100 ms. Thus, it is not clear if response enhancement occurs with SOAs < 100 ms and if response enhancement only depends on the SOA or requires a silent interval between the sequentially presented tones. Second, only a small number of frequency pairs with wide spectral spacing was used. This concerns the extent of the spectral range and the existence of preferred frequency intervals for enhancement. Third, in that study the tones of the sequences all had the same intensity. Therefore, no information is available regarding the intensity dependence of sequence sensitivity.

The current study explored the stimulus dependencies of response enhancement and other features of sequence-sensitive cells in auditory cortex for a considerably larger range of sequence parameters than in the study by Brosch and colleagues (Brosch et al., 1999Go). Accordingly, the dependence of response enhancement on the frequency and intensity of the first tone could be assessed more precisely. The use of short-duration tones allowed us to test the effects of SOAs < 100 ms and to test whether response enhancement depends on the SOA or on the duration of the silent interval between the tones of a sequence. Furthermore we compared the stimulus range inducing enhanced responses with the stimulus range inducing attenuated responses and with the single-tone spectral receptive field. Attenuating influences of the first tone on the response to the second tone have previously been published for the same neurons analyzed in the present report (Brosch and Schreiner, 1997Go). The experiments were conducted in AI of cats, which enabled us to compare properties of sequence-sensitive cells in different species.


    Materials and Methods
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Notes
 References
 
Animal Preparation

Data for the present report were from 12 adult cats. The methods for surgical preparation, recording and acoustic stimulation were identical to those described previously (Brosch and Schreiner, 1997Go), and were carried out in accordance with the guidelines for animal experimentation of the NIH (NIH publication no. 86-23, revised 1987) and with an approved protocol of the IACUC at UCSF. In 10 experiments, cats were anesthetized with a continuous infusion of sodium pentobarbital (1–2 mg/kg/h) in lactated Ringer solution (1–2 ml/kg/h). In two experiments the barbiturate was replaced by a mixture of ketamine–HCl (1–4 mg/kg/h) and Diazepam (0.5–2 mg/kg/h) following completion of the surgery.

Neural Recording

Action potentials from single neurons or from small groups of neurons were recorded extracellularly with tungsten microelectrodes (1–2 M{Omega} at 1 kHz) and triggering devices (Bak Dis-1; Alpha-Omega Engineering, MSD) from different locations in AI and stored in a computer (DEC 11/73 or IBM-compatible PC) with a temporal precision of 30 µs. The recording window started at the onset of each trial and lasted for a period of 50–500 ms.

Acoustic Signals

Experiments were carried out in a double-walled sound-shielded chamber (IAC). Acoustic signals were generated digitally by a microcomputer (TMS 32010 or TMS 320C30) and delivered via headphones (STAX 54) to both ears. Depending on the type of binaural interaction of the neuron under investigation, signals were presented to the left, right or to both ears.

Excitatory portions of the frequency response area (FRA) of a neuron were determined by presenting a pseudo-random sequence of 675 different bursts of pure tones (30 ms duration, 3 ms rise/fall time) with an intertone interval of 350–470 ms. The frequencies of the tones were selected from 45 frequency values out of a range of 3–5 octaves, which was centered on the neuron's characteristic frequency (CF). Tone intensities covered a range of 70 dB SPL, divided into 15 equally spaced intensity steps. For the following stimulus paradigms, a tone was selected from the FRA that, when presented alone, evoked reliable neural responses. This probe tone was usually at the CF and 10–20 dB above minimum threshold.

Inhibitory sidebands of a FRA, i.e. the range of tones that decrease the discharge probability of a neuron, were measured by simultaneously presenting the probe tone with the same set of tones that was used for the determination of the excitatory parts of the FRA.

The sequence sensitivity of a neuron was assessed by presenting various sequences of two tones. Upon the presentation of a tone sequence, the second tone, i.e. the probe tone, and the temporal separation between the tones were kept constant, whereas the frequency and the intensity of the first tone were varied, using the same list of 675 frequency/intensity combinations for the first tone that were used for the determination of the FRA. The temporal separation between the tones was measured with respect to the onsets of the two tones and will be referred to as ‘stimulus onset asynchrony’ (SOA). As both tones had a duration of 30 ms, the interval from offset of the first tone to probe onset was 30 ms shorter than SOA. On average, six (3–9) SOAs were consecutively tested for each neuron, ranging between 30 and 400 ms. In a few cases, SOA was < 30 ms, such that the first tone overlapped partially with the probe tone. Interpair intervals were adjusted to the SOA and varied between 410 and 1030 ms. In 29 neurons, we repeated selected SOAs with probes of different frequency and intensity.

Data Analysis

Single-tone Sensitivity

Excitatory portions of FRAs were assessed by counting the number of neural discharges that occurred during the presentation of each of the 675 single tones. For each tone, a vertical line was drawn at the corresponding coordinate of the frequency/intensity plane, whose length was proportional to the number of discharges (e.g. Fig. 1AGo). Note that each frequency/intensity combination was only presented once. For further analyses, several parameters were obtained from the response plane: (i) the lowest tone intensity that produced a neural response (FRA threshold); (ii) the frequency of this tone (CF); (iii) the highest tone intensity that produced a response (maximal FRA intensity); and (iv) the highest and (v) the lowest frequency 40 dB above FRA threshold that produced a response. The ratio of the two latter parameters were used to calculate the FRA bandwidth in octaves. Furthermore, rate/intensity functions were constructed at the CF and (vi) the transition point was defined as the intensity that marked the change from a fast-growing, low-intensity portion to a less fast-growing, saturating or decreasing high-intensity portion. (vii) The minimum response latency was obtained by constructing a latency/intensity function at the CF and determining its minimum.



