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Resolving dual-task interference an fMRI study

Resolving dual-task interference an fMRI study
Resolving dual-task interference an fMRI study

Resolving dual-task interference: An fMRI study

Yuhong Jiang

Harvard University

Correspondence should be addressed to

Yuhong Jiang

Department of Psychology

Harvard University

33 Kirkland Street, Room 820

Cambridge, MA 02138

E-mail:yuhong@https://www.doczj.com/doc/2f1778207.html,

Phone:(617)-496-4486

Fax:(617)-495-3728(“Room 820”)

Acknowledgement. This research is supported by a Helen Hay Whitney Research Fellowship and a Milton Fund to Y.J, and a Human Frontiers Grant to Nancy Kanwisher. It is also supported in part by the National Center for Research Resources (P41RR14075) and the Mental Illness and Neuroscience Discovery (MIND) Institute. I thank Nancy Kanwisher for her intellectual generosity and Rebecca Saxe and Laura C. Wagner for comments.

Abstract

The human cognitive system is severely limited in the amount of information it can process simultaneously. When two tasks are presented within a short stimulus-onset-asynchrony (SOA), reaction time of each task, especially task 2, is dramatically delayed. Previous studies have shown that such delay is accompanied by increased activation in right inferior frontal gyrus (GFi). In this study, we address the role of right GFi in resolving dual-task interference at two different stages: allocation of perceptual attention and response selection. We scan 12 subjects using functional MRI while they conduct two tasks – shape discrimination in task 1 and color discrimination in task 2 –and vary the SOA between tasks as 100 ms or 1500 ms. The targets are located at the center or at the periphery. When both are at the center, they compete primarily for response selection. When both are at the periphery, they additionally compete for the allocation of perceptual attention. Results show that the right GFi and frontal operculum regions are significantly more active in the short SOA than the long SOA condition, but only when subjects attend to the periphery in both tasks. We conclude that the right lateral frontal regions are important for resolving dual-task interference at the perceptual attention stage.

Introduction

One of the most fascinating aspects of human cognition is our ineffectiveness in conducting two tasks at the same time. Despite frequent wishes to divide attention between two tasks – such as turning left in traffic while carrying out a coherent conversation – most of us choose to stop performing one task until the other is complete. But what prevents one from responding to the traffic light at the same time as choosing the next sentence to say? Research in cognitive psychology has provided extensive evidence that human attention is limited in at least two respects: perceptual attention and response selection (Jiang & Kanwisher, 2003a).

Perceptual attention is used primarily to select targets and filter out distractors when multiple objects are presented. It can be simultaneously directed to approximately four visual objects. For example, in multiple-object tracking, subjects first see 10 dots, a few of them blinked initially, and then all dots move randomly on the screen. Subjects’ability to track the previously blinked dots is severely impaired if more than 4 dots are to be tracked (Pylyshyn & Storm, 1988).

Response selection also poses a cognitive limitation. Pashler and colleagues propose that there is a central cognitive bottleneck, involved whenever a stimulus has to be mapped onto a response on the basis of an arbitrary rule, such as deciding to step on the brake when the traffic light turns red (Pashler, 1984, 1994). Mapping a stimulus to a response – a decision process – precedes the execution of motor responses. Thus, while we can press a key and say a word at the same time (Pashler, 1993), we cannot simultaneously decide which key to press on the basis of a shape and decide which word to say on the basis of a tone.

Response selection is not only different from motor execution, but also separate from the allocation of perceptual attention. This is revealed in that the central bottleneck cannot be divided between two response selection processes, but perceptual attention can be divided between a few perceptual objects. Thus, when people encounter a competition for response selection, they hold the second task in a queue; but when they encounter a competition for perceptual attention, they divide a proportion of perceptual attention to each object. Therefore, perceptual attention can be simultaneously divided between up to four perceptual objects (Luck and Vogel, 1997; Pylyshyn & Storm, 1988), but response selection can only be sequentially allocated to one task at a time (Pashler, 1989, 1991).

