Movement helps us to think creatively


Movement helps us to think creatively. This insight is over 2000 years old – and already known to the philosophers in ancient Greece.

However, what is the connection between movement and cognition from a scientific point of view?

What happens in the brain when we walk?

Are people who rarely move less creative?

“Our research shows that it is not movement per se that helps us to think more flexibly,” says neuroscientist Dr. Barbara Händel from Julius-Maximilians-Universität Würzburg (JMU) in Bavaria, Germany. Instead, the freedom to make self-determined movements is responsible for it.

Accordingly, even small movements while sitting can have the same positive effects on creative thinking. However, the researcher does not derive any concrete movement suggestions from her work: “The important thing is the freedom to move without external constraints.”

Don’t stare at small screens for too long

It is important, she says, that movement is not suppressed or forced into regular patterns. “Unfortunately, this happens when people focus for example on a small screen,” explains the JMU researcher.

The increased use of mobile phones and similar devices—also in the field of education at the time of the Corona pandemic—could therefore have a negative effect on cognitive processes such as creativity.

The experiments that Barbara Händel and her doctoral student Supriya Murali conducted are described in detail in a recent publication in the journal Psychological Research.

Anecdotal literature suggests that creative people sometimes use bodily movement to help overcome mental blocks and to get deeper into a problem. Indeed, the philosopher Henry David Thoreau stated: “the moment my legs begin to move my thoughts begin to flow – as if I had given vent to the stream at the lower end and consequently new fountains flowed into it at the upper” (Thoreau, 1851).

Several studies have indeed shown that physical exercise in healthy adults may sometimes enhance creative thinking – even though the size of this effect can vary substantially (Gondola and Tuckman, 1985; Gondola, 1986, 1987; Steinberg et al., 1997; Blanchette et al., 2005).

Gondola and Tuckman (1985) investigated the effects of long-term physical exercise on creativity performance, showing small but significant improvements in Alternate Uses (spontaneous flexibility) and Remote Consequences (originality) tasks, but not for an Obvious Consequences (different ideas) task.

Gondola (1986) used the same creativity tasks to compare the effect of long-term and acute physical exercise and found improvements for both conditions and all three creativity measures. Gondola (1987) tested another form of acute aerobic activity (dance) and reported comparable enhancing effects. Steinberg et al. (1997) found only small improvements in a group of fit participants, and only in one of the three measures of the Torrance test of creative thinking.

Blanchette et al. (2005) used the same test and found enhancing effects of exercise over a 2 h period. It is possible that in some or all of these previous studies physical exercise provided the opportunity for mind-wandering or incubation in trained (and, thus, less challenged) people. Indeed, Baird et al. (2012) have reported that engaging in simple external tasks that allow the mind to wander may facilitate creative problem solving.

The methodological diversity across the available studies with regard to sample characteristics and creativity assessment (mainly targeting aspects of divergent thinking) is considerable, which renders it questionable whether they were actually assessing the same constructs and processes. Moreover, there is still no mechanistic model explaining how creative processes operate and how physical exercise might affect these operations.

To address this issue, we tried to avoid addressing creativity as a whole but focused on particular components of creative performance – components that are more transparent at the process level and thus easier to investigate. More concretely, we investigated the impact (during and after) of acute moderate and intense physical exercise on creativity tasks tapping into convergent and divergent thinking. Guilford (1950, 1967) has considered these two as the main ingredients of most creative activities, even though other processes are also likely to contribute (Wallas, 1926).

Divergent thinking is taken to represent a style of thinking that allows many new ideas being generated, in a context where more than one solution is correct. The probably best example is a brainstorming session, which has the aim of generating as many ideas on a particular issue as possible. Guilford’s (1967) alternate uses task (AUT) to assess the productivity of divergent thinking follows the same scenario: participants are presented with a particular object, such as a pen, and they are to generate as many possible uses of this object as possible.

Convergent thinking, in turn, is considered a process of generating one possible solution to a particular problem. It emphasizes speed and relies on high accuracy and logic. Mednick’s (1962) remote associates task (RAT) that aims to assess convergent thinking fits with this profile: participants are presented with three unrelated words, such as “time,” “hair,” and “stretch,” and are to identify the common associate (“long”). Interestingly for our purposes, performance on the AUT and the RAT were found to be uncorrelated (Akbari Chermahini and Hommel, 2010) and differently affected by the same experimental manipulations (Hommel et al., submitted), which supports Guilford’s (1967) suggestion that convergent and divergent thinking represent different, separable components of human creativity.

Such a scenario would fit with considerations of De Dreu et al. (2008), who proposed the Dual Pathway to Creativity model suggesting that creative performance arises from the interaction between cognitive flexibility and cognitive persistence – two dissociable cognitive control functions (Goschke, 2000; De Dreu et al., 2012). Consistent with this, divergent thinking was less pronounced in avoidance-motivated than in approach-motivated individuals, suggesting that the former need to compensate for their inflexible processing style by effortful and controlled processing (Roskes et al., 2012).

Along the same lines, Colzato et al. (2012) have argued that convergent thinking requires strong top-down control because it represents the tightly constrained search of very few or just one item. In contrast, divergent thinking should rely on weak top-down control, given that it implies a broad, loosely defined search space so to activate many items that satisfy the often relatively soft criteria (Hommel, 2012). Hence, convergent and divergent thinking are likely to differ in their reliance on executive control for the processing of information.

If so, acute exercise should affect these two processes differently. According to the ego-depletion hypothesis (Baumeister et al., 1998), the cognitive resources required for cognitive-control operations are tightly limited and thus deplete quickly during and after control-demanding tasks. Following a similar, though more motivational rationale, Inzlicht and Schmeichel (2012) have developed a process model to explain self-control failure.

According to that model, “exerting self-control at Time 1 reduces success at self-control at Time 2 by initiating shifts in motivation and attention that conspire to reduce self-control and increase immediate gratification” (p. 460). According to this reasoning, poorer self-control at Time 2 is attributed to reduced motivation to exert control and to reduced attention to cues that signal a need for control, as well as more impulsive behavior and more attention to reward cues. Given that exercising must use up some amount of control resources, more control-demanding tasks (like convergent thinking) should suffer more from exercise than less control-demanding tasks (like divergent thinking).

However, how resource-hungry exercise should not only depend on the kind of exercise (e.g., the complexity of the coordination required) but also on the skill level of the exercising individual. The same exercise that exhausts the resources of the less sportive student may have little impact on the highly practiced athlete. In athletes, many movement routines are overlearned and automatized, which can lead to dramatic reductions of conscious monitoring and control demands (Beilock and Carr, 2001; Schneider and Chein, 2003). Moreover, long-term fitness training leads to an increase of oxygenation and glucose in the frontal brain regions, which has been found to produce rather selective benefits for executive-control processes (Colcombe and Kramer, 2003). This means that athletes may not exhibit the same effects as non-athletes. While the latter should show exercise-induced costs in more control-demanding tasks (like convergent thinking), the former might either not show such costs or perhaps even show exercise-induced benefits.

To investigate these possibilities, we tested the impact of acute physical exercise on convergent and divergent thinking in athletes and non-athletes. We also took into account possible moderating factors, such as the intensity of the exercise (which was moderate or high, in different sessions) and the temporal overlap between exercise and creativity task (with the latter being performed during or after the exercise).

reference link:

Original Research: Open access.
Motor restrictions impair divergent thinking during walking and during sitting” by Supriya Murali et al. Psychological Research


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