Is there continuity between categorical and coordinate spatial relations coding?

Neuropsychologia 46 (2008) 576–594

Is there continuity between categorical and coordinate spatial relations coding? Evidence from a grid/no-grid working memory paradigm Romain Martin a,∗ , Claude Houssemand a , Christine Schiltz a,∗ , Yves Burnod b , Fr´ed´eric Alexandre c a

EMACS research unit, FLSHASE, University of Luxembourg Campus Walferdange BP 2, L-7201 Walferdange, Luxembourg b INSERM, Unit´ e 483, Paris, France c INRIA Lorraine/LORIA-CNRS BP 239, 54506 Vandoeuvre-les-Nancy Cedex, France Received 14 March 2007; received in revised form 4 October 2007; accepted 5 October 2007 Available online 23 October 2007

Abstract We ask the question whether the coding of categorical versus coordinate spatial relations depends on different neural networks showing hemispheric specialization or whether there is continuity between these two coding types. The ‘continuous spatial coding’ hypothesis would mean that the two coding types rely essentially on the same neural network consisting of more general-purpose processes, such as visuo-spatial attention, but with a different weighting of these general processes depending on exact task requirements. With event-related fMRI, we have studied righthanded male subjects performing a grid/no-grid visuo-spatial working memory task inducing categorical and coordinate spatial relations coding. Our data support the ‘continuous spatial coding’ hypothesis, indicating that, while based on the same fronto-parieto-occipital neural network than categorical spatial relations coding, the coding of coordinate spatial relations relies more heavily on attentional and executive processes, which could induce hemispheric differences similar to those described in the literature. The results also show that visuo-spatial working memory consists of a short-term posterior store with a capacity of up to three elements in the parietal and extrastriate cortices. This store depends on the presence of a visible space categorization and thus can be used for the coding of categorical spatial relations. When no visible space categorization is given or when more than three elements have to be coded, additional attentional and executive processes are recruited, mainly located in the dorso-lateral prefrontal cortex. © 2007 Elsevier Ltd. All rights reserved. Keywords: fMRI; BOLD; Attention; Parietal cortex; Dorso-lateral prefrontal cortex

1. Introduction 1.1. The classical categorical/coordinate theory The coding of spatial relations between objects and/or parts of objects is a fundamental process in spatial cognition. It is nowadays largely admitted that two different kinds of processes for coding spatial relations can be distinguished (Kosslyn, 2006). Categorical spatial relations refer to equivalence classes of spatial positions relative to a perceptually distinguishable reference object (e.g. left/right, below/above, inside/outside).

∗

Corresponding authors. Tel.: +352 46 66 44 9369; fax: +352 46 66 44 9453. E-mail address: [email protected] (C. Schiltz).

0028-3932/$ – see front matter © 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.neuropsychologia.2007.10.010

Coordinate spatial relations refer to precise spatial locations which can be expressed in terms of metric units (e.g. two objects are at a distance of 10.4 cm from one another). In terms of functional organization, the theoretical framework around the categorical/coordinate distinction predicts specific hemispheric lateralization, depending on the type of spatial relations. We will refer to this theory as the ‘separate spatial coding’ (SSC) hypothesis (cf. van der Lubbe, Sch¨olvinck, Kenemans, & Postma, 2006). The SSC hypothesis predicts a relative specialization of the left hemisphere for the processing of categorical spatial relations (viewed as a consequence of the proximity between categorical spatial relations and their corresponding verbal labels) and a relative specialization of the right hemisphere for the processing of coordinate spatial relations (proposed to originate from right-sided shifts and adjustments

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of attentional foci and body’s navigation in the physical space environment) (Kosslyn, 1987; Kosslyn, 1988; Kosslyn et al., 1989; Kosslyn, Maljkovic, Hamilton, Horwitz, & Thompson, 1995). 1.2. Potential critiques of the classical categorical/coordinate theory Although the theory of hemispheric specialization for categorical and coordinate spatial relations is largely accepted (Postma & Laeng, 2006), the empirical support for this theory is not univocal (Jager & Postma, 2003). Most of the evidence for this functional dissociation relies on interaction effects obtained in divided-visual-field studies (Banich & Federmeier, 1999; Kosslyn et al., 1989; Kosslyn et al., 1995; Michimata, 1997), but this methodology permits only a very global appreciation of the underlying hemispheric activations. Moreover, the presence of lateralization effects is modulated by subtle methodological factors, such as the display features, exposure duration and other task properties (Bruyer, Scailquin, & Coibion, 1997; Wilkinson & Donnelly, 1999). While studies with patients showing unilateral focal brain lesions (especially in the parietal cortex) were in line with the theory (Laeng, 1994), investigations on commissurotomized patients failed to give consistent support to the hemispheric specialization hypothesis (Sergent, 1991a, 1991b). And finally, there are few brain imaging studies on the subject and the existing ones do not converge on specific brain regions showing consistent lateralization patterns (Baciu et al., 1999; Kosslyn, Thompson, Gitelman, & Alpert, 1998; Trojano et al., 2002). It is also very important to note that all the abovementioned studies show a more consistent right-hemisphere advantage for coordinate processing than a left hemisphere advantage for categorical processing, whatever the methodologies used (Laeng, Chabris, & Kosslyn, 2003). Another major problem with the categorical/coordinate distinction is the fact that task difficulty is often a confounding factor, as the coding of coordinate relations is generally more difficult than the coding of categorical relations on comparable stimulus material (Bruyer et al., 1997). In a meta-analysis of 24 divided-visual-field experiments Laeng et al. (2003) report mean reaction times for coordinate judgments that are 100 ms slower than those for categorical judgments, while the mean left hemisphere advantage for categorical judgments is 8 ms and the mean right hemisphere advantage for coordinate judgments is 14 ms. Other authors report that a right hemisphere advantage for coordinate relations only shows up for difficult items and that for easy stimuli, the left hemisphere is more efficient both for categorical and for coordinate spatial relations coding (Parrot, Doyon, Demonet, & Cardebat, 1999; Slotnick, Moo, Tesoro, & Hart, 2001). These results suggest that there may be continuity between categorical and coordinate spatial relations coding along a complexity dimension which appears to be more fundamental for the hemispheric differences than the categorical/coordinate distinction per se (Reese & Stiles, 2006; van der Lubbe et al., 2006). Such a view is supported by recent computer simulations (Monaghan & Pollmann, 2003) suggesting that task complexity could be a driving factor for the appearance of hemi-

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spheric lateralizations with a bilateral distribution advantage emerging spontaneously for the solution of complex tasks. Contrary to the SSC hypothesis, the above data argue in favour of a ‘continuous spatial coding’ (CSC) hypothesis, in which the right and the left hemispheres are implicated in both types of spatial relation coding. According to specific task demand, factors such as visual complexity (Reese & Stiles, 2006; Vauclair, Yamazaki, & G¨unt¨urk¨un, 2006) and task difficulty (van der Lubbe et al., 2006) would modulate this general network underlying spatial relation coding and induce a specific lateralization pattern of cerebral activity. This CSC hypothesis would also be in line with results showing that categorical spatial relations may act as an initial step in the formation of the more complex coordinate spatial relations (Niebauer, 2001). The disappearance of a right hemisphere advantage for coordinate tasks with practice could then be interpreted as an effect of the reduction of task complexity with practice instead of being the consequence of the formation of new categorical representations (see also Trojano, Conson, Maffei, & Grossi, 2006). 1.3. SSC versus CSC hypothesis So even if there is good evidence for a lateralization of specific types of spatial relations coding, the question remains unanswered as to whether this lateralization truly reflects an hemispheric specialization for categorical versus coordinate spatial relations as proposed by the SSC hypothesis or whether these types of relations rely on lateralized general-purpose spatial coding (sub)processes which are more or less involved based on task demands1 . Answering this question is important, because if the SSC hypothesis is correct, the high level description of a task as being categorical or coordinate would be the most useful level of description. If nevertheless the CSC hypothesis is correct, the pertinent description would be in terms of the general-purpose functional components needed to handle more or less complex processing demands and not in terms of the categorical/coordinate distinction. Based on previous work, the SSC hypothesis posits the specialization of the right parietal cortex and more precisely the right angular gyrus for the coding of coordinate spatial relations while a symmetrical region in the left hemisphere is supposed to be specialized for the coding of categorical spatial relations (Baciu et al., 1999). The CSC hypothesis would predict that all types of spatial relations coding rely on identical, more general1 Thus it has been suggested that the hemispheric differences in categorical versus coordinate processing are a consequence of the association of categorical/coordinate processing with high/low spatial frequencies respectively (Okubo & Michimata, 2004). The hemispheric specialization would then be a consequence of a relatively higher input of the right hemisphere from the magnocellular pathway specialized in the processing of low spatial frequencies and of a relatively higher input of the left hemisphere from the parvocellular pathway especially efficient for the processing of high spatial frequencies (Hellige & Cumberland, 2001; Roth & Hellige, 1998). If this parvo-magnocellular hypothesis holds, the categorical/coordinate distinction would be reduced to a low-level perceptive dichotomy probably situated in the occipital areas. This view would contrast with the dominant role of high-level spatial encoding processes that are based on the parietal cortex.

