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Topic: Hebbian theory

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	Hebbian learning - Wikipedia, the free encyclopedia
		Hebbian learning is a hypothesis for how neuronal connections are enforced in mammalian brains; it is also a technique for weight selection in artificial neural networks.
		A variation of Hebbian learning that takes into account phenomena such as blocking and many other neural learning phenomena is the mathematical model of Harry Klopf, formerly of the Air Force Office of Scientific Research and presently with Wright-Patterson Air Force Base.
		Experiments on Hebbian synapse modification mechanisms at the central nervous system synapses of vertebrates are much more difficult to control than are experiments with the relatively simple peripheral nervous system synapses studied in marine invertebrates.
	en.wikipedia.org /wiki/Hebbian_learning (716 words)

	Richard Bowles' Idiot's Guide to Neural Networks (Site not responding. Last check: 2007-09-11)
		We want a Hebbian net to distinguish between these two faces, so we need one output, which will be 1 for the happy face, and 0 for the sad face.
		The source code section gives an example of a Hebbian net which has been trained on the "what-where" task, which is a task where a simple shape is placed somewhere on a grid and the network has to identify the shape (i.e.
		The where task is relatively easy for the Hebbian net to learn, but the what task (being linearly inseparable) is beyond its simple scope.
	members.tripod.com /~RichardBowles/neural/hebbian/hebbian.htm (1902 words)

	Synapse (Site not responding. Last check: 2007-09-11)
		Because the coincidence of sensory stimuli (the sound of a bell and the smell of meat, for example, in the experiments by Pavlov) can give rise to associative learning or conditioning, neuroscientists have hypothesized that synaptic strengthening through coincident activity in two neurons might underlie learning and memory.
		This is known as the Hebbian theory, while the variability of synaptic strength is often referred to as synaptic plasticity.
		Generally, if an excitatory synapse is strong, an action potential in the pre-synaptic neuron will trigger another in the post-synaptic cell; whereas at a weak synapse the excitatory post-synaptic potential ("EPSP") will not reach the threshold for action potential initiation.
	bopedia.com /en/wikipedia/s/sy/synapse.html (847 words)

	Memory, Learning and Our Virtual Brains: A Hebbian Web
		What follows is an integration of brain-based theories on internal representations of experience and memory for the purpose of providing perspective, and ultimately improving the conditions for learning and development in a progressive way.
		One theory, put forth by McClelland, McNaughton and O'Reilly (1) is that the Medial Temporal Lobe (MTL) memory system regulated the translation of information to LTM, and ultimately, the trade-off of plasticity and stability in the brain.
		Theories on how memory is translated from STM to LTM suggest that these pattern generations work in tandem such that relevant information is stored in a semi-systematic but non-linear way.
	serendip.brynmawr.edu /bb/neuro/neuro01/web3/Brennan.html (2677 words)

	Making causal maps: A cognitive and computational account of theory-formation (Site not responding. Last check: 2007-09-11)
		However, the theory theory does not seem to be as naturally applicable to other types of knowledge, for example, purely spatial knowledge, syntactic or phonological knowledge, musical knowledge or mathematical knowledge.
		On this view, infants are born with substantive innate theories as well as with mechanisms for revising those theories in the light of new evidence.
		The theory theory assumes that this knowledge is learned, but this knowledge also might be innately specified, or it might be directly taught by adults.
	www-psych.stanford.edu /~jbt/224/Gopnik_1.html (10665 words)

	Hebbian Learning
		From a neurophysiological perspective, Hebbian learning can be described as a time-dependent, local, highly interactive mechanism that increases synaptic efficacy as a function of pre- and post-synaptic activity.
		Within connectionism, Hebbian learning is an unsupervised training algorithm in which the synaptic strength (weight) is increased if both the source neuron and target neuron are active at the same time.
		A natural extension of this (alluded to by Hebb as the decay of unused connections) is to decrease the synaptic strength when the source and target neurons are not active at the same time.
	neuron-ai.tuke.sk /NCS/VOL1/P3_html/node14.html (427 words)