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Figure 1. Example of the frequency response area (FRA) and the enhancement response area (ERA) of a neuron recorded from the primary auditory cortex. (A) Excitatory subfields of the FRA. Number of spikes (indicated by line length; longest line represents three spikes) that were observed during the presentation of 675 single tones of different frequency (abscissa) and intensity (ordinate). Gray circles mark FRA threshold and FRA borders measured 40 dB above FRA threshold. The star indicates the probe tone (7.6 kHz, 55 dB), which was used to obtain the inhibitory subfields of the FRA (B) and the ERA (C,D). (B) Inhibitory subfields of the FRA are defined by those entries of the response plane in which no probe response were observed. (C) Number of spikes that were observed in the two-tone condition during the presentation of the probe tone, depending on the frequency (abscissa) and intensity (ordinate) of the first tone, which preceded the probe at a SOA of 120 ms. (D) Low-pass filtered version of (C) (see Materials and Methods for details). Here, size of rectangles is proportional to probe response strength. Open rectangles denote probe responses that were enhanced by the first tone, filled rectangles in turn denote non-enhanced probe responses. In the left ERA band, gray circles signify the stimulus range inducing response enhancement. In clockwise order: ERA threshold, lowest frequency of the ERA band (measured 40 dB above the FRA threshold), maximal ERA intensity, highest frequency of the ERA band, and the frequency (BEF) and intensity (BEI) of the first tone that produced the maximally enhanced probe response, which was 250%.

 
In an analogous fashion, inhibitory portions of FRAs were determined by counting the number of discharges that were evoked by 675 single tones, each of which was presented simultaneously with the constant probe tone, and observing for what frequency/intensity combinations no responses occurred (Fig. 1BGo). From the resulting response plane, the lowest and highest inhibitory frequency 40 dB above FRA threshold were measured for each sideband.

Sequence Sensitivity

The sequence sensitivity was assessed by counting the number of discharges that occurred during the presentation of the probe tone, separately for each frequency/intensity combination of the preceding or first tone. These numbers were plotted in a two-dimensional coordinate system with the frequency and intensity of the first tone on the abscissa and ordinate respectively (Fig. 1CGo).

The response plane was low-pass filtered to reduce the response variability due to single presentation of each sequence (Fig. 1DGo), as described previously (Brosch and Schreiner, 1997Go): the responses to tones of the same intensity but differing by one frequency step were weighted by 0.22, and those differing by two frequency steps by 0.11. Responses to tones of the same frequency but 5 dB louder or softer were weighted by 0.17. The resulting sum was then divided by 2 to give an average spike count. In this report, each response plane was filtered four times in this fashion.

After filtering, the first tones that produce an enhanced response to the probe tone were identified by comparing each probe response with the probe response when this response was not affected by a preceding tone. The magnitude of the unaffected probe response was estimated from the probe responses that were observed after the presentation of first tones below the single-tone threshold, i.e. from the 90–135 responses to tones of the lowest two or three intensities. Because of time limitations such a high number of probe-alone presentations could not be performed for each SOA. From the unperturbed responses of the two-tone condition, the second strongest response was obtained and used as a critical value. Subsequently, we marked all entries in the 12 or 13 upper rows of the response plane for which the response to the probe tone exceeded this critical value (Fig. 1DGo) and considered them to indicate the set of first tones that elicited response enhancement. Response enhancement for the two or three bottom rows of the response plane was not determined. This procedure was performed separately on all SOAs tested on a neuron, because the responsiveness of some neurons varied during the measurement period (see three bottom rows of the response planes shown in Figs 2 and 3GoGo).



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Figure 2. Example of the SOA, frequency and intensity dependence of response enhancement in the two-tone paradigm. The first, free-standing panel of the pseudo-three-dimensional plot shows the neural responses to the first tone of each of the 675 stimulus pairs, i.e. the FRA of the neuron. The following, connected panels depict the number of discharges that were evoked by the probe tone when it was preceded, at a SOA indicated below each frame, by a first tone with a frequency and intensity specified on the abscissa and ordinate respectively. Enhanced responses to the probe tone were observed at a SOA of 70 and 100 ms. They are marked by open rectangles in the response planes. At a SOA of 70 and 100 ms, the strongest probe response was enhanced by 810% and 650% respectively (indicated by arrows). All other conventions as in Figure 1Go.

 


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Figure 3. Second example of the stimulus dependence of response enhancement. The strongest probe response occurred at a SOA of 150 ms and was enhanced by 1620%. Same conventions as in Figure 2Go.

 

    Results
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Notes
 References
 
This report is based on 53 single units and 58 multiunits in AI. Thirty-two of the single units and 48 of the multiunits exhibited significantly enhanced responses to the probe tone in the two-tone paradigm, whereas 5 single units and 4 multiunits did not exhibit enhanced responses. The remaining 16 single units and 6 multiunits were not considered further either because their pure tone responses were too weak, because too few SOAs were tested, or because they exhibited responses at long latencies, which temporally overlapped with the response to the probe tone and, thereby, obscured genuine two-tone interactions. Generally, characteristics of response enhancement were similar in the single unit and multiunit sample (Table 1Go) and, thus, their results will be presented conjointly.


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Table 1 Similar characteristics for response enhancement in the single unit and multiunit sample
 
Enhancement Response Areas

Examples for the frequency/intensity combinations of first tones that produce enhanced responses to the probe tone are shown in Figures 1D, 2, 3 and 8GoGoGoGo. Inspection of different response planes revealed that the enhancing tones were not randomly distributed in the frequency/intensity plane but usually formed one, two or three spatially distinct clusters. This indicates that response enhancement was induced from circumscribed parameter sets of the first tone with similar frequencies and intensities. In analogy to FRAs for single-tone sensitivity, these clusters were considered as the enhancement response area (ERA) of a neuron and, thus, characterized the sensitivity of a neuron for tone sequences.



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Figure 8. Example of the influence of the frequency and intensity of the probe tone on response enhancement. Excitatory portions of the FRA of the neuron are shown in the left free-standing panel (I). Inhibitory sidebands of the FRA are indicated by thin lines (details shown in J). The location of eight probe tones with respect to the FRA are indicated by the stars. The other panels (AH) show the responses to the probe tone, depending on the frequency and intensity of the first tone of the sequence. They are arranged in an orderly fashion according to the frequency and intensity of the probe tones. The magnitude of the maximally enhanced probe response (as a percentage) is given in the upper left corner of each panel. SOA was 30 ms. All other conventions as in Figure 1Go.

