Top Summary Introduction Methods and Materials Results Discussion References

A. Schuett¹, E. Ba-ar1 and T. H. Bullock²

1 Institute of Physiology, Medical University of Luebeck
23538 Luebeck, Germany

2 Department of Neurosciences, School of Medicine
University of California, San Diego
La Jolla, CA 92093-0201, U. S. A.


Running title: Odorant-induced activity of the Helix brain.


Address for proofs: Atsuko Schuett
Institute of Physiology
Medical University of Luebeck
Ratzeburger Allee 160
23538 Luebeck, Germany
e-mail: schuett@physio.mu-luebeck.de

phone: 0451-500 4180
fax: 0451-5004171



List of abbreviations:

AFP Amplitude-Frequency-Plot
EEG electroencephalogram
FP field potential
PC procerebrum or procerebral
RMS root-mean-square
VG visceral ganglion

Summary

Top Summary Introduction Methods and Materials Results Discussion References

To test the hypothesis that different odorants are likely to cause distinctive changes in the ongoing electrical activity of populations of olfactory cells, we investigated field potentials (FP) in the Helix brain and their alterations by odorants as seen by semimicroelectrodes in an isolated preparation of the rostrum with ist olfactory organ and whole central nervous system. Five pure chemicals and two natural odorants were applied as stimulants. Signals recorded both from the procerebrum (PC) and the visceral ganglion (VG) were analyzed. In the PC the five pure chemical odorants induce stimulus-specific characteristic responses, mainly in the low frequency range (<15 Hz). Regardless of odor intensity, the frequency of the peak power of sustained induced activity is constant for each chemical: ammonia at 0.2 ( <0.02 Hz; formic acid at 0.36 ( 0.03 Hz; 2-pentanol at 0.48 ( 0.04 Hz; 2-butanol at 0.67 ( 0.03 Hz; ethanol at 1.31 ( 0.09 Hz (means ( 95% confidence limits). These peak power frequencies, which we define as (odor-specific frequencies(, are confined to the low frequency range of < 2.5 Hz. Those of natural odorants are: onion (0.36 ( 0.14 Hz) and apple (1.1 ( 0.25 Hz). The activities evoked in the PC propagate to VG. The order of behavioral aversion determined by withdrawal reactions of the tentacles, 1% ammonia > formic acid > 2-pentanol > 2-butanol > ethanol, coincides with (the order of molecular affinity( as well as with the sequence of peak power frequencies. There seems to be a strong correlation among behavioral valence, chemical nature of an odorant, and odor-specific frequency. The finding that, in the Helix olfactory center, odor input is processed as odorant specific low frequency FP activity may represent some general phenomena of olfactory information processing.

Introduction

Top Summary Introduction Methods and Materials Results Discussion References

Odor stimulation brings neurons of olfactory centers into rhythmical activity (Adrian 1942; Mellon 1992; Chase 1993). Oscillations have been observed in the olfactory systems of various vertebrates, such as fish, frog, turtle, rodent, opossum, rabbit, cat and human (Tank et al. 1994). Recently, odorant-induced field potentials (FPs) have been recorded from the olfactory systems of invertebrates, such as slug (Limax)(Gelperin 1994; Gelperin and Tank 1990, Gelperin and Flore 1997; Gelperin et al. 1993; 1996; Kimura et al. 1993; Kleinfeld et al. 1994; Gervais et al. 1996), land snail (Suzuki 1967; Balaban and Maksimova 1993; Schuett and Ba-ar 1994); locust (Laurent and Davidowitz 1994; MacLeod and Laurent 1996; Laurent et al. 1996). Odor induced modulation of FP oscillations has also been observed in vertebrate olfactory systems (Freeman 1975; Bressler and Freeman 1980; Eckert and Schmidt 1985; Delaney and Hall 1996; Duchamp-Viet et al. 1990). In humans, odor-evoked as well as event-related potentials have recently been studied by a number of authors (Kobal and Hummel 1988; Klemm et al. 1992; Zatorre et al. 1992; Van Toller et al. 1993; Evans et al. 1995; Lorig et al. 1991, 1995; 1996). These authors now predict that the oscillations in potential, which are modulated by odor-input, may have a functional role in odorant encoding. Molluscan central nervous systems exhibit spontaneous local field potential fluctuations which are both oscillatory and non-oscillatory. When one of the large cells happens to dominate the record (or a few units, well synchronized), the broad spikes are likely to be quite periodic, with a slowly shifting frequency; the great energy in the afterpotentials add a large component to the power spectrum in the < 3 Hz bands. When the recording locus avoids such units, as in most of the records analyzed here, it is usual to observe no oscillation standing out from the wideband activity. Peaks in the power spectra are usually not in a consistent position (frequency) in successive spectra. But interesting exceptions will be reported here. Electrical stimulation evokes in these ganglia slow waves with frequency components comparable to delta, theta, alpha, beta and gamma bands of mammalian EEG, that is energy throughout a broad range from < 2 Hz to > 30 Hz, though not consistently peaked at fixed frequencies.
Studies with a variety of species (snail, fish, cat and human) have compared the similar frequency components of stimulus-induced brain electrical activities, to look for shared basic aspects of information processing in the brain (Ba-ar et al. 1999; Bullock and Ba-ar 1988; Sturbeck 1988; Ba-ar-Eroglu and Ba-ar 1991; Bullock 1992; Schuett and Ba-ar 1992; Schuett et al. 1999).
The aims of the present study were: first, to test the hypothesis that different odorants can elicit distinctive changes in the ongoing electrical activity of populations of cells; second, to relate the changes to behavior in an attempt to find a candidate odor-encoding mechanism. We apply the technique of extracellular recording using semimicroelectrodes to measure population responses of the Helix procerebral lobe and the visceral ganglion as field potentials. The analytical procedure is based on frequency analysis and allows detection of subtle changes of amplitudes of frequency components. This study consists of three parts. First, we characterized the patterns of odor-elicited changes in the procerebrum (PC). Second, we repeated the same in the visceral ganglion (VG). Third, to elucidate the behavioral relevance of these induced activity patterns, we determined degree of aversiveness for each stimulant in active snails.

Materials and Methods

Top Summary Introduction Methods and Materials Results Discussion References

Preparation

The preparation of the isolated whole central nervous system with the intact antennal sense organs was removed from 15-30 g Helix pomatia (Dealer: Exoterra, Deringen, Germany). The animals were anesthetized by immersing in crushed ice for 40 min, after which the head and foot part was quickly separated from the rest of the body. The entire central nervous system was then isolated together with the superior tentacles and the olfactory nerves. The whole cerebral ganglia including the PC lobe were kept intact, but the VG was desheathed. The whole preparation was then transferred to the experimental chamber and fixed by holding the subesophageal ring lightly by a fine pin stuck in the silicone rubber bottom. The chamber contained 0.5 ml of a modified snail saline (Witte, et al. 1985)(130 mM NaCl, 4.5 mM KCl and 9 mM CaCl2, buffered with 5 mM HEPES-Na and adjusted to pH 7.5 with HCl) and was kept at 19(1oC. The preparation was immersed in saline except the receptor surface of one tentacle ipsilateral to the recording site.

