
	Where results make sense

Topic: Marr Albus model

Related Topics

Andrew Marr

Jim Marrs

David Marr

Wilhelm Marr

Birrarung Marr

Barbara La Marr

Marr Albus model

Alem Marr

Leslie Marr

La Marr Hoyt

Nikolai Marr

In the News (Tue 22 Dec 09)

Northern Trust

Marvin Harrison

Peter Chernin

Gary Locke

Match Play

Penelope Cruz

Mickey Rourke

AR Rahman

Danny Boyle

Hugh Jackman

	David Marr - Wikipedia, the free encyclopedia
		His doctoral dissertation was submitted in 1969 and described his model of the function of the cerebellum based mainly on anatomical and physiological data garnered from a book by J.C. Eccles.
		Marr is acknowledged as a founder of the discipline of Computational Neuroscience.
		Marr described vision as proceeding from a two-dimensional visual array (on the retina) to a three-dimensional description of the world as output.
	en.wikipedia.org /wiki/David_Marr (396 words)

	Structure, Function, and Dynamics:
		The models in Organization use neural networks in the sense of computational neuroscience in which the structure of the network and the function of the neuron is constrained, at some appropriate level of detail, by the data of neuroanatomy and neurophysiology.
		9.4 modeled the cerebellar role in saccade adaptation, refining the cortico-thalamic model by adjusting the metrics of saccades, a feat of learning that is impossible in animals or humans lacking certain portions of the cerebellum.
		The full model also includes the role of SII in creating and monitoring haptic expectations, the role of dorsal premotor cortex (F2) in the association of arbitrary stimuli with motor program preparation, and the role of area 46 as a working memory in tasks requiring information to be held during a delay period.
	www.bbsonline.org /Preprints/OldArchive/bbs.arbib.html (18540 words)

	Cerebellum - Wikipedia, the free encyclopedia
		This was first proposed by Marr and Albus in the early 1970s.
		The insights provided by the models have also led to extrapolations in the domains of artificial intelligence methodologies, especially neural networks.
		“David Marr's Theory of the Cerebellar Cortex: A Model in Brain Theory for the 'Galilean Combination of Simplification, Unification and Mathematization'”, Palm G., and Aertsen, A. Brain Theory.
	en.wikipedia.org /wiki/Globose (4238 words)

	MODELS OF THE CEREBELLUM AND MOTOR LEARNING
		Marr, Albus, and Braitenberg alike, assumed that individual Purkinje cells control elemental movements that are evoked when the Purkinje cell fires or pauses.
		In early versions of the model, the PFs were assumed to convey unprocessed mossy fiber input, whereas in our recent simulations we have used a layer of granule units combined with Golgi cell feedback to create a sparsely coded representation of the mossy fiber input, along the lines assumed in the Marr and Albus theories.
		The model by Moore and colleagues is most readily accomodated by current single unit data which demonstrates that sources of mossy fiber input to the cerebellum have a distribution of latencies.
	www.bbsonline.org /Preprints/OldArchive/bbs.neur4.houk.html (16207 words)

	Cerebellum - Encyclopedia, History, Geography and Biography
		This was first proposed by Marr and Albus in the early 1970s. The third, "Tensor Network Theory" provides a mathematical model of transformation of sensory (covariant) space-time coordinates into motor (contravariant) coordinates by cerebellar neuronal networks.
		Studies of motor learning in the vestibulo-ocular reflex and eyeblink conditioning demonstrate that the timing and amplitude of learned movements are encoded by the cerebellum. Many synaptic plasticity mechanisms have been found throughout the cerebellum.
		As mentioned in the preceding section, there have been many attempts to model the cerebellar function. The insights provided by the models have also led to extrapolations in the domains of artificial intelligence methodologies, especially neural networks.
	www.arikah.com /encyclopedia/Cerebellum (3828 words)

	237-240
		The Cerebellar Model Articulation Controller (CMAC) [1, 2] is a neural network that models the structure and function of the part of the brain known as the cerebellum.
		This model was, in turn, inspired by a series of experiments performed by Eccles [8] and others during the 1960s that showed a striking resemblance between the structure and function of the cerebellum and the Perceptron neural net developed by Rosenblatt [9] in the 1950s.
		The Albus model, combined with a similar model published in 1969 by David Marr [10], have become known as the Marr-Albus model of the cerebel-lum.
	nvl.nist.gov /pub/nistpubs/sp958-lide/html/237-240.html (2619 words)

