neuron-request@HPLMS2.HPL.HP.COM ("Neuron-Digest Moderator Peter Marvit") (07/10/90)
Neuron Digest Monday, 9 Jul 1990 Volume 6 : Issue 42 Today's Topics: Public Data Re: Public Data (machine learning) Genetic make-up of brains A questin about neural inhibition Some parameters in Kohonen's network + Hello RE: Neuron Digest V6 #40 Phone Number Given Incorrectly for GA Course Info POPLOG Conference announcement (UK) Send submissions, questions, address maintenance and requests for old issues to "neuron-request@hplabs.hp.com" or "{any backbone,uunet}!hplabs!neuron-request" Use "ftp" to get old issues from hplpm.hpl.hp.com (15.255.176.205). ------------------------------------------------------------ Subject: Public Data From: jcst@unix.cis.pitt.edu (John J Cierniakoski) Organization: Univ. of Pittsburgh, Computing & Information Services Date: 19 Jun 90 18:53:45 +0000 (This is the third time I am attempting to send this message, so if all 3 appear at the same time I apologize.) How can I get a copy, either machine readable or paper, of "Quinlan's Mushroom Data"? Did Quinlan use ID3 to analyze the Mushroom Data and then report the results? If so, then where is the report? How can I get a copy of the data Mingers used for his research reported in the recent issues of Machine Learning? I got Fisher's Iris data in an appendix to the Classification Algorithms book by Mike James and I got a complete description of the generated Breiman et. al data in their CART book. But there are a few other datasets that Mingers used which I cannot find. I wrote a computer program to analyze data and I am using it to analyze a file describing work-related injuries. I wish to make the data and program available to the public in the future but I do not wish to be bothered with the distribution myself. Is there some organization that handles such matters? Someone mentioned Stanford CS Dept. but when I phoned them asking about public data all of the people I talked with did not know what I was talking about. From: John Cierniakoski ------------------------------ Subject: Re: Public Data (machine learning) From: bradley@cs.utexas.edu (Bradley L. Richards) Organization: U. Texas CS Dept., Austin, Texas Date: 19 Jun 90 20:05:07 +0000 >How can I get a copy, either machine readable or paper, of >"Quinlan's Mushroom Data"? > >I wrote a computer program to analyze data and I am using it to analyze >a file describing work-related injuries. I wish to make the data and >program available to the public in the future but I do not wish to be >bothered with the distribution myself. Is there some organization that >handles such matters? UCI maintains an extensive set of publically available data sets suitable for machine learning implementations, including the "mushroom" data. They are also interested in new data sets with documentation. When I wrote the librarian, David Aha, he sent the following information on the database. To save him a flood of queries, I'm appending his response below. This is a very long file, but since your questions are probably of general interest I decided to post it in its entirity. It contains all the information you need to access the UCI database. Folks not interested in machine learning data should hit "j" now.... --------------------------------------------------------------------------- Bradley L. Richards uucp: cs.utexas.edu!bradley bradley@cs.utexas.edu CompuServe: 75216,1744 --------------------------------------------------------------------------- =============================================================================== This is the UCI Repository Of Machine Learning Databases 7 February 1990 ics.uci.edu: /usr2/spool/ftp/pub/machine-learning-databases Site Librarian: David W. Aha (aha@ics.uci.edu) 47 databases (5884K plus 1 offline database of unknown size) =============================================================================== Included in this directory are data sets that have been or can be used to evaluate learning algorithms. Each data file (*.data) consists of individual records described in terms of attribute-value pairs. See the corresponding *.names file for voluminous documentation. (Some files _generate_ databases; they do not have *.data files.) The contents of this repository can be remotely copied to other network sites via ftp. Both the userid and password are "anonymous". As of today, I've uncompressed the data files. However, they are usually in a compressed state: use the "binary" command to ftp in order to tell it that the file being transferred has been compressed. Otherwise, ftp will assume that it is an ASCII file and will not transfer it properly. Compressed files, whose filenames are postpended with ".Z", can be uncompressed using the "uncompress" and "uncompressdir" functions. Notes: 1. We're always looking for additional databases. Please send yours, with documentation. Thanks. Current documentation requirements are located in file DOC-REQUIREMENTS. Complaints and suggestions for improvements are welcome anytime. 