Working memory (WM) (Baddeley, 2000; Baddeley & Hitch, 1974; Engle, 2002)facilitates temporary maintenance of relevant information in the mind and plays a critical role in many complex cognitive tasks. Visual WM stores and manipulates visual and spatial information and these information are stored relatively separate within the visuospatial sketchpad (Baddeley, 2000) . Spatial WM and spatial attention are closely related (Awh & Jonides, 2001; Cowan, 2000) and spatial attention plays an important role in maintaining location information (Awh & Jonides, 2001) .

As widely accepted, spatial attention and eye movements are intimately coupled (Posner, 1980; Reeves & Sperling, 1986; Kurylo, Reeves, & Scharf, 1996; Kowler, Anderson, Dosher & Blaser, 1995; Kustov & Robinson, 1996; Moore & Fallah, 2004) . Shift of spatial attention can be overt or covert and eye movements demonstrate overt shift of spatial attention. Therefore, it is natural that eye movements interact with spatial WM. Refixations on an object when freely inspecting a scene improve the memory performance and it was proposed that refixations continuously update the availability of items in the memory (Zelinsky & Loschky, 2009) . On the contrary, there are also studies demonstrating the interference of eye movements on the spatial WM (Baddeley & Lieberman, 1980; Kerzel & Ziegler, 2005; Smyth & Scholey, 1994) . In line with the close relationship between spatial WM and attention, Lawrence, Myerson, and Abrams (2004 ) found that the spatial WM span was decreased by the covert shift of attention and even more by eye movements, demonstrating that eye movements interfere with spatial WM and the interference caused by eye movements is greater than covert attention shift. Moreover, keeping a location in memory curved eye trajectories away from the remembered location (Theeuwes, Olivers, & Chizk, 2005) . These studies demonstrate an intimate link between the control of eye movements, attention and working memory (Golomb, Chun, & Mazer, 2008; Theeuwes, Belopolsky, & Olivers, 2009).

In contrast with the clear relationship between spatial WM and eye movements, the relationship between eye movements and non-spatial WM is still under debate. In the study of Awh, Jonides, and Reuter-Lorenz (1998 ), a letter appeared and subjects had to memorize the location of the letter or the identity of the letter. At the same time, choice stimuli appeared during the retention interval and subjects indicated the shape of the stimuli by pressing button quickly. Reaction times to choice stimuli were faster if they appeared at the memorized location, suggesting that spatial attention is focused on the memorized location. In contrast, when remembering the identity of the letter, no benefit of the location of the letter was observed, suggesting the specific relation between spatial WM and visual attention. Similarly, in the study of Lawrence, Myerson, and Abrams (2004 ), the authors found a reduction in the spatial WM span by the attention shift, but not in the verbal WM. In line with these findings, a movement discrimination task interferes with the spatial WM task of memorizing dot locations, while a color discrimination task does not (Klauer & Zhao, 2004) . Additionally, Kerzel and Ziegler (2005) found that the color WM performance was unaffected by the addition of smooth pursuit task while the spatial WM performance was impaired by the additional smooth pursuit task. On the contrary, Makovski and Jiang (2009) found concurrent performance of a color WM task and attentive tracking task produced mutual interference with each other. In their study, subjects were encouraged to maintain fixation at the display center while attentively tracking multiple objects. They proposed that common attentional processes are engaged in these two tasks which are of central and amodal origin. Baddeley (2000) proposed a multiple component model, which included central executive, visuospatial sketchpad, phonological loop and episodic buffer. Furthermore, visual and spatial information were stored relatively separately within the visuospatial sketchpad. Therefore, we assumed that the common attentional resources shared by attentive tracking and color WM point to the central executive component in Baddeley’s model (2000).

