Neural binding of space and time: An introduction

VISUAL COGNITION, 2001, 8 (3/4/5), 273–285

Neural binding of space and time: An introduction Hermann J. Müller and Mark A. Elliott Institute of Psychology, General and Experimental Psychology, University of Munich, Germany

Christoph S. Herrmann Max Planck Institute of Cognitive Neuroscience, Leipzig, Germany

Axel Mecklinger Max Planck Institute of Cognitive Neuroscience, Leipzig, and Department of Psychology, Saarland University, Saarbrücken, Germany Some of the central problems to be solved by the brain, such as figure–ground coding and object recognition, concern the binding of separately coded feature elements into coherent object representations. The binding problem has recently been approached by a variety of disciplines, notably psychophysics and experimental psychology, electrophysiology and neurophysiology, and computational modelling. This Special Issue brings together 21 of papers, mainly all from psychology and computational modelling, that address issues in Gestalt formation, the relation of the grouping and binding processes to visual attention, the role of temporal factors for grouping and binding, the neuronal correlates of binding mechanisms, the development of binding operations in infants, and the breakdown of these processes following brain damage.

Some of the central problems to be solved by the brain—such as figure–ground coding, object recognition, and the formation of object memories—concern the binding of separable elements into coherent structures. The binding problem has recently been approached by investigators in a variety of disciplines,

Please address all correspondence to H.J. Müller, Allgemeine und Experimentelle Psychologie, Institut für Psychologie, Ludwig-Maximilians-Universitä t München, Leopoldstraße 13, D-80802 München, Germany. Email: [email protected] The authors express gratitude to the Deutsche Forschungsgemeinschaft (DFG, German National Research Council) for supporting the symposium “Neural binding of space and time” out of which this Special Issue developed. Preparation of this editorial was supported by DFG grant Schr 375/8-1 (3), and it benefited from insightful comments by Hans-Georg Geissler and Glyn W. Humphreys. Ó 2001 Psychology Press Ltd http://www.tandf.co.uk/journals/pp/13506285.html DOI:10.1080/13506280143000007

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notably psychology (psychophysics and experimental psychology), physiology (electrophysiology and neurophysiology), and computational modelling (neurocomputing). Within psychology, researchers have been concerned with the Gestalt principles of perceptual grouping, the relation of the grouping and binding processes to visual attention, the role of binding processes in memory formation, and with how these principles and processes are implemented in the feature–object coding system. One recent strand of the psychological work has examined the role of temporal factors for grouping and binding using psychophysical means. This work has been inspired by prominent studies in neurophysiology, which found that, when feature elements were presented simultaneously and their arrangement accorded to some Gestalt principle, visuo-cortical cells responding to those elements adjusted their firing pattern and oscillated in synchrony, with zero phase lag. These findings have been taken to suggest that the critical neurophysiological correlates of perceptual grouping and binding are synchronous and oscillatory patterns of activity that are phase-locked across feature-coding neurones. Last but not least, investigators in computational modelling have studied how synchronization and phaselocking may be realized in networks of oscillating neurons, what constraints must be implemented to achieve elementary grouping and binding operations, how such networks give rise to fully assembled object representations that may be compared with object descriptions stored in visual memory, and how contextual memories are formed. What follows is a brief overview of important issues and developments within the three disciplines of psychology, neurophysiology, and computational modelling, relating to the theme of this Special Issue.

PSYCHOLOGY In the first decades of this century, the Gestalt psychologists (Wertheimer, 1912, 1923; Köhler, 1924; Koffka, 1935) were concerned with the principles governing perceptual organization or grouping and figure–ground perception (e.g., Rubin, 1915). Amongst the “laws” of perceptual organization that have been described, are grouping based on proximity, continuation (e.g., collinearity), similarity, and common-fate motion. More recently, psychologists working within the Gestalt tradition have postulated further laws, such as uniform connectedness and common region (Palmer, 1992; Palmer & Rock, 1994). Furthermore, there have been attempts to re-address the issue of figure– ground coding. Using reversible patterns such as Rubin’s face–vase pictures, this work showed that the dividing edge is assigned to just one of the patterns: That which is perceived as the figure (e.g., Baylis & Driver, 1995). There have also been early attempts to explain the brain mechanisms underlying perceptual grouping (e.g., Köhler, Held, & O’Connell, 1952), which were, however, limited by the knowledge available at the time concerning the functioning of the