	[No title]
		If the domain theory is adequate and the initial description of the system is correct, then the actual behavior of the system must be in the set of possible behaviors QPC predicts.
		In particular, the theory provides a detailed methodology for constructing a formal problem representation, called physical representation, upon which physics laws may be appropriately selected and instantiated.
		Given a theory and a set of training examples, it performs a hill-climbing search in an attempt to minimally modify the theory to correctly classify all of the examples.
	www.cs.utexas.edu /ftp/pub/AI-Lab/backup.list (7238 words)

	Hebbian theory - Wikipedia, the free encyclopedia
		It has been suggested that Hebbian learning be merged into this article or section.
		Also known as cell assembly theory, the theory is often summarized as cells that fire together, wire together, although this is an oversimplification of the nervous system not to be taken literally.
		Hebbian theory has been the primary basis for the conventional view that when analyzed from a holistic level, engrams are neuronal nets or neural networks.
	en.wikipedia.org /wiki/Hebbian_theory (406 words)

	Comprehension
		This "theory of everything" is known as the string theory.
		A revolutionary discovery of the string theory is that the whole universe (called the "bulk universe") should have ten dimensions of space, instead of three dimensions (length, width and height).
		The string theory has been able to explain why they are invisible to us (more info).
	www.web-books.com /mobio/Free/Learning/Comprehension.htm (706 words)

	A NEURAL NETWORK THEORY OF PROPORTIONAL ANALOGY-MAKING (Site not responding. Last check: 2007-09-11)
		Underlying the development of this network is a theory for how the brain learns the nature of association between pairs of concepts.
		For example, a strong Hebbian connection between nodes representing “Paris” and “France” tells us only that Paris and France are somehow related: it does not tell us that Paris is a part of France, that it is “in” France, or that it is the capital of France.
		The theories of Piaget (see, for example, Gruber and Vonèche, 1995) hint that analogical reasoning should not become well established until the stage of formal operational thought, which Piaget believed did not start until about 11 years of age.
	www.uta.edu /psychology/faculty/levine/Analrev.htm (6331 words)

	[No title] (Site not responding. Last check: 2007-09-11)
		The theory of Hebbian learning was first introduced in his book, The Organization of Behavior.
		Now Hebbian learning is generally associated with an idea of mathematical abstractions with artificial intelligence.
		A variation of Hebbian learning is Klopfs model which is considered to be more accurate.
	www.oswego.edu /~rink/cogsci1/hebb.html (229 words)

	Tabernero and Ahumada, 1992 OSA Annual Meeting (Site not responding. Last check: 2007-09-11)
		Sanger's model [2] of this theory develops a `column' of units supported by a small patch of visual field.
		Sanger's recent model [2] of this theory is especially convenient because of the mathematical elegance of the result, originally found by Oja [13].
		Our hope was that they would be compatible and the Hebbian algorithm would develop cortex-like RFs and the TI algorithm would organize them into corresponding layers in each column across the visual field, correcting problems associated with the irregularities of the sampling array.
	vision.arc.nasa.gov /personnel/al/papers/92osa/lrn.html (2557 words)

	[No title]
		As with receptor arrays, it is assumed that, regardless of the three-dimensional configuration of the neurons in pattern assemblies, each such assembly is topologically equivalent to a sequence of neurons or a two-dimensional array of neurons.
		Unlike the Hebbian concept of a cell assembly, it is envisaged that the neurons in any one pattern assembly lie close together within the cortex.
		The main predictions of the theory are these: As in Hebb’s theory and other theories in that tradition, SP-neural proposes that knowledge is stored in functionally-coherent and inter-connected assemblies of neurons in the cortex.
	www.cognitionresearch.org.uk /papers/neural/bbs/spn9.doc (10460 words)

