1 Max-Planck-Institut für Hirnforschung, Deutschordenstraße 46, D-60528 Frankfurt, Departments of , 2 Psychiatry and , 3 Neuroradiology, Johann Wolfgang Goethe-Universität, Theodor-Stern-Kai 7, D-60590 Frankfurt, Germany and , 4 Department of Cognitive Neuroscience, Faculty of Psychology, Maastricht University, Postbus 616, 6200MD Maastricht, The Netherlands
Matthias H.J. Munk, Abteilung Neuro-physiologie, Max-Planck-Institut für Hirnforschung, Deutschordenstraße 46, D-60528 Frankfurt, Germany. Email: munk{at}mpih-frankfurt.mpg.de.
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Abstract |
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Introduction |
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In addition to prefrontal cortex, IT and PP cortex have also been assigned functions in STM. In IT, neurons exhibit delay activity when monkeys perform DMS tasks preferentially for the retention of object-specific features (Miller et al., 1993), while PP neurons seem to be activated more during the retention of spatial relations (Constantinidis and Steinmetz, 1996
). Relatively little is known about how these areas cooperate with the prefrontal cortex in STM. In order to address this issue, one requires information about the spatial and temporal distribution of activity associated with encoding, retention and retrieval of information in both domains.
Despite the rather limited temporal resolution of fMRI, evaluation of single trial responses (event-related fMRI) can provide some information about the temporal sequence of processing (Zarahn et al., 1999) and about the coherence of processes occurring simultaneously in different areas (Goebel et al., 1998a
). We therefore applied event-related fMRI to investigate visual STM in a design that allowed us to separate in time the encoding, retention, retrieval and response phases. We used a DDT rather than a conventional DMS task, because the latter is not balanced with respect to attention and response preparation for matching and non-matching trials. In experiment 1, subjects performed DDT tasks on series of different objects (Postle and DEsposito, 1999
) or identical objects in different places (where, see Fig. 1A
). Functional images were acquired at high rate (TR = 1 s) in order to allow for a separation of activity that is evoked by the presentation of the stimuli from the sustained activity that is related to retention. In experiment 2, visual sample stimuli consisted of four natural objects that were sequentially presented in an imaginary two-dimensional grid (Fig. 2A
). After the delay period, subjects had to decide whether one object presented as test stimulus at one of the positions of the imaginary grid matched one of the objects (Postle and DEsposito, 1999
), locations (Postle and DEsposito, 1999
), or both (what & where) of the preceding sample stimulus. This design permitted the comparison of cortical activation patterns associated with retention of conjunctions and single features (Rypma and DEsposito, 1999
), respectively. As most human subjects attempt to use verbal descriptions in order to retain information about natural objects, we added a control experiment using abstract stimuli.
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Materials and Methods |
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We recruited five right-handed healthy volunteers (four male, one female; mean age 30.8 years, range 2736 years) for experiment 1, 10 (eight male, two female; mean age 29.2 years, range 2439 years) for experiment 2 and eight (six male, two female; mean age 27.2 years, range 2135 years) for the non-verbal control experiment, who gave their informed consent to participate in the study. The reported experiments were undertaken with the understanding and written consent of each subject and in accordance with the Declaration of Helsinki. Three volunteers participated in all experiments. Experiment 1 was preceded by a training session which allowed subjects to undertake as many trials as necessary to familiarize themselves with the structure and timing of the task. Visual stimuli (for details about stimulus content and sequence see legends to Figs 1 and 2) were delivered under PC control to an LCD projector (EIKI LC-6000). The image was back-projected onto a frosted screen positioned at the foot end of the scanner.
In experiment 1, four randomly drawn (of 24 possible) sample stimuli (fruit drawings) were presented in rapid sequence (250 ms per item) during the first second of each trial. During what trials, a sequence of sample stimuli appeared at the center of the screen. During where trials, a single object appeared at four out of eight possible parafoveal positions. Thus, during the sample presentation period, the what and where tasks differed only by the number of different objects and the respective positions of the objects on the display. After a delay of 11 s, a test stimulus was presented for 4 s at the center of the screen in the what trials, or at one of the eight possible positions in the where trials. Subjects had to respond by left or right button presses (L/R in the lower traces of Fig. 1) if they detected a match or non-match, respectively. Following the test and response period, the fixation cross turned green or red for correct and incorrect responses, respectively. The design of the control experiment matched that of the what condition of experiment 1, except that non-natural objects (BORTS: blurred outlines of random tetris shapes) were used as visual stimuli.
