Somatic evoked high-frequency magnetic oscillations reflect activity of inhibitory interneurons in the human somatosensory cortex

ELSEVIER

Electroencephalography and clinical Neurophysiology 100 (1996) 189-203

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Somatic evoked high-frequency magnetic oscillations reflect activity of inhibitory interneurons in the human somatosensory cortex Isao Hashimoto a,,, Takunori Mashiko b, Toshiaki Imada b a Department of Psychophysiology, Tokyo Institute of Psychiatry, 2-1-8 Kamikitazawa, Setagaya-ku, Tokyo 156, Japan b Information Science Research Laboratory, NTT Basic Research Laboratories, Nippon Telegraph and Telephone Corporation, Atugi-shi, Kanagawa 243, Japan Accepted for publication: 27 October 1995

Abstract

High-frequency potential oscillations in the range of 300-900 Hz have recently been shown to concur with the primary response (N20) of the somatosensory cortex in awake humans. However, the physiological mechanisms of the high-frequency oscillations remained undetermined. We addressed the issue by analyzing magnetic fields during wakefulness and sleep over the left hemisphere to right median nerve stimulation with a wide bandpass (0.1-2000 Hz) recording with subsequent high-pass (> 300 Hz) and low-pass (< 300 Hz) filtering. With wide bandpass recordings, high-frequency magnetic oscillations with the main signal energy at 580-780 Hz were superimposed on the N20m during wakefulness. Isofield mapping at each peak of the high-pass filtered and isolated high-frequency oscillations showed a dipolar pattern and the estimated source for these peaks was the primary somatosensory cortex (area 3b) very close to that for the N20m peak. During sleep, the high-frequency oscillations showed dramatic diminution in amplitude while the N20m amplitude exhibited a moderate increment. This reciprocal relation between the high-frequency oscillations and the N20m during a wake-sleep cycle suggests that they represent different generator substrates. We speculate that the high-frequency oscillations represent a localized activity of the GABAergic inhibitory interneurons of layer 4, which have been shown in animal experiments to respond monosynaptically to thalamo-cortical input with a high-frequency (600-900 Hz) burst of short duration spikes. On the other hand, the underlying N20m represents activity of pyramidal neurons which receive monosynaptic excitatory input from the thalamus as well as a feed-forward inhibition from the interneurons. Keywords: Somatosensory cortex; High-frequency magnetic oscillations; Primary response (N20m); GABAergic inhibitory intemeurons; Pyramidal neurons; Wake-sleep cycle

1. Introduction

Previous studies of somatic evoked potentials (SEPs) have disclosed several brief inflections superimposed mainly on the ascending slope of the N20 primary response following stimulation of the median nerve (Cracco and Cracco, 1976; Abbruzzese et al., 1978; Maccabee et al., 1983; Eisen et al., 1984). Because these inflections are of much higher frequencies (more than 200 Hz) as compared with the N20 peak (approx. 30-50 Hz) having a duration of 10-15 msec, it has been considered that the high-frequency oscillations represent a different generator substrate from that of the N20 which is generated by

* Corresponding author. Tel.: + 81 3 33045701; Fax: + 81 3 33049396.

postsynaptic potentials of the pyramidal neurons in the 3b somatosensory cortex. In more recent work, high-frequency oscillations have been shown to change dramatically during a waking-sleeping cycle in spite of relative resilience of the underlying N20 (Emerson et al., 1988; Yamada et al., 1988). Furthermore, from differential recovery functions of the individual high-frequency peaks, Emori et al. (1991) speculated that they are generated cortically within a polysynaptic network and at least 1 synapse is interposed between the neighboring peaks. However, the precise location of high-frequency oscillations could not be determined in these previous studies. Curio et al. (1994) first reported magnetic recordings of high-frequency oscillations superimposed on N20m and, on the basis of a relatively constant amplitude ratio of high-frequency oscillations to N20m across the sensor

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1. Hashimoto et a l . / Electroencephalography and clinical Neurophysiology 100 (1996) 189-203

arrays, suggested a similar field distribution for the 2 components. They speculated that the high-frequency oscillations are of heterogeneous origin with contributions from presynaptic action potentials as well as postsynaptic potentials of different populations of cortical neurons. This paper attempts to elucidate the generator mechanisms of the high-frequency oscillations by analyzing the magnetic fields from over 49 locations on the left hemisphere following electric stimulation of the right median nerve in humans during waking and sleep. Based on the evidence presented here, we propose that the high-frequency oscillations represent activity of GABAergic inhibitory interneurons of layer 4 of the 3b somatosensory cortex which constitute 1 of the 2 important neural elements within the human cerebral cortex (McCormick, 1989; Jones, 1993).

2. Materials and methods The experiments were conducted on 11 healthy students, 7 females and 4 males between the ages of 20 and 32 years, in the magnetically shielded room of the Basic Research Laboratories of the Nippon Telegraph and Telephone Corporation (N'IT). Ten subjects were studied during wakefulness and the subject's state of arousal was continuously monitored with on-going magnetoencephalogram (MEG). The data were taken from a fairly uniform MEG pattern; data collection was terminated during drowsiness or sleep. Seven subjects were tested during natural sleep after staying up overnight on the previous day. No sedation was used. Background MEG was continuously monitored and the data were collected during NREM sleep stages 2-4 (Rechtschaffen and Kales, 1968). Six subjects participated in the experiments during both wakefulness and sleep on a separate day. Brief electrical stimuli with a 0.2 msec duration were delivered to the right median nerve at the wrist (cathode proximal). The stimulus intensity was about 3 times sensory threshold and elicited a mild twitch of the abductor pollicis brevis muscle. The stimuli were delivered at regular intervals with a repetition rate of 4 Hz. Magnetic recordings (bandpass 0.1-2000 Hz) were taken sequentially from 49 positions or more over the left hemisphere with two 7-channel SQUID gradiometer systems (BTi Model 607). The detection coils of the gradiometer are arranged in a hexagonal array on a spherical surface with a radius of 16 cm and the distance between the centers of 2 adjacent coils is 2.2 cm; each coil measures 1.8 cm in diameter. The sensors are configured as second-order axial gradiometers with a baseline of 4 cm. An epoch of 50 msec duration (10 msec pre and 40 msec post stimulus) was digitized at a 5 kHz/channel sampling rate and 5000 responses were averaged off-line. For separation and isolation of the high-frequency oscillations from the underlying N20m, the wide-band (0.1-2000