Similar to the intimate couple of visual spatial attention and saccades, smooth pursuit eye movements foveate moving objects and are closely related to visual attention as well. Dividing attention from the smooth pursuit could impair the pursuit performance (Acker & Toone, 1978; Brezinova & Kendell, 1977; Heinen, Jin, & Watamaniuk, 2011; Souto & Kerzel, 2008) . Addition of larger random dot cinematogram (RDC) that moves with the pursuit target helps to release attention from the pursuit which can be used to improve performance of secondary attention task (Jin et al., 2013) . These results demonstrate that attention is involved in the smooth pursuit eye movements. In addition, studies showed that attention is narrowly allocated around the smooth pursuit target although with some conflicts. Some studies showed that attention allocation during smooth pursuit is asymmetric, more attention is distributed ahead of the pursuit target (Kanai, van der Geest, & Frens, 2003; Khan, Lefe`vre, Heinen, & Blohm, 2010; Seya & Mori, 2012; Smeets & Bekkering, 2000; van Donkelaar & Drew, 2002) , while others proposed that attention is symmetrically distributed around the pursuit target (Lovejoy et al., 2009; Watamaniuk & Heinen, 2015) . Studies on schizophrenia demonstrated that spatial WM impairment was associated with dysfunctions in the oculomotor mechanisms (Park & Holzman, 1993; Snitz et al, 1999) . The deficit of spatial WM performance was related to smooth pursuit because of the limitation of attention distributed to position (Kerzel & Ziegler, 2005; Park, Holzman, & Levy, 1993) . However, color WM performance was unaffected by the addition of smooth pursuit task, suggesting the allocation of attention was restricted to position which is responserelevant dimension (Kerzel & Ziegler, 2005) . These studies again implied the ambiguity of the relationship between eye movements and non-spatial WM.

Therefore, we designed a delayed-match-to-sample paradigm (DMS), whereby a WM load task is interleaved with pursuit task during the maintenance period in the present study. In the experiment, subjects memorized the color of squares in the cued visual field and foveated a moving cross during the retention period. The cross moved toward or away from the visual field where the memory targets were presented. Since attention is narrowly distributed around the pursuit target, pursuing towards or away from the cued visual field might influence the color WM differently because the attention would be allocated in the cued VF or in the uncued VF in the present design. Therefore, we asked whether eye movements affect the performance of color WM and whether smoothly directing gaze toward or away from the previous location of the memory item would have differential effects on the color WM.

First, we compared the WM performance in the WM + pursuit session and the WM-only session to investigate whether adding secondary pursuit task in the retention period would harm the WM performance. To do this, we have conducted a two-way repeated-measure ANOVA using the WM load (load 2 and 4) and the presence of pursuit task (without and with pursuit task) as factors Figure 2. As usual, we found the WM accuracy decreased with higher load (F(1,15)=270.97, p=0.000) and adding the pursuit task did reduce the WM accuracy (F(1,15)=9.27, p=0.008). Consistently, the reaction times were longer with higher load (F(1,15)=11.94, p=0.004) and adding the pursuit task lengthened the reaction times (F(1,15)=4.83, p=0.044) as well. These results demonstrated that eye movements during the retention period harmed the WM performance.

We also compared the pursuit performance in the WM + pursuit session and the pursuit-only session to investigate whether adding secondary WM task would affect the pursuit performance. We found a significantly lower peak open loop gain (F(1,15)=14.39, p=0.002) in the WM + pursuit session (0.77 ± 0.05) compared with pursuit-only session (0.89 ± 0.05). In addition, the steadystate velocity gain was also lower in WM + pursuit session (0.92 ± 0.024) than in the pursuit-only session (0.98±0.014) (F(1,15)=10.57, p=0.005). These results indicated the addition of the secondary WM task harmed the pursuit performance.

Combining these results, we see that the WM and pursuit interfere with each other. However, it is still unclear whether it is general for secondary task or specific to the eye movement type. To check this, we analyzed the data from the WM + pursuit session in details.

Figure 3 shows the performance of working memory in the WM + pursuit session, which was assessed using a two-way repeated-measure ANOVA for load (load 2 vs. load 4) and consistency (consistent vs. inconsistent). Consistent with previous findings, the accuracy was decreased with higher load (F(1,15)=92.53, p=0.000) and the consistent condition revealed higher accuracy than the inconsistent condition (F(1,15)=4.73, p=0.046). No interaction between the load and consistency. Similarly, the reaction times increased with higher load (F(1,15)=14.50, p=0.002) and the consistent condition showed shorter reaction times than the inconsistent condition (F(1,15)=5.23, p=0.037). Further post hoc t-tests, Bonferroni corrected for multiple comparisons, showed longer reaction times in the inconsistent condition (881.6 ± 48.1 ms) than in the consistent condition (832.3 ± 45.6 ms) (Bonferroni adjusted t(15) = 3.15, p = 0.007) with load 2. In this comparison, the significance level was adjusted to 0.0083 (0.05/6 = 0.0083) due to 6 possible comparisons across the 4 conditions (4*3/2 = 6).