 
ERAs obtained at different SOAs and from different neurons could be quite variable in shape and sometimes were not very well defined. In part, the noisiness of ERAs was due to the fact that all tone sequences were presented only once and that the response planes of different SOAs were analyzed independently from one another. Yet some general features emerged when response planes of neurons were considered in which spike counts and magnitude of response enhancement were sufficient to reveal at least moderately defined ERAs: the majority of ERAs consisted either of one (40%) or of two circumscribed parameter regions (56%). The proportion of ERAs with three parameter regions was small (4%). The shape of the individual parameter regions was similar to the typical shapes of FRAs, i.e. they had the form of a diamond-shaped (58%) or a ‘V’-shaped band (42%). Eighty-eight percent of the ERA bands were located either on or close to the lowor high-frequency side of the FRA, whereas 12% were centered on the FRA.

For a comprehensive characterization of the response enhancement induced by different first tones, several parameters were measured in each ERA. The magnitude of enhancement was the maximal probe response in the ERA divided by the average unaffected probe response (see above). The best enhancing frequency (BEF) and the best enhancing intensity (BEI) were the frequency and the intensity of the tone evoking maximal enhancement respectively. The ERA threshold was the tone with the lowest intensity that produced response enhancement, and the maximal ERA intensity was the highest tone intensity. Finally, the lowest and the highest ERA frequency were measured at an intensity 40 dB above the FRA threshold. For some neurons, the extent of ERAs was underestimated because the extreme borders of the ERA bands were limited by the margins of the stimulus range tested. Note further that the low-pass filtering of response planes decreased the magnitude of enhancement and the precision of ERA parameters.

In addition to response enhancement, many response planes also reflected response attenuation (see Figs 1C, 2, 3 and 8GoGoGoGo), i.e. there were tone sequences with significantly reduced responses to the probe tone. Characteristics of the attenuation response area (ARA) of the neurons of the present report have been described earlier (Brosch and Schreiner, 1997Go).

Stimulus Dependence of Response Enhancement

Generally, response enhancement depended on the frequency and intensity of the first tone and on the SOA between the first and the probe tone. The stimulus dependence of enhancement effects could not be determined with highest precision because of physiological (fluctuations of responsiveness) and methodological limitations (single presentation of stimuli; low-pass filtering of ERAs). Therefore major features of response enhancement were obtained for each neuron from the SOA at which the maximally enhanced response was observed.

The magnitude of the maximally enhanced response to the probe tone ranged from 140 to 5270% in different neurons with our stimulus material, with a median of 340% (Fig. 4Go). This is similar to the magnitudes of enhancement found previously in the responses of neurons in bat auditory cortex (Fitzpatrick et al., 1993Go; Esser et al., 1997Go) and in the evoked N100 wave from human auditory cortex (Loveless and Hari, 1989; Budd and Michie, 1994Go).



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Figure 4. Distribution of the maximal magnitude of response enhancement observed in the single unit (black bars) and multiunit sample (gray bars).

 
Stimulus Onset Asynchrony

Response enhancement was usually non-monotonically related to the temporal separation between the two tones. In the first example (Fig. 2Go), response enhancement was observed only for SOAs between 70 and 100 ms, with no indication for enhancement at shorter and at longer SOAs. In the second example (Fig. 3Go), a longer minimal SOA (100 ms) was required for the induction of response enhancement. Beyond these SOAs, enhanced responses were seen for all SOAs up to 350 ms, the longest SOA tested in this neuron. Within the enhancing SOA range, the maximally enhanced response was observed at a SOA of 150 ms. At longer SOAs, the magnitude of response enhancement as well as the size of the two ERA bands decreased progressively. This indicates that no further enhanced responses occurred at some SOA > 350 ms.

The non-monotonic dependence of response enhancement on SOA was found in all neurons that were tested with a sufficiently wide SOA range. There was a minimal SOA required for the induction of response enhancement. This shortest enhancing SOA ranged from 20 to 100 ms, with a median of 50 ms (Fig. 5AGo). For SOAs longer than the shortest enhancing SOA, the magnitude of enhancement increased up to some SOA at which the maximally enhanced response was observed. This preferred SOA varied between 30 and 210 ms, median SOA was 100 ms (Fig. 5BGo). For even longer SOAs, the magnitude of enhanced probe responses decayed until, beyond the longest enhancing SOA, no more enhanced responses were detected. The longest enhancing SOA was in the range of 50 and 400 ms, with a median of 130 ms (Fig. 5CGo).



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Figure 5. Temporal characteristics of tone sequences resulting in response enhancement. (A) Distribution of the shortest enhancing SOA. (B) Distribution of the preferred SOA. This parameter represents the SOA at which the maximally enhanced response was observed in a neuron. (C) Distribution of the longest enhancing SOA. The three panels include only neurons in which we tested SOAs shorter than the shortest enhancing SOA, shorter and longer than the preferred SOA, and longer than the longest enhancing SOA respectively. Same conventions as in Figure 4Go.

 
Frequency and Intensity of the First Tone

At the preferred SOA, the probe responses of 50 out of 58 neurons were enhanced by first tones located in two spectrally separated ERA bands, and only eight neurons had a single ERA band. In some cases, it appeared that an ERA band was a superposition of two or more individual bands. The bandwidth of the lower ERA band varied between 0.4 and 3.4 octaves, with a median of 1.5 octaves (Fig. 6AGo). The bandwidth of the upper ERA band was in the range of 0.1–2.2 octaves, with a median of 1.3 octaves (Fig. 6BGo). Within the enhancing frequency range, different frequencies were differentially effective and there was a frequency, the BEF, that induced maximal response enhancement of the probe tone. The distribution of BEFs can be obtained from Figure 12EGo, where BEF is plotted in relation to the CF.