2. There is also the "undocumented" sub-directory which contains six databases that require attention before being incorporated into the repository. You are welcome to access them. 3. Ivan Bratko has asked me to restrict the access on the databases he donated from the Ljubljana Oncology Institute. These databases, under the breast-cancer, lymphography, and primary-tumor directories, are unreadable to you. However, we are allowed to share them with academic institutions upon request. If used, these databases (like several others) require providing proper citations be made in published articles that use them. The citation requirements can be found in each database's corresponding documentation file. 4. Finally, I'm maintaining a list of CORRESPONDENTS and TRANSACTIONS. Perhaps someone on your site is listed among the CORRESPONDENTS and can provide you with some of these databases and related information. (I have corresponded with over 75 people so far concerning these databases.) TRANSACTIONS is a log of my correspondence with others, which should enlighten you as to what problems we're having, etc. David W. Aha Repository Librarian - ---------------------------------------------------------------------- Brief Overview of Databases: Quick Listing: 1. annealing 2. audiology 3. autos 4. breast-cancer (restricted access) 5-6. chess-end-games 7. cpu-performance 8. echocardiogram 9. glass 10. hayes-roth 11-14. heart-disease 15. hepatitis 16. iris 17. labor-negotiations 18-19. led-display-creator 20. lymphography (restricted access) 21. mushroom 22. primary-tumor (restricted access) 23. shuttle-landing-control 24-25. soybean 26. spectrometer 27-34. thyroid-disease 35. university 36. voting-records 37-38. waveform domain 39-46. Undocumented databases: sub-directory undocumented 1. Bradshaw's flare data 2. Pat Langley's data generator 3. David Lewis's information retrieval (IR) data collection (offline) 4. Mike Pazzani's economic sanctions database 5. Ross Quinlan's latest version of the thyroid database 6. Philippe Collard's database on cloud cover images 7. Mary McLeish & Matt Cecile's database on horse colic 8. Paul O'Rorke's database containing theorems from Principia Mathematica 47. Nine small EBL domain theories and examples in sub-directory ebl Quick Summaries of Each Database: 1. Annealing data (unknown source) -- Documentation: On everything except database statistics -- Background information on this database: unknown -- Many missing attribute values 2. Audiology data (Baylor College) -- Documentation: On everything except database statistics -- Non-standardized attributes (differs between instances) -- All attributes are nominally-valued 3. Automobile data (1985 Ward's Automotive Yearbook) -- Documentation: On everything except statistics and class distribution -- Good mix of numeric and nominal-valued attributes -- More than 1 attribute can be used as a class attribute in this database 4. Breast cancer database (Ljubljana Oncology Institute) -- Documentation: On everything except database statistics -- Well-used database -- 286 instances, 2 classes, 9 attributes + the class attribute 5-6. Chess endgames data creator 1. king-rook-vs-king-knight -- Documentation: limited (nothing on class distribution, statistics) -- This concerns king-knight versus king-rook end games -- The database creator is coded in Common Lisp 2. king-rook-vs-king-pawn -- Documentation: sufficient -- This concerns king-rook versus king-pawn end games -- Originally described by Alen Shapiro 7. Computer hardware described in terms of its cycle time, memory size, etc. and classified in terms of their relative performance capabilities (CACM 4/87) -- Documentation: complete -- Contains integer-valued concept labels -- All attributes are integer-valued 8. Echocardiogram database (Reed Institute, Miami) -- Documentation: sufficient -- 13 numeric-valued attributes -- Binary classification: patient either alive or dead after survival period 9. Glass Identification database (USA Forensic Science Service) -- Documentation: completed -- 6 types of glass -- Defined in terms of their oxide content (i.e. Na, Fe, K, etc) -- All attributes are numeric-valued 10. Hayes-Roth and Hayes-Roth's database -- Described in their 1977 paper -- Topic: human subjects study 11-14. Heart Disease databases (Sources listed below) -- Documentation: extensive, but statistics and missing attribute information not yet furnished (perhaps later) -- 4 databases: Cleveland, Hungary, Switzerland, and the VA Long Beach -- 13 of the 75 attributes were used for prediction in 2 separate tests, each of which achieved approximately 75%-80% classification accuracy -- The chosen 13 attributes are all continuously