From Aaron Sloman Tue May 29 18:44:02 BST 2007
To: PSYCHE-D@LISTSERV.UH.EDU
Subject: Re: Decomposibility and recomposibility of conscious content
Arnold Trehub wrote:
> This is only one of several papers by this group that give evidence of
> single-neuron selectivity/categorization of complex stimuli. Other findings
> include, for example, Kreiman, Koch, and Fried (2000), *Nature Neuroscience*,
> and Quiroga, Reddy, Kreiman, Koch, and Fried (2005), *Nature*. Many other
> investigators, as well, have found *selective* single-cell responses to
> complex input patterns.
> ...
> Of course, all of the relevant cells that are involved from the input pattern
> to the detection/recognition of the input are part of the processing activity.
> But the question at issue is the claim that a single cell can *process* its
> proximal input to provide a selective and reliable recognition signal of the
> distal sensory pattern. Jonathan, I, and many other investigators claim that
> the activity of a single neuron can be a reliable indicator of a particular
> pattern of stimulation.
I guess this raises some questions:
what follows from this?
and
what does it have to do with what can be said about states
of the whole animal - e.g. such as that it recognizes something
or takes a decision?
I'll address those questions in an analogy below.
[Arnold]
> Consider this simple case:
>
> - There are two different input patterns, [A B] and [B A].
> - There are two detection neurons, (C1) and (C2).
> - Patterns [A B] and [B A] provide synaptic input to *both* detection neurons.
> - However the synaptic structure and dynamics of (C1) and (C2) differ so that:
>
> [A B] +++> (C1) (discharge) and [B A] ///> (C2) (no discharge)
> [B A] +++> (C2) (discharge) and [A B] ///> (C1) (no discharge)
>
> In such a case, the single cells clearly *process* their inputs to provide
> a selective detection/recognition response. This is analogous to the much
> more complex pattern recognition involved in the studies mentioned above.
Fair enough. But what makes the firing count as 'detection', or
'recognition' ?
Those are terms that have implications regarding the function that
the processes serve within the larger system. What that function is
can depend on many different things, including the causal
consequences of the firing.
Suppose someone asks about some country C
Q1. How does C choose its president?
Q2. How does C choose its favourite make of car?
These are questions about very different forms of information[*]
processing.
The answer to Q1 usually refers to a formalised, centrally
controlled, process of counting votes; and normally there is an
explicit recognition of the result of that process (i.e. the
selection of an individual) by some formal mechanism which makes the
result generally known to many other parts of the system.
The answer to Q2 need not involve any formalised, centrally
controlled, process and there need not be any explicit recognition
of the result, e.g. if nobody collects all the statistics.
But there may still be a make of car that is chosen more often than
any other make in millions of individual decisions, and those
choices can have all sorts of consequences, e.g. some manufacturers
going out of business, people becoming unemployed, some companies
growing, share prices changing, flows of capital across national or
regional boundaries, changes in total fuel consumption, numbers of
deaths on roads, etc. Many of those things can be going on without
anyone knowing that they are all going on (though individual
events, like a company going out of business would be noticed).
Many biological systems seem to be like that: lots of things going
on but without any centralised control or summarisation.
In some countries the information about car-buying may be available
in principle, but not actually collected, or collected but not used,
etc.
E.g. we can distinguish cases where the information cannot be
collected because the mechanisms for recording and transmitting
individual decisions do not exist or are not in place, cases where
the information can be collected but the mechanisms have not been
'turned on', cases where the information is collected but not
analysed, cases where the results are analysed but not made
available to any decision makers, etc. etc.
Those are all patterns of distributed 'decision making' where the
'global preferences' are real, and have real consequences, but are
never represented as such, and no summary information about the
decisions or their consequences is ever used, although a company
going out of business (because its debts exceed some threshold,
perhaps) could be an explicit localised consequence of the
distributed decision making, even though it is not recognized as
such.
Like the firing of a cell, the company going out of business could
be described as a reliable detection or recognition of a pattern in
the distal 'sensory' records of individual purchases. (In this case
the pattern is a large drop in the purchases of a particular make of
car.) Would you call that a recognition or detection mechanism for
that pattern?
Many biological systems process all their information in that
distributed, de-centralised fashion, without any explicit summary
representation of what is going on, but it is not clear whether all
major brain processes or which subsets of brain processes are like
that.
I expect some organisms have *only* totally decentralised
distributed decision making (eg plants, slime moulds ?), whereas
others have partially centralised decision making with 'localised'
events produced by cumulative effects like a company going out of
business, e.g. turning the eyes to look left under certain
conditions of combined auditory and visual stimulation.
Now compare Q1: the question about choosing a president.
Selection of a president is a process that can also take various
forms, but usually includes use of a centralised mechanism that
represents the selection explicitly. That is, instead of the
selection being represented only transiently in a pattern of causal
influences, at least one enduring record of the outcome is made
which is then capable of playing a role in many different causal
processes, in combination with other items of information.
Let's look at some typical features of presidential elections in
typical geographically large democratic countries. And then some
other things that may or may not go in parallel with the official
processes.
Depending on the country C, the answer to Q1 will usually refer to
an elaborate formalised process which involves candidates being
nominated, followed by formalised (i.e. rule-based) voting
procedures being followed.
If C is a large country made up of different regions, the votes from
the regions may be counted up separately and the totals for each
candidate for each region communicated to the chief voting officer O
who gets the totals for each region and then adds them up, and in a
prearranged way announces that candidate X has won, which in turn
triggers a whole lot of activities, subsequently leading to the old
president being replaced by X in many physical, legal, political and
social contexts.
