Analog VLSI circuit design of spike-timing-dependent synaptic plasticity
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.
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| Other Authors: | |
| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2010
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| Online Access: | http://hdl.handle.net/1721.1/54636 |
| _version_ | 1811088468716027904 |
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| author | Monzon, Joshua Jen C |
| author2 | Chi-Sang Poon. |
| author_facet | Chi-Sang Poon. Monzon, Joshua Jen C |
| author_sort | Monzon, Joshua Jen C |
| collection | MIT |
| description | Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008. |
| first_indexed | 2024-09-23T14:02:37Z |
| format | Thesis |
| id | mit-1721.1/54636 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T14:02:37Z |
| publishDate | 2010 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/546362019-04-12T23:37:33Z Analog VLSI circuit design of spike-timing-dependent synaptic plasticity Monzon, Joshua Jen C Chi-Sang Poon. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008. Cataloged from PDF version of thesis. Includes bibliographical references (p. 61-63). