# information in perception

**URL:** <http://discourse.iapct.org/t/information-in-perception/14028>\
**Category:** CSG1993\
**Created:** [March 16, 1993, 5:48am UTC](http://discourse.iapct.org/t/information-in-perception/14028 "1993-03-16T05:48:26Z")\
**Posts on this page:** 4\
**Page:** 1

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**Author:** ![Human\_Factors\_Lab](http://discourse.iapct.org/letter_avatar_proxy/v4/letter/h/b3f665/32.png) [@Human\_Factors\_Lab](http://discourse.iapct.org/u/Human_Factors_Lab)\
**Post date:** [March 16, 1993, 5:48am UTC](http://discourse.iapct.org/t/information-in-perception/14028/1 "1993-03-16T05:48:26Z")

</div>

[From Rick Marken (930315.2130)]

Avery Andrews (930316.1200)

> I don't think that people are all  
> necessarily as block-headed as Rick Marken thinks they are, but they  
> will act that way if the presentation isn't tailored to their current  
> state of mind.

If "block-headed" means stupid then I don't think that people who  
reject PCT are block-headed. In fact, I think most of them are very  
smart -- a lot smarter than me. If, however, "block-headed" means  
resistent to ideas that are disturbances to controlled perceptions  
then, yes, I think that people are "block-headed" simply because they  
are control systems. The peculiar disturbance resistant properties  
of a control system makes it impossible to get people to  
accept an idea that is a disturbance to a currently controlled  
variable. The reason that PCT has an acceptance problem is because  
most behavioral scientists (smart or not) are controlling for a variable  
that is disturbed by the concepts of PCT. I think the variable typically being  
controlled is something like "the input output model of behavior".  
But it might be something else.

Discovering this controlled variable is really why I am pushing  
this "information about disturbances" discussion with Martin  
and Allan. I believe that the idea that there is no information  
about disturbances in the perceptual input to a control system is  
very, very easy to understand -- even trivial. It requires no complex  
reasoning or the rejection of well understood physical principles. All  
it requires is a little, simple algebra (see below). But Martin and Allen  
are rejecting the idea that there is no information about disturbances  
in the perceptual input to a control system (by simply asserting that this  
just can't be so -- there must be such information) and I think they  
are doing this because this idea is a disturbance to their way of  
thinking about how living systems work. They believe that there  
must be something in the perceptual signal that can tell (inform,  
cause, guide, whatever) the output what to do. I think they consider  
this the only rational possibility because it is the only rational possibility  
if you are dealing with an input-output device (like a computer). In other  
words, I think they are not getting this very simple idea (no information  
about disturbances in the percetual input) -- not because they are  
stupid or bull headed -- but because this idea is a disturbance to their  
input-output view of behavior.

The fact that there is no information about the disturbance in the  
perceptual input to a control system can be easily seen from examining  
the formula for this input:

(1) p(t) = d(t) + o(t)

What the control system perceives (and controls) is a time varying signal,  
p(t) that is at any instant the result of the combined effects of an  
indepedent disturbance variable, d(t) and an output being generated  
by the system itself, o(t). All the system perceives is p(t); it has no  
way of knowing "how much" of p(t) is at any instant the result of d(t)  
or o(t). In other words, it has no information about d(t) -- all it has  
is p(t). Nevertheless, it generates outputs, o(t) that are a precise mirror  
or d(t) -- something that can only be determined by an observer of the  
system:

(2) o(t) = -k d(t)

The system does this, not by "seeing" information about d(t) in p(t) and  
generating the appropriate output o(t) in response to this information;  
that is, o(t) is not generated the way it is described algebraically in  
equation (2). Rather, o(t) is generated as the result of a comparison  
between p(t) and a (possibly zero) reference value;

(3) o(t) = g(r - p(t))

This output is generated in a loop and each change in o(t) -- in a  
dynamically stable loop -- 'nudges' p(t) closer to r. So the loop is  
continuously generating o(t) values proportional to the existing error  
which tends to move the existing error to zero. A "side effect" of this  
process is that o(t) happens to be a mirror of d(t) (eq. 2). But the loop  
doesn't "know" anything about the form of the function d(t) -- this is  
the sense in which there is no information about d(t) in the input.  
There is no information about d(t) because the closed loop doesn't "care"  
what causes p(t) to vary ; all that the loop does is generate o(t) (which it  
also has no information about) which tends to cancel out whatever is  
causing p(t) to move away from r.

The appropriate way to describe this process is "control of perception".  
Perception, p(t), has no control over anything; it just IS. Perception  
does not "inform" the system about what to do; nor do variations  
in perception (when the perception is affected by the outputs of the  
system) contain any information about the causes of that variation --  
that is, to what extent the variations are a result of disturbance or output.

