Less-is-More and Embodiment—How the Body Simplifies Cognition

Abstract

Less-is-more describes a principle underlying decision making. Embodiment, on the other hand, argues that the body plays an important role in processes that have classically been characterized as mental. We argue that decision making is facilitated by reducing the amount of mental information processing (less-is-more) through the exploitation of the constant stream of rich sensorimotor information (embodiment), a concept we call LIME. LIME argues that, via embodiment, information processing is “constrained” by and “off-loaded” into the body. Constraining involves the body reducing the input or generated options before they enter into mental information processing. Off-loading involves the body or the environment performing the information processing. LIME underlies cognition generally, but is most accessibly demonstrated in sport phenomena, and we use this domain to sketch out the breadth of this concept in four case studies. LIME connects first principles of cognition to real-life phenomena, providing explanatory insights into ecological rationality and frameworks explaining adaptive behavior.

Keywords

decision making embodied cognition embodied choices bounded rationality off-loading constraining

Introduction

Less-is-more is considered a governing principle of decision making (Gigerenzer & Gaissmaier, 2011; Shah & Oppenheimer, 2008), where a reduction in cognitive processing counterintuitively elicits more adaptive behavior, that is, context-sensitive functional activity that leads towards achieving an agent’s viability- and task-related goals (Ashby, 1960; Parr et al., 2022; Pfeifer & Scheier, 2001). We argue that embodiment, the notion that cognition is coupled to and constituted through the body and environment (Shapiro, 2007; Thelen et al., 2001), is one means with which this is achieved. This approach therefore views the body and action as part of the cognitive system. These two perspectives complement and augment one another, where less-is-more shapes cognition and drives development toward a more embodied cognition. This novel description explicates a previously implicit blueprint involved in much of cognition.

Cognition involves a constant stream of rich information in the body and its actions in the world. This richness means that cognition can produce adaptive behavior by distributing the information processing burden effectively. This especially involves reducing the burden for mental information processing by performing information processing with the body (Shapiro & Spaulding, 2019). In other words, information processing is—frequently—done with the body to reduce the proportion of information processing that is done mentally¹. While other embodiment perspectives posit “cognition is for action” (Engel et al., 2013; Pezzulo & Castelfranchi, 2009) less-is-more and embodiment (LIME) emphasizes the other direction: action is for cognition. In other words, cognition did not only evolve to support action, but also that action—as part of the cognitive system—performs much of the information processing classically assumed to be mental. In this paper, we present this new concept and how it underlies much decision making. Following, we present examples of classic phenomena from the realm of sport to demonstrate how LIME underlies adaptive behavior.

Research in sport has been forced to emphasize how cognition deals in complex and resource-limited situations using similarly complex actions to produce effective performance. It is therefore an excellent test bed for identifying the methods used by a cognitive system with action capabilities (Gordon et al., 2021). LIME expands on the thriving framework of embodied cognition, while also connecting it to existing traditionally accepted pillars in decision making, and extending it to align with the “ecological turn” (Fischer, 2024; Rączaszek-Leonardi, 2023) in embodied cognitive science, which involves the increasing acceptance of environmental influences on cognition.

Demonstrative Example of Mental and Bodily Information Processing—Shakey and Allen

How the body enables adaptive behavior by reducing mental information processing is eloquently demonstrated by Brooks’ (1991) assessment of “unembodied” and “embodied” robots². The first, Shakey, is constructed such that all information processing is “mental”: taking place in a detached central module, representing an unembodied brain. A camera sends visual input to a computer which transforms this input into symbols, these symbols are manipulated to identify adaptive behavior, and this is then back-transformed into an action plan. The second robot, Allen, does not rely on performing extensive information processing over symbols in a central module, but rather on perceptual inputs which are directly connected to motor output (e.g., “halt movement if an obstacle is in the path”). Allen, and other robots like it, can operate in real time, performing sophisticated tasks, whereas their unembodied siblings take hours to days (Braitenberg, 1986; Matarić, 1998; Shapiro, 2019). Most importantly, the robots’ performance seemingly goes beyond its processing limits, by virtue of using the body and situation for information processing. By constructing Allen such that information is processed with his body, it allows “mental” information processing to be completely removed and replaced by interaction with the environment. This has long been a foundational insight in motor control literature. Many prominent frameworks emphasize that limbs and joints self-organize into synergies, which obviates the need for central planning, that is, mental information processing (e.g., Bernstein, 1967; Kelso, 1995; Latash, 2008; Turvey, 1990). These mechanisms reduce mental information processing load by distributing control into the biomechanical and environmental dynamics of movement, and are therefore in line with off-loading as we have described it here. This is the reasoning of LIME: We argue that human cognition is more like Allen, adaptive behavior involves a significant proportion of information processing to be performed with the body acting in the environment. Although, of course humans also have further mental information processing capacities, in contrast to robots like Allen. Indeed, the findings surrounding these robots have often been used to support a more radical embodied view of cognition that denies the existence of mental representations, we do not make such claims. This example portrays that the tasks that are often considered mental can be performed by a body in action, and this is a distribution of responsibility which suits adaptive behavior.