Recording

For recording, two stainless steel semimicroelectrodes (Rhodes Medical Instruments SNE-300) with a shaft diameter of 100 m (impedance < 100 kohm at 1000 Hz) were used. The electrodes were both varnished to the tip and the recording was carried out against a distant electrode in the bath. For PC, the recording electrode was positioned directly on top of the sheath, away from the entrance of antennal nerves. For the visceral ganglion, the electrode was placed on the desheathed surface, in the central to lower part. The electrode was placed on the surface carefully avoiding any position where it recorded activity dominated by one or a few large unit spikes. These large unit spikes may respond to an adequate stimulus by large and long lasting afterpotentials in both directions (afterdepolarization and afterhyperpolarization) having a significant power and frequency components going down to < 1 Hz. An important caveat is that we do not have any assurance in this molluscan preparation that the potentials all come from neurons; tissue near the electrodes may include smooth muscle and connective tissue whose possible contribution, especially to slow potentials, cannot presently be assessed. The activity was constantly monitored on a digital oscilloscope.

Data processing

For data acquisition and analysis, we used a software package specially developed by BrainData( (Luebeck, Germany).
After wide-band filtering at 0.1-100 Hz, the analog signals, 18000-36000 times amplified, were continuously digitized at 200 Hz in epochs of 2048 samples (10.240 sec). For each experimental condition, 20 epochs = 204.8 sec were recorded without interval between epochs. The digitized data were stored in a computer and subsequently transferred to an optical disc for off-line data processing. Data analysis, performed off-line, used another computer, and included power spectra (0.1 Hz resolution) for single epochs to observe changes of transient activities and the (Frequency-Amplitude-Plot (FAP)(, G(j(), of the averaged signals based on all 20 epochs.

Frequency-Amplitude-Plot (FAP)

A power spectrum can be applied as an analytical tool for a system which fluctuates, such as the EEG or ganglionic activities. When odorants are administered to the sense organs, the ongoing field potentials of the snail ganglia change patterns and these can be characterized in frequency and amplitude.
We used the (Method of Transient Response Analysis( (Frequency-Amplitude-Characteristics measurement) to characterize these transient responses in frequency and amplitude (Ba-ar 1980; 1999a).
The frequency-amplitude-characteristics of a fluctuating system can be described by the following equation. We call the resulting plot, which depicts each frequency and its amount of activity as relative amplitude, the (Frequency-Amplitude-Plot((FAP).

where x(t) = the time history of the pattern to be analysed, G(j() = complex representation of the Fourier-transformed time series, ( = 2(f , the angular frequency, f = frequency of the input signal, and , the imaginary unit.FAP is like a filter which, if applied to white noise, would yield the observed power spectrum. FAP attempts to emphasize the relative heights of peaks in each sample de-emphasizing their absolute power by normalizing to the power of the lowest frequency passed by our filter. We do not claim this value has a unique comparability across samples of activity and therefore, the zero of the ordinate is arbitrary and fluctuates, relative to all other frequencies, depending on the amount of very slow potential shift (0.1 Hz and, with some attenuation, lower frequencies) at that time.
In an attempt to define the properties of the seemingly quasi-oscillations of the snail ganglia, we applied this method of FAP measurement. For this purpose we used a spectral averaging method (averaging in the frequency domain): We first computed Frequency Characteristic of each epoch (10.24 sec) and then the average of all 20 epochs (=204.8 sec) as average FAP. To determine the peak power frequency, at which power increase was largest, we subtracted the average FAP of the control from that of the response, manually plotted the difference and estimated the frequency, at which the power increase was largest. When the increase was strong, the peak power frequency matched that of the ongoing activity during odor exposure.
The low frequencies, including 0.1 Hz and lower frequencies, that are present even if attenuated by the filter, will be in random phase during the 10 s epoch and so the estimate of DC potential jumps around accordingly. The fluctuating values at the ordinate thus reflect the mean voltage over the 20 ten second epochs. The main effect of the random (DC( is that the position of the zero on our ordinates is (arbitrary( - in the sense that it has no interpretable significance for us and fluctuates by chance between curves or figures. The averaging starting at essentially random times obviously attenuates higher frequencies faster than lower frequencies.
We also plot power spectra of 20 individual epochs, 10.24 sec each, for each trial, study the time evolution of the spectral pattern, visually estimate the affected frequency range as well as the peak power and compare them with those detected in the corresponding FAP computed from the average of all the 20 trials (204.8 sec).

RMS-voltage

The time signals were also digitally filtered in different frequency bands. The pass-bands of 0.5 - 15 Hz or 0.1-15 Hz were arbitrarily chosen for the evaluation of Root-Mean-Square (RMS)-voltage ( V), since olfactory response occurs mainly in the range < 15 Hz. An additional pass-band of 15-50 Hz was also applied to determine RMS-voltage of the high frequency component of VG. Root-mean-square (RMS)-voltage ( V) of the filtered signals of each epoch, XRMS,



and the mean RMS-voltage of all 20 epochs were then computed. Fourier transform and digital filters are as described in Ba-ar (1980).

Odor response

Control activity was recorded just before each series of odor tests.
The odor was applied by placing a piece of filter paper, stuffed into a glass barrel (3-4 mm in diameter) and lightly soaked with the odorant, 1 to 2 mm away from the neuroepithelium. A sample of 20 epochs (=204.8 s) was recorded every 5 min starting immediately. The stimulus was then removed and two to three additional recordings were made. In some cases recordings were continued for some time to observe the changes much longer. Odorants were administered at least at four different concentrations (from just above threshhold to submaximal) to show that odor intensity was not so strong as to cause nociceptive components of response. (For all odorants, the effects of maximal intensities were also investigated for the purpose of comparison.) The intensities of odorants administered were: ethanol (99.8%):undiluted to 1:32; 2-butanol: undiluted to 1:64; 2-pentanol: undiluted to 1:64; formic acid: undiluted to 1:64; ammonia: 1% to 0.01%. A recovery time of 10-15 min (or till the spontaneous discharge seemed to have returned to normal) was allowed between trials.

