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date: 22 September 2018

The Role of Mental Processes in Elite Sports Performance

Summary and Keywords

Considerable debate has arisen about whether brain activity in elite athletes is characterized by an overall quieting, or neural efficiency in brain processes, or whether elite performance is characterized by activation of two simultaneous networks. One network exercises cognitive control using increased theta activation of premotor and cingulate gyrus, whereas the second reduces alpha activation in an inhibitory network that prevents the intrusion of debilitating thoughts emanating from the temporal lobe and other areas. Also, there is controversy about how a long-duration “quiet eye” (QE) can fit within a single efficient neural system, or whether a dual system where both increased cognitive control and reduced inhibitory processes has advantages. The literature on neural efficiency, the QE, and theta cognitive control, suggest that a long-duration QE promotes both an increase in theta band activation of the medial prefrontal cortex and anterior cingulate and reduced activation and inhibition of the temporal regions during high-pressure situations when a high level of focused, cognitive control is essential.

Keywords: neural efficiency, quiet eye, vision, expertise, sport, anxiety

The Elite Athlete’s Brain in Action

Physical behavior, which is readily observed and measured, assumedly tells the whole story about exceptional attainment in sport. Consider some of the most outstanding recent achievements in sport. In basketball, Stephen Curry has broken the three-point shooting record two seasons in a row, recording percentages 30% higher than any previous player. Talk about the mechanics of his shooting style is endless, but little mention is made of the possibility he possesses a powerful ability to focus mentally before and/or as the shot is taken. He is not a tall player (by NBA standards) nor has he proven to record exceptional results on physiological or biomechanical tests. He is similar to other great athletes who were far from being the biggest, strongest, or tallest when compared to their teammates and opponents. Lionel Messi, Diego Maradonna, and Pele are three of the best soccer players in history, but they are, respectively, 5 feet 7 inches, 5 feet 5 inches, and 5 feet 8 inches in height (http://ca.complex.com/sports/2013/03/the-best-little-men-in-sports-history/pele). Similarly, Wayne Gretzky is considered one of the world’s greatest ever hockey players, but he tested at the bottom of his team in speed, aerobic capacity, strength and other physical and physiological measures of prowess.

To further an understanding of why individuals such as these are exceptional, a brief review of the visuo-motor system is provided, then research that has focused on the neural efficiency hypothesis in expert athletes is reviewed. These hypotheses state that experts possess brains that are faster and more efficient, an idea that has attracted varying levels of support (Haier et al., 1988; Neubauer & Fink, 2009). The phenomenon of the “quiet eye” (Vickers, 1996a, 1996b, 2007) is introduced in the context of the “efficiency paradox” (Mann, Wright, & Janelle, 2016). The efficiency paradox questions how a long-duration quiet eye (QE), which has been shown to reliably distinguish elite and nonelite athletes (Mann, Williams, Ward, & Janelle, 2007; Lebeau et al., 2016), can function within a brain that is characterized by reduced activation of neural structures with increasing skill levels. Evidence shows, in agreement with Mann et al., that the long-duration QE of elite athletes may be responsible for both enhanced theta activation, which leads to effective focus (Cavanagh & Frank, 2014), and concurrent reduced alpha activation, which insulates the performer from the impact of stressors, leading to superior coping mechanisms under high levels of competitive pressure.

The Visuo-Motor System

In many sports, athletes must be able to pick up critical cues from the task environment so they can be processed further by the visuo-motor system. How athletes perceive and attend to their task environments is therefore of great interest to all who want to understand the role of mental processes during sports performance. The human eye perceives spatial information with full acuity only when light falls on a small region at the back of the retina called the fovea, leading to being able to see with high acuity over a very narrow 2 to 3 degrees of visual angle (Coren, Ward, & Enns, 2003; Holmqvist et al., 2011; Liversedge, 2011). Information that falls outside of the fovea is perceived using para-foveal or peripheral/ambient vision and becomes increasingly blurred the further the image falls away from the fovea. In contrast, the ambient or peripheral system is specialized for motion perception and function, particularly under low levels of illumination. Both the foveal and ambient system are needed for the visual system to function optimally. Usually, the eyes move before the head, localizing a target on the fovea first, followed by smaller movements of the head, with the latter being less efficient, due the head being larger and having more inertia. The movement of the eyes and head to the target is normally smooth, with the processing of visual information occurring within 100 ms of the eyes stabilizing on the new location (Abrams, Meyer, & Kornblum, 1990).

The development of mobile eye trackers around the mid-1980s resulted in scientists being able to accurately record fixations, pursuit-tracking eye movements, and saccadic eye movements as the participant moved naturally in realistic environments (Henderson, 2003; Vickers, 2007; Henderson, 2017). A fixation occurs when the gaze is held stable on an object or location within 3 degrees of visual angle (or less) for 100 ms or longer. The 100-ms threshold is the minimum amount of time the brain needs to recognize or become aware of what is being viewed. Pursuit-tracking eye movements are similar to fixations, except the eyes follow a moving object, such as a ball or a person. The 100-ms threshold still applies for the same reason it is used for fixations. Saccades occur when the eyes move quickly from one fixated or tracked location to another. During a saccade, the eyes can move with angular velocities exceeding 900 degrees per second. Saccades are ballistic eye movements that bring the point of maximal visual acuity onto the fovea so that an object can be seen with clarity. During saccades, information is suppressed (Thilo, Santoro, Walsh, & Blakemore, 2004; Wessel, Reynoso, & Aron, 2013), meaning that what may be picked up en-route from one fixated location to another is not consciously perceived. Instead, fixated is maintained in memory, ensuring the perception of a stable, coherent scene. Saccadic suppression prevents us from seeing a world that is blurry and difficult to comprehend.