Hz) recorded responses were digitally high-pass ( > 300 Hz) and low-pass ( < 300 Hz) filtered. For the highfrequency oscillations, the data at the maxima (the highest flux leaving the head) or minima (the highest flux entering the head) with an amplitude of twice or more that of the baseline noise level were considered as the signal and used for further analysis, The noise level was measured between 5 and 15 msec after the stimulus and prior to the onset of N20m. A 3-dimensional head coordinate system was measured for each subject using a 3-dimension digitizer (the BTi sensor position indicator system), and the location and orientation of the detection coils with respect to this coordinate system were stored prior to each measurement. The cartesian coordinate system was anchored on 3 fiducial points, 2 preauricular points and the nasion, on each subject's head. The line connecting the preauricular points served as the medial-left lateral or y axis and the line perpendicular to it and passing through the nasion as the postero-anterior or x axis. The third line, perpendicular to the x-y plane passing through the x-y origin and exiting near Cz served as the vertical or z axis. Magnetic resonance images (MRI) of 11 subjects were acquired for 3 planes (axial, coronal and sagittal) with a 0.5 T clinical MR imaging system (Toshiba). In order to define the same coordinate system for MRI as that for MEG measurement, the same 3 fiducial points, marked with vitamin pills having a 5 mm diameter, were used such that the estimated magnetic source locations could be projected on to the appropriate points on the MRI slices of the individual subjects. Isocontour maps of field strength for high-frequency oscillations were produced at 0.2 msec intervals using a 2-dimensional cubic interpolation. Source localization and signal strength at each peak of the oscillations were achieved by fitting of the theoretical field produced by a tangential current dipole source to the observed data using an iterative least squares minimization algorithm based on the Marquardt method. Source location and signal strength for the low-pass filtered N20m at the same points in time with those of high-frequency peaks were calculated for comparison. The adequacy of the dipole model was assessed by the dipolarity (d), the degree to which the theoretical fields could account for the measured data, where d = [1 - (Bm - Bt)2/Bm2]l/2 × 102 (Bt: theoretical fields, Bm: measured fields). The data with a dipolarity of more than 80% were accepted for further analysis. The statistical differences of localization and dipole strength of the equivalent sources between the highfrequency peaks and the underlying N20m at the same latencies were evaluated by means of paired t tests. Peak latency and amplitude differences of the N20m, and the amplitude differences of the high-frequency peaks between wakefulness and sleep were investigated by means of 2-sample t tests. The level of probability selected as significant was a value of P < 0.05 (2-tailed test).

1. Hashimoto et al./ Electroencephalography and clinical Neurophysiology 100 (1996) 189-203 3. Results

3.1. Somatosensory evoked fields during wakefulness The magnetic signals from the somatosensory cortex consisted of high amplitude N20m and P27m within 40 msec after median nerve stimulation. Superimposed upon the N20m, several small inflections could be recognized in the unfiltered original somatosensory evoked field (SEF) records. After high-pass filtering of the original records, these small inflections buried in the predominant N20m were isolated and could be discriminated from the background noise in all subjects studied. However, the amplitude and the number of the isolated high-frequency oscillation peaks differed among the individual subjects. The number of high-frequency peaks ranged from 4 to 13 (mean + S.D., 6.6 + 3.6). A Fast Fourier Transform (FFF) analysis with a Hamming window of the wide-band records between 5 and 35 msec post stimulus revealed 2-4 frequency peaks of signal energy (Fig. 1A and B). The power spectrum is shown on a log-log scale in which the abscissa is the frequency of the signals and the ordinate indicates the signal energy in an arbitrary unit. The main signal energy was distributed broadly between 20 and 300 Hz with a peak around 40-60 Hz, and a weaker signal energy with 1-3 peaks was found above 300 Hz. Among the weaker peaks above 300 Hz, the lower frequency peak ranged from 320 Hz to 420 Hz (mean ___S.D., 348.8 + 34.8 Hz) and the higher frequency peak from 580 Hz to 780 Hz (mean + S.D., 681.1 __+53.3 Hz), and the higher frequency peak carried the principal signal energy in all subjects. Because there was no significant energy above 900 Hz, the broad-band records were low-pass filtered at a cut-off frequency of 900 Hz for clarity of display and for mapping. Thus, for the subsequent analysis of the data, a digital low-pass (0.1-300 Hz) or high-pass (300-900 Hz) filtering was applied to the original wide-band records for separation of the lowfrequency and high-frequency activities. Peak latencies and amplitudes of N20m were computed separately for its maxima and minima from the isofield mapping of the low-pass filtered SEFs for 10 subjects, and the mean values of these maxima and minima were calculated (Table 1). The latency and amplitude did not differ significantly for the maxima and minima of the field topography. Fig. 2 illustrates a typical sample of wide-band records (A) and high-pass filtered records (B) of the somatosensory evoked magnetic signals obtained from 49 measuring points over the left hemisphere following fight median nerve stimulation. Figs. 2-4 as well as Fig. 1A are from the same subject (YO). Polarity reversal of the N20m is seen clearly between the lateral and medial locations in wide-band recordings. Fig. 2B shows the same data after application of the digital high-pass filter. High-frequency oscillations are seen above the noise level corresponding to the time period of N20m. It is evident from visual inspec-

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Frequency [Hz] Fig. 1. A: FFT analysis of the wide-band records of SEFs from subject YO shows 2 peaks of signal energy; one below 300 Hz and one above 300 Hz. The data are obtained from 7 sensors in a dewar over the centro-parietal area and the power spectrum is illustrated on a log-log scale in this and following figures. B: the power spectrum of the SEFs from another subject (KY) shows 3 peaks of signal energy; one below 300 Hz and two above 300 Hz.

tion of the 2 data sets that the amplitude distributions of the N20m and high-frequency oscillations are almost identical over the hemiscalp. It should be noted, however, that the amplitude calibrations are different; 300 fF for the N20m and 100 fT for the high-frequency oscillations. The magnetic signals of wide-band and high-pass filtered records from the same selected lower temporal (probe A), and upper centro-parietal (anterior to the z axis) (probe B) locations are displayed in Fig. 2C and D. No magnetic signals were detected from the lower temporal region. Table 1 Latencies and amplitudes of the N20m peak while awake (n = 10) Maxima

Minima

Mean

Latency (msec) Range Mean 4- S.D.