Reducing the Need for Mental Information Processing

The principle “less-is-more” is philosophically embedded in Simon’s notion of satisficing. In contrast to the homo economicus, envisioned in classical decision making, who maximizes possible gains by engaging in elaborate rational calculation to arrive at decisions, the homo heuristicus satisfices (Brighton & Gigerenzer, 2012; Simon, 1956). The satisficing decision maker reduces mental information processing by relying on methods that are generally effective in the current environment (i.e., ecologically rational), often replacing extensive decision-making rules with basic rules of thumb (e.g., take-the-first heuristic, which involves choosing the first option which is satisfactory, as opposed to considering all options and then choosing the best; Raab, 2012; Voigt et al., 2025) . Behavior in real life often has limits on time, information, and cognitive resources, which makes a maximizing method unfeasible and ineffective (Petracca, 2021). Satisficing entails reducing mental information processing load while retaining or even improving performance across many situations. Furthermore, the satisficer does not reach decisions that are optimal across contexts, but rather ecologically rational decisions, that is, good enough for the current context. The less-is-more principle relates to the ability to reduce the amount of information processing, while maintaining adaptive behavior. Past theories have always implicitly focused on reducing the amount of mental information processing. We are more specific and argue that especially mental information processing is attempted to be reduced and replaced by bodily information processing.

Although the less-is-more principle is most exhaustively described in decision-making literature, similar concepts exist across cognitive sciences. The “cognitive miser” describes the brain’s innate tendency to develop strategies that reduce mental information processing load (Fiske & Taylor, 1991). A number of social processes have been conceptualized as being the result of reducing the need for complex information processing already since the 1920s (Corcoran & Mussweiler, 2010; Lippmann, 1922; Shintel & Keysar, 2009). These examples underline a universal drive toward less-is-more: the amount of mental information processing is consistently reduced while retaining (and often in the case of naturalistic action, as we will see, improving) performance.

Information Processing in the Body

Embodied cognition describes a perspective on cognition which emphasizes the body (Thelen et al., 2001; Wilson, 2002; for applications in sport psychology see Voigt et al., 2023). The body includes all intero- and exteroceptive sensorimotor capabilities, including the central and peripheral nervous systems (including the brain) and other systems. This embodied cognition perspective also includes the situatedness of cognition: emphasizing the important dynamic role of the immediate environment and its action capabilities on cognition (Robbins & Aydede, 2001). The body, the body’s ability to act in the environment, and to subsequently perceive the environment in terms of action capabilities (henceforth termed just “the body”), is a core component of this view (Foglia & Wilson, 2013; Gibson, 1977). While the larger research programme around embodied cognition is a very broad perspective encompassing many distinct positions, the common factor unifying the many ways in which research has approached it is that the body’s role in shaping and furnishing cognition is more important than let on by classical approaches (Shapiro, 2019). In this paper, the framework of embodied cognition focuses on the contribution of the body in performing information processing, that is, in forming part of cognition itself (Gigerenzer, 2021; Shapiro & Spaulding, 2019). This view, therefore frames cognition as being co-constituted of the brain and body. The body does not act as an information input channel to purely mental information processing, but rather performs information processing itself. There exists therefore mental and bodily information processing.