Degree of aversion

To estimate the degree of aversion, we tested the odorants described above on a number of active snails, which were later used in the in vitro experiments.
First, as the parameter for degree of aversion, the distance between the superior tentacles and the odorant, at which the tentacles were quickly withdrawn, was estimated. Formic acid, 2-pentanol, 2-butanol, ethanol (99.8%), onion juice and apple juice were applied without dilution. For ammonia we chose 1% solution. The speed, at which the odor source was manually moved from a distance, was kept at approximately 3-4 cm/sec. We observed by eye when the tentacles withdrew and where the source was at that moment. Of course, a latent period of unknown length probably varies with substance and concentration, so the distance was actually greater when the snail sensed the average stimulus. We allowed a few minutes of rest between the trials.
Second, we measured latency in terms of visible withdrawal of the tentacles as the parameter of aversion to examine whether this parameter was related to that estimated in distance. An odor source, a piece of filter paper soaked with an odorant, was shielded in a microtube and placed ca. 1 cm from the tentacle. The shielding lid was quickly opened and the latency was determined. The chemicals were undiluted except ammonia which was at 1%. Several trials were made for each odorant with two of the active snails described above. An interval of 5 min or longer was allowed between trials.

Statistical evaluation

To give confidence in the results, we calculated 95% confidence limits for the average according to (Student( (Youden 1964).

Results

Top Summary Introduction Methods and Materials Results Discussion References

Description of activity

We consider that the boundary between (regular( and (irregular( fluctuation is arbitrary and varies according to the frame of reference. In our usage variation of period less than ca. .5 of an octave justifies the term "oscillation". We point out that according to this definition the snail activities are mostly non-oscillatory ( Figs. 1a,b; Figs. 2a,b; Fig. 3a,b). In the present study we avoided such recording sites where large, rhythmic spike-like discharges were conspicuous. The type of activity observed in the PC lobe and VG may be called a quasi-oscillation with a whole octave of fluctuation. To control any noise from the recording system, we also measured (bath controls( with one electrode on an inactive preparation and another in bath fluid. RMS-voltages obtained on four different days were 1.4 - 1.8 V in the 0.5-15 Hz band and < 1.0 V in the 15 - 30 Hz range.The intrinsic PC and VG activities were normally higher than the bath controls.
When odorant stimulation was applied to the sense organ, the activity pattern of the PC or VG was distinctively modulated in frequency and amplitude both in PC and VG. We define the change from control as the ganglionic (response(. This often took place as intermittent, strong spike-like discharges and we define this type of high activity as (bursts(.
In an attempt to characterize these activities, we recorded the responses of the ganglia to different odorants and analyzed them in various parameters. As stimulants, we applied five chemicals of different properties and, in case of PC, additionally two natural odorants, onion and apple.The results are summarized in Tables 1 and 2. We point out notable features of the activities in the following.

Procerebrum

Activity in the absence of odor
The PC lobe showed intrinsic FP fluctuations mainly in the low frequency band < 15 Hz. The frequency maxima of controls (the first of a series of experiments made with each of twenty preparations) varied between 0.2 and 1.3 Hz, but mostly between 0.4 and 0.7 Hz (0.54 ( 0.11 Hz, 95% confidence limits). The power decreased with increasing frequency (15 dB/octave). The RMS-voltage of the ongoing activity in the 0.5 - 15 Hz range was most often less than 4 V,
occasionally reaching 7 V.

Odorant-induced activity
Ethanol. As shown in Tables 1 and 3, ethanol evoked in the PC, regardless of concentration, wide-band activity in the 0.1 - 10 Hz range with peak power frequencies at 1.0 - 2.2 Hz (1.31(0.09 Hz , 95% confidence limits). To show consistency, all observations with typical responses are shown together (Fig. 4a). The pattern of the peak power frequencies was virtually not influenced by odor intensity. Notable was that the elevation of the 0.5 - 4 Hz activity was usually accompanied by a suppression of the 0.1 - 0.4 Hz activity (Fig. 1c, Panel 3). A typical example of the response is presented in Figs. 1a-c. Activity increased most strongly between 0.5 and 6 Hz with peak power at 1.5 Hz; another almost equally prominent peak was at 0.7 Hz (Fig.1c, Panel 3, 5 min). It remains to be investigated, however, whether or not this frequency is the same as the robust spontaneous oscillation at 0.7 Hz reported in Limax PC (25). Theta-rhythm (5-8 Hz) was elicited 9 min after stimulus onset (Fig. 1b,c, Panels 4).

Fig. 1. Ethanol-induced response of the procerebrum (Preparation No. 88). This is a typical example of the response sequence which we observed in more than 50 % of the trials. (a) Time signals from an experiment, in which 0.5-5 Hz burst activity occurred. In each panel an epoch of 10 sec is shown. From bottom: control (before stimulus); ca. 2 min, ca. 6.5 min and 9 min after stimulus onset. A multi-peaked fluctuation occurred starting around 5 min with dominance around 1.5 Hz and elevation of amplitude. In a few minutes the pattern of activity changed shifting the dominant frequency to < 1 Hz and increasing activity around 6 Hz. (b) The corresponding power spectra of single epochs. From bottom: control (before stimulus), immediately, 5 min, 9 min and 14 min after stimulus onset (stimulus removed at 14 min). Burst activity, occurring in the 0.5-5 Hz range 5 min after stimulus, showed numerous frequency peaks that seemed to change positions in every epoch. The pattern of activity then changed in a few minutes shifting the frequency center to < 1 Hz and at the same time elevating activity around 6 Hz, and finally subsiding altogether. (c) The corresponding average FAPs. The order of presentation is the same as (b). Note that the FAP of the burst activity at 5 min after stimulus depicts 1.5 Hz as the dominant peak and 0.7 Hz as almost equally strong peak. The change of activity 9 min after stimulus onset was here again visible as the shift of dominance to < 1 Hz.

Fig. 2. Ethanol-induced response of the visceral ganglion. The same preparation (No. 88) as Fig. 1. This is a typical response sequence which we observed in more than 70% of the trials. (a) Time signals from an experiment where burst oscillation of 1.5 Hz was intermittently elicited. Each panel is an epoch of 10 sec. From bottom: control; (1) 2.5 min, (2) 5 min, (3) 12.5 min after stimulus onset (stimulus was removed at 10 min after stimulus onset); (b) The corresponding power spectra of single epochs. Burst activity with strongest power around 1.5 Hz was elicited in intervals for 15 min and lasted longer than 50 min with frequency shifting to 2 Hz and power decreased; (c) The corresponding average FAPs. Ethanol elevated the 0.6-6 Hz activity peaking around 1.5 Hz most strongly the first 15 min and then a relatively robust 2 Hz activity dominated the following 45 min.