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(visual) brain. Importantly, however, the Gestalt psychologists proposed that perceptual organization and figure–ground coding is based on hard-wired brain mechanisms that operate preattentively. By contrast, subsequent theories in information processing psychology have proposed that (correct) feature–object bindings require attention (e.g., Treisman & Gelade, 1980). According to the notion of attentional binding, the initial parallel (or simultaneous) coding of feature elements across the visual scene is followed by a serial traversal of the display by a focal-attentional mechanism. As attention is focused on a cluster of features, they are transiently “bound” into a coherent object representation (see also Crick, 1984). In contrast, alternative theories of preattentive feature conjunction (e.g., Duncan & Humphreys, 1989) have proposed that at least some types of feature bindings can occur during the parallel stage of visual coding, and the resulting feature assemblies compete for access to the limited-capacity object recognition stage. Evidence in favour of the latter theories was provided by visual search experiments which showed that Kanizsa figures defined by good-continuation illusory contours were detected in parallel (e.g., Davis & Driver, 1994), as were breaches of collinearity within single Kanizsa-type figures (Donnelly, Humphreys, & Riddoch, 1991). Other recent research in psychology have been inspired by findings from single-cell recordings (see later) pointing to a role of synchronized visuocortical cell oscillations for feature-object binding (temporal binding). There have been several attempts to examine the temporal-binding hypothesis psychophysically, by testing whether synchronized target element presentation, asynchronized relative to background element presentation, promotes efficient target coding at particular stimulus presentation frequencies (e.g., Blake & Yang, 1997; Fahle, 1993; Fahle & Koch, 1995; Kiper, Gegenfurtner, & Movshon, 1991, 1996; Leonards, Singer, & Fahle, 1996). Although the results tended to be inconsistent, several novel paradigms have been developed recently supporting the notion that feature–object binding involves temporal coding (e.g., Elliott & Müller, 1998; Usher & Donnelly, 1998). Thus, the emerging psychological evidence is that perceptual organization operates at early, preattentive levels of visual processing and that temporal coding might play a role in these processes.

NEUROPHYSIOLOGY Single cell studies have long been informative about the nature of neural coding (e.g., Hubel & Wiesel, 1968). Much of the early work on low-level coding in vision indicated that there was considerable separation of the neural pathways for different properties of the image: For shape, motion, colour, depth, and so forth (see Zeki, 1993, for a summary). Within each of these streams, there may be some degree of “binding” based on local Gestalt properties; for instance,

