> > > The nature of neuroscience research doesn't really differentiate > between the two at present. In order to understand WHAT a brain part > does, we have to understand HOW it, and all structures connected to it > function. We need to understand the inputs and the outputs, and that's > all HOW. > > > > I wouldn't say even that much... The exact format of the IO is not > necessary either but only the general "Information X Y and Z is carried > to here from here".
We don't even know what the information is, honestly. Cells fire spikes. Sometimes there are clear behavioral correlates which makes it easy to figure out (place cells), usually not. The spike firing code depends on the function of the underlying structures. We have to know how they represent information to know what information is being transmitted. Understand, by the way, that there are plenty of computational and mathematical specialists working on this, applying plenty of information theoretic approaches. > > I've seen a very interesting report on the reverse engineering of the > hearing system though I am still months away from finishing my first > reading of Principles of neuroscience. The primary modalities are the easiest systems to decode, because you can control precisely what the inputs are. Those are the first systems to be decoded. > Yes, that is because they don't constitute a computer. > I suppose you need a really deep understanding of what computation is to > see how the cortex is a computer (and hence has all the same properties > of nonpredictability and such...) Well it computes. So... it's a computer, sure. Feel free to tell me more. > > Does it really? ;) > I would suggest that the individual cortical columns represent a fairly > consistient set of adaptive logic gates (of considerable complexity). I > would further suggest that as the ferrit example showed the computation > the cortical region performs depends mostly on where in the logic > network the inputs are sent and the outputs taken. In this way you can > take just about any cortical region and get it to do just about anything > any other region does (except for the extra layers of the occipital > lobe) just by hooking it up differently... I don't really have any strong data for or against that hypothesis. We're not sure how brittle columns are, functionally. Simple neural net models tell us though that it's very easy to drastically alter the functional character of a network by changing one parameter. I'll read the ferret example, but I'm guessing that all they found was evidence of striation, which doesn't mean the system is working correctly. However, given the resilience of the brain to changes performed at a young age, it is likely there was some visual perception. > > Where is the evidence for celular differentiation beyond the 20 or so > classes of neurons? I'm not talking just about neuron types, but also about connection patterns of neurons between and within areas. Subregions CA3 and CA1 of the hippocampus are identical from a cellular composition perspective, but their connectivity patterns are so different that noone who studies the system would expect them to do the same thing. Neurophysiological evidence demonstrates that they do in fact differ in their functional characteristics. > > Absent this evidence, how can you say that a certain structure of cells > X, Y, and Z which are arranged in layers 1-6 in cortical region A do > something significantly different from those in region B? > For starters, an autoassociative network performs differently than a heteroassociative one. Or add noradrenergic modulation(or one of 10+ other neuromodulators), or delete a subclass of GABA cells, or triple the percentage of stellate cells. It is easy to make a neural network behave differently. This is easily demonstrated with models. ------- To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/?[EMAIL PROTECTED]