In this study, we use functional MRI to investigate how the brain resolves dual-task interference at the stage of perceptual attention and the stage of response selection. Competition at a third stage – the motor response stage – has been addressed by a separate study by Herath et al. (2001) and will be discussed later. We use the “overlapping task” design, adopted from behavioral studies on the central bottleneck (Welford, 1952; Pashler, 1984). In this design, two tasks are presented, separated by a variable stimulus-onset-asynchrony (SOA). When the SOA is short (e.g., 100 ms), the two tasks overlap in time and compete for perceptual attention and response selection. In this case, subjects have to perform task 1 AND task 2. As the SOA increases (e.g., to 1500 ms), the two tasks no longer overlap, so subjects only need to perform task 1 OR task 2. The difference between a short SOA condition (“AND”) and a long SOA condition (“OR”) reflects how the brain copes with overlapping stages of processing between two different tasks.

Several previous neuroimaging studies have studied the effect of dual-task processing (e.g., Adcock et al., 2000; Bunge et al., 2000; D’Esposito et al., 1995; Klingberg, 1998; Koechlin et al., 1999). These studies compare blocks of concurrent processing of two tasks (e.g., sentence comprehension and mental rotation) with blocks of single tasks alone. They observe increased activation in the dual-task condition in the dorsolateral prefrontal cortex and other regions. This suggests that additional central executive control is needed to resolve the dual-task interference. However, two design properties make these studies non-ideal for determining what goes on during overlapping processes. First, the dual-task condition uses a mixed-block design, which entails task-set switching between the two tasks (Allport & Wylie, 2000; Monsell & Driver, 2000). When a difference is found between a mixed-block and a single-task block, it may be attributed to either dual-task processing or task-set switching. Second, although the two tasks overlap in time in some studies, other studies have deliberately avoided overlapping processing. For example, in Klingberg’s (1998) study, the two tasks in the dual-task block are scheduled apart by 1 second to avoid a competition in motor output, so the dual-task blocks actually involve the processing of “task 1 OR task 2”. In D’Esposito et al., Adcock et al., and Bunge et al.’s studies, although the two tasks are presented inside the same time window, each trial of one or both tasks is extended for several seconds. This may allow subjects to sequentially perform the two tasks (cf Pashler, 1994). Thus, these studies have primarily examined the effect of maintaining two task sets and switching between them (“OR” versus single tasks; see also Dove et al., 2000; Kimberg et al., 2000; Konishi et al., 19998; MacDonald et al., 2000; Rushworth et al., 2002), and have not isolated the effect of overlapping task processing per se (“AND” versus “OR”).

Four other studies have investigated the effect of overlapping tasks. Herath et al. (2001) present two tasks separated by either a short SOA (200-300 ms) or a long SOA (1150-1350 ms). One task is a simple visual RT task, in which subjects press a key whenever an LCD is illuminated. The other task is a simple tactile RT task, in which the subjects press another key whenever they receive a tactile stimulation. The choice of two different input modalities minimizes competition for perceptual processing (Pashler, 1998), and the choice of two simple RT tasks minimizes competition for response selection (Pashler, 1994). Herath et al. find increased activation in the right inferior frontal gyrus (GFi) in the short SOA compared with the long SOA condition. They suggest that the activation result from a competition for the same motor effector.

Szameitat et al. (2002) and Schubert and Szameitat (2003) test the brain regions involved in tasks that overlap at a central stage. They use two choice-RT tasks that compete for the central bottleneck: a visual-motor and an auditory-motor task. Subjects are tested in a short SOA condition and blocks of single tasks. The short SOA condition show increased activation in right GFi compared with single tasks, suggesting that this region is involved not only in competition for the same motor effector (Herath et al., 2001), but also in competition for the central bottleneck. The interpretation of Szameitat et al’s and Schubert and Szameitat’s studies is limited, however, by the omission of a long SOA condition. As noted earlier, the difference between a short SOA condition and single task blocks includes two components: resolving dual-task interference and switching task sets. It is unclear whether the right GFi activation is produced by the need to switching task sets in the short SOA condition, by competition for the central bottleneck, or both. In fact, when a long SOA condition is added in a recent fMRI study (Jiang et al., in press), the difference between the short SOA and the long SOA condition

in the right GFi and other brain regions largely disappears, while the difference between the long SOA condition and single task blocks remains (Jiang et al., in press). This suggests that the right GFi may be more involved in task-set switching than in overlapping processing of response selection.