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Figure 6. Frequency characteristics of response enhancement at the preferred SOA. (A) Distribution of the bandwidth of the lower ERA band. (B) Distribution of the bandwidth of the upper ERA band. (C) Relation between probe frequency and the highest frequency of the lower ERA band. Filled and open symbols represent single unit and multiunit data respectively. Diagonal indicates cases for which values on the abscissa and ordinate were equal. (D) Relation between probe frequency and the lowest frequency of the upper ERA band. (E) Distribution of the preferred frequency interval. It was calculated as the difference in octaves between the BEF and the probe frequency. ‘Upward’ and ‘downward’ mean that the BEF was lower and higher than the probe frequency respectively.

 


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Figure 12. Comparison between excitatory portions of FRAs and ERAs. ERA parameters were obtained at the preferred SOA. (A) Low-frequency FRA border versus high-frequency border of the lower ERA band. (B) High-frequency FRA border versus low-frequency border of the upper ERA band. (C) FRA threshold versus ERA threshold. (D) Maximal FRA intensity versus maximal ERA intensity. Largest symbol stands for six cases. (E) CF versus BEF. Same conventions as in Figure 11Go.

 
For a closer characterization of the sequence sensitivity, the range of enhancing first tones was related to the probe tone frequency. This analysis revealed that enhanced responses occurred mostly when the frequency of the first tone was sufficiently different from the frequency of the probe tone: the highest frequency of the lower ERA band was, with a few exceptions, below the frequency of the probe tone (Fig. 6CGo), and the lowest frequency of the upper ERA band was almost always higher than the probe frequency (Fig. 6DGo). The difference in octaves between the BEF and the frequency of the probe tone was termed the preferred frequency interval of a sequence-sensitive cell. Inspection of the distribution of the preferred frequency interval (Fig. 6EGo) revealed that there were about as many neurons that preferred sequences with upward frequency progressions (BEF < probe frequency) as there were neurons that preferred downward progressions (BEF > probe frequency). The absolute value of the preferred frequency interval was symmetrically distributed around a mean interval of 1.1 ± 0.4 octaves.

In the intensity domain, response enhancement was induced from a considerable range of intensities of the first tone (see Fig. 12A,BGo for the distribution of ERA threshold and maximal ERA). The ERA intensity range, i.e. the difference between maximal ERA intensity and ERA threshold, varied from 10 to 65 dB with a median of 30 dB (Fig. 7AGo). Within the ERA intensity range, there was the BEI at which the maximally enhanced response was observed. For all neurons combined, the BEI varied between 43 and 93 dB, with a median of 68 dB. In 80% of the neurons, BEI was softer than the most intense first tone that was tested. The intensity tuning was further reflected by the finding that in 30% of the neurons, the most intense first tones did not produce any enhanced responses at all.



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Figure 7. Distribution of intensity characteristics of response enhancement at the preferred SOA. (A) Intensity range of the first tone inducing response enhancement. (B) Difference between probe intensity and ERA threshold. (C) Difference between maximal enhancing intensity and probe intensity. (D) Preferred intensity interval. This parameter was defined as the difference between BEI and probe intensity. Same conventions as in Figure 4Go.

 
Comparison of the two tones in the sequence revealed that the response to the probe tone could be enhanced by first tones that were either less and or more intense than the probe tone: in the majority of neurons, the ERA threshold was below the intensity of the probe (Fig. 7BGo) and the highest or maximal enhancing intensity was above the probe intensity (Fig. 7CGo). The BEI was 14 dB (median; range –36 to 34 dB) above the intensity of the probe tone (Fig. 7DGo).

Probe Tone Properties

The characteristics of response enhancement described so far were determined by using probe tones close to the CF and 10–20 dB above the single-tone threshold of a neuron. However, responses to other probe tone conditions could also be enhanced by preceding tones, even if the probe parameters widely differed from the standard selection. An example is shown in Figure 8Go for eight different probe tones. If enhanced responses were observed in a neuron, they were most clearly detected when the probe tone was inside the excitatory portion of the FRA, i.e. when the probe itself evoked a response with a high probability (bottom rows in Fig. 8B,C,F,GGo), whereas less enhancement was observed when the probe evoked only a weak or no response at all (Fig. 8A,D,E,HGo). This was confirmed in another 19 single units and 9 multiunits, which were tested with probe tones of different frequencies and intensities and with different SOAs. For the entire sample of neurons with response enhancement, 85% of the neurons exhibited enhanced responses to other probe tones inside the excitatory FRA, whereas only 26% of the neurons did so when the probe tones were in the vicinity to but outside the border of the excitatory FRA. When a probe tone was enhanced, it was enhanced predominantly from a comparable range of frequencies and intensities of the first tone. ERAs obtained with suboptimal probe tones were often less well-defined and, thus, the ranges of enhancing frequencies, intensities and SOAs were often less precisely estimated.

The First Tone Does Not Affect the Timing of the Response to the Probe

The first tone had no systematic effect on the time of occurrence of enhanced responses to the probe tone. Figure 9Go shows the time course of the responses to different tones of the neuron whose FRA and ERA are displayed in Figure 1Go. The peristimulus time histograms demonstrate that, in the single-tone condition (Fig. 9A,BGo), all responses to the probe tone and to other tones within the excitatory FRA occurred 10–31 ms after tone onset. For none of the tones there were any late responses at latencies >50 ms after tone onset. In the two-tone condition, the probe responses occurred almost in the same time range. The mean latency of the responses to the probe tone observed in the single-tone condition was almost identical to the mean latency in the two-tone condition independent whether the first tone had no (Fig. 9CGo) or an enhancing effect (Fig. 9DGo; 18.9 versus 19.8 versus 19.2 ms) and the differences of the response latencies were statistically not significant (Kruskal–Wallis test, {chi}2 = 5.8, df = 2, P = 0.1). The small latency difference of the probe responses observed in the different stimulus conditions was confirmed in the entire sample (Fig. 10Go). At the preferred SOA, the mean latency difference between the non-enhanced and enhanced responses to the probe tone was found to be symmetrically distributed around 0.1 ± 1.9 ms.