The Role of Mental Processes in Elite Sports PerformanceClick to view larger

Figure 1. Superior temporal gyrus (TPJ) activity is suppressed during focused attention
(A) Subjects searched a rapid serial visual presentation (RSVP) display for a target digit. The number of distracter frames containing only letters prior to the target frame containing the target was varied. The graph shows the time course of activity in dorsal regions intraparietal sulcus (IPS) and frontal eye fields (FEF) and ventral region TPJ under conditions in which the target appeared near the end of the trial. In TPJ, a deactivation to the letter distracters was followed by an activation when the digit was presented or the trial was terminated. Interestingly, the deactivation to the letters was significantly greater when the subsequent digit was detected than when it was missed. Conversely, IPS and FEF showed sustained activations during search. (B) Subjects encoded a visual display that they had to remember and then match to a probe display. During the retention interval, TPJ showed a deactivation (purple disk in the surface-rendered brain) that increased with the number of display items that had to be retained. (C) The statistical map shows regions with sustained activity as subjects searched through letter distracters in the RSVP experiment (see panel [A]), including dorsal attention regions IPS and FEF (red/orange in surface-rendered brain) but also regions in anterior insula and anterior cingulate that form a putative task-control network. These regions may send top-down signals (see arrows) to the ventral network, which showed sustained deactivations during search (blue/green in surface-rendered brain), restricting its input to task-relevant objects (Shulman et al., 2003).

(Reprinted with permission from Corbetta, M., Patel, G., & Shulman, G. L. (2008). The reorienting system of the human brain: From environment to theory of mind, Neuron, 58(3), 311.)

Once an object, person or location is registered, visual information travels through two visual systems that work in parallel called the dorsal and ventral streams (Milner & Goodale, 2007). The dorsal system projects from the occipital lobe to parietal lobe and forward to the frontal lobe, while the ventral system projects through the temporal lobes to the frontal areas. Using a combination of positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), Corbetta and colleagues (e.g., Corbetta & Shulman, 2002; Corbetta, Patel, & Shulman, 2008) defined separate functions for the two streams that are relevant to elite sports performance. They required that participants respond to a cue in which attention was covertly shifted to a location in the periphery without eye movements, as well as overtly with a shift of the gaze, as shown in Figure 1. They found that the dorsal attention network (DAN) was used to sustain spatial focus and attention on a goal-directed location, while the ventral attention system (VAN) was used to inhibit attention to new or competing information. In addition, the VAN network was responsible for switching visual attention from one location to another, while the DAN system was used to sustain attention on one location or goal, potentially blocking harmful memories and emotions that can contribute to higher levels of anxiety and lower levels of performance. Figure 1 shows the intraparietal sulcus (IPS) and frontal eye fields (FEF), anterior insula and anterior cingulate being active during goal directed, top-down control, while there was sustained deactivation of the superior temporal gyrus. Corbetta and colleagues reported that additional frontal areas were involved in sustaining attention relevant to a cue, but where in the brain this occurred was left unclear. These authors suggested that another unknown area in the frontal cortex is recruited when expertise is developed, in particular for tasks that are more complex. Cavanagh and Frank (2014) identified two frontal locations, the medial frontal cortex and cingulate gyrus, as being active during tasks that require a high degree of cognitive control.

The Neural Efficiency Hypothesis

As increasing levels of expertise are attained, there are measureable changes in neural activation. The neural efficiency hypothesis was first proposed by Haier et al. (1988), who used positron emission tomography (PET) to determine the relationship between task performance and level of neural activation during the performance of intelligence tests. Haier and colleagues found an inverse relationship between brain glucose metabolism levels and the score obtained on the intelligence test. Participants who had high intelligence scores consumed less energy than those with lower scores and performed more quickly, leading the authors to suggest that superior intelligence was due to neural circuits that performed at faster speeds and with greater efficiency.

In a somewhat similar vein, researchers in the domain of motor learning have suggested that skilled performance is defined by high levels of automaticity, minimum energy expenditure, and reduced movement times (Schmidt & Lee, 2014). These documented changes have led to a general “faster is better” approach in terms of defining optimal motor behavior, brain function, and assumptions about how athletes should be trained. For example, athletes are often told they must learn to shift their gaze rapidly and speed their thought processes and movements to the point of reducing the level of conscious control of what they are doing. However, in a comprehensive review of the neural efficiency hypothesis, Neubauer and Fink (2009) reported 29 studies in support of the hypothesis, while 18 provided mixed support, and nine had contradictory results. The reason for the contradictory results was due to researchers in certain studies placing only minimal demands on participants and using tasks that required relatively low use of cognitive resources. Neubauer and Fink (2009) concluded that “the neural efficiency phenomenon is observable mostly when individuals are confronted with tasks of (subjectively) low-to-moderate task difficulty and it is most frequently observed for frontal brain areas. . . . However, in very complex tasks more able individuals seem to invest more cortical resources resulting in positive correlations between brain usage and cognitive ability” (p. 1004). This view challenges the widespread assumption that if an athlete is able to move quickly, then his or her neural processes must also function as fast, or even faster.

