Colour priming modulates the attentional boost effect

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C. Au, Alvin K. M. Tang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7343715/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Jan, 2026 Read the published version in Psychological Research → Version 1 posted 10 You are reading this latest preprint version Abstract The attentional boost effect (ABE) refers to the enhancement of memory encoding during a dual-task. To investigate the under-researched influence of target signal properties in the ABE, this study examined whether implicit colour priming influences passive attentional capture and modulates the magnitude of the ABE. Participants completed an encoding-recognition task across three priming conditions (red, green, and yellow). Each condition comprised four parts: a priming phase, an encoding phase, a wash-out period, and a recognition phase. During the priming phase, participants passively viewed a series of images predominantly associated with a specific colour. In the encoding phase, participants engaged in a dual-task requiring detection of red target signals (while ignoring green distractor signals) and simultaneous memorization of background words. Recognition performance was then assessed through an old-new classification task. Results revealed significant differences in ABE magnitude across the three colour conditions. Red priming produced the strongest memory enhancement, suggesting that congruent colour priming facilitated attentional capture. In contrast, green priming diminished the effect, which is potentially caused by interference linked to attentional shift toward the distractors. The ABE observed under the yellow control condition fell between those of the red and green conditions, establishing a valid baseline for assessing the colour-priming influences. These findings indicate that colour priming could strengthen passive attentional engagement and enhance memory encoding in divided attention conditions, highlighting the importance of feature congruence in modulating the ABE. Attentional boost effect Dual-task Memory encoding Passive attentional capture Priming Figures Figure 1 Figure 2 Introduction The attentional boost effect: an unexpected phenomenon of memory enhancement under dual-task conditions Daily activities often necessitate the execution of multiple tasks concurrently, such as when navigating a route during driving. While extensive research on attention has demonstrated that devoting more attention to one task typically diminishes the performance of the other, a growing body of research findings has discovered that the performance of a secondary task performance can be enhanced under dual-task conditions. Swallow and Jiang ( 2010 ) were among the earliest groups of researchers to document this counterintuitive phenomenon in research on attention and memory. They designed a dual-task paradigm which consisted of an encoding phase followed by a recognition phase. During the encoding phase, participants viewed a series of scene images, each superimposed with a coloured square (in white or black) at the centre of the screen. They were instructed to detect and respond to target-coloured (white) squares via button pressing, while simultaneously memorizing the scene images in the background. Subsequent recognition task indicated better accuracy on recognizing scenes previously paired with the target-coloured squares. This memory enhancement phenomenon was termed the “attentional boost effect” (ABE), suggesting that the target detection initiated transient attentional enhancement, which in turn facilitated the encoding of the concurrently presented visual information. Theoretical account for the ABE Early researchers proposed the temporal selection theory in the “Dual-Task Interaction” model to account for the ABE (Swallow & Jiang, 2013 ), which attempts to explain the effect by proposing that the perceptual processing of the background item would be enhanced when the item is presented at a moment that is behaviourally relevant to the presentation of the target (Swallow & Atir, 2019 ). Subsequent research pointed to a different perspective and introduced the early perceptual enhancement hypothesis as a theoretical framework for the ABE, which proposes that enhanced visual processing is elicited when a target stimulus appears concurrently with a visually encoded item (Spataro et al., 2013 ). Swallow and Jiang ( 2013 ) elaborated upon this view, proposing that target detection may facilitate perceptual processing in a modality-general manner rather than being limited solely to the visual domain. Empirical support for this hypothesis has been obtained through various experimental paradigms. For instance, Spataro et al. ( 2013 ) reported a robust ABE in lexical decision and word-fragment completion tasks (i.e., perceptual implicit tasks), while no significant effect was observed in tasks such as semantic classification (i.e., conceptual implicit tasks). However, Mulligan et al. ( 2014 ) challenged the perceptual encoding hypothesis by highlighting its limitation to account for the enhancement of non-perceptual word properties such as lexical, semantic, and phonological attributes. By employing experiments that utilized multiple modalities and incorporated free recall tasks, they observed a significant ABE irrespective of modalities, suggesting that perceptual encoding cannot fully explain the underlying mechanisms for the ABE. Consequently, they proposed the early-phase-elevated-attention hypothesis, which argued that robustness of the ABE across brief encoding intervals implies a more generalized enhancement process beyond strictly perceptual operations. The underexplored role of targets in the ABE Numerous empirical studies have substantiated the generality of the ABE across both visual and auditory modalities, encompassing visual and verbal stimuli, various memory systems, and diverse target detection paradigms. Spataro et al. ( 2013 ) were the first to examine the ABE by replacing pictorial stimuli with verbal stimuli and revealed that explicit memory enhancement for target-paired words was comparable to that observed for images. In a subsequent study, Mulligan et al. ( 2014 ) manipulated word frequency and employed both visual and auditory recognition tasks, demonstrating that ABE magnitude was greater for high-frequency words than for low-frequency ones. This finding implies that memory benefits occurring during the early phase of processing may diminish the memory enhancement typically associated with the ABE. Further research by Spataro et al. ( 2015 ) investigating orthographic distinctiveness reported that the ABE occurred only for low-frequency words with common orthographic features but not for those with rare features, thus supporting the view proposed by Mulligan et al. ( 2014 ). Extending from these findings, Smith and Mulligan ( 2018 ) explored the influence of primary distinctiveness by employing the isolation paradigm (i.e., identifying a stimulus with a salient feature among a list of stimuli that share a common feature). Their results demonstrated that primary distinctiveness elicited significant ABE under divided attention conditions and suggested that this form of distinctiveness originates from the retrieval phase, contributing an elaboration on earlier theoretical frameworks. Recent research on the ABE has increasingly shifted the focus toward the characteristics of target signals. Au and Cheung ( 2020 ) explored the physical attributes of the targets, demonstrating that both frequency and colour salience can significantly modulate the ABE magnitude. Meanwhile, other researchers have examined the role of target predictability. For instance, Sisk and Jiang ( 2020 ) reported a robust ABE when the digit ‘0’ served as a predictable target, which was facilitated by the preceding presentation of a countdown sequence (i.e., from ‘3’ to ‘1’). Expanding on this, Pan et al. ( 2024 ) investigated the temporal interval of target predictability and found that the ABE was evident under short (‘1’ to ‘0’) and medium (‘3’ to ‘0’) predictive durations, but not under extended ones (‘7’ to ‘0’). However, the influence of predictability on the ABE remains uncertain. Saraulli et al. ( 2023 ) reported inconsistent results by employing a design where five consecutive target signals were followed by five distractors. Their findings indicated reduced recognition accuracy for words paired with both targets and distractors compared to those observed in conventional ABE paradigms. Research examining the semantic nature of target signals has further enriched the theories on attentional boost mechanisms. Zheng et al. ( 2021 ) manipulated the semantic level of target numbers to assess its impact on ABE magnitude and observed a significant effect that appeared independent of the semantic load. All together, these studies revealed multiple dimensions of target signal processing in the ABE paradigm. However, further empirical investigation is essential to achieve a more comprehensive understanding of the underlying mechanisms of the effect (for an updated review, see Au & Tang, 2025 ). In attention research, Westerberg and Schall ( 2021 ) reviewed evidence demonstrating that priming modulates selective attention during visual search tasks by facilitating the selection of previously encountered features. Given that the ABE reflects memory facilitation driven by transient increases in attentional engagement, priming may offer a valuable perspective for exploring the underlying mechanisms that contribute to the ABE. Attention and priming In cognitive psychology, priming represents an implicit learning process, which denotes the influence of prior exposure to a stimulus on the perception or reaction towards a subsequent stimulus, which occurs without awareness (Tulving et al., 1982 ). Posner and Snyder ( 1975 ) conceptualized priming as the anticipatory activation of a target’s representation. Experimental evidence suggested that such cues can assist in predicting target attributes or spatial position, leading to an enhancement in visual search efficiency (Beller, 1971 ; Eriksen & Hoffman, 1972 ). Previous research has extensively examined the interaction between attentional processes and priming. Blough ( 1989 ) investigated the influence of two types of priming on attention by employing preceding cues prior to each trial. The findings revealed that both reaction time and accuracy significantly improved when predictive cues were presented, in contrast to non-predictive cues. Blough ( 1989 ) also observed that presenting non-prime targets following an informative prime impaired target detection performance. However, this impairment was diminished when targets were displayed without distractors. Altogether, these findings suggested that priming mechanisms may function similarly to the attentional processes in divided attention, as both are governed by the constraints of limited cognitive capacity. The relationship between priming and divided attention has also attracted the interest of researchers. While certain studies have reported that priming effects remained stable under conditions of divided attention (e.g., Parkin et al., 1990 ; Parkin & Russo, 1990 ), others have reported evidence suggesting that divided attention can reduce priming efficacy (e.g., Eich, 1984 ; Mulligan & Hartman, 1996 ). Objectives and rationale of the present study In ABE research, although substantial efforts have been focused on exploring the influence of various attributes of the to-be-encoded stimuli, procedures and population, a notable gap persists regarding the contribution of the target signal that initiates the attentional capture in the dual-task paradigm. To address this gap, the present study investigated the effects of ‘passive’ attentional engagement through implicit perceptual learning on the resultant ABE. The present experiment extended the previous studies on investigating the target signals and examined how priming could affect the passive attentional capture, consequently leading to changes in the strength of the resultant ABE. Traditionally, the ABE paradigm is structured around an encoding-recognition design in which participants engage in a dual-task during encoding. Specifically, the encoding phase requires participants to perform a primary task involving the detection of coloured target signals, while concurrently performing a secondary task of encoding the words presented in the background (e.g., Au & Cheung, 2020 ). To investigate the potential influence of priming on the passive attentional capture process and its resultant impact on the strength of ABE, the present experiment introduced a priming phase prior to the encoding phase. In the priming phase, participants were exposed to a set of images characterized by a dominant colour that was either congruent, incongruent, or neutral relative to the colour of the target signals that would appear in the encoding phase. Following priming, participants were instructed to maximize their accuracy in detecting the red-coloured target signals (and ignoring the green-coloured distractor signals) while simultaneously encoding the words which appeared in the background. Upon completion of the encoding phase, participants proceeded to the recognition phase in which memory performance for the previously presented words was assessed. The strength of ABE was evaluated by comparing the accuracy of memory for words previously paired with the target and distractor signals. Previous findings have suggested implicit learning may facilitate automatic attentional capture by salient stimuli (e.g., Luck et al., 2021 ). Thus, we anticipate the congruent-colour priming procedure in the present experiment would reinforce the target detection process, leading to a greater attentional capture and enhancing the encoding of the background words (i.e., a stronger ABE). Therefore, the first hypothesis for the present experiment was that participants’ corrected hit rate for the words in the recognition phase would be higher towards items paired with the target signal in the colour congruent condition, compared to the incongruent and control conditions. The second hypothesis was that the strength of ABE would be greater in the colour congruent condition than in the incongruent and control conditions. Method Participants A total of sixty-three healthy adult participants (mean age = 20.25 years, SD = 1.98 years) were recruited for the present experiment, all possessing normal or corrected-to-normal vision and intact cognitive functioning. Individuals who had any medical conditions potentially affecting cognitive performance were systematically excluded. Before the experiment, participants were shown a red (RGB: 255, 0, 0) target circle alongside a green (RGB: 0, 255, 0) distractor circle on a computer screen with no limit in presentation duration to check their ability to discriminate the two colours. All participants successfully differentiated the colours of the target and distractor signals before proceeding with the main task. Apparatus and materials Visual stimulus presentation and participant response collection were managed through a customized computer program developed using MATLAB R2022a (MathWorks, MA), incorporating the Psychophysics Toolbox Version 3.0.18 extension (Brainard, 1997 ; Kleiner et al., 2007 ; Pelli, 1997 ). The program was executed on a desktop workstation running the Windows 10 operating system and interfaced with a 24-inch LCD monitor. The monitor utilized in this study had display dimensions of 52.704 cm in width and 29.646 cm in height, with a screen resolution of 1920 × 1080 pixels and a refresh rate of 60 Hz. For preparing the images to be used in the priming phase, a total of 60 visual stimuli were selected from the Bank of Standardized Stimuli (BOSS; Brodeur et al., 2010 ), based on their perceptual and conceptual relevance to designated colour conditions of this experiment (e.g., tomatoes for the red condition, plants for the green condition, and the moon for the yellow condition). To enhance the consistency of colour among the images under the same colour condition, all images were modified to closely match the corresponding colour values at standardized RGB parameters: red (RGB: 255, 0, 0), green (RGB: 0, 255, 0), and yellow (RGB: 255, 255, 0). These images were presented during the priming phase in the three experimental blocks, each corresponding to a distinct colour condition. Specifically, 20 images were presented in the congruent (red) condition, 20 in the incongruent (green) condition, and 20 in the control (yellow) condition. The words to be memorised by the participants during the encoding phase were selected from the frequency dictionary of contemporary American English (Davies & Gardner, 2010 ) based on the following inclusion criteria: (i) the word must be a noun, (ii) consists of six to eight letters, and (iii) ranks within the top 5000 most frequently used words in daily communication. These criteria were employed to ensure the words used in the experiment would be familiar and cognitively accessible to participants. A total of 270 words were selected to be used in the experiment, with 90 items for each of the three blocks. Each block included 60 old items presented during the encoding phase and 30 new items introduced solely during the recognition phase. To minimize the potential influence of the priming procedure on lexical retrieval during the recognition phase, all selected words were carefully chosen to ensure they were not semantically or associatively related to the primed colour conditions (red, green, or yellow). Design and procedure The experiment was conducted in a quiet room inside the laboratory of the host university. Participants were seated at a standardized viewing distance of 62 cm from the monitor. The study comprised three distinct experimental blocks, each containing a priming phase, an encoding phase, an arithmetic task, and a recognition phase. The presentation order of the blocks was counterbalanced among the participants to minimise potential order effects. Before the start of experiment, participants were informed of their rights and compensation associated with participation. Written informed consent was obtained to document their voluntary participation. Participants also completed a practice session to ensure adequate understanding of all procedures. At the beginning of each experimental block, participants were presented with a series of 20 object images of the same dominant colour during the priming phase. This was designed to trigger a colour association and no response was required in this phase. In the congruent condition block, the images predominantly featured the red colour, which corresponded to the colour of the target signal to be displayed in the subsequent encoding phase. Example stimuli included images of tomato, no-entry sign, fire hydrant, and strawberry. In the incongruent condition, all images predominantly featured the green colour, aligning with the colour of the distractor signal. Sample stimuli included images of cabbage, clover, cucumber, and toy dinosaur. The control condition included 20 images associated with the yellow colour, such as banana, moon, lemon, and caution sign. All images were standardized to the dimension of 13.725 cm × 13.725 cm and were displayed centrally on the monitor for 2000 ms each. Following the priming phase, the encoding phase then began with presentation of the task instructions, and the participant initiated the phase by pressing the spacebar. During this phase, participants were instructed to memorize a total of 60 English words (i.e., the old items described in the Apparatus and materials section), all presented in Arial font. Among these stimuli, 30 words were accompanied by a red target signal and were designated as ‘Old_Target’ items, while the remaining 30 were paired with a green distractor signal and were designated as ‘Old_Distractor’ items. Each trial involved the presentation of a single word centrally displayed on the screen inside a hollow circle (diameter = 10.16 cm; border = 1.65 cm). The hollow circle served as the signal for detection during the dual-task encoding phase (red circle as the target and green circle as the distractor). The target and distractor signals (with the respective Old_Target and Old_Distractor words) were randomly presented across trials. Consistent with the methodology described in Au and Cheung ( 2020 ), the hollow circle functioned as a peripheral signal surrounding the word stimulus to maintain visual clarity and avoid interference with encoding the word. In the encoding phase, each trial began with a white fixation cross (length of the line = 1.098 cm; width = 0.082 cm) presented at the centre of the black screen for 1000 ms. Subsequently, the target word (in white) was displayed concurrently with a coloured hollow circle signal surrounding it. The signal lasted for 50 ms, while the word remained visible for an additional 350 ms (total duration for the word: 400 ms). A black blank screen then followed for another 500 ms. Participants were instructed to respond to the signal quickly and accurately by pressing the spacebar when a red target signal appeared, and to withhold their response when a green distractor signal appeared. Responses were allowed at any point during the period between the disappearance of the signal and the end of the blank interval. Figure 1 illustrates the flow of events during the encoding phase in the congruent priming block. In total, the encoding phase comprised 60 trials, corresponding to 2 signal colours × 30 words. Upon completion of the encoding phase, participants engaged in a 60-second arithmetic task consisting of mental multiplication problems involving two-digit numbers. Each problem was presented individually on the screen one after one. This task served to disrupt working memory and promote reliance on retrieval from long-term memory during the subsequent recognition phase. Participants verbally provided answers to the arithmetic problems, and the responses were not recorded. In each trial of the recognition phase, a single word stimulus (in white) was presented at the centre of the black screen. The words presented in the recognition phase consisted of either previously encoded words (i.e., those presented as Old_Targets or Old_Distractors in the encoding phase) or new words that had not been displayed in the encoding phase. Participants were instructed to make an old/new judgment by pressing the right arrow key if they recognized the presented word from the encoding phase or the left arrow key if the word appeared to be new. The recognition phase comprised a total of 60 trials, which included 15 ‘Old_Target’ items, 15 ‘Old_Distractor’ items, and 30 new items. The 15 Old_Target and 15 Old_Distractor items were randomly sampled from the original pool of 30 words presented with the red targets and the 30 words presented with the green distractors during the encoding phase. Upon completion of the recognition phase, participants were given a three-minute rest period before proceeding to the next block of colour priming condition until they complete all the three colour blocks. Results Data analyses were performed using IBM SPSS 29.0 (IBM Corporation, New York, USA). For each of the three colour blocks, the performance of each participant during the encoding phase was assessed using hit rate (HR; the percentage of correctly identifying the target signals), false alarm rate (FA; the percentage of incorrectly identifying distractor signals as targets), and mean reaction time (RT) of the detection responses. Across all conditions, participants exhibited consistently high HRs and low FAs (see Table 1), indicating high sensitivity to the target stimuli and effective attentional engagement throughout the encoding task. Table 1. The hit rates for the correct detection of target signals (HRs), false alarms for the incorrect detection of distractor signals (FAs), and the respective reaction time (RTs) in the encoding phase of the experiment. Colour condition in the priming phase Red Yellow Green Accuracy (%) Hits (HR) 99.84 (0.71) 99.52 (1.32) 99.52 (2.23) False alarms (FA) 4.23 (2.42) 4.12 (3.15) 3.94 (1.67) RT (ms) Hits 512.84 (78.99) 520.62 (77.27) 526.17 (74.41) False alarms 575.11 (170.94) 523.92 (187.53) 544.98 (171.05) Recognition performance was evaluated by computing hit rates (HR) and false alarm rates (FA) in identifying the words presented in the recognition phase across conditions. HR was computed as the proportion of trials in which a participant correctly identified old items, i.e., responses of pressing the right-arrow key when seeing Old_Target or Old_Distractor words. FA was calculated as the proportion of incorrect identifications, i.e., pressing the right-arrow key in response to new items. To ensure the strength of ABE was accurately assessed, analyses of data from the recognition phase were limited to data which met specific criteria as explained in the following. ABE is theorized to be elicited only when the target signal is successfully detected during the encoding phase, which leads to an enhanced memory for concurrently presented stimuli. In contrast, trials in which participants failed to detect the target signal or mistakenly responded to a distractor signal are unlikely to produce the ABE. Therefore, trials with incorrectly omitted target detection and those with incorrect detection of distractors were excluded. Consequently, ‘corrected hit rates’ for the recognition data