Oscillatory Brain Activity as Underlying Neural Mechanism of Human Memory

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Oscillatory Brain Activity as Underlying Neural Mechanism of

Human Memory

Dissertation

zur Erlangung des akademischen Grades des Doktors der Naturwissenschaften

an der Universität Konstanz Naturwissenschaftliche Sektion

(Fachbereich Psychologie)

Thomas Gruber

Schönaich

Tag der mündlichen Prüfung: 22.03.2002 1. Referent: Prof. Dr. Matthias Müller

2. Referent: Prof. Dr. Thomas Elbert

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 1

Danksagung

An erster Stelle möchte ich Professor Dr. Matthias Müller danken. Über die Jahre, in denen ich mit ihm zusammengearbeitet habe, war er mir Kollege, Förderer, Mentor und Freund.

Weiterhin gilt mein Dank Professor Dr. Thomas Elbert. In meiner Konstanzer Zeit, aber auch über den Ärmelkanal hinweg, stand er mit fachlich fundiertem Rat zur Seite.

Für die Datenerhebung in Konstanz bedanke ich mich bei Eva Bonna. Für die Hilfe bei der Auswertung gilt mein Dank Dr. Markus Junghöfer. In Liverpool war Heidi Messner für die Datenerhebung verantwortlich. Mein Dank an Sie gilt aber auch und vor allem der Tatsache, dass Sie es mir leicht gemacht hat, mich in England einzuleben.

Vielen Dank auch an Nicola Williams, die mein Englisch geduldig verbessert hat und noch verbessert und an Dr. Peter Malinowski, der ein exzellenter Kollege ist.

Ein ganz besonderer Dank gilt natürlich meinem „alten“ Kollegen und Freund Dr.

Andreas Keil, ohne den viele der vorgestellten Publikationen nicht zustande gekommen wären.

Meiner Familie gilt mein Dank für Ihre Unterstützung während meines Studiums und während meiner Promotion.

Claire-Marie Giabbiconi danke ich für den ganzen Rest und noch viel mehr...

Thomas Gruber

Liverpool im November 2001

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Summary / Zusammenfassung

Summary

In 1949, the famous Psychologist Donald Hebb proposed that learning is accomplished by dynamical binding of cell assemblies. Neuronal synchronization in the gamma band range is discussed as a plausible mechanism to integrate the activity within and between the elements of such a network. The main goal of the studies described in this thesis, was to examine if oscillatory activity in the human electroencephalogram is a signature of different memory processes. In particular the focus was directed on the formation of a cell assembly due to operant learning, implicit recall of a cell assembly due to perceptual learning or perceptual priming, repetition suppression (repetition priming), explicit recall due to short-term memory, and associative learning. Using multi-channel electroencephalography the following results were found: Firstly, the formation of a cell assembly led to an integration of activity within and between task specific modalities. Secondly, implicit recall processes led to an activation of a cell assembly, which stores the features of a percept close to the cortical areas that mediate the perception of those features. Finally, in contrast to implicit memory, explicit forms of memory recall activated a cell assembly, which included the storage sites of a learned percept and related higher order monitoring areas.

From this series of studies, it was concluded that memory recall and formation is indeed based on cell assemblies, which are established by neuronal synchrony amongst their elements. Induced gamma band responses and phase synchrony are a signature of activity within such a cell assembly in the human electroencephalogram.

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 5 Zusammenfassung

Der bekannte Psychologe Donald Hebb postulierte 1949, dass Lernen durch das dynamische Zusammenbinden von Zellverbänden verwirklicht wird. Neuronale Synchronisation im Bereich des Gammabandes wird als plausibler Mechanismus diskutiert, um die Aktivität innerhalb und zwischen den Elementen eines solchen Netzwerkes zu integrieren. Das Hauptanliegen der in dieser Arbeit vorgestellten Studien war es zu untersuchen, ob oszillatorische Aktivität im Elektroenzephalo- gramm des Menschen eine Signatur verschiedener Gedächtnismechanismen ist.

Insbesondere wurden folgende Mechanismen untersucht: Die Formation eines Zellverbandes aufgrund operanten Lernens, der implizite Abruf eines Zellverbandes infolge perzeptuellen Lernens (perzeptuelle Bahnung), Repetitions-Unterdrückung („repetition suppression“), der explizite Abruf von Information aus dem Kurzzeitgedächtnis und assoziative Lernmechanismen.

Die Verwendung hochauflösender Elektroenzephalographie ergab, (1) dass die Formation eines Zellverbandes zur Integration von Aktivität innerhalb und zwischen aufgabenrelevanter Modalitäten führt. (2) Implizite Abrufprozesse zur Aktivierung eines Zellverbandes führen, der die Merkmale eines Objektes nahe den kortikalen Arealen speichert, die diese Merkmale verarbeiten. (3) Weiterhin ergab sich, dass im Gegensatz zu impliziten Gedächtnisprozessen, explizite Formen des Gedächtnisses nicht nur den Speicherinhalt für ein gelerntes Perzept aktivieren, sondern auch höhere Kontrollareale.

Aufgrund dieser Serie von Untersuchungen wurde gefolgert, dass der Abruf und die Formation von Gedächtnisinhalten auf kortikalen Zellverbänden basiert, die über neuronale Synchronisation etabliert werden. Induzierte Gammabandantworten und

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 6 Phasensynchronisation sind ein Korrelat solcher Zellverbände im Elektroenzephalo- gramm des Menschen.

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List of relevant Publications

For reprints see Appendix.

Gruber, T., Keil, A., Müller, M. M. (2001). Modulation of Induced Gamma Band Responses and phase synchrony in a paired associate learning task in the human EEG. Neuroscience Letters, 316, 29-32.

Gruber, T., Keil, A., & Müller, M. M. (in press). Modulation of Induced Gamma Band responses in a perceptual learning task in the human EEG. Journal of Cognitive Neuroscience.

Gruber, T., & Müller, M. M. (in press). Effects of picture repetition on Induced

Gamma Band responses, evoked potentials, and phase synchrony in the human EEG. Cognitive Brain Research.

Gruber, T., Müller, M. M., Keil, A., & Elbert, T. (1999). Selective visual-spatial attention alters induced gamma band responses in the human EEG. Clinical Neurophysiology, 110, 2074-2085.

Keil, A., Müller, M. M., Gruber, T., Wienbruch, C., Elbert, T. (2001). Human large- scale oscillatory brain activity during an operant shaping procedure. Cognitive Brain Research, 12, 397-407.

Keil, A., Gruber, T., & Müller, M. M. (2001a). Functional correlates of macroscopic high-frequency brain activity in the human visual system. Neurosci Biobehav Rev, 25(6), 527-34.

Müller, M. M., Gruber, T., Keil, A. (2000). Modulation of induced gamma band activity in the human EEG by attention and visual information processing.

International Journal of Psychophysiology, 38, 283-299.

Müller, M. M., Gruber, T. (2001). Induced gamma-band responses in the human EEG are related to attentional information processing. Visual Cognition, 8(3/4/5), 579-592.

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General overview:

Oscillatory Brain Activity as Underlying Neural Mechanism of Human Memory

“In 1949, Donald Hebb predicted a form of synaptic plasticity driven by temporal contiguity of pre- and postsynaptic activity. This prediction was verified decades later [..] securing Hebb’s place in the scientific pantheon”

Sebastian Seung, 2000 (Seung, 2000)

Introduction

One of the more fundamental puzzles in neuroscience is how the brain integrates its disparate network activities. This question is commonly referred to as the ‘binding problem’. For example, in the visual modality object and scene recognition is built up in a series of stages in which primitive features of the visual image (colours, spatial frequencies, direction of motion) are first extracted and coded independently, and then reintegrated to a coherent perceptual unity. In particular, cortical visual processing for object recognition is considered to be organized as a set of hierarchically connected cortical and subcortical regions consisting at least of the LGN (lateral geniculate nucleus), V1, V2, V3, V4, V5, posterior inferior temporal cortex, inferior temporal cortex, anterior temporal cortex and parietal areas (Rolls, 1995). From each small part of a region there is convergence to the succeeding region

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 9 in such a way that the receptive field sizes of neurons become larger with each stage within this hierarchy (Felleman & van Essen, 1991). Visual pathways project from the retina to the LGN, further to the primary visual cortex until they reach the temporal and parietal lobe visual areas (Baizer, Ungerleider, & Desimone, 1991; Livingstone &

Hubel, 1988; Tootell, Dale, Sereno, & Malach, 1996; Zeki, 1993). These cortical pathways can be described as two major streams of information processing. The ventral pathway is thought to be specialized for the analysis of object features like colour and shape, while the dorsal pathway is specialized for the analysis of motion and spatial relationship between objects (Roland, Gulyas, Seitz, Bohm, & Stone- Elander, 1990; Ungerleider, 1995; Ungerleider & Haxby, 1994). A schematic overview of visual areas and pathways is given in Figure 1.

Figure 1: Schematical representation of the hierarchical organisation of the visual system. A:

Major streams of information processing in the human brain. B: Areas V1 (in grey), V2, V3, V4, and V5 in the macaque brain (Zeki, 1993).

Given these assumptions, the question arises as to the mechanism that integrates the neuronal activity within and between the elements of such a network.

primary visual areas

A B

dorsal stream

ventral stream

primary visual areas

A B

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 10 A powerful associative mechanism was proposed in 1949 by Hebb (Hebb, 1949), which stated that specific functions of different brain areas are integrated by dynamical binding of neuronal assemblies. Hebb argued that an association could not be localized to a single synapse. Instead, neurons have to be grouped in ‘cell assemblies’, and an association is distributed over their synaptic connections. A Hebbian cell assembly can be formed on the basis of the simple rule: ‘cells that fire together wire together’. Furthermore, Hebb believed that sensory stimulation could initiate patterns of neural activity maintained by ‘reverberatory activity’ within cortical cell assemblies. On a cellular level Hebb’s predictions were confirmed years later by two important findings: ‘delayed activity’ of neurons and ‘long-term potentiation’. Fuster and Alexander (Fuster & Alexander, 1971) found that certain neurons could be active during delays of many seconds, and encode information about the preceding stimulus. This delayed activity provided, for the first time, a candidate for the ‘reverberatory activity’. In addition, another important finding was the discovery of ‘long-term potentiation’ on a synaptic basis. If the postsynaptic side of a synaptic contact is inactive, the release of glutamate on the presynaptic membrane leads to an activation of non-NMDA (N-methyl-D-aspartate) receptors at postsynaptic membranes and to a depolarisation of the synaptic contact. However, if the postsynaptic side is already active (i.e. both neurons are active at the same time) an incoming impulse on the post-synaptic side leads to an activation of the NMDA receptor complex. This is followed by an uptake of calcium on the postsynaptic side and a diffusion of nitric-oxide (NO) from the dentritic side to the axonal side of a synaptic connection. This process is able to generate a persistent increase in synaptic strength (Bliss & Collingridge, 1993; Dawson, Dawson, & Snyder, 1992).

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 11 A further important step to verify Hebb’s ideas is based on theoretical considerations by von der Malsburg and Schneider (Malsburg & Schneider, 1986).

They argued that spatially separated cortical areas encoding different features of an object are represented in the brain by synchronization of neural firing (‘neuronal synchrony’) of these areas. It has to be mentioned that Hebb’s and Malsburg’s hypotheses were similar in the sense that both of them asserted that the function of each region in the brain is integrated by dynamical binding of neuronal assemblies, although, Hebb’s original idea can lead to a ‘superimposition catastrophe’ (Malsburg

& Schneider, 1986). That means that different objects in the visual field activate modality specific cells in the cortex, but it is not possible to distinguish which pattern of activity belongs to which object. Therefore, von der Malsburg’s hypothesis of binding by temporal synchrony extended Hebb’s assumptions by the idea that neurons synchronize their pattern of activity for coding features of the same object, but not for features of another object.