The Quiet Eye

Over recent decades the search for the perceptual-cognitive characteristics underlying elite sports performance has continued. Mann et al. (2016) state, “Perhaps the most robust phenomenon in all performance-related visual search research is the nearly ubiquitous finding that experts and expert performance are consistently characterized by an earlier onset and longer quiet eye (QE)” (p. 1). The QE is a period of sustained focus that begins prior to the onset of a critical phase of a motor task (Vickers, 1996a, 1996b, 2007, 2009). Following from the seminal work of Vickers (1996a, 1996b), considerable support has emerged for the QE as found in recent meta-analyses and reviews (Mann et al., 2007; Wilson, Causer, & Vickers, 2015; Lebeau et al., 2016; Rienhoff, Tirp, Strauss, Baker, & Schorer, 2016). The QE is formally defined as the final fixation or tracking gaze that is located on a specific location or object in the task space within 3 degrees of visual angle (or less depending on the task) for a minimum of 100 ms. The onset of the QE occurs prior to a critical final movement in the task, and the offset occurs when the gaze deviates off the object or location by 3 degrees (or less) of visual angle for a minimum of 100 ms. Therefore, the QE can carry through and beyond the end of the movement. The onset of the QE in elite performers is earlier, indicating that they have found a way to see critical information sooner, thus enabling the transmission of higher quality commands to the motor system. The QE of elite performers is longer and has an optimal duration given the constraints of the task, meaning it varies in length depending on the specific motor task.

The first meta analysis was carried out by Mann and colleagues (Mann et al., 2007), who, based on data from 42 published studies involving various sports, found that experts differed from nonexperts in being able to use advance perceptual cues that contributed to improved anticipation, decision making, and response times. The expert’s differed from the nonexperts in using fewer fixations of longer duration, while the nonexpert athletes used more fixations of shorter duration. In addition to fixation frequency and duration differences, in five QE studies, the experts had a longer QE period than the nonexperts, highlighting the importance of acquiring task specific information prior to a critical movement in the task. Subsequent research has demonstrated that the specific search behavior used is task, situation, and context specific (Roca, Ford, McRobert, & Williams, 2013).

In another meta-analytic report, LeBeau et al. (2016) provide a quantitative synthesis of the literature on the QE in sports settings. Several moderators were analyzed, including the source of data, sports setting, experimental design, manipulation of anxiety/pressure, type of motor task, and QE measurement using the terms quiet eye AND sport, gaze control AND sport, gaze AND sport, and gaze behavior. In total, 127 studies were identified. The studies were divided into two categories: (a) those that did not include QE training or any intervention, but compared novices/less successful performance to experts/successful performance (Synthesis 1, 26 studies), and (b) those that presented QE training interventions (Synthesis 2, 9 studies). The results for synthesis 1 revealed a large mean effect size (𝑑 = 1.04) for the between-individual differences (expert versus nonexpert) in the QE period. This effect was larger than the moderate-to-large effect size reported by Mann et al. (2007) but was in line with previously reported expert-novice differences (Vickers, 1996a, 1996b; Janelle et al., 2000). The results for synthesis 2 revealed a large mean effect size for QET for both experts (𝑑 = 1.53) and nonexperts (𝑑 = 0.84). Only one moderator was significant in both analyses, an inconsistency in how QE researchers define and select successful or unsuccessful trials. This issue has also been discussed by Vickers (2016).

Rienhoff et al. (2016) carried out a systematic review of the quiet eye research published between 1992 and 2015; 580 records were identified using the search terms “quiet eye” and “sport.” Abstracts, book chapters, and articles with inappropriate topics were excluded, resulting in 51 papers that included both intervention and nonintervention studies. The authors conducted a review of these studies and concluded that although there is substantial evidence that a long-duration QE is beneficial to sports performance, there is a lack of a theoretical rationale for the QE. The authors suggest that a long-duration QE contributes to an overall quieting of the perceptual motor system, which is essential for attention control and response programming, as well as aiding in the inhibition of distractors.

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Figure 2. A representation of the proposed links between neural efficiency, attentional networks, the quiet eye (QE) and movement control.

(Reprinted with permission from Wilson, M., Causer, J., & Vickers, J. N. (2015). Aiming for excellence: The quiet eye as a characteristic of expertise. In J. Baker & D. Farrow (Eds.), Routledge handbook of sport expertise (p. 24). New York: Routledge. Copyright (2015), Routledge.)

Wilson et al. (2015) provide a descriptive review of sport, medicine, and law enforcement studies that have measured the QE. They grouped the research into four categories: (a) expertise differences in QE in targeting tasks; (b) expertise differences in QE in interceptive tasks; (c) the effect of increased anxiety on QE and performance; and (d) QE training with experienced performers in sport. A total of 42 studies are reviewed and their main findings summarized in Figure 2. Corbetta et al.’s model of DAN and VAN attention is highlighted along with the delicate balance between a goal-directed, top-down (dorsal) system, and a stimulus-driven, bottom-up (ventral) system (Corbetta & Shulman, 2002; Corbetta et al., 2008). When an athlete is in an unfocused state, both the dorsal and ventral systems exert control over how fixations are allocated, resulting in information being processed that is both helpful and detrimental to motor control. However, when the athlete is in a focused, the ventral system is suppressed to prevent reorienting to distracting/irrelevant cues resulting in the dorsal system maintaining a longer duration QE focused on one location at a critical phase of the movement, thus maintaining effective, goal-directed attentional control, while reducing the impact of the stimulus-driven cues that disrupt motor control.

