Interference resolution in spatial working memory

www.elsevier.com/locate/ynimg NeuroImage 23 (2004) 1013 – 1019

Interference resolution in spatial working memory Hoi-Chung Leunga,c,* and John X. Zhangb,c a

Department of Psychology, State University of New York at Stony Brook, NY, USA Department of Linguistics, University of Hong Kong, Hong Kong c Molecular Imaging Research Center, Medical College of Shantou University, Shantou, China b

Received 28 January 2004; revised 16 July 2004; accepted 19 July 2004 Available online 14 October 2004 Anterior cingulate and lateral inferior prefrontal cortex (PFC) are considered important for conflict monitoring and interference resolution in many verbal tasks. We studied interference resolution in a spatial working memory task using event-related fMRI. The task required participants to ignore two locations from a set of four initially held in working memory and to remember the remaining two locations as the target set for a subsequent recognition test. Familiarity of nontarget probes was manipulated by drawing the probe from either the ignored locations [high familiarity (HF)] or locations not used in the present trial [low familiarity (LF)]. Precentral sulcus (PrCS) and superior parietal lobe (SPL), two regions commonly associated with motor planning and spatial attention, showed heightened activity in response to increased level of interference from nontargets of high familiarity. Our finding suggests that interference resolution in the spatial domain may involve a different subset of the working memory system from that in the verbal domain. D 2004 Elsevier Inc. All rights reserved. Keywords: Interference resolution; Spatial working memory; Superior parietal lobe; Precentral sulcus; Left inferior prefrontal cortex; Anterior cingulate; fMRI

Introduction Prefrontal cortex (PFC) is considered to play an important role in working memory, which is commonly referred to as the active maintenance and manipulation of task-relevant information through temporal gaps (Baddeley, 1986; Fuster, 1989; Goldman-Rakic, 1987). Good performance in working memory generally relies on successful interference resolution to ignore irrelevant or no-longerrelevant information. This topic has attracted attention in cognitive aging, where the inability to resolve interference from taskirrelevant information in older adults has been emphasized in behavioral (e.g., see Hasher and Zacks, 1988) as well as in

* Corresponding author. Department of Psychology, State University of New York at Stony Brook, NY 11794-2500. Fax: +1 631 632 7876. E-mail address: [email protected] (H.-C. Leung). Available online on ScienceDirect (www.sciencedirect.com.) 1053-8119/$ - see front matter D 2004 Elsevier Inc. All rights reserved. doi:10.1016/j.neuroimage.2004.07.053

neuroimaging research (e.g., see Jonides et al., 2000). Recent empirical studies and theories suggest that interference resolution and/or response inhibition is mediated by the same neural substrates underlying working memory (Bunge et al., 2001; Miller and Cohen, 2001). The neural substrate of interference resolution has been mostly studied using tasks that required resolving conflicts between stimulus dimensions (e.g., Stroop color–word interference task) and between responses (e.g., Eriksen flanker task), as well as inhibition of prepotent responses (e.g., go/no–go). Many neuroimaging studies emphasized the role of anterior cingulate cortex (ACC) in conflict monitoring and/or response inhibition in the aforementioned paradigms, yet other PFC and parietal areas were often activated along with the ACC (Botvinick et al., 1999; Bush et al., 1998; Carter et al., 1998; Konishi et al., 1999; Leung et al., 2000; Pardo et al., 1990). Recent neuroimaging studies further demonstrated that the ACC shows similar responses to conflicts across different stimulus domains (e.g., spatial and verbal) in a Stroop task (Barch et al., 2001) and across different task conditions (e.g., response inhibition and target detection) of low frequency events (Braver et al., 2001a). Interference resolution in working memory has been examined recently by manipulating the familiarity of nontarget test stimulus. Several studies demonstrated that the lateral inferior PFC [Brodmann area (BA) 44/45] in the left hemisphere is more active in response to familiar nontarget probes that appeared in study sets of previous trials than that of less familiar nontarget probes in delayed-recognition tasks with letter stimuli (D’Esposito et al., 1999; Jonides et al., 1998). Similar observation was noted using a running span design (Postle et al., 2001) and a verbal recognition task with an updating component (Zhang et al., 2003). The lateral inferior PFC is thus postulated for resolving the ambiguity from familiar but currently task-irrelevant probes. The anterior cingulate, however, either did not show clear involvement or showed very weak responses under this experimental manipulation (Jonides et al., 2002). To date, interference resolution in spatial working memory has not been investigated. In this report, we examined activations within the working memory system using a spatial delayedrecognition task with an updating manipulation, similar to the