In experiment 2, three different instructions (what, where and what and where) were presented at the beginning of each trial in a pseudo-randomized sequence. The structure of all trials was identical. Four out of 24 different fruit drawings were presented in 4 s (1 s per item) in 1 out of 8, 12 or 16 spatial positions, depending on subjective performance. After a delay of 12 s, a test stimulus was presented for 4 s, after which the subjects had to respond as above. Prior to experiment 2, each subject had to perform a training session in front of a PC screen with at least 240 trials, for which reaction times were recorded. The training sessions were balanced for match and non-match trials for each task type. Depending on the task instruction, which was randomized for each trial, the task-relevant and the task-irrelevant (spatial versus object) information was also balanced. The scanner sessions were then designed for each individual subject by selecting 3 x 12 trials from the training session that had yielded reaction times within one standard deviation of the individual mean, again balanced for task-relevant and task-irrelevant information.
fMRI Measurements and Analysis
fMRI data were acquired with a 1.5 T Magnetom Vision MRI scanner (Siemens, Erlangen, Germany) using a gradient echo EPI sequence [1 volume = 6 (experiment 1)/16 (experiment 2, control) axial slices; TR = 1000 ms (experiment 1)/2000 ms (experiment 2, control); TE = 60 (experiment 2, control)/69 ms (experiment 1); FA = 90°; FOV = 210 x 210 mm2; voxel size = 1.6 x 1.6 x 5.0 (experiment 1) or 3.2 x 3.2 x 5 (experiment 2, control) mm3] for fMRI. Each scan comprised the acquisition of 128 (experiment 1) or 256 (experiment 2, control) volumes. In experiment 1, the slices covered large parts of the occipital, temporal and frontal lobes (z-coordinate range from 5 to 25 at y = 50 and from 15 to 45 at y = 20, Talairach coordinates), whereas in experiment 2 and the control they covered the whole cerebrum. A T1-weighted 3-D MP RAGE scan was recorded in each session (magnetization-prepared rapid acquisition gradient echo, TR = 9.7 ms, TE = 4 ms, FA = 12°, matrix = 256 x 256, voxel size 1.0 x 1.0 x 1.0 mm3).
In experiment 1, subjects underwent four scans of each condition, yielding an overall of 16 what and 16 where trials. Experiment 2 consisted of three functional scans with a pseudo-random sequence of task types, yielding 12 trials of every task type (what, where, what and where).
The statistical analysis was based on the application of the multiple regression analysis to time-series of task-related functional activation (Friston et al., 1995). These analytical tools were implemented in BrainVoyager 4.4 (Goebel et al., 1998a
,b
; Dierks et al., 1999
).
Talairach transformation (Trojano et al., 2000) was performed for the complete set of functional data of each subject, yielding a 4-D data representation (volume time-course: 3 x space, 1 x time). Prior to statistical analysis, the time-series of functional images was aligned in order to minimize the effects of head movements. The central volume of the time-series was used as a reference volume to which all other volumes were registered, using a 3-D motion correction that estimates the three translation and three rotation parameters of rigid body transformation. Data pre-processing furthermore comprised spatial smoothing with a Gaussian kernel (FWHM = 8 mm), the removal of linear trends and (in experiment 2 and the control) temporal lowpass filtering (lowpass: 48 per functional run of 256 volumes).
The high resolution T1-weighted anatomical 3-D data set of a template brain (courtesy of the Montreal Neurological Institute) was used for the surface reconstruction and flatmap representation of both hemispheres.
