Response to reviewer # 1
Referee No: 1 ms/no: #98029 title: Can the neurons in the brain implement symbolic systems?
GENERAL COMMENTS The manuscript #AM98029 titled "Can the neurons in the brain implement symbolic systems?" deals with an important question. Unfortunately the manuscript is full of grammatical and typographical errors, and the main argument is weak. I enclose some comments that the authors might find useful but I doubt that this manuscript can be improved enough to warrant publication in an international journal.
a) The title is awkward as it implies that there is some other kind of neuron which could implement symbolic systems.
b) The authors claims that "the set of neurons that will tend to become active as a result of the activity of some specific neuron is stochastic" and that the set of neurons that will tend to become active as a result of the activity of some specific neuron is "uncorrelated to the set that will tend to become active as a result of the activity of any other neurons". To take one of their examples, the authors claim that contacts between LGN axons and their target neurons in area 17 are stochastic, that the trees of different axons can not be matched and that therefore they are not well specified. However, the authors have failed to provide evidence supportive of these assertions, Instead, readers are invited to pursue textbooks which admittedly fail to make a case for synaptic selectivity between individual neurons. This is very weak argument. The lack of specification of axonal trees and connections may have more to do with our ignorance of how brains are built and work and less with how brains are actually built and work.
c) If the authors could provide evidence to suggest that connections between individual neurons are indeed stochastic, the point they are trying to make would be much more convincing. I must admit that I would not bet much on their chances of success. To judge from what we know about the best studied synapse in the brain (the homonymous one between Ia fibers and alpha motoneurons of the triceps surae as described by Burkem, Fleshman, Segev and their colleagues) there are about 10 synapses per fiber no matter who the motoneuron of the fiber. Accordingly, I fail to see anything stochastic about this connection. Other connections could be different but evidence to suggest that this is the case should be presented.
d) The authors have failed to prove that symbol tokens can not be handled by larger scale structures in the brain. The notion that the neurons which belong to a 1 mm square of the cortex but send processes to other elements "are all mixed up together" is not consistent with neurobiology. For example, the cells that send processes to the Claustrum are not mixed up with the cells that send processes to the superior colliculus even if they inhabit the same 1 mm square of area 17. I have changed the text in section 6 (pp. 14-15) to be clearer. With the correct interpretation, my statement is obviously true to any neurobiologist. Even if they are mixed up they need not be non-separable and the authors have failed to provide evidence that this is indeed the case.
e) The number of grammatical and typographical errors is too large to
list. I enclose the ones I found in randomly selected page (#9):
1. P 9, 11:...connections (plural)
2. P 9, 12: .. Reasonably (advreb)
3. P 9, 13: .. in a smaller scale
4. P 9, 13: .. at lower scales (plural
5. P 9 15: .. when (lowercase letter)
6. P 9, 15: .. enters (third person singular)
7. P 9, 17: of a highly ordered.
8. P 9, 19: spans (third person singular)
9. P 9, 1 10: .. The
neuron forms axon contacts with a fraction of..
10. P 9, 1 12: Delete "a choice of".
11. P 9, 1 13 .. with a few..
12. P 9, 1 14: ..way to
the selection that what other neurons..
13. P 9, 1 16: ... for this
is comes from compari sonsng of the axon trees..
14. P 9, 1 18: comes (third person singular) to compari
15. P 9, p 4, 14: "it follows immediately" It doesn't follow, let alone "immediately".
16. P 9, p 4, 16: Delete "a" or "some" in the " the raltion between a some pattern of activity".
Review #2: "Can the neurons in the brain implement symbolic systems?"
The authors argue that the information-processing in the central nervous system[cns] of human human/animals[at least vertebrae] cannot be captured, even remotely, as symbolic manipulation as implemented in computers, i.e. rapid storing and retrieval of values attached to symbols -which are propagated to/from computed locations.
The argument is based on the empirical anatomy and physiology of the CNS, primarily on the[low level] connectivity pattern of the dendritic tree of an individual neuron, which is "stochastic". This refers to the fact that few thousands connections are realised from tens of thousands "available to it", with no apparent rule, "not related in a consistent way to the selection that other neurons do - in the same or other brains".
The novelty and persuasive force of the article is in focusing on this stochastic connectivity issue, and on the restriction to the negative conclusion only. It does not support the Connectinists' position that cognitive abilities of humans/animals should be modelled by neuron-like systems - a position which is in a strong controversy with the reductionist position of Fodor, Plyshyn and other prominent cognitive scientists.
It is tenable - according to the paper - that the whole cognitive system, which includes a body with sense organs and inputs from the outsize world, can implement a symbolic manipulation - it mentions that the stochastic connectivity is less apparent in the peripheral NS.
it is interesting to note, in passing, that Dryfus, in his book "what computers cannot do', uses the "body' as a partial explanation for the superiority of humans/animals over computers in most information processing manipulations essential for everyday life.
On the whole, the message is that even if we learn a lot more about the functioning of the CNS, the entire cognitive process may remain a mystery for a long time.
There are references to Vera and Simon, Smolemsky and the PDP group, but I feel references to Fodor and several other prominent Cognitive scientists, whose are relevant, are missing.
I read the paper you gave me. I cannot give a definite view on whether it's good or not, as there are arguments I'm not familiar with In general, the argument is this:
1. Symbol systems are dynamic and arbitrary in the sense they store and retrieve tokens of symbols in the process of computations - think about the dynamic of a program for adding numbers. This is correct.
2. Processes in humans brains are stochastic in the sense that the propagation of activation are stochastic - that is, (if I understand it right) you cannot tell in advance which neurons will get the information.
3. You cannot implement dynamic processes (in the sense of 1) in stochastic processes (in the sense of 2), because (if I understand it right) stochastic processes are not robust enough for the propagation of patterns.
Therefore: symbol systems cannot be implemented by human brains. My problem is that I cannot judge whether claim 3 is correct. I'm not that familiar with the theory of neural networks.
Otherwise, the argument is clear, and I'm pretty sure it's novel. Connectionists indeed argue that we should focus on more biologically-oriented models of cognition, and they raise the worry that there is seemingly a gap between symbol systems and the working of the brain. But they do not explicitly argue that human brains cannot implement symbol systems.