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collinearity between edges coded in V1 can lead to selective firing of cells in V2 (Peterhans & von der Heydt, 1989; von der Heydt & Peterhans, 1989). More recently, though, studies of neural responses at higher levels of vision (e.g., in inferior-temporal cortex) indicate that cells can respond not only to complex shapes (which must presumably be “bound” from their parts) but also to conjunctions of shape and colour (e.g., Tanaka, 1993). Thus, there is physiological evidence for neural coding of “bound” objects. However, cells in higher levels of cortex also tend to have large receptive fields, which introduces another constraint on binding, namely, that inputs to such cells may need to be modulated such that the cells are not driven by appropriate stimulus attributes in separate objects. In this context, modulation of cells in the ventral visual stream by cells in the dorsal stream linked to attention and action may offer one solution (e.g., Moran & Desimone, 1985). The role of temporal coding within the nervous system during feature– object binding was originally highlighted by the work of Gray, Engel, and colleagues. Gray, König, Engel, and Singer (1989) reported that, when the receptive fields of visuo-cortical cells were stimulated by separate bars of light moving in opposite directions, oscillatory neural activity showed low crosscorrelation. However, when bars were passed across the receptive fields in the same direction, a correlative relationship was observed between oscillatory activity within the 20–80 Hz frequency range. The strongest cross-correlations were obtained when a single bar, formed by the addition of a bar element connecting the previously unconnected elements, stimulated the two neurons. Thus, correlated neuronal activity was only obtained when cells responded to different aspects of the same “Gestalt”. Subsequent to this work, “binding” of neural oscillatory activity has been discovered between cells in various parts of the visual cortex (e.g., Engel, König, Kreiter, & Singer, 1991), subcortical structures such as the lateral geniculate nucleus (e.g., Sillito, Jones, Gerstein, & West, 1994), and the pulvinar complex (e.g., Shumikhina & Molotchnikoff, 1995). In each case, oscillations were found specific to neurons that coded different aspects of the same visual stimulus. In addition to the single-cell recordings of inter-neural oscillatory binding, studies recording EEG from the human scalp have also shown that oscillations in the mid-gamma (or 25–50-Hz) waveband reveal stimulus-specific activity. Mid-gamma band activity that is both evoked and induced by stimulus presentation (e.g., Galambos, 1992), has been found to accompany the presentation of stimuli that group preattentively (e.g., Tallon-Baudry & Bertrand, 1999), and stimuli that “bind” following a cued shift of focal attention (e.g., Müller, TederSälejärvi, & Hillyard, 1998). Gamma-band activity has been found to accompany both N100 (Herrmann, Mecklinger, & Pfeifer, 1999) and P300 (Bas¸ar, Bas¸ar-Eroglu, Demiralp, & Schürmann, 1993) ERP components. In addition, these and other studies have revealed that stimulus-specific gamma-band activity is not confined to the visual brain areas, but may be found across a wide

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region of cortex. Thus, stimulus-specific gamma-band oscillations have been recorded at electrode sites above the frontal lobes (Bas¸ar-Eroglu, Strüber, Kruse, Bas¸ar, & Stadler, 1996; Herrmann et al., 1999) and the premotor cortex (Tallon-Baudry, Bertrand, Delpeuch, & Pernier, 1996). More recent work employing coherence analysis techniques (e.g., Miltner, Braun, Arnold, Witte, & Taub, 1999) has demonstrated coherence between mid-gamma-band activity at occipito-parietal and occipito-central electrodes during an associative learning task. These findings raise the issue of the role of both stimulus and task specificity during generation of the cortical 40-Hz potential. EEG coherence between different cortical areas has also been reported for lower frequency ranges such as the beta1 range (von Stein, Rappelsberger, Sarntheim, & Petsche, 1999) or the theta band (Sarntheim, Petsche, Rappelsberger, Shaw, & von Stein, 1998), suggesting that these lower frequencies play an important role in synchronizing cortical ensembles across larger distances.

COMPUTATIONAL MODELLING Attempts to understand how the “binding process” may operate have also been made by computational modelling. In models developed within the connectionist framework, “binding” presents a serious problem. Stored knowledge may be “bound” by being represented within local units. However, there arises then a problem of scale, since the number of units required becomes equal to the number of individual elements of knowledge to be stored, something even beyond the capacity of the brain (a problem that had been noted before the rise of neo-connectionism; e.g., Weisstein, 1970). Alternatively, knowledge may be represented by distributed patterns of activation across multiple units. But this approach introduces problems concerning how the individual representations are linked in appropriate spatial and/or temporal relations. These are, of course, similar problems to those encountered by real neural systems. Explorations of how the binding problem may be solved in artificial networks can thus be helpful for attempting to understand how it is solved in the brain (e.g., Grossberg & Grunewald, 1997). In addition, artificial networks can make a valuable contribution to examining theories of neural binding. For example, simulations can be used to test the role in memory of learning “updates” provided by the hippocampus for cortical representations (e.g., McClelland, McNaughton, & O’Reilly, 1995), which have been suggested by “consolidation” theories of human learning. Such updates can help to prevent learned information from being overwritten by new items, and similar procedures can also be used, conversely, to prevent effects such as “catastrophic forgetting” in networks. We are now at an exciting stage in which direct collaborations between modellers and neuroscientists can lead to real advances in our understanding of behaviour within neural systems, gained by means of detailed model simulations.