Some examples of this include that we exploit sensorimotor capacity to aid in perception, abstract cognition, and language understanding. For example, participants wearing a heavy backpack judge the slant of a hill as steeper, arising from perceptual information about difficulty in climbing the hill (Bhalla & Proffitt, 1999). In place of extensive and uncertain mentally bound information processing about possible action, the sensorimotor-based simulation of walking up the hill is exploited. Similarly, the body can help with abstract information processing: children’s ability to move their fingers and to distinguish fingers predicts future math ability (Barrocas et al., 2020; Michirev et al., 2021). To scaffold the abstract (and more demanding) numerical cognition, the sensorimotor system is exploited to reduce the information processing load on mental processing (cf. also Vygotsky, 1978). Indeed, even adults use finger-based representations to perform arithmetic tasks (Andres & Pesenti, 2015; Klein et al., 2011; similarly, see also Boroditsky, 2000). Body-based representations also construct the understanding of language (Barsalou, 2008; Friedrich et al., 2025). When thinking about action concepts like the word “kick,” sensorimotor regions in the brain become active (Hauk et al., 2004; Trumpp et al., 2024). This even holds for abstract concepts, which we have never interacted with (Günther et al., 2020; Pulvermüller, 2005). These examples demonstrate the meaningful ways that even ostensibly non-body-based cognition is not independent from the body.

Reducing the Need for Mental Information Processing by Using the Body

Assuming less-is-more as a fundamental principle guiding information processing, and knowing significant parts of cognition are performed by the body, we argue that embodiment acts in service of less-is-more³ (a concept we term LIME). This seems feasible because the body is a source of very rich information. With rich, we mean that information “bits” coming from the body are more helpful in arriving at adaptive behavior. This richness comes from two attributes which body and situation have. First, the information is rich because it tends to be task relevant: The body can direct perceptual input towards relevant information, such as looking over the shoulder to find out whether a car is approaching. It is also task relevant because it is—save for a few hundred milliseconds of neural delay—immediate. Second, it is detailed (I can feel minute differences in the position of my toes) with understandable structure (my toes are perceived in relation to my foot, attached to my leg, attached to my hip). As with the embodied and unembodied robots, the information generated by a body in action is so rich that it allows to perform much information processing which would otherwise have to be performed mentally (or for robots by a central module), and is argued to be performed mentally in other, unembodied, frameworks.⁴ This richness of bodily information means that a system aiming to minimize mental information processing will find success when exploiting the body and situation to do this.

The core tenet of LIME is: there is a fundamental drive for mental information processing load to be reduced (less-is-more; Voigt et al., 2025) and to do this, information processing is performed by the body in action (embodiment). Yet, does this mean that less-is-more causes embodiment? Or does the brain make the body perform information processing? Arguing from the perspective of embodied cognition, we argue that this cannot be answered as such. We assume that adaptive behavior emerges from the interplay of all components of a cognitive system (i.e., brain and a body in action. and their respective abilities and limits) over time. The embodiment of certain tasks is produced because, over time, less mental information processing is always favored, so long as the outcomes are satisfactory. Performing information processing using the body acting in an environment (i.e., embodied cognition), because it allows to reduce the amount of information processing which has to be performed mentally, is a characteristic that naturally emerges with time (Petracca, 2021). Over time, as non-mental information processing is always favored, the body takes on increased information processing load. A natural consequence of the less-is-more principle is therefore embodied cognition. Consequently, we can say embodied cognition serves the less-is-more principle, and simultaneously, embodied information processing strategies are driven by less-is-more. This is also why we argue that the embodiment research program should be joined to less-is-more research, because their contents are complementary. This therefore presents a central contribution of the LIME approach, as it describes how, over (phylogenetic and ontogenetic) evolution, the proportion of bodily information processing is favored.

Having described less-is-more and embodiment, we turn to how embodiment serves the less-is-more principle. In other words, how does embodied cognition allow to reduce mental information processing while maintaining (or improving) performance. We argue that the body (1) constrains the amount of information which is processed, and (2) allows cognition to off-load information processing into the sensorimotor system and environment.

Constraining

Firstly, embodiment reduces mental information processing by constraining5. Information input is constrained to task-relevant stimuli (e.g., reducing visual input to solely the most relevant and informative point of information, subsuming the task of weeding out irrelevant information). There is ample evidence that effective performance involves reducing perceptual input (Haider & Frensch, 1999). For example, sport expertise is often accompanied by a reduction in the number of visual fixations during performance (Brams et al., 2019; Gegenfurtner et al., 2011). Second, not just sensory input, but also perceived options for future actions are constrained (Pezzulo & Cisek, 2016). The body limits focus solely to feasible action opportunities, which in turn improves performance. A classic example is that individuals, based on their leg-length or strength, perceive steps on a staircase as “steppable” or not (Konczak et al., 1992; Warren, 1984). This use of bodily constraints to constrain action possibilities is similarly reflected in athletes such as climbers who consider options and adjust the complexity of their actions based on their ability to perform a climb (Luis del Campo et al., 2024; Seifert et al., 2021). Similarly, expertise corresponds to reducing the amount of time to determine whether a grasp can be reached (Seifert et al., 2018). The richness of information (e.g., knowing the exact action capabilities of my arm) allow for perception (e.g., perceiving distance in relation to one’s arm length) to immediately discard unfeasible action possibilities without including them in any information processing.