The idea of synchronized cortical activity was not widely accepted until two independent laboratories in Germany conducted experimental studies that supported the theory. Using anesthetized cats, Eckhorn et al. (Eckhorn et al., 1988) and Gray et al. (Gray, König, Engel, & Singer, 1989) found that firing of neurons in the primary visual cortex, oscillates stimulus-dependent and the oscillatory firing is synchronized under certain stimulus conditions in a high frequency range above 20 Hz, i.e. the gamma band. Furthermore, they found that!"hese synchronized oscillations are neither phase- nor time-locked to stimulus onset, thus, they are termed induced gamma band responses (GBRs). In Figure 2 an example of the properties of induced gamma band responses is depicted. Due to the jitter in latency of induced responses in single epochs (Figure 2-A), these responses are averaged out in the averaged evoked

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 12 response (Figure 2-B) (Eckhorn, Reitboeck, Arndt, & Dicke, 1990). Furthermore, in this example the first burst of induced gamma activity appears in a latency range of approximately 400-600 ms after stimulus onset, and the variance in frequency and duration of ‘bursts’ is nicely shown.

Figure 2: Stimulus specific synchronization in cat visual cortex Area 17 and Area 18. A:

Local field potentials of single trials. B: Averaged local field potential. Whereas the visual evoked potential (VEP) is pronounced, induced activity in 60 and 53 Hz band is averaged out (reproduced from (Eckhorn et al., 1990)).

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In the original version of the temporal binding hypothesis, synchronized neuronal activity is thought to be related to ‘feature binding’ or ‘perceptual integration’, i.e. the integration of different aspects or features belonging to one perceived object or visual scene (Singer & Gray, 1995). However, as argued above, early feature integration and large-scale integration of higher cognitive functions such

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 14 as language processing, emotional evaluation or memory processes might share the same mechanism but at opposite ends of the spatial continuum (Varela et al., 2001). In particular, regarding memory processes it has been emphasized that an increase in synchronized activity between cortical areas could fulfil the criteria required for the formation of Hebbian cell assemblies. Thus, synchronized neuronal activity might be a crucial pre-requisite for different types of learning and memory (Miltner, Braun, Arnold, Witte, & Taub, 1999; Pulvermüller, Birbaumer, Lutzenberger, & Mohr, 1997). Furthermore, a cell assembly has not only to be consolidated during memory formation, but also activated during the recall of a learned percept. Since object knowledge seems to be stored in a distributed cortical system in which information regarding specific features of a perceptual entity are stored close to the regions of cortex that mediate the perception of those features (Martin, Haxby, Lalonde, Wiggs,

& Ungerleider, 1995), oscillatory activity in the respective assembly might be a correlate of the activation of a learned percept (Pulvermüller, Keil, & Elbert, 1999).

Based on the assumption that oscillatory brain activity might be an underlying mechanism of human memory, the main goal of the studies described in this thesis was to examine if oscillatory activity in human EEG is a signature of different memory processes¹. The choice of experimental paradigms used to study different types of memory was guided by a memory taxonomy proposed by Graf and Schacter (Graf & Schacter, 1985). In brief, they proposed that implicit forms of memory can be clearly dissociated from explicit recollection processes (Schacter & Badgaiyan, 2001;

Schacter, Buckner, & Koutstaal, 1998). Whereas implicit memory can be described as a facilitation of performance in an automatic fashion (Schacter, 1987), explicit

1 It has to be mentioned that four of the studies, which will be presented in this overview, were carried out in our own laboratories in Konstanz and Liverpool, whereas two studies were performed by other groups working in the field of high-frequent brain activity.

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 15 memory comprises mechanisms related to intentional recall processes. According to Schacter the first largely reflects changes in a cortically based presemantic perceptual re-presentation system (PRS), composed of several domain-specific subsystems, whereas explicit forms of memory might involve prefrontal areas (Schacter, 1992).

Prefrontal areas possibly monitor the activation of sensory representations in posterior processing areas (Chelazzi, Miller, Duncan, & Desimone, 1993; Miller, Li, &

Desimone, 1993).

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 16 Based on the hypothesis that memory recall and formation is based on cell assemblies, which are established by neuronal synchrony the following assumptions were made:

(1) Induced GBRs and phase synchrony are a signature of activity within a cell assembly representing a stimulus.

(2) The formation of a cell assembly should lead to an integration of activity within and between task specific modalities

(3) Implicit recall processes lead to an activation of a cell assembly, which stores the features of a percept close to the cortical areas that mediate the perception of those features. No higher order monitoring processes are necessary for such an automatic retrieval. Furthermore, a cell assembly established by synchronized activity underlies general mechanism in implicit learning (e.g. repetition priming).

(4) In contrast to implicit memory, explicit forms of memory recall should activate a cell assembly, which includes the storage sites of a learned percept and related higher order monitoring areas.

Figure 3 summarizes in an schematic fashion the different mechanisms in memory, their relation to the idea of Hebbian cell assemblies, and one possible paradigm to study the process. In particular the focus will be directed on: (I) formation of a cell assembly due to operant learning, (II) implicit recall of a cell assembly due to perceptual learning or perceptual priming, (III) repetition suppression (repetition priming), (IV) explicit recall due to short-term memory, and (V) associative learning.

It has to be mentioned that types of memories associated with deeper cortical structures such as the hippocampus (Eichenbaum, 1995; Eichenbaum, 1999), possibly

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 17 related to memories of more complex behavioural events, maps, scenes, etc., are not considered in this overview.

