Frontal gamma-band enhancement during multistable visual perception

INTERNATIONAL JOURNAL OF PSYCHOPHYSIOLOGY

ELSEVIER

International

Journal of Psychophysiology

24 ( 1996) 113- 125

Frontal gamma-band enhancement during multistable visual perception Canan BaSar-Eroglu a,*, Daniel Sttiber a, Peter Kruse a, Erol Bagar b, Michael Stadler a a Institute of Psychology and Cognition Research, Unioersity of Bremen, D-28334 Bremen, Germany b Institute of Physiology, Medical Universiry of Liibeck, Liibeck, Germany Received 6 March 1995; revised 15 February

1996; accepted

14 March 1996

Abstract The aim of our study was to find out whether an increase in the gamma band may be related to the reversal phase during viewing of an ambiguous pattern. The present study describes the significant gamma band (30-50 Hz) activity increase in EEG during states of perceptual switching (reversal state). In our experiments the multistability was induced with an ambiguous stimulus pattern, known as stroboscopic alternative motion (SAM). The investigations carried out in 11 subjects included a measuring strategy with three different experimental conditions: (1) recording of spontaneous EEG as baseline; (2) recording of the EEG during naive observation of the ambiguous pattern; (3) recording of EEG during active observation of SAM. The results indicate that the multistable perception is one of the multifold cognitive processes giving rise to 40 Hz enhancement in the entire cortex. The most significant 40 Hz enhancements were measured in frontal areas and can reach increases of 40 to 50% in states of naive and active observations of SAM, respectively, in comparison to spontaneous EEG recordings. The results indicate that the increase of frontal gamma band is related to the destabilization of the perceptual system when viewing multistable patterns. Keywords: Multistable perception; motion; Selective attention

Ambiguous

pattern;

EEG; Event-related

1. Introduction The present study was undertaken for analysing changes in brain 40 Hz activity (gamma band) during states of perceptual multistability induced by a dynamic ambiguous stimulus pattern (Stroboscopic Alternative Motion: SAM). Results obtained in our

* Corresponding (421) 218-4600; bremen.de

author. Tel: +49 (421) 218-2360; Fax: +49 e-mail: [email protected]

0167-8760/96/$15.00 Copyright PI1 SO167-8760(96)00055-4

potentials;

40 Hz-gamma

rhythms;

Stroboscopic

alternative

recent study revealed first hints of increasing gamma band during perceptual switching (Bagar-Eroglu et al., 1995). Following the application of several of our experimental strategies, it will be shown that during observation of multistable patterns, 40 Hz increases are elicited in frontal lobes of the human brain. Comparison with earlier results opens the possibility to discuss, step by step, candidates of functional correlates of perceptual multistability interwoven with learning, selective attention and decision making of subjects during this highly active state of the CNS.

0 1996 Elsevier Science B.V. All rights reserved.

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Since the early days of Gestalt theory, it is of great theoretical interest to analyze the neurophysiological dynamics that underlie the perceptual processes (Wertheimer, 19 12). Accordingly, Kiihler introduced reversible figures as a paradigm hoping L‘ . . . to learn more about brain correlates if we turn to instances in which perceptual processes seem to be in a more active state” (Kohler, 1940). Following this line, Kijhler and coworkers pioneered the application of evoked potentials to the study of visual perception (Kiihler and Held, 1949; Kijhler et al., 1952). Multistability, i.e. the property of a dynamic system to attain different stable states in a nonlinear self-organized manner, can be characterized as a universal phenomenon in mind and nature &ruse and Stadler, 1995). In visual perception, the so-called reversible or ambiguous figures like the Necker cube (Fig. 1A) represent multistable phenomena (e.g. Gregory, 1966; Attneave, 1971). The spontaneous oscillation between different stable percepts of the same physical pattern elucidates the fundamental role of instability as a process characteristic for the autonomous order formation in perception &ruse et al., 1991). It has been shown by means of psychophysical experiments that perceptual multistability is an appropriate paradigm for research on cognitive self-organization &ruse et al., 1995). A lot of work has been done showing the influence of physical and psychological variations in stimulus properties on exogenous and endogenous components of the event-related potential (ERP). For a review of ERP components see Regan (1989). However, there are only a few studies concerning

03

o-0 O-0

X

0

0

I 1 X

Y

A Fig. 1. Multistable patterns: (A) The Necker cube. The perspective reversal of Necker cube is a familiar example of the phenomenon that a constant stimulus pattern alternates between different percepts. (B) Stroboscopic Alternative Motion (SAM). The reversible pattern used in the present study. X, fixation point. During fixation of the SAM a horizontal apparent motion alternates with a vertical apparent motion.

24 (1996) 113-125

EEG potential changes related to changes in perceptual interpretation of an invariant stimulus as is the case in viewing reversible patterns. Johnston and Chesney (1974) reported that an ambiguous symbol, which could be interpreted as the letter B or the number 13, elicited different visual evoked potentials (VEPs) depending on whether it was seen in the context of a letter or a number string. The authors interpreted their results as indicating that the late components (160 ms) of the VEP recorded over the frontal area of the brain reflect neural activity correlated with the meaning of the stimulus, while the posterior components reflect the sensory features of the stimulus. Landis et al. (1984) reported the slow waves (352-480 ms> to be more negative during the perception of a recognizable face (‘hidden man’), than when no meaningful figure could be extracted from the ground. It was suggested that extraction of a figure out of the ground may be an active ‘constructing’ process. Elbert et al. (1985) studied the interaction of Necker cube reversal with the Bereitschaftspotential (BP). They found that positive potentials diminished the negative BP at parieto-occipital sites. O’Donnell et al. (1988) investigated the effect of variations in the perceived orientation of a Necker cube on the VEPs. VEPs associated with perceptual (illusory) reversals and non-reversals of the cube were compared with VEPs elicited by a sequence of physically varying cubical figures which were perceptually stable. The findings showed that both types of reversals were associated with a late positive component (400-700 ms), which was smaller in amplitude in the illusory condition. The authors suggest that illusory reversals are more difficult to discriminate than physical reversals, and require additional cognitive resources for evaluation. The EEG consists of the activity of an ensemble of generators producing rhythmicities in several frequency ranges. These rhythmicities are active usually in a random way, however, by application of sensory stimulation these generators are coupled and act together in a coherent way. This synchronization and enhancement of EEG activity gives rise to an ‘evoked’ or ‘induced rhythmicity’. These rhythmicities may also occur without defined physical stimulation but may be triggered by hidden sources, for example, as a result of a cognitive process (Bullock, 1992). Results from several investigators on this

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topic were recently collected in a volume by Ba$ar and Bullock (1992). Following neurophysiological data concerning 40 Hz neural oscillations in the visual cortex of the cat brain (Gray and Singer, 1987) and the significant extension of these results by E&horn et al. (19881, research on 40 Hz gained tremendous importance. Galambos (1992) classified the gamma rhythms recorded in different species into four categories: spontaneous, induced, evoked and emitted (see Bazar-Eroglu et al., 1996, this issue). Our research group has recently published data concerning potential changes in the EEG related to task-relevant multistable perception. The subjects pressed a button when they perceived a switch from one alternative of the multistable pattern to the other. During continuous viewing of an ambiguous pattern, a slow positive EEG wave was found only in EEGepochs containing a perceptual switching (BagarEroglu et al., 1993), and not in epochs where perceptual switching did not occur. Therefore, we have called this compound potential ‘perceptual switching-related positivity’. This slow wave has a greater amplitude in the right parietal location in comparison to the other scalp sites. By using digital filtering we were able to show that the frequency composition of perceptual switching-related positivity contains 0.1-5 Hz and 0. l- 12 Hz slow frequency components. Further analysis also showed an increase in 40 Hz activity during perceptual switching, whereas the alpha band (8-15 Hz) was decreased in comparison to the non-reversal phase (Bagar-Eroglu et al., 1995). In our earlier studies we have published a 40 Hz component accompanying the P300 wave of ERPs recorded from cat and human brain. Based on these results we will focus the analysis of EEG-ERP during viewing of reversal pattern first to the gamma band. The other frequencies such as theta and alpha will be published separately. It is well-known that the motor potentials are strongly related to the high frequencies of EEG. It was, therefore, in our interest to investigate the 40 Hz frequency components in an extended manner firstly in naive subjects, who perceive the ambiguous pattern without any knowledge of perceptual switching, while they passively view a multistable pattern (without motor task). The subjects were not informed about the fact that in the pattern observed perceptual

115

switching would appear spontaneously. During this experiment, all subjects have experienced the perceptual switching and we repeated the same experiment with the same subjects who were now informed. The results obtained were then compared with the 40 Hz activity in naive and informed subjects. In the case of perceptual multistability, EEG-correlates are of a special kind, because no external trigger exists. The real stimulus is the switching, i.e. an endogenous process. We assume that such a paradigm which activates internal events is very important in order to understand the functional interpretation of different EEG frequencies (Baaar et al., 1995). The aim of the present study is to find out whether an increase in the gamma band may be related to the destabilization of the perceptual system during the switching from one perceptual interpretation into the other.