1 8 . 2 - 21.2 19.3 4- 0.9

18.419.5 4-

20.6 0.9

1 8 . 3 - 21.0 19.4+ 0.8

-650.2 --269.9 -397.94124.1

241.0 -660.4 407.04- 138.8

Amplitude (iT) Range Mean4-S.D.

212.0 -670.6 416.24- 167.0

1. Hashimoto et al. / Electroencephalography and clinical Neurophysiology 1O0 (1996) 189-203

192

Thus, the traces indicate the residual noise consisting of instrumental and brain noises after 5000 averages. The noise level is typically 5 fT or less baseline-to-peak. On the other hand, over the centro-parietal region, SEFs were recorded and consisted mainly of N20m and P27m peaking at about 18 and 23 msec respectively after stimulation. The

(A)

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measured magnetic fields over the centro-parietal region showed spatial variation within a small area with a diameter of 4.4 cm over the somatosensory hand area, reversing polarity of N20m medio-laterally (channels B2, B3 and B7 are located laterally, and channels B5 and B6 medially with channels B 1 and B4 on the zero line). In addition, a

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Fig. 2. A: wide-band recorded SEFs obtained from 49 locations over the left hemisphere following right median nerve stimulation. Polarity reversal of the initial N20m peak is evident medio-laterally. In this and following figures (Figs. 2-4), typical samples from subject YO are used for illustrating the data obtained while awake. B: high-pass filtered SEFs (300-900 Hz) show high-frequency oscillations roughly coincident with the N20m spatio-temporally. C: the broad-band SEFs from selected lower temporal (probe A) and centro-parietal (probe B) locations are displayed on an extended time base. The N20m reverses polarity within a small area of the centro-parietal region and in addition a series of low-amplitude, high-frequency inflections is seen to superimpose on the underlying N20m (see B2 and B6 tracings). D: high-frequency oscillations from the same measurement locations as in C. E: high-frequency oscillations with an enlargement of time scale (10-25 msec) clearly show a phase-reversal medio-laterally (compare B2 and B6).

193

1. Hashimoto et al. / Electroencephalography and clinical Neurophysiology 100 (1996) 189-203

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series of low amplitude, high-frequency inflections is seen to be superimposed on the initial and second slopes of the N20m (Fig. 2C). High-frequency oscillations start approximately at or later than the onset of the N20m and end in the middle of the second slope (Fig. 2D). Similar to N20m, each peak of the high-frequency oscillations reversed polarity medio-laterally at exactly the same location as was seen clearly in Fig. 2E with an extended time base. Fig. 3A shows a series of isofield patterns of the isolated high-frequency oscillations during 15.8-17.6 msec with 0.2 msec intervals. Continuous red lines indicate magnetic flux out of the head and dashed blue lines flux into the head. The isofield lines are separated by 2.5 fT. The field patterns were distinctly dipolar around the 3 peaks of alternating polarity (16.0-16.4 msec, 16.8-17.0 msec and 17.6 msec). The field patterns of the low-pass filtered SEFs during 16.0-17.8 msec are displayed for comparison (Fig. 3B). The isofield lines are separated by

20 fT. The patterns did not change throughout the initial slope of increasing amplitude to the N20m peak. The field patterns at the peaks of the high-frequency oscillations and the low-pass filtered SEFs at the corresponding period showed a close similarity. The 3-dimensional location of the equivalent dipole for each peak of the high-frequency oscillations agrees with activation of the 3b area of somatosensory cortex on the MRI of the same subject. Fig. 4A shows an example of the overlay of the estimated source at a peak of the high-frequency oscillations presented in Fig. 3A (16.8 msec). The location of the dipole for the low-pass filtered SEFs at the same point in time with that of the high-frequency peak (16.8 msec) was also at the 3b area and was approximately the same as or slightly deeper than that for the high-frequency peak (Fig. 4B). Table 2 shows the dipole localization and dipolarity computed for each peak of the high-frequency oscillations and for the corresponding point in time of the low-pass filtered SEFs. There were no significant differences in localization for x and y axes between the high-frequency peaks and the underlying N20m. However, the localization for the z axis for the high-frequency peaks was higher than that for the N20m by 3 mm and this difference reached statistical significance ( P < 0.001). Similarly, the absolute distance (D) from the center (origin) of the coordinate system defined as ~/x2 + y2 + z 2 was slightly longer for the high-frequency oscillations ( P < 0.001). Dipolarity of the equivalent sources for the high-frequency peaks was significantly lower than that for the N20m due to a lower signal-to-noise ratio. Table 3 shows the dipole strength for each peak of the high-frequency oscillations and for the low-pass filtered SEFs at the identical point in time. The dipole strengths of the high-frequency peaks for each axis were on the order of - 3 to 2 nA × m or less. However, the mean strength of the high-frequency peaks for each axis was close to zero because of summation of positive and negative values as a result of alternating polarity of the high-frequency peaks. The underlying N20m strength at the same latencies for each axis was much greater than for the high-frequency peaks. However, apart from the dominant x axis for the

Table 2 Localization of the equivalent sources for the high-frequencypeaks(HFPs) and for the underlying N20m at the same latenciesduring wakefulness(n = 42) Component Coordinates (cm) Dipolarity(%) X

Y

Z

D a

- 0.6 -2.8 1.1+0.9

3.2 -5.6 4.65:0.7

7.7 - 10.8 9.45:0.7 *

8.9 - 11.8 10.6± 0.7 *

80.9 -98.2 89.55:7.7 *

- 0.3 -2.7 1.15:0.9

3.6 -5.3 4.45:0.6

7.2 - 10.2 9.14- 0.7

9.1 - 11.5 10.35:0.6

88.9 -99.5 95.75:2.7

HFPs

Range Mean+S.D. N20m

Range Mean+S.D.

a D: absolute distance from the center of the coordinate system defined as ~/x 2 + y2 + z 2 " * P < 0.001.