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design of our previous verbal working memory study (Zhang et al., 2003). Our goal was to identify brain regions that are responsible for detecting or resolving interference in the spatial domain for successful working memory performance. Based on the literature reviewed above, if there is a general neural circuit for interference resolution, we expect the lateral inferior PFC to be involved in the present task. Note that inferior frontal gyrus (IFG) and inferior PFC are used throughout the paper interchangeably.

Materials and methods Participants Sixteen individuals (seven males, mean age = 27.3 years, SD = 6.1) were recruited from the Yale University and the Stony Brook University community to participate in this study, none with a history of neurological or psychiatric disorder according to selfreport. All had normal or corrected-to-normal vision and were strongly right-handed except one, who was ambidextrous. Handedness was determined using the Edinburgh scale (Oldfield, 1971). Participants gave informed consent to the protocol that was reviewed and approved by the institutional review boards of both universities. Spatial working memory updating task The spatial working memory task was a recognition task with an updating manipulation to generate three response conditions. A schematic drawing of the paradigm is shown in Fig. 1A. Each trial began with the presentation of a fixation screen (a 4  4 grid) for 1 s. The study display (four dots at four different positions on the grid) was then shown for 2 s followed by a delay of 3 s. The cue display (two dots selected from the study display) was presented for 1 s followed by another delay of 2 s. The probe (a ring) was displayed for 1 s before the resting period began. The intertrial interval (ITI) was 14 s, and a central fixation cross was presented during this period. The total duration of each trial was 24 s. Participants were told to fixate throughout the entire trial. The positions of the study dots were displayed pseudorandomly. The two dots in the cue display were randomly picked from the four positions in the study display. Participants were told to remember the positions of the four dots that appeared in the study display. They were instructed to disregard the locations of the two dots in the cue display from the initial memory set such that their final memory set is reduced to the other two locations. When the probe appeared, they were to response bYesQ if the probe matched one of the locations in their final memory set, and bNoQ otherwise. Correct responses thus require participants to ignore or discard the two no-longer-relevant locations specified by the cue display. There were three response conditions: (1) match (Yes), the probe matched one of the two taskrelevant locations; (2) high familiarity nonmatch (No-HF), the probe did not match the two task-relevant locations but was at one of the locations in the cue display; and (3) low familiarity nonmatch (No-LF), the probe did not match any of the locations presented in the current trial. Following the rationale in previous studies of interference in verbal working memory (D’Esposito et al., 1999; Jonides et al., 1998; Zhang et al., 2003), we expected to find an interference effect, that is, longer reaction times in the NoHF condition relative to the No-LF condition, due to the increased

Fig. 1. The spatial working memory task and behavioral results. (A) Sequence of trial events in the spatial delayed-recognition task with an updating manipulation. Participants first remembered the locations of four dots in the study display. They then disregarded the two locations indicated by the black dots in the cue display and remembered only the other two locations (dashed circles, not shown in the actual presentation) as the final memory set. When the probe appeared, they were to respond bYes,Q only if the probe matched one of the locations in their final memory set, and bNoQ otherwise. Arrows indicate delay periods between stimulus presentations. There was an initial fixation of 1 s at the beginning of the trial that is not shown in the figure. The three response conditions are labeled as follows: Yes, match; No-LF, nonmatch of low familiarity; No-HF, nonmatch of high familiarity. (B) Average reaction times for each response condition.