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purpose functional network components. These components can be lateralized and they are recruited at different degrees along a complexity continuum by both spatial coding types. A prominent candidate for such a lateralized general-purpose spatial function recruited for complex tasks would be spatial attention. The neuro-anatomical network underlying spatial attention is known to be right-hemisphere dominant and relies on a fronto-parietal functional network including the angular gyrus (Behrmann, Geng, & Shomstein, 2004). The increased difficulty observed especially in coordinate relations coding tasks (Jager & Postma, 2003; Trojano et al., 2006); could indeed trigger the recruitment of spatial attention needed to track the invisible space boundaries which are required for coordinate relations coding. According to this hypothesis a sufficiently difficult categorical relations coding task would also show right hemispheric dominance, due to the involvement of right-lateralized attentional processes. 1.4. Contrasting hypotheses by using a visuo-spatial working memory paradigm To provide empirical evidence in support of one of the two above-mentioned hypotheses, it will be most useful to design visuo-spatial tasks that systematically vary both (a) the type of spatial relations coding (categorical vs. coordinate) and (b) the load imposed on the coding tasks (easy vs. difficult) in order to disentangle the contribution of either factor to the cerebral activation pattern (and its lateralization). The present study addresses this question by using a grid/nogrid working memory paradigm. Such grid/no-grid tasks have been used in several studies differentiating categorical and coordinate spatial relations coding (Kosslyn et al., 1995; Reese & Stiles, 2006) and have led to the expected hemispheric differentiations. First, the rationale is that grid lines serve as a perceptive crutch on which categorical/propositional codings can be based (without necessarily applying verbal labels) and which thus avoid using precise spatial codings as they are found for coordinate relations (Kosslyn et al., 1995). On the other hand, when there is no visible grid, the lack of perceptive spatial structure requires a coordinate/precise coding of spatial positions when multipart mental images have to be formed. Second, the grid offers the possibility to implement task variations which should further enhance categorical coding of spatial relations. Besides presenting a regular grid in the ‘categorical-regular’ condition, we also present a randomly distorted grid in the ‘categoricaldistorted’ condition (see Fig. 1). If categorical relations are coded in the form of abstract spatial categories, as is suggested by the categorical/coordinate theory, the distorted and the regular backgrounds should not be different in processing terms. On the contrary, the distorted grid condition should even reinforce the use of such abstract space categories. The precise coordinate

coding of locations would imply a supplementary workload to account for the random displacements of the image subparts in the distorted grid, while this degree of precision is not necessary for an efficient task resolution (in the sense of categorical spatial relations use). On the other hand, if it is not the spatial coding type per se but task load which is the crucial factor modulating neuronal activity, then the processing demands have to be analyzed on the basis of the specific perceptive characteristics of a given spatial relations coding situation, be it categorical or coordinate. Consequently processing of the more complex distorted grid should imply a higher processing load than the load imposed by in the ‘categorical-regular’ condition, especially if spatial attention is needed to handle the more complex grid structure. Whereas the SSC hypothesis predicts the largest differences in activation pattern between the ‘coordinate’ and the ‘categoricaldistorted’ condition, the CSC hypothesis expects the latter to be intermediate between the ‘coordinate’ and ‘categorical-regular’ conditions. By using a working memory task we can manipulate memory load by increasing the number of spatial elements that have to be coded and memorized. This allows for load variations that are simple, continuous and independent from the type of spatial coding at hand. Indeed the formation of multipart mental images in the visuo-spatial scratch pad (the storage component of visuospatial working memory) should depend on the use of one or the other type of spatial relations coding, which thus gives the possibility to combine systematically the two coding types with a continuum on task load. In other words, using a working memory task we will be able to investigate the neuronal correlates of two spatial coding types at different difficulty levels. The systematic variation of the type of spatial relations coding and task load within such a working memory paradigm then provides the possibility to test competing predictions resulting from the two above-mentioned hypotheses about the origin of hemispheric lateralizations in the context of spatial relations coding. In the present study, the three factors of interest thus are (1) type of spatial relations coding, operationalized through the different task backgrounds, (2) task difficulty, operationalized through memory load and (3) hemispheric lateralization of neuronal activity. The SSC hypothesis predicts a strong ‘hemisphere × coding type’ interaction: the left hemisphere (and particularly the left parietal cortex) being more activated for categorical relations and the right hemisphere (notably the right parietal cortex) being more activated for coordinate relations. However, the SSC theory does not expect a ‘hemisphere × load’ interaction (e.g. easy/difficult tasks activating respectively the left/right hemisphere), nor strong hemispheric main effects (e.g. right dominance in all spatial coding types). The CSC hypothesis on the contrary, predicts the recruitment of essentially the same (lateralized) functional network components for both cod-

Fig. 1. Coordinate and categorical (regular and distorted) versions of the working-memory task, trial timing and fMRI acquisition. (A) Identical resting masks are followed by an encoding period where five crosses are presented on different backgrounds. In the comparison period, a figure composed of five gray squares is presented and subjects have to judge whether it covers the spatial positions corresponding to the previously presented crosses. (B) Timing of the different events occurring during a trial. (C) Scan frame numbering during a trial (as used in Figs. 4–6). The scan frame after presentation of the first cross (frame 1) is taken as base line for the evaluation of subsequent signal change. (D) The image on the left shows the parieto-frontal regions scanned in subjects 1–12, while the image on the right shows the occipito-temporo-frontal regions scanned in subjects 13–18.

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ing types, which will be differentially weighted along a difficulty continuum. One would therefore expect a main effect of hemispheric lateralization, as well as strong interactions for ‘coding type × load’ and, most importantly, for ‘hemisphere × load’. 2. Methods 2.1. Subjects Eighteen healthy male subjects recruited in the region of Paris (France) participated in the study. All subjects were strongly right-handed as measured by the Edinburgh handedness inventory (Oldfield, 1971) and were aged 20–31 years (mean 23.7). They had no history of neurological or psychiatric illness, had normal or corrected to normal visual acuity and were not taking any medication known to affect blood flow. The choice to limit subjects to the population of right-handed males was taken in order to ensure comparability with previous studies on the categorical/coordinate framework which were also mainly based on populations of right-handed males (Kosslyn et al., 1989). The study was approved by the local ethics committee (CCPPRB), and informed consent was provided by all participants.