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THE SPECIAL ISSUE This Special Issue brings together 21 papers mostly from psychology and computational modelling, which are based, in the main, on invited presentations delivered at the interdisciplinary symposium “Neural binding of space and time”, held in Leipzig on 16–18 March 2000 (supported by the Deutsche Fortschungsgemeinschaft—German National Research Council). The call for Special Issue contributions stated that papers should be theoretically focused on the theme of the symposium and that they should make a novel theoretical and/or empirical contribution to the study of binding. Following an extensive process of peer review, the collection of 21 papers included in this Special Issue provides such a contribution. The following sections provide a précis of the individual papers. From the perspective of Gestalt psychology, the problem of binding involves the problem of the relationship between wholes and their constituent parts. One fundamental point of controversy concerning the general concept of feature binding is the extent to which object and Gestalt perception relies upon the construction of wholes from basic, featurally separable constituent parts. Both Chen, and Markovic´ and Gvozdenovic´ raise this issue in their contributions. Chen argues strongly against this local-to-global assumption, maintaining that the “problem” of feature binding arises essentially as a consequence of this particular perspective. According to Chen, “local-to-global” suggests a fundamentally inaccurate description of the hierarchy of processing stages through which a given Gestalt grouping or stimulus object would proceed. Instead, Chen attempts to show that, through the analysis of perceptual invariants across transformations, the nature and rules of perceptual organization may be precisely expressed in terms of topological invariants that describe the geometrical potentiality of the entire stimulus configuration. Chen’s position is in part (although not entirely) supported by that of Markovic´ and Gvozdenovic´, who show that the perceptual system will adopt processing strategies on the basis of the relative simplicity or complexity of the entire stimulus configuration. This approach emphasizes that fine-scaled (or feature) analysis will be more effective when stimulus configurations are relatively simple, and as such reverses the hard assumption of the feature-binding approach that stimulus analysis proceeds exclusively from local-to-global levels of processing. The role of figural specification as a determining factor for elementary perceptual operations, such as figure–ground segmentation, is also illustrated by Peterson and Kim. They show, by means of a priming paradigm, that object memories are accessed for regions initially seen as ground when their outline contours correspond to the silhouette of an object, but not when ground outline contours do not form object silhouettes. Finally, Aksentijevic´, Elliott, and Barber suggest a “force field” theory, based on a differential-geometric interpretation of perceptual space, can provide a promising starting point for a systematic

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exploration of the subjective properties of certain classes of visual and auditory grouping phenomena, such as apparent motion, grouping within static twodimensional displays and auditory streaming. The issue of binding between brain regions and, by extension, binding between different attributes of the same object and between different objects is addressed in the contributions by Baylis, Gore, Rodriguez, and Shisler, Humphreys, and Davis. For some time, it has been suggested that there is a division of the visual system into a dorsal and a ventral stream (e.g., Ungerleider & Mishkin, 1982). The dorsal stream, running from the occipital lobe into the parietal lobe, is concerned with scene-based properties such as location and movement; the ventral stream, running from occipital areas into the inferior part of the temporal lobe, analyses object-based properties such as shape and colour. The correct binding of the dorsal “where” system to the ventral “what” system would seem essential for unified awareness of objects within a scene. In support of this, Baylis et al. present new neuropsychological evidence that visual extinction may be greatest when information about object location cannot be bound to information about object identity. Similarly, Humphreys reviews neuropsychological data from patients with lesions to different visual areas (in the ventral and dorsal streams) that result in impairments of separable binding processes. Binding from elements to contours, contours to shapes, and shapes to surfaces can be differentially impaired, suggesting a hierarchy of binding processes at different stages of the visual system. Finally, Davis reviews his recent work on differences in performance between within-object and between-object comparisons. His findings lead him to suggest that the visual system binds together features between different objects, just as it binds features within an object. He argues that the information stored about relationships between different objects should be considered as a form of binding, similar to the combination of information within an object representation. The within-object links and between-object links are stored in different brain regions, ventral stream vs. dorsal stream, and they serve different functions, object recognition vs. guidance of actions. Taken together, the papers just mentioned suggest that the problem of “binding” extends beyond a simple description of feature integration and Gestalt formation. Rather, there are likely to be different forms of binding subserved by different types of mechanism. This raises the question as to the precise system states and processes by which the various types of binding are generated—an issue that has lain at the core of the binding problem since it was first posed. Perceptual binding and selective attention have been extensively studied with human and animal experiments, both behaviourally and electrophysiologically, but also by the development of computational models that incorporate physiological principles and architectures of connectivity to account for psychophysical data. Raizada and Grossberg offer such an approach. In their model, they show basic perceptual operations such as