The GLMs of the what and where sessions of experiment 1 were computed from the 20 (five subjects, four scans per subject) z-normalized volume time-courses. The signal values during the encoding, delay and retrieval phases were considered effects of interest. The GLMs of experiment 2 were computed from 30 volume time-courses (10 subjects, three scans per subject). GLMs were computed for the encoding (two volumes), early delay (two volumes), delay (six volumes) and retrieval (two volumes) phases, and the task type (what, where, what and where) was considered the effect of interest. The corresponding predictors, obtained by convolution of an ideal box-car response (assuming a value of 1 for the volumes of task presentation and a value of 0 for the remaining time points) with a linear model of the hemodynamic response (Boynton et al., 1996), were used to build the design matrix of the experiment. The global level of the signal time-courses in each session was considered to be a confounding effect and a fixed effects analysis was employed. To analyze the effects of conditions compared to baseline and contrasts between conditions, 3-D individual and group statistical maps were generated by associating each voxel with the F-value corresponding to the specified set of predictors and calculated on the basis of the least mean squares solution of the GLM. Statistical results were then visualized through projecting 3-D statistical maps on the flattened surface reconstruction of the MNI template. Effects were only shown if, considering an F distribution with n1 and n2 degrees of freedom (n1 = number of orthogonal predictors and n2 = number of time samples n1 1), the associated P-value yielded P' < 10-2, corrected for multiple comparisons (RC maps), or P < 10-3, uncorrected (superposition maps) and if a minimum cluster size of 100 mm3 was reached.
RC Maps
For significantly activated voxels, the relative contributions, RC, between two selected sets of conditions in explaining the variance of a voxel time-course were computed as
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In experiment 2, each of the effects of interest (the three task types) was given a color of the RGB system. In order to visualize all three effects on a single flatmap, colors were superimposed and areas of overlap (cortical regions showing an activation during more than one condition) received the appropriate mixed color (superposition maps). Time-courses of experiment 1 and experiment 2 were computed by event-related averaging of the mean time-courses of indicated clusters over all 20 volume time-courses, using the same voxels (in Talairach space) for all subjects and all repetitions.
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Results |
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Subjects performed at high accuracy (>85%) in all experiments. In experiment 1, reaction times of correct responses did not differ significantly between the what and where conditions (P = 0.68, MannWhitney U-test). In experiment 2, where the response had to be delayed until the disappearance of the stimulus, accuracy rather than reaction time was used as measure of task performance. Accuracy rates (what and where, 86%; where, 87%; what, 89%) did not differ significantly between conditions (2, P = 0.78).
Experiment 1
In experiment 1, data were acquired from the occipital, temporal and frontal lobes only in order to achieve high temporal resolution. The results confirm that stimulus and retention-related activity can be separated by event-related fMRI. In IT cortex of both hemispheres, the presentation of the target and the test stimuli evoked temporally well-segregated activities that peaked ~4 s after the onset of the respective stimuli (Fig. 1C,D). In prefrontal cortex, by contrast, the same stimulus constellation was followed by a sustained activation that rose more slowly, remained high during the delay period, peaked ~5 s after the presentation of the test stimulus and then returned to baseline (Fig. 1C,D
). We will call activity occurring immediately after the presentation of the target and test stimuli encoding and retrieval activation, respectively, and activity present during the delay period retention activation. RC maps (see Materials and Methods) between encoding and retention-related brain activation in experiment 1 yielded prominent bilateral clusters in the temporal lobes during encoding and in the frontal lobes during retention (maps in Fig. 1C,D
). The parietal lobe was not included in the sampling volume for experiment 1. During encoding, temporal lobe activation occurred in similar regions in the what and where conditions. In the what condition, the size of activated clusters was larger and their position, as estimated by their center of mass, was more posterior than in the where condition (Fig. 1
and Table 1
). During retention, frontal activation occurred more anteriorly in the what condition, particularly in the right hemisphere, than in the where condition and showed a clear asymmetry in favor of the left hemisphere, while it was fairly symmetrical during the where condition (Table 1
). In experiment 1, subjects were instructed to respond immediately after the presentation of the probe, whereas in experiment 2 they had to hold off their button press response for 4 s. This element of the task design allowed for a separation of activation related to the execution of the button press response from retrieval-related activation.
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Superposition Maps
In experiment 2, slices covered the entire cortex. Encoding activity covered bilateral occipito-temporal and parietal cortex and was also prominent in the DLPFC, particularly for the where and what and where conditions, in the left VLPFC and bilateral INS, particularly for the what and what and where conditions, and in frontal midline structures (SMA/anterior cingulate; Fig. 2). Retention activity was observed mainly in the frontal and parietal lobes (Fig. 2D
). While the overlap between conditions in the superposition maps was large, it was not as widespread as in the encoding maps. In particular, the parietal lobes showed very little contribution of the what predictor, and activation in the right IPL showed a clear preponderance for the where predictor. In the frontal lobes, large areas in the anterior middle and inferior frontal gyri and INS (particularly in the left hemisphere) showed a predominance of what and what and where over where, while the posterior middle and superior frontal gyri of both hemispheres showed little contribution of the what as compared to the where and what and where predictors.