2.2. Procedure, behavioural task and material We used event-related fMRI to measure brain activity while subjects progressively constructed a mental image made up by assembling a set of imagined squares whose spatial positions were cued by the brief presentation of small crosses (Fig. 1A). The memorization of five different sequentially presented elements in a 4 × 4 grid assured a continuous increase in memory load for every item, so that the effect of increasing memory load could be studied within and between the different spatial coding conditions. There were two different versions for the categorical task (presence of a grid): one with a regular grid similar to those used in the known grid versus no-grid protocols and one with a distorted grid. The distorted grid was designed to preserve all categorical relations in the figure to be constructed, but with a more irregular perceptive space categorization than in the regular grid condition (Fig. 1). Stimuli were generated by a Compaq laptop computer running ERTS (Experimental Runtime System, BeriSoft Cooperation, Frankfurt, Germany) under Microsoft Windows 95 real-mode DOS mode. During the fMRI session, stimuli were back-projected onto a screen situated at the head of the scanner’s bore by a Panasonic LCD projector. Subjects viewed the screen through a mirror attached to the head coil. Behavioural responses (accuracy and RTs) were recorded by a two-button keypad held in the subject’s right hand and connected to the computer by a fiber-optic cable. The display consisted of a blue fixation point on a square-shaped background. Each item started with the presentation of a resting background which was identical for all types of items (Fig. 1A). After 6430 ms this resting background was replaced by one which determined the item type: a grey background either without a grid, with a distorted 4 × 4 grid or with a regular 4 × 4 grid. After 1005 ms the first cross appeared on this background cueing a spatial location where the subject was instructed to mentally imagine a dark square fitting the perceived (in case of the presence of a grid) or an imagined (in case of the absence of a grid) 4 × 4 subdivision of the background. The cross remained for only 67 ms in order to prevent eye movements of the subject who was instructed to permanently focus on the blue fixation point in the center of the screen. After 3014 ms, the second cross appeared on the background for 67 ms, again followed by a 3014 ms delay period before the onset of the third cross and so forth. After the fifth cross, there was again a delay period of 3014 ms, then the background disappeared for 151 ms before the comparison configuration appeared, consisting of a configuration of five dark squares contained in a 4 × 4 subdivision of the same background that was used during the encoding period. This comparison stimulus remained for a fixed time period of 2000 ms during which the subject had to give his answer (Fig. 1B). Subjects were asked to give their answers as quickly as possible but without sacrificing accuracy. They were instructed to answer with their right index finger when they detected a difference between the comparison configuration and the memorized spatial configuration constructed at the locations cued by the five crosses and they answered with their right middle finger when the two configurations were identical. When subjects

did not answer during the 2000 ms of the comparison period, their RT was set to 2200 ms and their answer considered as incorrect. Subjects were instructed not to make any keypresses after the comparison period was over. A total of 90 trials was performed over three sessions, containing a total of 30 trials of each type. Fifty percent of the trials had identical encoding and comparison configurations while the other 50% had different configurations. Subjects were explicitly instructed to form mental images of the comparison stimulus and avoid using verbal strategies. Moreover the distracters were designed in such a way that the categorical relations of the original stimulus were preserved (i.e. the only difference between the encoding and the comparison stimuli was a positional change of one of the squares, so that even for different comparison stimuli the categorical relations were preserved). This was true in the categorical and in the coordinate conditions and therefore prevented comparison strategies based on verbal labels.

2.3. MR scanning For 12 subjects we performed parieto-frontal scans (primary region of interest; Fig. 1D) and for six subjects we performed occipito-temporo-frontal scans (secondary region of interest; Fig. 1D). Whole-brain scans were not performed, because the main ROI was known by previous work and in order to keep TR small. The MR images were acquired using a 1.5-tesla General Electric Signa System (GE Medical Systems, Milwaukee) equipped with a standard birdcage head coil. T2*-weighted, gradient echo, echo-planar images were acquired with TR = 2100 ms, TE = 60 ms, flip angle = 90◦ , 14 axial slices, 6 mm slice thickness (no gap), 240 mm in-plane FOV, ±62.5 kHz bandwidth, 64 × 64 grid, resulting in voxels that were 3.75 mm × 3.75 mm × 6.00 mm. Head movement was minimized using an adjustable headband and cushions. For each subject, 1089 functional volumes were acquired during three consecutive sessions of 12 min 42 s each (363 volumes per session). Following the functional images, a T1weighted whole-brain axial three-dimensional spoiled gradient-echo (3D SPGR) anatomical data set was acquired with min full TE, flip angle = 35◦ , 124 axial slices, 1.5 mm slice thickness, 240 mm in-plane FOV, 256 × 256 grid, resulting in voxels of 0.94 mm × 0.94 mm × 1.50 mm. These anatomical images were used for normalization of the functional images. Total time in the scanner was about 75 min for most of the subjects.

2.4. Preprocessing Image preprocessing was done using SPM2 (Wellcome Department of Cognitive Neurology, London, UK) implemented in MATLAB (version 6.5 Mathworks Inc., Sherborn, MA). Differences in image acquisition time between slices were corrected in order to make the data on each slice correspond to the same time point (the 9th out of 14 sequentially acquired slices was chosen as a reference slice so that after this correction each single volume reflected a time point corresponding to 1300 ms after the start of volume acquisition). Motion correction was then achieved by realigning the functional images of each series to the first image in that series. In order to correct for motion occurring between the acquisition of the functional series and the anatomical volume, the T1-weighted anatomical images were coregistered to the first functional image in each series. These coregistered anatomical images were then normalized to Talairach space using a template from the Montreal Neurological Institute. After this normalization, the resulting parameters were used to normalize the functional images. Normalized functional images were interpolated to 4 mm × 4 mm × 4 mm cubic voxels and spatially smoothed using a 6 mm full width at half-maximum Gaussian kernel. The first 4 volumes of each series were not used in subsequent data analysis in order to include only volumes in the analysis for which scanner signal was stabilized.

2.5. Data analysis (general linear model) The preprocessed data were analyzed with SPM99 (Wellcome Department of Cognitive Neurology, London, UK) implemented in MATLAB (version 6.1 Mathworks Inc., Sherborn, MA). For each subject, the BOLD response for the encoding period of the five sequentially presented crosses was modeled using a standard SPM99 canonical hemodynamic response function (consisting of the sum of two gamma functions) on the onset of each one of the five crosses

R. Martin et al. / Neuropsychologia 46 (2008) 576–594 presented in a single item. This resulted in a statistical model consisting of five partially overlapping and thus cumulative hemodynamic response functions. In addition to this statistical model covering the entire encoding period, three submodels modeling BOLD response for the beginning, the middle and the end of the encoding period were defined. These submodels were similar to the described model but they either used only the first two, the third, or the last two hemodynamic response functions out of the five that were included in the statistical model for the whole encoding period (covering the five sequentially presented crosses). We used a high-pass filter set at 438 s, corresponding to two and a half times the maximal temporal difference between the onset of two items of the same experimental condition (defined by the type of grid). Data were also low-pass filtered by temporally smoothing with a 4 s Gaussian kernel. A “fixed-effects” general linear model group analysis was performed on the group of 12 subjects with fronto-parietal scans (see Fig. 1D) and on the group of six subjects with temporo-occipital scans. The resultant statistical parametric maps were height corrected for multiple comparisons to a threshold of p < 0.01 using the false discovery rate method (Genovese, Lazar, & Nichols, 2002), while also excluding clusters with less than five neighbouring voxels. Individual analyses were also performed on each of the 18 subjects. These individual analyses were used for a secondary “random-effects” analysis for which an uncorrected threshold of p < 0.01 was chosen. There was one randomeffects analysis for the group of 12 subjects with fronto-parietal scans and one for the group of six subjects with temporo-occipital scans. As far as ROI analyses were concerned (see below), four ROIs were present as well in the fronto-parietal as in the temporo-occipital scans (angular gyrus, inferior precuneus, VLPC 47 and medial fronntal gyrus), thus yielding for these ROIs random-effects analyses based on all 18 subjects. The random-effects analysis confirmed the results of the fixed-effects analysis and thus broadens the generalization of the obtained results. The individual analyses were also used to evaluate activation time course and lateralization of hemispheric activation during the encoding period.