The Quiet Eye Neural Efficiency Paradox

The finding that a longer-duration QE results in better performance in motor tasks has led Mann et al. (2016) to identify an “efficiency paradox” that runs contrary to the neural efficiency hypothesis. They state, “From both scientific and intuitive perspectives, endorsement of a ‘longer is better’ recommendation seems rather crude, and the principal mechanisms associated with this recommendation remain speculative. Simply stated, it seems illogical to expect that a longer is better adage is advantageous across performance situations” (pp. 1–2). However, extensive evidence emanating from QE studies shows that, paradoxically, the type of QE control that accompanies excellence in motor skills is not itself rapid and of short duration, but instead just the opposite. Even for tasks that are fast and ballistic, like making a save in ice hockey goal tending (Panchuk & Vickers, 2006; Panchuk & Vickers, 2009; Panchuk, Vickers, & Hopkins, 2016), the QE onset is early, on a specific location (the puck on the stick before it is released) and has a duration that is longer during saves than on goals. Similarly, in skeet, trap, and/or double trap shooting (Causer, Bennett, Holmes, Janelle, & Willams, 2010; Causer, Holmes, & Mark, 2011; Causer, Holmes, Smith, & Williams, 2011), where the clay travels at speeds exceeding 100 kph, the QE onset is early on the clay, and QE tracking duration is longer on successful than on unsuccessful shots. Because the human brain is a relatively slow visual processor, it is incumbent on the athlete to find ways to access complex spatial information earlier and to maintain his or her focus under the most challenging of situations.

Quiet Eye and Anxiety in Sport

In addition to the benefits a long-duration QE affords the visual perception and attention systems discussed thus far, Mann et al. (2016) argue that another principal benefit comes from “a long duration QE reducing the debilitating effects of anxiety on performance, processing efficiency, and cue utilization” (p. 4), leading to higher levels of motor performance. At the highest levels of sport, athletes are faced with immense levels of pressure, unpredictable playing conditions, and actions of opponents and officials that can be difficult to control. Paramount in handling these factors is the ability to manage anxiety so that it is optimal rather than too high. Two components of anxiety have been defined in the literature: (a) a mental component normally termed cognitive anxiety (or worry) and (b) a physiological component termed somatic anxiety (Martens, Burton, Vealey, Bump, & Smith, 1990). An athlete who is anxious from a cognitive perspective has “negative expectations and cognitive concerns about oneself, the situation at hand, and potential consequences” (Martens et al., 1990, p. 118). Performers who experience high levels of cognitive anxiety are worried about their ability to perform and are fearful of the negative consequences. Somatic anxiety is defined as “one’s perception of the psychological affective elements of the anxiety experience, that is, indications of autonomic arousal and unpleasant feeling states such as nervousness and tension” (Morris, Davis, & Hutchings, 1981). Somatic anxiety refers to the perception of one’s physiological arousal symptoms, such as a rapid heart rate, shortness of breath, clammy hands, butterflies in the stomach, and tense muscles. Of the two components, cognitive anxiety has been shown to have the greater and more controversial effect on sport performance (Martens et al., 1990).

A number of models have been used to explain the effects of anxiety and QE on sports performance. These theories include processing efficiency theory (PET; Eysenck & Calvo, 1992), attentional control theory (ACT; Eysenck, Derekshan, Santos, & Calvo, 2007), and the biopsychosocial model of challenge and threat (BPSM; Blascovich, 2008). The PET focuses on the negative effects of worrisome thoughts, which in turn leads to fewer resources being available for information processing, working memory, and task completion. The PET holds that optimal levels of anxiety cause an increase in motivation and more on-task behavior and recruitment of additional cognitive resources, while high levels of anxiety can lead to a loss of motivation, less on-task behavior and decrements in performance. The ACT was created to alleviate deficiencies in PET and to provide greater clarification on how attention and anxiety affect performance. High-anxiety leads to an inability to control attention and the processing of irrelevant stimuli. The ACT distinguishes between top-down goal-directed attention and bottom-up stimulus-driven attention. The ACT predicts that high-anxiety leads to a shift from a predominantly goal-directed gaze control and attention, to a more stimulus-driven gaze strategy, which in turn leads to lower levels of performance. The BPSM model distinguishes between challenge and threat effects on performance. It holds that before a task is performed, individuals evaluate the demands of high-pressure events such as exam taking, speech giving, sports competition, and it evaluates whether they have sufficient resources to meet the demands of the task. If so, then a challenge state occurs that is accompanied by an ability to focus on important cues and information. In contrast, if the individual decides he or she is unable to meet the demands of the task, a threat state occurs, and the individual feels that they do not possesses the ability to perform well on the task. The BPSM additionally predicts that challenge states focus attention on task-relevant cues, a low frequency of fixation, and a QE that is on a specific task location that is early and of longer duration, leading to higher performance. In contrast, during threat states, there is a lack of focus, a higher frequency of fixation on varied locations, a later onset of QE of shorter duration, and lower levels of performance.