were calculated to adjust for response bias: Corrected HR Old_Target = HR Old_Target – FA; Corrected HR Old_Distractor = HR Old_Distractor – FA (see Au & Cheung, 2020 for more details on the rationale). Summary statistics including raw HRs, FAs, corrected HRs, and RTs in the recognition phase for each condition are presented in Table 2. Table 2. The data of the recognition phase, including the raw hit rates (HR) and false alarm rates (FA), corrected HRs for old items, and reaction times (RTs) for item recognition across the three colour priming conditions. The reported counts reflect the number of trials included in the analysis after excluding trials that involved words associated with incorrectly omitted target signals or incorrectly recognized distractor signals during the encoding phase. Colour condition in the priming phase Red Yellow Green Raw rates (%) HR Old_Target 72.98 (16.37) 70.58 (17.04) 63.77 (17.78) HR Old_Distractor 59.89 (18.95) 62.30 (18.47) 60.97 (21.39) FA 22.96 (14.37) 25.93 (15.15) 19.05 (14.78) Corrected HR (%) Corrected HR Old_Target 50.02 (17.62) 44.66 (17.68) 44.72 (19.51) Corrected HR Old_Distractor 36.93 (21.48) 36.38 (18.24) 41.92 (24.30) RT (ms) Old items (target) 867.93 (176.05) 868.61 (150.67) 884.03 (137.37) Old items (distractor) 899.03 (194.16) 880.98 (162.15) 878.09 (144.04) New items 943.45 (222.67) 920.42 (227.00) 892.53 (151.56) Count Old items (target), out of 15 14.98 (0.13) 14.94 (0.25) 14.97 (0.25) Old items (distractor), out of 15 14.71 (0.52) 14.81 (0.43) 14.79 (0.45) To examine whether the recognition performance, as measured by corrected HRs, were different across the three colour priming conditions and between the two old item types, a 3 (Colour: red, yellow, green) × 2 (Old Item Type: target, distractor) repeated measures ANOVA was conducted (Figure 2A shows the relevant data). The analysis revealed a significant main effect of Old Item Type [ F (1, 62) = 35.543, p < 0.001, partial η 2 = 0.364] and the Colour × Old Item Type interaction [ F (2, 124) = 9.982, p < 0.001, partial η 2 = 0.139]. However, the main effect of Colour was not statistically significant [ F (2, 124) = 1.159, p = 0.317, partial η 2 = 0.018]. Simple main effect analysis showed that the effect of Colour was significant in both old item types of Old_Target and Old_Distractor (at p < 0.05). Among the Old_Target item type, pairwise comparisons showed significant difference between the red vs. green and red vs. yellow priming conditions (both at p < 0.05), but not between the green vs. yellow priming conditions (at p = 0.977). Among the Old_Distractor item type, pairwise comparisons showed significant difference between the red vs. green and green vs. yellow priming conditions (both at p < 0.05), but not between the red vs. yellow priming conditions (at p = 0.838). Furthermore, simple main effect analysis for Old Item Type (i.e., comparing between the target-paired items and distractor-paired items) was significant in the red and yellow priming conditions (both at p < 0.001), but not in the green priming condition ( p = 0.120). The ABE strength was calculated for each colour priming condition by comparing the corrected hit rates between the two item types (i.e., ABE = Corrected HROld_Target – Corrected HROld_Distractor; Figure 2B shows the relevant data). To examine the effect of colour priming on the strength of ABE, a one-way repeated measures ANOVA was performed to compare across the three priming conditions. The analysis showed significant effect of colour priming on ABE strength [ F (2, 124) = 9.982, p < 0.001, partial η 2 = 0.139]. Pairwise comparison showed that the ABE strength differed significantly among the three colour priming conditions (all at p < 0.05). In summary, the results demonstrated that colour congruent priming led to stronger ABE than colour incongruent priming and control conditions. In addition, the colour incongruent priming condition showed weaker ABE compared to the colour congruent priming and control conditions. Discussion The present experimental findings provided empirical support for the first hypothesis. Simple main effect analysis on Colour showed that the corrected HR towards target-paired words (i.e., Old_Target items) was significantly higher in the colour congruent (red) priming condition compared to the incongruent and control conditions. In addition, simple main effect analysis on Old Item Type revealed that the corrected HR for Old_Target items was significantly higher than that for Old_Distractor items in the colour-congruent priming condition. This enhancement in memory performance may be attributed to the presentation of red-coloured object images prior to the encoding phase, which corresponded with the colour of the subsequently presented target signals. Such congruence may have facilitated perceptual processing and attentional engagement on the red target signals during target detection, leading to an enhancement of memory encoding for the associated target-paired words. A few previous studies on colour priming might be relevant to explaining our findings. For example, Marangolo et al. ( 1993 ) observed that colour cues can facilitate the subsequent recognition of target hues via a repetition priming paradigm. Through separate manipulations of colour and spatial position, Geyer and Müller ( 2009 ) demonstrated that priming effects facilitate performance independently and are susceptible to top-down processing modulation. These findings suggest that colour priming induces the anticipation of subsequent colour-congruent stimuli. In the colour congruent condition of the present experiment, repeated exposure to red-coloured object images may have strengthened the efficiency of attentional focus on the red targets and the concurrently displayed words, resulting in the higher corrected HR for Old_Target items. On the other hand, the colour-incongruent priming involved the presentation of green-coloured object images that matched the colour of the distractor signals in the subsequent encoding phase. The priming phase did not affect perceptual processing of the red target signals, but rather facilitated the processing of the green distractor signals. This may have led to increased attentional allocation toward the distractor-paired words and subsequently improved the recognition performance for those items. According to the feature priming theory proposed by Maljkovic and Nakayama ( 1994 ), repeated exposure to a colour facilitates attentional guidance toward subsequent presentations of that colour, thereby enhancing the encoding of concurrent stimuli and strengthening memory traces. This mechanism may account for the higher corrected HR for distractors observed in the colour-incongruent priming condition in our study. Under the colour incongruent condition, presentation of green-coloured objects induced a priming effect that might have selectively enhanced attentional allocation toward green distractor signals. This elevation in attentional engagement contributed to improved memory performance for items paired with distractors. Furthermore, the control condition employed yellow-coloured object images that were perceptually unrelated to the colours of the target (red) and distractor (green) signals in the detection task. Consequently, these neutral stimuli were unlikely to influence the processing of either signal type during the encoding phase, and that the yellow priming condition could serve as a baseline reference for illustrating the effect of congruent and incongruent priming. For instance, a higher corrected HR for Old_Target items was observed under the red priming condition over the control condition, and a higher corrected HR for Old_Distractor items was observed under green priming than the control condition. This pattern of results might suggest that colour priming can modulate the memory encoding processes in a feature-specific manner, with different colours selectively enhancing attention towards distinct signal-paired items. Lastly, the present results supported the second hypothesis that the strength of ABE would be greater in the colour-congruent condition than in the colour-incongruent and control conditions. These patterns can be explained by attentional mechanisms described by Swallow and Jiang ( 2010 ) who proposed that the ABE arises from a widened attentional gate in which detecting a target transiently enhances attentional resources for encoding concurrently presented stimuli. In line with this perspective, Becker et al. (2014) proposed that attentional gain is selectively enhanced for a chosen target colour, potentially diminishing attentional resources allocated to non-target colours. Similarly, Ramgir and Lamy ( 2021 ) demonstrated that repeated exposure to a specific colour enhances attentional priority toward the colour in subsequent tasks, even when it functions as a distractor. Relating this to the present study, repeated exposure to red-coloured object images during the priming phase in the colour-congruent condition may have heightened attentional engagement with red target signals. The increased attention likely widened the attentional gate proposed by Swallow and Jiang ( 2010 ), resulting in a more substantial enhancement in memory encoding. This enhanced selective attention facilitated encoding of target-paired items, resulting in a stronger ABE. In contrast, priming with green-coloured object images in the colour-incongruent condition may have shifted attentional priority toward the green distractor signals. Consequently, the encoding of distractor-paired items was enhanced and offset the memory facilitation on target-paired items, leading to a diminished overall ABE strength compared to both the congruent and control conditions. The results of the present experiment revealed two valuable insights into the ABE. One notable finding was that the corrected HR for the Old_Distractor items in the colour-incongruent priming condition was higher than that in the control condition. This suggests that colour priming can enhance memory encoding for items that are not behaviourally relevant, such as the Old_Distractors (i.e., stimuli that participants were not instructed to attend to or respond to via button press). Notably, this enhancement occurs when the priming colour differs from the colour of the instructed target, indicating that the effect of colour priming is not limited to task-relevant stimuli. More importantly, the corrected HR for the previously encoded distractor-paired items (i.e., Old Distractor items) in the colour-incongruent priming condition reached a level comparable to that for the target-paired items. The enhancement of colour priming appears to occur independently of the facilitation typically associated with target detection in the ABE. In other words, the memory benefit observed for the distractor-paired words under incongruent colour priming did not interfere with the encoding benefit toward the target-paired words conferred by detection of the red targets, which are generally linked to an increased attentional engagement. This finding implies that colour priming supports encoding process through a parallel attentional pathway, through enhancing memory without interfering with the facilitation from target detection. Another key finding was that the corrected HR for the Old_Target items in the colour-congruent priming condition was significantly higher than that in the control condition. This result indicates that colour-congruent priming can enhance the memory encoding beyond the facilitation typically provided by the ABE, suggesting that the memory facilitation conferred by target detection in the ABE could be further amplified through the presentation of a perceptually-identical feature (i.e., the colour) before the encoding phase. More specifically, when the priming colour was congruent with the colour associated with target detection, the memory enhancement towards the target-paired items typically observed in the ABE was not only preserved, but further facilitated, as evidenced by the higher corrected HR observed in the colour congruent (red) priming condition compared to the control (yellow) priming condition. This additive effect implies that congruent perceptual cues, such as colour, can interact with temporal attention mechanisms to produce a compounded benefit for memory encoding. This highlights the potential for feature-based priming to modulate attentional engagement in a way that enhances memory encoding beyond the traditional ABE paradigm. Potential research on the role of priming in the ABE While the present study provides new evidence that colour priming can influence the attentional capture in the ABE, it highlights new possibilities for examining the underlying mechanisms of this modulation. Specifically, it remains an open question whether the enhancement from priming stems primarily from perceptual features (e.g., colour congruence) or from conceptual associations embedded in the object images used during the priming procedure. To isolate the perceptual and conceptual factors, future research could employ abstract, non-conceptual stimuli such as coloured geometric shapes or spatial sequences of coloured shapes for the priming phase. Another direction involves expanding the scope of priming beyond colour. For example, spatial priming effect could be examined by presenting stimuli at specific locations on the screen to test whether position-based priming cues can affect the attentional level and modulates the ABE magnitude. These ideas may help broaden the theoretical scope of priming effects on the ABE and enhance new understanding on the influence of priming on passive attentional capture and memory encoding processes. Conclusion In conclusion, using priming, this study investigated the influence of implicit learning on passive attentional capture and its impact on the ABE. The experimental results demonstrated that colour congruence between the primed stimuli and the target signals significantly modulated the magnitude of ABE. Specifically, priming with colour-congruent stimuli enhanced attentional capture and yielded the strongest ABE magnitude, while incongruent colour priming diminished the effect. These findings provide new evidence that passive attentional engagement can be shaped by implicit learning mechanisms, and that pre-exposure to colour-congruent stimuli can improve memory encoding performance under divided attention. Declarations Ethical approval: Ethical approval to conduct this study has been obtained from the Research Ethics Committee of the authors’ host university. Informed consent: Informed consent was obtained from all participants in this study. Conflict of interest: On behalf of all authors, the corresponding author states that there is no conflict of interest. Data availability: The data analysed in this study are available from the corresponding author upon reasonable request. Funding: The work described in this paper was fully supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (UGC/FDS16/H29/23). Authors’ Contribution: Ricky K. C. Au – study conceptualisation, data collection and data management, statistical analyses, manuscript preparation. Alvin K. M. Tang – data collection and management, statistical analyses, manuscript preparation. All authors approved the final manuscript. References Au, R. K. C., & Cheung, C. N. (2020). The role of attention level in the attentional boost effect. Journal of Cognitive Psychology , 32 (3), 255–277. https://doi.org/10.1080/20445911.2020.1736086 Au, R. K. C., & Tang, A. K. M. (2025). The attentional boost effect: Current landscape and future directions. Cognitive Processing . https://doi.org/10.1007/s10339-025-01266-9 Becker, S. I. (2014). Guidance of attention by feature relationships: The end of the road for feature map theories? In M. Horsley, M. Eliot, B. A. Knight, & R. Reilly (Eds.), Current trends in eye tracking research (pp. 37–49). Springer. https://doi.org/10.1007/978-3-319-02868-2_3 Beller, H. K. (1971). Priming: Effects of advance information on matching. 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Journal of Experimental Psychology: Human Perception and Performance , 1 (4), 303–322. https://doi.org/10.1037/0096-1523.1.4.303 Saraulli, D., Mulligan, N. W., Saraulli, S., & Spataro, P. (2023). Exploring the roles of distinctiveness and performance anticipation in the attentional boost effect. Memory (Hove, England) , 31 (10), 1282–1294. https://doi.org/10.1080/09658211.2023.2260147 Sisk, C. A., & Jiang, Y. V. (2020). The yellow light: Predictability enhances background processing during behaviorally relevant events. Journal of Experimental Psychology: Learning Memory and Cognition , 46 (9), 1645–1658. https://doi.org/10.1037/xlm0000838 Smith, S. A., & Mulligan, N. W. (2018). Distinctiveness and the attentional boost effect. Journal of Experimental Psychology: Learning Memory and Cognition , 44 (9), 1464–1473. https://doi.org/10.1037/xlm0000531 Spataro, P., Mulligan, N. W., & Rossi-Arnaud, C. (2013). Divided attention can enhance memory encoding: The attentional boost effect in implicit memory. Journal of Experimental Psychology: Learning Memory and Cognition , 39 (4), 1223–1231. https://doi.org/10.1037/a0030907 Spataro, P., Mulligan, N. W., & Rossi-Arnaud, C. (2015). Limits to the attentional boost effect: The moderating influence of orthographic distinctiveness. Psychonomic Bulletin and Review , 22 (4), 987–992. https://doi.org/10.3758/s13423-014-0767-2 Swallow, K. M., & Atir, S. (2019). The role of value in the attentional boost effect. Quarterly Journal of Experimental Psychology , 72 (3), 523–542. https://doi.org/10.1177/1747021818760791 Swallow, K. M., & Jiang, Y. V. (2010). The attentional boost effect: Transient increases in attention to one task enhance performance in a second task. Cognition , 115 (1), 118–132. https://doi.org/10.1016/j.cognition.2009.12.003 Swallow, K. M., & Jiang, Y. V. (2013). Attentional load and attentional boost: A review of data and theory. Frontiers in Psychology , 4 (274), 1–13. https://doi.org/10.3389/fpsyg.2013.00274 Tulving, E., Schacter, D. L., & Stark, H. A. (1982). Priming effects in word-fragment completion are independent of recognition memory. Journal of Experimental Psychology: Learning Memory and Cognition , 8 (4), 336–342. https://doi.org/10.1037/0278-7393.8.4.336 Westerberg, J. A., & Schall, J. D. (2021). Neural mechanism of priming in visual search. Attention Perception and Psychophysics , 83 (2), 587–602. https://doi.org/10.3758/s13414-020-02118-8 Zheng, S., Meng, Y., & Lin, G. (2021). The attentional boost effect with semantic information detection tasks. Quarterly Journal of Experimental Psychology , 74 (3), 510–522. https://doi.org/10.1177/1747021820969037 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 10 Jan, 2026 Read the published version in Psychological Research → Version 1 posted Editorial decision: Revision requested 01 Oct, 2025 Reviews received at journal 21 Sep, 2025 Reviews received at journal 12 Sep, 2025 Reviewers agreed at journal 14 Aug, 2025 Reviewers agreed at journal 13 Aug, 2025 Reviewers agreed at journal 12 Aug, 2025 Reviewers invited by journal 12 Aug, 2025 Editor assigned by journal 12 Aug, 2025 Submission checks completed at journal 11 Aug, 2025 First submitted to journal 11 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7343715","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":500681701,"identity":"ede5b78f-baa5-4cf2-9599-452b998756d8","order_by":0,"name":"Ricky K. C. Au","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArklEQVRIiWNgGAWjYHACxscMB8AMAwbGhgSitDAbk6yFTZo0LebtZ8yqC85sS2xgb94mwbgjjbAWmTM5Zrdn3Lid2MBzrEyC8UwOYS0SDEAtPB+AWiRyzCQY2yqI0ML/xqwYrEX+DbFagIYz84AcJsED0kKMwySeFUvznLlt3MaTVmyR2EaE9yX4kzd+5jl2W7af/fDGGx/bkglrgQM2EJFAgoZRMApGwSgYBXgAAJp5N7bY1tQeAAAAAElFTkSuQmCC","orcid":"","institution":"Hong Kong Metropolitan University","correspondingAuthor":true,"prefix":"","firstName":"Ricky","middleName":"K. C.","lastName":"Au","suffix":""},{"id":500681702,"identity":"c238c22f-9deb-4a98-9cd4-47bc77d6c248","order_by":1,"name":"Alvin K. M. Tang","email":"","orcid":"","institution":"Hong Kong Metropolitan University","correspondingAuthor":false,"prefix":"","firstName":"Alvin","middleName":"K. M.","lastName":"Tang","suffix":""}],"badges":[],"createdAt":"2025-08-11 07:53:45","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7343715/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7343715/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00426-025-02233-x","type":"published","date":"2026-01-10T15:58:52+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":89463660,"identity":"9e651e06-6f95-4fe1-85c8-58e4268fd052","added_by":"auto","created_at":"2025-08-20 08:14:24","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":147893,"visible":true,"origin":"","legend":"\u003cp\u003eThe progression of events during the encoding phase of the congruent colour (i.e., red) priming condition. The procedure was identical in the incongruent, and control priming conditions, except that the predominant colour of the priming images were green and yellow respectively.\u003c/p\u003e","description":"","filename":"Picture1.png","url":"https://assets-eu.researchsquare.com/files/rs-7343715/v1/518017f5af2e33c06dda0f95.png"},{"id":89463656,"identity":"ea2ee94e-88f1-4110-b04a-a9a02200092f","added_by":"auto","created_at":"2025-08-20 08:14:24","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":27312,"visible":true,"origin":"","legend":"\u003cp\u003eThe recognition performance and strength of ABE across the three colour priming conditions. (A) Recognition performance is represented by corrected hit rates (HR) for old items, separately for the two item categories: items encoded with a correctly detected target signal (Corrected HR\u003csub\u003eOld_Target\u003c/sub\u003e) and items encoded with correctly ignored distractor signals (Corrected HR\u003csub\u003eOld_Distractor\u003c/sub\u003e) during the encoding phase; (B) The strength of ABE (computed as ABE = Corrected HR\u003csub\u003eOld_Target\u003c/sub\u003e – Corrected HR\u003csub\u003eOld_Distractor\u003c/sub\u003e) is displayed for each priming condition. As shown in the chart, ABE strength was the highest in the red (congruent) priming condition, moderate in the yellow (control) condition, and the lowest in the green (incongruent) condition, indicating that congruent-colour priming enhanced memory performance more effectively than neutral or incongruent priming.\u003c/p\u003e","description":"","filename":"Picture2.png","url":"https://assets-eu.researchsquare.com/files/rs-7343715/v1/4e5c59a5f6d7cbdc3751f8f4.png"},{"id":100069376,"identity":"35b11b27-dadc-4c46-a7a3-91c5afbef55d","added_by":"auto","created_at":"2026-01-12 16:13:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":841451,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7343715/v1/a29e124d-b21e-4711-9969-09d34003ec8d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Colour priming modulates the attentional boost effect","fulltext":[{"header":"Introduction","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003eThe attentional boost effect: an unexpected phenomenon of memory enhancement under dual-task conditions\u003c/h2\u003e\u003cp\u003eDaily activities often necessitate the execution of multiple tasks concurrently, such as when navigating a route during driving. While extensive research on attention has demonstrated that devoting more attention to one task typically diminishes the performance of the other, a growing body of research findings has discovered that the performance of a secondary task performance can be enhanced under dual-task conditions. Swallow and Jiang (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) were among the earliest groups of researchers to document this counterintuitive phenomenon in research on attention and memory. They designed a dual-task paradigm which consisted of an encoding phase followed by a recognition phase. During the encoding phase, participants viewed a series of scene images, each superimposed with a coloured square (in white or black) at the centre of the screen. They were instructed to detect and respond to target-coloured (white) squares via button pressing, while simultaneously memorizing the scene images in the background. Subsequent recognition task indicated better accuracy on recognizing scenes previously paired with the target-coloured squares. This memory enhancement phenomenon was termed the \u0026ldquo;attentional boost effect\u0026rdquo; (ABE), suggesting that the target detection initiated transient attentional enhancement, which in turn facilitated the encoding of the concurrently presented visual information.