2.6. Activation time course and hemispheric differences A time course analysis of BOLD signal was performed for several regions of interest (ROI). The ROI masks were generated by the WFU PickAtlas tool which provides an automated method for neuroanatomic and cytoarchitectonic atlas-based ROI mask generation (Maldjian, Laurienti, Kraft, & Burdette, 2003). The ROIs were constructed in order to cover the main activation foci found in the abovementioned group analyses. The neuroanatomic localization and extent of ROI definition also took into account the neuroanatomic localizations described in previous work on categorical/coordinate tasks and visuo-spatial working memory. The main purpose of the time course analysis was to study the main effects and the interactions of the different types of spatial relations coding (i.e. background conditions), memory load (i.e. scan frames) and hemispheres on activation intensity. For every subject, adjusted raw BOLD signal was extracted for all bilaterally present voxels in a ROI showing a significant activation (p < 0.05 uncorrected) in at least one hemisphere for the three experimental conditions at the end of the encoding period (results show that at the end of the encoding period, the three experimental conditions yield very similar activation patterns in the different ROIs). So, a voxel was included bilaterally for time course extraction when it showed for example a significant activation in the left hemisphere for the first experimental condition and a significant activation in the right hemisphere for the other two experimental conditions, thus allowing for different experimental conditions to be represented in symmetrical regions of the two hemispheres while at the same time only including bilateral regions activated by all experimental conditions. When no voxel in a ROI met the abovementioned criterion for a specific subject, the height threshold (initially fixed at a value of z = 1.648) was progressively decremented by steps of 0.01 until the first voxel was found that met the criterion. For a specific ROI and subject, the mean adjusted raw BOLD signal was calculated for each combination of the three within-subject factors likely to have an influence on brain activation: the type of spatial relations coding (no grid, distorted grid, regular grid), the memory load (a total of 12 scan frames covered an entire item, see Fig. 1C), and the hemispheres (except for median regions where hemispheric differences were not taken into account). The calculation, for every subject and every ROI, of these 72 mean signal values (3 backgrounds × 12 scan frames × 2 hemispheres) was based on signal extraction of all bilateral voxels meeting

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the abovementioned activation criterion. The first scan frame for an item was defined as the one following the onset of the first cross (and thus marking the beginning of the encoding period). The activation level of this scan frame was taken as a baseline (set to 0 for each background and hemisphere) with regard to subsequent signal change (cf. Figs. 6–8). For each ROI, a data set with the 72 activation values for every subject whose scan covered this ROI was constructed and analyzed with SPSS (version 11). Group analyses were conducted on ROI data using repeated measures ANOVA. A first analysis with two withinsubject factors (spatial relation coding type and hemispheres) was performed in order to clarify hemispheric differences for initial spatial coding resulting only from the coding of the first cross (and thus without the memory load caused by the presentation of the remaining four crosses). This first analysis was based exclusively on the activation found for scan frame two which was the only scan frame that was prior to the presentation of the second cross and thus reflected solely activation due to the spatial encoding of the first cross. This analysis was thus representing hemispheric differences for a simple categorical/coordinate spatial encoding task without memory load which provides an experimental setting which is very similar to those used in previous categorical/coordinate studies. In order to analyze activation time course and hemispheric differences during working memory rehearsal, a second analysis was performed with three within-subject factors (spatial relation coding type, memory load and hemispheres except for median regions where the hemisphere-factor was omitted). The effect of memory load was reduced to three different periods: the beginning (mean value of scan frames 2–4), the middle (mean value of scan frames 5–7) and the end (mean value of scan frames 8–10) of the encoding process. The factor “scan frame” is thus reduced from 12 to 3 modalities which leaves sufficient degrees of freedom for calculating the different repeated measures ANOVAs despite a reduced sample size (varying from 6 to 18 subjects depending on the ROI under consideration). The significance levels indicated in Tables 2 and 3 give the significance values for the different main and interaction terms. These values are based on a multivariate approach when the test of sphericity signals significant departures from the sphericity assumption. Otherwise, the univariate approach is used for the determination of significance levels (which is more powerful under the sphericity assumption). In this repeated measures ANOVA, subjects were treated as a random effect so that results can be generalized across the population. The ROI masks were also used for calculating the percentage of activated voxels in a specified ROI (see %act column in Table 1). In order to use this percentage in the study of hemispheric differences, only symmetric voxels bilaterally available in the brain mask were used as the total number of available voxels in relation to which the percentage of activated voxels was determined. An activation threshold of uncorrected p < 0.05 was chosen in this analysis.

3. Results 3.1. Behavioural data The behavioural performance reveals that the items without grid were more difficult than both types of items showing a grid for space categorization, both in terms of response times (RT, see Fig. 2A; coordinate: 1338 ± 49 ms (mean ± S.E.M.); categorical distorted: 1176 ± 40 ms; categorical regular: 1111 ± 42 ms) and in terms of accuracy (Fig. 2B; coordinate: 74.8% ± 2.8% correct; categorical distorted: 84.3% ± 1.6% correct; categorical regular: 86.9% ± 1.3% correct). A repeated measures ANOVA revealed a highly significant overall effect of grid type, for response time (p < 0.001) and for accuracy (p < 0.001). The within subjects contrasts revealed a highly significant difference (p < 0.001) between the coordinate condition and the two pooled grid-present conditions for both RT and accuracy. The difference between the categorical regular condition and the categorical distorted condition was also significant for RT (p < 0.001), while there was no significant difference for accuracy (p = 0.135),

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Table 1 Regions of significant activation increase or decrease when contrasting the different coding types (in coordinates corresponding to the Montreal Neurological Institute template) Contrast and regiona

BA

Left hemisphere (or medial regions)

Right hemisphere

%act

x

y

z

%act

x

y

z

Zb

Coordinate vs. categorical regularc Parietal cortex activationsd Superior precuneus/SPL Inferior precuneus Inferior parietal lobule Supramarginal gyrus/TPJ Angular gyrus/MTG

7 7 40 40 39

61.3 47.8 48.0 24.7 5.6

−12 −12 −56 −40 −36

−68 −68 −36 −44 −56

44 36 44 36 36

3.78 3.16 4.74 3.80 3.81

69.7 39.1 53.0 20.0 34.7

16 16 40 36 36

−60 −68 −40 −48 −64

44 36 48 32 36

3.78 3.70 4.65 3.13 3.71

Premotor cortex activationsd FEF Inferior precentral sulcus

6, 8 6

56.3 56.7

−32 −44

−4 0

56 32

4.57 3.99

80.3 30.0

28 44

−4 0

56 28

4.83 3.46

Prefrontal cortex activationsd Anterior cingulate/CGf DLPFC DLPFC VLPFC VLPFC

32 9 10, 46 44, 45 47

26.6 65.6 69.2 43.3 29.5

0 −52 −44 −48 −32

8 4 40 0 20

48 40 20 24 0

3.88 4.06 3.47 3.34 3.07

– 73.3 68.5 48.5 48.7

– 44 44 48 32

– 28 32 28 24

– 36 24 24 0

– 3.91 3.99 3.79 3.43

Deactivationsd Medial frontal gyrusf Posterior cingulated/PCunf

9, 10 30, 31

60.7 39.3

−8 −4

52 −24

28 52

4.23 3.88

– –

– –

– –

– –

Categorical regular vs. coordinatec Occipital cortex activationse Middle occipital gyrus 18, 19 Cuneus 17, 18, 19 Lingual gyrus 17, 18, 19

35.3 46.7 45.7

−28 −20 −24

−80 −84 −84

0 12 −12

2.43 3.13 3.22

62.8 28.5 64.7

32 16 12

−76 −88 −80

0 8 −8

3.09 3.48 3.40

Categorical distorted vs. categorical regular Parietal cortex activationsd Superior precuneus/SPL 7 Inferior precuneus 7 Angular gyrus/MTG 39

17.2 9.8 –

−20 −20 –

−72 −80 –

44 36 –

2.38 2.66 n.s.

40.6 – 16.7

20 – 36

−64 – −68

48 – 24

2.71 n.s. 2.37

– –

Premotor cortex activationsd FEF

6, 8

–

–

–

–

n.s.