difficulty in rejecting probes of high familiarity in the former condition. Participants responded by pressing one of the two buttons with the index and middle fingers of their right hand. The correspondence between the two fingers and Yes/No responses was counterbalanced across participants. For each run, there were six bYesQ trials and six bNoQ trials. Three of the bNoQ trials had probes at locations that did not match any of the four locations in the study set (No-LF condition). The other three of the bNoQ trials had probes at locations that matched those in the cue display (No-HF condition). The conditions within a run were randomly assigned. All participants were given a practice run outside and a practice run inside the magnet. For the functional scans, each participant completed a total of eight runs, which included 48 Yes trials, 24 No-LF trials, and 24 NoHF trials. General experimental conditions Participants were in supine position during scanning. Head movements were restrained using foam pillows and a band across

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Image analyses—activation maps, regions of interest (ROIs), and time courses

Fig. 2. Overall responses during the recognition stage. The mean percentage signal changes from fixation baseline are shown for areas that were activated above thresholds of P b 0.001 and cluster size of N20 voxels. Positive activations are indicated by red to yellow, and negative activations are indicated by blue to purple. R, right; L, left. The numbers are the positions (z) of the slices in millimeters according to the Talairach atlas.

the forehead. Imaging was performed on a GE 1.5 T Signa LX scanner (Milwaukee, WI) with images acquired using the standard quadrature head coil and a T2*-sensitive gradientrecalled single-shot echo planar pulse sequence. Fifteen anatomical and functional images (7-mm axial-oblique slices, no skip) were prescribed parallel to the anterior–posterior commissural (AC–PC) line. The acquisition parameters for the anatomical images were as follows: repetition time (TR) = 500 ms, echo time (TE) = 14 ms, flip angle = 908, matrix size = 256  192, and field of view = 20  20 cm. The acquisition parameters for functional images were as follows: TR = 1500 ms, TE = 45 ms, flip angle = 778, matrix size = 64  64, field of view = 20  20 cm, and repetition = 192 images/slice/run. The first 10 images for each functional scan were discarded. All visual stimuli were presented in black against a light gray background. Visual stimuli were back-projected onto a screen positioned at the front of the magnet bore opening. The visual presentation was controlled using the VisionShell software (Micro M.L., Quebec, Canada) running on a Macintosh G3 computer (Apple Computer, Cupertino, CA).

Image analyses were performed using the Yale fMRI statistical package (by Pawel Skudlarski, http://mri.med.yale.edu/individual/ pawel/fMRIpackage.html). Before any analysis, functional images were corrected for motion using a version of the SPM99 algorithm (Friston et al., 1996). Images were removed from analysis if motion was greater than 0.5 voxels or if subjects made incorrect responses. Images were then spatially smoothed with a Gaussian filter (full width at half maximum of 6.3 mm). Individual activation maps were generated for the overall response and individual response conditions by calculating average percent change of signal relative to fixation baseline. For each condition, baseline signal was averaged using four images composed of the first two images before the study display and the last two images of the ITI period. Task-related signal was averaged using six images starting the second image after the probe onset. One image was skipped to correct for the delay in hemodynamic response. Group maps were generated after transforming each individual’s map into a standardized coordinate system (Talairach and Tournoux, 1988). Statistical group maps were calculated using a bootstrapping randomization technique (Manly, 1997). The final composite maps for the overall response condition (Fig. 2) were cluster-filtered (with 20 or more contiguous voxels) and thresholded to reveal only voxel clusters with percentage signal change values that fall above the 99.9 percentile of the random sampling distribution. Region of interest (ROI) analyses were also performed to test specific frontal and parietal regions that were activated during the recognition stage of the task. ROIs were defined from a previous spatial working memory study (Leung et al., Cognitive Neuroscience Society Annual Meeting abstract, 2003) and were drawn in accordance with the Talairach and Tournoux maps (1988). The ROIs that we planned for analyses include aPFC, vIFG, ACC, MFG, IFG, SPL, and PrCS (see Table 1). The average percentage

Table 1 Percentage signal change and statistical results ROIs

BA

Hemisphere

aPFC

10

vIFG

47

ACC

24/32

MFG

9/46

IFG

44

SPL

7

PrCS

6

Right Left Right Left Right Left Right Left Right Left Right Left Right Left

x

y 32 32 27 29 7 7 40 39 44 44 17 17 35 34

z 53 54 10 10 19 17 27 26 8 7 68 71 1 1

9 9 12 12 41 42 27 27 27 27 46 46 46 46

Yes

No-LF

No-HF

d1 (No–Yes)

t for d1

0.092 0.084 0.043 0.050 0.083 0.131 0.172 0.076 0.129 0.069 0.428 0.354 0.206 0.126