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eTheoretical account for the ABE\u003c/h2\u003e\u003cp\u003eEarly researchers proposed the temporal selection theory in the \u0026ldquo;Dual-Task Interaction\u0026rdquo; model to account for the ABE (Swallow \u0026amp; Jiang, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), which attempts to explain the effect by proposing that the perceptual processing of the background item would be enhanced when the item is presented at a moment that is behaviourally relevant to the presentation of the target (Swallow \u0026amp; Atir, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Subsequent research pointed to a different perspective and introduced the early perceptual enhancement hypothesis as a theoretical framework for the ABE, which proposes that enhanced visual processing is elicited when a target stimulus appears concurrently with a visually encoded item (Spataro et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Swallow and Jiang (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) elaborated upon this view, proposing that target detection may facilitate perceptual processing in a modality-general manner rather than being limited solely to the visual domain. Empirical support for this hypothesis has been obtained through various experimental paradigms. For instance, Spataro et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) reported a robust ABE in lexical decision and word-fragment completion tasks (i.e., perceptual implicit tasks), while no significant effect was observed in tasks such as semantic classification (i.e., conceptual implicit tasks). However, Mulligan et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) challenged the perceptual encoding hypothesis by highlighting its limitation to account for the enhancement of non-perceptual word properties such as lexical, semantic, and phonological attributes. By employing experiments that utilized multiple modalities and incorporated free recall tasks, they observed a significant ABE irrespective of modalities, suggesting that perceptual encoding cannot fully explain the underlying mechanisms for the ABE. Consequently, they proposed the early-phase-elevated-attention hypothesis, which argued that robustness of the ABE across brief encoding intervals implies a more generalized enhancement process beyond strictly perceptual operations.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eThe underexplored role of targets in the ABE\u003c/h3\u003e\n\u003cp\u003eNumerous empirical studies have substantiated the generality of the ABE across both visual and auditory modalities, encompassing visual and verbal stimuli, various memory systems, and diverse target detection paradigms. Spataro et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) were the first to examine the ABE by replacing pictorial stimuli with verbal stimuli and revealed that explicit memory enhancement for target-paired words was comparable to that observed for images. In a subsequent study, Mulligan et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) manipulated word frequency and employed both visual and auditory recognition tasks, demonstrating that ABE magnitude was greater for high-frequency words than for low-frequency ones. This finding implies that memory benefits occurring during the early phase of processing may diminish the memory enhancement typically associated with the ABE. Further research by Spataro et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) investigating orthographic distinctiveness reported that the ABE occurred only for low-frequency words with common orthographic features but not for those with rare features, thus supporting the view proposed by Mulligan et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Extending from these findings, Smith and Mulligan (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) explored the influence of primary distinctiveness by employing the isolation paradigm (i.e., identifying a stimulus with a salient feature among a list of stimuli that share a common feature). Their results demonstrated that primary distinctiveness elicited significant ABE under divided attention conditions and suggested that this form of distinctiveness originates from the retrieval phase, contributing an elaboration on earlier theoretical frameworks.\u003c/p\u003e\u003cp\u003eRecent research on the ABE has increasingly shifted the focus toward the characteristics of target signals. Au and Cheung (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) explored the physical attributes of the targets, demonstrating that both frequency and colour salience can significantly modulate the ABE magnitude. Meanwhile, other researchers have examined the role of target predictability. For instance, Sisk and Jiang (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) reported a robust ABE when the digit \u0026lsquo;0\u0026rsquo; served as a predictable target, which was facilitated by the preceding presentation of a countdown sequence (i.e., from \u0026lsquo;3\u0026rsquo; to \u0026lsquo;1\u0026rsquo;). Expanding on this, Pan et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) investigated the temporal interval of target predictability and found that the ABE was evident under short (\u0026lsquo;1\u0026rsquo; to \u0026lsquo;0\u0026rsquo;) and medium (\u0026lsquo;3\u0026rsquo; to \u0026lsquo;0\u0026rsquo;) predictive durations, but not under extended ones (\u0026lsquo;7\u0026rsquo; to \u0026lsquo;0\u0026rsquo;). However, the influence of predictability on the ABE remains uncertain. Saraulli et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) reported inconsistent results by employing a design where five consecutive target signals were followed by five distractors. Their findings indicated reduced recognition accuracy for words paired with both targets and distractors compared to those observed in conventional ABE paradigms. Research examining the semantic nature of target signals has further enriched the theories on attentional boost mechanisms. Zheng et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) manipulated the semantic level of target numbers to assess its impact on ABE magnitude and observed a significant effect that appeared independent of the semantic load. All together, these studies revealed multiple dimensions of target signal processing in the ABE paradigm. However, further empirical investigation is essential to achieve a more comprehensive understanding of the underlying mechanisms of the effect (for an updated review, see Au \u0026amp; Tang, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In attention research, Westerberg and Schall (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) reviewed evidence demonstrating that priming modulates selective attention during visual search tasks by facilitating the selection of previously encountered features. Given that the ABE reflects memory facilitation driven by transient increases in attentional engagement, priming may offer a valuable perspective for exploring the underlying mechanisms that contribute to the ABE.\u003c/p\u003e\n\u003ch3\u003eAttention and priming\u003c/h3\u003e\n\u003cp\u003eIn cognitive psychology, priming represents an implicit learning process, which denotes the influence of prior exposure to a stimulus on the perception or reaction towards a subsequent stimulus, which occurs without awareness (Tulving et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1982\u003c/span\u003e). Posner and Snyder (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1975\u003c/span\u003e) conceptualized priming as the anticipatory activation of a target\u0026rsquo;s representation. Experimental evidence suggested that such cues can assist in predicting target attributes or spatial position, leading to an enhancement in visual search efficiency (Beller, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1971\u003c/span\u003e; Eriksen \u0026amp; Hoffman, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1972\u003c/span\u003e). Previous research has extensively examined the interaction between attentional processes and priming. Blough (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1989\u003c/span\u003e) investigated the influence of two types of priming on attention by employing preceding cues prior to each trial. The findings revealed that both reaction time and accuracy significantly improved when predictive cues were presented, in contrast to non-predictive cues. Blough (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1989\u003c/span\u003e) also observed that presenting non-prime targets following an informative prime impaired target detection performance. However, this impairment was diminished when targets were displayed without distractors. Altogether, these findings suggested that priming mechanisms may function similarly to the attentional processes in divided attention, as both are governed by the constraints of limited cognitive capacity. The relationship between priming and divided attention has also attracted the interest of researchers. While certain studies have reported that priming effects remained stable under conditions of divided attention (e.g., Parkin et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Parkin \u0026amp; Russo, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1990\u003c/span\u003e), others have reported evidence suggesting that divided attention can reduce priming efficacy (e.g., Eich, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Mulligan \u0026amp; Hartman, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1996\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eObjectives and rationale of the present study\u003c/h3\u003e\n\u003cp\u003eIn ABE research, although substantial efforts have been focused on exploring the influence of various attributes of the to-be-encoded stimuli, procedures and population, a notable gap persists regarding the contribution of the target signal that initiates the attentional capture in the dual-task paradigm. To address this gap, the present study investigated the effects of \u0026lsquo;passive\u0026rsquo; attentional engagement through implicit perceptual learning on the resultant ABE. The present experiment extended the previous studies on investigating the target signals and examined how priming could affect the passive attentional capture, consequently leading to changes in the strength of the resultant ABE.\u003c/p\u003e\u003cp\u003eTraditionally, the ABE paradigm is structured around an encoding-recognition design in which participants engage in a dual-task during encoding. Specifically, the encoding phase requires participants to perform a primary task involving the detection of coloured target signals, while concurrently performing a secondary task of encoding the words presented in the background (e.g., Au \u0026amp; Cheung, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). To investigate the potential influence of priming on the passive attentional capture process and its resultant impact on the strength of ABE, the present experiment introduced a priming phase prior to the encoding phase. In the priming phase, participants were exposed to a set of images characterized by a dominant colour that was either congruent, incongruent, or neutral relative to the colour of the target signals that would appear in the encoding phase. Following priming, participants were instructed to maximize their accuracy in detecting the red-coloured target signals (and ignoring the green-coloured distractor signals) while simultaneously encoding the words which appeared in the background. Upon completion of the encoding phase, participants proceeded to the recognition phase in which memory performance for the previously presented words was assessed. The strength of ABE was evaluated by comparing the accuracy of memory for words previously paired with the target and distractor signals. Previous findings have suggested implicit learning may facilitate automatic attentional capture by salient stimuli (e.g., Luck et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Thus, we anticipate the congruent-colour priming procedure in the present experiment would reinforce the target detection process, leading to a greater attentional capture and enhancing the encoding of the background words (i.e., a stronger ABE). Therefore, the first hypothesis for the present experiment was that participants\u0026rsquo; corrected hit rate for the words in the recognition phase would be higher towards items paired with the target signal in the colour congruent condition, compared to the incongruent and control conditions. The second hypothesis was that the strength of ABE would be greater in the colour congruent condition than in the incongruent and control conditions.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eParticipants\u003c/h2\u003e\u003cp\u003eA total of sixty-three healthy adult participants (mean age\u0026thinsp;=\u0026thinsp;20.25 years, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.98 years) were recruited for the present experiment, all possessing normal or corrected-to-normal vision and intact cognitive functioning. Individuals who had any medical conditions potentially affecting cognitive performance were systematically excluded. Before the experiment, participants were shown a red (RGB: 255, 0, 0) target circle alongside a green (RGB: 0, 255, 0) distractor circle on a computer screen with no limit in presentation duration to check their ability to discriminate the two colours. All participants successfully differentiated the colours of the target and distractor signals before proceeding with the main task.