| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
1Nijmegen Institute for Cognition and Information, 2FC Donders Centre for Cognitive Neuroimaging, Radboud University Nijmegen, Nijmegen, The Netherlands; 3Canadian Institutes of Health Research Group on Action and Perception, 4Imaging Research Labs, Robarts Research Institute, London, Ontario; and 5Physiology and Pharmacology, University of Western Ontario, London, Ontario, Canada
Submitted 30 August 2005; accepted in final form 6 November 2005
 |
ABSTRACT |
|---|
 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
|---|
|
INTRODUCTION |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
|---|
A prominent and well-studied region within the monkey PPC is the lateral intraparietal area (LIP). The functional role of LIP, however, is controversial. That is, some have associated LIP with the planning of saccades, whereas others have suggested that the activity of neurons in the region describes salient spatial locations, independent of the generation of any specific movement (see Andersen and Buneo 2002
; Colby and Goldberg 1999; Gottlieb 2002 for reviews).
In humans, neuroimaging studies on the posterior parietal cortex have recently identified a bilateral region that topographically represents targets for saccades (Sereno et al. 2001). In subsequent experiments, we have exploited the topography of the region to gain more insight into its functional organization. In so doing, we established that the region has an eye-centered organization that is updated when the eyes move (Medendorp et al. 2003). Furthermore, using memory anti-saccades, we have demonstrated that the topography is linked to the location of saccadic goals and not to the coordinates of the visual stimulus (Medendorp et al. 2005a). Finally, we showed that the region is activated for movements of the eyes and either hand, but that the activation is modulated by which effector is selected to act on the targets (Medendorp et al. 2005b). Based on the collective weight of this evidence, this human PPC region may correspond to the monkey area LIP (Duhamel et al. 1992; Snyder et al. 1997; Zhang and Barash 2000).
Would this region, which we will refer to as retinotopic IPS (or retIPS), have the capacity for storing multiple targets for successive saccades? Monkey LIP has been demonstrated to lack such resources. That is, Mazzoni et al. (1996) recorded from LIP neurons using a memory double-saccade paradigm in which a monkey had to memorize the locations of two stimuli and subsequently made saccades to both locations. They found that the majority of LIP neurons coded the next planned eye movement even though the animals must hold in memory two cued locations. Their results suggest that the second target (or movement plan) must be stored outside of LIP, perhaps in frontal areas (Schall and Hanes 1993; Tian et al. 2000). However, a recent fMRI study by Todd and Marois (2004) has suggested that the human PPC does indeed have storage capacity for multiple target locations in a delayed visual matching-to-sample task. More specifically, the authors showed that activity in their region, which exhibits some overlap with human retIPS, is tightly correlated with the limited amount of target representations that can be stored in memory.
To address this issue, we tracked fMRI signal changes in retIPS while subjects were presented with two brief visual targets, separated by a long delay, in either the same or different visual hemifields. Subjects were required to memorize these two target locations and after another delay saccade to them in sequence. Our results suggest that retIPS is involved in storing multiple target locations, but with a significant bias toward the target for the first saccade.
|
METHODS |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
|---|
and will be briefly summarized here. MRI scanning
Data were collected with a 4-Tesla Varian (Palo Alto, CA) Unity Inova whole-body MRI scanner equipped with a Siemens Sonata Gradient system (Siemens, Erlangen, Germany). We used a quadrature radio-frequency surface coil, centered on the posterior parietal lobe, to image nine contiguous slices that instantiated a functional volume coinciding with the known locations of the parietal regions-of-interest (see Fig. 1). Functional data were obtained using navigator echo corrected T2*-weighted spiral imaging (TE = 15 ms; FA = 45°; FOV = 19.2 x 19.2 cm; TR = 1 s; in-plane pixel size = 3 x 3 mm; THK = 4 mm). Functional data were superimposed on high-resolution inversion prepared three-dimensional T1-weighted anatomical images of the brain (typically 128 slices, 256 x 256, FOV = 19.2 x 19.2 cm, TE = 5.5 ms, TR = 10.0 ms). In separate sessions, full brain anatomical images were acquired using a high-resolution inversion prepared 3D T1-weighted scan sequence (FA = 15°; voxel size: 1.0 mm in-plane, 256 x 256, 164 slices, TR = 0.76 s; TE = 5.3 ms).