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Figure 9. Time course of the responses to acoustic signals of the neuron shown in Figure 1Go. (A) Peristimulus time histogram (PSTH) computed from all discharges of the FRA shown in Figure 1AGo. Tones commenced at the origin of the PSTH and had a duration of 30 ms. (B) PSTH calculated only from the responses to nine single tones with frequencies between 6.2 and 8.5 kHz and intensities between 48 and 58 dB. This PSTH represents an estimate of the response to the probe tone alone. (C,D) PSTHs of the probe responses when the probe tone was preceded by a first tone of low intensity (23–33 dB; C) and of the probe responses that were enhanced by the first tone (D).

 


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Figure 10. Distribution of the difference between the mean latency of enhanced probe responses and the mean latency of probe responses that were not enhanced by the first tone. Same conventions as in Figure 4Go.

 
Comparison between Response Enhancement and Response Attenuation

In all but four neurons exhibiting response enhancement, the first tone could also attenuate the response to the following probe tone (Brosch and Schreiner, 1997Go). In these four neurons no response attenuation was seen for methodological reasons as the response to the probe tone was too weak. If both types of post-stimulatory effects were detected, response attenuation was always induced from a single frequency band, whereas response enhancement was induced mostly from two frequency bands. The enhancement and attenuation regions (ERA and ARA bands) had little overlap. This was evident when ERAs and ARAs obtained at the same SOA were compared. However, there was also little overlap between ERAs and ARAs obtained at different SOAs. Figure 11Go compares characteristics of the ERA bands obtained at preferred SOA, i.e. when response enhancement was strongest in a neuron, with respective characteristics of the ARA band obtained at a SOA of 30 ms (when the maximal extent of attenuation was observed). The largest difference between the two types of response modulation was in the frequency domain: in 32 out of 52 neurons, the lower ERA band did not overlap with the ARA (Fig. 11AGo). In 49 out of 52 neurons, the upper ERA band had no overlap with the ARA (Fig. 11BGo). For most of the neurons with overlap, the overlap was small compared to spectral extent of the ERA and ARA bands. Moreover, the BEF was ~1 octave above or below the frequency of the least intense tone that induced response attenuation (Fig. 11EGo). In the intensity domain, there was considerable overlap between the tones producing response enhancement and response attenuation, albeit response enhancement was induced from a smaller intensity range than was response attenuation.



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Figure 11. Comparison between response enhancement and response attenuation. In (A)–(D), enhancement (ERA) parameters were obtained at the preferred SOA and attenuation (ARA) parameters at a SOA of 30 ms. (A) Low-frequency ARA border versus high-frequency border of the lower ERA band. (B) High-frequency ARA border versus low-frequency border of the upper ERA band. (C) ARA threshold versus ERA threshold. (D) Maximal ARA intensity versus maximal ERA intensity. Size of symbols is proportional to the number of cases. Largest symbol represents four cases. (E) BAF versus BEF. BAF was defined as the frequency of the least intense tone-inducing response attenuation. The two diagonals denote cases in which BEF was one octave above or below BAF. (F) Longest attenuating SOA versus longest enhancing SOA (r = 0.63). Same conventions as in Figure 6Go.

 
In the temporal domain, response enhancement depended non-monotonically on the SOA between tones as described above, whereas response attenuation decreased monotonically with increasing SOA (Brosch and Schreiner, 1997Go). Nevertheless, the longest enhancing SOA was strongly correlated (r = 0.63) with the longest SOA for which response attenuation was observed (Fig. 11FGo).

Relation between Sequence Sensitivity and Single-tone Sensitivity

Tones that enhance the response to a subsequent tone usually were different from the tones that directly evoke an excitatory response in a neuron. The dissimilarity between ERAs and FRAs was most obvious in the frequency domain. Comparison of ERAs at the preferred SOA with single tone FRAs showed that, in most cases, the lower ERA band did not overlap with the low-frequency border of the FRA (Fig. 12AGo) and that there was almost no case in which the upper ERA band overlapped with the high-frequency border of the FRA (Fig. 12BGo). For the remaining cases, the overlap region was small compared to the extent of the ERA bands and the FRA. The frequency difference between the range of the enhancing tones and the normal excitatory tones was also reflected in the relation of BEF and CF (Fig. 12EGo). The two frequencies were always different and the distribution of the absolute value of their difference peaked at ~1 octave, indicating that BEF was either ~1 octave below or above CF. This was similar to the preferred frequency interval because the probe tone was usually set at the CF of a neuron.

The intensity range that induced response enhancement overlapped with and generally was smaller than the intensity range evoking an excitatory response. This was reflected by finding that, in 68% of the neurons, the ERA threshold was higher than the FRA threshold (Fig. 12CGo) and that, in 22% of the neurons, the maximal ERA intensity was smaller than the maximal FRA intensity (Fig. 12DGo).

Although ERAs and FRAs had little overlap, there were a number of associations between the sequence sensitivity and the single-tone sensitivity of neurons, expressed by statistically significant correlations between various enhancement and FRA parameters (Table 2Go). This included a positive correlation between excitatory bandwidth of the FRA and the preferred SOA. In addition, it was found that the minimum response latency to single tones was positively correlated with the SOA with strongest enhancement (Fig. 13AGo) and with the magnitude of enhancement (Fig. 13BGo).


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Table 2 Relations between characteristics of response enhancement and single-tone sensitivity
 


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Figure 13. Minimum response latency was positively correlated with (A) preferred SOA (r = 0.37) and (B) strongest magnitude of enhancement (r = 0.58). Same conventions as in Figure 6Go.