	[No title]
		Marr (1968), drawing extensively from the work of Eccles and colleagues, developed a model of cerebellar function which detailed the manner in which learning might occur in this system.
		Albus proposed that parallel fiber synapses with Purkinje cells, basket cells, and stellate cells are all modifiable.
		Albus model is explicitly formulated in terms of classical conditioning.
	www.uwm.edu /~rswain/class/SUM05/slect12.html (1647 words)

	Diffusion of nitric oxide can facilitate cerebellar learning: A simulation study -- Schweighofer and Ferriol 97 (19): ...
		We modeled four microzones: a flexor and an extensor microzone for the shoulder and the elbow joints.
		The large NO concentration in the most rightward microzone (elbow flexor microzone) was caused by a large error in the elbow flexor during this movement; conversely, low concentration in the most leftward microzone (shoulder extensor microzone) was caused by a small error in the shoulder extensor.
		We modeled four microzones (35): a flexor and an extensor microzone for the shoulder and elbow joints.
	www.pnas.org /cgi/content/full/97/19/10661 (4175 words)

	A New Functional Role for Cerebellar Long Term Depression
		A few years later, Albus (1971) refined this theory by suggesting that the cerebellum functions as a modified perceptron (Minsky and Papert, 1969) pattern-classification device, with the complex spike as the unconditioned stimulus and mossy fiber (MF) input as the conditioned stimulus.
		Albus also proposed that the CF stimulus is an error signal and that the PF synapse is weakened instead of facilitated.
		The computer model shows that the activation of dendritic Ca channels required for these amplification mechanisms (De Schutter and Bower, 1994c) is similar to that observed experimentally (Eilers et al., 1995) and does not result in the appearance of burst activity in the firing pattern.
	www.tnb.ua.ac.be /publications/pub019/TNB_pub19.shtml (7566 words)

	[No title]
		This network was developed by Albus (1971) as a model of the cerebellum and was later applied to the control of robot manipulators (Albus, 1975; 1979; 1981).
		For example, it has been shown (Minsky and Papert, 1969) that this particular perceptron model cannot determine whether or not all the parts of its input image (geometric figure) are connected to one another, nor it can determine whether or not the number of 'on' pixels in a finite input image is odd.
		This model, Gallant-Smith-Hassoun (GSH) model, is also similar to a version of an early model studied by Gamba (1961), and referred to as the Gamba Perceptron (Minsky and Papert, 1969).
	neuron.eng.wayne.edu /tarek/MITbook/chap6/6_2.html (2691 words)

	Roxolana - free download text. (Site not responding. Last check: 2007-11-03)
		This commonly-seen model of aromatic rings was developed by Friedrich August Kekulé von Stradonitz.
		The model for benzene consists of two Resonance (chemistry) forms, which corresponds to the double and single bonds' switching positions.
		The quantum mechanical origins of this stability, or aromaticity, were first modelled by Erich Huckel in 1931.
	roxolana.en.pdabuy.org (3428 words)

	Prediction of Complex Two-Dimensional Trajectories by a Cerebellar Model of Smooth Pursuit Eye Movement -- Kettner et ...
		The structure of the network model is shown in terms of the neuronal architecture of the cerebellum in Fig.
		The model was trained afresh on each stimulus from the initial state defined in the description of the model, until we observed
		Although the monkey behavior during perturbed circular pursuit is qualitatively similar to that of the model (Fig.
	jn.physiology.org /cgi/content/full/77/4/2115 (8455 words)

	Chapter 4
		Levels in the world model hierarchy are defined by temporal resolution of events, spatial resolution of maps, and by parent-child relationships between entities in symbolic data structures.
		Modeling of the neurophysiology and anatomy of the brain by a variety of mathematical and computational mechanisms has been discussed in a number of publications [16,32,40,41,61,65-71].
		The results of sensory processing are incorporated within or rejected by the knowledge base where the World Model is held and maintained (the set of knowledge and data bases in a variety of representational forms).
	www.ece.drexel.edu /courses/ECE-C490_AIS/chapter4.html (10603 words)

	15-883: Computational Models of Neural Systems
		Albus, J. (1971) A theory of cerebellar function.
		These are optional background articles on various aspects of neuronal modeling to help you understand the Wicks paper.
		Suarez, H., Koch, C., and Douglas, R. (1995) Modeling direction selectivity of simple cells in striate visual cortex within the framework of the canonical microcircuit.
	www.cs.cmu.edu /afs/cs.cmu.edu/academic/class/15883-s01/syllabus.html (1927 words)