In this study we further investigate the role of the right GFi in resolving dual-task interference at two different stages: perceptual attention and response selection. We hypothesize that GFi is activated whenever two processes proceed simultaneously, but not when they occur sequentially. We further hypothesize that simultaneous processing occurs when two perceptual processes or when two motor processes are separated by a short SOA, but not when two response selection processes are separated by a short SOA. As a result, the GFi will increase its activation when two tasks compete for the allocation of perceptual attention or for motor processing (Herath et al., 2001), but not when they compete for response selection. This study focuses on perceptual attention and response selection.

We test subjects in three task combinations: when subjects attend to the center target in both tasks, when they attend to the center target in task 1 and to the peripheral target in task 2, and when they attend to the peripheral target in both tasks.

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On each display subjects are presented with one central target, one peripheral target, and seven peripheral distractors. The items are geometric shapes in task 1 (square or circle as the targets and triangles as the distractors) and colors in task 2 (red or green as the targets and mixed colors as the distractors). Subjects are told to attend

either to the central or to the peripheral targets and make responses to the target’s shape in task 1 and to the target’s color in task 2. Because the perception of a central target is easy, the competition involved in the center-center condition is primarily between the response selections of the two tasks. In the center-periphery condition, subjects have to shift attention from the center to the periphery. Finally, in the periphery-periphery condition the two tasks compete not only for response selection but also for spatial attention to the periphery. Thus, while response selection is the main competition in the center-center condition, perceptual attention is an additional source for competition in the periphery-periphery condition. Will the neural substrates involved in resolving these two kinds of interference be different?

Method

Participants: Twelve healthy adults between 18 and 32 years old were tested. They all had normal or contact-corrected normal visual acuity and normal color vision. Subjects participated in a 30 min practice before scanning.

Tasks: Ten subjects completed 6 sessions of fMRI scans; the other two subjects completed 2 sessions. Each session included 6 task blocks, composed of 3 task combinations and 2 SOAs. Each task block was preceded by a 14 second fixation and a 2 second instruction. The instruction informed subjects whether they should attend to the center or to the periphery. Each task block lasted 48 seconds and included 16 task pairs presented at 3 seconds / pair. Each display contained one central target, one periphery target, and 7 periphery distractors. The items in task 1 were geometric shapes. The distractors were triangles and the targets were square or circle. The items in task 2 were colored crosses. The distractors had mixed colors with one segment being red and the

other segment being green. The targets were pure colors of either red or green. The peripheral target was chosen randomly from 8 locations on an invisible circle (Radius = 3.3 degrees for task 1, and 3.0 degrees for task 2). Its identity could be the same or different from the central target. Figure 1 shows a sample display.

The instruction informed subjects to attend to (1) the central shape and the central color; (2) the central shape and the peripheral color; or (3) the peripheral shape and the peripheral color. Subjects were asked to press ‘1’ for a square and ‘2’ for a circle, using their left hand, and to press ‘3’ for red and ‘4’ for green, using their right hand. Attention was tested in different blocks.

Each trial started with the presentation of the first task display for 0.1 seconds. After an interval of zero or 1.4 s the second task display was presented for 0.1 seconds. The displays were presented briefly to discourage eye movements to the peripheral targets. Subjects were asked to respond as accurately and as quickly as possible to both tasks, within a time-window of 3 seconds.

FMRI design: Subjects were tested in the Martinos imaging center in Charlestown, MA, on Siemens 3.0 T research scanners. We first collected 128 saggital slices during the anatomical scans. During the functional scans 28 contiguous axial slices (4mm thick) were taken to cover the whole brain except the bottom half of the cerebellum (TR = 2s, TE=30ms, flip angle = 90 degrees). Each functional scan lasted 6 min 40 s, including 6 task blocks (48s each) and 7 fixation blocks (16s each). The first 6 fixation blocks (each preceding a task block) were composed of 14s of fixation and 2s of instruction. The order of the six task blocks was counter-balanced.

FMRI data analysis. Using SPM99, we first preprocessed each subject’s data, including motion correction, normalization to the MNI space, and spatial smoothing

with a Gausian kernel (FWHM = 5mm). Low frequency drifts were corrected in the analysis. Individual subjects’ data were analyzed to test for “all task > fixation” and the main effect of “short SOA > long SOA”. These contrast maps were then tested in a random-effect model for across subjects’ consistency. Because of the small number of subjects, a threshold of P < .001 (extended to 5 voxels) uncorrected for multiple comparisons was used. Finally, based on the “task > fixation” contrast, we defined 15 functional regions of interest (ROI) including the parietal cortex, frontal eye fields, lateral prefrontal cortex, basal ganglia, occipital cortex, and cerebellum, and tested the percent signal change (PSC) in each task condition.