In the non-verbal control experiment (which only consisted of what trials) we could replicate the finding of experiment 1 and experiment 2 of predominantly left hemispheric retention activity in prefrontal cortex (Table 1; Figs 1C and 2
), but not the activation of mesial superior frontal cortex shown in Figure 2
.
RC Maps
The RC maps (Fig. 3), which had a more conservative threshold than the superposition maps, again showed much larger overlap during encoding than during retention. For encoding, the contrast what versus where revealed a higher contribution of the what predictor in some occipito-temporal and inferior frontal areas bilaterally and of the where predictor in the right IPL and DLPFC bilaterally. The contrast what and where versus where again revealed a higher contribution of the what and where predictor in occipito-temporal areas bilaterally and the left INS and of the where predictor in the right IPL, while the contribution of both conditions to the signal in DLPFC was approximately equal. The contrast what and where versus what mainly yielded a higher contribution of the what and where predictor to right DLPFC activation.
The RC maps for the delay period tended to show a higher degree of separation of the predictors. The what versus where contrast yielded distinct clusters of where-related activation in the parietal lobes and DLPFC bilaterally and of what-related activation in left VLPFC and INS. The what and where versus where map showed preponderance of where activation in the right SPL and IPL and of what and where activation in the left VLPFC and bilateral INS. The what and where versus what map showed that bilateral superior parietal and frontal midline activity had a higher contribution from what and where trials.
Time-courses
The detailed documentation of the BOLD signal change time-courses of the areas whose activation was found to be accounted for differently by the task condition predictors during encoding and/or retention contributed important additional information. The color coded statistical maps revealed the areas whose activation is explained by predictors at a determined threshold. The time-course plots, however, reveal the temporal dynamics of activation changes in the task phases of a particular condition in a particular area in relation to the other conditions and phases (Fig. 4). They can thus help to determine if differential effects observed during retention are mere carry-over effects of encoding-related activation and if significant differences between conditions during a phase of the task (e.g. encoding) are specific to that phase (Table 2
). The time-courses revealed that most retention areas had also shown a response in the encoding phase. Yet, while occipito-temporal areas showed an early response (peaking 6 s after onset of stimulus presentation) and returned to baseline after another 8 s (and then showed a second response to the probe stimulus), activity in the frontal and parietal areas peaked later (810 s), remained above baseline during the delay period and showed a second peak in response to the probe stimulus. In order to account for this first transient response evoked by the sample stimulus (that peaked 35 s later than would have been expected from a pure hemodynamic shift of stimulus onset), we introduced the early delay predictor to the statistical analysis of differences between conditions (Table 2
). While significant differences in the early delay predictor might be carry-over effects from encoding, this is rather unlikely for differences that are present in the time-courses (and significant) during the entire delay. For a full account of the statistical analysis of differences between conditions see Table 2
.
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Discussion |
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The time-courses and maps presented in Figures 1 and 2 confirm that the design of the study permitted a separation of encoding-, retention- and retrieval-related brain activity. Experiment 1 revealed distinct time-courses in IT and prefrontal cortex during visual STM. While activity in IT peaked at ~5 s the commonly assumed time-to-peak of the BOLD signal (Boynton et al., 1996
) after the onset of a visual stimulus and returned to baseline immediately afterwards, activity in prefrontal cortex rose more slowly after the presentation of the target stimulus, remained high during retention and peaked after the test stimulus. Experiment 2, which used a lower sampling rate than experiment 1 (2 instead of 1 s) but covered the entire brain, revealed a similar pattern of time-courses (Fig. 4
) and additional retention-related activation in the parietal lobe, predominantly for the where and conjunction conditions. Retention-related activity can thus be regarded as being largely confined to the frontal and parietal lobes (Fig. 2D
), while the first response to a new target stimulus, which can be seen as the neural correlate of stimulus encoding, was observed in IT (Figs 1C,D and 2C
). Retrieval-related activity was also present in the temporal, frontal and parietal lobes (Fig. 4
).
