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
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/?&; > Powered by Listbox: http://www.listbox.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