2-Butanol. This higher alcohol induced a different response in the PC compared with ethanol and elevated activity mainly in the frequency range < 8 Hz (occasionally reaching 10-15 Hz) with the maximal peak at (0.7 Hz (0.67(0.03 Hz, 95% confidence limits) at all concentrations and in all preparations (Tables 1and 4.). As with ethanol, diluted butanol seemed to cause a decrease of amplitude in some cases.
2-pentanol (amyl alcohol). PC responded to this odorant with elevation of a lower frequency range compared with either ethanol or 2-butanol, i. e., < 4 Hz with power maximum at (0.5 Hz (0.48(0.04 Hz, 95% confidence limits; Tables 1 and 4). Amyl alcohol induced fluctuations at all concentrations and in all preparations.
Formic acid. The frequency range of the induced activity lay below 5 Hz with peak power frequencies at 0.3-0.5 Hz (0.36 ( 0.03 Hz, 95% confidence limits) which seemed to be independent of the stimulus concentration (Fig. 4b and Table 4). Typical records of the response are shown in Fig. 3a. Note that a slow fluctuation occurred starting at 1 min after stimulus onset bursting strongly at 10 min. The early response of PC to formic acid was most evident in the increase of power in the lower frequency range (< 0.7 Hz) with the peak power at 0.4 Hz (Figs. 3a-c, Panels 2). The later response burst (Fig. 3a-c, Panels 3) reached 10 Hz by its inctrease of power, but the strongest increase took place in the range < 1.0 Hz with maximal frequency at the same 0.4 Hz (Fig. 3c, Panel 3).

Fig. 3. Formic acid-induced response of the procerebrum. (a) Typical time signal of an epoch (10 sec.) From bottom: control; 1 min, 10 min and 15 min after stimulus onset. (b) The corresponding power spectra of single epochs. Burst activity with many sharp peaks occurred intermittently. (c) The corresponding average FAPs. Elevation of 0.4 Hz activity was clearly visible in the response.

Fig. 4. Induced field potential activities of the procerebrum at different odorant intensities. (a) Ethanol-induced response: the affected frequency range of an observation and its peak power frequency (( 1 Hz), marked on the horizontal line. In about 33% of observations, elevation of activity occurred at > 0.5 Hz; (b) Formic acid-induced response. Elevated activity went down to 0.1 Hz without exception, which was different from that of ethanol. Note that induced activities seldom reached beyond 15 Hz in both cases and that in 56% of ethanol-induced activities and in 24% of formic acid-induced activities the frequency range extended beyond 5 Hz.

Ammonia. This chemical, found in nature as a metabolic product, induced an activity which was conspicuous in the following points. a) The frequency range of the response varied widely from < 0.7 Hz to < 25 Hz depending on the preparation and was, without exception, characterized by the maximal peak at 0.2 ( < 0.02 Hz. b) Latency was always very short. c) At all concentrations the induced 0.2 Hz activity decreased within 20 to 30 seconds. But in spite of the adaptation, the response activity in the other frequency range lasted longer than 10 min
Onion. In all preparations procerebral response occurred immediately, but largely in frequency. When freshly obtained onion juice was applied to the tentacle, activity below 1 Hz was enhanced with average FAPs depicting elevation of power between 0.2 and 0.6 Hz (0.36 ( 0.14 Hz, 95% confidence limits; Tables 1 and 4). It is noteworthy that this onion-induced peak power frequency was very similar to that of formic acid, though the former was less aversive than the latter (Table 3).
Apple. This fruit is strongly favoured by the snail as food and stimulation with the fresh juice accordingly induced different response from onion (Tables 1, 3 and 4).: immediate elevation of activity took place mainly in the 0.3-4 Hz band with the peak power frequencies varying between 0.9 and 1.3 Hz (1.10 ( 0.25 Hz, 95% confidence limits). Both apple and ethanol (( 25%), attractive to the snail (cf. Locomotion behavior), notably had peak power frequencies > 1 Hz.

Visceral ganglion

Activity in the absence of odorIntrinsic activity of VG was more spiky (Fig. 2a, bottom) than PC (Fig. 1a, bottom). It depended on the preparation and exact placement of the electrodes, but the activity was most often with a moderate amount of spiking (a power peak below 10 Hz) and, occasionally with a high amount of bursts (one peak at < 50 Hz and another between 50 and 150 Hz) (Schuett et al., 1992; Schuett and Ba-ar, 1992). Under the present digitization, the power of the activity of VG extended to at least up to 50 Hz and was higher than that of the PC lobe. This was also evident in the RMS-voltages: in the 0.5-15 Hz band, RMS-voltage of VG was 2.6 - 9.1 V (that of PC was 1.5 - 7.0 V); in the 15 - 50 Hz band, RMS-voltage of VG was 2.7-8.1 V (that of PC was 0.7-1.0 V).

Odorant-induced activity
VG controls the digestive as well as sexual organs and is certainly expected to be involved in olfactory information processing. Although the neuronal pathway from PC to VG is not known, odor input markedly altered activity. The responses of the VG shared similarity with those of PC in frequency. The results are summarized in Table 2. We state some notable features of the responses in the following.

Ethanol. Olfactory stimulation with ethanol evoked strong FP fluctuations which were characterized by frequency peaking at 1.0 - 2.3 Hz (1.60(0.08 Hz, 95% confidence limits; Tables 2 and 4). Typical records from one experiment are shown in Fig. 2a. Ethanol elicited burst activity enhancing nearly the same frequency component as that in PC lobe of the same preparation (cf. Figs. 1a-c and Figs.2a-c), but with higher power at ( 2 Hz. These intermittent bursts some minutes apart are largely due to quite regular spike discharges of a single unit or a synchronized group of them. Any periodicity in the response was not maintained for long. The typical voltage vs. time records of the response (Fig. 2a, Panels 2-4) also clearly depict these frequency components. It is noteworthy that the (2 Hz activity occurred intermittently for as long as 52 min in this particular preparation decreasing its power with time. Interestingly, in VG, this induced ( 2 Hz fluctuation lasted long without shifting the frequency to below 1 Hz. On the contrary, in PC, the ethanol-induced activity either diminished after 10-15 min or shifted the frequency center to < 1 Hz.
2-Butanol. The responses induced in VG by this higher alcohol were not so conspicuous as in PC, differing in the following respects. i)The stronger the intensity, the higher the frequency range extended to. ii) The peak power frequencies of response were not so strongly consistent as in PC, fluctuating slightly between 0.3 and 0.9 Hz (0.65(0.07 Hz, 95% confidence limits; Table 4). iii) Response in amplitude hardly depicted a possible dose dependency, such as observed in PC.
2-Pentanol (amyl alcohol). As observed with ethanol or 2-butanol, the stronger the stimulus intensities (undiluted and 1:8), the higher the frequency range of the induced activities. The peak power frequencies of the response activities were 0.4-0.7 Hz (0.43(0.08 Hz, 95% confidence limits; Table 4). Response in amplitude appeared to be less conspicuous in VG compared with PC.
Formic acid. Spectral analyses depicted responses with peak power mainly at 0.4 Hz, but occasionally at 1.5 - 2.5 Hz. The response had smaller increase of the < 0.5 Hz component compared with that of PC and varied more intra- and inter-individually. The immediate response took place mainly in alteration of frequency and did not appear to be correlated with odorant intensities. The induced activity with maximal peak at 0.4 Hz, for instance, lasted at least for 5 min and sometimes longer than 20 min (Table 2).
Ammonia. This odorant induced strong responses in VG and their patterns were partly similar to those in PC. Elevation of power occurred over a wide frequency range extending from 0.1 up to at least 50 Hz, but most strongly < 1 Hz. The most prominent frequency of the response was 0.2 ( < 0.02 Hz (Table 4). The response occurred always immediately after stimulus onset. Interestingly, the 0.2 Hz activity of VG lasted much longer (5-10 min) than that of PC (20 - 30 sec) although the other frequency components lasted much longer.
We may conclude from these findings: a) Each odorant induced, in the low frequency range, characteristic, wideband FP activities in the < 15 Hz band. The peak power frequencies, which lay below 2.5 Hz, seemed to be constant regardless of preparations and intensities and hence may be specific for the odorant. b) Peak power frequencies induced in PC and those induced in VG were either the same or very similar, but the amplitude of the < 15 Hz band was smaller in PC than that in VG.