194

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L Hashimoto et al./Electroencephalography and clinical Neurophysiology 100 (1996) 189-203

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Fig. 3. A: isofieid maps of the high-frequency oscillations over the left hemisphere. The maps are shown at 0.2 msec intervals. Continuous red lines indicate magnetic flux out of the head and dashed blue lines flux into the head. The isofield lines are separated by 2.5 IT. The field patterns are dipolar at the 3 peaks (16.2, 17.0 and 17,6 msec) of alternating polarity. B: isofield maps of the low-pass filtered SEFs (0.1-300 Hz) during a similar time period. The isofield lines are separated by 20 fT. The patterns are consistent with a tangential dipole within somatosensory area 3b and very similar to those of the high-frequency peaks. Table 3 Dipole strength for high-frequency peaks (HFPs) and for the underlying N20m at the same latencies during waking (n = 42) Component

mx

Mean+S.D.

Awake

my

mz

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2.1 1.24

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2.2-39.1

-13.7-3.0

15.7+ 9.1

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2.8

Range Mean+S.D.

1.2+ 0.7

Amplitude(fl')

2.8-43.1

Range Mean+S.D.

17.0+ 9.4

a ma: absolute dipole strength defined as ~ m x 2 + my 2 + mz 2 .

Sleep

Difference (S - A)

Latency (msec)

ma a

N20m Range

(n = 6)

Strength (nA × m)

HFPs Range

Table 4 Comparison of latencies and amplitudes of N20m while awake and asleep

• P < 0.005.

1 8 . 8 - 19.9 19.2+ 0.5

1 8 . 9 - 20.9 19.8+ 0.8

284.5 - 556.8 390.3+110.0

307.9 - 608.7 429.0+117.2

0 . 1 - 1.4 0.6+ 0.6 21.1 - 69.2 38.6+18.7 *

L Hashimoto et al./Electroencephalography

and clinical Neurophysiology 100 (1996) 189-203

195

A

B

Fig. 4. A: estimated source location of a high-frequency peak (16.8 msec) superimposed on the subject's MRI slices. Left: an axial slice viewed from above. Right: a coronal slice viewed from front. B: estimated source location of the low-pass filtered SEFs at the same latency as for the high-frequency peak. The locations for the 2 components are almost the same and are at somatosensory area 3b.

Table 5 Localization of the equivalent sources for high-frequency peaks (HFPs) and for the underlying N20m at the same latencies during sleep (n = 10) Compo- Coordinate (cm)

Dipolarity

nent

X

Y

Z

D a

HFPs Range Mean ±S.D.

1.0-2.9 2.0-t-0.6

2.9-5.4 4.3+0.7

8.1-12.0 10.0± 1.1

8.7-13.0 80.4-95.7 11.1+ 1.3 88.3+ 5.1 *

N20m Range Mean ±S.D.

0 . 2 - 2.3 1.8±0.6

3 . 0 - 5.5 4.2±0.8

9 . 2 - 10.6 9.8± 0.5

a D is defined as V/x 2 + y 2 + z 2 . P < 0.001. *

(%)

9 . 8 - 11.5 9 3 . 4 - 97.8 10.8± 0.6 96.2± 1.4

N20m dipole, a similar effect of cancelation was observed due to individual variation of the dipole direction. Therefore, the absolute strength defined as ~/mx2 + my 2 -t- mz 2 provides a more relevant parameter for comparison of the strength between the high-frequency peaks and the N20m. The mean absolute strength was 1.2 nA × m for the highfrequency peaks and 17.0 nA × m for the low-pass filtered N20m at the corresponding points in time.

3.2. Somatosensory evoked fields during sleep The N20m was detected in all subjects during waking and sleep. Eor 6 subjects tested during both wakefulness and sleep, the latencies and amplitudes of the N20m peak were compared between the 2 states (Table 4). For statistical analysis, the data at the maxima and minima were combined and the mean values were used for comparison.

1. Hashimoto et a l . / Electroencephalography and clinical Neurophysiology 100 (1996) 189-203

196

were compared between the 2 states (Table 4). For statistical analysis, the data at the maxima and minima were combined and the mean values were used for comparison. Although the N20m showed a longer mean latency during sleep, this difference (mean, 0.6 msec) did not reach statistical significance. However, the mean N20m peak amplitude was significantly larger during sleep (P < 0.005). Fig. 5 illustrates wide-band records of the SEFs obtained during waking (A) and during sleep (B) from the

(A)

z

same subject (JO). Although measurement locations were not identical between the 2 sets of magnetic recordings, the amplitude of the initial N20m peak was approximately of the same size in this subject. In contrast, high-pass filtered SEFs showed a significant difference in amplitude between the 2 states. Although strong high-frequency oscillations were present during waking (Fig. 5C), they were reduced in amplitude and were no longer detected from the background noise during sleep (Fig. 5D). However, low amplitude high-frequency oscillations were detectable during

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Fig. 5. A: wide-band recorded SEFs from subject JO during wakefulness. B: wide-band recorded SEFs from the same subject during sleep. C: high-frequency oscillations during waking after application of the high-pass filter (300-900 Hz) to the original data presented in A. D: high-frequency oscillations during sleep after application of the high-pass filter to the original data illustrated in B. Note remarkable reduction of amplitude.

L Hashimoto et al./Electroencephalography and clinical Neurophysiology 100 (1996) 189-203

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peak was centered around 650-700 Hz during waking (Fig. 6A). On the other hand, the higher frequency peak disappeared during sleep and as a result, the lower frequency peaks of 300-500 Hz predominated (Fig. 6B). Table 5 shows the dipole localization of the highfrequency peaks and N20m at the corresponding latencies during sleep for the detected and analyzed 10 peaks from 4 subjects. For the vertical z axis and for the absolute distance from the center of the coordinate system, the mean localization of the high-frequency peaks was higher and longer than that of the N20m by 2 mm and 3 mm respectively. This trend is similar to the data during wakefulness, but the difference did not reach statistical significance. Only the dipolarity for the high-frequency oscillations was significantly lower than that for the N20m due to a lower signal-to-noise ratio. Amplitude data were not obtained from 2 subjects because the high-frequency oscillations were less than twice the baseline noise level on visual inspection. For the 10 peaks analyzed, the absolute dipole strength ranged between 0.2 nA x m and 1.1 nA × m (mean + S.D., 0.6 + 0.3 nA X m) and the mean strength was significantly smaller than that during waking (P < 0.02). The absolute dipole strength of the low-pass filtered SEFs at the same latencies as the high-frequency peaks was also computed and ranged from 8.0 nA × m to 51.4 nA × m (mean + S.D., 19.2 + 13.3 nA × m).