	W. H. Calvin's "Cortical Columns, Modules, and Hebbian Cell Assemblies" (MIT Press 1995)
		Representations via a pattern are familiar from the trichromatic theory of color perception and the similar aspects of taste.
		Evoking the memory of your grandmother's face is probably not a matter of activating a single specialized neuron; rather, it is thought to involve the activity pattern in an ensemble of cortical neurons, each of which helps to implement other memories as well.
		A somewhat more general version of a Hebbian cell assembly (Calvin & Ojemann 1994) would avoid anchoring the spatiotemporal pattern in particular cells, to make it more like the way the message board can scroll.
	williamcalvin.com /1990s/1995Handbook.htm (3209 words)

	hebbian-theory
		A separate handout on "The Neurobiology of Memory" then takes a more reductionist approach and looks at the subcellular dynamics of neurotransmission and neural growth (that is to say, at the processes which allow the networks to connect themselves up in the first place).
		In other words, psychology, biology, computing, electronics, and robotics now share a single common goal, namely unravelling the processes of memory and cognition; it is just that some workers prefer to study men and women directly, whilst others prefer things they can more easily dissect, such as goldfish, worms, and printed circuit boards.
		This was a largely Hebbian approach, although for its underlying mechanism it relied more on the concept of opening up pre-existing-but-inactive synapses than on new axon growth.
	www.smithsrisca.demon.co.uk /hebbian-theory.html (2701 words)

	The Symphonic Architecture of Mind
		The theory I propose below is an attempt to account for the subjective and objective aspects of consciousness, at the level of physiology, drawing directly on the evidence uncovered by physiological research.
		The mediodorsal thalamic nucleus, which is also implicated directly, is widely acknowledged to be grand integrative (straddling the sensory-motor boundary), and of course the whole of sensory cortex feeds into consciousness through intracortical, corticostriatal, and corticothalamic projections.
		This theory predicts that cingulate cortex will be found to have large, dense projections to most, or all, regions of isocortex that can be components of memory constellations.
	www.mega.nu:8080 /wavetrain.html (18705 words)

	Hubert Dreyfus's "Intelligence Without Representation" (Site not responding. Last check: 2007-09-11)
		The performer's theory of the skill, as represented by rules and principles, will thus gradually be replaced by situational discriminations accompanied by associated responses.
		Walter Freeman's theory of how the brain produces skilled behavior explains precisely how goal-directed behavior could be controlled by a brain state that, only in the weakest sense, could be called a representation of the satisfactory gestalt that behavior is drawn towards.
		According to Freeman, the simulated neural network and the brain operate according to the Hebbian theory of learning, that is, the strength of the connections between the neurons changes on the basis of experience.
	www.hfac.uh.edu /cogsci/dreyfus.html (6318 words)

	Synaptic
		A bug in the Generalized Hebbian Algorithm that caused the principal components to be incorrectly scaled has been fixed.
		It is because of their simplicity that they get ignored, but as we shall show, they do have some practical applications for which they are really good.
		In Synapse Hebbian learning is embodied by the Hebbian Layer component and the Hebbian and Oja’s update rules.
	blog.peltarion.com (1614 words)

	Methods in Computational Neuroscience
		Some problems in nonlinear and linear network theory.
		The Hebbian paradigm reintegrated: local reverberations as internal representations.
		Representation of spatial orientation by the intrinsic dynamics of the head-direction cell ensemble: a theory.
	hebb.mit.edu /courses/mcn (265 words)

	memory (Site not responding. Last check: 2007-09-11)
		A hypothesized celluar basis of memory and learning, for which there is some evidence, involves strengthening of the synapses that link nerve cells (or neurons).
		This is known as the '''Hebbian theory,''' after the Canadian neuropsychologist Donald O. Hebb.
		It has been asserted that GABA signals interfere with the registration and consolidation stages of memory formation.
	encyclopedia.mysleepcenter.com /memory.htm (869 words)