The predictions of PET, ACT, or BPSM on QE duration have been investigated in archery (Behan & Wilson, 2008), basketball (Wilson, Vine, & Wood, 2009), soccer (Wilson et al., 2009), golf (Moore, Vine, Wilson, & Freeman, 2012; Vine, Lee, Moore, & Wilson, 2013), and shooting (Vickers & Williams, 2007; Causer, Holmes, Smith, et al., 2011; Wood & Wilson, 2012) High levels of cognitive anxiety have been shown to negatively affect the QE and performance outcomes. Anxiety and other stressors detrimentally affect the QE period such as physiological workload, but maintaining or lengthening the QE period is a compensatory strategy that mediates negative effects on performance. Furthermore, quiet eye training (Adolphe, Vickers, & LaPlante, 1997; Harle & Vickers, 2001; Vickers, 2007; Vickers, 2009) has been shown to positively effect QE duration and performance outcomes under pressure in golf (Vine, Moore, & Wilson, 2011; Moore, Vine, Cooke, Ring, & Wilson, 2012), basketball (Vine & Wilson, 2011; Ryu, Mann, Abernethy, & Poolton, 2016), shooting (Causer, Holmes, & Mark, 2011; Nieuwenhuys & Oudejans, 2011), soccer (Williams & Davids, 1998; Wood & Wilson, 2011, 2012), and other tasks (Rienhoff et al., 2016; Lebeau et al., 2016).

Vickers and Williams (2007) assessed the QE of elite biathlon shooters during high-pressure (national team tryouts) and low-pressure (practice) counterbalanced conditions in which physiological workload increased to 100% of their individual maximum. Anxiety levels were elevated under high pressure, leading to choking at a very low shooting percentage at the 100% workload (29%) for most athletes. However, those athletes that increased their QE duration on the target by an average of 600 ms maintained their shooting accuracy above 80%. Causer, Holmes, Smith, and Williams (2011) examined the effect of anxiety on QE of elite shotgun shooters tested under counterbalanced low-anxiety (i.e., practice) and high-anxiety (i.e., competition). The QE was the final fixation prior to the trigger pull. Participants demonstrated longer QE durations and more efficient gun motion, along with higher accuracy scores in the low-anxiety compared to the high-anxiety condition, thus supporting the predictions of ACT. Anxiety disrupted goal-directed attention led to a significant impairment in performance outcomes. Causer et al. (2011) trained the QE of a group of elite shooters matched to an elite control group that received traditional technical training. The QE group increased their QE duration, and at the same time reduced gun-barrel displacement and absolute peak velocity. The QE-trained group increased shooting accuracy from 63% to 77%, pre to posttest, whereas the control group accuracy did not change from (63%) to posttest (61%). The improved accuracy scores also transferred into competition, with the QE-trained group scoring higher in competition.

In a basketball free-throw study, Vine and Wilson (2011) examined whether QE training would protect novices against disruptions caused by anxiety. Participants were allocated to either a control or QE training group, with the latter receiving a 360-trial QE training period in which they were taught to fixate on the hoop for a second prior to beginning the shooting action (Harle & Vickers, 2001). The QE-trained group performed more accurately than a control group across retention tests under normal conditions. However, under increased anxiety, the control group performed worse than in the pretest, whereas the QE training group maintained their levels of performance.

Vine, Moore, and Wilson (2011) examined the effect of a QE training program on golf putting performance in elite golfers when anxious. Golfers were randomly assigned to a control or QE training (QET) group, both of which received video feedback relating to their gaze behaviors during the pretest, followed by the QET group receiving additional instructions to maintain a long QE period on the ball prior to the stroke and as the stroke was performed. Putting accuracy was determined during laboratory-based retention and pressure tests, as well as after 10 rounds of competitive golf had been completed. Participants in the QET group were able to maintain a long QE duration during the pressure test that was similar to their low-anxiety condition, whereas the control group showed a reduction in QE duration. These differences also transferred to the competitive setting where the QET group made 1.9 fewer putts per round than during the preintervention period, whereas the number of putts increased for the control group.

Moore, Vine, Cooke, et al. (2012) examined the effects of QE training on golf-putting performance, QE duration, club-head acceleration, and physiological heart rate and muscle activity of novice golfers assigned to either a QE-trained (QET) or technically trained (TT) group during baseline, training, retention, and pressure conditions. No differences were found at baseline between the QET and TT groups, but across retention and pressure conditions, the QET group performed more accurately than the TT group and displayed no significant change in lateral club-head acceleration. The TT group displayed significantly greater lateral acceleration during the pressure test. The QET group also exhibited greater heart-rate deceleration and reduced muscle activity than TT group, both of which are characteristics of elite golfers.

Thus far, five areas of research relating to the mental processes employed by elite athletes have been reviewed. First, evidence has been presented showing that a high level of performance in sport is dependent on the function of the visuo-motor system, in particular the DAN system, which has the ability to maintain focus on a target prior to and during motor skill execution, and the VAN system that is responsible for switching visual attention and therefore is susceptible to distractions that can be detrimental to performance in sport. Second, the neural efficiency hypothesis was presented, which states that elite performance is dependent on a brain that can process information fast and efficiently, while lower performance is characterized by a slower brain and inefficient information processing. Third, the QE was reviewed, and extensive evidence was presented showing that elite performers, in a wide range of sports, exhibit an earlier and longer-duration final QE fixation on a critical task-related location, prior to and as the movement is made. Fourth, the QE neural efficiency paradox was presented, which states that a long-duration QE runs counter to the characteristics of neural efficiency, as well as widely held beliefs in sport that if an athlete is physically fast and efficient, then he or she must also possess a brain that is even faster and more efficient. Fifth, several reasons for the QE paradox were provided, including enhanced focus and attention control, as well a long-duration QE helping the athlete handle the debilitating effects of high anxiety.