i

14.0

Free~ency [Hz]*tO~ Fig. 6. A: FFT analysis of the bandpass filtered SEFs (200-900 Hz) during waking shows the main signal energy at higher frequencies. The data are obtained from 7 sensors in a dewar over the centro-parietal area and the power spectrum is illustrated in linear plots. B: FFT analysis of the bandpass filtered SEFs (200-900 Hz) during sleep from the same subject shows that the main signal energy is shiftexl to lower frequencies.

sleep in 4 out of 7 subjects. The number of detected high-frequency peaks ranged between 0 and 5 (mean + S.D., 2.8 ___2.3) and this number during sleep was significantly smaller than that of the high-frequency peaks during wakefulness (P < 0.05). The FFT analysis of the wide-band SEF records during sleep showed 2-4 peaks in the power spectrum; above 300 Hz, the lower frequency peak ranged between 310 Hz and 380 Hz (mean + S.D., 342.9 + 29.8 Hz) and the higher frequency peak between 560 Hz and 720 Hz (mean + S.D., 678.6 + 55.5). There were no significant differences in the mean frequencies of both the lower and higher frequency peaks between SEFs measured during waking and sleep. It should be noted, however, that during sleep, the higher frequency peak evident during wakefulness was attenuated and the main signal energy was shifted from the higher frequency peak to the lower frequency peak in 4 out of 6 subjects. Fig. 6 shows the power spectrum of the highfrequency oscillations in linear plots after application of the high-pass filter set at 200 Hz (200-900 Hz). The main

4. Discussion

4.1. Localization of the high-frequency oscillations In this first multichannel MEG recording from wide areas of the contralateral hemisphere to median nerve stimulation, somatosensory evoked responses within the high-frequency range (300-900 Hz) were obtained from each of 10 subjects during wakefulness. The high-frequency oscillations were superimposed on the underlying N20m of the primary cortical response. The dipole strength of the oscillations was 1.2 nA x m and about one fourteenth of the N20m determined at the same latencies as the highfrequency oscillation peaks. Nevertheless, the magnetic topographic analysis produced consistent results: the sources of the high-frequency peaks of the SEFs were found to be located within the somatosensory cortex. Furthermore, a close spatial colocalization of the equivalent dipoles was demonstrated between the N20m and the superimposed oscillations. In fact, there was no statistically significant difference in location for the 2 components for the horizontal x-y plane. However, the location differed significantly between the 2 components along the vertical z axis and for the distance from the center of the sphere; the location of the high-frequency oscillations was 3 mm higher and 3 mm longer than that of the N20m. It may be argued to what extent this small difference in localization is relevant in view of the spatial resolution of

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the present measurements. It has been shown that the spatial resolution can be estimated from the signal-to-noise ratio of the magnetic measurements (Had et al., 1988). The system noise of the gradiometer used in the present experiment was 15 fT v'I-Iz or less. Assuming that the brain noise is about the same level as the system noise, the combined noise is 1/152+ 152fT ~/Hz = 21.2 IT x/Hz. Since 5000 responses were averaged with the passband of 300-900 Hz for high-frequency oscillations, the final noise is 21.2 × (~/900A/5000) fT = 9.0 fT. The value would be reduced to 6.4 tT if the brain noise is assumed to be zero, and this estimated final noise is close to the measured noise. On the other hand, the signal strength of the high-frequency oscillations was maximally about 35 fT (range 20-50 IT), and the signal-to-noise ratio is thus 3.9-5.5. This would lead to a spatial resolution of about 4 - 6 mm for the sagittal x-z plane for dipoles at a depth of 20 mm beneath the scalp (Had et al., 1988). For the low-pass filtered (0.1-300 Hz) signals, the final noise would be 21.2 × (~/300/~/5000) fT = 5.2 IT. If the brain noise can be neglected, the final noise would be further reduced to 3.7 fT. On the other hand, the signal strength of the N20m was maximally about 400 fT and the signal-to-noise ratio is thus 80-110, giving a spatial resolution of less than 1 mm. From the above theoretical considerations, the difference in dipole locations between the 2 components, even if statistically significant, should be interpreted with caution. We speculate, however, that the presumed caudal and deeper location of the underlying N20m relative to that of the high-frequency oscillations can be explained in part by a contribution of the thalamic fields overlapping temporally on the onset and early part of the cortical N20m. There has been a long-standing controversy over whether or not the thalamus can produce an open field so that the thalamic activity can be measured at a distance from the source (Arezzo et al., 1979; Allison and Hume, 1981; Katayama and Tsubokawa, 1987; Urasaki et al., 1990). In a recent study using micro SQUID sensors, we were able to detect the magnetic signals from the thalamus in decorticated animal preparations following electric stimulation of the snout (Hashimoto et al., 1994, 1996). The somatic evoked signals of 5-10 pT could be recorded 10 mm above the thalamus and smaller amplitude signals could even be detected 20 mm above it. These thalamic signals preceded or overlapped the initial phase of the primary response when the cortex was left intact. Similar observations were made in human subjects where, with a single dipole model, the sources tended to be deeper and nearer the thalamus at the onset of the N20m, with a progressive shift towards the somatosensory cortex during the ensuing initial phase of the N20m (Hashimoto et al., unpublished observation). Recently, Tesche (1995) was able to determine wave forms for responses in the somatosensory cortex and the VPL of the thalamus using signal-space projection. Thus, it is likely that the individual thalamic and cortical dipoles overlapping in time may combine to

make a single dipole estimation deeper than that of the cortical dipole alone. On the other hand, the high-frequency oscillations are localized within the cortex and a similar shift of the dipole locations with successive peaks was not observed. It is concluded therefore that the sources for the 2 cortical components are very close to each other in area 3b, provided that the presumed effect of the thalamic dipole can be excluded. It is now well established that N20m is generated within the apical dendrites of the pyramidal cells in area 3b on the basis of electrical recordings from the cortex (Lueders et al., 1983; Allison et al., 1989), magnetic recordings (Tiihonen et al., 1989; Suk et al., 1991) or both (Wood et al., 1985). However, the physioanatomical basis of the high-frequency oscillations remains to be clarified and we will discuss this in a later section.