|
Stimulus presentation was performed using a Silent Vision SV-4021 projection system (Avotec, Stuart, FL). This system includes an MEyeTrack-SV (Silent Vision) eye tracker (SensoMotoric Instruments GmbH, Teltow, Germany). This device uses fiber optics housed in dual stalks that sit in front of a subject's eyes, allowing presentation of visual stimuli and simultaneous CCD video-based infrared eye tracking. The visual display subtends 30° horizontally by 23° vertically with a resolution of 800 x 600 pixels and a refresh rate of 60 Hz. Eye position was sampled at 60 Hz with an accuracy of 
1°. Before scanning, we calibrated the system with a five-point calibration, with one point in each corner of the visual display as well as a central point. All experimental targets were within the range of the calibration. Analysis of the eye movement traces was performed off-line.
Location of retinotopic IPS
To localize retIPS, we used a delayed-saccade task, which was incorporated in a block-design paradigm, as described in detail by Medendorp et al. (2005a). In separate blocks, subjects either made delayed saccades or maintained fixation. In the saccade blocks, subject viewed a brief peripheral dot, the target, while they fixated centrally. Then, a band of distractors, consisting of similar dots, blinked during a 2.5-s period, while the subjects maintained fixation. At distractor offset, subjects made a saccade to the remembered target location and then immediately back to center. The time between successive movements was 5 s. Subjects made no movement during the fixation (F) task. Each scan consisted of 14 blocks (each 20 s): first two blocks of fixation, then 10 blocks in which four targets in the left visual field were alternated with four targets in the right visual field, and finally two fixation blocks that concluded the scan. Thus in each run, subjects made 20 delayed-saccades into the left hemifield and 20 in the right hemifield. Subjects were tested in four runs, each lasting for 4.67 min. Subjects were given one minute of rest between runs, so that the total time devoted to the localizer was 22 min.
Memory-delayed double-step saccades
An event-related paradigm was used to test the response of the retIPS region for memory-delayed double-step saccades. Figure 2A illustrates the paradigm. While subjects fixated centrally on a gray square (Fix), a brief peripheral gray dot (Tar) flashed for 200 ms, either left or right of central fixation, at a random eccentricity between 7.5 and 9° and at a random angular elevation within a range of 3 and 4°, in either the lower or upper visual field. Figure 2B illustrates the potential stimulus locations, which were also used in the retIPS localizer task. Subsequently, a masking pattern (30° horizontal x 15° vertical, dot's eccentricity 0.36°, density 0.3 dots/deg2) blinked for 100 ms to disrupt iconic visual memory. This was followed by a long 11.6-s memory delay during which the subject maintained fixation. Subsequently, 12 s after the trial began another peripheral gray dot (Tar) was flashed for 200 ms, either in the left or right visual field, followed by the same masking pattern (Msk). Subjects had to memorize the locations of both targets. At all times, it was ensured that when the first target was flashed in the upper visual hemifield, the second was presented in the lower and vice versa. This was randomized across trials, conditions, and runs. Next, 12 s after cueing of the second target, the fixation square was turned off, prompting the subject to make saccades to the remembered locations of the targets, in the same sequence as their appearance. To motivate the subjects to saccade to the correct location at the right time, a small letter, either c or o, was flashed briefly, 300 and 600 ms after fixation point offset, respectively, at either remembered location (not shown in Fig. 2A). Due to their very small size (0.3°), the letters were distinguishable only if the subject fixated at the correct location at the right time. Thus the letter task provided a strong incentive for the subjects to remember the precise position of the two targets and, as such, may also have facilitated the formation of a preparatory set. Subsequently, the central fixation square (Fix) was turned on again, 1.2 s after its offset, instructing the subject to make a saccade back to the center of the screen and fixate till the end of the trial. During this period, subjects had to report whether they had seen two identical letters (c-c, or o-o) or different ones (c-o, or o-c), by pressing one of two buttons on a key pad using their right hand. The subject's actual performance was determined from the eye-movement recordings described in the following text.
|
Control experiment
Three naïve subjects and one of the subjects that participated earlier in the double saccade task (described in the preceding text) participated in a control experiment without saccades. In this experiment, subjects viewed the same set of sensory stimuli as above, presented at the same times but were instructed to keep fixation at all times. This control experiment served to measure the neural response that can be attributed to sole sensory processing, thus excluding the processing that follows this stage in the double saccade paradigm.