Comparison of Spatial, Non-spatial and Conjunction Memory
Frontal activation
Beyond the segregation of the phases of a typical STM task, our design permitted the comparison of cortical activation patterns associated with spatial, non-spatial and conjunction STM. Particularly during delay (and most clearly in the left hemisphere), the RC maps (Fig. 3) show a separation of more ventral prefrontal areas (anterior IFG and MFG) involved in the what and more dorsal prefrontal areas (posterior MFG and SFG) involved in the where condition, while what and where recruits parts of both regions. From this perspective, our results might seem to confirm a clear-cut segregation of dorsal where and ventral what areas in prefrontal cortex. Yet the superposition maps (Fig. 2
) and the time-courses of the prefrontal areas (Fig. 4
) even more so, reveal that the issue is more complex than this. Even areas with high RC values in favor of one condition still show a considerable and very stable departure from baseline during the other conditions. For example, the left INS, albeit displaying a significantly higher activation for what and what and where compared to where during delay, still shows a clear difference from baseline for the where condition. Conversely, the what condition was accompanied by a consistent activation of right SFG in all phases, although this area clearly showed a more prominent modulation for the spatial conditions. This shows that if only activations that survive a very stringent threshold are considered, some aspects of the distributed cortical activity subserving complex cognitive processes might be lost, as has also been observed for categorical visual processing (Ishai et al., 1999
). It thus seems that a wide range of prefrontal areas is recruited during visual STM, regardless of the characteristics to be remembered and that the additional processing required by the precise nature of the task leads to the differential modulation of subsets of this network. Moreover, the role of the prefrontal cortex in STM is clearly not only confined to functions during the delay period. Most areas of PFC that showed task-related activity in the present study responded even more strongly in the encoding phase (although they differed from pure encoding areas in that their activity remained significantly higher than baseline during the entire delay period) and showed a second peak for retrieval (Fig. 4
). Our data show that PFC is active during all phases of visual STM. Furthermore they confirm a non-exclusive DLPFC/ VLPFC dissociation for spatial and non-spatial memory. This is consistent with the claim that while there is considerable overlap of delay activity in lateral prefrontal areas, the level of participation is generally higher for the SFS region bilaterally in spatial and for left inferior and mid-frontal cortex in non-spatial tasks (Courtney et al., 1998a
; Haxby et al., 2000
).
Most identified frontal areas were also active during the different phases of the conjunction task (what and where). Yet conjunction-related activation was clearly not an addition of the activations related to the component processes. Some ventro-lateral prefrontal areas showed higher activity for what than conjunction and some dorsolateral areas for where than conjunction. However, in areas where one of the component tasks evoked the highest activation, conjunction always took the second place. This would be compatible with a theory that regards not the addition, but the recruitment of parts of the networks for the components as the likely neuronal mechanism for the solution of conjunction tasks. The only area that consistently displayed the highest BOLD signal change for conjunction versus the component tasks was found in the mesial superior frontal cortex bilaterally (extending from the SMA to the anterior cingulate). This region has been identified as being a central element of the network for feature integration in working memory in a number of previous studies (Mitchell et al., 2000; Prabhakaran et al., 2000
).
The superposition map of experiment 2 (Fig. 2) shows that the dissociation of lateral PFC into more dorsal areas that participated more in the spatial conditions and more ventral areas that participated more in the non-spatial conditions tended to be present in both hemispheres. Yet significantly higher activation for what versus where during delay was only found in the left inferior and mid-frontal cortex, whereas the SFG and parietal activation was significantly higher for where than what in both hemispheres (Fig. 3A
and Table 2
). Predominantly left hemispheric what activation during maintenance has recently been described by Postle and DEsposito (Postle and DEsposito, 2000
) who proposed that the difference between maintaining spatial and non-spatial information might be hemispheric. However, of the previous studies that included a direct comparison between spatial and non-spatial working memory, only some have reported a left lateralized prefrontal activation for the non-spatial task (Courtney et al., 1998a
), while a number of studies have found bilateral activation in mid-frontal cortex (McCarthy et al., 1996
; Belger et al., 1998
). Prefrontal activation for the spatial task was either bilateral (Courtney et al., 1998a
) or predominantly on the right (McCarthy et al., 1996
; Belger et al., 1998
). In terms of lateralization, the most consistent finding of both the previous and the present studies seems to be the predominantly left-hemispheric IFG activation for the non-spatial task. The fact that the activation of left IFG could be confirmed in our control experiment suggests that it is not exclusively associated with the verbal components of working memory.