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orientation contrast, perceptual grouping, and visuo-spatial attention can be accounted for by the activity of interlaminar circuits in early visual areas V1 and V2. In order to account for visual selection, Cave considers two means of achieving feature-object binding (besides binding by conjunction units): Attentional binding and temporal binding. He argues that a location-based attention mechanism, as implemented in his “FeatureGate” computational model, can initiate selection (and binding) processes very quickly, and that the visual system employs location selection and attentional binding whenever possible because of their reliability. However, temporal binding can potentially enhance selection in complex scenes, to (1) allow a target object to be selected without also selecting a superimposed distractor, (2) maintain representations of objects after attention has moved to another object, and (3) permit multiple parts of an object to be selected, segmented, and analysed simultaneously. Hummel proceeds from behavioural, neural, and computational considerations, which suggest that the visual system may use at least two approaches to binding an object’s features and/or parts into a coherent representation of shape: Dynamically bound (e.g., by synchrony of firing) representations of part attributes and spatial relations form a structural description of an object’s shape, while units representing shape attributes at specific locations (i.e., a static binding of attributes to locations) form an analogue (image-like) representation of that shape. Hummel presents a computational model of object recognition based on this proposal and empirical tests of the model. One central topic in this Special Issue, also related to the nature of the states and processes by which binding is realized, concerns the tendency for neurons to synchronize their firing following presentation of stimulus elements that group according to one or another Gestalt principle. These findings have resulted in the “temporal-correlation hypothesis”, which, in its simplest form, states that binding occurs through the temporal correlation of neuronal firing (Singer, 1993; von der Malsburg, 1981). A more specific formulation of this hypothesis refers to the tendency for neurons that synchronize to stimulus Gestalten to do so within a relatively broad range of frequencies referred to as the “gamma band”. The gamma band extends, at the most liberal estimate, from around 20 to 120 Hz, although activity in the 30–60 Hz region, and more specifically in a narrower bandwidth at around 40 Hz, appears to be of particular importance. Synchronous firing has so far mostly been demonstrated using cross-correlation of the firing rates of two neurons (e.g., Gray et al., 1989). Eckhorn, Bruns, Saam, Gail, Gabriel, and Brinksmeyer present an extension of the binding-by-synchronization hypothesis by showing how elementary perceptual processes such as figure–ground segmentation, object continuity, and feature binding are reflected in temporal and spatial aspects of gamma activity recorded in single units of monkey brain. A new aspect of this model is the idea that long distance coupling of neuronal activation patterns between different

