Finding Beauty in Effortlessness: How Our Brains Prefer Energy-Efficient Visuals

There’s something captivating about gazing at a serene sunset or a star-filled night sky that can hold our attention for hours. These natural scenes aren’t just visually pleasing—they might actually be gentle on our brain’s energy consumption. Recent research published in PNAS Nexus reveals that humans tend to prefer looking at visual stimuli that require minimal cognitive effort to process, suggesting an intrinsic connection between aesthetic preferences and neural efficiency.

Our brains are extraordinary energy consumers, using more calories proportionally than any other organ in the body. Visual processing alone accounts for nearly half of the brain’s total energy expenditure, making it one of our most metabolically expensive cognitive functions. This metabolic reality has led researchers to explore an intriguing possibility: perhaps our sense of beauty is partially shaped by our brain’s desire to conserve energy. “Not only is the visual system optimized for efficiency, but we might have aesthetic preferences for stimuli that are efficient to process,” explains Mick Bonner, a neuroscientist at Johns Hopkins University not involved in the study. This perspective offers a new evolutionary lens through which to understand beauty—as cognitive shortcuts that help organisms navigate their environment while minimizing unnecessary mental effort.

To investigate this connection between visual processing costs and aesthetic preferences, researchers led by Dirk Bernhardt-Walther at the University of Toronto utilized functional MRI data from four individuals who viewed 5,000 different images while their brain activity was monitored. By measuring oxygen consumption across different brain regions, the team could estimate the metabolic activity required for processing each image. They also employed an artificial neural network trained in object and scene recognition to provide a computational model of processing effort. These objective measurements were then compared with subjective aesthetic ratings of the same images gathered from over 1,000 online survey participants who scored each picture on a five-point scale. The results were striking: both in human brains and artificial systems, images that required less metabolic effort to process consistently received higher aesthetic ratings.

This relationship between energy efficiency and aesthetic appeal was most pronounced in high-level visual processing regions of the brain—areas responsible for complex recognition tasks rather than simple feature detection. The fusiform face area, which specializes in face recognition, showed particularly strong correlations between lower metabolic activity and higher aesthetic ratings. According to Bernhardt-Walther, this suggests that energy savings occur primarily during advanced stages of visual processing such as object recognition, rather than in earlier stages like detecting edges or contrasts. The parallel findings in artificial neural networks further strengthened this conclusion, as deeper layers of the network (corresponding to higher-level processing) showed similar patterns.

This metabolic efficiency theory helps explain several well-established aesthetic preferences. For instance, previous research has shown that people generally prefer faces and even objects like cars that closely resemble the average or prototypical version rather than unusual variants. Bernhardt-Walther suggests this occurs because outliers force the brain to expend additional energy updating its internal models of what constitutes a typical face or car. The familiar requires less cognitive restructuring, making it more metabolically efficient and consequently more aesthetically pleasing. This principle extends beyond visual experiences to other cognitive domains as well. Consider the satisfaction that comes from solving a challenging puzzle after considering multiple possible solutions—the “aha!” moment delivers pleasure precisely because it marks a sudden decrease in cognitive effort.

While this research offers compelling insights into the relationship between brain metabolism and aesthetic experience, important questions remain unanswered. Bonner points out that future studies should determine whether metabolic costs directly cause aesthetic preferences, or if both stem from shared underlying features such as familiarity with certain visual patterns. Additionally, researchers still don’t fully understand which specific properties make some images more pleasing and efficient for brain processing than others. “What precisely makes an image easier for the visual system to process remains a huge open question,” Bonner notes. By continuing to explore these connections between neural efficiency and aesthetic experience, we may gain deeper insights into why beauty captivates us and how our perception of it has evolved alongside our brain’s constant quest for energy conservation.