 
To test whether response enhancement might be associated with postinhibitory rebound excitation (Suga, 1990Go), we compared the ERA bands with the inhibitory subfields of the FRA. This was assessed for 14 single units and 8 multiunits with the simultaneous two-tone paradigm (see Materials and Methods). Examples of the resulting inhibitory subfields of FRAs are given in Figures 1B and 8JGoGo. Comparison of the inhibitory parts of the FRA with corresponding ERAs (Figs 1D and 8AD,F,GGoGo) revealed that the tones producing simultaneous inhibition were mostly different from the tones producing sequential response enhancement. Combined for all 22 sites with two-tone estimates, 16 of the lower inhibitory FRA sidebands had no overlap with the lower ERA band (Fig. 14AGo) and 20 of the upper inhibitory FRA sidebands had no overlap with the upper ERA band (Fig. 14BGo). For the remaining cases, the relative overlap region was small compared to the extent of the ERAs and the inhibitory portions of the FRA.



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Figure 14. The frequency range that suppressed the neural response was largely different from the frequency range that induced response enhancement. (A) The lowest inhibitory FRA-frequency was mostly greater than the high-frequency border of the lower ERA band. (B) The highest inhibitory FRA-frequency was almost always smaller than the low-frequency border of the upper ERA band.

 

    Discussion
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Notes
 References
 
The present study extends previous findings on sequence-sensitive neurons in auditory cortex (Suga et al., 1978Go, 1983Go; Sullivan, 1982; Tsuzuki and Suga, 1988Go; Dear et al., 1993Go; Fitzpatrick et al., 1993Go; Esser et al., 1997Go; Brosch et al., 1999Go). Virtually all neurons in the primary auditory cortex of cats were found to respond more strongly to particular sequences of tones than to the individual tones of the sequence. Because tone sequences produced stronger responses than did single tones, these cells can be considered to show sequence sensitivity, if not sequence selectivity. The preferred sequence usually consisted of two tones that were separated in frequency by ~1 octave, in onset-time by ~100 ms and in intensity by ~14 dB in favor of the first tone.

Are All Neurons in Auditory Cortex Sequence Sensitive?

The present study found that ~90% of the neurons in AI responded more strongly to a tone played in a sequence than to a single tone. The proportion of such sequence-sensitive cells varies considerable among different reports, if such number were given or if enhanced responses were observed at all: the percentage was 15% in the auditory cortex of Eptesicus fuscus (Dear et al., 1993Go); 21% in the FM–FM area (Esser et al., 1997Go) and 76% of the neurons in AI with CFs > 60 kHz of Pteronotus parnellii (Fitzpatrick et al., 1993Go); 77 and 82% in the auditory cortex of Myotis lucifugus (Sullivan, 1982; Wong et al., 1992Go); 67% in the auditory cortex of Macaca fascicularis (Brosch et al., 1999Go). A number of factors determine the proportion of sequence-sensitive cells that can be encountered in a study, such as the species, the frequency tuning and area membership of cells, the number and range of stimulus sequences that are tested, the spectral composition of the individual tones used in the sequence, the type of neural activity and animal preparation, as well as the methods used for the detection of an enhanced response. Thus, it could be that the 10% of neurons in which no response enhancement was detected in the present study would have exhibited enhanced responses as well had we used, for instance, an even wider range of tone sequences or a different anesthetic. This raises the possibility that all neurons in auditory cortex are sequence-sensitive when stimulated with the appropriate sequence.

Dependence of Response Enhancement on Sequence Parameters

Influence of the Probe Tone

Response enhancement in cortical neurons depended on properties of both tones in a sequence, although the two tones played a different role. Response enhancement was induced from a limited range of frequencies and intensities of the first tone and only when an appropriate second tone was presented during an effective enhancement period. This finding suggests that response enhancement provides a mechanism, which acts forward in time on the neural signals evoked by a succeeding stimulus but has no backward component (Brosch et al., 1998Go, 1999Go). Generally, it was favorable to use probe tones inside the excitatory FRA of a neuron, in accordance with reports from auditory fields considered to be involved in echolocation (Suga et al., 1978Go, 1983Go) and from auditory fields of yet unidentified functions (Brosch et al., 1999Go). Suboptimal probe tones and probe tones outside the range of the single-tone sensitivity tended to be enhanced less strongly and, because all tone sequences were presented only once, ERAs were often less well-defined and the ranges of enhancing frequencies, intensities and SOAs were often underestimated.

Temporal Separation of Tones

In the temporal domain, usually no response enhancement occurred for sequences with very short SOAs and a minimal SOA was required for the induction of response enhancement. For longer SOAs, the enhancing influence of the first tone increased and reached a maximum at the preferred SOA. Beyond preferred SOA the enhancement effect declined until it seized at the longest enhancing SOA. Because of methodological limitations, this non-monotonic SOA dependence was not observed in a recent study in monkey auditory cortex (Brosch et al., 1999Go), in which no SOAs < 100 ms could be tested. A non-monotonic SOA dependence has also been obtained for neurons in various areas of the auditory cortex of echolocating bats (Suga et al., 1978Go, 1983Go; Sullivan, 1982; Tsuzuki and Suga, 1988Go; Dear et al., 1993Go; Fitzpatrick et al., 1993Go). It is further substantiated by other signal enhancement effects found in auditory cortex, such as paired-pulse facilitation of electrically evoked intracellular and field potentials in rats (Metherate and Ashe, 1994Go) and facilitation of the acoustically evoked magnetic field N100m in humans (Loveless and Hari, 1993Go). Thus it appears that the non-monotonic SOA dependence is a basic and common characteristic of sequence-sensitivity in auditory cortical neurons.

There is good agreement with a recent report on the auditory cortex of monkeys (Brosch et al., 1999Go) that the preferred SOA of neurons is ~100 ms (although this study did not test SOAs < 100 ms) and that response enhancement can be found for SOAs up to ~300 ms. This is corroborated by studies of paired-pulse facilitation of electrically evoked potentials in rat auditory cortex (Metherate and Ashe, 1994Go) and of the facilitation of the acoustically evoked N100 wave in humans (Loveless et al., 1989Go; Loveless and Hari, 1993Go; Budd and Michie, 1994Go). The minimum delay between the onsets of two tones necessary for enhancements was 50 ms, similar to values found in studies on enhancement effects in rat (Metherate and Ashe, 1994Go) and human auditory cortex (Loveless and Hari, 1993Go).