4.2. Frequency distribution of the high-frequency oscillations Previous studies of SEPs have shown that the primary N20 potential has several subcomponents over its ascending and descending phases (Cracco and Cracco, 1976; Abbruzzese et al., 1978; Maccabee et al., 1983; Eisen et al., 1984; Green et al., 1986; Emerson et al., 1988; Yamada et al., 1988; Emori et al., 1991). In order to identify the fast subcomponents, analog high-pass filters above 100 Hz (Maccabee et al., 1983) or digital high-pass filters at different cut-off frequencies ranging from 200 Hz (Green et al., 1986; Emori et al., 1991) to 250 Hz (Yamada et al., 1988) were applied. However, the frequency distribution of the fast subcomponents was not examined in detail in previous SEP studies. Curio et al. (1994) analyzed the frequency content of the high-frequency oscillations in a single magnetic record following median nerve stimulation. Their FFT analysis of a wide-band record (0.5-1500 Hz) with a Hanning window centered at 20 msec after stimulation showed 2 frequency peaks; one below 100 Hz contributed by the N20m and the other above 400 Hz with a single peak at 600 Hz contributed by the high-frequency oscillations. The present study employing a similar F F r analysis revealed 2 - 4 peaks of frequency distribution. A low-frequency peak below 100 Hz carried the main signal energy with contributions from N20m and P27m, consistent with the results reported by Curio et al. (1994). However, there were 1-3 peaks above 300 Hz in our measurements as against a single peak in the above study. Moreover, the higher frequency peak ranging from 580 Hz to 780 Hz with a mean of 680 Hz constituted the major peak in the highfrequency oscillations. The findings suggest interindividual variation in the frequency distribution of the high-frequency signals.

4.3. Effect of sleep on the high-frequency oscillations High-frequency oscillations were consistently recorded during wakefulness. In contrast, during sleep, they showed

L Hashimoto et aL/Electroencephalography

marked attenuation in amplitude and also diminution in the number of peaks. This is in line with an SEP study during a waking-sleep cycle, showing progressive attenuation of the fast subcomponents as a function of deepening sleep stages from 1 to 4 (Yamada et al., 1988). Although the amplitude of the fast subcomponents recovered during REM sleep to a certain extent, it was between 30 and 80% of the level of the waking state. In this study, the data were collected during NREM sleep stages 2-4. The highfrequency oscillations totally disappeared in 2 subjects. This is probably related to a longer period of deep sleep (stages 3 and 4) maintained during data collection. In other subjects, the high-frequency oscillations were detected during sleep and 1-3 peaks of similar frequencies to those recorded during wakefulness were observed. However, the main signal energy was shifted from the higher frequency peak to the lower frequency peak, suggesting that the changes observed during a waking-sleep cycle are mainly due to a state-dependent alteration in the higher frequency energy between 580 Hz and 780 Hz. 4.4. Effect of sleep on the N20m The peak latency of the N20m was slightly longer during sleep than during wakefulness by an average of 0.6 msec. This difference, however, did not reach statistical significance. It has been shown that SEP components occurring after N20 vary in amplitude and latency depending on the subject's state of arousal. In contrast, N20 has long been recognized as a remarkably stable component and is resistant to the effects of state parameters such as waking and sleep (Liiders et al., 1986) as well as barbiturate-induced coma (Hume et al., 1979). In support of this, animal experiments have demonstrated that the latency of short-latency SEPs including the homologue of the human N20 does not change during barbiturate anesthesia (Mezzo et al., 1981; Sutton et al., 1982). Although Yamada et al. (1988) showed that the parietal N20 and frontal P20 of the high-pass filtered SEPs with a cut-off frequency of 250 Hz were reduced in amplitude and increased in latency during sleep, they did not systematically examine the state-dependent amplitude and latency changes of the N20 and P20 in their original open bandpass tracings. However, it can be surmised from their illustrated figures that the parietal N20 and frontal P20 might be prolonged in latency during deep sleep (see Figs. 4 and 5 of Yamada et al., 1988). It is not clear whether this prolongation of the N20/P20 peak was the direct effect of sleep or due to a secondary effect of sleep such as a body or limb temperature change during sleep, because the temperature can affect conduction velocities of the peripheral nerves and the ascending tract fibers in the spinal cord and central nervous system (cf., Stegeman and De Weerd, 1982). For example, the linear regression line computed from the experimental data had a slope of 2.0 m / s e c / ° C for the peripheral nerve conduction velocities. Assuming that the average conduction velocity

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of the median nerve is 50 m / s e c at normal body temperature (Buchthal and Rosenfalck, 1966; Hari et al., 1989; Hashimoto et al., 1989, 1991), a I°C decline in body temperature during sleep corresponds to a 4% decrease in the conduction velocity of the peripheral nerve. Provided that the conduction velocities of the ascending somatosensory tract fibers in the spinal cord and the central nervous system are affected to the same extent as in the peripheral nerve, the I°C temperature decrease may increase the N20 peak latency (approx. 20 msec) by 0.8 msec. In fact, intracranial temperature has been shown to fluctuate across a sleep-wake cycle and the reported difference between the maximum and minimum temperatures was 0.5-1.0°C (Landolt et al., 1995). Thus, without rigorous monitoring of the body and limb temperatures, "the state-dependent latency difference" in N20 or N20m during a wake-sleep cycle may lead to erroneous interpretations. The risk can be partly avoided by measuring the latency of the compound action potentials from Erb's point as a reference. Emerson et al. (1988) actually measured the interpeak latency between the Erb's point potential and the cortical N20 peak recorded with a wide bandpass (30-3000 Hz) and showed interpeak latency shifts of 0.3-0.9 msec, with a mean of 0.5 msec, during sleep. However, the data were collected during drag-induced sleep in 11 out of 13 experimental sessions. Thus, the direct effect of the sedatives (diazepam or triazolam) on the central nervous system transmission cannot be ruled out. Taken together, the effect of natural sleep on the latency of N20 or N20m is uncertain at present and needs further studies. The amplitude of the N20m was approximately 10% larger during sleep than during wakefulness, and this amplitude difference was statistically significant (P < 0.005). In the study by Yamada et al. (1988) on SEP changes during a wake-sleep cycle, the amplitude of the N20 in the open bandpass records was not systematically examined. However, on close inspection of their illustrated figures, the parietal N20 amplitude was about 10% higher during sleep than during waking measured either from the baseline or from the P14 peak (compare Figs. 1 and 3 in Yamada et al., 1988). Furthermore, the frontal P20 component measured from the baseline showed up to 30-50% increase during slow wave sleep (see Fig. 4 in Yamada et al., 1988). In support of the above findings, animal studies showed that the primary SEP component corresponding to human N20/P20 was increased in amplitude during slow wave sleep compared to waking (Okuma and Fujimori, 1963; Allison et al., 1966). Although it is likely that the human N20/P20 component also increases its amplitude during sleep, further studies on a larger scale are needed for a conclusive interpretation. It has to be recognized that for this purpose, low-pass filtered data (cut-off frequency of about 300 Hz) need to be used for comparison, because during waking the high-frequency oscillations superimposed on the N20 will spuriously increase the amplitude of the underlying N20.