The next section presents a more in-depth examination of why the QE neural efficiency paradox exists. A review and synthesis of EEG studies by Cavanagh and Frank (2014) is presented; they have determined that increased, prolonged theta activation in prefrontal and mid-cingulate gyrus is characteristic of tasks that require increased cognitive control. This discussion is followed by a review of studies in golf and shooting that show increased theta activation when performance levels are high. Finally, the five characteristics of the QE (i.e., QE location, QE onset, QE critical phase of movement, QE offset, QE duration) are discussed, and reasons are provided for why a long-duration QE contributes to both an increase in theta-band activation of the medial prefrontal cortex and anterior cingulate as well as reduced activation and inhibition of the temporal regions during high-pressure situations when a high level of focused, cognitive control is essential.

Expertise Differences in EEG Frontal Theta Cognitive Control

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Figure 3. A variety of eliciting events is associated with a similar neuroelectrical signature on the scalp. (A) Traditional event-related potential (ERP) components in the time domain. N2: an ERP component elicited by novelty or stimulus–response conflict. Feedback-related negativity (FRN): a similar N2-like component elicited by external feedback signaling that one’s actions were incorrect or yielded a loss. Correct-related negativity (CRN): a small, obligatory component evoked by motor responses even when these are correct according to the task, and enhanced by response conflict. Error-related negativity (ERN): a massive ERP component evoked by motor commission errors. Although these ERP components (i.e., peaks and troughs in the signal locked to particular external events and averaged across trials) are related to learning and adaptive control, they represent a small fraction of ongoing neural dynamics. (B) Time-frequency plots show richer spectral dynamics of event-related neuroelectrical activity that allow one to study power following particular events without requiring signals to be phase locked. Here, significant increases in power to novelty, conflict, punishment, and error are outlined in black, revealing a common theta-band feature. (C) Scalp topography of event-related theta activity. The distribution of theta power bursts is consistently maximal over the frontal midline.

(Reprinted with permission from Cavanagh, J. F., & Frank, M. J. (2014). Frontal theta as a mechanism for cognitive control. Trends in Cognitive Sciences, 18(8), 414–421. Copyright (2014), with permission from Elsevier.)

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Figure 4. Theta as a biophysical mechanism for organizing local and distal neurocomputational functions. (A) In humans, midfrontal theta evoked by errors (here, the error-related negativity, ERN) has been localized to midcingulate cortex (MCC) on the basis of dipole source modeling (red) and concurrent hemodynamic activity (blue). (B) Theta activity recorded from the rostral cingulate sulcus in rhesus macaques. (C) Midfrontal theta is thought to reflect the synchronization of goal-relevant information around critical decision points, such as action selection. In this example, theta activities coordinate inputs across cortical areas (arrows), particularly at the trough of the oscillation (gray bars). (D) Theta-band phase consistency is thought to reflect the instantiation of transient functional networks (purple and green traces). For instance, intersite theta-band phase consistency following signals of the need for control have been observed between sources modeled in the MCC, lateral prefrontal cortex (lPFC), motor areas, and sensory (i.e., extrastriate visual) cortex. Theta activity may also implement communications between the MCC and the basal ganglia (BG).

(Reprinted with permission from Cavanagh, J. F., & Frank, M. J. (2014). Frontal theta as a mechanism for cognitive control, Trends in Cognitive Sciences, 18(8), 414–421. Copyright (2014), with permission from Elsevier.)

Published reports involving electroencephalography (EEG) have typically investigated neural frequencies within four ranges: (a) theta, 4–7 Hz, which is activated in goal directed situations; (b) low alpha, 8–10 Hz which is active according to task demands and attentional processes, such as vigilance and inhibition (Bertollo et al., 2016); and (c) high alpha, 11–13 Hz and (d) low beta (14–22 Hz), which are related to task-specific attention as well as inhibitory processes. Analyses of the EEG signals provides insight into the level of activation in different cortical areas, while EEG coherence provides information about the functional communication between different regions of the cortex. High coherence indicates communication between different areas of the cerebral cortex, whereas low coherence is indicative of reduced activation. Phase angles indicate the direction of cortical influence between different regions.

Cavanagh and Frank (2014) state that the frontal cortex allows humans “to transcend routines and habits to make better decisions. However, how does it actually ‘do’ this?” (p. 414). Cavanagh and Frank (2014) stress the importance of slow oscillation theta waves emanating from the prefrontal cortex and anterior cingulate during tasks that require goal-directed cognitive control. Figure 3 shows high activation when participants are placed in situations of high versus low levels of conflict, punishment and/or error. Because high and low levels of goal-directed cognitive control, conflict, punishment, and error often occur in sport, this finding is especially relevant to understanding mental processes during high-level performance. Figure 3 shows heightened arousal as indicated by event related potentials, time-frequency plots and scalp topography found in theta oscillations emanating from the medial prefrontal cortex and anterior cingulate gyrus. Theta appears to act as “a temporal template for organizing mid-frontal neuronal processes, which are then enhanced following events indicating a need for increased control” (Cavanagh & Frank, 2014, p. 415).

Figure 4 (Cavanagh & Frank, 2014) shows not only that is there increased theta waves in the mid-cingulate gyrus but also that greater top-down control is exerted across a broad network, reflecting “a common mechanism, a lingua franca, for implementing adaptive control in a variety of contexts involving uncertainty about actions and outcomes” (p. 415). Figure 4 (D) extends these results and shows that theta originating from the mid-cingulate gyrus affects the lateral prefrontal cortex, the motor cortex, the extrastriate visual cortex, and the basal ganglia. Although extensive research shows increased theta oscillations during increased cognitive control, far less is known about how that control is instantiated. What is the source of information that acts as the stimulus? Next, evidence from EEG studies in sport shows that an optimal QE duration may be the source of task-relevant spatial information that causes an increase in EEG theta frontal cognitive control, which in turn, leads to increased higher levels of motor success.