The temporal range of enhancement obtained in rats, cats and monkeys is about an order of magnitude above the range observed in neurons in different areas of the auditory cortex of echolocating bats (Suga et al., 1978Go, 1983Go; Sullivan, 1982; Dear et al., 1993Go). In bats, the temporal sensitivity range of neurons roughly corresponds to the spatial range in which bats use echolocation for the detection and identification of auditory objects. If sequence-sensitive cells in the auditory cortex of less-specialized mammals were also involved in the extraction of sound source–echo relations, the temporal range of sequential enhancement of ~50–500 ms would cover only a limited spatial range of sound source–echo relations between 7.5 and 75 m. The different temporal ranges of enhancement in the auditory cortex of echolocating and non-echolocating mammals might thus reflect different functional roles of the enhancement effects in the signal processing of these animals.

The temporal dependence of cortical enhancement effects in non-echolocating mammals has been obtained with sequences of stimuli of widely different durations (Loveless et al., 1989; Loveless and Hari, 1993; Budd and Michie, 1994; Eggermont, 1994; Metherate and Ashe, 1994; Brosch et al., 1999; this study). This suggests that response enhancement is more determined by the temporal separation between the onsets of the tones than by the duration of the individual tones or by the interval between the cessation of the leading and the commencement of the trailing tone. The importance of the onsets of the tones in a sequence might reflect that the majority of studies have found that cortical cells are more sensitive to onsets than to offsets of acoustic signals (Heil, 1997Go).

Frequency of Tones

In virtually all neurons analyzed in the present study, enhanced responses were induced from two distinct frequency bands. This finding is in contrast to that of a recent report on response enhancement in monkey auditory cortex, in which only 31% of the neurons had two ERA bands (Brosch et al., 1999Go). This discrepancy might be due to methodological differences. In the present study, ~100 times as many first tones were tested as in the monkey study, and the intensity of the first tones was varied as well. Thus, the chances to detect response enhancement were markedly increased. However, the difference in the number of ERA bands could also reflect dissimilarities between sequence-sensitive cells in different species and cortical fields. The present study was performed on AI of cats whereas, in the study of Brosch and colleagues (Brosch et al., 1999Go), most neurons were from non-primary auditory fields of monkeys. That such differences might exist is also suggested by studies on bat auditory cortex, in which almost all neurons had single-banded ERAs, which was always below the frequency of the probe tone (Suga et al., 1978Go, 1983Go).

That sequence-sensitive neurons in various cortical areas might have different functional roles in the processing of sequential stimuli is further suggested by the widths of ERA bands. In bat auditory cortex, average bandwidth of individual ERA bands was ~1/5 octave, whereas it was >=1 octave in cat and monkey auditory cortex (Brosch et al., 1999Go). Because bandwidths in bat auditory cortex are within the frequency range of Doppler shifts of moving objects, sequence-sensitive neurons in bats have been suggested to underlie specific echolocation tasks (Suga, 1990Go). Wider bandwidths, like those found in non-echolocating mammals, would make neurons sensitive to Doppler shifts of >20%. Such frequency shifts result from objects moving at speeds >60 m/s, speeds hardly ever encountered in natural environments.

In sequences for which response enhancement was observed, the frequency of the first tone was different from the frequency of the probe tone. Little or no response enhancement was found when the tones of a sequence had the same frequency. For such sequences, mostly response attenuation prevailed (Calford and Semple, 1995Go; Brosch and Schreiner, 1997Go). The maximally enhanced response occurred when the first tone was either ~1 octave below or above the probe tone. This finding is in good agreement with a recent study on the frequency dependence of response enhancement in monkey auditory cortex (Brosch et al., 1999Go). The importance of octave relations in tone sequences for the induction of response enhancement is unclear but may relate to issues of spectral contrast enhancement in sequential stimuli beyond the range of critical bands. In bat auditory cortex, sequence-sensitive neurons exhibit enhanced responses when the emitted pulse FM was harmonically related to the echo FM (Suga et al., 1978Go, 1983Go), which is in accordance with the specific properties of biosonar sounds.

Intensity of Tones

Response enhancement was also determined by, and tuned to, the intensity of the first tone of a sequence. The importance of the intensity of the first tone for the induction of response enhancement has previously been shown only for neurons in bat auditory cortex considered to be involved in echolocation (Suga et al., 1978Go; Sullivan, 1982; Tsuzuki and Suga, 1988Go). These studies have obtained intensity dependencies qualitatively similar to those of the current study. In bat auditory cortex, the intensity dependence of response enhancement has been suggested to play a role in distance and size measurement of acoustic targets. The functional role of the intensity dependence of sequence-sensitive cells in non-echolocating mammals is yet unknown but may be implemented to counteract forward masking of weaker stimuli.

Neural Coding of Tone Sequences

In this study, enhancing tones caused an increase of the number of discharges in response to the consecutive tone, without altering the latency of this response. This effect is similar to enhancement phenomena seen in neurons in bat auditory cortex (Suga et al., 1978Go; Sullivan, 1982; Dear et al., 1993Go), but it is in contrast to those of neurons in monkey auditory cortex (Brosch et al., 1999Go) and to the facilitation of intracellular and extracellular potentials in humans (Loveless et al., 1989Go; Loveless and Hari, 1993Go; Budd and Michie, 1994Go) and rats (Metherate and Ashe, 1994Go). In the latter studies, initial portions of the response to the probe were largely unaffected by the preceding stimulus and enhancement was effective in a latency range of ~30–90 ms after onset of the probe. The differences in the latency range in which enhancement was effective could result from methodological differences, such as animal preparation or use of different interpair intervals, or from the fact that different types of neural signals were considered, namely action potentials from single cells and slow wave electrical potentials and magnetic fields from a large number of cells. Furthermore, differences in the time period of enhancement are paralleled by the complexity of responses to single stimuli. In this and the cited bat studies, most neurons had a rapid and brief phasic response. In the studies in other animals, most neurons had temporally complex responses that lasted up to several hundreds of milliseconds after stimulus onset. Such responses were indeed observed in the present study, but only in a small fraction of neurons and they were not further considered. Thus, the differences in the latency of the responses could also result from fundamentally different coding mechanisms utilized in different species. This might indeed be the case for neurons in bat auditory cortex involved in echolocation. However, it would be an unsatisfactory explanation of the current findings in cat auditory cortex because the stimulus dependence of response enhancement was in close correspondence with the one observed in monkey auditory cortex (Brosch et al., 1999Go).

