Defense Technical Information Center

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.,..„„„ ,. ,,„,,ae 1 Hour per response, including the time tor reviewing instructions. >earc.n,nq .'w ^-.=ai.,'■'cr^3l!'' ;;-:^?'e,„vv°nr-'-e Ollea.onof Information. Send comments regaraing this burden estimate :r ,nv -." ■ jrc -air.t-)ir.i-= t-e :ata neecea. ..no come:.-.:" ,no reviewing ..e olectio £ Services. Directorate for Information Operations äna ^r.s ,,::c, --.c..c,^ suggestions ,0_r_r«uor_,, tn.s ^«^^^qTmeSt arS gSS|« Paperwork Reduction Rrqect (0704-0188), Wasn,ng:cn. -X .3;. jna '-C :ne Ct

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1 2. REPORT DATE

banuary 19, 1996

3. REPORT TYPE AND DATES COVERED

Final 5. FUNDING NUMBERS

-. "iTLE .-iiND uU3T]TL£

Self-Organization of Hebbian Synapses on Hippocampal Neurons

G N00014-90-4136

6. AUTHCF.(S)

Thomas Huntington Brown 8. PERFORMING ORGANIZATION REPORT NUMBER

7. PERFORMING ORGANIZATION NAMEIS) AND ADDRESS(ES)

Yale University, Grants and Contracts Administration, 12 Prospect Place, New Haven, CT 06511-3516 Attn: Ms Sally Tremaine, Associate Director 10. SPONSORING/MONITORING AGENCY REPORT NUMBER

9. SPONSORING, MONITORING AGENCY NAME(S) AND ADDRESS(ES)

Same

11. SUPPLEMENTARY NOTES

See attached letter

from Thomas H. Brown dated September 7, 1995.

12b. DISTRIBUTION CODE

12a. DISTRIBUTION/ AVAILABILITY STATEMENT

No known restrictions on release of information

13. ABSTRACT (Maximum 200 words).

■'

The near-term goal of thVpro.ect was to create -dfs^-f^iT^TelTlll s implement these on a relatively fast platform. ^ ^^ neurons and been used to create insights into th%crpUtatl^n?iMc studies The longer-term the processing elements typically used xn ^^^l^^ lament them into g0al

was to •^^^.^^^e^ ho7 o *£«ZBI°too low-power, reliable learning cxreuxts, and ultxmately *igu« °^ aWractions and have begun to implement circuit-level VLSI. We have succeeded xn ^eab8"a^^1"Jng VLSI options, these into circuits that learn and encode txme. We are exploring v

15. NUMBER OF PAGE; 14. 3U3JECT TERMS

electrotonxc Single-neuron computation; Hebbian learning; ion. structure; learning circuits; danger predxcti -•-v.-slT'' -LASS.FXATiCN ^T'EPCRT

|18.

SECURITY CLASSIFICATION OF THIS PAGE

19.

SECURITY CLASSIFICATION OF ABSTRACT

16. PRICE CODE 20. LIMITATION OF A3G,

THIS DOCUMENT IS BEST QUALITY AVAILABLE.

THE

COPY FURNISHED TO DTIC CONTAINED A SIGNIFICANT NUMBER OF PAGES WHICH DO NOT REPRODUCE LEGIBLY.

Yale University

Grant and Contract Administration 12 Prospect Place New Haven, CT 06511-3516 203-432-2460/FAX 203-432-7138

January 19, 1996

Monique B. Dillon Procurement Technician Office of Naval Research 495 Summer Street, Room 103 Boston, MA 02210-2109 RE:

N00014-90-J-4136

Dear Ms. Dillon: Enclosed please find a copy of the Final Technical Report for the referenced grant which was submitted in September 1995 to the program director. Also enclosed is a copy of the Final Invention Statement which was sent to your office in October 1995. A copy of the technical report is also sent forwarded to the Defense Technical Information. Cordially,

Sally S. Tremaine Assistant Director

Enclosures cc:

Defense Technical Information Center (w/enc.)

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September?, 1995 Thomas M McKenna Office of Naval Research Code 1142/BI Division of Cogniüve &. Neural Sciences 800 North Quincy Street - Room #823 Arlington, VA 22217-5660 Re: MBD 4330 Ser. 479 08 Aug. 1995 Dear Dr. McKenna: . . f Following is the final technical report on the gr ant »SeH-0 ^™at way back. ... *„ To reverse-engineer the learning machinery of the brain it is necessary to

synapuc plasticity. 0„r hypothesis has been that learning is a function not only of the training imr n>pw"g^ "aa • of the individua neurons—especially their

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specializes in circuit simulations using fast parallel implementations. The research has produced numerous publications and abstracts plus nr^entiuonsatTeveral meetings. There have been major technical, theoretical V ^^^%^^oJs. The new technology will resuIt u.i cor^ereid developments and significant scienüfic advances. Transitions to industry have been numerous. .

responsible for the anatomacal aspects of this project. _ • As Drorrmed we developed computational models of all of the principal types o?h^Äneurons-CA3 pyrarnidal neurons, CAl pyramidal neurons,

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cells of the den,, ^^2«^^^^ ^nluSed have been published already (1.2] [i U11 ana sc ^ ^ is being d or are about to be submitted. A ma.tei■