Behavioral response

Locomotion behavior
To examine attractiveness of etanol and apple, we performed experiments with two active snails by observing locomotion behavior. We presented an active snail a piece of filter paper soaked with 25% ethanol at a distance of 6 cm from the tentacles. The snail steadily crawled towards the odor source and remained, for at least 5 min, at such a position that the extended tentacles were within 1 mm reach of the odorant. This result suggested that the snail was attracted by 25% ethanol. Undiluted ethanol was, however, repellent to the snail to a certain degree: it reacted with the tentacle withdrawal reflex at a distance of 1.0 ( 0.5 cm or with a latency of 6 ( 0.9 sec (Tab. 3). In another similar experiment with a piece of fresh apple, it was shown that the snail was strongly attracted by the fruit moving steadily forward with the tentacles extended and chewed on it for a long time.

Degree of aversion
To see how differently the snail reacts to each odorant, we also estimated the degree of aversion for each odorant, with visible withdrawal of the tentacles as parameter, in two different ways: distance and latency. For this purpose we used a number of active snails that were later submitted to the in vitro experiments. The results are shown in Table 3. The snail senses ammonia (1%) as the most aversive of all odorants tested, withdrawing the tentacles at the longest distance of 8.5 (1.0 cm (confidence limits) or at the shortest latency of < 1 sec and ethanol as the least aversive, at the shortest distance of 1.0 ( 0.5 cm or the longest latency of 6.1 ( 0.9 sec (95% confidence limits). The parameters measured in distance seemed to be linearly related to those in latency. Based on these parameters the order of aversiveness can be described as follows: 1% ammonia > formic acid > 2-pentanol > butanol > ethanol.

A point of some interest, comparing our findings with the paper of Ohloff (1986), is that the order of aversiveness of the five pure chemicals tested here, behaviorally, seems to correspond to that expected from consideration of the molecular properties of these chemicals that lead to adhesion of the molecules to the receptor cell membrane.

Relationship between degree of aversion and odorant-induced frequencyTo examine if there was any correlation between the behavioral valence of an odorant and the odorant-specific peak power frequency, the degree of aversiveness in distance was semilogarithmically plotted against the peak power frequency (Hz) of the induced FP activity in the isolated PC lobe as well as VG (Fig. 5a,b). There was evidently a linear relationship between them. This may suggest that there is some correlation between the most dominant low frequency component of the characteristic FP response and behavior, i. e., the chemical nature of the odorant: the lower the induced peak power frequency, the more aversive the odorant. Furthermore, these most prominent frequencies may be considered to be odor-specific, since they are invariably observed regardless of intensities and preparations.

Fig. 5. Relationship between degree of aversion and frequency of odorant-induced activity. The bars represent 95% confidence limits for the means. Numerical values are also presented in Table 4. Note that there was a linear relationship between degree of aversiveness and peak power frequency of odorant-induced FP activity in the Helix procerebrum and visceral ganglion. This diagram suggests: (a) order of aversiveness appears to reflect that of molecular affinity: the stronger in affinity an odorant, the more aversive it is to the snail; (b) order of affinity is correlated to peak power frequency of induced FP: the stronger in affinity an odorant, the lower the odorant-induced frequency.; (c ) the more aversive an odorant, the lower the peak power frequency; (d) extrapolation of the curve to the abcissa yields a value of ( 2.5 Hz. This is the area for an appetitive odorant (ethanol) for the snail. These curves suggest that the odorant-specific frequencies may, together with other frequency components, be involved in identification, classification and discrimination of odorants or their classes and that the most crutial FP activities relevant for this function may exist below (2.5 Hz.

Discussion

Top Summary Introduction Methods and Materials Results Discussion References

We used semimicroelectrodes for recording electrical activity and analyzed intrinsic as well as odorant-induced fluctuations by power spectra. This approach allowed us to describe and characterize changes of activity in frequency and amplitude, and relate them to specific odorants. We could also correlate these changes to behavior.

Odor-specific responses of the ganglia

Both PC and VG responded to each of the odorants tested here specifically in frequency, but PC also in amplitude (the < 15 Hz band) exhibiting diffuse dose-dependencies. Interestingly, the curve of this dose dependency appeared different for each odorant indicating a distinct sensitivity. This may suggest that, in PC, odor input is processed not only in frequency, but in amplitude as well. Response in amplitude may also be related to odor quality and, in part, to odor intensity. Notably, in VG, no dose-relatedness was observed. It is still to be studied whether or not this is due to weak coupling between PC and VG, as observed between pedal cells and PC (Gelperin and Flores 1997).
A number of studies with invertebrates (Derby and Ache, 1984; Giradot and Derby, 1988; 1990; Gelperin and Tank 1990; Gelperin A 1994; Gelperin et al. 1996; Gelperin et al. 1993; Kimura et al., 1993; Kleinfeld et al. 1994; Kuettner et al. 1995; Laurent and Davidowitz 1994; Schuett and Ba-ar 1994; Cinelli et al. 1995; Gervais et al., 1996; Laurent et al., 1996; MacLeod and Laurent, 1996; Gelperin and Flores 1997) have shown that odor information brings neurons of the olfactory neuronal circuit into increased FP fluctuation by spatio-temporal organization of neuronal assemblies and predicted that this induced/evoked activity may strongly be related to the mechanism of odor encoding in general. Our findings also strongly support this idea evidencing odor-induced frequency patterns that are specific to odorants tested in the present study.

