> > I whipped this up this afternoon in case any of your are > interested. I tried to gear it towards functionally relevant > features. Enjoy > > Reference document: The Hippocampal navigational system > by Brad Wyble
Brad, Thanks for the very interesting summary! On the face of it, these place maps are very reminiscent of attractors as found in formal "attractor neural networks." When multiple noncorrelated maps are stored in the same collection of neurons, this sounds like multiple attractors being stored in the same formal neural net. About the ability to study 200 neurons at once: With what time granularity can this be done? Do there exist time series of the activity of these 200 neuron, both during map learning and during map use? Analyzing this 200-dimensional time series would be interesting. (Not that I have time to do it .. but it would be interesting.) We are currently using Novamente to analyze coupled time series in another biological domain (gene expression data). If there is decent time series data, it could be interesting to codevelop a grant application with someone to see what Novamente can find in this data.... On a more philosophical note, I like the idea that the machinery used for place mapping in rats is similar to the machinery used for more abstract sorts of "mapping" in humans. Indeed, this reflects the point someone made last week on this list, regarding the fact that humans have much better reasoning ability in familiar domains than unfamiliar ones. Maybe one of the reasons is that when we know a domain well we figure out how to map the domain into a physical-environment metaphor so we can use some "physical mapping machinery" to reason about it. But some familiarity is needed to create the map into the physical-environment metaphor. I think this is what someone suggested last week -- and your essay makes me like the hypothesis even more. If this is the case, it is a good example of the maxim "Your strengths are your weaknesses." Because some domains are not going to be effectively mappable into physical-environment domains. A good example is the quantum world, or the world of molecular biology (related to the quantum world). We are bad at reasoning about these, unless we learn a formal framework and use it. Because our intuitive modes of inference are based too heavily on physical-environment metaphors, and machinery tuned for manipulating these metaphors.... But the nice thing about the physical-metaphor approach to complex reasoning is that it is a heuristic way of trimming down huge search spaces. Without this approach, other heuristics for inference control and complex-concept-formation are needed... I am reminded a bit of some management-consulting ideas developed by my friend Johan Roos, see e.g. http://www.seriousplay.com/images/landscapes.pdf His work explores the notion of "knowledge landscapes", and the use of the physical-landscape metaphor in human thinking about business. -- Ben G ------- To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED]