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4.5. Physioanatomical basis of the high-frequency osciUations The results of the present study have shed a new light on the neural mechanisms of the high-frequency oscillations in the somatosensory cortex. The physiological features of the high-frequency somatic signals can be summarized as follows. First, the equivalent dipoles for the high-frequency peaks and the underlying N20m are temporally overlapped and spatially colocalized within the 3b area. Second, the high-frequency oscillations have their main signal energy at 580-780 Hz and are distinct from the N20m which has principal signal energy at 40-60 Hz. Third, the high-frequency oscillations present during wakefulness attenuate or disappear during sleep. Fourth, the underlying N20m in contrast increases its amplitude during sleep. Thus, there exists a reciprocal relationship between the high-frequency oscillations and the N20m during a wake-sleep cycle. It has been generally accepted that the N20 and N20m are generated by ensemble EPSPs in the apical dendrites of the pyramidal neurons in the somatosensory cortex. The thalamic afferent fibers terminate on the apical dendrites of these pyramidal neurons in the middle and deep layers of the somatosensory cortex (Jones, 1975; White, 1986). The short-latency dendritic EPSPs in the deeper layer of the cortex produce a deep current sink and a superficial current source. Because individual apical dendrites of the pyramidal neurons have an orderly and parallel arrangement within the cortex, synchronous activation of a sufficient number of the pyramidal cells builds up large extracellular potential fields. Thus, the initial EPSPs in area 3b of the somatosensory cortex summate to produce the primary response which is recorded as N20 from the parietal scalp and as P20 from the frontal scalp. Similarly, the intracellular currents associated with the activation of the pyramidal neurons generate a magnetic signal around the apical dendrites which can be recorded as N20m outside the head. It had long been the prevailing concept of cortical organization that the intrinsic neurons of layer 4 are the principal thalamic recipient cells in the cortex that then serve as relays to the pyramidal neurons. This concept of hierarchical organization has been modified because the pyramidal cells have also been shown to be the recipients of the direct thalamic synapses (Jones, 1975; White, 1986). Morphological studies on the monkey sensorimotor areas have shown that there are several different types of interneurons in the major thalamic terminal region in layer 4 and the adjacent part of layer 3; the majority of which are non-spiny, GABAergic inhibitory interneurons and only one type belongs to presumably spiny excitatory interneurons (Jones, 1975). These interneurons receive direct thalamic axon synapses and have their own axon terminations focused on the cell somata, proximal dendrites and initial segments of the pyramidal cells (Somogyi et al., 1982;

DeFelipe et al., 1985, 1986). The findings suggest that GABA-mediated inhibition plays a powerful role in the shaping of the response profiles of pyramidal neurons. Furthermore, the patterns of connectivity of many GABAergic interneurons are bidirectional in which the vertical projections between deep and superficial layers are particularly strong while the horizontal projections are less prominent (Jones, 1975, 1993). This parallel arrangement of the interneurons provides the anatomical basis for spatial summation of activity of individual neurons. Thus, synchronous monosynaptic activation of a population of GABAergic interneurons, by summating individual intracellular currents spatiotemporally, may produce magnetic fields strong enough to be detectable outside the head. The concept of inhibitory processes as a physiological mechanism subserving discrimination processes during wakefulness was first proposed by Jasper (1958). Moruzzi (1966) suggested further that sleep is involved with slow recovery processes of the inhibitory interneurons where plastic changes occur while awake as a consequence of learning or conditioning. Thus, the inhibitory interneurons decrease their activity or may be actively inhibited during sleep. This hypothesis of reduced excitability of the inhibitory interneurons during sleep is in line with the study of antidromic responses of pyramidal tract neurons in monkeys during waking and sleep (Evarts, 1964). Furthermore, iontophoretic application of the GABA g antagonist bicuculline in the somatosensory cortex (Dykes et al., 1984) led to an enlargement of the receptive fields of pyramidal cells, whereas the application in the visual cortex produced loss of direction and orientation selectivity as well as center-surround antagonism in the receptive fields of relay cells (Sillito, 1979). Livingstone and Hubel (1981) showed in cat visual cortex that the response selectivity is enhanced while background activity of the cells is reduced on arousal, leading to an increase in the signal-to-noise ratio. They speculated that the enhanced inhibitory mechanism underlies the improved signal-tonoise ratio in sensory processing while awake. It is widely accepted that information processing in the cerebral cortex is modulated by the arousal system of the brain-stem that is composed of 3 ascending fiber systems which release the neurotransmitters acetylcholine, noradrenaline and serotonin at their target sites (for review see Steriade et al., 1990). Thus, the inhibitory processes are enhanced during arousal (Livingstone and Hubel, 1981) and by local application of acetylcholine (see Steriade et al., 1990) and serotonin (Funke and Eysel, 1995) in the cortex and the subcortical relay nucleus. From the foregoing, it may be concluded that the GABAergic inhibitory intemeurons represent a major neural element in the cerebral cortex contributing to cortical functions such as those involved in sensations, cognition, movement, learning and memory. Electrophysiological characteristics of cortical interneurons are high-frequency spike bursts (200-1000 Hz) in