Off-Loading

Secondly, mental information processing is reduced by off-loading. Off-loading entails information being held or manipulated by the body (cf. Müller & Hoffmann, 2017; Wilson, 2002). Take the outfielder problem, a prototypical example in embodiment literature to demonstrate the ways which a body in action performs sophisticated tasks without resorting to elaborate mental information processing (McBeath et al., 1995; Oudejans et al., 1996). An outfielder, attempting to catch a fly-ball is tasked with identifying where to stand in order to catch the ball. While it could be possible that this is a solely mental task, in which a likely landing location is computed based on the strength of the hit, air friction, gravity, and other forces, this corresponds to significant mental information processing burden. The embodied method, which maintains (and even improves) accuracy, is that the outfielder instead runs so that the visual angle remains constant while tracking the baseball. Elaborate mental information processing of various variables is replaced by a body in movement maintaining a perception, which, given it is physically feasible, has a one-hundred percent accuracy rate. The information processing is being performed, using the same input (sensory information about location, speed, and other conditions of the ball’s movement), but much like our fingers performing arithmetic when clicking buttons on a calculator or remembering a forgotten pin code at the ATM, the body holds and manipulates the information of the landing location of the ball. In other words, the information processing is off-loaded into the body. The outfielder not only performs better because the method is more accurate but also more generally because mental resources are preserved for other mental information processing, such as deciding which baseman to throw to.

LIME in Four Exemplary Sport Phenomena

Having outlined the concept of LIME, we aim to give shape to the abstract explanations above by providing examples from research on real-life phenomena. Each of the phenomena describes a domain in sport and how it is an instance of LIME. We choose sport psychology as the domain of interest because it most extensively portrays cognition in the context of a body acting in the world with limited information processing capacity (i.e., vast, changing, and complex perceptual information; Beilock, 2008; Gordon et al., 2021). The examples are intentionally not perfectly parallel and certainly non-exhaustive. This diversity demonstrates the strength which this proposal has, providing clarity and explanatory power beyond lines in the sand drawn by prior frameworks, extending and connecting previously disparate fields. Furthermore, these examples demonstrate: LIME connects first principles of cognition to explain, not only other theories, but real-life decisions in applied research. This underlines how fundamentally it functions and demonstrates the relevance of this theoretical contribution.

Skill Execution

The first example argues that movement analogies in skill execution are a way to reduce mental information processing load by off-loading it to the body. The utilization of movement analogies in motor skill learning exploits the richness of pre-existing sensorimotor representations, which improves athletic performance by letting existing sensorimotor representations guide motor processes. This serves to improve performance in high-pressure situations by preventing the occurrence of reinvestment, a potential cause of performance detriment under performance pressure (Masters & Maxwell, 2008).

Analogy learning consists of providing athletes with a biomechanical metaphor for the to-be-learned skill, that is, a familiar movement from another domain. For example, one can learn the topspin forehand movement in table tennis by pretending that the bat is traveling up the side of a mountain (Poolton et al., 2006). Analogy learning places the guidance of control into existing motor programs. By tapping into already existing sensorimotor representations, step-by-step control is replaced by larger chunks, which in turn reduce mental information processing load (Cabral et al., 2020; Poolton & Masters, 2014; see for a review Kal et al., 2018). This can improve performance in high demand situations and can help to prevent performance declines under pressure due to reinvestment (Masters & Maxwell, 2008), as learning transpires implicitly with minimal accumulation of explicit knowledge (Lam et al., 2009; Masters, 1992), thereby limiting the potential to reinvest under pressure.

Reinvestment refers to athletes consciously monitoring and controlling their movements and decisions using explicit knowledge (Kinrade et al., 2010; Masters & Maxwell, 2008), which results in the loss of the automatic movement sequence of athletes (Sullivan et al., 2022; Tang et al., 2023). Movement analogies counteract this loss by activating deeply ingrained, chunked sensorimotor patterns (Liao & Masters, 2001; Maxwell et al., 2000). In this way, the mental information processing involved in motor control is minimized by off-loading mental information processing into the body, thereby stabilizing and enhancing performance in high-pressure situations like competitions (Lam et al., 2009; Voigt et al., 2025).