2. Methods 2.1. Subjects Eleven healthy, right-handed, neurologically normal volunteers (6 female, 5 male) aged between 18 and 43 years participated in this experiment. They were medical students and members of the university. All subjects had normal or corrected to normal vision and none of them had prior knowledge about the dynamic ambiguous pattern used in this experiment (naive subjects). They were instructed to keep their eyes open and to maintain fixation all the time, to minimize blinking and eye movements. 2.2. Electrophysiological

recording

The EEG was recorded from Ag-AgCl electrodes at positions F3, F4, C3, Cz, C4, P3, P4, 01 and 02, according to the international lo-20 system. The electrodes were attached to the skin with collodion or adhesive collars. Linked earlobe electrodes served as reference. All electrode impedances were maintained at less than 5 kOhm. The EOG was also registered from medial upper and lateral orbital rim of the right eye. The EEG activity was amplified by means of a Schwarzer EEG apparatus with band limits between 0.1 and 70 Hz (24 dB/octave). An

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additional 50 Hz notch filter (36 dB/octave) was also applied to remove the main interference. The EEG was digitized on-line at a sampling rate of 250 samples per second and stored on the hard disc of the computer (HP 1000 F) for off-line EEG analysis. All channels were displayed on paper and on-line by monitor scope in order to observe both single trials and averaged signals. 2.3. Stimulus pattern The ambiguous stimulus pattern used in this experiment is based on the phenomenon of apparent motion (AM). Dynamic ambiguous AM displays seem to be most adequate to analyze multistable behaviour because their relevant variables can be better controlled than in static pictures like the Necker cube (Fig. 1A) and they are very reliable in their perceptual characteristics (Kruse et al., 1986). The one used here is a multistable stroboscopic motion display which was first introduced by Von Schiller (1933) and which we have called ‘Stroboscopic Alternative Motion’ (SAM). Four spots are positioned in an upright rectangle. Two diagonally positioned spots are always flashed simultaneously and after a short pause replaced by a flashing of the other two spots (Fig. 1B). During fixation of the SAM, a horizontal apparent motion alternates clearly and regularly with a vertical apparent motion when the distance of the lights and time of flashing is correctly tuned (Hoeth, 1966). Another theoretically possible percept of the SAM is either clockwise or counterclockwise motion. However, these circular motion phenomena cannot be achieved with the presentation conditions of the SAM display used in this experiment. Thus, the Table 1 An overview

Control condition Naive observation Active observation

of experimental

2.4. Experimental

procedure

The subject sat in a soundproof and echo-free room which was dimly lit. There were three experimental conditions (Table 1) for each subject. (1) Recording of spontaneous EEG as a baseline: subjects had to look at a fixation point on the computer screen in front of them, no pattern was presented. (2) Naiue observation of the SAM: subjects were instructed to look at the SAM pattern (for approximately 9 min); they were not informed about the multistable character of the SAM. After the session, all subjects were asked about the perceptual impressions during viewing of the SAM. It was established that all subjects perceived the alternation of horizon-

sessions and conditions

Subjects

Experimental

condition

condition

Eyes open and fixed Not informed

observation of percepts induced by SAM is essentially bistable similar to the Necker cube (e.g. Ramachandran and Anstis, 1983). In this study, the flashing frequency of the diagonal point-lights was 2 Hz. The resulting flashing duration was 165 ms for each diagonal with a pause of 85 ms between flashing. The horizontal to vertical ratio of the distances between points was approximately 5/8, which as a rule leads to equal probability of perceived horizontal and vertical motion (Hoeth, 1968). The horizontal distance of the spots was 2.4 cm, and the vertical 3.8 cm. At a viewing distance between subject and SAM display of 150 cm, the resulting visual angle for the horizontal direction is 0.92”, and for the vertical direction 1.45”. Each point light was 0.11” and their colour were white on a black background. In order to attenuate the possible on and off response in every 165 ms flashing time, the contrast of pattern was decreased.

Stimulation

Percepts

Spontaneous

No pattern SAM

Informed

Only observation: no motor-reaction task Motor-reaction task

Informed

No motor-reaction

SAM

task

SAM

Nomenclature

Pattern reversal and non-reversal phases Pattern reversal: 1 s prior to task; perceptual switching Pattern non- reversal: 2 s following perceptual switching