Parietal Activation
The parietal retention activation seems to be linked to the spatial component of STM, because it was mainly observed in the where and conjunction conditions of experiment 2 and much less prominent in the what task that was based on the same stimulus material. Thus, our results confirm the view that spatial STM involves coactivation of PP and prefrontal cortical areas (Chafee and Goldman-Rakic, 1998). Primate PP is known to play a key role in visuomotor integration (Sakata et al., 1997
; Goodale, 1998
; Quintana and Fuster, 1999
), the spatial analysis of the visual scene (Colby and Goldberg, 1999
) and the integration of spatial information from different sensory modalities (Andersen, 1997
). Posterior parietal areas LIP, 7a and 7ip of non-human primates have been shown to be active during delayed saccade tasks (Andersen et al., 1990
; Chafee and Goldman-Rakic, 1998
) and DMS paradigms (Constantinidis and Steinmetz, 1996
). A preponderance of parietal over DLPFC activity during visuospatial STM in humans has recently been described by Pochon et al. (Pochon et al., 2001
) who found a prominent DLPFC activation only when the preparation of a sequential movement was required. While our data suggest that the STM-related DLPFC activation also occurs in the delay phase of simple response tasks, we can confirm their finding of the important role of the parietal-premotor network in visuospatial STM. The observation of a hemispheric difference of parietal activation is consistent with most of the imaging and neuro-psychological literature on the spatial functions of the parietal lobe. However, the finding that the right SPL showed a higher response for the where than the conjunction condition might seem surprising, because the spatial attention load and need to rehearse the positions mentally would have been the same in both conditions. Yet, in the present experiment, the where condition actually involved a higher demand on visuospatial attention because the number of possible locations was higher (based on individual performance in the test trials) in order to match the two conditions for difficulty. Furthermore, there is evidence that the presence of a second feature on which the matchnon-match judgement can be based (in this case the identity of the object) leads to a reduced recruitment of the parietal lobes in conjunction as opposed to pure visuospatial tasks (Sack et al., 2002
).
Infero-temporal Activation
The typical time-course of the BOLD signal in IT cortex showed a prompt response to sample stimuli, returned to baseline during the delay and peaked again in response to the probe stimulus. Thus we could observe the expected stimulus responses, but not the delay activity described for IT in a number of studies (Fuster and Jervey, 1981; Miller et al., 1993
, 1996
). A possible explanation might be provided by the particular nature of our DDT task. Our sample stimulus always consisted of four sequentially presented items. Based on the finding that intervening stimuli cancel out delay activity in IT but not in prefrontal neurons of macaque monkeys (Miller et al., 1996
), we would expect delay activity only in IT neurons responding to the fourth item of the samples. Considerably fewer neurons in IT cortex than PFC would thus be active during the delay phase of our task and the population of active IT neurons might have been too small to evoke a BOLD response.
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Conclusion |
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In conclusion, our data suggest that retention of different aspects of visual stimuli (what, where and conjunctions) depends on processes that recruit, in a task-specific manner, partly overlapping combinations of prefrontal and parietal areas.
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Abbreviations |
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CaS calcarine sulcus
CiS cingulate sulcus
CoS collateral sulcus
CU cuneus
DDT delayed discrimination task
DLPFC dorsolateral prefrontal cortex
DMS delayed matching-to-sample (task)
FA flip angle
fMRI functional magnetic resonance imaging
FOV field of view
GF gyrus fusiformis
GL gyrus lingualis
GLM general linear model
GPrC precentral gyrus
IFG/IFS inferior frontal gyrus/sulcus
INS insula
IPL inferior parietal lobule
IPS intraparietal sulcus
IS insular sulcus (sulcus circularis insulae)
IT inferior temporal cortex
LS lateral sulcus
MFG/MFS middle frontal gyrus/sulcus
MNI Montreal Neurological Institute
MTS middle temporal sulcus
OF orbito-frontal sulci
OTS occipito-temporal sulcus
PCS postcentral sulcus
PFC prefrontal cortex
POS parieto-occipital sulcus
PP posterior parietal cortex
RC relative contribution
RGB redgreenblue
RS Rolandic (central) sulcus
SFG superior frontal gyrus
SFS superior frontal sulcus
SMA supplementary motor area
SPL superior parietal lobule
STM short-term memory
STS superior temporal sulcus
TE echo time
TR repetition time
VLPFC ventrolateral prefrontal cortex
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Footnotes |
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Acknowledgments |
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References |
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