Behavioral analysis
We recorded the button presses during scanning from five of seven subjects who participated in the double-saccade paradigm; their performance was >94% correct. Eye movements were recorded in all seven subjects. An example of one subject's eye traces [(horizontal component (black) and vertical component (gray)] during the four testing conditions is shown in Fig. 3B in relation to the temporal order of events (Fig. 3A). As shown, this subject maintained fixation during the presentation of the cues and made eye movements in the correct directions after the fixation spot was turned off. Figure 3C shows the trajectories of the saccades from this subject for all conditions separately. As shown, the responses were fairly accurate even though the subject had memorized the respective locations for 24 and 12 s. We used the following criteria to distinguish error trials from correct trials. First, during the fixation periods, eye movements should be restricted to <1°, i.e., they should remain less than the noise of our recording system. Second, after the GO signal (fixation point offset), saccades should be aimed in the correct direction. We did not put a criterion on saccade amplitude, but as shown (Fig. 3C), saccade metrics were typically of correct size. Eye-movement recordings in all seven subjects confirmed that they generally performed the double saccade task correctly: only in <5% of the trials, did the subjects either break fixation or make their saccades in the wrong direction. We excluded these error trials from further analysis. Furthermore, reaction time analysis revealed that the saccades occurred with a latency of 275 ± 9 (SE) ms after being prompted by fixation point offset. This confirms that the saccades were driven by memory of the previously viewed targets and not simply guided by the visual appearance of the letters. There were no statistically significant differences in saccade latencies among the four conditions [ANOVA F(3,128) = 0.26, P = 0.85].
|
Image analysis and regions of interest (ROIs)
Analysis was performed using Brain Voyager 4.8 and BrainVoyager QX 1.4 software (Brain Innovation, Maastricht, The Netherlands) and Matlab software (The Mathworks). Surface coil images were aligned manually to head-coil images. For functional data analysis, scans were corrected for linear drift and scans with motion artifacts were excluded. Anatomical and functional images were transformed to Talairach space (Talairach and Tournoux 1988).
Using the localizer scans, the parietal region of interest (retIPS) was identified by contrasting the blocks devoted to leftward saccades with the blocks for rightward saccades. We also used the anatomical criteria about the location of retIPS reported by previous studies (Medendorp et al. 2003, 2005a,b; Sereno et al. 2001l). We used the false discovery rate (FDR) controlling procedure to correct for multiple comparisons, with a maximum threshold value of 0.05, thus q(FDR) < 0.05 (Genovese et al. 2002). Our ROIs contained all contiguous voxels within a cubic cluster of 8 x 8 x 8 mm centered on the point of peak activation that exceeded a threshold of q(FDR) < 0.05 (t = 2.74, P < 0.0065).
Using this independently defined bilateral retIPS region, fMRI time courses corresponding to all activated voxels within this region were extracted for each of the subsequent event-related scans and then averaged. The average percent signal change for the four conditions, RR, LL, RL, and LR, was computed using the precueing fixation periods as a baseline. We took this baseline so that the most of the activations reported could be directly compared with the activation when no targets are stored in memory. For each condition, a mean signal and SE were computed.
|
RESULTS |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
|---|
|
|
; Medendorp et al. 2003, 2005a,b; Sereno et al. 2001).
|
To test between these hypotheses, we used an event-related fMRI paradigm in which subjects performed a double-delayed double-saccade task. In this task, subjects first saw the target for the first saccade, then, after a 12-s delay the target for the second saccade and then, after another 12-s delay, they made saccades successively to the remembered stimulus locations (see Fig. 2). The paradigm consisted of four different conditions regarding the cued locations of the two targets: either both were cued in the right visual field or in the left visual field or the first target was flashed in the right and the second target in the left visual field or vice versa. The four conditions are represented as RR, LL, RL, and LR, respectively (Fig. 6A).