Multistable

EEG perception

Reversal phase Non-reversal

phase

C. Ba far-Eroglu et al. /International Journal ofPsychophpiology 24 (1996) 113-125

tal and vertical motion. This naive condition makes plausible that the switching between two motion directions of the SAM is due to a spontaneous self-organizing process and not only due to high-level influences such as knowledge of multistability (Girgus et al., 1977; Rock et al., 19941, expectancy (Lindauer, 1989) or voluntary control (Ulrich and Ammons, 1959; Pelton and Solley, 1968). (3) Active observation of the SAM (also 9-min duration): this experiment was performed immediately after naive observation of the SAM (same subjects). The subjects were informed about the perceptual switching and they were instructed to press the button immediately following switching. The button press served as a marker for separating two different phases in this condition: - Reversal phase: this phase contains the 1 s preceding the button press. This time window encloses the presumed instability-phase prior to switching, the switching itself, and the reaction time needed for pressing the button. Thus, the reversal phase is considered to represent a destabilized state of the perceptual system. (The contamination of premovement potentials in this phase will be discussed separately in Section 4.3.). Non-reversal phase: this phase was made up of the third second after the button press to ensure that the motor potentials following the button press have relaxed. This time window contains no perceptual switching so that the non-reversal phase is considered to be a stable state of the perceptual system. Fig. 2 illustrates the time course of occurrence of the reversal and non-reversal phase of the third condition. l

2.5. Data analysis Selective averaging and artifact rejection of data: for the elimination of artifactual trials, first an on-hne artifact rejection procedure is applied in addition to the manual off-line selective averaging procedure. An automatic on-line artifact rejection procedure is used for the elimination of global artifactual EEG epochs. These epochs contain movement artifacts, excessive muscle activities and the epochs whose amplitude exceeded 50 PV at any electrode. Addi-

117

WSTABLE STATE I

STAELE STATE t

I

-sdu

I

I

I

-4s

-3

-2

,AmLB, 1 I ,

r

-I

2

y

I

i 3

4s

Fig. 2. Two selected time windows for the evaluation of the EEG data during active observation of stimulus pattern by informed subjects. (A) Reversal phase (perceptual switching): the RMS values of gamma band (30-50 Hz) were evaluated in the time window - 1000 ms to 0 ms. T = 0 ms indicates finger-movement onset. (Et) Non-reversal phase: 2 s after finger-movement onset.

tionally, in an off-line procedure, the on-line recorded, digitized and stored single artifact-free EEG epochs were selected. The EOG channel was visually inspected for each trial, and trials with eye movement or blink artifact were rejected. On average, 70% of the 120 epochs per experimental condition were analyzed. The methodology to evaluate the averaged EEG data, power spectrum, amplitude frequency characteristics (AFC) and digital filtering methods were previously described (Bagar, 1980; Bagar-Eroglu et al., 1992). The method we used here was basically the same except for minor modifications. DigitaEfiltering: the gamma-band limits have been selected after the inspection of the power spectra/AFCs of each subject in each location. The center frequencies of the gamma peaks varied between 35 and 45 Hz in different subjects and in different locations. Therefore, a broad gamma-band filtering between 30 and 50 Hz has been carried out on the data. Thus, all these varying peaks were included into further analysis and possible artifacts induced by narrow band filtering were avoided. Evaluation of the root mean square (Rh4S) values: after digital filtering of single trials (30-50 Hz), the absolute RMS values for 1 s were first computed and averaged for each location and experimental condition. For a discrete time series X, the RMS value is computed as follows: /IN-I

\I/’

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118

2.6. Statistical

N=l

analysis CONTROL-EEG

The artifact-free single EEG epochs were digitally filtered in gamma band (30-50 Hz). Following this step, RMS amplitude values of single EEG epochs, lasting 1000 ms each, were evaluated and averaged for every location and experimental condition. The differences between experimental conditions and electrode sites were tested by means of a non-parametric analysis of variance (Friedman’s two-way analysis by ranks with post-hoc Wilcoxon-Wilcox tests, Lienert, 19861, since the data do not appear to be normally distributed. The significance values below 0.05 are given in the figures.

NAIVE OBSERVATION F4 single

sweeps

(30-50Hz)

=

3. Results Fig. 3 shows representative results of one subject at F4 location. The dashed line presents the power spectrum computed from spontaneous EEG (control) and the solid line presents AFC computed from the data recorded during the naive observation of the SAM. The gamma band was increased in the region at F4 for 2-3 dB during naive observation of SAM in comparison to the spontaneous EEG. Fig. 4 presents 30-50 Hz filtered single sweeps of one subject from two experimental conditions [A: spontaneous EEG (control), B: naive observation of SAM]. In the control condition the maximum amplitude of the 40 Hz activity reached values only up to 10 pV, whereas in the second experimental condition the amplitudes were drastically increased (factor

F4

1

5 10

50Hz

Fig. 3. The frequency analysis. Dashed line: spontaneous-EEG (control); solid line: naive observation of SAM in a representative subject. n-axis: frequency in logarithmic scale; y-axis: Amplitude in relative units (dB).