Operant learning

Short-term memory

Associative learning

I

IV

V

Figure 3: Five types of memory processes, one possible experimental paradigm to study the process, and the relation to the idea of Hebbian cell assemblies. Note: The neuronal network representing a stimulus is presented in a simplistic and schematic form. Solid black circles depict neurons that are an ‘active’ part of the assembly, white circles indicate ‘inactive’ neurons.

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 18 General Method

In the studies on human memory conducted in the laboratories in Liverpool and Konstanz, EEG was recorded using a 128 channel EEG-montage. Spectral changes in gamma band oscillatory activity during the experiment were analysed by means of a Morlet wavelet analysis of single experimental epochs. Single epochs were used for the analysis due to the properties of induced gamma band responses (see Figure 2). Wavelet analysis was used to overcome problems with constant FFT window length. This method provides a good compromise between time and frequency resolution (Sinkkonen, Tiitinen, & Naatanen, 1995), in particular time resolution of this procedure increases with frequency, whereas frequency resolution decreases. Thus, this technique is especially suited for detecting induced high- frequency oscillations that may occur during brief periods of time. The present procedure has been proposed by Bertrand and co-workers (Bertrand & Pantev, 1994) and is described in detail elsewhere, e.g. by Tallon-Baudry et al. (Tallon-Baudry et al., 1997; Tallon-Baudry et al., 1998) or in the Appendix of this thesis. Furthermore, it was suggested that phase synchrony between pairs of electrodes, independent of amplitude, provides a better measure of synchronized neural activity forming a cell assembly (Lachaux, Rodriguez, Martinerie, & Varela, 1999; Miltner et al., 1999;

Rodriguez et al., 1999). Therefore, phase synchrony analysis was performed elaborating on a procedure suggested by Rodriguez et al. (Rodriguez et al., 1999), which provides a method of measuring synchronous oscillatory activity independent of signal’s amplitude. For each subject phase synchrony was computed for a distinct frequency f0 of his/her maximal gamma activity. Phase is measured by convoluting the signal with a complex Morlet wavelet designed for f0. To provide a topographical representation of phase locking values over individual pairs of electrodes in a distinct

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 19 time window, a statistical randomisation technique was used. (See Rodriguez et al.

(Rodriguez et al., 1999) for a detailed description of the method see Gruber and Müller (Gruber & Müller, in press), and Gruber et al. (Gruber, Keil, & Müller, in press) (see Appendix) for our adaptation of the method).

Operant learning

(See also Appendix: Keil et al. (2001), Human large-scale oscillatory brain activity during an operant shaping procedure. Cognitive Brain Research)

To study the formation of a cell assembly and the relation to oscillatory brain- electric activity, we used an operant learning paradigm, which is presented in a schematic form in Figure 3-I). Induced gamma band responses were studied using a fixed-interval reinforcement schedule with a variable limited hold period, which was decreased depending on response accuracy. Thus, participants' behavior was shaped during the course of the learning session. After each response, numbers indicating the money value of that response served as reinforcing stimuli (see Figure 3-I, upper panel). Random reinforcement and self-paced button pressing without reinforcement were added as control conditions. Results showed a broad anterior distribution of the gamma band enhancement during shaping, possibly related to the emergence and consolidation of a cell assembly during the learning process (see Figure 3-I, lower panel). The frontal power increase observed during shaping might be specific for processing contingencies between behaviors and external stimuli with a behavioral or motivational relevance, i.e. reinforcers. This interpretation is consistent with the view that areas in the prefrontal cortex are elements of networks necessary for assembling memories and behavioral patterns that enable the individual to react appropriately on

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 20 the basis of past experience (Zald & Kim, 1996). In addition, it is in line with recent reports from neuroimaging studies showing prefrontal activation during associative learning (Molchan, Sunderland, McIntosh, Herscovitch, & Schreurs, 1994; Wagner et al., 1998). Furthermore, it is likely that pre-motor areas, which are involved in the processing of information that serves to adjust behavior to the changing requirements of the reinforcement schedule, have contributed to this finding. Similar phenomena have been reported with respect to oscillatory activity in this frequency range during execution of motor tasks in monkeys (Murthy & Fetz, 1992; Murthy & Fetz, 1996a;

Murthy & Fetz, 1996b).

In addition, results revealed a decrease of gamma power at electrode sites over visual areas due to repeated presentation of visual feedback stimuli. This gamma reduction is in line with the ‘repetition suppression’ phenomena described in the repetition priming study below. Although, we have not analyzed phase synchrony in this study, the presented findings give rise to the notion that macroscopic high- frequency dynamics of neuronal cell assemblies may be regarded as a mechanism involved in learning and memory formation.

Perceptual learning

(See also Appendix: Gruber et al. (in press). Modulation of Induced Gamma Band responses in a perceptual learning task in the human EEG)

Fragmented pictures of an object, which appear meaningless when seen for the first time, can easily be identified after the presentation of an unfragmented version of the same picture (Ramachandran, 1994). This process known as rapid perceptual learning, i.e. the facilitation in identification of fragmented pictures after prior

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 21 exposure has been described first by Leeper in 1935 (Leeper, 1935). We assumed that in a rapid perceptual learning task the features of learned objects are stored in a widespread cell assembly, which integrates activity across multiple visual areas. After learning took place, the fragmented version of a learned picture should activate this cell assembly and, thus, allow for identification of that fragmented picture (see Figure 3-II). To study this hypothesis we designed an EEG experiment using fragmented pictures from the Snodgrass and Vanderwart inventory (Snodgrass & Vanderwart, 1980), which could not be identified when seen in their fragmented version (Figure 3- IIa). However, when subjects saw the complete picture (Figure 3-IIb), they were easily able to identify the fragmented picture in the following sequence of the experiment (Figure 3-IIc). To allow for a control of processes independent of perceptual learning only half of the pictures were presented in their complete version.

For the drawings never presented in their unfragmented version subjects were not able to establish an unequivocal object representation.

Results showed an increase of spectral gamma power at parietal electrode sites related to rapid perceptual learning. In addition, neural activity in the gamma band was highly synchronized between posterior electrode sites. For pictures never presented in their complete version, no such pattern was found. The main results of the study are depicted in Figure 4.

Although somewhat speculative at present, we assume that the integration of activity across multiple visual areas might have contributed to our findings. The speculative nature of our assumption is based on the fact that scalp recordings do not allow us to draw direct conclusions on underlying cortical generators. However, an increase of activity in parietal and temporal areas was reported in human imaging and animal studies. Tovee et al. (Tovee, Rolls, & Ramachandran, 1996) reported an

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 22 increase in neurons firing rate using a rapid perceptual learning paradigm in temporal cortical visual areas in macaques.

Figure 4: A: Time frequency (TF) representations related to identified and unidentified pictures. B: Spherical spline interpolated topographies of the induce GBR peak. C:

Synchronies between electrode pairs for identified and unidentified pictures in the same time window. Lines are drawn only if the phase-locking value is beyond the distribution of shuffled data (p<0.01).

In an experiment using human PET, Dolan et al. (Dolan et al., 1997) showed an increase in activity in parietal and temporal areas after rapid perceptual learning. In a visual pattern memory study using PET, Roland and co-workers (Roland et al., 1990) reported an increase in activity in parieto-occipital areas during recall of stimuli. An interesting point is that we neither found a significant enhancement of gamma power at frontal electrode sites nor any significant phase locking from posterior to frontal electrode locations. We assume this is due to the more implicit nature of our task, i.e. the facilitation of performance without intentional recollection (Schacter, 1987). A similar lack of prefrontal activation was reported by Klingberg

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 23 and Roland (Klingberg & Roland, 1998) in an associative learning task. These authors speculated that the prefrontal cortex is not activated when retrieval is automatic.

Repetition suppression

(See also Appendix: Gruber and Müller (in press). Effects of picture repetition on Induced Gamma Band responses, evoked potentials, and phase synchrony in the human EEG)

As shown in our study on rapid perceptual learning, a cell assembly may be established by synchronized activity among the elements of the network in the gamma band range. Recently, Desimone (Desimone, 1996) suggested that a neuronal network representing an object’s features becomes sparser and more selective with repeated experience with the stimulus (repetition priming). He proposed that after repetition priming neurons show a decreased in firing rate, and thus, that they are dropping out of the population of activated cells coding the stimulus. This process might yield a more efficient cell assembly representing an object. Motivated by the hypothesis that repetition priming is based on such a ‘repetition suppression’ phenomena of neuronal activity, an experimental paradigm was designed, in which the modulation of induced GBRs and phase synchrony was investigated when line drawings were presented either once or consecutively two or three times. A schematic representation of the idea of ‘sharpening’ of a cell assembly is given in Figure 3-III (a, b, and c depict consecutive presentations of a stimulus). Due to the fact that the EEG measures large- scale macroscopic neuronal mass activity, we expected that a reduction in the number of neurons representing a stimulus should result in a decrease in induced gamma power and a sparser pattern of phase synchrony between electrode sites.

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 24 Results were found to be in line with our hypothesis. In particular, after the first presentation of a picture of an object, induced gamma power showed a significant increase above baseline level. Furthermore, synchronized activity was found between distant posterior cortical areas. After the second or third repetition of the same object we found a decrease in induced gamma power and phase synchrony between distant electrode sites. Figure 5 represents the main results of this study.

Figure 5: A: Time by frequency plots averaged across posterior electrode sites for initial and repeated picture presentations for the gamma frequency range. B: Synchrony (solid lines) and desynchrony (dashed lines) between 10-20 electrode pairs for initial and repeated picture presentations in the time window of the induced gamma peak and one time window before and after the peak. Lines are drawn only if the phase-locking value is beyond the distribution of shuffled data (p<0.01).

With respect to the topographical distribution of induced GBRs, we found a broad posterior distribution. Regarding this broad distribution and the pattern of phase synchrony the integration of activity across multiple visual areas might have contributed to our findings. The assumption of a synchronized cortical network involving widespread cortical areas fits well with our hypothesis on the establishment

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 25 of cell assemblies. However, as in our study on perceptual learning, we cannot draw direct conclusions on underlying cortical generators. On the other hand, the interpretation is in line with a decrease of activity in temporal and dorsal areas after repetition of stimuli as reported in human imaging studies (Fischer, Furmark, Wik, &

Fredrikson, 2000; James, Humphrey, Gati, Menon, & Goodale, 1999). Although the cortical basis of blood flow in the brain is still under discussion, recently Logothetis et al. (Logothetis, Pauls, Augath, Trinath, & Oeltermann, 2001) showed that the blood- oxygen-level-dependent (BOLD) signal directly reflects changes in neural electrical activity. Using fMRI, James et al. (James et al., 1999) showed a decrease of BOLD response in the occipito-temporal region and the intraparietal region for primed as compared to unprimed objects. In a study using PET, Fischer and co-workers (Fischer et al., 2000) reported a decrease in regional cerebral blood flow (rCBF) in both the secondary visual cortex and the right medial temporal cortex during the repetition of complex visual stimuli. Thus, it might be possible that the activity in similar cortical areas have contributed to our findings. In this context it is important to mention that although we found decreased gamma activity for repeated picture presentations as compared to initial presentations, gamma power was still above baseline level for repeated presentations, i.e. the stimulus is still represented in the cortex.

Short-term memory

A further important mechanism of human memory is short-term memory. The relationship of induced high-frequency responses to short-term memory was examined by Tallon-Baudry and co-workers (Tallon-Baudry et al., 1998). They studied the retention of a visual object in short-term memory during the delay period of a delayed-matching-to-sample task. In brief, two stimuli, S1 and S2, were

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 26 presented for 400 ms separated by an 800 ms delay (see Figure 3-IV, upper panel, for an example of the stimuli used). The task was to detect the matching S2. A further condition was introduced, in which no S2 stimulus was presented. This was done in order to control for effects independent of short-term memory. It was expected that in the memory condition a cortical representation from S1 is activated before S2 appearance, which is related to rehearsal in memory. Regarding the idea of cell assemblies, a schematic idea of this hypothesis is given in Figure 3-IV (a: S1 onset, b:

S1 rehearsal in short-term memory). Analysis of spectral changes revealed an increase of induced gamma power at both occipito-temporal and frontal electrodes. The authors interpreted these results as a signature of a synchronized cortical network centered in prefrontal and visual areas that ensures the rehearsal of S1. This interpretation is in line with findings in animal studies, which revealed an interplay between ventral and frontal areas in stimulus retention in short-term memory (Fuster, 1997). Furthermore, imaging studies showed an activation of frontal and visual areas during working memory tasks (Ungerleider, 1995). In addition, it has been suggested that prefrontal cells may monitor the activation of sensory representations, thus, being the originators of the delay activity in visual processing areas (Chelazzi et al., 1993;

Miller et al., 1993).

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 27 Associative learning

(See also Appendix: Gruber et al. (2001), Modulation of Induced Gamma Band Responses and phase synchrony in a paired associate learning task in the human EEG, Neuroscience Letters)

Associative learning is regarded as an important mechanism in both short-term and long-term memory storage and retrieval of complex episodes or stimulus configurations. Miltner et al. (Miltner et al., 1999) showed that increased gamma band activity is involved in associative learning. Furthermore, these authors showed an increase in gamma band coherence, i.e. a measurement of phase synchrony, between regions in the brain that mediate the perception of stimuli related to different sensory modalities. In particular, subjects learned an associative connection between a conditioned stimulus (CS+, visual stimulus) and an unconditioned stimulus (UCS, electric shock) during a classical conditioning paradigm. Results showed significant coherence in the gamma band between occipital and somato-sensory electrode sites, which was interpreted a signature of a Hebbian cell assembly, binding together parts of the brain that must communicate with one another, in order for associate learning to take place.

In one of our own studies we investigated associative learning by means of a paired-associate learning paradigm. Subjects had to learn several pairs of objects (S1 and S2) during a learning period (For an example see Figure 3-V, upper panel). In the recall period of the experiment subjects had to judge whether a presented cue (S1) and a following stimulus (S2) formed one of the memorized pairs or not. As a control condition we used a simple choice reaction task in which no link between S1 and S2 had been learned. Results showed a significantly higher increase of induced GBRs at

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 28 posterior and anterior electrode sites after the presentation of S1 as compared to the control condition. Furthermore, phase synchrony revealed a broad distribution pattern of phase synchrony between posterior and frontal electrode sites in the learning, but not in the control condition. An overview of the results is depicted in Figure 6.

Figure 6: A: Time by frequency plots (induced gamma power) for the choice reaction task and the paired associate learning task after S1 presentation (0 ms). Averages across 10-20 electrode sites are presented. Note: time and frequency windows used for further analysis are indicated by rectangles. In PAL an average across paired/un- paired S2 stimuli and in CR an average across target/non-target S2 stimuli is shown. B: Synchrony (solid lines) and desynchrony (dashed lines) between 10-20 electrode pairs for the learning and the choice reaction task, respectively. Five non-overlapping time windows are depicted. Lines are drawn only if the phase-locking value is beyond the distribution of shuffled data (p<0.01). Note:

extended 10-20 electrode names are given in one electrode layout.

We concluded that induced gamma band responses and phase synchrony may be a signature of a widespread cell assembly covering frontal and posterior areas, which is crucial for the storage and recall of a learned stimulus configuration. A

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 29 schematic representation of this idea is given in Figure 3-V (a: no connection between S1 and S2 is established, i.e. the cell assemblies representing S1 and S2 are not connected. b: The connection between S1 and S2 is learned). The frontal activity found in the present paired associate learning paradigm might reflect explicit recall processes, which are necessary to solve the task. This interpretation is in line with imaging studies, which reported activity in pre-frontal areas related to intentional retrieval processes (Schacter et al., 1998).

Discussion

The studies presented in this thesis were motivated by the hypothesis that memory recall and formation is based on cell assemblies, which are established by neuronal synchrony amongst their elements. Induced GBRs and phase synchrony might be a signature of activity within such a cell assembly. In particular, we assumed that (1) the formation of a cell assembly should lead to an integration of activity within and between task specific modalities. (2) Implicit recall processes lead to an activation of a cell assembly, which stores the features of a percept close to the cortical areas that mediate the perception of those features. (3) In contrast to implicit memory, explicit forms of memory recall should activate a cell assembly, which includes the storage sites of a learned percept and related higher order monitoring areas.

The first hypothesis was examined using an operant learning paradigm. This task revealed an increase in spectral power at electrode sites over pre-motor and frontal areas, possibly related to the formation of a neuronal network representing contingencies between behaviours and external stimuli with a behavioural or motivational relevance (Keil, Müller, Gruber, Wienbruch, & Elbert, 2001b).

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 30 Interestingly, other studies examining the relationship between human memory and high-frequent brain activity reported an enhancement of induced GBRs not only at anterior but also at occipito-temporal electrode sites (Gruber, Keil, & Müller, 2001;

Gruber et al., in press; Tallon-Baudry et al., 1998). This seems plausible because the shaping procedure emphasized operant learning and behaviour modification, whereas occipito-temporal activation was found as correlate of the mental representation of a visual object. Furthermore, the study by Miltner and co-workers (Miltner et al., 1999) gives further raise to the notion that cell assemblies are centered in task specific modalities. In their classical conditioning paradigm, which established a link between visual and somatosenory stimuli an increase in gamma coherence between electrode sites over posterior and somatosensory cortical areas was found.

The second hypothesis we formulated was that implicit recall processes lead to an activation of a cell assembly, which stores the features of a percept. This assumption was examined in an experiment using a rapid perceptual learning paradigm. It was shown that a cell assembly, possibly covering distributed visual areas, can be activated by perceptually primed stimuli. In this study no increase in induced GBRs and phase synchrony at frontal electrode sites was found (Gruber et al., in press). We assumed that this lack of frontal activity was due to the implicit nature of the task used in this study, which is in line with the notion that the prefrontal cortex is not activated when retrieval is automatic (Klingberg & Roland, 1998; Schacter, 1992). Furthermore, it was shown that a cell assembly established by synchronized activity underlies a typical mechanism in implicit learning, namely repetition suppression. We found a decrease of induced GBRs and phase synchrony after repeated presentations of a stimulus as compared to the initial presentation of the same stimulus, which was seen by us as a signature of a ‘sharpening’ of the respective

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 31 cell assembly (Gruber & Müller, in press). This repetition suppression effect was replicated at similar electrode sites over visual areas as in the operant learning task described above in relation to the visual feedback stimuli (Keil et al., 2001b).

The third assumption that was made stated that explicit forms of memory recall activate a cell assembly, which includes the storage sites of a learned percept and higher order monitoring areas, presumably located in prefrontal cortical areas.

This was verified in a short-term memory task by Tallon-Baudry and colleagues (Tallon-Baudry et al., 1998), which showed an increase of gamma power over visual, but also pre-frontal areas. Paralleling these findings we found a similar topographical pattern of synchronized activity in an associative memory task (Gruber et al., 2001).

The described studies give raise to the notion that neuronal interactions in the gamma range are not only restricted to perceptual integration at a local level, i.e.

between sites within monosynaptic connections as suggested for example by von Stein et al. (von Stein, Chiang, & König, 2000). It was shown that high frequency brain activity was also found in an intermediate and large scale of the spatial continuum and is related to higher cognitive functions such as implicit memory, explicit types of learning, somatosensory and visual integration, and the integration of motor planning. It has to be concluded that gamma band activity and phase synchrony play a crucial role in the formation and recall of learned representations of a stimuli and associations between different stimuli. However, it should be emphasized that this conclusion does not mean that GBRs are exclusively related to processes of active memory as suggested by Pulvermüller et al. (Pulvermüller et al., 1999). Rather, synchronized neural activity in the human brain might be general cortical mechanism to integrate different forms of information. Thus, different assumptions on the role of GBRs in brain functioning are not mutually exclusive. Rather they mirror mechanisms

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 32 in the brain that might share the same mechanism but at opposite ends of the spatial continuum. This notion finds support regarding the latencies of induced GBRs in the described learning paradigms. As predicted for higher cognitive functions (Varela et al., 2001), we found maximal gamma activity in late time windows approximately 300 ms after stimulus onset. This latency is far beyond time windows of early visual processing (Gomez Gonzalez, Clark, Fan, Luck, & Hillyard, 1994). In contrast, in an experiment recruiting early perceptual mechanisms (small squares were used to form objects on the basis of common motion and colour), induced GBRs showed a much earlier increase (Gruber, Keil, & Müller, 2000). Furthermore, it might be the case, that low level processing in early visual areas is reflected by evoked GBRs in the human EEG, which might be complementary to visual evoked potentials (see results by Hermann et al. (Herrmann, Mecklinger, & Pfeifer, 1999)). However, the significance of evoked GBRs and their relation to induced responses is still not clear (Tallon- Baudry & Bertrand, 1999). We have analyzed this relationship in our studies on perceptual priming and repetition priming. The fact that we found no significant relation of induced GBRs neither to the evoked gamma band response nor to the components of the visual evoked potential (VEP) indicates that evoked responses may play a functionally different role in different brain functions as compared to induced gamma high frequency responses.

A general concern in studies examining human memory is that the level of attention paid to a stimulus, which has to be learned or was learned, is higher as compared to unlearned objects. As induced GBRs are known to be modulated by attention (Gruber et al., 1999; Müller et al., 2000) (see Appendix) this might be an alternative explanation for the reported results. Although, we controlled for that effect in all of our studies, the role of attention in memory processes and vice versa must be

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 33 discussed more closely. Induced GBRs in the human EEG and their relation to attentional information processing is described in detail by Müller et al. (Müller &

Gruber, 2001) (see Appendix). It is suggested that besides being associated with enhanced amplitude of neuronal responses (i.e. the VEP), selective attention is related to enhanced synchronization of neural activity. Induced GBRs are closely linked to visual bottom-up and top-down information processing (Keil et al., 2001a; Tallon- Baudry & Bertrand, 1999). Both processes will cause that a subset of stimuli present in the field of view is processed preferentially. While bottom-up processes might facilitate synchronization of neurons’ responses due to the salience of the stimulus, top-down processes may bias information selection by facilitating synchronization of neurons coding certain features of a stimulus. Furthermore, attention is often thought of as a gateway to learning and memory, because as an inherent characteristic of memory processes one learns and remembers much more about attended stimuli, than about ignored stimuli (Desimone, 1996). On the other hand, due to the finite computational resources of the brain, only a limited number of stimuli will be processed at a given time (Desimone & Duncan, 1995). Therefore it was suggested that a selective attentional mechanism focuses these resources to specific objects or locations in the visual field (Hillyard, Mangun, Woldorff, & Luck, 1995). As a result memory will often determine the ‘winner’ of this competition for resources, thus, some mechanisms of memory and attention are so intertwined that one might question if they are distinguishable at all (Desimone, 1996).

One possible solution to overcome this problem is to study memory processes by using implicit memory paradigms. Since implicit memory processes can be defined as a facilitation of performance without intentional effort (Schacter, 1987), one might assume that at least top-down attentional influences are diminished and that implicit

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 34 forms of memory offer the possibility to interpret the influence of past events on current behaviour independently of top-down attentional mechanisms. However, such a strategy does not diminish bottom-up stimulus driven attentional processing. For example in our perceptual learning paradigm it might well be possible that an identified object but not an unidentified object pops-out of the presented stimuli, and, thus, results in further attentive processing. In future experiments this problem might be tested by instructing subjects to identify certain targets in the stream of learned stimulus configurations. Such a paradigm could fulfil the requirements to compare

‘memorized-attended’ and ‘memorized-unattended’ stimuli; a strategy which might allow separating the two highly intertwined mechanisms.

It has to be mentioned that a number of authors have questioned the reliability and validity of human GBRs as extracted from EEG recordings. Menon et al. (Menon et al., 1996) argued that if gamma band spatial patterns exist in the human brain, no existing technology would be capable of measuring them at the scalp. However, it was questioned if the paradigm used by these authors was suitable to measure GBRs. The cortical area they stimulated might be much too small to measure high frequency activity in the human EEG (Lutzenberger, Preissl, Birbaumer, & Pulvermüller, 1997).

Furthermore, Jürgens and collaborators (Jürgens, Guettler, & Eckhorn, 1999) showed that with grating stimuli presented to monkeys and human subjects, modulations of gamma band oscillations could be obtained from monkey local field potentials and scalp EEG, but not from human EEG. This finding is relevant regarding the views described above, namely that human GBR may be related to coupling within and between cell assemblies encoding attended aspects of the perceived stimulus.

Interestingly, monkeys in the standard experimental setup for recordings learn allocation of attention to the visual stimuli by means of reinforcement schedules.

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 35 Thus, the visual stimuli acquire a high amount of motivational significance and are observed attentively. In humans, a fixation of simple stimulus arrays without related experimental tasks is usually achieved by instruction only and thus has a low level of behavioral significance, leading to a low level of attention to the stimulus in question.

For the discussion of the influence of possible sources of artifacts as an explanation for the observed oscillations (like muscle activity and harmonics of lower frequency bands (Jürgens, Rösler, Hennighaus, & Heil, 1995)) I would like to refer to Gruber at al. (Gruber et al., 1999), Keil et al. (Keil et al., 1999), Müller et al. (Müller et al., 1996; Müller, Junghöfer, Elbert, & Rockstroh, 1997; Müller, Keil, Gruber, &

Elbert, 1999), and Pulvermüller et al. (Pulvermüller et al., 1997). However, some alternative explanations why cell assemblies oscillate should be mentioned.

Kirschfeld stated that oscillations are not used for coding but are simply a by-product of the functional architecture of any neural network. In other words, they are epiphenomena, with no functional significance (Kirschfeld, 1992). However, this argument can be refuted on the basis of experiments, which use identical experimental setups in different conditions (Gruber et al., in press; Gruber et al., 1999; Tallon- Baudry et al., 1997). Here, it seems difficult to argue that differences in gamma power are due to different levels of noise in the experimental conditions. Further suggestions as to the role of oscillatory processes include encoding the stimulus itself (Freeman, 1995). Furthermore, it was proposed that oscillations reflect “idling” in neural mass systems, which would prevent that the systems activate themselves when there is little or no input to the network. Idling would also allow the system to start more rapidly than by cold start (Hari & Salmelin, 1997). In the motor cortex narrow-band activity at about 19-20 Hz was prominent during the motor preparation over sensory-motor cortex, but did not appear during sensory-motor integration or during eyes open or

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Gruber Oscillatory Brain Activity as underlying Neural Mechanism of Human Memory 36 closed resting conditions. Apparently this “motor preparation rhythm” is a regular feature of both human (Kristeva-Feige, Feige, Makeig, Ross, & Elbert, 1993) and mammalian motor systems (Murthy & Fetz, 1992). Fukai (Fukai, 1995) argued that the contribution of a particular cell to a cell assembly is measured by the number of spikes it provides to the ensemble. If so, a time interval needs to be set, over which spikes are counted. Oscillations might provide the clock signal, needed to update the contribution of the individual neurons.

A further interesting point was pointed out by Gollege et al. (Golledge, Hilgetag, & Tovee, 1996). They argued that induced gamma band responses in the human EEG measure spectral power of oscillations, but the crucial point in temporary binding is synchrony. It may well be that assemblies of strongly coupled neurons distributed over various visual cortices are the generator of gamma band power changes visible in the EEG. Such neural assemblies may ‘oscillate’ simultaneously in the gamma range after stimulation with behaviourally significant visual stimuli.

However, differential spectral responses may also result from more complex spatio- temporal patterns of neuronal activity to which large numbers of neurons contribute (Abeles, 1991). It is, however, important to note that coherent oscillations or repetitive spatio-temporal patterns of activity are only possible in strongly coupled cell assemblies (Braitenberg, 1990). Furthermore, a number of authors suggested that the measurement of phase synchrony between pairs of electrodes, independent of amplitude, provides a method to overcome this problem (Lachaux et al., 1999; Miltner et al., 1999; Rodriguez et al., 1999), a strategy which we adopted in our experiments on perceptual priming, repetition priming and associative learning. In a rapid perceptual learning task an increase in gamma power at electrode sites over different visual cortical areas, which co-existed with an increase in phase synchrony was

Oscillatory Brain Activity as Underlying Neural Mechanism of Human Memory

Oscillatory Brain Activity as Underlying Neural Mechanism of

Human Memory

Dissertation

zur Erlangung des akademischen Grades des Doktors der Naturwissenschaften

an der Universität Konstanz Naturwissenschaftliche Sektion

(Fachbereich Psychologie)

Thomas Gruber

Schönaich

Contents

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