EEG in Sport

Three distinctive advantages result from using electroencephalography (EEG) in sport. First, studies can be carried out in the live “in-situ” setting in sports, such as golf and shooting, thereby allowing the measurement of neural activation as specific sport tasks are performed successfully or unsuccessfully. Second, EEG studies provide precise measurement of the temporal activation of neural networks as movements are prepared, unlike MRI, which is too slow to provide this information. Third, eye movements can be determined as EEG is recorded, thereby providing insight into the spatial locations fixated (QE location), when this occurs (QE onset and offset), and the duration of focus on critical cues (QE duration). The QE also identifies the critical phase of the movement when the QE must be focused to lead to successful versus unsuccessful trials. In the next section, EEG studies that determined theta activation levels in shooting and golf putting are reviewed, as well as studies that have determined the EEG and QE concurrently. To our knowledge, no study has been completed to date that has determined EEG theta and QE during successful and unsuccessful trials in an in-situ setting.

In the seminal studies involving EEG in sport, researchers predicted that elite shooters would be more accurate when they exhibited greater neural efficiency, defined as a relative absence of effortful cognition, as indicated by low EEG activation (Janelle et al., 2000; Janelle, Hillman, & Hatfield, 2000). The findings initially supported this prediction, with a quieting of the left temporal region being reported in experts prior to shooting and an overall reduction of neural processes. However, this view was revised in subsequent studies. Elite athletes in shooting and golf putting are more accurate when they exhibit both reduced activation in temporal areas and when simultaneous heightened activation of the prefrontal and mid-cingulate gyrus during tasks when a high level of cognitive control is required (Doppelmayr, Finkenzeller, & Sauseng, 2008; Deeny, Haufler, Saffer, & Hatfield, 2009; Cooke, 2013; Cooke et al., 2014, 2015; Bertollo et al., 2016; di Fronso et al., 2016; Gallicchio, Cooke, & Ring, 2016; Gallicchio, Finkenzeller, Sattlecker, Lindinger, & Hoedlmoser, 2016).

In a shooting study, Doppelmayr, Finkenzeller, and Sauseng (2008) found greater frontal midline theta activation in experts than in novices prior to the trigger pull. They found that that −1500 ms to −500 ms preceding the shot, the experts differed from novices in having greater activation of the frontal midline and anterior cingulate areas. Also, experts exhibited maximum activation at the moment of trigger pull, while the novices were erratic in terms of synchronizing EEG activation with the trigger pull.

Gallichhio et al. (2016) determined both frontal-midline theta and temporal alpha power during the final second before trigger pull in experienced biathletes. Shots were first taken at rest and then immediately after bicycle ergometer exercise at 90% of maximum heart rate, in a manner similar to that reported by Vickers and Williams (2007). During the rest condition, theta activity was reduced and alpha increased over the temporal and occipital regions; however, when shots were taken after reaching the 90% arousal level, accuracy was higher when there was increased frontal-midline theta and lower-left-central alpha power. The authors concluded that when physiological arousal is high and there is greater difficulty aiming the gun so the barrel is maintained on the target prior to trigger pull, greater cognitive effort is exerted by the mid-cingulate and presupplementary areas accompanied by lower activation of the temporal region, which indicated increased inhibition. These results, in combination with the QE results from Vickers and Williams (2007), suggest that the location of optimal QE cognitive control is the prefrontal and mid-cingulate gyrus.

Similar results have been found in golf putting. Baumeister, Reinecke, Liesen, and Weiss (2008) required expert and novice golfers to putt at their own pace for 4 minutes, trying to be as accurate as possible. Experts had better performance, which was associated with higher fronto-midline theta power in the experts and not in the novices. Cooke et al. (2015) investigated the extent to which the outcome of the putt would influence the amount of resources allocated to programming the next putt. They hypothesized that more cognitive control would be exerted after an error was made, leading to more resources being allocated. They collected data from Fz, F3, F4 (located in the frontal cortex) and Cz, C3, and C4 (the motor cortex), and they assessed high alpha EEG power (regrettably theta was not determined in prefrontal and mid-cingulate gyrus). Activation was stronger in experts than in novices after a miss, indicating that they were more likely than novices to increase the amount of cognitive resources devoted to motor planning when there was a need for greater cognitive control to correct for previous errors. The authors state that their results support those of Cavanagh and Frank (2014) and challenge “the popular view that the mobilization of fewer motor programming resources characterize sporting excellence. They suggest that, at least for the skill of golf putting, players should make an effort to increase the amount of resources they allocate to programming key movement parameters, to achieve putting success” (Cooke et al., p. 980).

EEG and QE in Sport

Mann, Coombes, Mousseau, and Janelle (2011) combined electroencephalography (EEG) and eye tracking to investigate neural activation and the QE of nonexpert and highly skilled golfers. Mann and colleagues assessed the Bereitschaftspotential, which is an event-related potential linked to greater task involvement and sensorimotor efficiency and cortical activation. Alpha and beta recording were taken from electrodes placed over central motor areas, as well as parietal area (no recordings were made from the prefrontal or mid cingulate regions). Systematic differences in QE duration and the Bereitschaftspotential were observed, with the highly skilled golfers exhibiting a prolonged QE period and greater cortical activation in the right-central region compared with nonexperts. These results support the QE period as being critical in visuomotor preparation, as well as the efficiency and quality of motor processing. The authors conclude that “prolonged fixations, particularly during the final fixation that defines the QE, apparently permit the detailed processing of information and cortical organization necessary for effective motor performance” (p. 232).