0

500

1oLmoc

ms

0

500

1000

1500

2000 ms

Fig. 4. Single EEG epochs digitally filtered in the gamma band (30-50 Hz) at F4 location. Left column: single epochs of controlEEG. Right column: single EEG epochs during the naive observation. In this experimental condition the epochs contain both reversal states and non-reversal states. The subjects were required to observe SAM pattern without task. Note that all the subjects have reported towards the end of the experiment that they detected the perceptual switching of the pattern presented.

1.5-3) during naive observation of SAM pattern. Furthermore, in this case not only peak-to-peak amplitude values were increased, but also the duration of 40 Hz oscillatory wave-packets has become longer. These observations led us to compute RMS values in the gamma band for all the locations from each subject. These computations provide a distribution of gamma bands, acquired by means of considering amplitudes and duration of EEG activity in the gamma-frequency range. In other words, an increase in RMS values would reflect an increase in amplitude, duration and occurrence of 40 Hz oscillations. We must emphasize here that the amplitude increase can be better observed in the single subjects than the mean value of 11 subjects, which is presented in Table 2, because of the averaging process of the RMS values.

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24 (1996) 113-125

RMS30-5OHz K-**

o_

*

1 0

F3 0

F4

C3

Control - EEG

Cz

C4

P3

P4

01

02

@@j Naive Observation

Fig. 5. The mean RMS value histograms of 11 subjects obtained in all locations. The y-axis represents the RMS mean values in kV. The 40 Hz RMS values due to SAM pattern differ significantly between scalp locations (p < 0.001). The RMS values at F3, Cz, C4 (p < 0.05) and at F4 (p < 0.001) are significantly higher than control experiments. Significance levels: * p < 0.05, * * * p < 0.001. Bars represent standard error.

Fig. 5 shows the mean RMS value histograms of 11 subjects measured in two different experimental conditions from all scalp locations. As can be seen, the amplitude of 40 Hz activity is highest at frontocentral locations during multistable perception of SAM in naive subjects. The differences between scalp locations were highly significant ( p < 0.00 1). Values of 40 Hz activity at F3, Cz, C4 (p < 0.05) and F4 (p < 0.001) were significantly higher during the naive observation of SAM than during the control EEG (Friedman two-way analysis by ranks). Fig. 6 is an extension of Fig. 5 with the RMS values of 40 Hz activity during the perception of SAM with a task (active observation). The subjects were instructed to press the button immediately after perceptual switching (task). The RMS values were computed for a duration of 1 s before finger-movement onset, during the period, in which perceptual

P3

P4

01

02

Fig. 6. Histograms of grand average RMS values in /JV of three different experimental sessions of 11 subjects. The RMS values were computed for 1 s. The differences between scalp locations were highly significant ( p < 0.001). The amplitude distributions of 40 Hz RMS values for the four experimental conditions also differ significantly (p < 0.001). The RMS values in experiments of naive observation and in the reversal phase differ significantly from control experiment at F3, Cz, C4 and F4 (p < 0.05. Wilcoxon-Wilcox test). Bars represent standard error.

switching occurred (reversal phase). We also evaluated the data 3 s after finger-movement onset again for 1 s duration (non-reversal phase). Although non-

Table 2 Percentual increase of 40 Hz RMS mean values of three experimental conditions informed subject vs. in naive observation by naive subjects. n = 11)

vs. control-EEG

(note the increase in active observation

Locations

EEG/naive EEG/active EEG/active

observation (o/o) observation (%) (reversal phase) observation (%I (non-reversal phase)

F3

F4

C3

CZ

c4

P3

P4

01

02

30.4 34.1 10.8

36.1 48.9 19.1

18.4 18.4 5.26

16.0 - 10.7 1.78

27.5 30.0 17.5

15.6 31.2 18.7

17.1 25.7 17.1

5.1 28.2 20.5

7.1 23.8 9.5

by

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reversal phase begins immediately following button press, we selected this time window (cf. Fig. 2, phase B) in order to eliminate the post-motor potentials. In this state the subjects perceived SAM pattern either in a horizontal direction or vertical direction without switching. The differences of 40 Hz activity between experimental conditions were significant at F4 location ( p < O.OOl), F3, Cz and C4 location (p < 0.05), i.e. the 40 H z partition was more extensive in the reversal phase. A similar trend, although nonsignificant, is seen for parietal and occipital locations. Significant differences were found between experimental conditions (Wilcoxon-Wilcox test) at the F4 location (EEG vs. naive observation, p < 0.05 and EEG vs. reversal phase, p < O.OS>, at the F3 location (EEG vs. naive observation, p < O.OS>, and at the Cz location (naive observation vs. reversal phase, p < 0.05). However, at the Cz location the 40 Hz activity was decreased (p < 0.05). Furthermore. the increase of 40 Hz activity was significantly higher on the right hemisphere than left hemisphere during all the experimental conditions, except the control EEG. Table 2 presents the percentual increase of 40 Hz RMS mean values of three experimental conditions vs. control EEG. As can be seen, during naive observation as well as during active observation, the percentual increase of gamma band is highest at the frontal location.