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brain regions is accomplished by transmitting the strength of local gamma activities, that is, “gamma envelopes”. Intracellular recordings often display a wide variation in the precise frequency of synchronization. In order to address this issue, Panzeri, Golledge, Zheng, Tovée, and Young discuss a new method for differentiating the functionally significant patterns of neuronal activity and neuronal synchrony, based on Information Theory. In her contribution, Giersch presents psychopharmacological manipulations of visual integration processes, which show that the benzodiazepine lorazepam, and, by extension, a very specific subset of receptors within the GABAergic interneural system, is specifically involved in the processing of primitive feature elements such as luminance discontinuities. These physiological and psychophysiological findings point to much greater sophistication in our understanding of how visual information processing may be specified in terms of particular properties of dynamic and anatomical cortical structures. Johnson addresses developmental aspects in visual perception that provide insights into mechanisms underlying visual binding. In a comprehensive review of developmental studies that use the habituation paradigm in infants between birth and 4 months of age, he shows that (infants’) veridical surface segregation relies on a variety of subprocesses, such as “depth placement” and “contour ownership”, that develop in this early period of life. Johnson addresses computational and neurophysiological issues in visual development and stresses the importance of the interplay of experience-independent (figure– ground segregation, attention towards motion and contour) and experiencedependent (changes in synaptic strength and neuronal firing patters) mechanisms for visual development in early childhood. The findings of bandwidth-specific neuronal responses in the animal cortex have encouraged investigations of the patterning of the human EEG response, which offer interpretations of brain activity according to psychophysical and psychological models of perceptual processes. Müller and Gruber review a number of these studies, showing that power in the frequency range at around 40 Hz is indeed enhanced during experimental tasks requiring the deployment of focal-attentional mechanisms. However, whether an attentional account provides a sufficiently general description for the role of 40-Hz brain activity during perceptual processing is brought into question by the findings of Herrmann and Mecklinger, who show that the strength of a 40-Hz response is closely related to a memory-based feature comparison process (related to Gestalt classification), and that this response occurs in a time period before full deployment of focal attention. Perceptual binding and “unbinding” are needed when ambiguous figures (e.g., the Necker cube or Rubin’s vase) are sequentially perceived with one or the alternative interpretation. Here, Strüber, Bas¸arEroglu, Miener, and Stadler report that subjects who quickly change from one to the other of two alternative percepts exhibit more gamma activity in their EEG as compared to subjects who switch more slowly. The fact that this

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gamma activity was measured over frontal electrodes is taken as another indication that attentional, top-down mechanisms influence perceptual reversals. The development of the temporal-binding hypothesis has also encouraged the development of psychophysical paradigms designed to probe the temporal dynamics of the binding process, normally associated with physiological research. Herzog, Koch, and Fahle present two new visual illusions: “feature inheritance” and “shine-through”, which involve the attribution of stimulus properties such as the tilt, spatial offset, or apparent motion of a very briefly presented stimulus to subsequently presented stimuli. The experiments presented by Herzog et al. contribute to our understanding of the role of attention for binding and the spatial limitations of binding in terms of a few neighbouring stimuli, with the transfer of feature attributes from a first to a subsequent stimulus promising an indication of the temporal development of global configuration influences on the percept. Recently, Usher and Donnelly (1998) presented psychophysical evidence that external temporal modulation can influence the visual grouping of dots in a symmetric (ambiguous) grid into either rows or columns of elements, and Elliott and Müller (1998) demonstrated that synchronized prime stimulus presentation resulted in the generation of a pattern of prime activity that expedited detection of a Kanizsa-type figure in a subsequently presented target display, even though the prime stimulus was nondetectable. Parton, Donnelly, and Usher take their work further in three experiments designed to rule out possible problems with the Usher and Donnelly findings and to examine the interaction between temporal (external temporal modulation) and spatial cues in the perceptual organization of the dot grids. The results strengthen and extend upon the grouping account, according to which spatial cues dominate over temporal cues. Elliott and Müller examine another issue concerning the theoretical significance of figural bindings evoked by flickering stimulus presentation, namely, to which extent perceptual (figural) correlations might result from correlations ordinarily computed within systems sensitive to the motion signals generated by the flickering stimuli. Elliott and Müller show that this explanation is not sufficient to account for the priming effects in their paradigm, suggesting that the use of spatially static, flickering displays offers a paradigmatic means of manipulating the binding processes in operation. Finally, research on binding has long been concerned with apparent motion phenomena and associated stimulus groupings, such as in “beta motion”. Geissler and Kompass ask whether a relationship can be established between psychophysically determined temporal characteristics of apparent motion and critical temporal parameters of spatio-temporal binding. In particular, they examined at what inter-stimulus intervals (ISIs) between periodically presented stimuli at separate locations apparent motion transforms into the perception of simultaneous (at their respective locations) flickering stimuli, that is, at what ISIs one state of binding transforms into another. They found that such

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transitions are likely to occur only at ISIs that are multiples of a smallest quantum time interval. Such discrete time quantum-like structurings, which are also manifest in other perceptual phenomena (such as in the paradigm of Elliott and Müller; see this issue), raise the question of the physiological correlate of very fast periodic processes, the physiological basis of the high temporal precision observed, and the physiological implementation of “single-shot” periods, which the authors discuss.

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