valued 15. Hepatitis database (G.Gong: CMU) -- Documentation: incomplete -- 155 instances with 20 attributes each; 2 classes -- Mostly Boolean or numeric-valued attribute types 16. Iris Plant database (Fisher, 1936) -- Documentation: complete -- 3 classes, 4 numeric attributes, 150 instances -- 1 class is linearly separable from the other 2, but the other 2 are not linearly separable from each other (simple database) 17. Labor relations database (Collective Bargaining Review) -- Documentation: no statistics -- Please see the labor directory for more information 18-19. LED display domains (Classification and Regression Trees book) -- Documentation: sufficient, but missing statistical information -- All attributes are Boolean-valued -- Two versions: 7 and 24 attributes -- Optimal Baye's rate known for the 10% probability of noise problem -- Several ML researchers have used this domain for testing noise tolerancy -- We provide here 2 C programs for generating sample databases 20. Lymphography database (Ljubljana Oncology Institute) -- Documentation: incomplete -- CITATION REQUIREMENT: Please use (see the documentation file) -- 148 instances; 19 attributes; 4 classes; no missing data values 21. Mushrooms in terms of their physical characteristics and classified as poisonous or edible (Audobon Society Field Guide) -- Documentation: complete, but missing statistical information -- All attributes are nominal-valued -- Large database: 8124 instances (2480 missing values for attribute #12) 22. Primary Tumor database (Ljubljana Oncology Institute) -- Documentation: incomplete -- CITATION REQUIREMENT: Please use (see the documentation file) -- 339 instances; 18 attributes; 22 classes; lots of missing data values 23. Shuttle Landing Control database -- tiny, 15-instance database with 7 attributes per instance; 2 classes -- appears to be well-known in the decision-tree community 24-25. Soybean data (Michalski) -- Documentation: Only the statistics is missing -- (2 sizes) -- Michalski's famous soybean disease databases 26. Low resolution spectrometer data (IRAS data -- NASA Ames Research Center) -- Documentation: no statistics nor class distribution given -- LARGE database...and this is only 531 of the instances -- 98 attributes per instance (all numeric) -- Contact NASA-Ames Research Center for more information 27-34. Thyroid patient records classified into disjoint disease classes (Garavan Institute) -- Documentation: as given by Ross Quinlan -- 6 databases from the Garavan Institute in Sydney, Australia -- Approximately the following for each database: -- 2800 training (data) instances and 972 test instances -- plenty of missing data -- 29 or so attributes, either Boolean or continuously-valued -- 2 additional databases, also from Ross Quinlan, are also here -- hypothyroid.data and sick-euthyroid.data -- Quinlan believes that these databases have been corrupted -- Their format is highly similar to the other databases 35. University data (Lebowitz) -- Documentation: scant; we've left it in its original (LISP-readable) form -- 285 instances, including some duplicates -- At least one attribute, academic-emphasis, can have multiple values per instance -- The user is encouraged to pursue the Lebowitz reference for more information on the database 36. Congressional voting records classified into Republican or Democrat (1984 United Stated Congressional Voting Records) -- Documentation: completed -- All attributes are Boolean valued; plenty of missing values; 2 classes -- Also, their is a 2nd, undocumented database containing 1986 voting records here. (will be) 37-38. Waveform data generator (Classification and Regression Trees book) -- Documentation: no statistics -- CART book's waveform domains -- 21 and 40 continuous attributes respectively -- difficult concepts to learn, but known Bayes optimal classification rate of 86% accuracy 39-46. Undocumented databases: see the sub-directory named undocumented 1. Bradshaw's flare data 2. Pat Langley's data generator 3. David Lewis's information retrieval (IR) data collection (offline) 4. Mike Pazzani's economic sanctions database 5. Ross Quinlan's latest version of the thyroid database 6. Philippe Collard's database on cloud cover images 7. Mary McLeish & Matt Cecile's database on horse colic 8. Paul O'Rorke's database containing theorems from Principia Mathematica 47. Nine simple small EBL domain theories and examples in sub-directory ebl 1. cup 2. deductive.assumable (contains three domain theories) 3. emotion 4. ice 5. pople 6. safe-to-stack 7. suicide ------------------------------ Subject: Genetic make-up of brains From: kingsley@hpwrc02.hp.com Date: Mon, 25 Jun 90 18:40:38 -0700 Would anyone like to speculate about which part of our brain comes from our fathers, and which part comes from our mothers? Is it half and half? Does the right half come from