|
What happens when the location of a second saccade target must be stored in memory? As shown, in all conditions, there is a phasic response coincident with the appearance of the target (time interval: 14–22 s). Again the amplitude of this response relative to the level of activation prior to target presentation is selective to the spatial location of the target. More specifically, the amplitude of the phasic response is higher in the hemisphere contralateral to the target. This pattern of activation is thus not different from the observations made for the phasic response of the region to the first target. More interesting is the region's activation in the later part of the second delay period (time interval: 22–26 s), when the phasic response has virtually diminished. Then the region's sustained activation seems to depend on the specific spatial configuration of the two saccade targets. That is, for the left cortex, if the two saccade targets were presented in the contralateral hemifield (the RR condition), a high sustained activation was observed in the second delay period. But if they were cued in the ipsilateral hemifield (the LL condition), the level of activation was low. The right parietal region (Fig. 6C) showed a similar, but mirrored, pattern of activation. Furthermore, when the two saccade targets were in opposite hemifields, the RL and LR conditions, the region's sustained activation reached a value in between these two levels, close to the level of activation that was reached in the first delay for just one memorized contralateral target. This suggests that the activation of each unilateral retIPS depends on the number of targets that need to be memorized from its contralateral hemifield. Closer scrutiny of RL and LR conditions, however, also suggests a difference between these activation levels. Even though the visuospatial stimulation is identical in these conditions—a target in either hemifield—the region seems more responsive to the first target memorized, which is the first target for action. In other words, this would suggest that retIPS is not only involved in storing the memory of subsequent targets but is also selectively tuned to the target that drives the first saccade.
The observations made in Fig. 6 were also seen in individual subjects. More specifically, we observed this pattern of activity in six of seven subjects for the left retIPS region and in five subjects for the retIPS region in the right hemisphere. In the following, we will further quantify the observations made in Fig. 6 and test the significance of the effects across subjects. We will first focus our analysis on the phasic response to the two cues, the peak of which can be observed at 6 s after presentation of the cue, consistent with the hemodynamics of the BOLD response (Boyton et al. 1996). Figure 7 illustrates the results for the four different conditions, presenting the amplitude of the phasic response, which was computed as the difference between the mean activation at 5–6 s after presentation and 1–2 s before presentation of the cue, averaged across subjects. As the top panels show, the amplitude of the phasic activity related to first cue was significantly higher in the hemisphere contralateral to its location [(F(1,6) = 9.1, P = 0.02]. This is in correspondence with the topographic nature of the region. The same was found for the BOLD response to the presentation of the second cue, irrespective of the remembered location of the first stimulus. Again there was significantly more activation in the hemisphere contralateral to the cue [F(1,6) = 245.6, P << 0.001], irrespective of whether the first cue was presented in the contralateral or ipsilateral hemifield [F(1,6) = 0.4, P = 0.55].
|
, 2005a,b). The bottom panels in Fig. 8 quantify the sustained responses in the second delay period. Recall that during this time interval our subjects had to remember two stimulus locations for later successive saccades. As shown, the activation in either hemisphere is significantly higher when two contralateral targets are to be memorized compared with just one [F(1,6) = 11.6, P = 0.01]. This shows that the region retains storage capacity for multiple (at least 2) target locations, with the neural activation distributed across the two hemispheres. The region in the left hemisphere stores the locations of targets cued in the right visual field; the region in the right hemisphere encodes target representations from the left hemifield. The activation during the second delay, with two target locations in memory, differs for all four stimuli conditions. A repeated-measures MANOVA, with hemisphere (left/right) and test condition (LL, LR, RL, RR) as factors, revealed a significant two-way interaction F(3,18) = 16.4, P<<0.001]. This interaction effect confirmed that the sustained activations prior to the saccades clearly depend on the respective locations of the two stimuli and that the activity in the right and left retIPS was dissociable.
