--- On Thu, 12/11/08, Eric Burton <brila...@gmail.com> wrote: > You can see though how genetic memory encoding opens the door to > acquired phenotype changes over an organism's life, though, and those > could become communicable. I think Lysenko was onto something like > this. Let us hope all those Soviet farmers wouldn't have just starved! > ;3
No, apparently you didn't understand anything I wrote. Please explain how the memory encoded separately as one bit each in 10^11 neurons through DNA methylation (the mechanism for cell differentiation, not genetic changes) is all collected together and encoded into genetic changes in a single egg or sperm cell, and back again to the brain when the organism matures. And please explain why you think that Lysenko's work should not have been discredited. http://en.wikipedia.org/wiki/Trofim_Lysenko -- Matt Mahoney, matmaho...@yahoo.com > On 12/11/08, Matt Mahoney <matmaho...@yahoo.com> > wrote: > > --- On Thu, 12/11/08, Eric Burton > <brila...@gmail.com> wrote: > > > >> It's all a big vindication for genetic memory, > that's for certain. I > >> was comfortable with the notion of certain > templates, archetypes, > >> being handed down as aspects of brain design via > natural selection, > >> but this really clears the way for organisms' > life experiences to > >> simply be copied in some form to their offspring. > DNA form! > > > > No it's not. > > > > 1. There is no experimental evidence that learned > memories are passed to > > offspring in humans or any other species. > > > > 2. If memory is encoded by DNA methylation as proposed > in > > > http://www.newscientist.com/article/mg20026845.000-memories-may-be-stored-on-your-dna.html > > then how is the memory encoded in 10^11 separate > neurons (not to mention > > connectivity information) transferred to a single egg > or sperm cell with > > less than 10^5 genes? The proposed mechanism is to > activate one gene and > > turn off another -- 1 or 2 bits. > > > > 3. The article at > http://www.technologyreview.com/biomedicine/21801/ says > > nothing about where memory is encoded, only that > memory might be enhanced by > > manipulating neuron chemistry. There is nothing > controversial here. It is > > well known that certain drugs affect learning. > > > > 4. The memory mechanism proposed in > > > http://www.ncbi.nlm.nih.gov/pubmed/16822969?ordinalpos=14&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_DefaultReportPanel.Pubmed_RVDocSum > > is distinct from (2). It proposes protein regulation > at the mRNA level near > > synapses (consistent with the Hebbian model) rather > than DNA in the nucleus. > > Such changes could not make their way back to the > nucleus unless there was a > > mechanism to chemically distinguish the tens of > thousands of synapses and > > encode this information, along with the connectivity > information (about 10^6 > > bits per neuron) back to the nuclear DNA. > > > > Last week I showed how learning could occur in neurons > rather than synapses > > in randomly and sparsely connected neural networks > where all of the outputs > > of a neuron are constrained to have identical weights. > The network is > > trained by tuning neurons toward excitation or > inhibition to reduce the > > output error. In general an arbitrary X to Y bit > binary function with N = Y > > 2^X bits of complexity can be learned using about 1.5N > to 2N neurons with ~ > > N^1/2 synapses each and ~N log N training cycles. As > an example I posted a > > program that learns a 3 by 3 bit multiplier in about > 20 minutes on a PC > > using 640 neurons with 36 connections each. > > > > This is slower than Hebbian learning by a factor of > O(N^1/2) on sequential > > computers, as well as being inefficient because sparse > networks cannot be > > simulated efficiently using typical vector processing > parallel hardware or > > memory optimized for sequential access. However this > architecture is what we > > actually observe in neural tissue, which nevertheless > does everything in > > parallel. The presence of neuron-centered learning > does not preclude Hebbian > > learning occurring at the same time (perhaps at a > different rate). However, > > the number of neurons (10^11) is much closer to > Landauer's estimate of human > > long term memory capacity (10^9 bits) than the number > of synapses (10^15). > > > > However, I don't mean to suggest that memory in > either form can be > > inherited. There is no biological evidence for such a > thing. > > > > -- Matt Mahoney, matmaho...@yahoo.com ------------------------------------------- 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=123753653-47f84b Powered by Listbox: http://www.listbox.com