	Dr. James Albus (Site not responding. Last check: 2007-11-03)
		It was 1969 when David Marr burst onto the scientific stage with the publication of his theory of cerebellar cortex.
		The main result of this line of research was to demonstrate that neural nets can (and by extension neurons in the brain may) compute the all the functions required to implement sophisticated feedforward and feedback control for position, velocity, and force in nonlinear actuators such as muscles.
		During the 1980´s, the RCS reference model architecture provided the fundamental integrating principle of the National Bureau of Standards (NBS) Automated Manufacturing Research Facility (AMRF.) The AMRF was an $80 million experimental automated factory-of-the-future funded by the U.S. Navy Manufacturing Technology Program and the National Bureau of Standards (NBS).
	www.jamesalbus.org /interest.htm (2866 words)

	Entrez PubMed (Site not responding. Last check: 2007-11-03)
		As such, unloading models that exhibit many if not all of the same responses observed in aged muscle, including the capacity of exercise to reverse these responses, may provide valuable insight into the skeletal muscle aging process.
		This paper integrates investments in health to a standard growth model where physical and human capital investments are the combined engines of growth.
		The model also leads to the important hypothesis that the epidemiological transition may induce an economy to switch to a modern growth regime.
	elegans.uky.edu /pubmed/human_aging_pubmed.5-30-2004.html (8494 words)

	Dendritic Voltage and Calcium-Gated Channels Amplify the Variability of Postsynaptic Responses in a Purkinje Cell Model ...
		The model simulated the "in vivo" state of the neuron described in De Schutter and Bower (1994b)
		Correlation of somatic EPSP amplitude with mean dendritic membrane potential at times indicated before the activation of the synchronous input in the active membrane model (thick line) and passive membrane model (thin line).
		Because excitability in the model was a dendritic property, the correlation of EPSP amplitude with the dendritic membrane
	jn.physiology.org /cgi/content/full/80/2/504 (8872 words)

	Autonomous Agents as Embodied AI
		Modeling the environment is both difficult and computationally expensive.
		Though the Internal Models principle warns against over doing it, some internal modeling of the environment will be needed to allow for expectations (important to perception, for instance), planning, problem solving, etc. This principle also points to the distinction between reactive and deliberative action selection (see for example Sloman 1995).
		Deliberative actions are selected with the help of internal models, planners, schedulers, etc. These models use internal representations in the strict sense of the word, that is, they are consulted for their content.
	www.msci.memphis.edu /~franklin/AAEI.html (5618 words)

	Low rates yield big returns - Nature Neuroscience
		Lance M. Optican is chief of the section on Neural Modeling in the Laboratory of Sensorimotor Research at the National Eye Institute, NIH, Bethesda, MD 20892, USA.
		Although much research and modeling has focussed on the role of climbing fibers in movement control, it has been assumed that complex spikes do not encode movement features because of their very low firing rate.
		This can be particularly useful when the firing pattern of the neuron (e.g., a complex spike in a PC) is known, but when the cause of this response is not known (i.e., what generates climbing fiber activation?).
	www.nature.com /neuro/journal/v1/n1/full/nn0598_8.html (1555 words)

	Neuroscience Wiki: MarrAlbusIto
		Peterson has made a software implementation of the abstract model.
		Albus, J. ``Mechanisms of Planning and Problem Solving in the Brain.
		Kanerva, P. “Sparse Distributed Memory and related models.” In M.H. Hassoun (ed.), Associative Neural Memories: Theory and Implementation; 50-76.
	www.ifi.unizh.ch /~andel/neurowiki/nw.cgi?action=browse&diff=1&id=MarrAlbusIto (1068 words)

	The Influence of Somatosensory Cortex on Climbing Fiber Responses in the Lateral Hemispheres of the Rat Cerebellum ...
		Huerta MF, Frankfurter A, Harting JK (1983) Studies of the principal sensory and spinal trigeminal nuclei of the rat: projections to the superior colliculus, inferior olive, and cerebellum.
		Marr D (1969) A theory for cerebellar cortex.
		McCurdy ML, Gibson AR, Houk JC (1992) Spatial overlap of rubrospinal and corticospinal terminals with input to the inferior olive.
	www.jneurosci.org /cgi/content/full/22/15/6819 (7849 words)

	[No title]
		Marr, Albus, and Ito have proposed several theories on how these computations may be performed.
		In the laboratory of Thomas Anastasio I have had the opportunity to learn from classical models, and observe their progression to contemporary models such as the Input Minimization model.
		While these models adhere to the basic anatomical structure of the cerebellum, they ignore the biophysical properties of the neurons.
	www.tiger-marmalade.com /~yash/journal.php?y=2002&m=1 (1099 words)