|
Finally, we performed a control experiment to test whether the tonic activation as described in Figs. 6 and 8 is truly related to the processing of target locations for saccades. The results of four subjects are shown in Fig. 9. As the figure shows, there is a clear response after presentation of each of the two stimuli suggesting that the phasic component of the activation is sensory in nature. In the left hemisphere (Fig. 9B), the phasic response to the first stimulus appears to be more spatially selective than the response to the second stimulus.
|
|
|
DISCUSSION |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
|---|
; Todd and Marois 2004). In addition, the results have revealed several new properties of the memory representation in this retinotopic region along the IPS. First, memory activity in retIPS is spatially selective with each hemisphere predominantly representing contralateral targets. Second, activity for two memorized targets, one from either hemifield, depends on the sequence in which they were presented with more activation in the hemisphere contralateral to the first target—the target for the first action. This suggests that the role of retIPS cannot be limited to visuospatial memory alone, but extends to participating in action (saccade) planning (Andersen and Buneo 2002; Mazzoni et al. 1996; Medendorp et al. 2005a). One could also argue that storing target locations and selecting the goal for first action should reflect separate and successive stages in sensorimotor processing (Tian et al. 2000). However, here we have shown that in humans they occur in the same brain region: retIPS.
Our results have shown that in response to the visual cue, either the first or the second cue, the phasic component of the activation was higher in the hemisphere contralateral to the cue (Figs. 6 and 7). What type of processing does this response reflect? Because the same response was found in our control experiment (Fig. 9), in which subjects viewed the stimuli but did not have to memorize them for later saccades, it can be argued that the phasic component merely characterizes a sensory response. In the monkey, Bisley et al. (2004) have shown that the initial burst in LIP in response to a visual stimulus has an extremely short and precise latency (45 ms), also suggesting it reflects an uncontaminated sensory signal. In due course, the later sustained activity would reflect more cognitive functions that transcend simple visual analysis. Let us now further discuss this component and its relation to previous studies and interpretations.
In a recent study, monkey area LIP was shown to reflect the outcome of the process of target selection for saccades rather than a storage center for multiple targets (Mazzoni et al. 1996). The same was found for the parietal reach region, located on the medial bank of the intraparietal sulcus, which specifies the target for the impending reach (Batista and Andersen 2001). In the experiment by Mazzoni et al., monkeys were presented with two brief visual stimuli and, after a delay, looked to them in sequence. Most neurons sampled in monkey LIP showed persistent activity during the delay period only when the first target (the target for the 1st saccade) was in the neuron's receptive field and not when the second target (for the subsequent saccade) appeared in the receptive field. The fact that retIPS shows a predominant contralateral bias toward the first presented cue is consistent with the notion of a selection mechanism that selects the first cue as target for first planned action. This mechanism may operate by means of a top-down control signal that enhances the internal representation of the first cue, as relevant for the first action. This could be tested by changing the sequence of saccades to the targets and examining whether the activity in retIPS is specific to the location of the second cue, which is then the target for the first intended action.
However, the virtual absence of memory activity related to the target for the subsequent, second saccade (2nd target) in monkey LIP, as found by Mazzoni and colleagues, disagrees with the present demonstration that the massed activation in retIPS does represent the goals of both saccades. Thus although retIPS shares the property of target selection with monkey LIP on the basis of its predominant bias toward the first target, it is, in contrast to its monkey equivalent, also involved in the storage of the location of the second target. If it is assumed that human retIPS is homologous to monkey LIP, what could account for this difference? Two explanations can be advanced. First, the discrepancy may be explained by the fact that, in monkeys, usually a selected population of neurons is studied, while BOLD activation may reflect activity of any group of neurons in a given area. Second, the spiking activity recorded in monkeys likely represents the output of LIP because microelectrode recordings are biased toward large pyramidal cells. On the other hand, fMRI signals appear to be correlated to a large degree with synaptic potentials (Logothetis et al. 2001). Thus they represent local processing and inputs as well as outputs. The storage for the second target may reflect top-down or intracortical processes that do not appear in the output spiking activity.
One could also argue that the bias for the first saccade as observed in the present study may support the view that the region stores multiple saccadic amplitudes rather than multiple locations of targets relative to a current reference point (say, gaze direction). More specifically, in that scheme, the bias for the fist saccade follows from the fact that the metrics of the second saccade are such that it does not activate the voxels that comprise retIPS as defined by our localizer because this was identified using smaller saccades in mainly horizontal directions. In other words, the second saccade in the present RL or LR conditions is about double in amplitude compared with the localizer saccades. Likewise, the direction of the second saccade is mainly in vertical direction in the RR and LL conditions—a direction not incorporated in the localizer saccades. If the tonic activation of the region would indeed code saccadic amplitudes, including the amplitude and direction of the second saccade, one could thus argue that retIPS should not tonically respond to the second stimulus. The data show that this is not the case: there is a clear tonic activation to either of the two targets. Other evidence against this view has been provided by our previous fMRI study showing that retIPS codes target location relative to the current gaze direction and updates this information after the eyes have moved (Medendorp et al. 2003). As an example, consider the RL case. At time zero, a target, say 9° to the right, is displayed briefly and its location stored in the left parietal cortex. At time 12 s, a target of 9° to the left is displayed and stored in the right parietal cortex. At time 24 s, a saccade is made to the first target and then after 300 ms to the second target. There is no doubt regarding remapping of target locations after the first saccade so that the second target location is now coded as 18° to the left in the right parietal cortex. However, it is important to note that this would occur at a time after the first saccade and thus after our measurement period, beyond 24 s. At the time of our measurements (Fig. 8), the target locations would be coded as 9° to the left and 9° to the right. Thus on the basis of our previous and current data, we can rule out that retIPS stores multiple saccade amplitudes but rather the targets that define these saccades relative to the current gaze direction. It should also be emphasized that this is most consistent with monkey physiological evidence (Schall et al. 1995; Sparks 2002).
Recently, two reports have suggested that the human PPC contains several topographically organized regions for delayed saccades and visual spatial attention (Schluppeck et al. 2005; Silver et al. 2005). It remains to be established whether one of these exhibits the functional properties we have defined for retIPS here, and in our previous studies (Medendorp et al. 2003, 2005a,b).
What are the limits of the storage capacity of the map in retIPS? Here we have shown that a hemisphere can encode at least two contralateral target locations. Other evidence has shown that activity in bilateral posterior parietal cortex increases with the number of objects to be stored, to a maximum of about four objects (Linden et al. 2003; Todd and Marois 2004). These studies, however, did not examine lateralized effects on working memory capacity constraints. Therefore in the context of our findings, it remains to be elucidated whether this number of four objects relates to a capacity limit per hemisphere or if it reflects the total resource available to store target locations, to be shared across hemispheres. In this vein, Vogel and Machizawa (2004) reported ERP evidence for lateralized activity over posterior parietal sites in human spatial memory. They found the amplitude of this activity to be strongly modulated by the number of objects being held in memory but approaching a limit of about three to four targets. Thus a crucial experiment to be performed in retIPS should go along the lines of Vogel and Machizawa's experiment, testing the configuration of target locations that can be reliably encoded by this region.
Could the persistent activity in retIPS simply reflect visual attention? A popular account of visual attention is the spotlight theory, which states that attention can only be directed to one region of space at a time (Brefczynski and DeYoe 1999; Posner et al. 1980; Tootell et al. 1998). The spotlight can be switched rapidly between locations and can be adjusted, like a zoom lens, to expand or contract the size of the attended region. Our data are incompatible with this single resource model of attention. For example, when subjects have to memorize two targets, one in either hemifield (the RL and LR conditions), the focus of attention should span both fields, and thus be more diffuse. Accordingly, we might expect the activation after the second cue to become reduced, which is not what the data show. That is, the tonic activation during the RL and LR conditions after the second cue is greater than that after the first cue (Figs. 6 and 8).
Recent studies however have challenged the unitary spotlight theory of visual attention, and suggested that the spotlight can be divided flexibly to disparate locations (McMains and Somers 2004; Muller et al. 2003). As of yet, the cost of this division is unknown as are the factors that determine it (Tong 2004). Nevertheless, accepting this idea of divided attention, it could be argued that spatial working memories or maintained attention to particular regions in space (indicated by our targets) are two sides of a single coin. In other words, in the context of the present study, multiple attentional spotlights and spatial memories are concepts that may reflect the same neural mechanism.
