Richard,

It might be more useful to discuss more recent papers by the same
authors regarding the same topic, such as the more accurately-titled

***
Sparse but not "Grandmother-cell" coding in the medial temporal lobe.
Quian Quiroga R, Kreiman G, Koch C and Fried I.
Trends in Cognitive Sciences. 12: 87-91; 2008
***

at

http://www2.le.ac.uk/departments/engineering/extranet/research-groups/neuroengineering-lab/

-- Ben G

On Mon, Nov 24, 2008 at 1:32 PM, Richard Loosemore <[EMAIL PROTECTED]> wrote:
> Ben Goertzel wrote:
>>
>> Hi,
>>
>> BTW, I just read this paper
>>
>>
>>> For example, in Loosemore & Harley (in press) you can find an analysis of
>>> a
>>> paper by Quiroga, Reddy, Kreiman, Koch, and Fried (2005) in which the
>>> latter
>>> try to claim they have evidence in favor of grandmother neurons (or
>>> sparse
>>> collections of grandmother neurons) and against the idea of distributed
>>> representations.
>>
>> which I found at
>>
>>  http://www.vis.caltech.edu/~rodri/
>>
>> and I strongly disagree that
>>
>>> We showed their conclusion to be incoherent.  It was deeply implausible,
>>> given the empirical data they reported.
>
>
> The claim that Harley and I made - which you quote above - was the
> *conclusion* sentence that summarized a detailed explanation of our
> reasoning.
>
> That reasoning was in our original paper, and I also went to the trouble of
> providing a longer version of it in one of my last posts on this thread.  I
> showed, in that argument, that their claims about sparse vs distributed
> representations were incoherent, because they had not thought through the
> implications contained in their own words - part of which you quote below.
>
> Merely quoting their words again, without resolving the inconsistencies that
> we pointed out, proves nothing.
>
> We analyzed that paper because it was one of several that engendered a huge
> amount of publicity.  All of that publicity - which, as far as we can see,
> the authors did not have any problem with - had to do with the claims about
> grandmother cells, sparseness and distributed representations.  Nobody - not
> I, not Harley, and nobody else as far as I know - disputes that the
> empirical data were interesting, but that is not the point:  we attacked
> their paper because of their conclusion about the theoretical issue of
> sparse vs distributed representations, and the wider issue about grandmother
> cells.  In that context, it is not true that, as you put it below, the
> authors "only [claimed] to have gathered some information on empirical
> constraints on how neural knowledge representation may operate".  They went
> beyond just claiming that they had gathered some relevant data:  they tried
> to say what that data implied.
>
>
>
> Richard Loosemore
>
>
>
>
>
>
>
>> Their conclusion, to quote them, is that
>>
>> "
>> How neurons encode different percepts is one of the most intriguing
>> questions in neuroscience. Two extreme hypotheses are
>> schemes based on the explicit representations by highly selective
>> (cardinal, gnostic or grandmother) neurons and schemes that rely on
>> an implicit representation over a very broad and distributed population
>> of neurons1–4,6. In the latter case, recognition would require the
>> simultaneous activation of a large number of cells and therefore we
>> would expect each cell to respond to many pictures with similar basic
>> features. This is in contrast to the sparse firing we observe, because
>> most MTL cells do not respond to the great majority of images seen
>> by the patient. Furthermore, cells signal a particular individual or
>> object in an explicit manner27, in the sense that the presence of the
>> individual can, in principle, be reliably decoded from a very small
>> number of neurons.We do not mean to imply the existence of single
>> neurons coding uniquely for discrete percepts for several reasons:
>> first, some of these units responded to pictures of more than one
>> individual or object; second, given the limited duration of our
>> recording sessions, we can only explore a tiny portion of stimulus
>> space; and third, the fact that we can discover in this short time some
>> images—such as photographs of Jennifer Aniston—that drive the
>> cells suggests that each cell might represent more than one class of
>> images. Yet, this subset of MTL cells is selectively activated by
>> different views of individuals, landmarks, animals or objects. This
>> is quite distinct from a completely distributed population code and
>> suggests a sparse, explicit and invariant encoding of visual percepts in
>> MTL.
>> "
>>
>> The only thing that bothers me about the paper is that the title
>>
>> "
>> Invariant visual representation by single neurons in
>> the human brain
>> "
>>
>> does not actually reflect the conclusions drawn.  A title like
>>
>> "
>> Invariant visual representation by sparse neuronal population encodings
>> the human brain
>> "
>>
>> would have reflected their actual conclusions a lot better.  But the
>> paper's
>> conclusion clearly says
>>
>> "
>> We do not mean to imply the existence of single
>> neurons coding uniquely for discrete percepts for several reasons:
>> "
>>
>> I see some incoherence between the title and the paper's contents,
>> which is a bit frustrating, but no incoherence in the paper's conclusion,
>> nor between the data and the conclusion.
>>
>> According to what the paper says, the authors do not claim to have
>> solve the neural knowledge representation problem, but only to have
>> gathered some information on empirical constraints on how neural
>> knowledge representation may operate.
>>
>> -- Ben G
>>
>>
>> -------------------------------------------
>> agi
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>
>
>
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> agi
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-- 
Ben Goertzel, PhD
CEO, Novamente LLC and Biomind LLC
Director of Research, SIAI
[EMAIL PROTECTED]

"The empires of the future are the empires of the mind."
-- Sir Winston Churchill


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agi
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