Individuals perform motor tasks with differing levels of attention. Traditional views considered attention as a passive spotlight or gatekeeper, acting prior to perceptual processing to merely filter out undesirable inputs in favor of others (i.e., it does not affect cognitive control of perception) [1,2,3,4,5,6]. In contrast, attention currently is viewed as a dynamic mechanism that actively modulates cognitive control of perceptual computations in almost all stages or levels of processing [7,8,9,10], see also [11,12,13,14]. At the neural level, studies suggest that attention not only modulates activity of sensory neurons in various ways [15, 16], but contributes to ’hypothesis testing’ by making predictions about sensory information that should be encoded by lower neuronal levels [13, 17]. Behavioral studies also show that attention modulates perceptual and motor aspects of human behavior such as speed, reaction time, and performance accuracy . A large number of attentional focus studies in the field of sport science and rehabilitation show that an external focus (i.e., focusing on the environmental task-relevant information outside of the performer’s body) enhances performance compared to an internal focus (i.e., focusing on the body or its movements) in a variety of motor tasks [19, 20]. For instance, an external focus improved performance accuracy and reduced pre-movement time relative to an internal focus during an isometric force production task . These findings therefore may provide support for the role of attention in cognitive control of perception and its impact on motor outcomes. The constrained action hypothesis, as the most widely accepted theoretical explanation for external attentional focus effects, suggests that, unlike an internal focus that elicits controlled cognitive processing and impedes performance, an external focus enhances motor skill performance by invoking automatic processing that is characterized by faster and more reflexive adjustments .
Aside from attentional focus, mental imagery is another cognitive mechanism that may affect individuals’ perceptual-motor performance. Given the mental imagery definition as “representations … of sensory information without a direct external stimulus”  or perceptual processing, in the absence of immediate sensory input from a relevant sense-modality [24, 25], some researchers suggest that mental imagery has a critical role in cognitive control of perception . Studies show that pre-cuing effects (e.g., increased visual search time) occur in the absence of any physical stimuli (i.e., it is not triggered by corresponding sensory stimulation) and it has been suggested that perception is indeed cognitively controlled by means of mental imagery rather than attention . In other words, the argument is that individuals’ ability in creating mental images is the main modulator of perception. In the literature, these initial mental images have been considered as a type of attention known as preparatory attention (also known as attentional templet, attentional set, or search image) [26, 27]. Preparatory attention seems to be a phase in perception in which mental images of a given object are created in the sensory cortices (e.g., visual cortex) prior to presence of physical stimuli . Furthermore, these initial mental images have identical, but reverse, perceptual processing path than sensory (e.g., visual) perception . That is, while sensory perception involves a bottom-up neural network path from visual to frontal cortex, mental imagery involves a top-down direction from the frontal cortex to sensory areas (e.g., visual cortex). Therefore, attention and mental imagery, although mainly studied separately in sport science and rehabilitation, are closely inter-connected factors. To this extent, recent works suggest that mental imagery should be applied to attention  as both of them involve cognitive  and perceptual processes [28, 31] and share common neuro-cognitive circuits with perception [32, 33]. Furthermore, it seems that mental imagery is dependent upon attentional resources  and conversely, mental imagery may also impact attention . Based on these findings, it seems quite reasonable to assume that mental imagery ability or individual differences in creating mental images modulates perceptual and motor aspects of performance during different attentional focus conditions. From a practical perspective, gaining more understanding in this regard would help practitioners to decide whether and how mental imagery should be applied to attentional focus strategies to further enhance perceptual and motor aspects of individuals’ performance.