I suspect that Martin and Allen will still want to defend the idea that  
there is information in p(t) which guides o(t). I, of course, will resist  
this defense because I am controlling for my understanding of the  
operation of a control system. All I can say is that their defense will  
be most effective if they can tell me how I can find the information  
in p(t) that will allow me to reconstruct the d(t) that was (partially) the  
cause of p(t) (see eq. 1). As I have said before, I have already tried one  
approach to finding the information in p(t); and I found no  
such information. What I found was that

o1(t) = o2(2) when d1(t) = d2(t) even though p1(t) \<\> p2(t)

where the 1's and 2's index the tracking trial during which these functions  
were obtained. In fact, the equality o1(t) = o2(2) was not perfect;  
the correlation between o1(t) and o2(2) was typically .997865 or so.  
Similarly, the inequality, p1(t) \<\> p2(t) is not perfect -- the correlation  
between p1(t) \<\>and p2(t) was not zero -- it was .0032 (or more, but never  
much greater than .2).

I think that Martin and Allan would have to claim that, in the tiny  
little correlation between p1(t) and p2(t) is the common "information"  
that is used to guide o1(t) and o2(t) -- making them approximately equal;  
I say that Martin's and Allen's position (that there is this information  
about d(t) in p(t)) invokes "magic" and, thus, I propose A NEW CHALLENGE:

I challenge Martin and Allan (and anyone else) to show me how to get  
the information about d(t) out of p(t) and reconstruct d(t) from it. I  
would bet a LOT of money that such a reconstruction algorithm will NOT be  
forthcoming --- but I think betting on the net is probably frowned upon  
-- so how about a big, embarassed concession from me when I get the  
algorithm and construct my first d(t) from the p(t) of your choice. The  
only caveat is that the reconstructed d(t) [call it d'(t)] represent the  
actual d(t) just as well as o(t) did in the actual run of the experiment.  
That is, the correlation between d'(t) and d(t) should be about the same as  
the correlation between d(t) and o(t).

Best

Rick

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<div class="post-metadata">

**Author:** ![\_Martin\_Taylor](http://discourse.iapct.org/letter_avatar_proxy/v4/letter/_/a9adbd/32.png) [@\_Martin\_Taylor](http://discourse.iapct.org/u/_Martin_Taylor)\
**Post date:** [March 16, 1993, 3:37pm UTC](http://discourse.iapct.org/t/information-in-perception/14028/2 "1993-03-16T15:37:41Z")

</div>

[Martin Taylor 930316 10:20]  
(Rick Marken 930315.2130)

> The peculiar disturbance resistant properties  
> of a control system makes it impossible to get people to  
> accept an idea that is a disturbance to a currently controlled  
> variable.

We (Martin and Allan) are not in that group, but we recognize, all too well,  
that people do exhibit resistance to disturbances of cherished perceptions,  
and that we, like you, are people.

> But Martin and Allen  
> are rejecting the idea that there is no information about disturbances  
> in the perceptual input to a control system (by simply asserting that this  
> just can't be so -- there must be such information) and I think they  
> are doing this because this idea is a disturbance to their way of  
> thinking about how living systems work.

I could very easily paraphrase this with only changes from "Martin and Allan"  
into "Rick" and deleting the word "no" in the second line. What good  
would it be to do so, except to point out the symmetry of the situation?

However, there are substantive comments that can be made.

> (1) p(t) = d(t) + o(t)
> 
> What the control system perceives (and controls) is a time varying signal,  
> p(t) that is at any instant the result of the combined effects of an  
> indepedent disturbance variable, d(t) and an output being generated  
> by the system itself, o(t). All the system perceives is p(t); it has no  
> way of knowing "how much" of p(t) is at any instant the result of d(t)  
> or o(t). In other words, it has no information about d(t) -- all it has  
> is p(t)

Fine, except that the last sentence is a non-sequitur. It indicates that  
the core of the argument is a misunderstanding about the nature of  
information. p(t) = d(t) + o(t), and therefore p(t) contains information  
derived from d(t). This in no way implies that d(t) can be recovered  
from p(t) without knowledge of (as distinct from information from) o(t).

> Nevertheless, it generates outputs, o(t) that are a precise mirror  
> or d(t)

That word "precise" is an argument killer. o(t) is NOT a precise mirror  
of d(t). It differs by an proportion that is roughly 1/Gain. In an  
integrating control, 1/Gain approaches infinity at infinite time, and  
then you can talk about o(t) being a precise mirror of d(t), but only  
if no disturbing "events" have happened in the interim. You can't use  
infinite gain without going to zero bandwidth, because otherwise you would  
be infinitely amplifying the least little noise in the comparator or  
perceptual input function. That again is a question of information.

> But the loop  
> doesn't "know" anything about the form of the function d(t) -- this is  
> the sense in which there is no information about d(t) in the input.

I'll certainly go along with this sense. But it is irrelevant to the  
points Allan and I have been trying to get across.

> All I can say is that their defense will  
> be most effective if they can tell me how I can find the information  
> in p(t) that will allow me to reconstruct the d(t) that was (partially) the  
> cause of p(t) (see eq. 1)

I have no intention of defending the straw man Rick posts for me to defend,  
but as I mentioned to him privately, this question is quite interesting  
in its own right, and some day I'd like to look into it, if no-one else  
has done so and if it doesn't fall out of the information-theory analysis  
of the control loop.

If I could hazard a guess, the imagination loop is going to figure quite  
strongly in the solution.