4. Discussion As will be discussed below, only few reports describe brain electrical activity during multistable perception. In the present report, the results indicate strong increases in the amplitude of gamma band with a chain of interwoven experimental steps. There is an increasing interest in search of psychophysiological correlates of the gamma band, and in the last decade a large amount of data from various research groups and directions have been accumulated. Accordingly, for an appropriate interpretation of the results in multistable perception, the recent findings on functional correlates of 40 Hz activity must be incorporated in our discussion (see also Bagar-Eroglu et al., 1996, in this issue, for an actual review of the 40 Hz brain activity).

4.1. Functional perception

interpretation

of the gamma band in

Freeman (1975) emphasized that the 40 Hz wave-packet has a key function in perceptual models of the olfactory bulb of the rabbit. Freeman (1975) and Freeman and Skarda (1985) have shown that the EEG of the olfactory bulb and cortex in awake and motivated rabbits and cats shows a characteristic temporal pattern consisting of bursts of 40-80 Hz oscillations, superimposed on a surface negative baseline potential shift coupled to each inspiration. Gray and Singer (1987, 1989) and Gray et al. (1989) have reported that neurons in the cat visual cortex exhibit oscillatory responses in the frequency range of 40 to 60 Hz. These oscillations occur in synchrony with cells located within a functional column and are tightly correlated with local oscillatory field potentials. Based on these results, Gray and Singer ( 1989) proposed that the synchronization of oscillatory responses of spatially distributed, feature-selective cells might be a way to establish relations between features in different parts of the visual field. E&horn et al. (1988, 1989a,b,1992) also found stimulus evoked resonances of 35-85 Hz throughout the visual cortex when the primary coding channels were activated by their specific stimuli, and raised the question whether coherent oscillations do reflect a mechanism of feature linking in the visual cortex. Related to these findings (Eckhom et al., 1988) obtained with neurophysiological methods, Kojo et al. (1993) reported psychophysical experiments concerning the spatial and temporal properties of illusory figures. They demonstrated that the illusory Kanizsa triangle could be seen although only one inductive element was present at any time. This spatiotemporal window - within which the illusion is visible - was related to the synchronized gamma waves. The authors suggest that two different brain locations where gamma waves are synchronized would activate the ‘neurons’ between them and cause the illusory contours. Lutzenberger et al. (1995) published that the visual stimulation alters local 40 Hz responses in humans. Their results show that the neuronal 40 Hz responses from occipital lobe are a correlate of the perception of coherent visual patterns in humans. During selective somatic attention, Desmedt and

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Tomberg (1994) demonstrated a transient phaselocking of the gamma waves generated in the contralateral prefrontal and parietal cortical areas in spite of their wide separation. The phase-locking started about 130 ms after the finger stimulus, stayed phase-locked for about 125 ms and then desynchronized until after the reaction time and P300-closure. It can be seen from the above examples and the results of the present study that the gamma-band activities can be recorded in different brain structures of different species with seemingly different functional and behavioral correlates. This rhythm has also different dynamics in various structures and under different experimental conditions: it exists spontaneously and/or can be evoked, induced or emitted with different latencies and relations to sensory-cognitive events (see BaSar-Eroglu et al., 1996, this issue).

4.2, Interpretation ception

of 40 Hz during multistable

per-

4.2. I. Frontal 40 Hz. activity and multistable perception The results of the present report demonstrating a prominent increase of 40 Hz RMS values of approximately 40-50% in frontal locations, can be associated with several cognitive mechanisms. (a) The perceptual switching itself is one important factor giving rise to 40 Hz enhancement. The task was unpredictable, has low probability, and therefore the subjects reported the need for great concentration and attention. In our recent studies, we have shown that during reversal phase, a positive slow wave occurred in all the locations. This positivity in right parietal locations had a greater amplitude in comparison to the other scalp sites. The low frequency components of this positivity have a similarity to the frequency content of stimulus-locked P300 wave and 40 Hz frequency component was increased. (b) Furthermore, during observation of SAM, the subjects are in a state of increased or focused attention prior to the recognition of perceptual switching. (c) Since all subjects have reported that they detected perceptual switching during the naive observation, a ‘leaming task’ probably also contributed to recorded electrophysiological changes. (d) Decision-making