A number of previous works have attempted to provide evidence regarding the modulating roles of motor imagery (MI: a type of mental imagery that is characterized by mentally imagining an action without any overt physical execution)  on motor performance and learning under different attentional focus conditions (i.e., internal versus external focus). In particular, MI modalities (i.e., kinesthetic MI: mentally ‘sensing’ proprioceptive or somatosensory aspects of movements, and visual MI: mentally ‘seeing’ different aspects related to performance such as distance and size) , and MI perspectives (i.e., internal visual imagery perspective: seeing from first-person perspective, and external visual imagery perspective: seeing from a third-person perspective)  during different attentional focus conditions have been investigated. Indeed, MI significantly modulates the effects of attentional focus during performance of different fine and gross motor tasks including trajectory tracing tasks, dart throwing, overhand ball throwing, and balance control [38,39,40,41]. Further investigations nevertheless are required for several reasons. Thus far, studies have yielded inconsistent results regarding the role of MI on motor performance and/or learning during different attentional focus conditions. In individuals with higher kinesthetic MI, an internal focus facilitated visuomotor performance (tracing a circular trajectory with a mouse-controlled cursor) and learning relative to an external focus, whereas individuals with higher visual MI benefitted from an external relative to an internal focus [38, 39, 42, 43]. Other studies however have failed to observe that kinesthetic MI facilitates performance and learning during any attentional focus condition [41, 44]. In addition, studies have mainly used relatively simple tasks including computer-based visuomotor tasks with a mouse (e.g., circle-tracing) [38, 42, 43] and dart throwing . Therefore, there is a need to understand if MI modulates attentional focus effects in novices performing inherently more complex tasks (i.e., with relatively high index of difficulty). Furthermore, most of these works have investigated MI modalities (kinesthetic, vs. visual MI) without considering if MI perspectives (internal visual MI vs. external visual MI) have potential unique contributions to outcomes. To the best of our knowledge, only one recent study in children distinguished between MI perspectives (Bahmani et al. 2021), showing that while high levels of kinesthetic MI deteriorated overhand ball throwing learning in children adopting an external focus, external visual MI dominance resulted in superior motor learning for children adopting an external focus , suggesting that MI perspectives may also differently modulate attentional focus effects on motor performance. Finally, studies have focused on performance accuracy and there is little information about how attentional focus and MI interact to affect perceptual processing and movement time. In the present study, we sought to investigate whether MI modulates perceptual and motor functions under different attentional focus conditions. To determine whether perception is cognitively controlled by MI or attentional focus, and also given the existence of some inconsistencies regarding the role of kinesthetic MI on attentional focus effects, we employed additional tasks and outcome variables to complement traditional performance indicators related to end-point accuracy. To this end, we measured performance time, aiming point stability (i.e., aiming trace speed), and performance accuracy during shooting performance of a group of young novice 10-m air-pistol shooters.
Ninety-two young adult university students (M age = 21.84 ± 2.25 years; 29 females) with normal or corrected to normal vision, and with no self-reported musculoskeletal or postural disorders voluntarily participated in the study. Of note, a few incomplete datasets were excluded from the final analyses due to general optical system failure.Footnote 1 All participants were novice (i.e., had no previous experience with the task) and naïve to the purpose of the study. The study was approved by Baghiatallah University of Medical Sciences review board (approval code: IR.BMSU.REC.1399.337).
Movement Imagery Questionnaire-3 (MIQ-3)
The MIQ-3 is a 12-item questionnaire  to measure individuals’ ability (i.e., ease or difficulty) of generating mental imagery for four movements (knee lift, jumping, arm movement, and toe touch) via kinesthetic MI, internal visual MI, and external visual MI. The MIQ-3 asks participants to physically perform each movement first, then mentally imagine each movement. Participants were asked to rate each movement on a 7-point Likert scale from 1 (very hard to see/feel) to 7 (very easy to see/feel). Therefore, the maximum sum score that one could obtain in each subscale is 28.