Results

1.Behavioral results.

We calculated accuracy for all trials, RT for correct trials, and the correlation between task 1 and task 2’s RT. Table 1 shows the results.

Presenting the two tasks within 100ms of each other led to a dramatic increase in RT 1 of about 200ms and in RT2 of about 400ms. An ANOVA on attention (center-center, center-periphery, periphery-periphery) and SOA (short vs. long) revealed significant main effects of attention and SOA in RT1 and RT2, P’s < .0001. The interaction between attention and SOA was not significant for RT1, but was significant for RT2, P < .001. The SOA effect on RT2 was substantially larger when subjects attended to the peripheral targets (periphery-periphery, PRP = 491 ms) than when they attended to the central targets (center-center, PRP = 329 ms). This is consistent with the idea that the two tasks competed not only for response selection (which should be the same in all task combinations), but also for spatial attention when subjects attended to

the periphery. Further evidence that task 2 was waiting for the completion of task 1 came from the correlation data between RT1 and RT2. The correlation coefficients were about .30 when the SOA was long, but jumped to around .80 when the SOA was short.

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Insert Table 1 here

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2.fMRI results

(1) The effect of SOA

A random-effects analysis on the main effect of SOA (short SOA > long SOA, averaged across different task combinations) revealed two regions that showed an increased activation in the short SOA condition. The right inferior frontal gyrus (area 9, [48 15 33], 6 voxels) and the right frontal operculum (area 47, [30 24 0], 11 voxels) were significantly more active during the short than the long SOA conditions (Figure 2).

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To find out whether these two frontal regions showed a significant SOA effect in all task combinations, we calculated the percent signal change (PSC) in two regions-of-interest (ROIs) centered on the above locations (radius = 6mm). This analysis showed that the SOA effect was primarily driven by a higher PSC for short than long SOA conditions when subjects attended to the periphery in both tasks. The SOA effect was significant in the periphery-periphery condition in both frontal regions (P < .05), but was not significant in the other two conditions (P > .15). The interaction between SOA

and attentional condition was significant in the frontal operculum (P < .05) and was marginally significant in the GFi (P < .08).

(2) Regions of interest analysis.

To find out whether we had missed any other brain regions involved in resolving the competition between two concurrent tasks, we used a regions-of-interest (ROI) approach to increase statistical power. We selected 15 additional brain regions that showed a significant effect of “task > fixation” (P < .001 uncorrected, random effects analysis). The ROIs were centered on the most significant voxel and included all task-related voxels (“task > Fixation”) within a spherical volume of 9mm of the peak voxel. Figure 3 shows task related activation and Table 2 shows the percent signal change above fixation in the 15 ROIs.

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Insert Figure 3, and Table 2 here

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All ROIs showed a significant main effect of attention, with higher PSC when subjects attended to the periphery (center-periphery and periphery-periphery) than when they attended to the center. Only one region – right anterior IPS, showed a significant main effect of SOA, with higher PSC during the short than the long SOA conditions. The SOA effect was significant in the center-periphery and periphery-periphery conditions, but was not significant in the center-center condition.

It is interesting that the behavioral interference effect associated with SOA (about 400ms) was numerically larger than that associated with allocating attention to the

periphery (about 140ms), yet many more brain regions were sensitive to spatial attention than to the competition induced by shortening the SOA.

Discussion

In this study we confirm that a significant behavioral interference is observed when subjects have to perform two tasks overlapping in time. The duration of response to both tasks is dramatically increased (by about 200 ms in task 1 and about 400 ms in task 2). The interference is larger when both targets are in the periphery than when they are at the center. This suggests that in addition to competing for response selection, the two tasks compete for perceptual attention in the periphery-periphery condition. Results show a significant increase in activation in the right lateral prefrontal regions when the two tasks are presented within a short SOA rather than a long SOA. This activation is primarily driven by the periphery-periphery condition, suggesting that the right GFi is important for resolving interference at the level of perceptual attention.

