Learn to pay attention

June 8, 2011

(Medical Xpress) -- A new scientific theory on what we learn to pay attention to and what we learn to ignore could turn 30 years of research on its head.

Research by Dr Mark Haselgrove from The University of Nottingham (UK), and Dr Guillem Esber from the University of Maryland (USA), challenges two long held and contradictory theories on which cues our brains use to predict events of significance.

The theory, published today (Wednesday June 8 2011) in the journal , has important implications for the psychology and of attention. It has implications for our understanding of how uncertainty, such as the uncertainty surrounding a risky investment, may bias our attention. Furthermore, by advancing the theoretical basis of how learning influences attention, this research may inform our understanding of what happens when the allocation of attention is inappropriate, such as occurs in such as .

Dr Haselgrove said: “Animals, and that includes humans, spend a great deal of their waking hours learning about and using cues to predict events of significance — such as food, danger, or the opportunity to have sex. One question that has long captivated the imagination of psychologists is how animals come to attend to the appropriate cues. Decades of research have singled out two variables — predictiveness and uncertainty — as key factors in determining how much attention animals and humans pay to a cue.”

It turns out that existing theories that have tried to explain the influence of these two variables on attention are contradictory. One theory suggests attention is captured by cues that are good predictors of significant events — to enable animals to work out what cues are relevant to them. The rival theory argues instead that attention is applied where it is most needed — to cues that may or may not be followed by events of significance — that is to say, to cues that possess uncertainty. Both of these theories seem intuitively plausible and have scientific evidence to back them up but they are, unfortunately, contradictory.

“Can the really be wired up to attend to the world in two contradictory ways?” asks Dr Haselgrove. “Surely there must be a resolution to this problem.”

Dr Esber said: “The basis for solving the problem is to appreciate that uncertainty can be thought of as another type of predictiveness. For example, the ripples on a lake caused by a fish under its surface may frequently help a hungry heron in his hunt and will be associated with a tasty meal. However, the fish will sometimes be too quick for the heron, or the ripples will be caused by the wind — and the heron will go hungry. Although the ripples can be thought of as an uncertain cue for fish, they are in fact predictive of two things: the satisfaction associated with a tasty meal, and the frustration that accompanies hunger.”

In other words, uncertainty is a situation where a cue is predictive of two opposite events.

From this insight Dr Haselgrove and Dr Esber were able to apply the principles of associative learning that have developed since the time of Pavlov’s investigations into conditioned reflexes to devise an entirely new explanation for how learning influences in animals and importantly resolve the contradiction between and predicitiveness.

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5 / 5 (6) Jun 08, 2011
Other than tell us that "uncertainty is a situation where a cue is predictive of two opposite events" this article - unless I am totally missing the point - stops short of actually telling us anything about Dr Haselgrove's and Dr Esber's "new explanation for how learning influences attention in animals and importantly resolve the contradiction between uncertainty and predicitiveness".
1 / 5 (1) Jun 08, 2011
Pure bullshit. Why?
Before Dr.Haselgrove or Dr Esber open their mouths, let us first be blessed with an EXACT, WORKING, UNIVERSAL DEFINITION of "to learn".

Preferably in AXIOMATIC form.
I'm waiting, gentlemen. No?
Thought so. Bye, bye gentlemen.
not rated yet Jun 13, 2011
I did not read the original article but the things they declare has been explained in detail in a previous article. "Shohamy D., Myers C. E., Kalanithi J., Gluck M. A. (2008). Basal ganglia and domapine contributions to bprobabilistic category learning. Neuroscience and Biobehavioral Reviews, 32, 219-236"
It is freely reachable through ScienceDirect.
5 / 5 (1) Jun 13, 2011
Drcandanesin: There is some similarity between the model described by Esber and Haselgrove (2011) and those described by Shohamy et al (2008) - both use variants of the Rescorla-Wagner model, for instance. But the applications are to rather different problems. E-H model is looking at how you can use such models to increase attention to relevant and uncertain cues using one mechanism, a problem that in the past that has required two mechanisms. I'm surprised you think the things declared in the press release are so similar to Mark Gluck's work. I had another look at their paper, and the overlap between the work they cite and the work we cite is rather small.

hush1: Nice troll.

Peteri: Take a look at the original model. If you google the name of the second author (Mark Haselgrove) you can link to the appropriate webpage and acquire a pdf. (I would place a link here, but I think such posts get deleted by the moderator.
1 / 5 (1) Jun 13, 2011

You have been here three days?
What is your theoretical basis of learning?

"Reconciling the influence of predictiveness
and uncertainty on stimulus salience:
a model of attention in associative learning."


My model avoids any and all forms of salience.
Yes, that is simply beyond incredulous. Simply preposterous.
My evidence?

You are literally looking at the resolution to any contradiction. Salience or otherwise.

I am more than willing to contact you. You can dismiss me after a 1 minute phone call at my cost. I am not looking for any recognition or credit for the model I have. If you want it, it's yours.

Simply post here again with the words: no interest.
I don't need a bigger hint to waste your time. I will simply turn to another until I am shown a irreconcilable flaw or insufficiency in my model.

And forget my Diss. I have no excuse for it. Only an explanation. I have read too much nonsense.
not rated yet Jun 14, 2011
Mr. Haselgrove,
Yes.When I read your original article I realised I misinterpreted what is written in the news. Sorry and thank you for your kind enlightenment.
not rated yet Jun 14, 2011

Take a look at the publication and you will see that our theoretical basis for learning is a standard prediction error algorithm of the kind found in Rescorla & Wagner (1972), Pearce and Hall (1980), and other general process models of association formation.

I am interested to learn that your model avoids any and all forms of salience, particularly when we have known for some time that variations in stimulus salience have an impact on learning (e.g. Kamin & Schaub, 1963).

Have you written a desription of the model? I am happy to take a look at it. My contact details are on the paper.

not rated yet Jun 14, 2011
Thank you for your reply and your interest to take a look. For the diss, an apology. I will contact you.

not rated yet Jun 14, 2011
Not everyone is born to bear the burden of changing current theory. No matter how good or watertight the alternative.
I make no judgement, whatever your take on this.
Expect an email. Phoning, although attempted, runs the risk of taking time away from your clientele.
not rated yet Jun 17, 2011
Email send. Await email.
Thank you for your interest.

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