Apparatus and task
The participants were asked to shoot an air-pistol as accurately and as quickly as possible at an electronic target 10 m away in an indoor environment. The SCATT shooting system (SCATT Co., Russia) was used to quantify pistol shooting performance, congruent with prior work . The SCATT system records the location of shots in two-dimensional space as a function of time throughout each shooting trial. This is accomplished using multiple optical camera devices, including a barrel-mounted light emitting and sensing unit with a reflective target border enabling the position of the aiming point to be recorded. The location of each shot was recorded as the position of the aiming point on the target at the time of the trigger pull, which was detected upon dry firing via a small microphone attached to the pistol. The system is comprised of a wired optical unit fixed on the pistol barrel and connected to a PC that automatically recorded all outcome variables. For the present study, we used accuracy, performance time, and aiming trace speed as our dependent/outcome (i.e., performance) variables of interest. Accuracy was determined by the position of the aiming point on the target at the time of trigger pull – two dimensional coordinates were converted to a ‘score’ via a series of concentric circles. A shot hitting the ‘bulls-eye’ of the target scored 10.9, the maximum possible score, with depreciating scores for each subsequent surrounding circle (the lowest possible score was ‘0’ if the shot missed the target entirely). Performance time was quantified as the time from lifting the gun to initiation of the trigger pull (in ms) and aiming trace speed was defined as the speed of pistol barrel (stability of hold of weapon stability) during the last second (mm/sec) [47, 48].
Following completion of the MIQ-3, participants began the shooting task. After a short familiarization period, participants were asked to shoot at the target in three different attentional focus conditions: (1) control condition, (2) IF, and (3) EF. Participants completed their shooting performance under control (no focus instruction) conditions first, then ordering of internal and EF conditions was counterbalanced between participants. Similar to previous attentional focus studies, we issued participants the control focus condition first, followed by the counterbalancing of attentional focus conditions, to ensure one condition could be used as a stable control that was not biased by previous attentional focus instruction (i.e., eliminate order effects for baseline performance, only) [49, 50]. While order effects may have reduced control task performance or improved internal or external focus performance (i.e., less ‘practice’ time given control task always performed first), the total number of trials for the entire experiment was relatively small, thus minimizing the potential for order effects in any condition . Internal and EF instructions used in the current study were similar to previously published work on shooting performance that has demonstrated attentional focus effects . In the IF condition participants were instructed to “focus on keeping your hand steady” and in the EF condition participants were instructed to “focus on keeping the gun steady.” In addition to attentional focus instructions, participants were also informed that they needed to complete each trial as accurately and as quickly as possible after seeing an optical signal. Participants completed 10 trials in each attentional focus condition, and participants’ scores in each condition were averaged to obtain total score of each condition.
First, repeated measure analyses of variance were performed to investigate if shot accuracy was different among the attentional focus conditions. Similar analyses were done for performance time and aiming trace speed between attentional focus conditions. An alpha level of p < .05 was set a priori, and post-hoc analyses were performed using Bonferroni adjustments as appropriate. In addition, we ran simple regression analyses to investigate potential associations between each MI measure and each air-pistol shooting performance measure in different attentional focus conditions (i.e., between KMI and performance accuracy, between KMI and performance time, between KMI and aiming trace speed, between internal visual MI and performance accuracy, and so forth). Also, the association between performance time and shot accuracy, and between aiming trace speed and shot accuracy during each attentional focus condition were examined to help interpret findings. Finally, using MEMORE process macro , we ran separate simple model repeated measures analyses (see Montoya 2019) to investigate if each MIQ-3 score (i.e., global MI, internal visual MI, external visual MI, and kinesthetic MI) moderated performance during different attentional foci (i.e., during internal vs. control condition, external vs. control, and internal vs. external focus). Analyses were done for performance accuracy, performance time, and aiming trace speed that resulted in 12 separate simple model repeated measure analyses (4 MI measures: global MI, internal visual MI, external visual MI, and kinesthetic MI by 3 pair of attentional focus comparisons: internal focus vs. control, external focus vs. control, and internal focus vs. external focus). In addition to these primary analyses, we performed a secondary data analysis using motor imagery dominance to enhance reader interpretation (see Additional file 1).