31.7

48

4

48

2.35

Prefrontal cortex activationsd DLPFC DLPFC

9 10, 46

– –

– –

– –

–– –

n.s. n.s.

12.1 24.6

44 36

4 52

36 8

2.39 2.51

a SPL, superior parietal lobule; TPJ, temporo-parietal junction; MTG, middle temporal gyrus (posterior superior part); FEF, frontal eye field; CG, cingulate gyrus; DLPFC, dorso-lateral prefrontal cortex; VLPFC, ventro-lateral prefrontal cortex; PCun, precuneus. b Z-scores are from the RFX-analysis. Only Z-scores from regions showing significant activations/deactivations in the random effects analysis are shown (p < .01 uncorrected). The corresponding fixed effects analysis showed highly significant and more extended activations/deactivations in the same cortical regions (p < .01 FDR corrected, 5 voxels extent threshold). c The contrasts comparing the no-grid condition with the distorted-grid condition are not shown. These contrasts yielded a similar, albeit less pronounced activation/deactivation difference than the contrasts comparing the no-grid condition with the regular-grid condition. d Regions identified on the group analyses of the 12 subjects with parieto-frontal scans. e Regions identified on the group analyses of the six subjects with occipito-temporo-frontal scans. f Medial regions.

although this non-significant difference could be due to a lack of statistical power. Overall, this result is in line with the finding that the encoding of coordinate spatial relations is generally more difficult than the encoding of categorical spatial relations when a similar encoding material is used (Bruyer et al., 1997). The slight, but significant difference between the regular and distorted categorical conditions, where the categorical distorted condition proves to be more difficult, indicates that this condition does not reinforce the use of more simple, abstract categorical

spatial relations. On the contrary, subjects’ performance was intermediate between the coordinate and the regular condition. 3.2. Activation differences between the three coding types 3.2.1. Functional network activated by the different coding conditions Fig. 3 shows a glassbrain view of the activations generated by the different coding type conditions at the beginning, in the

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Fig. 2. Working-memory task performance (n = 18). (A) Response time by trial type; (B) accuracy by trial type (mean, error bars represent S.E.M.).

middle and at the end of the encoding period. It shows that the three coding types rely essentially on similar neural networks including parietal, premotor and prefrontal regions (occipital regions were also activated but are not shown in this glassbrain which is only based on subjects with parieto-frontal scans). It also becomes clear from Fig. 3 that there are differences in the extent of activation between the three coding types, the coordinate condition leading to larger activation extents than the two categorical conditions. This larger activation extent for the coordinate condition is especially visible at the beginning and in the middle of the encoding period and is less pronounced at the end of it. 3.2.2. Activation differences between the coordinate condition and the two categorical conditions The contrast between the coordinate condition with either of the two categorical conditions yielded similar activation patterns. Albeit activation was generally more pronounced when comparing the coordinate condition with the categorical regular, than when comparing it with the categorical distorted condition. The coordinate condition induced higher activation (compared

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to the two categorical conditions) in a parieto-premotor-frontal network (Table 1). In the parietal cortex, we found higher activation bilaterally in a posterior region extending from the superior parietal lobule, through the superior and inferior precuneus to the angular gyrus, including the posterior superior part of the middle temporal gyrus. More anteriorly, activation was found in the inferior parietal lobule around the intraparietal sulcus and extending to the supramarginal gyrus around the temporo-parietal junction. Activation in premotor cortex included the frontal eye field (defined as the intersection of Brodmann areas 6 and 8 with the middle frontal gyrus) (Maldjian et al., 2003) and extended ventrally to the inferior precentral sulcus. In prefrontal cortex, we found medial activation in the anterior cingulate extending to the part of the cingulate gyrus covered by Brodmann area 32 (Fig. 4). Activation was also found in dorsolateral prefrontal cortex (DLPFC) covering Brodmann areas 9, 10 and 46, as well as in ventrolateral prefrontal cortex (VLPFC) covering Brodmann areas 44, 45 and 47 (Fig. 4). The involvement of a similar neural network in the processing of coordinate and categorical spatial relations has been documented in other studies (Kosslyn et al., 1998; Trojano et al., 2002). The only cortical region where the categorical conditions yielded higher activation compared to the coordinate condition was the extrastriate cortex. The contrasts between each of the two grid conditions and the coordinate condition showed similar activation patterns including the middle occipital gyrus, lateral cuneus and lateral lingual gyrus (Table 1). Besides these activation effects, a progressive deactivation could be found for every condition in the medial frontal gyrus (Brodmann areas 9, 10) and in the posterior cingulate/precuneus (Brodmann areas 30, 31) (see Table 1). This deactivation was stronger in the coordinate condition than in the two grid conditions, as the corresponding contrast shows (Table 1).

3.2.3. Activation differences between the categorical distorted and the categorical regular condition The activation difference between the categorical distorted and the categorical regular condition revealed activation differences restricted to the abovementioned parieto-premotor-frontal network, but a with clear right-hemisphere dominance. Nevertheless, activations resulting from the corresponding contrast were small compared to the differences existing between the coordinate and the two categorical conditions. Concerning lateralization, we found that only the posterior parietal region extending from the superior parietal lobule to the inferior precuneus yielded bilateral activation (albeit with a stronger right hemisphere activation in the superior precuneus/superior parietal lobule), but the remaining activations were restricted to the right hemisphere. They were found in the right angular gyrus, the right frontal eye field and the right DLPFC (Brodmann areas 9, 10, 46) (Table 1). From an activation point of view, the categorical distorted condition is thus intermediate between the coordinate and the categorical regular conditions, although it is much closer to the categorical regular than to the coordinate condition, in line with the behavioural data.

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Fig. 3. Cortical regions activated by the three different working memory tasks at the beginning, in the middle and at the end of the encoding period. The three coding types rely essentially on similar neural networks including parietal, premotor and prefrontal regions, but the three coding types activate the network to different extents. Only activated regions from the group analyses of the 12 subjects with parieto-frontal scans are shown (p < .01 FDR correction, 5 voxels extent threshold). (A) Categorical regular condition; (B) categorical distorted condition; (C) coordinate condition.

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Fig. 4. Activation time course by trial type illustrated in prefrontal regions of interest that were more strongly activated by the coordinate condition than by the two categorical conditions. Mean signal change resulting from left and right hemisphere activations is shown. (CG, cingulate gyrus; DLPFC, dorso-lateral prefrontal cortex; VLPFC, ventro-lateral prefrontal cortex).

3.3. Hemispheric differences for initial spatial encoding Table 2 provides significance levels of main and interaction effects of a Repeated Measures ANOVA analysis for activation due to initial spatial encoding in the absence of working memory rehearsal (i.e. before the presentation of the second cross). The table provides results for activated brain regions with factors hemisphere and coding type. The initial activation measured should provide activations for a simple spatial encoding task without memory load which provides a close match to previous categorical/coordinate studies mainly using simple spatial encoding tasks. Results show that there are only three regions which show consistent hemispheric differences across subjects: the inferior parietal lobule shows higher activations in the right hemisphere (p = .016), while the inferior precuneus and cuneus show higher activations for the left hemisphere (p = .002 for inferior precuneus and p = .018 for cuneus, see Fig. 5). From these three regions (and more generally from all the activated regions) only one region, namely the inferior parietal lobule shows a consistent and strong hemisphere × coding type interaction (p < .001). This interaction is due to a relatively higher right hemisphere activation in the coordinate condition compared to the two categorical conditions which show a less pronounced right hemisphere advantage (see Fig. 5). This right hemisphere advantage for coordinate encoding in a parietal region known for its implication in spatial relations coding is consistent with the SSC hypothesis, but nevertheless it has to be noticed that this region does not

show a relatively higher activation of the left hemisphere for either one of the two categorical conditions which would also have been expected under the SSC hypothesis. It also has to be noticed that among the two regions which show a higher left hemisphere activation (inferior precuneus and cuneus), we also find the only region which shows consistently higher activation for the two categorical conditions compared to the coordinate condition, namely the cuneus. But neither the inferior precuneus, nor the cuneus show a hemisphere × coding type interaction in the sense of a relatively higher activation of the left hemisphere compared to the right for categorical compared to coordinate encodings. 3.4. Hemispheric differences for activation time course during working memory rehearsal Table 3 provides significance levels of main and interaction effects of a Repeated Measures ANOVA analysis for activation time courses in activated brain regions with factors hemisphere, coding type and memory load. 3.4.1. Hemisphere × coding type interactions Hemisphere × coding type interactions which are expected under the SSC hypothesis were only significant or close to significance in parietal and premotor regions. The only region that reached significance was the inferior parietal lobule (p = .033), but the interaction was due to the fact that an overall right hemisphere advantage for this region, that was found for every coding