121

mechanisms might also play an important role for the enhanced 40 Hz. It is probably not possible to interpret whether all of the above indicated behavioural tasks contributed to the 40 Hz activity. In connection with these straightforward interpretations, the perception itself or focussed attention increase of 40 Hz activity have been confirmed by several papers. The role of the learning effect can be confirmed only with new experiments. A differentiation of 40 Hz increase during observation of SAM is possible by comparing both paradigms used in this report: (1) In naiue subjects the increase of RMS 40 Hz is not as strong as the increase during perceptual switching in informed subjects. These results indicate that the naive observation of reversal and nonreversal states already elicits a testable, marked physiological change in the state of the brain. These changes can be attributed to learning effects and also to the discovery of a new, yet unknown event. However, the 40 Hz increase in the fronto-central area cannot be explained only with attention or increased vigilance since the 40 Hz increase in naive subjects observing the perceptual switching (without any knowledge) is higher than 40 Hz responses during the non-reversal phase (stable state) in informed subjects (Fig. 6, compare second and fourth columns). In this recorded gamma-amplitude increase, effects of pattern reversal probably play an important role. Accordingly, it can be stated that the multistable perception clearly induces an energy increase in the gamma band. (2) The informed subjects press a button, following the perceptual switching. Then the EEG-epochs 1 s prior to finger-movement onset are analyzed. These data indicate the highest RMS values in the gamma band. Percentual increases up to 48% are recorded in the frontal area during the perceptual switching (reversal phase) in informed subjects. It can be assumed that during this state subjects are highly motivated to detect pattern reversal and are in a highly increased selective-attention state. In this observation state, the contribution of selective attention in informed subjects is probably greater than in naive subjects. In fact, the induced 40 Hz increase reaches the maximal levels during the reversal phase. Tiitinen et al. (1993) reported that selective atten-

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tion enhances the auditory 40 Hz transient response in humans, especially over the frontal and central areas. The 40 Hz response was larger when subjects paid attention to stimuli rather than ignored them, so that they demonstrated a physiological correlate of selective attention in the 40 Hz transient response in humans. This interpretation supports our results during perceptual switching, although the 40 Hz activity evoked by SAM is endogenously induced and not stimulus driven. (3) Non-reversal phase in informed subjects: immediately after the finger-movement onset (t = 0), the non-reversal phase begins. This means, for a short period of time, subjects do not observe pattern reversal. In this stable phase, the 40 Hz activity in frontal and central locations is decreased in comparison to the other experimental conditions, in which the perceptual switching occurred (compare Table 2 and Fig. 6). The 40 Hz activity during the non-reversal phase is slightly higher than control EEG (approximately up to 5-20% in all recordings). This effect is, however, not surprising since the subjects are certainly in a state of higher vigilance because of the expectation of the next perceptual switching.

4.2.2. Why is the most dominant increase of 40 Hz over the frontal areas? Fuster (1989) reported that “the greater the attention to the stimulus, the greater is the activation of the prefrontal area activated by it”. This has been experimentally demonstrated by instructing subjects to expect or merely imagine the stimulus in a certain sector of the sensorium. A possible interpretation with higher reaction of frontal activity is as follows: during perceptual switching the sensation of patterns in receptive fields is amplified by signal processing over visual association areas and all visual processing signals finally reach the frontal cortex, which is a multimodal association area per excellence. A necessary extension to this hypothesis is that the hippocampal-frontalparietal system would be involved as a loop. BasarEroglu and BaSar (1991) reported a significant 40 Hz response in CA3 layer of the cat hippocampus superimposed to a P300 response thus indicating increase of the hippocampal 40 Hz activity during cognitive processes. Since in the present report scalp record-

ings are measured, the link to hippocampus cannot be directly demonstrated. The findings of O’Donnell et al. (1988) already mentioned in Section 1, showed that the late positivity to illusory reversal was also distinguished by a broad (200-700 ms) positive component over frontal and central recording sites which was absent over oz. Lang et al. (1986) reported electrophysiological evidence for right frontal lobe dominance in spatial visuomotor learning. They compared various visuomotor tasks and they found a positive correlation between the enhancement of negativity by slow cortical potentials and the success in motor learning. There is evidence from neuropsychological findings that patients with frontal brain lesions show significant changes in the rate of apparent change (RAC) when viewing reversible figures. Cohen (1959) reported an increase of RAC in case of bilateral frontal lesion, while unilateral frontal lesion produced a significantly decreased RAC. Ricci and Blundo (1990) found in patients with unilateral frontal and posterior brain damage that frontal patients exhibited greater difficulty in shifting from one aspect of an ambiguous figure to the other than did patients with more posterior lesions and control subjects. The results of the present study - the enhanced frontal 40 Hz activity during the perceptual switching gives neurophysiological evidence for frontal lobe activity in multistable perception. 4.3. Contributions of motor potentials activity during multistable perception

to the gamma

Studying 40 Hz EEG needs special efforts to differentiate between brain and muscle activity. In our study, the influence of muscle activity can be ruled out because the increase in 40 Hz oscillations was found primarily during naive observation of the SAM. Furthermore, in this case, not only the amplitude value of gamma band was increased, but the duration of gamma-band oscillations has become longer. We should emphasize that this experimental session contains neither planning of finger movement nor motor task with pressing the button. Therefore, the increase in gamma-band activity cannot be influenced by muscle activity during naive observation of multistable pattern.