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eApparatus and materials\u003c/h3\u003e\n\u003cp\u003eVisual stimulus presentation and participant response collection were managed through a customized computer program developed using MATLAB R2022a (MathWorks, MA), incorporating the Psychophysics Toolbox Version 3.0.18 extension (Brainard, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Kleiner et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Pelli, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). The program was executed on a desktop workstation running the Windows 10 operating system and interfaced with a 24-inch LCD monitor. The monitor utilized in this study had display dimensions of 52.704 cm in width and 29.646 cm in height, with a screen resolution of 1920 \u0026times; 1080 pixels and a refresh rate of 60 Hz.\u003c/p\u003e\u003cp\u003eFor preparing the images to be used in the priming phase, a total of 60 visual stimuli were selected from the Bank of Standardized Stimuli (BOSS; Brodeur et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), based on their perceptual and conceptual relevance to designated colour conditions of this experiment (e.g., tomatoes for the red condition, plants for the green condition, and the moon for the yellow condition). To enhance the consistency of colour among the images under the same colour condition, all images were modified to closely match the corresponding colour values at standardized RGB parameters: red (RGB: 255, 0, 0), green (RGB: 0, 255, 0), and yellow (RGB: 255, 255, 0). These images were presented during the priming phase in the three experimental blocks, each corresponding to a distinct colour condition. Specifically, 20 images were presented in the congruent (red) condition, 20 in the incongruent (green) condition, and 20 in the control (yellow) condition.\u003c/p\u003e\u003cp\u003eThe words to be memorised by the participants during the encoding phase were selected from the frequency dictionary of contemporary American English (Davies \u0026amp; Gardner, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) based on the following inclusion criteria: (i) the word must be a noun, (ii) consists of six to eight letters, and (iii) ranks within the top 5000 most frequently used words in daily communication. These criteria were employed to ensure the words used in the experiment would be familiar and cognitively accessible to participants. A total of 270 words were selected to be used in the experiment, with 90 items for each of the three blocks. Each block included 60 old items presented during the encoding phase and 30 new items introduced solely during the recognition phase. To minimize the potential influence of the priming procedure on lexical retrieval during the recognition phase, all selected words were carefully chosen to ensure they were not semantically or associatively related to the primed colour conditions (red, green, or yellow).\u003c/p\u003e\n\u003ch3\u003eDesign and procedure\u003c/h3\u003e\n\u003cp\u003eThe experiment was conducted in a quiet room inside the laboratory of the host university. Participants were seated at a standardized viewing distance of 62 cm from the monitor. The study comprised three distinct experimental blocks, each containing a priming phase, an encoding phase, an arithmetic task, and a recognition phase. The presentation order of the blocks was counterbalanced among the participants to minimise potential order effects. Before the start of experiment, participants were informed of their rights and compensation associated with participation. Written informed consent was obtained to document their voluntary participation. Participants also completed a practice session to ensure adequate understanding of all procedures.\u003c/p\u003e\u003cp\u003eAt the beginning of each experimental block, participants were presented with a series of 20 object images of the same dominant colour during the priming phase. This was designed to trigger a colour association and no response was required in this phase. In the congruent condition block, the images predominantly featured the red colour, which corresponded to the colour of the target signal to be displayed in the subsequent encoding phase. Example stimuli included images of tomato, no-entry sign, fire hydrant, and strawberry. In the incongruent condition, all images predominantly featured the green colour, aligning with the colour of the distractor signal. Sample stimuli included images of cabbage, clover, cucumber, and toy dinosaur. The control condition included 20 images associated with the yellow colour, such as banana, moon, lemon, and caution sign. All images were standardized to the dimension of 13.725 cm \u0026times; 13.725 cm and were displayed centrally on the monitor for 2000 ms each.\u003c/p\u003e\u003cp\u003eFollowing the priming phase, the encoding phase then began with presentation of the task instructions, and the participant initiated the phase by pressing the spacebar. During this phase, participants were instructed to memorize a total of 60 English words (i.e., the old items described in the Apparatus and materials section), all presented in Arial font. Among these stimuli, 30 words were accompanied by a red target signal and were designated as \u0026lsquo;Old_Target\u0026rsquo; items, while the remaining 30 were paired with a green distractor signal and were designated as \u0026lsquo;Old_Distractor\u0026rsquo; items. Each trial involved the presentation of a single word centrally displayed on the screen inside a hollow circle (diameter\u0026thinsp;=\u0026thinsp;10.16 cm; border\u0026thinsp;=\u0026thinsp;1.65 cm). The hollow circle served as the signal for detection during the dual-task encoding phase (red circle as the target and green circle as the distractor). The target and distractor signals (with the respective Old_Target and Old_Distractor words) were randomly presented across trials. Consistent with the methodology described in Au and Cheung (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), the hollow circle functioned as a peripheral signal surrounding the word stimulus to maintain visual clarity and avoid interference with encoding the word.\u003c/p\u003e\u003cp\u003eIn the encoding phase, each trial began with a white fixation cross (length of the line\u0026thinsp;=\u0026thinsp;1.098 cm; width\u0026thinsp;=\u0026thinsp;0.082 cm) presented at the centre of the black screen for 1000 ms. Subsequently, the target word (in white) was displayed concurrently with a coloured hollow circle signal surrounding it. The signal lasted for 50 ms, while the word remained visible for an additional 350 ms (total duration for the word: 400 ms). A black blank screen then followed for another 500 ms. Participants were instructed to respond to the signal quickly and accurately by pressing the spacebar when a red target signal appeared, and to withhold their response when a green distractor signal appeared. Responses were allowed at any point during the period between the disappearance of the signal and the end of the blank interval. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the flow of events during the encoding phase in the congruent priming block. In total, the encoding phase comprised 60 trials, corresponding to 2 signal colours \u0026times; 30 words.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e Upon completion of the encoding phase, participants engaged in a 60-second arithmetic task consisting of mental multiplication problems involving two-digit numbers. Each problem was presented individually on the screen one after one. This task served to disrupt working memory and promote reliance on retrieval from long-term memory during the subsequent recognition phase. Participants verbally provided answers to the arithmetic problems, and the responses were not recorded.\u003c/p\u003e\u003cp\u003eIn each trial of the recognition phase, a single word stimulus (in white) was presented at the centre of the black screen. The words presented in the recognition phase consisted of either previously encoded words (i.e., those presented as Old_Targets or Old_Distractors in the encoding phase) or new words that had not been displayed in the encoding phase. Participants were instructed to make an old/new judgment by pressing the right arrow key if they recognized the presented word from the encoding phase or the left arrow key if the word appeared to be new. The recognition phase comprised a total of 60 trials, which included 15 \u0026lsquo;Old_Target\u0026rsquo; items, 15 \u0026lsquo;Old_Distractor\u0026rsquo; items, and 30 new items. The 15 Old_Target and 15 Old_Distractor items were randomly sampled from the original pool of 30 words presented with the red targets and the 30 words presented with the green distractors during the encoding phase. Upon completion of the recognition phase, participants were given a three-minute rest period before proceeding to the next block of colour priming condition until they complete all the three colour blocks.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eData analyses were performed using IBM SPSS 29.0 (IBM Corporation, New York, USA). For each of the three colour blocks, the performance of each participant during the encoding phase was assessed using hit rate (HR; the percentage of correctly identifying the target signals), false alarm rate (FA; the percentage of incorrectly identifying distractor signals as targets), and mean reaction time (RT) of the detection responses. Across all conditions, participants exhibited consistently high HRs and low FAs (see Table 1), indicating high sensitivity to the target stimuli and effective attentional engagement throughout the encoding task.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e The hit rates for the correct detection of target signals (HRs), false alarms for the incorrect detection of distractor signals (FAs), and the respective reaction time (RTs) in the encoding phase of the experiment.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 346px;\"\u003e\n \u003cp\u003e\u003cem\u003eColour condition in the priming phase\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cem\u003eRed\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cem\u003eYellow\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cem\u003eGreen\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cem\u003eAccuracy (%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e\u003cem\u003eHits (HR)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e99.84 (0.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e99.52 (1.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e99.52 (2.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e\u003cem\u003eFalse alarms (FA)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e4.23 (2.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e4.12 (3.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e3.94 (1.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cem\u003eRT (ms)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e\u003cem\u003eHits\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e512.84 (78.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e520.62 (77.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e526.17 (74.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e\u003cem\u003eFalse alarms\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e575.11 (170.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e523.92 (187.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e544.98 (171.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eRecognition performance was evaluated by computing hit rates (HR) and false alarm rates (FA) in identifying the words presented in the recognition phase across conditions. HR was computed as the proportion of trials in which a participant correctly identified old items, i.e., responses of pressing the right-arrow key when seeing Old_Target or Old_Distractor words. FA was calculated as the proportion of incorrect identifications, i.e., pressing the right-arrow key in response to new items. To ensure the strength of ABE was accurately assessed, analyses of data from the recognition phase were limited to data which met specific criteria as explained in the following. ABE is theorized to be elicited only when the target signal is successfully detected during the encoding phase, which leads to an enhanced memory for concurrently presented stimuli. In contrast, trials in which participants failed to detect the target signal or mistakenly responded to a distractor signal are unlikely to produce the ABE. Therefore, trials with incorrectly omitted target detection and those with incorrect detection of distractors were excluded. Consequently, \u0026lsquo;corrected hit rates\u0026rsquo; for the recognition data were calculated to adjust for response bias: Corrected HR\u003csub\u003eOld_Target\u003c/sub\u003e = HR\u003csub\u003eOld_Target\u003c/sub\u003e \u0026ndash; FA; Corrected HR\u003csub\u003eOld_Distractor\u003c/sub\u003e = HR\u003csub\u003eOld_Distractor\u003c/sub\u003e \u0026ndash; FA (see Au \u0026amp; Cheung, 2020 for more details on the rationale). Summary statistics including raw HRs, FAs, corrected HRs, and RTs in the recognition phase for each condition are presented in Table 2.