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Table 2 Repeated measures MANOVA results on activation time course with factors hemisphere and coding type, when analyzing the response to the first cross Regiona

BA

Hemisphere (p-value)

Coding type (p-value)

Hemisphere × coding type (p-value)

Nb

Left/right activations Parietal cortex Superior precuneus/SPL Inferior precuneus Inferior parietal lobule Supramarginal gyrus/TPJ Angular gyrus/MTG

7 7 40 40 39

.081 .002 .016 .069 n.s.

.007 .015 .001 .002 .003

0.098 n.s. <.001 n.s. n.s.

12 18 12 12 18

Premotor cortex FEF Inferior precentral sulcus

6, 8 6

n.s. n.s.

.001 .031

n.s. n.s.

12 12

Prefrontal cortex DLPFC DLPFC VLPFC VLPFC

9 10, 46 44, 45 47

n.s. .062 n.s. n.s.

.001 .098 .002 .002

n.s. n.s. n.s. n.s.

12 12 12 18

Occipital cortex Middle occipital gyrus Cuneus Lingual gyrus

18, 19 17, 18, 19 17, 18, 19

n.s. .018 n.s.

.075 .015 n.s.

n.s. n.s. n.s.

6 6 6

a SPL, superior parietal lobule; TPJ, temporo-parietal junction; MTG, middle temporal gyrus (posterior superior part); FEF, frontal eye field; DLPFC, dorso-lateral prefrontal cortex; VLPFC, ventro-lateral prefrontal cortex. b Depending on the localization of the region of interest, only the 12 subjects with parieto-frontal scans, only the six subjects with occipito-temporo-frontal scans, or all the 18 subjects (in case of regions lying in the intersection of the two previously mentioned scan areas) were included in the analyses.

type (p = .006 for main effect of hemisphere), was stronger in the coordinate condition than in the two categorical conditions (Fig. 6). Thus no hemispheric specialization for a specific coding type could be found in this region. This was also true for most of the other regions in parietal/premotor cortex for which an hemisphere × coding type interaction close to significance was found: for the angular gyrus, the frontal eye field and the inferior precentral sulcus all showed consistent hemispheric differences through all different coding types, but with different effect sizes for hemisphere according to coding type, thus yielding significant main effects for hemisphere, as well as hemi-

sphere × coding type interactions close to significance (Fig. 6). An overall right hemisphere advantage was found for the angular gyrus (p = .030) and the frontal eye field (p = .001), while an overall left hemisphere advantage was found for inferior precentral sulcus (p = 0.032) (Fig. 7). The only region that showed an activation pattern that was slightly in agreement with the hemisphere × coding type interaction expected from the SSC hypothesis was the superior precuneus (BA7) (Fig. 8). This region showed a small but significant (paired t-test, p = .019) left hemisphere advantage for the categorical regular coding type at the beginning of the coding period, which was still present but

Fig. 5. Activation as a function of grid type and hemisphere for initial spatial encoding. The activation shown is based exclusively on the activation found for scan frame two which is the only scan frame that is prior to the presentation of the second cross and thus reflects solely activation due to the spatial encoding of the first cross. The three regions that are shown (inferior parietal lobule N = 18, inferior precuneus N = 12 and cuneus N = 6) are the only regions showing significant hemispheric differences for initial spatial coding. For the inferior parietal lobule, there is also a highly significant interaction of coding type × hemisphere.

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Table 3 Repeated measures MANOVA results on activation time course with factors hemisphere, coding type and memory load, when analyzing the response over the entire encoding period Regiona

BA

Main effects (p-value)

1st order interactions (p-value)

2nd order interaction (p-value)

Nc

Hemisphere × coding type

Hemisphere × memory type

Coding type × memory load

Hemisphere × coding type × memory load

<.001 <.001 <.001 <.001 <.001

.080 n.s. .033 n.s. .072

.007 .003 <.001 n.s. .005

.065 n.s. .002 .001 n.s.

n.s. n.s. .031 n.s. n.s.

12 18 12 12 18

<.001 .015

<.001 <.001

.081 .073

<.001 n.s.

.001 .096

n.s. n.s.

12 12

n.s. n.s. n.s. n.s.

.001 .003 <.001 <.001

<.001 <.001 <.001 <.001

n.s. n.s. n.s. n.s.

n.s. n.s. n.s. n.s.

.006 .022 .029 .026

.070 n.s. n.s. n.s.

12 12 12 18

18, 19 17, 18, 19 17, 18, 19

n.s. .014 n.s.

=.002 .054 .023

<.001 <.001 .001

n.s. n.s. n.s.

n.s. n.s. n.s.

.015 .036. n.s.

.019 .010 n.s.

6 6 6

Medial activations Anterior cingulate/CG

32

–

<.001

<.001

–

–

.011

–

12

Medial deactivations Medial frontal gyrus Posterior cingulate/PCun

9,10 30, 31

– –

.016 n.s.

<.001 .001

– –

– –

.002 n.s.

– –

18 12

Hemisphere

Coding type

7 7 40 40 39

n.s. .031 .006 .007 .030

.001 .022 <.001 <.001 .002

Premotor cortex FEF Inferior precentral sulcus

6, 8 6

.001 .032

Prefrontal cortex DLPFC DLPFC VLPFC VLPFC

9 10, 46 44, 45 47

Occipital cortex Middle occipital gyrus Cuneus Lingual gyrus

Left/right activations Parietal cortex Superior precuneus/SPL Inferior precuneus Inferior parietal lobule Supramarginal gyrus/TPJ Angular gyrus/MTG

Memory loadb

a

SPL, superior parietal lobule; TPJ, temporo-parietal junction; MTG, middle temporal gyrus (posterior superior part); FEF, frontal eye field; DLPFC, dorso-lateral prefrontal cortex; VLPFC, ventro-lateral prefrontal cortex; CG, cingulated gyrus; PCun, precuneus. b The effect of the memory load (i.e. scan frames) was reduced to three different periods: the beginning (mean value of scan frames 2–4), the middle (mean value of scan frames 5–7) and the end (mean value of scan frames 8–10) of the encoding process (see Section 2). c Depending on the localization of the region of interest, only the 12 subjects with parieto-frontal scans, only the six subjects with occipito-temporo-frontal scans, or all the 18 subjects (in case of regions lying in the intersection of the two previously mentioned scan areas) were included in the analyses.

not significant for the categorical distorted task and which was completely absent at the beginning of the coordinate coding (but there was still no reversal of hemispheric advantage, i.e. no right hemisphere advantage for the coordinate condition at the beginning of the coding period in this region). Nevertheless, it has to be noticed that at the end of the coding period, the superior precuneus showed a higher right hemisphere activation for every coding type, but this effect did not reach significance. 3.4.2. Hemisphere × memory load interactions Hemisphere × memory load interactions which are expected under the CSC hypothesis were also mainly found in the parietal and premotor cortex. Unlike the hemisphere × coding type interactions which mostly failed to reach significance, the hemisphere × memory load interactions were significant in several parietal and premotor regions. For the frontal eye field and the angular gyrus this significant interaction is due to a clear increase of an initially small right hemisphere advantage with increasing memory load (Fig. 6). The hemisphere × memory load interac-

tion effect for the inferior parietal lobule is also due to a right hemisphere advantage which is modulated by memory load, but for this region the largest hemispheric difference is found for a medium memory load while the hemispheric difference is less pronounced for small and large memory loads (Fig. 6). A similar modulation of hemispheric difference (with largest difference for medium memory load) but with an overall left hemisphere advantage was found for the inferior precuneus (Fig. 7). The significant interaction effect for the superior precuneus was due to an inversion of small hemispheric differences from low memory load (slight left hemisphere advantage) to high memory load (slight right hemisphere advantage, see Section 3.4.1). 3.4.3. Hemispheric differences as part of a second-order interaction hemisphere × coding type × memory load A significant second-order interaction (hemisphere × coding type × memory load) was found for the inferior parietal lobule, a region for which an overall right hemisphere advantage was found (Fig. 6). Hemispheric differences were largest for medium