Consider a Padel (a popular racquet sport similar to tennis and squash) player learning a Padel stroke through analogies. The player is instructed to envision holding the racket like a tray with a drink on it for learning the “Bandeja” stroke or to liken the arm movement for a forehand volley to making stones splash on a lake. Instead of teaching the single components of this movement in several step-by-step instruction (e.g., to raise the elbow of the dominant arm to face height to reach the plateau position with the racket), a single chunked representation (holding a drink tray or making stones splash on a lake) is activated and details are filled in by rich sensorimotor information stemming from previous movement experiences with the analogy (as opposed to mental information processing). This approach improves performance under pressure by reducing the purely mental processing of information for motor control, promoting instead an implicitly automated, body-based coordination, thereby minimizing mental information processing.

The less-is-more aspect of movement analogies is evident in the off-loading of mental information processing. The single analogy offers rich information because many minute details about movement execution are referenced in a single familiar sensorimotor representation. It is embodiment because the richness comes from the existing sensorimotor representations, which are executed to perform the skill. Athletes off-load the coordination of motor execution to existing representations in the sensorimotor system and rely on larger chunks of movement information, thereby reducing the need for step-by-step control and enabling smoother, more effective motor execution. In other words, the skill execution is embodied.

Importantly, LIME in skill execution improves performance in two key ways. First, generally by reducing mental information processing load. This frees up mental information processing capacity for other task-relevant processes (e.g., remembering the weakest stroke of the opponent). Second, they mitigate performance breakdowns under high demand generally, and considerably improve performance by preventing the reinvestment of step-by-step control during movement execution.

Tactical Decision Making

The second example argues that decision making under physical fatigue involves information processing being performed by the body. In decision making under fatigue, options which are too effortful are a priori not considered. The, ostensibly mental, task of identifying and excluding unfeasible action options is replaced by the body providing direct access to rich information that exclude unfeasible options. Athletes do not consider action possibilities which are not in their (present) action repertoire. By letting the body’s capabilities constrain action options, performance is maintained and arguably even improved because athletes make decisions better suited to their current physical capacity.

Physical fatigue is a momentary reduction in the body’s action capability as a result of exertion (Trendall, 2000), which has profound detrimental effects on an athlete’s performance by limiting abilities, for example, in the form of declined muscle activity (Abd-Elfattah et al., 2015). Fatigue also has effects on athletes’ decisions by increasing the likelihood of making energy-conserving decisions (Barte et al., 2020; Iodice et al., 2017).

Consider a beach volleyball player who adapts their strategies during competition based on their physical state. For example, in conditions of extreme heat and humidity, where fatigue is more prominent, the player chooses to employ less energy-intensive tactics. They opt for strategic positioning over agile movements, or simpler plays that are less physically demanding. This decision-making process, constrained by the body’s physical state, ensures that the employed tactics are not only effective but also sustainable given the athlete’s condition.

The less-is-more aspect of fatigue is evident in the constraining of generated options. Firstly, less-is-more must be present under fatigue. Fatigue reduces the capacities of athletes, yet their performance is often maintained. For example, fatigued cyclists showed a reduction in visual information uptake, but still maintained performance when fatigued (Zeuwts et al., 2021). This demonstrates how, under fatigue, sensory input is constrained. Yet, also the generation of action possibilities is constrained. When making decisions which are executed with the motor system, models of possible movements form the space of action possibilities (Lepora & Pezzulo, 2015; Raab, 2017). Importantly, these models are linked to the body, reflect current action capabilities. The current sensorimotor input limits the generated action possibilities, and are impacted by fatigue: For example, mental simulations of movements are slower when a person is fatigued than when not (Demougeot & Papaxanthis, 2011; Pezzulo & Cisek, 2016). This reduction in options facilitates quicker and more efficient decision making. Mental information processing is reduced, yet decisions are made that are more adaptive, because they are necessarily aligned with current physical capacity.

Pacing Strategies

The third example argues that processing of information related to homeostatic balance is off-loaded into the body and constrains action possibilities. Many aspects of the individual’s bodily response to the given task and environmental conditions are summarized in the single interoceptive signal of heart rate. Mental information processing is reduced, in line with the less-is-more principle, by letting the body integrate much diverse visceral information into the cardiac signal, which in turn serves to constrain the space of action possibilities. In endurance athletes, performance benefits are attained through efficient pacing, by preventing excessive strain on their body. By virtue of the structure of visceral information, cardiac signals are an ecologically rational summary index to make effective pacing decisions.