Finally, in our study we did not record from the frontal cortex; the surface coil limited us to only the parietal ROIs, with the necessary high sensitivity. Thus the patterns of activation in the frontal areas during our saccade task remain to be discovered. Several studies have emphasized the importance of the frontal lobe in visual working memory for saccades (Linden et al. 2003; Tian et al. 2000). However, other recent studies have argued against the intimate involvement of these regions in spatial storage but instead have proposed that they perform top-down executive functions, such as response selection, movement initiation, and rehearsal, on representations stored in more posterior cortical regions, including PPC (Curtis and D'Esposito 2003). Although our results cannot differentiate between these interpretations, it is obvious that future research is required to determine more precisely the nature of the code in the networks of the brain that store and transform spatial information into motor action.
|
GRANTS |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
|---|
|
ACKNOWLEDGMENTS |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
|---|
|
FOOTNOTES |
|---|
Address for reprint requests and other correspondence: W. P. Medendorp, Nijmegen Institute for Cognition and Information, Radboud University Nijmegen, NL-6500 HE, Nijmegen, The Netherlands, (E-mail: p.medendorp{at}nici.ru.nl)
|
REFERENCES |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
|---|
Batista AP and Andersen RA. The parietal reach region codes the next planned movement in a sequential reach task. J Neurophysiol 85: 539–544, 2001.
Bisley JW, Krishna BS, and Goldberg ME. A rapid and precise on-response in posterior parietal cortex. J Neurosci 24: 1833–1838, 2004.
Boynton GM, Engel SA, Glover GH, and Heeger DJ. Linear systems analysis of functional magnetic resonance imaging in human V1. J Neurosci 16: 4207–4221, 1996.
Brefczynski JA and DeYoe EA. A physiological correlate of the "spotlight" of visual attention. Nat Neurosci 2: 370–374, 1999.[CrossRef][ISI][Medline]
Colby CL and Goldberg ME. Space and attention in parietal cortex. Annu Rev Neurosci 22: 319–349, 1999.[CrossRef][ISI][Medline]
Curtis CE and D'Esposito M. Persistent activity in the prefrontal cortex during working memory. Trends Cogn Sci 7: 415–423, 2003.[CrossRef][ISI][Medline]
Duhamel JR, Colby CL, and Goldberg ME. The updating of the representation of visual space in parietal cortex by intended eye movements. Science 255: 90–92, 1992.
Genovese CR, Lazar NA, and Nichols T. Thresholding of statistical maps in functional neuroimaging using the false discovery rate. Neuroimage 15: 870–878, 2002.[CrossRef][ISI][Medline]
Gottlieb J. Parietal mechanisms of target representation. Curr Opin Neurobiol 12: 134–140, 2002.[CrossRef][ISI][Medline]
Koyama M, Hasegawa I, Osada T, Adachi Y, Nakahara K, and Miyashita Y. Functional magnetic resonance imaging of macaque monkeys performing visually guided saccade tasks: comparison of cortical eye fields with humans. Neuron 41: 795–807, 2004.[CrossRef][ISI][Medline]
Linden DE, Bittner RA, Muckli L, Waltz JA, Kriegeskorte N, Goebel R, Singer W, and Munk MH. Cortical capacity constraints for visual working memory: dissociation of fMRI load effects in a fronto-parietal network. Neuroimage 20: 1518–1530, 2003.[CrossRef][ISI][Medline]
Logothetis NK, Pauls J, Augath M, Trinath T, and Oeltermann A. Neurophysiological investigation of the basis of the fMRI signal. Nature 412: 150–157, 2001.[CrossRef][Medline]
Mazzoni P, Bracewell RM, Barash S, and Andersen RA. Motor intention activity in the macaque's lateral intraparietal area. I. Dissociation of motor plan from sensory memory. J Neurophysiol 76: 1439–1456, 1996.
Medendorp WP, Goltz HC, Vilis T, and Crawford JD. Gaze-centered updating of visual space in human parietal cortex. J Neurosci 23: 6209–6214, 2003.