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response to synaptic volleys, combined with an absence of antidromic activation from any stimulus site (Steriade, 1978). In addition, the extracellular spike wave form originating from the interneurons is short in duration ("thin spikes") and about one-half (approx. 0.4 msec) that of the "regular spikes" (about 1.0 msec) produced by the pyramidal neurons, reflecting mainly different cell morphology (Mountcastle et al., 1969; Simons, 1978; McCormick et al., 1985; Swadlow, 1989). The burst pattern of local-circuit inhibitory cells has been found in several areas of the central nervous system such as the olfactory bulb (Shepherd, 1963), hippocampus (Andersen et al., 1964), cerebellum (Eccles et al., 1966), inferior olive (Llin~s et al., 1974), and somatosensory cortex (Steriade, 1978; Swadlow, 1989). Swadlow (1989) recorded a burst of 3 or more spikes at frequencies of 600-900 Hz from the primary somatosensory cortex of the rabbit with electrical stimulation of the ventrobasal thalamus. The activity of cortical inhibitory interneurons studied in animal experiments bears striking similarities to the high-frequency oscillations in the somatosensory cortex in humans. First, the inhibitory interneurons of the somatosensory cortex show a burst of high-frequency spikes at a frequency range of 600-900 Hz (Swadlow, 1989). Second, GABAergic interneurons were activated by acetylcholine and serotonin upon arousal, which causes enhancement of inhibition of downstream glutamatergic pyramidal cell activity (Steriade et al., 1990; Funke and Eysel, 1995). This GABA-mediated feed-forward inhibition or disinhibition of the pyramidal neurons may underlie the reciprocal relation of the amplitude between the high-frequency oscillations and the N20m during a wake-sleep cycle. Thus, an amplitude reduction of the high-frequency oscillations is associated with an increase in the N20m during sleep and vice versa during wakefulness. Although we have no human data on possible modulation of the thalamic activity during sleep, our results suggest that at least the shortlatency thalamic response is not grossly affected by sleep. In the cat, however, the VPL thalamic response to medial lemniscal stimulation was consistently smaller during slow wave sleep (Allison, 1965; Dagnino et al., 1971), whereas in about one-third of the animals, the VPL response to peripheral stimulation was as large or larger during slow wave sleep than during wakefulness (Allison et al., 1966). This difference may reflect changes in excitability at the first synapse of the afferent pathway. For example, the afferent volley recorded in the medial lemniscus to cutaneous stimulation was found to be larger during sleep than during arousal (Favale et al., 1965). Thus, decreased transmission through the second synapse (VPL) during sleep may be counteracted by increased transmission through the first synapse (cuneate nucleus). These data suggest either decreased or increased thalamocortical input to the cortex during sleep. Thus, the decreased thalamocortical excitatory drive on pyramidal cells (generating N20m) during sleep is apparently more than compensated for by the

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decreased inhibition via the interneurons of layer 4. On the other hand, the increased thalamocortical volley on pyramidal neurons will result in an amplitude increase of N20, while the same increased excitatory drive on the interneurons produces less excitation due to the reduction of interneuronal responsiveness during sleep. Thus, reduction of the feed-forward inhibition to the pyramidal neurons produces enhanced monosynaptic activation of the pyramidal neurons, leading to an increased N20m amplitude. Allison (1968) recorded cortical SEPs to stimulation of thalamocortical afferents in cats during slow wave sleep and waking. In this study, an early wave 2 during waking was maximally enhanced, while later waves 3-5 were depressed. Furthermore, recovery functions showed a reciprocal relationship between the increase in wave 2 amplitude and decrease in wave 4 amplitude. From these reciprocal relations between the early and later waves, Allison (1968) speculated that wave 2 is the summated activity of interneurons. Based on these convergent lines of evidence, as discussed above, it may be concluded that the highfrequency oscillations represent the activity of the GABAergic inhibitory interneurons in layer 4 of area 3b of the primary somatosensory cortex. It may be questioned as to how averaged and summated activity of the somatosensory cortex has such a highfrequency component between 300 Hz and 900 Hz given the presumed biological jitter in central nervous system activity. Sugihara et al. (1993) showed that rhythmic firing in the inferior olive reaches all sites of the cerebellar cortex at the same time, regardless of the distance between the various portions of these 2 brain regions. This synchronicity is accomplished by varying conduction velocities of the olivo-cerebellar axons such that their conduction time is the same to all parts of the cerebellar cortex. Provided that such a principle of synchronicity is present in the somatosensory and other sensory systems as well as in the cerebellum, it is possible that the mass response as an envelope of individual unit activities has a sharp temporal profile with a high-frequency content. In fact, far-field somatosensory and auditory evoked potentials from the brain-stem and thalamus have similarly high frequency components with a duration of 1-2 msec (for review see Hashimoto, 1984, 1989; Desmedt, 1989). These data suggest that they originate in extremely secure and highly synchronized generator systems. The high-frequency signals in SEPs and SEFs were previously ascribed to presynaptic action potentials and fields on the basis of their high-frequency spectral energy which is common to peripheral nerve compound activity and subcortical white matter activity (Maccabee et al., 1983; Katayama and Tsubokawa, 1987; Curio et al., 1994). In this connection, we have shown in a previous study that the compound action fields of the median nerve over the elbow following stimulation at the wrist have a high-frequency signal ranging from 200 Hz to 900 Hz (Hashimoto et al., 1991). However, the decrease or total abolition of the high-

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frequency oscillations during sleep in spite of enhanced N20m reflecting EPSPs of the pyramidal neurons would argue against a contribution of the thalamo-cortical afferent activity to the high-frequency oscillations. It is possible though that the presynaptic activity of terminal arbors of thalamo-cortical afferents may play a minor role in the generation of the high-frequency oscillations as suggested by a combined study of intracortical field potentials, current source density analysis and multiunit activity in the monkey somatosensory cortex (Peterson et al., 1995).

Acknowledgements This research was supported by a grant from the Ministry of Education, Science and Culture of Japan

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