The greater sensitivity of the right GFi to competition for perceptual attention than to competition for response selection is consistent with the idea that these two types of interference are resolved differently. Unlikely response selection, perceptual attention is divisible and can be simultaneously allocated to two tasks (Pashler, 1989). On this account, subjects in the periphery-periphery, short SOA condition allocate perceptual attention to both targets simultaneously, although both tasks may be impaired because of the limited resources for perceptual attention. In contrast, when the two tasks compete mainly for response selection, as is the case in the center-center, short SOA condition, the interference is resolved primarily by holding task 2 in a queue. Because the working memory load produced by holding task 2 in a queue is minimum,

the short and the long SOA conditions are essentially processed similarly. That is, in both conditions the two response selection processes are dealt with sequentially.

At first glance, the emphasis on the role of right GFi in resolving perceptual interference appears to be inconsistent with previous functions attributed to this region. Many studies have shown, for example, that the right GFi is involved in suppressing a prepotent response and in making a response selection (e.g., Bunge et al., 2002; Jiang & Kanwisher, 2003a, b; Hazeltine et al., 2000; Passingham et al., 2000; Sohn et al., 2000; Rubia et al., 2003). Few studies have ascribed a role of perceptual attention to the right GFi (Duncan & Owen, 2000). How should we reconcile the present result with other findings?

The answer to this question lies in that the current study is specifically about resolving overlapping task processing, while the other studies have focused on a given stage of process in single tasks. That is, we compared a short SOA condition with a long SOA condition, while other studies compared the presence with the absence of a certain cognitive process, such as inhibition of prepotent response. When subjects conduct a single task, which requires them to select a target among distractors, and to map the target onto an appropriate response, the right GFi is involved both during perceptual attention and during response selection (Jiang & Kanwisher, 2003a, 2003b). The particular process tapped in the current study though, is not about how perceptual attention or response selection is conducted, but about how the brain deals with overlapping task processes. Our finding is that the right GFi appears to be highly sensitive to overlapping perceptual attention processes, and less so to overlapping response selections. This finding fits well with behavioral observations that perceptual attention can be divided between multiple objects, but response selection has to proceed

sequentially. That is, presenting two tasks simultaneously changes how perceptual attention is allocated, but it does not change how response selection is conducted. When the SOA is long, both perceptual attention and response selection are allocated sequentially, whereas when the SOA is short, perceptual attention is allocated simultaneously and response selection remains sequential. In addition to perceptual attention, motor processing can be conducted in parallel (Pashler, 1994): one can simultaneously press a key and say a word, for example. Reducing the SOA between two tasks also potentially changes motor processes from sequential allocation to simultaneous allocation. Consistent with this analysis, Herath et al. found that the right GFi is involved in resolving interference at the level of motor process.

To conclude, we found that the inferior frontal gyrus, frontal operculum, and anterior IPS of the right hemisphere increase their level of activation when two tasks overlap in time. This is observed particularly when both tasks compete for perceptual attention. We suggest that in addition to their roles in response selection and perceptual attention of single tasks, the right ventral prefrontal regions are involved when attention has to be simultaneously divided between two perceptual attention processes.

References

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Table 1. Behavioral data collected during scanning.

Attention Center-center Center-periphery Periphery-periphery SOA Short Long Interference Short Long Interference Short Long Interference Accuracy1.99.97-.02, n.s..94.92-0.03, n.s..92.940.02, n.s. Accuracy2.95.950, n.s..84.870.03, n.s..88.910.03 *

RT1 (ms)805570235 ***944647297 ***1025776186 ***

RT2 (ms)931602329 ***1193747445 ***1232741491 ***

r(RT1,RT2).85.35N/A.80.30N/A.80.24N/A

Difficulty Rating #4.73 3.86 D = 0.87,

n.s.

8.25 6.18 D = 2.07 **8.37 6.83 D = 2.46 **

1 was “very easy” and 10 was “very difficult”. * P < .05; ** P < .01; *** P < .001; n.s. non-significant; N/A not applicable.