Combining the accuracy and reaction time results, we found pursuing towards the locations where the WM stimuli were presented produced better WM performance than pursuing away from those during the retention period. In addition, we computed the mean horizontal eye positions in a 200 ms time window since the test display onset to see whether eyes returned to the central fixation cross. A two-way repeated-measures ANOVA on load (load 2 vs. load 4) and consistency (consistent vs. inconsistent) showed a significant effect of consistency (F(1,15)=5347.64, P=0.000) and interaction between load and consistency (F(1,15)=14.46, P=0.002). Further comparison showed that the eyes deviated more from the fixation cross with load 2 (9.857 degree) compared with load 4 (9.510 degree) (t(15) = 2.59, p = 0.021). These data showed that the eyes posited around the positions where pursuit ended and had not returned to the fixation cross yet when the test display appeared, resulting in bigger retinal eccentricity in the inconsistent condition. Interestingly, the retinal eccentricity was smaller with load 4 than with load 2, indicating that memorizing more colors urged eye to return to the central fixation.

In addition, to check the effect of the WM on the pursuit, we analyzed the open-loop gain and steady-state gain using a two-way repeated-measures ANOVA using load (load 2 vs. load 4) and consistency (consistent vs. inconsistent) as factors respectively Figure 4. The ANOVA revealed lower open-loop gain (F(1,15)=29.50, p=0.000) and steady-state gain (F(1,15)=10.08, p=0.006) with higher load. Moreover, the steady-state gain was higher in the inconsistent condition (F(1,15)=8.30, p=0.011) and there was a marginally significant interaction between the load and consistency (F(1,15)=3.85, p=0.069). Further pairwise comparison using 0.0083 (0.05/6 = 0.0083) as the significance level due to 6 possible comparisons across the 4 conditions (4*3/2 = 6) showed mean steady state gain in the inconsistent condition was higher than that in the consistent condition with higher WM load (Bonferroni adjusted t(15) = 3.28, p=0.008). Additionally, we also found higher saccade frequency with higher load (F(1,15)=9.31, p=0.008), indicating the worse pursuit performance with higher load. Overall, these results showed that the pursuit performance was further impaired by higher load and the steady-state performance was even influenced by the consistency between the WM and the pursuit.

In order to check whether the change of squares’ colors in the uncued VF affected the WM performance, we grouped the trials in two types in each load condition for the data from the WM only session. One type included trials with the color change (change) and the other type included trials without color change (same) in the uncued VF. Since the color changes in the cued and uncued VF were independent each other and all trial type had equal opportunities, we would not expect an effect of the trial type. We assessed the WM performance using the repeated-measures ANOVA for WM load (load 2 vs. load 4) and trial type (same vs. change). There was only a significant effect of load for accuracy (F(1,15)=300.95, p=0.000) and no effect of the trial type was found, indicating that the color change in the uncued VF did not affect he WM performances. Therefore, we suggested that the subjects followed the instruction.

In the current study, we showed that the color WM and the smooth pursuit eye movements interfered with each other. More interestingly, pursuing towards the cued visual field resulted in enhanced color WM performance compared with pursuing away from it. In turn, the higher load of WM impaired the pursuit performance more than the lower load of WM.

The color WM performance was impaired by adding the pursuit task during the retention period and the pursuit performance was also impaired by adding the color WM task, demonstrating that the color WM and smooth pursuit interfere each other and further suggesting smooth pursuit share common resources. We think that common attentional resources shared by the color WM and SPEM might be of central, amodal origin, which might point to the central executive component in Baddeley’s model (2000). This also agrees with the resource model of working memory which propose that a limited resource is distributed flexibly across all representations which are maintained in memory (Ma, Husain & Bays, 2014) . Consistently, higher WM load impaired the pursuit performance more as shown by the lower open-loop gain and steady state gain, and higher saccade frequency in the load 4 condition.