0.108 0.099 0.069 0.048 0.095 0.145 0.194 0.094 0.146 0.065 0.431 0.371 0.203 0.124

0.147 0.138 0.059 0.063 0.117 0.192 0.208 0.117 0.158 0.081 0.479 0.398 0.248 0.148

0.036 (0.019) 0.035 (0.011) 0.021 (0.013) 0.007 (0.009) 0.023 (0.011) 0.039 (0.019) 0.029 (0.010) 0.029 (0.014) 0.023 (0.014) 0.005 (0.013) 0.028 (0.014) 0.030 (0.013) 0.019 (0.010) 0.011 (0.010)

1.90 3.25* 1.59 0.75 2.01 2.03 2.81* 2.12 1.61 0.36 2.02 2.33* 1.89 1.09

d2 (No-HF–No-LF) 0.039 0.039 0.010 0.015 0.022 0.047 0.014 0.023 0.012 0.015 0.048 0.027 0.045 0.025

(0.028) (0.022) (0.023) (0.024) (0.018) (0.025) (0.023) (0.027) (0.016) (0.018) (0.021) (0.024) (0.016) (0.013)

t for d2 1.41 1.74 0.43 0.64 1.22 1.91 0.64 0.86 0.75 0.86 2.34* 1.14 2.76* 1.86

Average percent changes of signal from the baseline for each response condition are shown for each ROI in both hemispheres. Average signals during the response conditions were calculated using six images starting from the second image following probe presentation. Standard errors are in parentheses. The average centers of mass are in Talairach coordinates (x, y, z). Abbreviations: aPFC indicates anterior prefrontal cortex; vIFG, ventral inferior frontal gyrus; ACC, anterior cingulate cortex; MFG, middle frontal gyrus; SPL, superior parietal lobe; PrCS, precentral sulcus. Brodmann areas (BA) of each ROI are given in the second column. * Significant differences between the combined nonmatch and match (d1, No/Yes) conditions and between the two nonmatch conditions (d2, No-HF/No-LF), P b 0.05 (paired t tests).

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signal change of each ROI was calculated for each response condition (Yes, No combined, No-LF, No-HF) relative to the baseline of each condition. Significant signal differences between response conditions were determined using paired t tests. Significant differences between response conditions were set at P b 0.05 level. Time course of each response condition was plotted for each ROI. Individual time course averages (percentage signal change) at each time point were calculated relative to the baseline signal. Variations in slice acquisition times were adjusted for each slice. Before performing the interpolation and resampling, all time course data were time-smoothed by a Gaussian filter (full width at half maximum of 1.5 s).

Results

PrCS and SPL during the No-HF condition relative to the No-LF condition started to emerge following the probe presentation (Fig. 3), confirming that the difference in activity between the two nonmatch conditions indeed originated from the recognition stage of the task. Nonmatch versus match We also compared brain activity from the match condition with that from the combined nonmatch condition (Fig. 4). ROI analyses revealed overall stronger responses to the nonmatch probes than to the match probes in several areas, including the left anterior PFC (by the superior frontal sulcus, BA 10), the left SPL, and the right dorsal MFG (BA 46) ( P b 0.05, Table 1). No brain region showed significantly higher activation for the match condition than for the nonmatch condition.

Behavioral results Discussion The overall performance accuracy was high inside the magnet (97.4% F 0.66% for Yes, 96.5% F 1.16% for No-LF, and 97.6% F 1.32% for No-HF), and differences between the conditions were not significant ( F b 1). With the reaction time data (Fig. 1B), the effect of response type was significant [ F(2,30) = 10.7, P = 0.0003]. Post hoc contrast indicated that responses in the nonmatch conditions (combined No-LF and No-HF) were significantly slower than in the match conditions [907 vs. 775 ms, t(15) = 3.87, P = 0.0015]. The responses in the high familiarity nonmatch conditions were also slower than that in the low familiarity nonmatch conditions, although only marginally significant [941 vs. 872 ms, t(15) = 2.12, P = 0.051]. Nonetheless, this result was robust and reliable as the same analysis was highly significant in a pilot behavioral study with more data points per condition [899 vs. 803 ms, t(15) = 5.07, P = 0.0001].

