What is categorical perception of colour commonly taken to explain?
The diagram below represents sequences of three colours.
The vertical sequence shows three greens and the uppermost horizontal sequence shows a
blue, a purple and a pink.
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Each colour differs from its neighbours by the same amount according to a standard
measure based on the human eye's abilities to discriminate wavelengths.
Yet the greens are often judged to look quite similar and the blue-pink-purple to look very different \citep[p.\ 12--7]{Roberson:1999rk}.
When people are asked to name these colours, they often give the same name to the greens but different names to members of the blue-pink-purple sequence.
And people are generally faster and more accurate in discriminating between members of the blue-pink-purple sequence than members of the green sequence
(faster: \citealp{Bornstein:1984cb}; more accurate: \citealp[p.\ 22--7]{Roberson:1999rk}).
Let me show you how speed an accuracy of discimination are usually measured.
This is a 2-alternative forced-choice task (2AFC).
So far we've talked about three ways in which the blue-pink-purple sequence differs
from the greens.
The green sequence also differs from the blue-pink-purple sequence on other measures.
But these results are not confined to just two sequences.
There is a way of dividing a colour space into categories that predicts all of these
results and more.
When the members of a sequence of colours fall into different categories, the colours
are said to look very different, they are given different verbal labels, and the
subject can discriminate them faster and more accurately than when they don't fall
into different categories (all other things being equal).
The fact that, for an individual subject, all these effects are predicted by a single
way of dividing the colour space into categories is what categorical perception of
colour is supposed to explain.
- Reports of phenomenal similarity and difference
- Linguistic labels
- Speed and accuracy of discrimination
An ERP like the vMMN stands to an overall EEG measurement a bit like the number 78 bus does to a collection of atoms.
While we're on methods, let's quickly talk about fMRI.
So let me show you a task that uses this odd-ball effect
Fixate on this cross.
And when you see the rectangle, press the space bar with both index fingers.
That's it.
Except that you also see a block of colour on every trial.
You're instructed to ignore this block of colour.
And generally that's easy because it's always the same colour.
But just occasionally it's a different colour.
In one condition, the usual and odd-ball colours are the blues.
And in the other condition, the usual and odd-ball colours are cross-category, from blue-green.
We're interested in whether there's a sign that your brain has detected the change when the odd ball colour occurs.
Put roughly, the results show that there is signal of pre-attentive change detection at around 100-200 milliseconds in the left visual field.
This is another way of presenting the same finding.
The vMMN is a DRN, but not all DRNs are vMMNs (see the paper).
Since this study \citep{clifford_color_2010}, \citet{he:2014_color} have challenged
the results arguing that there is no vMMN when you control for irregularities in
colour spaces using JNDs. However \citet{zhong:2015_shortterm} find a vMMN for
newly trained categorical colour properties (which \citep{clifford:2012_neural}) didn’t.
For our purposes, it isn’t essential that there is a vMMN.
We should also be agnostic on whether categorical perception is pre-attentive.
For us the important point is that it’s automatic.
And all the studies agree on this.