Odor-nonspecific responses of the ganglia

Activities in the >15 Hz were seen regularly in the VG, but only occasionally in PC. In VG, the FPs in this band were enhanced by ethanol and ammonia and, in some experiments, by formic acid and 2-pentanol. In PC undiluted ethanol and dilutions of formic acid and 2-butabol induced fluctuations in this band. The RMS-voltages of, for examples, the 15-30 Hz and 30-50 Hz bands increased and this may suggest that these frequency bands are also involved in processing of odor information. One other important response activity to be mentioned is that of the 3-20 Hz range, especially the activities in the 3-7 Hz band. In this case, a power peak between 3 and 7 Hz, weaker but relatively consistent, appeared over several epochs: in PC mainly by stimulation with ethanol and, in one case, with 2-pentanol and in VG by administration of all five odorants.
When there was a response in the > 15 Hz band, the activity in the 3-15 Hz band also normally increased. Whether or not there is some correlation between these frequencies remains still to be answered. In one preparation we observed a conspicuous fluctuation in the 6-20 Hz band lasting over several epochs with a power maximum at 10 Hz. Interestingly, odorant-nonspecific 7-13 Hz FP oscillations have also been observed in the frog olfactory bulb (Delaney and Hall 1996). These apparently odorant-nonspecific frequencies seem to exist in a variety of species, but the functional meaning of each of these frequencies is not yet known.
Odorant-evoked 20 Hz local field potential oscillations (Laurent and Davidowitz 1994; Delaney and Hall 1996) and 40 Hz- (gamma-) activity (Eckert and Schmidt 1985; Freeman and Skarda 1985; Bressler and Freeman 1980) have been reported, but the nature of these high frequency activities appears to be, more or less, odorant-nonspecific. The gamma-activty, for instance, is evoked in different species, including the Helix, with a variety of stimulus modalities (Ba-ar et al. 1999; Schuett et al. 1999). Interestingly, we observed, in some preparations, similar nonspecific > 15 Hz activities where increases of the RMS-voltages in the 15-30 Hz and 30-50 Hz bands were evident. We also consider these high frequency activities to be involved, together with the other frequencies, in olfactory information processing, as hypothesized by the others.

Other features of the ganglional responses

There are several other features to be noted: a) In many cases the activity first subsided for one to several minutes after stimulus onset over a wide range of frequency with waves or spikes totally disappearing (0.1- > 15 Hz; Figs 1b and 2b, Panel 2) and then became suddenly bursting. This phenomenon may be due to reorganization of cellular activity before coming to a frequency tuning. b) The power often increased with time during stimulation (Figs. 2b-c and 3b-c) and then subsided probably due to adaptation. In some preparations, however, removal of an odor coincided with sudden increase of the potentials in the < 15 Hz band. It is still to be investigated whether the enhancement of the potentials was due to an OFF effect or related to some other function. c) Another interesting aspect is that there was a large difference in the duration of the odor-specific activity of ethanol between PC and VG: In VG, a characteristic bursting occurred intemittently for a long time (Figs. 2b and 2c) while in PC it either subsided in a few minutes or continued shifting the frequency center to < 1 Hz. This intermittent activation of VG at ( 2 Hz, for instance, may be related to specific memory function of this ganglion.

Propagation of activity

Although the recordings from PC and VG were not carried out simultaneously, our findings suggest that the activity patterns evoked in PC apparently propagate to VG. VG is known to control functions of digestive and sexual organs, both of which may be activated by input of attractive or repellent odors. Although the neuronal pathways to VG are still unidentified, cells are known in the ganglion in Helix that respond to chemical stimulation with quinine - e.g. serotonergic giant parietal neurons. The origin of this response is assumed to be in PC cells (Zakharov et al.1995). Since the parietal ganglia have connections to VG, olfactory signals could propagate from PC to VG through the parietal ganglia.
Our most recent experiments with the Helix pedal ganglion (PG) (Schuett, Bullock and Ba-ar 1999) showed that in this center of locomotion odor input evoked responses similar to those observed in VG. The pedal cells with dendrites in the PC lobe are very likely to carry outputs from PC to PG, based on studies in Achatina (Chase and Tolloczko 1989). Our preliminary study with simultaneous recordings from PC and PG showed that responses with the same odorant-specific frequencies were elicited in these ganglia (unpublished data). Further study in this direction would add tests of our hypothesis.
Moreover, it has recently been reported that the spontaneous action potentials of cells in the Limax PG are weakly coupled to the local field potential oscillation in the PC lobe (Gelperin and Froles 1997). The mechanism of the signal transfer from PC to VG or PC to PG that we observed may be explained by such a coupling.

Relation to behavioral valence of odolant

Although our estimates of behavioral valences of the odorants were based on observation by eye and manual movement of odor source, the parameters thus obtained were linearly correlated to the odor-specific frequencies. There seem to be strong correlations among chemical nature of an odorant, odor-specific peak power frequency and behavior. In other words: (a) The stronger the chemical affinity, the more aversive to the snail. (b) The stronger the chemical affinity, the lower the odor-specific frequency. (c) The more aversive the odor is to the snail, the lower the odor-specific frequency of induced FP activity. (d) Sensitivity manifested as rate of RMS-amplitude increase of the low frequency range (<15 Hz) may also be related to odor quality and, in part, to odor concentration. (e) Extrapolation of the curves in Fig. 5 strongly suggests that the behaviorally relevant frequencies may exist exclusively in the low frequency range of < 2.5 Hz, and play significant roles in the mechanism of encoding odor quality.
Our results seemed to agree with the observations made by Kimura and his colleagues (1993) as well as Gervais and his colleagues (1996) who reported that the frequency of local field potentials in the slug's PC lobe was increased by stimulation with an appetitive odor and decreased by an aversive one. However, these authors could not relate the changed frequency patterns to specific odors or to their behavioral valences.

Relevance for comparative studies

The olfactory system of terrestrial molluscs has been described as fundamentally similar to that of vertebrates in its anatomical architecture and may therefore be heuristic for studying olfactory function in general (Chase and Tolloczko 1993). The findings from the present species as a model may possibly be interpreted as representative of some general phenomena of olfactory information processing. Concerning the relevance of the isolated brain, Delaney et al. (1996) demonstrated that there are no differences in odorant induced local field potentials between in vitro and in vivo preparations. Bullock (1945) claimed, for his material and criteria, that (the activity manifested by the completely isolated brain or ganglion is essentially the same as that in the intact animal in the intervals between gross movement and in the absence of obvious stimulation.( Our preparations were equivalent.
Recently, a number of reports on chemosensory evoked or event-related potentials in mammals have appeared (Klemm et al. 1992; Sawada et al. 1992; Van Toller et al. 1993; Brauchli et al. 1995; Hummel et al. 1995; Lorig, et al. 1995; 1996). Some of them report increase of theta and/or alpha activity in EEG during odor application. However, correlation of these olfactory rhythms to specific odors has not yet been established and similarities with the same parts of the spectrum in Helix can not yet be asserted with any confidence. Regarding delta (0.5-3.5 Hz) oscillations induced in the mammalian brain, known are those which are universally evoked by a variety of non-olfactory, cognitive inputs (Ba-ar et al. 1984; Ba-ar-Eroglu et al. 1993; Parnefjord and Ba-ar 1995; Schuermann et al. 1995; Ba-ar et al. 1996; Ba-ar 1998a,b). The possibilities of comparable meanings or mechanisms represent a challenging agenda for comparative studies.