Mom and the left half from Dad? Visa-versa? Or, considering that humans have 23 genes which cross over during reproduction, then the Mom and Dad parts could be separated by a 23 dimensional hyperplane. But what are the dimensions? Space? Neurons? Synapses? Axons, dendrites or thresholds? Cell adhesion molecules? Has anyone seen studies of the genetics of intelligence, akin to Mendels studies of peas? Or, has anyone seen studies of the distribution of brain genes along a chromosome? Has anyone mapped the genes for brains? And why does everyone have a cortex, a cerebellum, cortical columns and a corpus callosum? Why doesn't the material we inherit from our parents just make a blob? Kingsley Morse kingsley@hpwrc02.hp.com ------------------------------ Subject: A questin about neural inhibition From: "DAVE MCKEE" <mckee@tisss.radc.af.mil> Date: 26 Jun 90 10:51:00 -0400 I would like to pose a question to the list about inhibiting neurons. As I look at various photographs and diagrams of biological neurons, it strikes me that dendritic branches or input connections to neurons are not simply a collection that is summed into the central body of the cell. All of the neural net models I have seen in papers and proceedings use the basic summation of the activation signals coming into the input dendrites, perhaps multiplied by some weighting factor. It seems to me, however, that the inhibiting neurons might not simply be a negative activation acting to cancel some positive one, but instead act as a "main switch" that shuts off or attenuates to some degree, whole branches of input dendrites, while leaving the other branches unaffected. I have yet to see this kind of idea employed in any neural models to date, but I would be very appreciative if anyone does know of such models and could give me references. To better get an flavor of what I am talking about I will attempt to draw a crude picture here: _____ _____\ Inhibitor input (top branch is attenuated) ______\ | _______\ | _______ \______v_________________ / \ \_____/ \________ ________________________/ \neuron / ________/ \_______/ _______/ ______/ (lower branch is unaffected) _____/ The overall effect would appear to be the ability to modify the input paradigm of the node. As the inhibitor moves further back in the tree branching of the input connections to the node, the effects would be more and more subtle. Obviously the complexity of such a structure is many orders of magnitude over the straightforward NN's that have been thus far explored, but I think that this particular implementation should not be ignored. Digressing a moment, I have been thinking about creating a standard for a software simulation/hardware description language for neural nets (I work with simulation languages and HDL's , specifically VHDL). I think perhaps the best way to create a standard modeling/specification language for neural nets would be to implement a subset of the C language and define some basic structural types that allows the flexibility for most any network configuration, but also gives the means to translate that structure into real hardware. This has been successfully done with the VHSIC/VLSI Hardware Description Language (VHDL). The C subset would be compilable by any C compiler with the proper library packages, but eventually accepted tools that check the syntax of the standard could be built. These tools would not be restricted to C, but only have to process the standard itself. The language would have to model the structure of how nodes are connected, while the behavioral modeling capabilities of the language would describe how the nodes, the synaptic junctions (weight changes), "growth" functions (new connections, new nodes, connections or nodes being destroyed ), etc. would evolve. One eventual goal would be to translate this information to actual design layout on a CAD station. For correspondence please feel free to E-mail me at: mckee@tisss.radc.af.mil until July 13, 1990 at which time I will be leaving Rome Air Development Center. After that date I can be reached by Snail Mail at: David T. McKee 1821 Calibre Place Apt 204 Raleigh, NC 27604 I can be reached now at: 369A Steadman Rd. Lee Center, NY 13363 ###################################################################### David T. McKee # "The opinions expressed within Software Engineer # are totally mine, I accept Microelectronics Reliability Division # full responsibility for them Rome Air Development Center # unless, of course, they cause Griffiss AFB # any liability whatsoever, in Rome, NY 13363 # which case I've never seen # them before!"