Martin

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<div class="post-metadata">

**Author:** ![Marken\_Richard\_S1](http://discourse.iapct.org/letter_avatar_proxy/v4/letter/m/977dab/32.png) [@Marken\_Richard\_S1](http://discourse.iapct.org/u/Marken_Richard_S1)\
**Post date:** [March 16, 1993, 11:43pm UTC](http://discourse.iapct.org/t/information-in-perception/14028/3 "1993-03-16T23:43:42Z")

</div>

[From Rick Marken (930316.1400)]

Martin Taylor (930316 15:30)--

> I give up.

Aw. Common. We're workin' on it.

> Every attempt at explanation is gobbledygook or  
> plain wrong.

Well, every time I say something you don't understand it's a  
non-sequiter -- but I keep tryin'.

> It's obvious that there is NO explanation that will suffice,  
> other than simple capitulation.

That is not true (for me). I just want an explanation of where  
the information is in p(t). If there is no way to get at that  
information or if it is unusable then I want to know why you  
think it is so important. I just want to know what you (and Allan)  
are trying to say. Believe me, your claim that there is information  
about the disturbance in p(t) sounds just as crazy to me as my claim  
(and Bill's) that there is NO such information in p(t) appears to  
sound to you.

> So, for the purposes of clearing the  
> CSG airwaves, I capitulate,

That avoids it; it doesn't clear it.

> and will continue this information-theory  
> discussion with Bill Powers separately. At least Bill and I can see  
> common ground, even if we don't yet have a common understanding.

I look forward to that discussion; but I warn you; Bill P. may  
seem seem a lot nicer than me, but he understands PCT just as well  
as I do (he he). So you will still be stuck with the problem of  
explaining why you think there is information about anything (let  
alone the disturbance) in p(t).

> With Rick, as soon as there appears to be the possibility of common  
> ground, the rug gets whipped away to reveal a chasm. I don't like  
> that style of argument. T'is so, t'aint so. Stupid.

It's not a style of argument; it's an approach to knowledge. I'm  
all for common ground when that ground is, indeed, common. But  
I can't agree with something that just flat out contradicts a basic  
tenet of the PCT model. If what I hear from you just seems wrong  
because of our disparate ways of using language then let's try to  
work that out -- and the only way I know of to get past language is  
to agree on what experiences we expect our models to produce in  
agreed on circumstances. I've described my attempt at a demo of  
lack of information in p(t). You have never said what is  
wrong with that demo (described in chapter 3 of Mind Readings)  
or what the appropriate demo would be to show that there is  
information in p(t).

> For an example, one final quote from Rick:

> > What does the lack of precision that comes from having a loop gain  
> > of 1,000,000 instead of infinity have to do with INFORMATION.

> Everything.

I'm willing to believe this, really. It's just not obvious at all  
to me. I am really trying to understand you. Could you please get  
quantitative; what is the information in p(t) that exists when the  
loop gain is less than infinity but is gone when it is infinity.  
Since most real control systems have loop gains that are considerably  
less than infinity it should be easy to explain how I could set  
up a control demo that would convince me that there is information  
in p(t); show me how to do it.

Best

Rick

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<div class="post-metadata">

**Author:** ![Human\_Factors\_Lab](http://discourse.iapct.org/letter_avatar_proxy/v4/letter/h/b3f665/32.png) [@Human\_Factors\_Lab](http://discourse.iapct.org/u/Human_Factors_Lab)\
**Post date:** [April 3, 1993, 6:42pm UTC](http://discourse.iapct.org/t/information-in-perception/14028/4 "1993-04-03T18:42:14Z")

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[From Rick Marken (930403.1000)]

Kent McClelland. How nice to hear from you -- and on a nice new  
topic too. Stay tuned. I will have a comment on your sociology  
post later this (one hour short) weekend; promise.

First, I would like to propose MY solution to the "information  
about the disturbance in perception" debate. Perhaps I can  
make both sides happy with this proposal:

1) There IS information in the perceptual signal of an ECS! (Happy  
IT people?). It is information in the IT sense, in that it reduces  
the receiver's uncertainty about the message being sent. All the  
theoretical paraphenalia of IT is, thus, relevant to PCT.

2) The information in the perceptual signal is about the REFERENCE  
SIGNAL, NOT THE DISTURBANCE. The state of a controlled perception,p,  
in a hierarchy of control systems is information that can be used by  
other control systems in the hierarchy to determine the value of the ref-  
erence signal being sent to the system controlling p. MOST IMPORTANT:  
the state of the perceptual signal is information that can be used by  
an OBSERVER of the control system (an observer who has access to p or  
to an observable correlate thereof) to determine the value of the control  
system's reference setting for p.

This solution opens up the possibility of an IT approach to doing  
The Test for the controlled variable. In The Test, an observer  
(the experimenter) wants information about 1) what p corresponds  
to in the observer's own perception and 2) what the reference level  
is for p. We can only get information about r (goal 2) if we have  
properly defined the perception, p. IT might be able to contribute  
to our ability to quantify The Test -- ie. measure how much infor-  
mation we are getting about r from our current hypothesis about  
the observable corelate of p.

How's this?

Best

Rick