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Fig. 6. Activation time course by trial type and hemisphere illustrated in regions of interest showing a higher right hemisphere activation (main effect for hemisphere), as well as hemisphere × coding type interactions. The only region where the hemisphere × coding type interaction (expected under the SSC hypothesis) reached significance was the inferior parietal lobule, but the interaction was due to the fact that a generic right hemisphere advantage for this region was stronger in the coordinate condition than in the two categorical conditions. (MTG, middle temporal gyrus; FEF, frontal eye field).

memory load and overall activation was more rapid in the coordinate than in the two categorical conditions. Two occipital regions (middle occipital gyrus and cuneus) also showed a significant second-order interaction, but with an overall left hemisphere advantage (Fig. 7). In these regions, left hemisphere activation is stronger in the categorical conditions than in the coordinate condition, a difference which is especially visible at low and medium memory load and which becomes less important at high memory load. 3.5. Interactions between coding type and memory load A major difference between the categorical and the coordinate conditions turned out to be the absence of prefrontal

activation in the two categorical conditions, but only at the beginning of the encoding period, thus at a low memory load (Fig. 3A and B). For the coordinate condition however, prefrontal activation was found right from the beginning of the encoding period (Fig. 3C). In the middle and end parts of the encoding period, prefrontal activation was also shown for the two categorical conditions, thus leading to more and more similar activation patterns for the three different conditions at high memory load (end of the encoding period, see Fig. 3). This differential activity pattern gave way more rapidly for the categorical distorted than for the categorical regular condition. A detailed analysis of the activation time course (Fig. 4) shows that the initiation of this activation process in the prefrontal cortex for the two categorical conditions generally started

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Fig. 7. Activation time course by trial type and hemisphere illustrated in regions of interest showing a higher left hemisphere activation. The cuneus also showed a significant second-order interaction (hemisphere × coding type × memory load), since the left hemisphere activation was stronger in the categorical conditions than in the coordinate condition, but this difference was larger at low and medium memory loads than at high memory loads.

with the 5th scan frame, which roughly corresponded to the presentation of the 4th cross (out of 5) of the encoding period (see Fig. 1B and C). The later activation of the prefrontal cortex for the two categorical conditions compared to the coordinate

condition corresponded to a coding type × memory load interaction for the repeated measures ANOVA carried out on signal time course (see Section 2). This interaction is indeed significant (p < .05) for every prefrontal region under consideration

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Fig. 8. Activation time course by trial type and hemisphere illustrated in the superior precuneus (BA7). This region was the only one showing an activation pattern that was slightly in agreement with the hemisphere × coding type interaction expected from SSC hypothesis. At the beginning of the coding period this region showed a small but significant left hemisphere advantage for the categorical regular coding type, which was still present but not significant for the categorical distorted task and which was completely absent in the coordinate coding. However, the SSC hypothesis cannot account for the fact that we failed to observe a reversal of the hemispheric advantage (i.e. no right hemisphere advantage for the coordinate condition). It is also not in line with the fact that the superior precuneus tended to show a stronger right hemisphere activation for every coding type at the end of the coding period.

(Table 3). The same effect of a later activation for the two categorical conditions occurred for several other regions: inferior parietal lobule (p = .002), supramarginal gyrus (p = .001), inferior precentral sulcus (albeit only marginally significant p = .096) (see Table 3). The inverse pattern, namely a later activation in the coordinate condition compared to the two categorical conditions thus also leading to a coding type × memory load interaction was found in the extrastriate cortex, in the middle occipital gyrus (p = .015) and in the cuneus (p = .036) (see Table 3 and Fig. 7). The activation time course also indicates that there were only two regions which showed consistent activations for all conditions right from the beginning of the encoding period, namely the superior precuneus/parietal lobule and the frontal eye field (see Figs. 8 and 6). 4. Discussion To our knowledge this is one of the first functional imaging studies investigating the hemispheric lateralization of different types of spatial relations coding (as defined by the categorical/coordinate framework) as a function of task difficulty (instantiated here by memory load). The present results show that there is a much greater continuity between the coding of categorical and coordinate spatial relations than has been assumed so far. Indeed, in line with previous work on categorical and coordinate spatial relations coding (Baciu et al., 1999; Kosslyn et al., 1998; Trojano et al., 2002), we observed hemispheric differences, especially in the parietal cortex, but we did not find the ‘hemisphere × coding type’ interactions which would be expected according to the separate spatial coding theory. A consistent and strong hemisphere × coding type interaction which was partly in line with the SSC hypothesis was only found in inferior parietal lobule for both initial encoding and encoding under working memory load. This parietal region known to be part of the spatial encoding functional network showed indeed a relatively higher right hemisphere activation for coordinate

encoding compared to the two categorical conditions. But at the same time we did not find a relatively higher activation of the left hemisphere for the two categorical conditions in this region. Instead, we found for this and for other regions essentially the same hemispheric differences for the different types of spatial relations coding. However, the effect size of these hemispheric differences often varied with task difficulty (i.e. memory load) thus leading to significant ‘hemisphere × load’ interactions which is a result lending support to the continuous spatial coding hypothesis (see also van der Lubbe et al., 2006). The direct comparison of the categorical-distorted and the categorical-regular conditions also supports the CSC hypothesis. The parieto-premotor-frontal network resulting from this contrast resembled the network obtained when comparing the coordinate to the categorical working memory tasks. The activation pattern related to the categorical distorted condition was intermediate between the coordinate and the categorical regular conditions. This result contrasts with the SSC hypothesis, which predicts that the distorted grid condition should even have reinforced the use of abstract perceptually delimited spatial equivalence classes (i.e. categorical relations) compared to the precise coordinate codings that are needed in the coordinate condition. When taking a closer look at the present results, one finds that they are not necessarily in contradiction with previous reports showing hemispheric differences for categorical/coordinate spatial relations. When analyzing for instance the response to the first cross only, we find a right hemisphere advantage in the inferior parietal cortex which is stronger for the coordinate condition and a higher left hemisphere activation for the categorical condition in the cuneus. This activation pattern could very well lead to the hemisphere × coding type interaction observed in studies giving support to the SSC hypothesis by using the divided hemifield technique and observing hemispheric differences at a very global and undifferentiated level. But the more differ-