(just kidding) ###################################################################### ------------------------------ Subject: Some parameters in Kohonen's network + Hello From: JJ Merelo <jmerelo@ugr.es> Date: 28 Jun 90 11:48:00 +0200 I am trying to software-implement Kohonen's network, and I have met some parameters, k1 and k2 on the gain factor alfa. Does anybody know how to vary them, and which range is suitable? Please, write back JJ ================== Date: 26 Jun 90 12:01 +0200 From: JJ Merelo <jmerelo@ugr.es> To: neuron-request@hplabs.hp.com Message-ID: <44*jmerelo@ugr.es> Subject: Introduction Return-Receipt-To: JJ Merelo <jmerelo@ugr.es> My name is JJ Merelo, I am working in Granada University. Our grooup is called CSIP and we are more prone to the hardware stuff, but I am myself concerned with software. I have already implemented a Kohonen network, that is being used for Spanish speech r ecognition. The source code is available in C, should anyone be interested. That's all by now. JJ ------------------------------ Subject: RE: Neuron Digest V6 #40 From: livingston_d%frgen.dnet@smithkline.com (David Livingstone, Med. Chem., Ext 3856) Date: Mon, 02 Jul 90 10:01:28 -0400 >I am interested in applications of Neural Networks in > protein structure prediction, > chemical reaction product prediction, > drug interaction effects ... and the like. Here are a few more on protein structure prediction: [1] H.Bohr, J.Bohr, S.Brunak, R.J.M.Cotterill, B.Lautrup, L.Norskov, O.H.Olsen and S.B.Petersen, FEBS Lett., 241 (1988) 223-228. [2] M.J.McGregor, T.P.Flores and M.J.E.Sternberg, Protein Eng., 2 (1989) 521-526 [3] H.Bohr, J.Bohr, S.Brunak, R.M.J.Cotterill, H.Fredholm, B.Lautrup and S.B.Petersen, FEBS Lett., 261 (1990) 43-46 And one which carries out discriminant analysis on structure-activity data: [4] T.Aoyama, Y.Suzuki and H.Ichikawa, J.Med.Chem., 33 (1990) 905-908 I have prepared a paper on the use of a neural net as a dimension reduction device for the display of multivariate data used in Quantitative Structure-Activity Relationships. If anyone would like a pre-print please send me your postal address (the figures won't go by E-mail). David Livingstone. Organization: Medicinal Chemistry, SmithKline Beecham Pharmaceuticals, The Frythe, Welwyn. Herts. AL6 9AR England. E-Mail: Livingston_d%frgen.dnet@smithkline.com (Internet) ------------------------------ Subject: Phone Number Given Incorrectly for GA Course Info From: "Dave Goldberg (dgoldber@ua1vm.ua.edu)" <DGOLDBER@UA1VM.ua.edu> Date: Tue, 03 Jul 90 06:06:56 -0500 For those of you seeking information regarding the five-day short course entitled "Genetic Algorithms in Search, Optimization, and Machine Learning" to be presented at Stanford University's Western Institute in Computer Science on August 6-10, the wrong phone number was given previously. Contact Joleen Barnhill, Western Institute in Computer Science, PO Box 1238, Magalia, CA 95954, (916)873-0575. The course, presented by John Koza and myself, includes in-depth coverage of GA mechanics, theory and application in search, optimization, and machine learning. Students will be encouraged to solve their own problems in hands-on computer workshops monitored by the course instructors. New material on Walsh functions, Boltzmann tournament selection, Koza's genetic programming, messy genetic algorithms (mGAs), and the theory of real-coded GAs and virtual alphabets will be presented in a classroom setting for the first time. I hope to see some of you there. Dave Goldberg ------------------------------ Subject: POPLOG Conference announcement (UK) From: POPX@vax.oxford.ac.uk Date: Thu, 05 Jul 90 10:07:30 +0000 FROM: Jocelyn Paine, Department of Experimental Psychology, South Parks Road, Oxford OX1 3UD. JANET: POPX @ UK.AC.OX.VAX Phone: (0865) 271444 - messages. (0865) 271339 - direct. ******************************************* * * * POPLOG USERS' GROUP CONFERENCE 1990 * * * * JULY 17TH - 18TH * * * * OXFORD * * * ******************************************* Why am I posting news about a Poplog conference to the neural net digests? After all, Poplog is an implementation of Pop-11, Prolog, Lisp, and ML - all very conventional and symbolic AI languages. Well, following from work done by David Young at Sussex, you can now buy from Integral Solutions Limited (Poplog's commercial distributors) the "Poplog Neural" package. This allows you to design neural nets of various kinds; display them graphically using Poplog's windowing system; build fast production versions; and integrate what you've designed with existing code written in Pop-11, Prolog, Lisp, or ML. So if you need to build a mixed net/symbolic program, Poplog is well worth considering. And you get the convenience of a rather nice development environment for your nets; plus the four languages I've mentioned, a built-in editor, a window manager, and the object-oriented "Flavours" package. If you want to find out more about Poplog Neural, and Poplog in general, this year's User Group conference, PLUG90, is the place to do it. We still have places left at PLUG90, and can accept bookings if made quickly. The