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eThe data of the recognition phase, including the raw hit rates (HR) and false alarm rates (FA), corrected HRs for old items, and reaction times (RTs) for item recognition across the three colour priming conditions. The reported counts reflect the number of trials included in the analysis after excluding trials that involved words associated with incorrectly omitted target signals or incorrectly recognized distractor signals during the encoding phase.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cem\u003eColour condition in the priming phase\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eRed\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cem\u003eYellow\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eGreen\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cem\u003eRaw rates (%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eHR\u003csub\u003eOld_Target\u003c/sub\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e72.98 (16.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e70.58 (17.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e63.77 (17.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eHR\u003csub\u003eOld_Distractor\u003c/sub\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e59.89 (18.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e62.30 (18.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e60.97 (21.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eFA\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e22.96 (14.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e25.93 (15.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e19.05 (14.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cem\u003eCorrected HR (%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eCorrected HR\u003csub\u003eOld_Target\u003c/sub\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e50.02 (17.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e44.66 (17.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e44.72 (19.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eCorrected HR\u003csub\u003eOld_Distractor\u003c/sub\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e36.93 (21.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e36.38 (18.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e41.92 (24.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cem\u003eRT (ms)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eOld items (target)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e867.93 (176.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e868.61 (150.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e884.03 (137.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eOld items (distractor)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e899.03 (194.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e880.98 (162.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e878.09 (144.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eNew items\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e943.45 (222.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e920.42 (227.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e892.53 (151.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cem\u003eCount\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eOld items (target), out of 15\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e14.98 (0.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e14.94 (0.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e14.97 (0.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eOld items (distractor), out of 15\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e14.71 (0.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e14.81 (0.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e14.79 (0.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eTo examine whether the recognition performance, as measured by corrected HRs, were different across the three colour priming conditions and between the two old item types, a 3 (Colour: red, yellow, green)\u0026nbsp;\u0026times; 2 (Old Item Type: target, distractor) repeated measures ANOVA was conducted (Figure 2A shows the relevant data). The analysis revealed a significant main effect of Old Item Type [\u003cem\u003eF\u003c/em\u003e(1, 62) = 35.543, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, partial \u003cem\u003e\u0026eta;\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e = 0.364] and the Colour \u0026times; Old Item Type interaction [\u003cem\u003eF\u003c/em\u003e(2, 124) = 9.982, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, partial \u003cem\u003e\u0026eta;\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e = 0.139]. However, the main effect of Colour was not statistically significant [\u003cem\u003eF\u003c/em\u003e(2, 124) = 1.159, \u003cem\u003ep\u003c/em\u003e = 0.317, partial \u003cem\u003e\u0026eta;\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e = 0.018]. Simple main effect analysis showed that the effect of Colour was significant in both old item types of Old_Target and Old_Distractor (at \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05). Among the Old_Target item type, pairwise comparisons showed significant difference between the red vs. green and red vs. yellow priming conditions (both at \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05), but not between the green vs. yellow priming conditions (at \u003cem\u003ep\u003c/em\u003e = 0.977). Among the Old_Distractor item type, pairwise comparisons showed significant difference between the red vs. green and green vs. yellow priming conditions (both at \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05), but not between the red vs. yellow priming conditions (at \u003cem\u003ep\u003c/em\u003e = 0.838). Furthermore, simple main effect analysis for Old Item Type (i.e., comparing between the target-paired items and distractor-paired items) was significant in the red and yellow priming conditions (both at \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), but not in the green priming condition (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.120).\u003c/p\u003e\n\u003cp\u003eThe ABE strength was calculated for each colour priming condition by comparing the corrected hit rates between the two item types (i.e., ABE = Corrected HROld_Target\u0026nbsp;\u0026ndash; Corrected HROld_Distractor; Figure 2B shows the relevant data). To examine the effect of colour priming on the strength of ABE, a one-way repeated measures ANOVA was performed to compare across the three priming conditions. The analysis showed significant effect of colour priming on ABE strength [\u003cem\u003eF\u003c/em\u003e(2, 124) = 9.982,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, partial \u003cem\u003e\u0026eta;\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e = 0.139]. Pairwise comparison showed that the ABE strength differed significantly among the three colour priming conditions (all at\u0026nbsp;\u003cem\u003ep \u0026lt; 0.05).\u0026nbsp;\u003c/em\u003eIn summary, the results demonstrated that colour congruent priming led to stronger ABE than colour incongruent priming and control conditions. In addition, the colour incongruent priming condition showed weaker ABE compared to the colour congruent priming and control conditions.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present experimental findings provided empirical support for the first hypothesis. Simple main effect analysis on Colour showed that the corrected HR towards target-paired words (i.e., Old_Target items) was significantly higher in the colour congruent (red) priming condition compared to the incongruent and control conditions. In addition, simple main effect analysis on Old Item Type revealed that the corrected HR for Old_Target items was significantly higher than that for Old_Distractor items in the colour-congruent priming condition. This enhancement in memory performance may be attributed to the presentation of red-coloured object images prior to the encoding phase, which corresponded with the colour of the subsequently presented target signals. Such congruence may have facilitated perceptual processing and attentional engagement on the red target signals during target detection, leading to an enhancement of memory encoding for the associated target-paired words. A few previous studies on colour priming might be relevant to explaining our findings. For example, Marangolo et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1993\u003c/span\u003e) observed that colour cues can facilitate the subsequent recognition of target hues via a repetition priming paradigm. Through separate manipulations of colour and spatial position, Geyer and M\u0026uuml;ller (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) demonstrated that priming effects facilitate performance independently and are susceptible to top-down processing modulation. These findings suggest that colour priming induces the anticipation of subsequent colour-congruent stimuli. In the colour congruent condition of the present experiment, repeated exposure to red-coloured object images may have strengthened the efficiency of attentional focus on the red targets and the concurrently displayed words, resulting in the higher corrected HR for Old_Target items.\u003c/p\u003e\u003cp\u003eOn the other hand, the colour-incongruent priming involved the presentation of green-coloured object images that matched the colour of the distractor signals in the subsequent encoding phase. The priming phase did not affect perceptual processing of the red target signals, but rather facilitated the processing of the green distractor signals. This may have led to increased attentional allocation toward the distractor-paired words and subsequently improved the recognition performance for those items. According to the feature priming theory proposed by Maljkovic and Nakayama (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1994\u003c/span\u003e), repeated exposure to a colour facilitates attentional guidance toward subsequent presentations of that colour, thereby enhancing the encoding of concurrent stimuli and strengthening memory traces. This mechanism may account for the higher corrected HR for distractors observed in the colour-incongruent priming condition in our study. Under the colour incongruent condition, presentation of green-coloured objects induced a priming effect that might have selectively enhanced attentional allocation toward green distractor signals. This elevation in attentional engagement contributed to improved memory performance for items paired with distractors.\u003c/p\u003e\u003cp\u003eFurthermore, the control condition employed yellow-coloured object images that were perceptually unrelated to the colours of the target (red) and distractor (green) signals in the detection task. Consequently, these neutral stimuli were unlikely to influence the processing of either signal type during the encoding phase, and that the yellow priming condition could serve as a baseline reference for illustrating the effect of congruent and incongruent priming. For instance, a higher corrected HR for Old_Target items was observed under the red priming condition over the control condition, and a higher corrected HR for Old_Distractor items was observed under green priming than the control condition. This pattern of results might suggest that colour priming can modulate the memory encoding processes in a feature-specific manner, with different colours selectively enhancing attention towards distinct signal-paired items.