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. 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 Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244&id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