Our behavioral results indicate that the manipulation of familiarity of nontarget probes induced a spatial interference effect; that is, participants took longer time to reject nontarget locations that had been more recently presented than to reject those that had not. This spatial interference is behaviorally analogous to the interference observed in previous verbal working memory studies (D’Esposito et al., 1999; Jonides et al., 1998) and particularly in our recent study, which utilized a similar experimental design to the current study except with letters as stimuli (Zhang et al., 2003). However, in contrast to studies performed in the verbal domain, we found that activity in the lateral inferior PFC was not modulated by the spatial interference manipulation. Rather, the right precentral sulcus and the right superior parietal

Overall response-related activation We first examined brain activation during the response/ recognition stage of the spatial working memory task by pooling activity from the three response conditions and comparing it with the fixation baseline. Generally, frontal areas including ACC, precentral sulcus (PrCS), and dorsolateral, ventral, and anterior PFC showed strong suprathreshold activity ( P b 0.001, uncorrected; Fig. 2). Most of the activations were bilateral except those in the dorsolateral PFC, which were right lateralized. Other nonfrontal areas were also activated, including the superior parietal lobe (SPL), middle temporal gyrus, middle occipital gyrus, basal ganglia, and thalamus. These results were similar to previous findings in spatial working memory studies (Leung et al., 2002). Interference effect We determined which regions among the predefined ROIs showed activity differentiating between the two nonmatch conditions and found that the right PrCS and the right SPL show greater activity in response to the high familiarity (No-HF) than to the low familiarity (No-LF) probes ( P b 0.05, see Table 1). However, the inferior frontal gyrus did not show significant differences between the No-LF and No-HF. This was different from the previous findings in the verbal working memory studies. Time course analyses indicated that the increased activity in the

Fig. 3. Average percentage signal changes and temporal dynamic differences between the two nonmatch probe conditions. Time courses for SPL and PrCS are shown. The x-axis represents time (scans in 1.5-s steps), and the y-axis represents average percentage signal change relative to fixation baseline. Time zero is the onset of the fixation display. The vertical line in each panel marks the onset of the probe. The thin green line is for the Yes (match) condition, the dashed blue line for the No-LF (low familiarity nonmatch) condition, and the thick red line for the No-HF (high familiarity nonmatch) condition. See Fig. 1 legend for notations and Table 1 note for abbreviations.

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Fig. 4. Average percentage signal changes and temporal dynamic differences between the match and nonmatch probe conditions. Time courses for MFG and aPFC are shown. The dashed magenta line is for the Yes (match) condition and the solid blue line for the No (combined nonmatch) condition. See Figs. 1 and 3 legends for notations and Table 1 note for abbreviations.

lobe, two brain regions that had not been reported to be sensitive to interference in verbal working memory, showed an activation pattern in conformity with the spatial interference effect. Therefore, the present study, in the context of previous research, failed to locate a single brain region serving as a general mechanism for interference resolution in working memory. Rather, different brain regions may be involved in interference resolution in working memory for different stimulus types: the left inferior frontal gyrus is involved in overcoming interfering verbal stimuli; the right precentral sulcus and superior parietal lobe are involved in overcoming interfering spatial stimuli. These findings thus raise the possibility that the cortical representation of interference resolution in working memory may be material-specific. Our study is the first to show that the right precentral sulcus and superior parietal lobe play a role in spatial working memory to resolve interference induced by familiar nontargets. In the literature, both PrCS and SPL are typically activated along with other frontal areas including the dorsolateral PFC during tasks engaging working memory (Duncan and Owen, 2000; Smith and Jonides, 1999). Both regions show strong sustained activity throughout a long delay period in a spatial delayed-recognition task and transient activity during encoding and recognition phases of the task (Leung et al., 2002). Neuroimaging studies have also demonstrated that both regions are sensitive to load manipulations in spatial working memory studies (Glahn et al., 2002; Leung et al., 2002). The precentral sulcus activation is in the dorsal premotor cortex, which is considered crucial for the selection of appropriate movement and motor planning (Grafton et al., 1998; Wise et al., 1997). Although not emphasized, this area was commonly activated in tasks involving conflict monitoring or interference resolution such as the color–word Stroop interference (Pardo et al., 1990) and other forms of Stroop interference (Bush et al., 1998). Besides, the precentral sulcus activation in the present study overlaps with the region that is suggested to be specialized for spatial working memory (Courtney et al., 1998; Sala et al., 2003).