The body strives to maintain a homeostatic balance, and changes in heart rate during exercise reflect these alterations (Berntson & Cacioppo, 2007; Craig, 2003). Heart rate is the output of integrating various visceral signals including vascular and respiratory-driven ones. Additionally, heat, high altitude, and dehydration further increase the heart rate during prolonged exercise, suggesting its sensitivity to factors other than exercise intensity (Jeukendrup & VanDiemen, 1998) and its ability to summarize the current level of bodily imbalance. Through cardiac interoception, that is, the awareness of and sensitivity to one’s heartbeat and its changes (Garfinkel et al., 2015; Herbert & Pollatos, 2012), athletes detect changes in their heart rate and use this information to make decisions regarding the distribution of their power output. Indeed, it has been demonstrated that athletes rely on cardiac changes in effort estimation. In an auditory manipulation of the heart rate feedback during a cycling task, hearing faster rather than true heart rate led to higher perceived effort, despite cycling at the same intensity level (Iodice et al., 2019). Furthermore, chosen pacing strategy was found to correlate with cardiac interoception ability, demonstrating the importance of perceived heart rate in pacing (Herbert et al., 2007).

Consider a long-distance runner competing in an ultra-trail race such as Tor des Géants, a race involving running up and down mountain trails for more than 60 hours (cf. Hutchinson, 2018). The runners continuously break their homeostasis to gain an advantage over other competitors. The considerable distance to be covered, however, does not permit them to perform at maximum power output throughout, necessitating adjustments in pacing behaviour to re-establish homeostasis (St Clair Gibson et al., 2018). The runner makes continuous decisions to increase, maintain, reduce their speed, or to stop. It has been suggested that bodily balance may be affected by factors such as excessive heat and sleep deprivation but “our brain protects us against our own excess – almost always” (Hutchinson, 2018, p. 11). Instead of attempting laborious mental information processing of all available information (e.g., breathing frequency, incline, heat, humidity, and oxygen level), the status of a single, ecologically rational, signal constrains action possibilities. We argue that our body plays a crucial role in protecting our homeostatic balance by executing part of the information processing involved in pacing decisions: via changes in cardiac signal which summarizes visceral information and is thereby used to constrain options.

The less-is-more aspect of cardiac interoception is evident in the constraining of generated options. Information processing-heavy consideration of numerous influencing factors, including current fitness level and environmental conditions, is inefficient, uneconomical, and at times impossible. Instead, interoceptive information such as increased heart rate summarizes these factors and allows constraining of the pacing options. Those action possibilities that would substantially disrupt athletes’ homeostatic balance and be detrimental to their performance are a priori excluded (Pezzulo & Cisek, 2016). Following the less-is-more principle, athletes may therefore use cardiac feedback to perform part of the information processing necessary for decision making, such as the pacing strategy in endurance sports.

Anticipation

The fourth example argues that the use of sensorimotor simulation in anticipation is a way that mental information processing is off-loaded into the body. Through the ability to simulate observed actions, athletes can off-load parts of the ostensibly mental information processing into the sensorimotor system. This mechanism provides performers with rich, readily accessible information while reducing the mental information processing load needed to process the continuous incoming information (Prinz, 1990; Prinz et al., 2013). This not only maintains performance compared to purely mental information processing, but improves anticipation skills and thereby performance.

Across a wide range of sport disciplines, and beyond, anticipation is a critical skill (Williams & Ericsson, 2005). Anticipation often involves athletes simulating others’ movements. Simulation involves the activation of the motor system during action observation (Buccino et al., 2001; Rizzolatti & Craighero, 2004). The role of simulation in visual perception is so critical that even movements which have never been visually perceived are discriminated better when they have been learned motorically (Casile & Giese, 2006). Furthermore, athletes’ expertise augments the extent to and detail in which simulation occurs (Beilock, 2008). This allows to anticipate others’ movements more finely, such as detecting whether a movement is deceptive or not based on very small differences (Cañal-Bruland, 2017).