In turn, greater impairment of the color WM performance which was shown by lower accuracy and longer reaction time, was observed in the inconsistent condition where the pursuit during the retention period was away from the location of the WM stimuli, showing that the direction of smooth pursuit plays a role in our WM task. In the current study, the fixation cross moved towards or away from the cued VF from the display center. Therefore, in the trials where the cross pursued towards the cued VF, the smooth pursuit target moved within the cued VF during the whole retention period and vice versa. Studies agreed that attention is narrowly distributed around the pursuit target, while they disagree about the symmetry of the attention distribution during smooth pursuit (Kanai, van der Geest, & Frens, 2003; Khan, Lefe`vre, Heinen, & Blohm, 2010; Seya & Mori, 2012; Smeets & Bekkering, 2000; van Donkelaar & Drew, 2002; Lovejoy et al., 2009; Watamaniuk & Heinen, 2015) . Hence, we propose that more attention could be distributed in the cued VF during the retention period in the consistent condition and more attention benefited the color WM. The results showed that shifting attention smoothly to the locations where the memory target was presented would help the color WM compared to when shifting attention away from it. These results mimic attention-based rehearsal hypothesis (Awh & Jonides, 2001) . This hypothesis proposes the rehearsal of stored spatial information is accomplished by shifts of spatial selective attention to memorized locations. Therefore, our finding further extends the hypothesis to the relationship between spatial attention and non-spatial WM and further suggest that spatial attention plays a functional role in maintaining non-spatial information. However, our results could not exclude the possible effect caused by the closer eye position to the WM target in the consistent condition at the onset of the test display.

At the same time, the pursuit performance was better in the inconsistent condition than in the consistent condition during the steady-state, especially when the WM load was higher. Since spatial attention plays an important role in maintaining location information (Awh & Jonides, 2001) and attention is allocated around the pursuit target, a conflict or competition of attention resources might occur in the inconsistent condition, especially when the demand for attentional resources is intensified. This imitates the anti-saccade task, which requires subjects to suppress a reflexive saccade towards a visual stimulus and perform a voluntary saccade away from the target (Cutsuridis et al. 2007; Everling & Fischer 1998) . Therefore, the pursuit in the inconsistent condition was more difficult than that in the consistent condition and more cognitive control is needed for the pursuit in the inconsistent condition. This is in line with the previous finding that eye-target synchronization improved under higher cognitive load (five-words) for normal subjects (Contreras et al., 2011) .

Taken together, our results are in line with the finding from Makovski and Jiang (2009) and support that the visual WM and smooth pursuit share common attentional resources. Due to the presentation of the colored squares on the display, it is still possible that the locations of squares were encoded and memorized automatically. However, we tried to reduce this possibility by fixing the possible locations of the squares in each condition and forbidding exchanging colors between squares when comparing the colors of the target and test stimuli. Such a design reduced possible effect of stimuli location, so we suggest that our results can be interpreted as the relationship between the color WM and smooth pursuit. Many studies have shown persistent neural activities during the retention period of WM in the prefrontal areas (Funahashi et al., 1993) , frontal eye fields (Curtis et al., 2004; Tark & Curtis, 2009) and posterior parietal cortex (Schluppeck et al., 2006). Since smooth pursuit-related brains areas mainly involve fronto-parietal network, such as the frontal eye field, supplementary eye fields and posterior parietal cortex, there are many overlaps in the brain areas related to the WM and smooth pursuit. Similarly, we supposed that there might be a competition for the shared neural resources of fronto-parietal network, resulting in competition between the color WM and pursuit tasks.

In sum, the current study found mutual interference between the color WM task and smooth pursuit eye movements. Furthermore, the pursuit direction plays a role in the color WM that the color WM benefited when pursuing towards the locations where the WM stimuli were presented. We propose that it is because more attentional resources are directed to the locations of the WM stimuli during the retention period by the help of the smooth pursuit eye movements.