The different latency ranges could also suggest that response enhancement is established by different cellular mechanisms in the auditory cortex of different species. A disinhibition model accounted best for sequential enhancement phenomena observed in the auditory cortex of humans (Loveless et al., 1989Go; Loveless and Hari, 1993Go; Budd and Michie, 1994Go), monkeys (Brosch et al., 1999Go) and rats (Metherate and Ashe, 1994Go). In this model, the first stimulus blocks inhibitory potentials which are induced by the second stimulus and which normally suppress excitatory potentials which are also induced by the second stimulus (Mitzdorf, 1987Go). Disinhibition does not appear adequate to explain the occurrence of enhanced responses in the present study because probe tones that produced inhibition when presented in isolation were not more strongly enhanced than probe tones that produced an excitatory response. Furthermore the inhibitory sidebands of a neuron had little overlap with the enhancement areas.

For the bat auditory system involved in echolocation, Suga has proposed that a coincidence detection mechanism detects the coincidence in time of the excitatory response to the second stimulus and a delayed response to the first stimulus (Suga, 1990Go). The delayed response is generated either by neuronal delay lines for short SOAs or by inhibition of different durations, which is followed by an excitatory rebound for longer SOAs. This model also appears to be incompatible with current findings. First, it is highly unlikely that neuronal delay lines establish late responses with delays equivalent to the range of enhancing SOAs observed in the auditory cortex of non-echolocating mammals. Second, generation of late responses by postinhibitory rebound excitation can also not account for response enhancement because there was almost no correlation between the tones inducing enhancement and the tones evoking inhibition, as indicated by the little overlap of the ERAs with the inhibitory portions of the FRA (Fig. 14Go) and the little overlap of the ERAs with the ARA (Fig. 11Go).

Therefore, the present results are most consistent with a presynaptic facilitation mechanism, in which the cellular signals evoked by the first stimulus augment the signals evoked by a consecutive stimulus, which in turn results in an enhanced number of discharges in response to the second stimulus (Volgushev et al., 1997Go).

Functional Considerations

The cited studies on response enhancement, together with reports on response attenuation with sequential stimuli, demonstrate that the responses to an acoustic signal of neurons in auditory cortex are influenced by preceding acoustic signals. There is a clear relation between the tones that themselves evoke a response and the tones that enhance (Figs 12, 14GoGo), as well as those that attenuate the response to a consecutive tone (Calford and Semple, 1995Go; Brosch and Schreiner, 1997Go). These findings indicate that all neurons in auditory cortex have complex and often non-separable spectro-temporal receptive fields (Aertsen and Johannesma, 1980Go), whose components cannot be determined independently by separately measuring spectral and temporal filter functions. Accordingly, the spectral filtering of cortical neurons varies with the temporal stimulus context and the temporal filtering varies with the spectral content of consecutive acoustic signals. This implies that both rate and synchronization measures of conventionally determined temporal modulation transfer functions (Schreiner and Urbas, 1986Go; Eggermont, 1999Go) change considerably when they are measured with temporally modulated acoustic signals in which the spectral content of consecutive segments varies as well.

The specific relationships between single-tone receptive fields and sequence sensitivity of cortical neurons (Figs 12–14GoGoGo) as well as characteristics of response attenuation (Calford and Semple, 1995Go; Brosch and Schreiner, 1997Go) suggests that different neurons in auditory cortex encode different aspects of spectro-temporal relations of acoustical sounds. We consider response enhancement and response attenuation as important neuronal mechanisms that shape the responses of cortical neurons to sequences of complex acoustic signals. Post-stimulatory suppression generates the preference of cortical neurons to respond only to slow temporal modulations of complex acoustic signals. The suppression lasts longest when the spectral content of the consecutive segments of an acoustic signal is similar. Thus cortical neurons can phase-lock their discharges to faster temporal modulations when the frequency content of consecutive segments varies over time. The preference for sequences with segments of varying spectral content is further augmented by response enhancement, which causes cortical neurons to respond even more strongly when consecutive segments of acoustic signals have sufficiently differing frequency, intensity and temporal properties. Response attenuation and response enhancement can thus provide temporal analogies of inhibitory and facilitatory sidebands involved in the creation of simultaneous contrast sensitivity.

The sequence-sensitivities of cortical neurons are reasonably well matched to certain aspects of spectro-temporal features commonly encountered in speech sounds, animal vocalizations and music. Speech is composed of a series of sequential segments with different distributions of spectral energy and overall intensity and has segmentation rates similar to the observed range of the enhancing SOA range (Plomp, 1975Go). In music, octave relations and movements of tones play a major role in the musical scales of nearly all human cultures (Handel, 1994). It is thus likely that response enhancement contributes to a robust cortical representation of the temporal structure of sound sequences and auditory streams.


    Notes
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Notes
 References
 
We thank Dr Barbara Calhoun and Dr Sarah Wong for help during some of the experiments, Cornelia Bucks for assistance in data analysis and Dr Peter Heil for valuable suggestions on the manuscript. The work was supported by NIH P01 NS34835, NIH R01 DC02260, NSF 9720398, and the Deutsche Forschungsgemeinschaft (Br 1385/1).

Address correspondence to Michael Brosch, Ph.D., Leibniz-Institut für Neurobiologie, Box 1860, 39008 Magdeburg, Germany. Email: brosch{at}ifn-magdeburg.de.


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