Conclusion

Slow (< 1Hz) spontaneous fluctuations exist in the Helix brain as wideband, nonrhythmic FP activity. Olfactory input modulates these fluctuations presumably bringing neurons to synchronous activities eliciting bursts, with characteristic frequencies and amplitudes possibly specific to certain odors of the limited number of odorants tested here.
The induced activities >5 Hz are probably odorant non-specific. Peak power frequencies induced in PC and those induced in VG are either the same or very similar and this may mean that olfactory signals processed in the PC propagate further to VG.
These odorant-specific frequencies, that are also correlated to behavioral output and exist exclusively in the low frequency range of < 2.5 Hz, may play significant roles in the mechanism of encoding odor quality. These odor-specific low frequencies in combination with the other frequencies may function as identification codes for the odorants or the classes of odors they each represent.

Acknowledgements

We thank Alan Gelperin, Bell Labs Innovations, Lucent Technologies, N. J., U. S. A., for important suggestions in initiating this work, Ronald Chase of McGill University, Montreal, Canada, and David Kleinfeld of University of California, San Diego, Calif., U. S. A., for helpful discussions. The authors also thank Martin Schuermann for valuable discussion, Ferdinand Greitschus for developing softwares, Martin Gehrmann and Gabriele Huck for technical assistance and Gabriela Fletschinger for preparing graphics. This work was supported by DFG grants Ba 831/11-1/2.

References

Top Summary Introduction Methods and Materials Results Discussion References

1. Adrian ED. Olfactory reactions in the brain of the hedgehog. J. Physiol. Lond. 1942;199:459- 473.

2. Balaban PM and Maksimova OA. Positive and negative brain zones in the snail. Eur. J. Neurosci. 1993;5: 768-774.

3. Ba-ar E. EEG-Brain Dynamics. Relation between EEG and brain evoked potentials. Amsterdam: Elsevier, 1980.

4. Ba-ar E. Brain Oscillations: Principles and Approaches. Berlin Heidelberg New York : Springer, 1999.

5. Ba-ar E. Integrative Brain Function: Neurophysiology and Cognitive Processes Based on EEG Oscillations. Berlin Heidelberg New York: Springer, 1999.

6. Ba-ar E, Schuermann M and Ba-ar-Eroglu C. Potentials, rhythmic slow, behavioral correlates. In: Adelman G and Smith B, editors. Encyclopedia of Neuroscience. Boston: Birkh"user , 1996.

7. Ba-ar E, Ba-ar-Eroglu C, Rosen B and Schuett A. A new approach to endogenous event-related potentials in man: Relation between EEG and P300-wave. Intern. J. Neuroscience. 1984; 24: 1-21.

8. Ba-ar-Eroglu C and Ba-ar E. A compound P-300-40 Hz response of the cat hippocampus. Int. J. Neurosci. 1991; 60: 227-237.

9. Ba-ar-Eroglu C, Strueber D, Stadler M, Kruse P and Ba-ar E. Multistable visual perception induces a slow positive wave. Intern. J. Neurosci. 1993; 73: 139-151.

10. Ba-ar E, Schuett A and Bullock TH. Dynamics of potentials from the brain of anamniotes. In Ba-ar E. Brain function and oscillations. Vol. II. Integrative brain Function. Neurophysiology and cognitive processes. Berlin Heidelberg New York: Springer, 1999: 109-116.

11. Brauchli P, Rueegg PB, Etzweiler F and Zeier H. Electrocortical and autonomic alteration by administration of a pleasant and an unpleasant odor. Chem. Senses 1995; 20: 505-515.

12. Bressler SL and Freeman WJ. Frequency analysis of olfactory system EEG in cat, rabbit and rat. Electroencephalogr. Clin. Neurophysiol.1980; 50: 19-24.

13. Bullock TH. Problems in the comparative study of brain waves. Yale J. Biol. & Med. 1945;17: 657-679.

14. Bullock TH. Introduction to induced rhythms: A widespread, heterogeneous class of oscillations. In: Ba-ar E and Bullock TH, editors. Induced rhythms in the brain. Boston, MA: Birkh"user, 1992: 1-26.

15. Bullock TH and Ba-ar E. Comparison of ongoing compound field potentials in the brains of invertebrates andd vertebrates. Brain Research Reviews 1988;13: 57-75.

16. Chase R and Tolloczko B. Interganglionic dendrites constitute an output pathway from the procerebrum of the snail Achatina fulica. J. Comp. Neurol. 1989, 283: 143-152.

17. Chase R and Tolloczko B. Tracing neural pathways in snail olfaction: From the tip of the tentacles to the brain and beyond. Microscopy Research and Technique 1993;24:214-230.

18. Cinelli AR, Hamilton KA and Kauer JS. Salamander olfactory bulb neuronal activity observed by video rate, voltage-sensitive dye imaging. III. Spatial and temporal properties of responses evoked by odorant stimulation. J. Neurophysiol.

19. Derby CD and Ache BW. Quality coding of a complex odorant in an invertebrate. J. Neurophysiol. 1984;51: 906-924.

20. Delaney KR and Hall BJ. An in vitro preparation of frog nose and brain for the study of odour-evoked oscillatory activity. J. Neurosci. Methods 1996;68: 193-202.

21. Duchamp-Viret P, Duchamp A and Vigouroux M. Temporal aspects of information processing in the first two stages of the frog olfactory system; influence of stimulus intensity. Chem. Senses 1990;15: 349-365.

22. Eckert M and Schmidt U. The influence of permanent odor stimuli on the postnatal development of neural activity in the olfactory bulbs of laboratory mice. Dev. Brain Res. 1985;20: 185-190.

23. Evans WJ, Cui L and Starr A. Olfactory event-related potentials in normal human subjects: effects of age and gender. Electroencephalogr. Clin. Neurophysiol. 1995;95: 293-301.

24. Freeman WJ.: Mass Action in the Nervous System. New York: Academic, 1975.

25. Freeman WJ and Skarda CA. Spatial EEG patterns, non-linear dynamics and perception: the neo-Sherringtonian view. Brain Research Reviews 1985;10: 147-175.

26. Gelperin A. Nitric oxide mediates network oscillations of olfactory interneurons in a terrestrial mollusc. Nature 1994; 369: 61-63.

27. Gelperin A, Kleinfeld D, Denk W and Cooke RC. Oscillations and gaseous oxides in invertebrate olfaction. J. Neurobiol. 1996; 30: 110-122.

28. Gelperin A, Rhines LD, Flores J and Tank DW. Coherent network oscillations by olfactory interneurons: Modulation by endogenous amines. J. Neurophysiol. 1993;69: 1930-1939.