\u003c/p\u003e\u003cp\u003eLastly, the present results supported the second hypothesis that the strength of ABE would be greater in the colour-congruent condition than in the colour-incongruent and control conditions. These patterns can be explained by attentional mechanisms described by Swallow and Jiang (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) who proposed that the ABE arises from a widened attentional gate in which detecting a target transiently enhances attentional resources for encoding concurrently presented stimuli. In line with this perspective, Becker et al. (2014) proposed that attentional gain is selectively enhanced for a chosen target colour, potentially diminishing attentional resources allocated to non-target colours. Similarly, Ramgir and Lamy (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) demonstrated that repeated exposure to a specific colour enhances attentional priority toward the colour in subsequent tasks, even when it functions as a distractor. Relating this to the present study, repeated exposure to red-coloured object images during the priming phase in the colour-congruent condition may have heightened attentional engagement with red target signals. The increased attention likely widened the attentional gate proposed by Swallow and Jiang (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), resulting in a more substantial enhancement in memory encoding. This enhanced selective attention facilitated encoding of target-paired items, resulting in a stronger ABE. In contrast, priming with green-coloured object images in the colour-incongruent condition may have shifted attentional priority toward the green distractor signals. Consequently, the encoding of distractor-paired items was enhanced and offset the memory facilitation on target-paired items, leading to a diminished overall ABE strength compared to both the congruent and control conditions.\u003c/p\u003e\u003cp\u003eThe results of the present experiment revealed two valuable insights into the ABE. One notable finding was that the corrected HR for the Old_Distractor items in the colour-incongruent priming condition was higher than that in the control condition. This suggests that colour priming can enhance memory encoding for items that are not behaviourally relevant, such as the Old_Distractors (i.e., stimuli that participants were not instructed to attend to or respond to via button press). Notably, this enhancement occurs when the priming colour differs from the colour of the instructed target, indicating that the effect of colour priming is not limited to task-relevant stimuli. More importantly, the corrected HR for the previously encoded distractor-paired items (i.e., Old Distractor items) in the colour-incongruent priming condition reached a level comparable to that for the target-paired items. The enhancement of colour priming appears to occur independently of the facilitation typically associated with target detection in the ABE. In other words, the memory benefit observed for the distractor-paired words under incongruent colour priming did not interfere with the encoding benefit toward the target-paired words conferred by detection of the red targets, which are generally linked to an increased attentional engagement. This finding implies that colour priming supports encoding process through a parallel attentional pathway, through enhancing memory without interfering with the facilitation from target detection.\u003c/p\u003e\u003cp\u003eAnother key finding was that the corrected HR for the Old_Target items in the colour-congruent priming condition was significantly higher than that in the control condition. This result indicates that colour-congruent priming can enhance the memory encoding beyond the facilitation typically provided by the ABE, suggesting that the memory facilitation conferred by target detection in the ABE could be further amplified through the presentation of a perceptually-identical feature (i.e., the colour) before the encoding phase. More specifically, when the priming colour was congruent with the colour associated with target detection, the memory enhancement towards the target-paired items typically observed in the ABE was not only preserved, but further facilitated, as evidenced by the higher corrected HR observed in the colour congruent (red) priming condition compared to the control (yellow) priming condition. This additive effect implies that congruent perceptual cues, such as colour, can interact with temporal attention mechanisms to produce a compounded benefit for memory encoding. This highlights the potential for feature-based priming to modulate attentional engagement in a way that enhances memory encoding beyond the traditional ABE paradigm.\u003c/p\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003ePotential research on the role of priming in the ABE\u003c/h2\u003e\u003cp\u003eWhile the present study provides new evidence that colour priming can influence the attentional capture in the ABE, it highlights new possibilities for examining the underlying mechanisms of this modulation. Specifically, it remains an open question whether the enhancement from priming stems primarily from perceptual features (e.g., colour congruence) or from conceptual associations embedded in the object images used during the priming procedure. To isolate the perceptual and conceptual factors, future research could employ abstract, non-conceptual stimuli such as coloured geometric shapes or spatial sequences of coloured shapes for the priming phase. Another direction involves expanding the scope of priming beyond colour. For example, spatial priming effect could be examined by presenting stimuli at specific locations on the screen to test whether position-based priming cues can affect the attentional level and modulates the ABE magnitude. These ideas may help broaden the theoretical scope of priming effects on the ABE and enhance new understanding on the influence of priming on passive attentional capture and memory encoding processes.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, using priming, this study investigated the influence of implicit learning on passive attentional capture and its impact on the ABE. The experimental results demonstrated that colour congruence between the primed stimuli and the target signals significantly modulated the magnitude of ABE. Specifically, priming with colour-congruent stimuli enhanced attentional capture and yielded the strongest ABE magnitude, while incongruent colour priming diminished the effect. These findings provide new evidence that passive attentional engagement can be shaped by implicit learning mechanisms, and that pre-exposure to colour-congruent stimuli can improve memory encoding performance under divided attention.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval: \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval to conduct this study has been obtained from the Research Ethics Committee of the authors\u0026rsquo; host university.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed consent: \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all participants in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest: \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOn behalf of all authors, the corresponding author states that there is no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability: \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data analysed in this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe work described in this paper was fully supported by a grant from the Research\u003c/p\u003e\n\u003cp\u003eGrants Council of the Hong Kong Special Administrative Region, China (UGC/FDS16/H29/23).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contribution:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRicky K. C. Au \u0026ndash; study conceptualisation, data collection and data management, statistical analyses, manuscript preparation.\u003c/p\u003e\n\u003cp\u003eAlvin K. M. Tang \u0026ndash; data collection and management, statistical analyses, manuscript preparation.\u003c/p\u003e\n\u003cp\u003eAll authors approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAu, R. K. C., \u0026amp; Cheung, C. N. (2020). The role of attention level in the attentional boost effect. \u003cem\u003eJournal of Cognitive Psychology\u003c/em\u003e, \u003cem\u003e32\u003c/em\u003e(3), 255\u0026ndash;277. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/20445911.2020.1736086\u003c/span\u003e\u003cspan address=\"10.1080/20445911.2020.1736086\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAu, R. K. 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The attentional boost effect with semantic information detection tasks. \u003cem\u003eQuarterly Journal of Experimental Psychology\u003c/em\u003e, \u003cem\u003e74\u003c/em\u003e(3), 510\u0026ndash;522. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/1747021820969037\u003c/span\u003e\u003cspan address=\"10.1177/1747021820969037\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"psychological-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prpf","sideBox":"Learn more about [Psychological Research](http://link.springer.com/journal/426)","snPcode":"426","submissionUrl":"https://submission.nature.com/new-submission/426/3","title":"Psychological Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Attentional boost effect, Dual-task, Memory encoding, Passive attentional capture, Priming","lastPublishedDoi":"10.21203/rs.3.rs-7343715/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7343715/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe attentional boost effect (ABE) refers to the enhancement of memory encoding during a dual-task. To investigate the under-researched influence of target signal properties in the ABE, this study examined whether implicit colour priming influences passive attentional capture and modulates the magnitude of the ABE. Participants completed an encoding-recognition task across three priming conditions (red, green, and yellow). Each condition comprised four parts: a priming phase, an encoding phase, a wash-out period, and a recognition phase. During the priming phase, participants passively viewed a series of images predominantly associated with a specific colour. In the encoding phase, participants engaged in a dual-task requiring detection of red target signals (while ignoring green distractor signals) and simultaneous memorization of background words. Recognition performance was then assessed through an old-new classification task. Results revealed significant differences in ABE magnitude across the three colour conditions. Red priming produced the strongest memory enhancement, suggesting that congruent colour priming facilitated attentional capture. In contrast, green priming diminished the effect, which is potentially caused by interference linked to attentional shift toward the distractors. The ABE observed under the yellow control condition fell between those of the red and green conditions, establishing a valid baseline for assessing the colour-priming influences. These findings indicate that colour priming could strengthen passive attentional engagement and enhance memory encoding in divided attention conditions, highlighting the importance of feature congruence in modulating the ABE.\u003c/p\u003e","manuscriptTitle":"Colour priming modulates the attentional boost effect","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-20 08:14:20","doi":"10.21203/rs.3.rs-7343715/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-01T14:39:37+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-21T15:15:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-12T16:22:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"112107472374127678473599360438666970368","date":"2025-08-14T17:38:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"312326995167462925443699670782672210123","date":"2025-08-13T09:36:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"204660489703367477994653751861717674590","date":"2025-08-12T14:18:54+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-12T13:50:31+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-12T11:11:31+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-12T01:03:15+00:00","index":"","fulltext":""},{"type":"submitted","content":"Psychological Research","date":"2025-08-11T07:45:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"psychological-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prpf","sideBox":"Learn more about [Psychological Research](http://link.springer.com/journal/426)","snPcode":"426","submissionUrl":"https://submission.nature.com/new-submission/426/3","title":"Psychological Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"b2f2f60e-9763-480f-98af-0ef9b611cf2a","owner":[],"postedDate":"August 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-12T16:05:06+00:00","versionOfRecord":{"articleIdentity":"rs-7343715","link":"https://doi.org/10.1007/s00426-025-02233-x","journal":{"identity":"psychological-research","isVorOnly":false,"title":"Psychological Research"},"publishedOn":"2026-01-10 15:58:52","publishedOnDateReadable":"January 10th, 2026"},"versionCreatedAt":"2025-08-20 08:14:20","video":"","vorDoi":"10.1007/s00426-025-02233-x","vorDoiUrl":"https://doi.org/10.1007/s00426-025-02233-x","workflowStages":[]},"version":"v1","identity":"rs-7343715","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7343715","identity":"rs-7343715","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}