(Let's ignore the cases where the result is challenged, etc. Also if
necessary replace the officer O by a computer, or a committee: it
makes no difference for now. Another possibility that we ignore for
now is use of intermediate stages where votes are counted for
sub-regions then reported centrally within each region, etc.)
Now consider what happens if somehow an illegal copy of all the
regional totals is sent to someone, e.g. a financier F, who manages
to get them and add up the totals before O does, and takes actions
for his/her own benefit, e.g. buying and selling shares.
Now O and F are both localised bits of the country C, and each can
"*process* its proximal input to provide a selective and
reliable recognition signal of the distal sensory pattern
(i.e the votes cast in the regions).
But the consequences are very different. What O does is part of the
process of choosing the president whereas what F does is not. It is
a side-effect of an initial part of the process.
There could be many different similar (legal or illegal) processes
going on, involving interception of the voting information at
various stages and re-routing it to various individuals or
organisations who use the information, in some cases before the
central counting has been finished and the result announced -- e.g.
servants and collaborators of the old, defeated, president who
immediately start looking for new jobs, and people who support the
winner who start actions designed to facilitate the transfer of
power, or who start jockeying for positions in the new government,
etc.
This begins to take on some of the features of the answer to Q2 (the
distributed implicit choice of a favourite type of car), except
that in addition to all the distributed and nowhere collated
decision-making there is also a formal generally recognized
centralised decision-making process. The two sorts of processes can
coexist and play different roles in the whole system at the same
time.
Of course, many variants on these stories are possible.
There could be formalised mechanisms whereby the results from the
regions, or even the individual votes, are transmitted concurrently
to different subsystems to be used for various purposes (e.g.
statistical analysis of voting patterns, checks against voting
irregularities, speeding up processes connected with regime change,
etc. etc.).
As a precaution, the official process could involve collating the
individual votes in two (or more) different ways, using two sets of
routes for information transfer and the officer O may need to check
that the different routes produce the same result before the
decision is announced. (Compare adding rows and columns in an array
of numbers to check for errors in addition.)
So although there is a clear sense in which the nation as a whole
does not know the result, and has not formally decided until the
officer O has completed his/her task and announced the result, the
information about the result could be available and used implicitly
in many formal and informal, legal and illegal, sub-processes that
start up before the final decision, some of which help to improve
and accelerate the implementation of the high level decision.
Moreover, some aspects of those distributed processes may be noticed
and reported either locally or nationally or in organisations that
are involved in administration and administration changes. So
*subsystems* may be conscious of them even even if the whole system
is not.
On the basis of what I know about humans and brains I would expect
that the correct account of how we work is something like the
multi-functional mixture of centralised and distributed information
processing and decision making just described.
(I referred to this as a 'labyrinthine' architecture, as opposed to
a 'modular' architecture, in a paper on vision in 1989
http://citeseer.ist.psu.edu/758487.html )
When all the bits work smoothly together, as they normally do, we
think a belief has been acquired, a sensation has been experienced,
a decision has been taken, etc. and we think this is a simple
process about which we can ask questions like 'where does it
occur?', 'when does it occur?', 'what is its function?', etc.
When things go wrong or become abnormal, e.g. because of brain
damage, or effects of drugs or anaesthetics, or hypnotism, or
dreaming, or because abnormal development interferes with the
construction of properly functioning information management
subsystems, the hidden complexity begins to be more visible,
and 'neat' theories look less plausible.
Moreover, in some cases, as Neil Rickert pointed out in his message
of Fri, 25 May 2007, it may be far more useful to describe what's
going on in terms of *virtual* machine processes (possibly in
several levels of virtual machinery) rather than in terms of
underlying *physical* implementation details.
For instance, my answers to Q1 mentioned votes, counting,
information communication, etc. not the physical mechanisms used to
implement those processes. Most of the sciences, apart from physics,
talk about virtual machines implemented in physical systems.
But physics also has layers.
An event in a virtual machine, e.g. a bad decision taken because
some information was corrupted or because the rules used lack the
required generality, can be a real cause, with real effects -- as
any software engineer knows: debugging software involves identifying
such unwanted virtual machine events and changing the virtual
machine so that they don't occur or their effects are changed.
Our intuitive ideas about causation that lead many people to reject
that notion are based on a false model of causation as a kind of
fluid that flows through the universe subject to conservation laws.
If, instead, we analyse causal relations in terms of truth and
falsity of various sets of counterfactual conditional statements, we
can admit causes in both virtual machines and also the underlying
physical machines. But that's another, long, story.
-----------
[*]Yet another long story is what I mean by 'information', a word I
have deliberately used many times above, rather than talking about
e.g. neuronal excitation patterns.
The word 'information' is as indefinable as 'matter', 'energy', and
other deep concepts developed in our attempts to understand the
universe.
Their meanings are determined not by explicit definitions (which
always end up circular or vacuous -- like many definitions proposed
on this list) but by the powerful theories in which they are used.
It's primarily the theories and their associated research programmes
(which, as Imre Lakatos pointed out, can be progressive or
degenerative) that have to be tested and compared. Sometimes that
can take decades, or centuries because we don't know enough.
I've written more about the (non-shannon) concept of information
here:
http://www.cs.bham.ac.uk/research/projects/cogaff/misc/whats-information.html
Comments and criticisms welcome.
Aaron
http://www.cs.bham.ac.uk/~axs/
Maintained by
Aaron Sloman
School of Computer Science
The University of Birmingham