29. Gelperin A and Flores J. Vital staining from dye-coated microprobes identifies new olfactory interneurons for optical and electrical recording. J. Neurosci. Methods. 1997;72: 97-108.

30. Gelperin A and Tank DW. Odour-modulated collective network oscillations of olfactory interneurons in a terrestrial mollusc. Nature Lond. 1990;435: 437-440.

31. Gervais R, Kleinfeld D, Delaney KR and Gelperin A. Central and reflex neuronal responses elicited by odor in a terrestrial mollusc. J. Neurophysiol. 1996;76: 1327- 1339.

32. Girardot MN and Derby CD. Neural coding of quality of complex olfactory stimuli in lobsters. J. Neurophysiol. 1988;60: 303-324.

33. Girardot MN and Derby CD. Independent components of the neural population response for discrimination of quality and intensity of chemical stimuli. Brain Behav. Evol. 1990;35: 129-145.

34. Hummel T, Pauli E, Schuler P, Kettermann B, Stefan H and Kobal G. Chemosensory event-related potentials in patients with temporal lobe epilepsy. Epilepsia 1995;36: 79-85.

35. Kimura T, Suzuki B, Yamada A, Sekiguchi T and Mizukami A. Response of oscillatory field potential to some conditioned odors in slug's brain. Zool. Sci. 1993;9: 1241.

36. Kleinfeld D, Delaney KR, Fee MS, Flores JA, Tank DW and Gelperin A. Dynamics of propagating waves in the olfactory network of a terrestrial mollusk: an electrical and optical study. J. Neurophysiol. 1994;72: 1402-1419.

37. Klemm WR, Lutes SD, Hendrix DV and Warrenburg S. Topographical EEG maps of human responses to odors. Chem. Senses 1992;17: 347-361.

38. Kobal G and Hummel C. Cerebral chemosensory evoked potentials elicited by chemical stimulation of the human olfactory and respiratory nasal mucosa. Electroencephalogr. Clin. Neurophysiol. 1988;71: 241-50.

39. Kuettner A, Joerges J and Menzel R. Optical imaging studies of olfactory coding in the honeybee's antennal lobes. Soc. Neurosci. Abstr.1995; 21: 135.

40. Laurent G and Davidowitz H. Encoding of olfactory information with oscillating neural assemblies. Science 1994;265: 1872-1875.

41. Laurent G., Wehr M. and Davidowitz H. Temporal representations of odors in an olfactory network. J. Neurosci. 1996;16: 3837-3847.

42. Lorig TS, Huffman E, DeMartino A and DeMarco J. The effects of low concentration odors on EEG activity and behavior. J. Psychol. 1991;5: 69-77.

43. Lorig TS, Turner JM, Matia DC and Warrenburg S. The contingent negative variation in an odor labeling paradigm. Psychophysiology 1995;32: 393-398.

44. Lorig TS, Matia DC, Peszka J and Bryant DN. The effects of active and passive stimulation on chemosensory event-related potentials. Int. J. Psychophysiol. 1996;23: 199-205.

45. MacLeod K and Laurent G. Distinct mechanisms for synchronization and temporal patterning of odor-encoding neural assemblies. Science. 1996;274: 976-979.

46. Mellon DeF. Characterization of oscillatory interneurons in the procerebrum of the crayfish. J. exp. Biol. 1992;167: 15-38.
47. Ohloff G. Chemistry of odor stimuli. Experientia 1986; 42: 271.

48. Parnefjord R and Ba-ar E. Delta oscillations as a correlate to acoustical perception at the auditiry threshhold. Soc. Proc. Electroenceph. clin. Neurophysiol. 1995;94: 44.

49. Sawada K, Koyama E, Kubota M, Hayashi I, Komaki R, Inui M and Torii S. Effects of odors on EEG relaxation and alpha power. Chem. Senses 1992;17: JASTS XXV Abstracts 88.

50. Schuermann M, Ba-ar-Eroglu C, Kolev V and Ba-ar E. A new metric for analyzing single-trial event-related potentials (ERPs): Application to human visual P300 delta response. Neuroscience Letters 1995;197: 167-170.

51. Schuett A and Ba-ar E. The effects of acetylcholine, dopamine and noradrenaline on the visceral ganglion of Helix pomatia - II. Stimulus-evoked field potentials. Comp. Biochem. Physiol. 1992;102C: 169-176.

52. Schuett A and Ba-ar E. Olfactory field potential oscillations in the isolated Helix brain: different odors induce different rhythmicities. Proceedings of the 39th Annual Meeting of the German Electroencephalography Society 1994;148.

53. Schuett A, Ba-ar E and Bullock TH. The effects of acetylcholine, dopamine and noradrenaline on the visceral ganglion of Helix pomatia - I. Ongoing compound field potentials of low frequencies. Comp. Biochem. Physiol. 1992;102C: 159-168.

54. Schuett A, Bullock TH and Ba-ar E. Dynamics of potentials from invertebrate brains. In: Ba-ar E. Brain function and oscillations. Vol. II. Integrative brain function. Neurophysiology and cognitive processes. Berlin Heidelberg New York: Springer, 1999: 91-108.

55. Schuett A, Bullock TH and Ba-ar E. Odorant-evoked field potentials of the Helix pedal ganglion are correlated to behavior. G"ttingen Conference of the German Neuroscience Society, May 1999.

56. Sturbeck K. Vergleichende Analyse evozierter Potentiale von Invertebraten und Vertebraten. Dissertation, Medical University Luebeck, 1988.

57. Suzuki N. Behavioral and electrical responses of the land snail, Ezohelix flexibilis (Fulton), to odours. J. Faculty of Science Hokkaido Universiy 1967;16: 174-185.

58. Tank DW, Gelperin A and Kleinfeld D. Odors, oscillations, and waves: Does it all compute? Science 1994;265: 1819-1820.

59. Van Toller S, Behan J, Howells P, Kendal-Reed M and Richardson A. An analysis of spontaneous human cortical EEG activity to odours. Chem. Senses 1993;18: 1-16.

60. Witte OW, Speckmann E.-J and Walden J. Acetylcholine responses of identified neurons in Helix pomatia - II. Pharmacological properties of acetylcholine responses. Comp. Biochem. Physiol. 1985;80C: 25-35.

61. Youden WJ. Statistical Methods for Chemists. New York: John Wiley & Sons, Inc., 1964 : 18-20.

62. Zakharov IS, Ierusalimsky VN and Balaban PM. Pedal serotonergic neurons modulate the synaptic input of withdrawal interneurons of Helix. Invertebrate Neuroscience 1995;1: 41-52.

63. Zatorre RJ, Jones-Gotman M, Evans AC and Meyer E. Functional localization and lateralization of human olfactory cortex. Nature 1992;360: 339-340.