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Although in the second experimental session, the informed subjects were required to press the button immediately following switching, the increase in gamma-band activity was found before finger-movement onset. In this study, the epochs with fingermovement onset were eliminated, but in our recent study we could show that the gamma-band activity was suppressed during the finger movement (BaSarEroglu et al., 1995). Similar results were reported by Pfurtscheller (1994). Because of technical limitations, we were only able to digitize and spectrally analyse the EMG first in a new pilot study in seven subjects. We found the maximum of premovement muscle activity at 60-80 Hz. Furthermore, we observed an enhancement of amplitude at 60-80 Hz frequency range during movement onset (unpublished observations). Our results are mentioned here only for a short discussion, in order to exclude possible interference of EMG. Special reports on muscle activity and 40 Hz will be published separately. Also, Cacioppo et al. (19901 reported the spectral power of EMG response increases with a frequency of at least 80 Hz. We would like to emphasize here that in our present study, none of the evaluated epochs contain button press. Therefore, we can rule out the contamination of muscle activity in the reported results. The reversal phase entails only the planning of finger movement. Planning of finger movement involves different cortical regions such as motor, premotor, supplementary motor (SMA) as well as somatosensory areas (Pfurtscheller and Neuper, 1992; Pfurtscheller et al., 1994). The authors reported the 40 Hz synchronization during voluntary finger movements. Recently, we published the comparative data from two different experiments in seven right-handed subjects: (a) during perceptual switching and (b) during voluntary finger movement. The results showed that during perceptual switching - within 1 s before finger movement - the amplitude of 40 Hz activity was higher than during the finger-movement onset. The opposite changes were observed in motor potentials. The amplitude of gamma band of the motor potentials was decreased prior to voluntary finger movement and increased after movement onset, as was to be expected (BaSar-Eroglu et al., 1995). 40 Hz EEG during motor programming was reported over central and parieto-occipital areas,

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whereby a significant increase in 40 Hz waves over the left hemisphere during right-handed motor programming was found (De France and Sheer, 1988), and integrated in a cognitive model of attention by Sheer (1989). Jokeit and Makeig (1994) have measured different event-related patterns of gamma-band power of fast and slow reacting subjects by means of FFT. They suggested that two different modes of auditory-response processing underlie subject reaction time differences, supporting claims that 40 Hz activity has functional significance in sensomotor processing. In our study, the increase in gamma band was significant at the F3, F4, C4 locations, during naive observation and also during reversal phase. Therefore, it is unlikely to explain the significant increase of right frontal 40 Hz activity only with motor potentials, because the gamma-band increase occurred during naive observation, where no motor task was required by the subjects. Furthermore, during reversal phase with motor task, the significant increase of gamma band was not contralateral, but ipsilateral, except in F3.

5. Conclusion The results of the present report demonstrating a prominent increase of gamma band RMS values in frontal locations, can be associated with several cognitive mechanisms. The perceptual switching itself is the most important factor giving rise to the 40 Hz enhancement as can be seen from the approximately 50% increase of 40 Hz RMS values in the reversal phase compared with spontaneous EEG at F4. Also, at the other locations (except Cz), the highest RMS values in the gamma band are recorded during active observation of the SAM in the reversal phase, indicating that the gamma band is related to the destabilization of the perceptual system when viewing multistable patterns. Other cognitive factors such as focused attention, detection, decision making, learning and memory contribute in different degrees to the 40 Hz increase in the various experimental conditions in this study. Thus, it can be concluded that multistable perception is one of several cognitive processes giving rise to 40 Hz enhancement in the EEG.

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Acknowledgements This research was supported by a grant from the Deutsche Forschungsgemeinschaft (No. RO 48 l/ 1 l1, Project 6). We are grateful to Dr. T. Demiralp, Dr. J. Yordanova, Dr. V. Kolev and Dr. M. Schlrmann for valuable discussion of results and help for statistical analysis. Our thanks to Ing. F. Greitschus for expert software development, to Ing. M. Gehrmann for technical help, and to K. Hoyler for excellent technical assistance. We would also like to thank B. Ranwig for careful reading of the manuscript and her secretarial help.

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