Conclusion

The collection of studies reviewed in this chapter provide evidence that high levels of performance in motor tasks are dependent on the athlete being able to use an earlier and longer duration QE which contributes to both increased theta activation of the frontal midline and medial anterior cingulate and reduced alpha activation in the temporal lobe inhibitory network. Furthermore, this combination of activation appears to be specific to elite performers, especially when subjected to high-pressure situations in which there is a perceived need for cognitive control.

Therefore, it is likely that during high-pressure situations, elite athletes have a significantly earlier and longer QE duration, increased theta activation in premotor and anterior and/or mid cingulate gyrus prior to and as a critical phase of the movement is performed. At the same time, there should be reduced activation in the temporal region, which inhibits or prevents the intrusion of the negative effects of distracting thoughts and emotions and allows for high levels of concentration and focus to be maintained when needed. A long-duration QE exploits the architecture of the mid-frontal cortex and anterior cingulate gyrus through extended slow theta oscillations, and it facilitates the inhibition of activation from the temporal lobe and frontal areas that can distract and disrupt performance.

Overall, a long-duration QE facilitates motor performance in five specific ways:

  • First, there is usually only one QE location fixated per trial, which is a single task specific, spatial cue consistently identified by elite athletes before a critical phase of the movement. Reducing fixation frequency to a single QE location that is rich in meaningful information, contributes to higher levels of performance. Wilson et al (2015) state that “a single, long, final fixation to a relevant target is actually more efficient than a series of fixations around the target” (p. 25). The QE situates cognition on a specific location in the task environment, thereby providing coachable information about selective attention processes used by elite performers in a motor task.

  • Second, the QE onset of elite performers occurs earlier, providing evidence of superior anticipation and feed-forward of motor commands. The earlier QE onset of elite athletes gives the performer more time to prepare the movement, both in terms of biomechanical effectiveness and emotional regulation. The QE also supports the idea that gaze control is necessary for accurate motor prediction, as argued recently by Henderson (2017) in a recent theoretical perspective on gaze control underlying prediction.

  • Third, there is a critical QE movement phase, which is undoubtedly the most unique aspect of the QE, compared to other fixation and/or gaze behaviors proposed in the literature. The QE onset always occurs before the onset of a critical phase of the movement, thereby recognizing the importance of precise perception-action coupling, as well as providing evidence of optimal perceptual-motor coordination and timing.

  • Fourth, the QE offset is task dependent and may carry through and beyond the final movement of the task (as occurs in the golf putt), or occur earlier before the movement is completed (as occurs in basketball shooting). The elite QE offset is therefore sensitive to specific task constraints, such as objects moving through the visual field (as in a basketball free throw), or compressed time periods where an action follows that is fast and dynamic (as in goal tending).

  • Fifth, the QE duration is longer during successful performance, indicating that a period of sustained visual focus and concentration is needed to optimally organize the billions of neurons that are used to plan, initiate, and control the movement. EEG evidence from Cavanagh and Frank and others show that extended theta processing occurs within the medial prefrontal cortex and anterior cingulate cortex. Because these areas are located in the middle of the brain (Figure 4), slow-wave theta oscillations act as a central hub of activity, which Cavanagh and Frank (2014) describe as follows: “The mid-cingulate is strongly interconnected to cortical and subcortical areas in a hub-like manner, suggesting that FM0 signals entrain disparate neural systems by this theta-band phase dynamic when cognitive control is needed. Indeed, a large-amplitude low-frequency temporal organization scheme may be ideal for organizing activities across large spatial distances. Thus, cross-cortical information transmission could function in an emergent manner if phase-locked FM0 naturally entrains activities in disparate neural systems” (p. 416).

Finally, the five characteristics of the QE can be likened to an orchestra that has one or many conductors. Less skilled athletes typically fixate many locations in short durations, providing task information that lacks cohesion and overall strategic sense. In this sense, they behave like an orchestra that has separate conductors for each section (the woodwinds, brass, percussion, and strings), resulting in a performance that is discordant, lacks timing that is inadequate for each musician to make the contribution they are capable of, and lacks overall synchrony. In contrast, an athlete who has optimized the five QE characteristics is governed by one QE conductor, resulting in superior sports performance. Because the five characteristics of the QE are obtained as the task is physically performed under conditions similar to the real world, objective evidence is obtained about the specific spatial attention (i.e., QE location), anticipation (i.e., QE onset), perceptual motor-coordination (i.e., QE movement onset), optimal control (i.e., QE offset), and the focus and concentration (i.e., QE duration) used by the best performers in the world to be successful. The strength of this information is illustrated in its use in QE training programs, which have been shown to lead to greater improvements in motor performance than traditional technical training programs, not only in sport but also in surgery, child development, and other areas (Causer, Harvey, Snelgrove, Arsenault, & Vickers, 2014; Causer, Vickers, Snelgrove, Arsenault, & Harvey, 2014; Miles, Wood, Vine, Vickers, & Wilson, 2015a, 2015b; Gonzalez et al., 2017). In conclusion, this review has not only provided a recent comprehensive review of some of the visual and neural processes operating in the elite athlete’s brain but also has presented a number of topics and hypotheses for future research.

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