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James Lawley

James LawleyJames Lawley is a UKCP registered psychotherapist, coach in business, and certified NLP trainer, and professional modeller. He is a co-developer of Symbolic Modelling and co-author (with Penny Tompkins) of Metaphors in Mind: Transformation through Symbolic Modelling. For a more detailed  biography see about us and his blog.

 
Monkey see, monkey don't
By James Lawley | Published  24 01 2011

“According to new work from researchers at the University of Bristol in England, it is not  our peers’ successes that stick with us, but their failures” so says Nikhil Swaminathan in the current issue of Scientific American Mind. He reports that when volunteers played a simple computer game and they saw their competitors get an unexpectedly high reward, functional MRI scans showed no measurable brain activity. But when they got an unexpectedly low payout parts of a player’s brain associated with inhibition were excited.

Paul Howard-Jones, who co-led the study with Rafal Bogacz. notes that while the computer was making its move, the player’s mirror neuron system—which is known to respond to the actions of others—was active, as if the player was making the same choice. When that action led to failure, the inhibitory areas put an immediate stop to the mental simulation. Howard-Jones says this is the first time that researchers have seen people show a mirror neuron response to an action performed by a computer (the players were aware that their opponent was simply software).

This research suggest while we can learn by acting like someone, we can also learn to not act like them when they fail. This has implications for modelling, especially the ‘unconscious uptake’ method championed by John Grinder.

Like many studies, this research used clear success/fail criteria. In the real world success/failure can be much more difficult to discern. We normally model people who can do something much more excellently than ourselves. How do we know whether they are succeeding or not?

I say to people learning Symbolic Modelling that they will need to re-calibrate their signals for when the process is, or s not, working well. While some of the general-context signals applicable to traditional therapy, counselling and coaching map over to clean facilitation, many of detailed-context signals are counter-indicated in Symbolic Modelling.

The vast majority of books, audios and videos of facilitators working with clients (including ours) show successes, and usually one session successes at that. This research suggests we are missing out by leaving the ‘failures’ on the cutting room floor.

David Grove was an exception. During his workshops he would be quick to point out his own ‘mistakes’. This taught me two important lessons. First, even the master occasional misjudges the situation, so perhaps the student shouldn’t feel too bad when he does also. Second, and more importantly, I learned how David instantly learned from and utilised his ‘errors’ – often discovering something unexpected yet beneficial.

To his credit, David featured a spectacular mistake in one of early videos known as ‘Jesse’. David mistakenly thinks that beautiful flowers in the garden of the client’s inner child are a resource. In fact, each flower symbolised a sexual abuse by the kind and otherwise loving Jesse, the gardener. Once David realised from the client’s reaction his error he took steps to recovered and the session continued. David decided to publish the video because his desire for others to learn was greater than his embarrassment at his mistake.

What can we learn from this? In the land of idiosyncratic metaphor we cannot assume a symbol has a traditional meaning. Also that, what Judy Rees and Wendy Sullivan call, ‘mismodelling’ is always a possibility. We need to carefully calibrate the client’s responses and remain vigilant since we, like everyone else, are subject to ‘confirmation bias’.

Finally, the article sounds a word of caution:

Marco Iacoboni, a mirror neuron expert at the University of California, Los Angeles, who was not involved with the study, cautions that fMRI’s resolution is not fine enough to distinguish whether the neurons firing are mirror neurons or just motor cortex neurons, which fire both when we think about an action and when we actually perform an action. Even if the computer is simply recruiting a player’s motor neurons, however, that is still a compelling finding. “It’s really a mechanism for why we anthropomorphize pretty much everything,” Iacoboni says. “We tend to mentalize even things that we know have no mind.”

Reference

‘Monkey See, Monkey Don't: We learn from our competitors' failures by not repeating them’, Nikhil Swaminathan, Scientific American Mind (Jan/Feb 2011)
 www.scientificamerican.com/article.cfm?id=monkey-see-monkey-dont

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