	Hebbian - OneLook Dictionary Search (Site not responding. Last check: 2007-09-11)
		Tip: Click on the first link on a line below to go directly to a page where "Hebbian" is defined.
		Hebbian : FOLDOP - Free On Line Dictionary Of Philosophy [home, info]
		Phrases that include Hebbian: hebbian learning, hebbian theory
	www.onelook.com /cgi-bin/cgiwrap/bware/dofind.cgi?word=Hebbian (80 words)

	Lecture schedule
		Amit, N. Brunel, and M. Tsodyks, Correlations of cortical Hebbian reverberations: theory versus experiment, J. Neurosci., 14, 6435-45 (1994).
		Zhang, Representation of spatial orientation by the intrinsic dynamics of the head-direction cell ensemble: a theory, J.
		Ben-Yishai, R. Bar-Or, and H. Sompolinsky, Theory of orientation tuning in visual cortex, PNAS, 92, 3844 (1995).
	hebb.mit.edu /courses/9.641/2000/lectures (791 words)

	Temporal Characteristics of the Predictive Synchronous Firing Modeled by Spike-Timing-Dependent Plasticity -- Kitano ...
		In all of the present simulations with the increased ratio, the temporal distributions of the epochs with excessively many spike coincidences showed no predictive power.
		Hebbian learning, may substitute for the (additive) STDP in
		Rubin, J., Lee, D.D., and Sompolinsky, H. Equilibrium properties of temporally asymmetric Hebbian plasticity.
	www.learnmem.org /cgi/content/full/11/3/267 (6265 words)

	How Does a Neuron Know What To Do?
		The most well-known theory about how local interactions between neurons determine changes in neuronal connections is that of Donald Hebbs.
		For example, consider an input neuron X whose firing is somewhat correlated with the firing of the neuron Y that it sends information to, and suppose (for this example) that it is connected by an excitatory synapse.
		The Hebbian theory predicts that the connection from neuron X to neuron Y will be strengthened because of this correlation (so whatever mechanism it is that determines the strengthening, this mechanism must involve the detection of the relevant correlation).
	www.1729.com /blog/HowDoesANeuronKnowWhatToDo.html (1458 words)

	CiteULike: Tag hebbian (Site not responding. Last check: 2007-09-11)
		posted to 3 critical_period hebbian language language_acquisition neural_network self-organization som by neural_nets_chapter as
		Toward a modern theory of adaptive networks: expectation and prediction.
		posted to conditioning hebbian reinforcement by stain as
	www.citeulike.org /tag/hebbian (80 words)

	David Clark's Neural Net Introduction
		One long standing theory, called Hebbian learning, [Hebb,1949], states that the strength of a synapse between two neurons increases when both neurons fire simultaneously.
		A more recent theory, put forth by Alkon [Alkon,1989], is based upon conditioned and un-conditioned stimuli received on neighboring synapses.
		McCulloch and Pitts [McCulloch,1943] proposed a simple mathematical expression for a formal neuron model and showed that any finite logical expression could be realized with combinations of formal neurons.
	www.cs.dartmouth.edu /~brd/Teaching/AI/Lectures/NN/clark.html (1394 words)

	Correlations of cortical Hebbian reverberations: theory vs experiment - DJ, Tsodyks (ResearchIndex) (Site not responding. Last check: 2007-09-11)
		Correlations of cortical Hebbian reverberations: theory vs experiment (1994)
		Amit DJ, Brunel N and Tsodyks MV 1994 Correlations of cortical Hebbian reverberations: theory vs experiment, J. Neurosci., 14 6445 http://citeseer.ist.psu.edu/88149.html More
		The graph only includes citing articles where the year of publication is known.
	citeseer.ist.psu.edu /88149.html (386 words)

	Dyslexia, and what it can teach us.
		On a cellular level learning is the result of change in the strength of a connection due to synaptic activity.
		We can use Hebbian learning to explain repetitive actions that allow us to learn, say a piece of music.
		At this point the synapses that were being used in the musicians brain have physically and chemically changed so that there is now a stronger connection.
	serendip.brynmawr.edu /bb/neuro/neuro02/web2/glappingcarr.html (1219 words)

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