conference will be held in Oxford on the 17th and 18th of July; accomodation is provided in Keble College, and talks themselves will be in Experimental Psychology. Registration will open at 11 am on the 17th, with the conference proper beginning at 2; it will close at about 4 on the 18th. There will be a rather good conference dinner on the night of the 17th (main course: duck in lime and ginger sauce). The price is #75 to members of PLUG and #95 to non-members (#15 non-residential without dinner; #37 non-residential with dinner). Integral Solutions Limited, who distribute Poplog commercially, has generously paid for three free places. These will be offered to academic members of PLUG who have not attended a PLUG conference before, and who have difficulty raising funds. All three are still available. ~~~~~ This is the provisional list of talks: "Poplog Neural", Colin Shearer, Integral Solutions Ltd. (30 mins) A demonstration of ISL's new neural-networking system. It's implemented in Poplog, does its number crunching in Fortran, and allows you to build and test nets by drawing on a window. Fully interfaceable with Pop-11, Prolog, Lisp and ML. "Pop9X - The Standard", Steve Knight, Hewlett-Packard Labs. (1 hour) Gives a review of the BSI standardisation process and the progress of the Pop standard - the language YOU will be writing soon (ish). "Assembly code translation in Prolog" Ian O'Neill, Program Validation. (30 mins) State of the art assembly language translation in Prolog. "THESEUS: a production-system simulation of the spinning behaviour of an orb-web spider", Nick Gotts, Oxford University Zoology Department. (30 mins) As well as giving a demo, Nick will talk about his experiences of using AlphaPop: Theseus runs on a Macintosh. "MODEL: From Package to Language", James Anderson, Reading University. (1 hour) A six year old software package for model based vision goes up in flames under the heat of self-criticism - to be replaced by a language. TALK INCLUDES VIDEO PRESENTATION "GRIT - General Real-time Interactive Ikbs Toolset", Mark Swabey, Avonicom. (30 mins) Mark will talk about GRIT, but also about his experiences (nice and otherwise) of Poplog as a development environment. "IVE - Interactive Visual Environment" Anthony Worrall, Reading University. (30 mins) The software environment that beat the pants off MODEL (based on MODEL and PWM and quite a lot of other things besides.) TALK INCLUDES VIDEO PRESENTATION "Embedded Systems", Rob Zancanato, Cambridge Consultants. (30 mins) Poplog for embedded systems - especially MUSE for designing real-time controllers. We hope to have a demo of one such self- contained system. "Doing representation theory in Prolog", John Fitzgerald, Oxford University Maths Department. (30 mins) Representation theory is part of the study of (mathematical) groups. Prolog copes surprisingly well with such a geometric topic. "Building User Interfaces with Flavours", Chris Price, Department of Computer Science, University College of Wales. (30 mins) Object-oriented user-interface design, using Poplog's OO flavours package and window manager. "TPM - a graphical Prolog debugger", Dick Broughton, Expert Systems Limited. (1 hour) Dick will show how a debugger should be designed: with TPM, you can display Prolog proof trees as trees, rewind and fast forward execution, zoom in and out, watch the "cut" prune branches, and generally do everything you can't do with 'spy'. "Processing of Road Accident Data", Jiashu Wu, UCL Transport Studies. (30 mins) UCL use Poplog for an EMYCIN-based expert system which advises on accident blackspots, taking 'raw' accident data from incident reports. They like Poplog because it's an "open system": its jobs include fuzzy matching, stats, and handling very big databases. "Faust - an online fault-diagnosis system", David Cockburn, Electricity Research and Development Centre. (30 mins) (to be confirmed) "Design for testability", Lawrence Smith, SD Scicon. (30 mins) (to be confirmed) A system for advising the users of CAD packages on loopholes in testability. Something on the future of Poplog Integral Solutions. (1 hour) (details awaited) ~~~~~ And this is the provisional timetable: Accomodation is provided in Keble College, Parks Road, Oxford. Luggage can be left there from mid-day on the 17th. The conference itself will be in the Department of Experimental Psychology, South Parks Road. July 17th - --------- Registration and coffee: 11:00 - 12:30 Lunch: 12:30 - 2:00 Talks: 2:00 - 3:30 Tea: 3:30 - 4:00 Talks: 4:00 - 6:00 (Depart for Keble). Keble bar opens from 6 to 11 pm. Dinner starts at 7. July 18th - --------- Talks: 9:00 - 10:30 Coffee: 10:30 - 11:00 Talks: 11:00 - 1:00 Lunch: 1:00 - 2:00 Talks: 2:00 - 3:30 Tea: 3:30 - 4:00 ------------------------------ End of Neuron Digest [Volume 6 Issue 42] ****************************************