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We therefore suggest that the precentral sulcus is involved in selection of spatial information from working memory by differentiating irrelevant from relevant information, which is critical for accurate response execution. The superior parietal lobe activation is in the posterior parietal cortex, which is most implicated in spatial processing as part of the dorsal visual pathway. Both electrophysiology and neuroimaging studies have demonstrated that the posterior parietal cortex is particularly involved in spatial attention (Corbetta and Shulman, 2002; Desimone and Duncan, 1995). SPL is also one of the regions most consistently involved in spatial working memory tasks (Chafee and Goldman-Rakic, 1998; Constantinidis and Steinmetz, 1996; McCarthy et al., 1996; Owen et al., 1996; Postle and D’Esposito, 1999), although the center of the activation in the current study is slightly inferior to the parietal activations in a typical spatial delayed-recognition task (Leung et al., 2002). Furthermore, Banich et al. (2000) have recently demonstrated that part of the SPL showed increased activity in relation to different task-irrelevant stimuli in a Stroop study using color words and color objects. They concluded, bit appears that when there is conflicting information, attentional control occurs more by modulating processing of the task-irrelevant information than by modulating processing of task-relevant informationQ (Banich et al., 2000). Our result on SPL is consistent with this view as interference resolution can be based on a mechanism to disregard familiar but no-longer-relevant information in spatial working memory. However, one caveat is that the interference-related activity in the SPL was not as robust as that of the PrCS. Future studies are thus needed to further elaborate the role of SPL in interference resolution and attentional control. It is worth mentioning that the ROI analysis of ACC in our results showed a trend to be more activated by nontargets of high familiarity than by low familiarity (see Table 1). Such a weak involvement of ACC in detecting or resolving the familiarityinduced conflict is perplexing because the ACC has been most emphasized in monitoring stimulus or response conflicts and resolving cognitive interference in many studies including the Stroop interference (Carter et al., 1998; Pardo et al., 1990) and the flanker interference (Botvinick et al., 1999; Bunge et al., 2002). However, similar to what we found in the present study, other verbal working memory studies also reported weak ACC responses to familiar nontarget probes than to the less familiar ones (Jonides et al., 2002; Zhang et al., 2003). These findings suggest that ACC may play a minor role in interference resolution in working memory. A secondary finding, the preferential activation of anterior PFC to nontarget probes than to target probes, agrees with our recent results in another spatial delayed-recognition task (Leung et al., Cognitive Neuroscience abstract, 2003). Activation of anterior PFC has been consistently found in episodic memory studies (Duncan and Owen, 2000) and has been suggested to be specific to episodic retrieval (Tulving et al., 1994). However, recent studies start to question this proposal (MacLeod et al., 1998). For example, some studies that directly examined brain activations in both working memory and episodic memory have demonstrated that the anterior PFC is involved in both forms of memory (Braver et al., 2001b; Ranganath et al., 2003). In addition, it has also been associated with higher level cognitive processing and/or integrative functions (Christoff and Gabrieli, 2000; Koechlin et al., 1999). Our finding of anterior PFC in the recognition stage of this spatial working memory task supports the notion that this area is not unique to episodic retrieval.

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Acknowledgments We thank the anonymous reviewers for their comments. We thank Dr. Pawel Skudlarski for his help with data analysis, and we thank Terry Hickey and Hedy Sarofin for their technical assistance. This work was supported by SUNY Stony Brook. Other supports include grants from Key International Collaboration Project (NSF F2003-79), the Natural Science Foundation of Guangdong, China (#010434), and Research Grants Council Central Allocation Vote (RGC CAV) group research grant (HKU 3/02C).

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