	Neural Model (Site not responding. Last check: 2007-11-03)
		The new model described here remains rather high-level, but does incorporate the basic circuitry of the cerebellum (Ito, 1984): Inputs arrive via mossy fibers to the granule cells whose axons bifurcate to form parallel fibers in the cerebellar cortex.
		Learning occurs at the parallel fiber-Purkinje dendrites in the form of long term depression (LTD) of parallel fiber-Purkinje dendrites after activation of parallel and climbing fibers with appropriate timing relationships (Albus, 1971; Marr, 1969).
		Figure 2 shows the systems-level circuitry of the model.
	www-hbp.usc.edu /_Documentation/DartModel/doc/node2.html (173 words)

	Learning in a Simple Motor System -- Broussard and Kassardjian 11 (2): 127 -- Learning & Memory
		In the model, CS and US arise from the vestibular nerve and climbing fibers, respectively.
		Li, J., Smith, S.S., and McElligott, J.G. Cerebellar nitric oxide is necessary for vestibulo-ocular reflex adaptation, a sensorimotor model of learning.
		Peterson, B.W., Baker, J.F., and Houk, J.C. model of adaptive control of vestibuloocular reflex based on properties of cross-axis adaptation.
	www.learnmem.org /cgi/content/full/11/2/127 (7536 words)

	Aspergillus fumigatus Variant with Decreased Susceptibility to Multiple Antifungals -- Balajee et al. 48 (4): 1197 -- ...
		Articles by Balajee, S. Articles by Marr, K. Antimicrobial Agents and Chemotherapy, April 2004, p.
		Neosartorya fischeri: an invasive fungal pathogen in an allogeneic bone marrow transplant patient.
		Marr, K. Carter, M. Boeckh, P. Martin, and L. Corey.
	aac.asm.org /cgi/content/full/48/4/1197?view=full&pmid=15047520 (3924 words)

	Curriculum Vitae for James S. Albus
		NASREM has been used by NASA and NASA contractors, plus a number of companies and university laboratories throughout the world for designing telerobotic systems.
		This hierarchical control system development was recognized by the Robot Industries Association with the Joseph F. Engelberger Award, presented at the 1984 International Symposium for Industrial Robots by the King of Sweden.
		CMAC has become well known by students and researchers in adaptive learning-generalizing mechanisms, and is the subject of neural network studies in a number of laboratories in several countries.
	www.isd.mel.nist.gov /personnel/albus/vitae.htm (698 words)

	Cogprints - Learning in the Cerebellum with Sparse Conjunctions and Linear Separator Algorithms (Site not responding. Last check: 2007-11-03)
		We review evidence that input to the cerebellum is sparsely expanded by granule cells into a very wide basis vector, and that Purkinje cells learn to compute a linear separation using that basis.
		We review learning rules employed by existing cerebellar models, and show that recent results from Computational Learning Theory suggest that the standard delta rule would not be efficient.
		We suggest that alternative, attribute-efficient learning rules, such as Winnow or Incremental Delta-Bar-Delta, are more appropriate for cerebellar modeling, and support this position with results from a computational model.
	cogprints.org /2310 (363 words)

	BIEN 289 Exam 1 Prep
		Give the conditions under which an RBFN and FIS are functionally equivalent (e.g., see p.
		Draw a block diagram structure for a neural network model reference controller and plant, and then describe how you would go about setting up plant identification and controller training using Matlab (e.g., what parameters are needed for the controller training algorithm?)
		Draw the basic Cerebellar circuit, and using it, discuss how it might learn to recognize patterns (e.g., ideas of Marr, Albus, etc).
	www.eng.mu.edu /wintersj/bien-289/bien-289_examprep1.htm (597 words)

	ITU \| Home (Site not responding. Last check: 2007-11-03)
		The goal of this course is to provide students a broad and practical understanding of the ASIC design process and issues.
		Fault modeling: single stuck-at fault (SSF) and multiple stuck-at fault, fault equivalence and dominance, fault simulation techniques: serial, parallel and concurrent, testing algorithms for SSF and bridge fault, functional testing, PLA testing, use of CAD tools and introduction of commercial tools and their capabilities.
		Neuronal activity and mathematical models, perception type machines and learning, cerebellar models (work by Marr, Albus, Pellionisz and Llinas), parallel distributed processing (work by Hopfield, Grossberg, MeClelland and Rumelhart), and feedforward and feedback networks.
	www.itu.edu /msce.html (1933 words)

Try your search on: Qwika (all wikis)