Consider a professional basketball player who, as a result of extensive motor experience, has improved their anticipation abilities. Compared to individuals with similar visual experience (coaches and sports journalists) and novices, basketball players can predict the outcome of free throw shots earlier and more accurately (Aglioti et al., 2008). The reason for their superior ability is that with expertise, the athletes are better able to simulate others’ actions. Furthermore, the influence of simulation is not limited to anticipation skills, but also visual discrimination, such as professional gymnastic judges. These demonstrate higher judgment accuracy in evaluating movement performance when possessing motor experience in a movement compared to judges without (Pizzera, 2012). This visual discrimination also translates onto the field, where rugby players’ ability to detect deceptive movements is improved with increasing motor experience (Jackson et al., 2006).

The less-is-more aspect of simulation is evident in the off-loading of action consequences. Anticipation of likely consequences of movements would, under the standard cognitivist approach, require extensive calculation of many components such as angle of body, or gaze locations. Instead, the sensorimotor system provides the same information without mental information processing (as in the outfielder example) by letting the movements be perceived in one’s own sensorimotor system (cf. Prinz, 1990). We deem the perceptual information provided by simulation rich because it goes beyond visual information, to include causes of movements and transfer of force, among others. For this reason, in predicting action outcomes, it fares better than a purely “mental” calculation, but simultaneously allows this calculation to be performed by the body. Less mental information processing is required for the athlete to process more information, and despite this reduction in mental information processing, performance is improved, because the information processing is off-loaded into the body.

How LIME Advances Our Understanding of Ecological Rationality

While many embodied cognition proponents have argued that cognition should be viewed as stemming from the need to perform action (cognition is for action; e.g., Glenberg, 1997; cf. Wilson, 2002), we argue for the case that action is often a critical part of cognition (action is for cognition)⁶. We have argued that to perform ecologically rational behaviour, necessarily in line with the less-is-more principle, cognition is constrained and off-loaded by and into the body, respectively. It is able to do this because the body provides rich information, being task-relevant and detailed without becoming opaque. We have outlined a variety of sport examples that have demonstrated how athletes’ decision making adheres to less-is-more by exploiting the body to perform information processing.

We used sport phenomena to exemplify LIME because this was more facilitative in portraying the concept, and also because research in sport has unique strengths. Regarding the first point, it is difficult to draw a demonstrative example of off-loading from a person sitting at a desk (but see finger-counting and language understanding examples in Section 3). LIME is much more accessible if naturalistic action is required. Furthermore, the uncertainty, complexity, and time pressure, which are assumed under ecological rationality, are exacerbated in the sport context. Therefore, here more than anywhere, cognition must adhere to the less-is-more principle, while also having a body in action with which to do it. Second, research in sport also has the unique strength that it has made significant progress in understanding subjects in action, because these are de facto components of the research object (Maselli et al., 2023). Other research may have failed to identify off-loading and constraining, because its research relies on synthetic laboratory situations without a body in action to constrain or off-load. Nonetheless, LIME should apply beyond sports and also explain real-world everyday situations. Despite many everyday activities involving tasks with minimal action, it is likely that even here information processing involves bodily information processing to some degree. For the majority of its existence, cognition has served to act in a rich environment, as opposed to reason (Cisek & Pastor-Bernier, 2014; Gordon et al., 2021). Therefore, the ways we currently traverse our (comparatively brain-based) everyday experience evolved to serve a body in action and are built on a sensorimotor substrate (Bain, 1868; Glenberg, 1997; Pezzulo, 2011; Shepard, 1984).

One major contribution of LIME is that it provides a description for the development of embodied cognition and may present a way to explain empirical findings. LIME argues that much embodied cognition is the result of aiming to distribute the information processing load beyond the confines of the skull. This would be a parsimonious resolution to discussions about whether cognition is body-based, by arguing for the moderate position: it can be embodied, and very often is, when this is the most ecologically rational solution (see also, Clark, 2015). When given the option, cognition is readily performed by the body in order to reduce mental information processing. We are surely not the first to point this out. Authors working on morphological computation (e.g., Pfeifer & Gómez, 2009), comparative biomechanics (e.g., Vogel, 2013), distributed cognition (e.g., Hutchins, 1995; Spivey, 2023), aforementioned work on motor control and synergies (e.g., Latash, 2008; Turvey, 1990) along with others (e.g., Port & Van Gelder, 1995), have argued for the diversity of information processing mechanisms, and the ability to perform tasks which have classically fallen under the domain of mental processing without remaining skull-bound. We are indebted to these authors and acknowledge their important insights. Our addition to this literature is to take some of their insights to frame them in such a way as to be integrated with the less-is-more principle. This provides the novel insight that the same task, when embodied, can free up mental information processing.