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entiated time course analyses which are possibly due to the working memory task used in combination with an event-related paradigm give a different explanation for these hemispheric differences, as they occur in different regions of an extended neural network and are under the influence of task load factors. Similar results were recently found by van der Ham, van Wezel, Oleksiak, & Postma (2007) who found the expected hemisphere × coding type interaction only for brief and not for longer retention intervals. Essential questions are therefore (1) which parts of the network are responsible for what kind of cognitive processes and (2) how do these processes relate to the different types of spatial relations coding? The only regions which are consistently activated by all conditions from the beginning of the coding period are the superior precuneus and the frontal eye field. These regions are known to be involved in orienting attention and might be responsible for covert attention orienting (Corbetta, Miezin, Shulman, & Petersen, 1993; Gitelman et al., 1999; Grosbras & Paus, 2002; Nobre et al., 1997) to the spatial positions cued by the five sequentially presented crosses. This process is required for each of the three conditions, independently of coding type. In line with the well-known right hemisphere dominance of attention orienting (Corbetta et al., 1993; Gitelman et al., 1999; Grosbras & Paus, 2002; Nobre et al., 1997), we found a strongly right dominant activation pattern in the frontal eye field. The superior precuneus showed a less clear lateralization pattern, even having a tendency to a left hemisphere advantage at the start of the categorical coding conditions. This latter finding could be due to an initial input of left hemisphere dominant information coming from the extrastriate cortex (especially the cuneus) to the superior precuneus and parietal lobule (see below). Our results show that all the right-hemisphere dominant activations are found in parietal and premotor cortex which are generally more activated in the coordinate coding condition. Consistent with previous research, the coding of coordinate spatial relations might rely above all on the right angular gyrus (Baciu et al., 1999), not because this region is specialized in the processing of coordinate spatial relations, but because it is responsible for reorienting and maintaining spatial attention. Several authors reported that the angular gyrus plays a role in reorienting attention towards unattended visible, as well as invisible memorized positions (Chambers, Payne, Stokes, & Mattingley, 2004; Rushworth, Ellison, & Walsh, 2001). The angular gyrus also plays a role in maintaining spatial focus on these positions (Nobre et al., 2004). Note that coding of coordinate spatial relations heavily relies on the latter processes of orienting and maintaining attention to memorized spatial positions. Indeed, coordinate spatial relations coding should imply the direction of spatial attention towards the visible stimulus whose coordinate position has to be evaluated. Then attention is redirected to the invisible, but memorized space limit (for example a grid or a 1 cm distance) to evaluate the distance between the physically present stimulus and the memorized landmark. This process of redirection might well rely on the well-known functional network of spatial attention including the right angular gyrus (Behrmann et al., 2004). Additional executive attentional processes would be supported by the prefrontal cortex. Given the

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initial differences in difficulty level between the categorical and coordinate conditions, these additional prefrontal resources are already present at low loads in the coordinate task, but they only appear at high loads in the categorical conditions (as indicated by the significant ‘coding type × load’ interactions). According to the CSC hypothesis, coordinate coding tasks would thus be generally more difficult (because more resource-intensive) than similar categorical relations coding tasks. The right hemisphere would essentially play a role in providing the supplementary spatial attention that is needed for handling the increased load which is implied for most situations of coordinate relations coding. The above proposal would explain both the right hemisphere advantage of coordinate compared to categorical spatial relations coding and the temporal precedence observed for the prefrontal activation in the former compared to the latter condition. Such a view would also explain why an intact right hemisphere is sufficient for the successful realization of both coordinate and categorical tasks, while an intact left hemisphere is not sufficient for a successful realization of more complex coordinate tasks (Schatz, Craft, Koby, & DeBaun, 2004). One of the major, but unexpected results of this research is the finding that both categorical conditions did not activate the prefrontal cortex until the presentation of the 4th cross. This might imply that, when a perceptual categorization of space is provided, a single configuration of up to three spatial stimuli can be stored in posterior parietal and extrastriate visual cortices (Todd & Marois, 2004). This posterior parietal and extrastriate store of three spatial positions could be related to the fact that a quantity of up to three elements can be immediately recognized, without counting, a phenomenon known as subitizing (Dehaene & Cohen, 1994; Kaufman, Lord, Reese, & Volkmann, 1949) and related to extrastriate preattentive visual processing (Piazza, Mechelli, Butterworth, & Price, 2002; Sathian et al., 1999; Trick & Pylyshyn, 1994). The recruitment of the prefrontal cortex beyond three spatial stimuli might be the consequence of a multipart image storage which requires an updating process where attention has to be continuously redirected to the memorized stimulus parts (Corbetta, Kincade, & Shulman, 2002), thus adding spatial attention and executive resources for the coordination of this attentional updating process. Such a close link between visuo-spatial working memory, attentional and executive processes is in line with previous work (Awh, Jonides, & Reuter Lorenz, 1998; Awh et al., 1999; Engle, 2002; Kane & Engle, 2003). This attentional updating is characterized by temporal aspects of covert shift sequencing as well as spatial aspects of redirecting attention to spatial locations of interest. The temporal aspects of motor sequencing might be assured by the left supramarginal gyrus (Rushworth et al., 2001) and the left inferior precentral sulcus (Beauchamp, Petit, Ellmore, Ingeholm, & Haxby, 2001), while the spatial redirection should rely above all on the right angular gyrus. This shared implication of a left-hemisphere dominant network for temporal attention and a right hemisphere dominant network for spatial attention (Coull, Frith, & Nobre, 1997; Coull & Nobre, 1998) conjointly assuring the attentional process of working memory update might explain the lack of hemispheric differences in the prefrontal cortex. Indeed the left

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prefrontal cortex might assure the executive processing for the temporal attention aspects, while right prefrontal regions do so for the spatial attention aspects. The deactivation observed in frontal medial and posterior cingulate cortex underpins the implication of an attentional network, since such a deactivation is characteristically found in tasks recruiting attentional processes (Raichle et al., 2001). In line with the generation of mental images occurring in the present working memory tasks, we detected activation predominantly in the left inferior precuneus. This region is known to play a role in visual mental image generation (Fletcher, Shallice, Frith, Frackowiak, & Dolan, 1996; Ghaem, Mellet, Crivello, Tzourio, & Mazoyer, 1997; Ishai, Ungerleider, & Haxby, 2000), with a left hemisphere advantage (Behrmann, 2000; D’Esposito et al., 1997; Loverock & Modigliani, 1995). The highest activation level was obtained in the coordinate/no-grid condition, which also has the highest demands in terms of mental image generation. The occipital cortex was also the only region showing higher activation in the categorical conditions and it mainly showed a higher left hemisphere activation. The higher left hemisphere activation found in the lateral cuneus (and which extends into the middle occipital gyrus) might be the consequence of a left-hemisphere specialization for specific types of visual processing which are required by the processing of the grids. Here we observe this left hemisphere advantage in response to the first cross and it is maintained over the entire time course of working memory rehearsal period. Such kind of visual processing might often, but not always, be associated with categorical coding situations, thus explaining the inconsistent left hemisphere advantages found for categorical spatial relations. Such a left hemisphere advantage in extrastriate cortex has been found for mental image generation (D’Esposito et al., 1997), pattern recognition (Barrett et al., 2001), discrimination of overlapping shapes (Larsson et al., 2002) and cortical mechanisms common for processing visual object construction and discrimination (Georgopoulos et al., 2001). A simple categorical relations coding situation might thus correspond to a pattern recognition task, where for example a pattern corresponding to the labels “left” or “right” has been memorized and is recognized by the means of left hemisphere dominant extrastriatal processing. A simple coordinate spatial relations coding task might also be viewed as such a pattern recognition task or turned into it by training. This could explain why simple coordinate tasks show a left hemisphere advantage or tend to lose their right hemisphere advantage with practice. In summary the current findings support the CSC hypothesis, suggesting that the coding of categorical and coordinate spatial relations does not show qualitative, but rather quantitative differences (see also van der Lubbe et al., 2006). Our data indicate that both types of spatial relations coding draw on a common neural network, whose exact profile depends on the task requirements. This extended network most likely includes general-purpose subparts, like attentional processes, which show hemispheric differences. According to the specific type of spatial coding, the exact weighting of these subparts can vary and thereby lead to a hemispheric lateralization pattern. We therefore propose that the observed hemispheric dominances do not translate the

existence of dedicated lateralized modules for the coding of categorical versus coordinate spatial relations, but that they reveal the differential weights of general-purpose processing units. In other words, the observed hemispheric dominances do not support the SSC, but lend support to the CSC hypothesis and offer an explanation for the often inconsistent results found in the categorical/coordinate literature. Moreover, our work provides information regarding the nature of visuo-spatial working memory, which seems to consist of a posterior parietal and extrastriate visuo-perceptive store for up to three spatial positions combined with an attentional updating process under executive control for the storage of more demanding visuo-spatial arrays containing more than three elements.

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