Medendorp WP, Goltz HC, and Vilis T. Remapping the remembered target location for anti-saccades in human posterior parietal cortex. J Neurophysiol, 94: 734–740, 2005a.
Medendorp WP, Goltz HC, Crawford JD, and Vilis T. Integration of target and effector information in human posterior parietal cortex for the planning of action. J Neurophysiol 93: 954–962, 2005b.
McMains SA and Somers DC. Multiple spotlights of attentional selection in human visual cortex. Neuron 42: 677–86, 2004.[CrossRef][ISI][Medline]
Muller MM, Malinowski P, Gruber T, and Hillyard SA. Sustained division of the attentional spotlight. Nature 424: 309–312, 2003.[CrossRef][Medline]
Posner MI, Snyder CR, and Davidson BJ. Attention and the detection of signals. J Exp Psychol 109: 160–174, 1980.[ISI][Medline]
Schall JD and Hanes DP. Neural basis of saccade target selection in frontal eye field during visual search. Nature 366: 467–469, 1993.[CrossRef][Medline]
Schall JD, Morel A, King DJ, and Bullier J. Topography of visual cortex connections with frontal eye field in macaque: convergence and segregation of processing streams. J Neurosci 15: 4464–4487, 1995.[Abstract]
Schluppeck D, Glimcher P, and Heeger DJ. Topographic organization for delayed saccades in human posterior parietal cortex. J Neurophysiol 94: 1372–1384, 2005.
Sereno MI, Pitzalis S, and Martinez A. Mapping of contralateral space in retinotopic coordinates by a parietal cortical area in humans. Science 294: 1350–1354, 2001.
Silver MA, Ress D, and Heeger DJ. Topographic maps of visual spatial attention in human parietal cortex. J Neurophysiol 94: 1358–1371, 2005.
Snyder LH, Batista AP, and Andersen RA. Coding of intention in the posterior parietal cortex. Nature 386: 167–170, 1997.[CrossRef][Medline]
Sparks DL. The brain stem control of saccadic eye movements. Nat Rev Neurosci 3: 952–964, 2002.[CrossRef][ISI][Medline]
Talairach, J, and Tournoux, P. Co-Planar Stereotaxic Atlas of the Human Brain. New York: Thieme. 1988.
Tian J, Schlag J, and Schlag-Rey M. Testing quasi-visual neurons in the monkey's frontal eye field with the triple-step paradigm. Exp Brain Res 130: 433–440, 2000.[CrossRef][ISI][Medline]
Todd JJ and Marois R. Capacity limit of visual short-term memory in human posterior parietal cortex. Nature 428: 751–754, 2004.[CrossRef][Medline]
Tong F. Splitting the spotlight of visual attention. Neuron 42: 524–526, 2004.[CrossRef][ISI][Medline]
Tootell RB, Hadjikhani N, Hall EK, Marrett S, Vanduffel W, Vaughan JT, and Dale AM. The retinotopy of visual spatial attention. Neuron 21: 1409–1422, 1998.[CrossRef][ISI][Medline]
Vogel EK and Machizawa MG. Neural activity predicts individual differences in visual working memory capacity. Nature 428: 748–751, 2004.[CrossRef][Medline]
Zhang M and Barash S. Neuronal switching of sensorimotor transformations for antisaccades. Nature 408: 971–975, 2000.[CrossRef][Medline]
This article has been cited by other articles:
|
|
 |
|
  C. E. Curtis and J. D. Connolly Saccade Preparation Signals in the Human Frontal and Parietal Cortices J Neurophysiol, January 1, 2008; 99(1): 133 - 145. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 W. P. Medendorp, G. F.I. Kramer, O. Jensen, R. Oostenveld, J.-M. Schoffelen, and P. Fries Oscillatory Activity in Human Parietal and Occipital Cortex Shows Hemispheric Lateralization and Memory Effects in a Delayed Double-Step Saccade Task Cereb Cortex, October 1, 2007; 17(10): 2364 - 2374. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
E. P. Merriam, C. R. Genovese, and C. L. Colby Remapping in Human Visual Cortex J Neurophysiol, February 1, 2007; 97(2): 1738 - 1755. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||