As mentioned in Section 4, we argue that LIME is an emergent phenomenon, resulting from an interplay of brain and body. Therefore, less-is-more is perhaps best viewed as a principle governing the maintenance of cognitive processing (cf. dynamical minimalism; Nowak, 2004), in a “information processing Occam’s razor”; assuming all else is equal, in deciding between two strategies, the one where mental information processing is most reduced will be preferred (Kruglanski & Gigerenzer, 2011). Information processing strategies with heavy mental information processing load will be weeded out over time, which means that those which are maintained will be those that require least mental information processing. As described above, the body is well-suited to effectively serve information processing for situated behaviour and will therefore often win the information processing Occam’s razor and be retained. This natural selection on the distribution of information processing resources, scaled up to the monumental number of milliseconds, minutes, and days which humans must make decisions, leads to the emergence of a cognitive system that is heavily reliant on bodily information processing (i.e., is heavily embodied). Therefore, information processing could likely be performed in parts without embodiment, but under the pressures of naturalistic action, it is most ecologically rational to do so. Off-loading and constraining are the two main ways in which body and situation can perform information processing.

From a meta-theoretical perspective, LIME has the strength that it unifies two distinct research lines. Integrating theories is the hallmark of scientific progress (Kuhn, 1962; Schaffner, 1993), therefore we argue that solely on this point, LIME provides a valuable contribution. Beyond though, as demonstrated in the examples above, giving a common language to different fields allows them to communicate. It provides a common denominator to problems that are typically assessed on different levels of analysis, which should allow to extrapolate principles from one field to another. This commensurability and understanding between fields is likely to invite collaboration and cross-fertilizing ideas.

Conclusion

Whereas classical decision-making literature argued that the information processing load of real-life environments was too high and therefore cognition often failed (e.g., Tversky & Kahneman, 1974), or that in dealing with the high load, cognition consistently resorted to “fast-and-frugal” heuristic decision-making (e.g., Gigerenzer & Todd, 1999; Todd & Gigerenzer, 2000), we argue that mental information processing load can be reduced by letting the body perform it (for similar positions, see Clark & Chalmers, 1998; Raab, 2020; Voigt et al., 2025). In this sense, a more implicit contribution we have made in the current paper is that less-is-more is the aim to reduce mental information processing. With embodiment being the answer to this task, we posit that the information processing capacity of a body in action seems to be greater (albeit likely much less precise) than that of mental information processing (Clark, 2015; Shapiro & Spaulding, 2019).

Footnotes

ORCID iD

Jannis Friedrich

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Notes

Author Biographies

Jannis Friedrich works at the intersection of cognitive science and philosophy of mind. His, mainly theoretical, work centers on mental representations and how higher cognitive abilities can emerge in embodied agents. He has special interests in complexity sciences and predictive processing.

Patricia Grove is a PhD student at the Institute of Psychology at the German Sport University Cologne. Her research focuses on the psychological phenomenon reinvestment, particularly its psychophysiological underpinnings and its impact on performance. She is especially interested in how physiological variables influence reinvestment and aims to develop an intervention to mitigate its negative effects on motor-cognitive performance.

Maša Iskra is pursuing her doctorate at the Institute of Psychology, Department of Performance Psychology. Her PhD topic focuses on using the psychophysiological approach to study the effects of paced breathing on motor-cognitive performance and embodied cognition.

Sandra Ittlinger completed her PhD at the German Sport University in Cologne, specializing in applied performance psychology. In her research, she explores how psychological principles can be used to enhance performance in high-pressure environments. A central focus of her work lies in understanding the decision-making strategies of elite athletes — particularly how they make complex, rapid choices during competition and how these decisions are shaped by experience, context, and cognitive factors.

Lisa Koop is a PhD student at the German Sport University in Cologne. Drawing on her extensive career as a professional basketball player, her research focuses on the judgment and decision-making processes of sport officials and embodied cognition.

Markus Raab is tenured professor, head of the Department of Performance Psychology. Furthermore, he is currently editor in chief of Psychology, Sport and Exercise. His main interests are in judgment and decision making, motor learning and control and embodiment in sport psychology and beyond.

Laura Voigt holds a PhD in Psychology and has been the scientific coordinator of the Graduate School Embodied Choices Cologne at the Institute of Psychology of the German Sport University Cologne. Her research interests focus on understanding and improving decision making and acting in high-pressure settings. Her work ranges from laboratory experiments to field studies with specific target populations (e.g., athletes, police officers, medical personnel).

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