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课文是学生学习文化知识的重要材料,也是学生写作的典型范例。教师可充分利用课文资源,结合课文内容,让学生练习改写、续写、扩写等想象性作文,是一种行之有效的再造想象途径,能有效提高学生的想像能力。 例如《凡卡》一文,当凡卡满怀希望地把信寄出去后,爷爷能收到吗?爷爷在乡下会怎样想念凡卡呢?小凡卡后来的命运又会如何呢?让学生大胆去想象,续写出符合事情发展的故事,这样既加深了对课文内容的理解,又激活了学生想象的火花。 另外,还可以根据文中的插图进行补充或扩写。如《我的战友邱少云》一文在的插图,邱少云被烈火烧身时的巨大痛苦,是通过作者的心理活动侧面描写的,那么邱少云的心理感受会怎样呢?可引导学生观察他的神态、动作进行想象。 三、填补一些空白,设置整体形象。 在教学中选取一些相关的事物或词语,让学生进行整合,填补其中的空白,也是提高学生想象能力的重要手段。例如:画下几种不同的小动物,让学生按照自己的思维说出它们之间的关系,并想象出这些小动物之间会发生什么样的故事,然后进行口述表演,这样激起学生的童趣,他们的想象力就会更活跃。或者随便写下几个词语,让学生编上一段故事,用上这几个词语。这类填空白的训练,可以让学生的想象能力得到逐步提高。坚持长期训练,会收到意想不到的效果。 总之,学生作文能力的提高与教师的训练密不可分。我们应该在平时的作文教学中善动脑子,力求科学、有效,为学生作文插上想像的翅膀,让他们飞得更高、更远。

最新一缕春风拂面来初三作文800字

【篇一】一缕春风拂面来初三作文800字 无论冬天怎样漫长,春天就如同樱花般总会熬过严冬,以最美的姿态绽放于枝头,与你相见。——题记 20XX年的冬天似乎格外漫长,一场突如其来的新冠肺炎疫情袭卷神州大地。原本热热闹闹的新年,突然变得冷冷清清,和煦的春风也被阻隔在口罩之外。 出于安全考虑,人与人之间时刻注意保持安全距离,每个人的微笑也被隐藏在口罩之中。有一天上完网课,有些疲惫的我抬头看向窗外,突然发现门前的那棵树居然长出了嫩芽。之前因为功课太繁忙,每天早出晚归,披星戴月,所以从未注意到窗前的那棵树。今年春天延迟开学,我在家里上网课,所以有幸能见证它的生长。 那些刚刚长出的幼小嫩叶簇拥在一起,就像一朵小小的绿色荷花。那绿就像被雨水冲洗过一般,即使身在火热的夏天,也能让你的心底泛起一阵清凉。生命有时很脆弱,也许一场大雨就能把这些嫩叶摧残,可生命又如此顽强,即使被暴雨摧残,它们依旧能够长出新芽,继续生长。我们人类又何尝不是这样呢? 也许无情的病毒会夺走我们的生命,但是我们有能力、有信心从死神手里抢回。在这场人与病毒的战争中,我们看不到硝烟四起,但每天都有生死离别,阴阳两隔。疫情发生以来,每个人都在全力为抗疫作贡献。你看,爱与希望总比死亡与病毒蔓延得更快,这就是生命的张力与尊严。回顾历史,人类经受过很多苦难,在苦难面前,生命是何等渺小,但我们从不放弃活下去的希望。即使在苦难中,我们也艰难地摸索前行,去等待属于我们的春天,去感受那春风拂面的温柔。 这个春天,即使我们遭受过挫折,但生命却不会因为这些挫折而停滞,相反,它会拼命生长,在苦难中开花、结果。我想每一个熬过冬天的种子都有一个春天的梦想。让我们再等等,等到这个春天真正的到来,等到所有的花儿都开放,等到看樱花的人比樱花还要多,等到和煦的春风又再次抚摸脸颊。我们一定会摘下口罩,微笑问好。 【篇二】一缕春风拂面来初三作文800字 春风拂面,在其他任何季节,也会有一番如沐春风的舒畅与感动。 冬,一个寒冷的冬日,呼呼的寒风猛烈地刮着,呵气成冰的天气让我倍感不适,我因病体育课时在班中休息,听着外面强烈的风声,望着自己已冻得通红甚至有些僵硬的手,不禁一阵猛搓。这是,老师轻轻推开了门走了进来,端来一杯热水,关切的问道:“感觉好些了吗?喝点水,暖暖身子,如果不舒服直接去办公室打电话啊,不用找我。”我点点头,喝着水,感到无比的暖意,在这寒冬,我有一份感动,如同春风拂面。 不仅是在冬日,在夏日,也会有春风拂面的感觉。

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