Research into the Brain: Implications for Game Design

Image courtesy of  Frenkieb on Flickr

There has been quite a bit of research into the effects of games on the brain.  For example, a study looking at the effects of playing Mario 64 by researchers from the Max Planck Institute for Human Development had very interesting findings.  The research found that those who played at least 30 minutes of Mario 64 every day for two months grew significant amounts of new grey matter in three areas of the brain.  The areas were correlated with spatial navigation, strategic planning, working memory, and motor performance.  The control group who did not play Mario, didn’t have the same growth (their grey matter actually decreased; attributed to ageing).  For a nice summary of the research, click here.

However, what can games designers learn from research into the brain?

A fantastic article by Ben Lewis-Evans looks at research into dopamine.  He concludes that while the research is interesting and may provide some insights, it is rarely applied and especially not to gaming.  He thinks it would be more useful for games designers to use observational data from test subjects playing their game, than looking to neuroscience for answers.  However he does say: “One exception could be that a theoretical neurological approach may be able to detect if a player was ‘wanting’ to play your game without consciously realising it (something that may indeed be possible)” and “All this said, if you are interested in knowing what your games may be doing to peoples brains, or perhaps you are working in serious games and want to see if games can improve (or worsen) brain function. Then, here, neuroscience can be valuable.”

While this seems negative, it is a powerful insight.  Ben discusses how people both over-use and over-trust the prefix ‘neuro’.  He urges us to be ‘neuroskeptical’ and not think something is more worthwhile just because it sounds scientific and important.  He thinks that while research into the brain may improve and be more useful in the future, at the moment it might be better to stick with observing people’s behaviours.  And what is wrong with that?  Most games designers won’t have access to laboratories and MRI scanners.  So, if games designers can try and use some premises of neuroscience, along with common understandings of people’s behaviours and observations, they should be suitably well informed where the brain is concerned.  And, if researchers do try to see the serious effects of games (as in the example above), that is great and could help to fill in some of the blanks and provide much sought after ‘evidence’ that games can have serious learning outcomes.

Ben also lists some of the findings from non-neuro research into the preferences/motivations etc. of gamers, which provide powerful insight and help for games designers.  Just because these findings weren’t obtained through peoples’ brains being hooked up to a machine, they are no less of an insight into the mind’s inner workings and human behaviour.  For example:

• Rewards that are unpredictable (loot drops) are generally more motivating than rewards that are predictable (100 xp per monster).
• Rewards should be meaningful, e.g. food is not particularly motivating for most people if you are already full, or if you are in a relatively visually sparse setting then new, unusual, stimuli will attract your attention more readily.
• People tend to have a preference for immediate rewards and feedback and are not so motivated by delayed rewards and feedback. This preference for immediate gratification is strongest when young, but persists throughout life.
• A predictor for a reward can serve/become a replacement for that reward in terms of behavioural response (e.g. getting points in a game becomes associated with having fun and points can therefore become a motivating reward in themselves).

For the full article and Ben’s list of sources, click here.

Image courtesy of Scott M on Flickr

I have referred to cognitive flow before in my article: “10 Resources on Creating your Own Learning Game”.  This is another area of research into the brain through observations, and it has many implications for game design.  Mihaly Csikszentmihalyi found that skill and task difficulty cause people to have different cognitive and emotional reactions to stimuli.  When their skill level is too low and the task is too hard, people become anxious.  However, if the task is too easy and their skill level is too high, people become bored. ‘Cognitive Flow’, like in the story of Goldilocks, is when skill level and difficulty are ‘just right’.

During this state, there are several effects.  For example, extreme focus on the task and the experience of the task itself being the justification for continuing it.  Csikszentmihalyi also defined four characteristics found in tasks likely to induce Flow states.  Tasks were likely to:

1. Have concrete goals with manageable rules.
2. Demand actions to achieve goals that fit within the person's capabilities.
3. Have clear and timely feedback on performance and goal accomplishment.
4. Diminish extraneous distraction, thus facilitating concentration.

This obviously has huge potential for games designers, and particularly for learning games designers.  A fantastic job of describing Flow in more detail and unpacking its implications for game designers has been done by Gamasutra here.

So, as you can see, observations into human behaviour and mental states can be powerful tools for game designers.  I couldn’t resist tagging this article about neuro-gaming onto the end of this blog post.  It looks at how future gaming technologies could tap into our whole nervous system and drive gameplay (brain wave data, emotional states, emotional recognition, pupil dilation etc.).

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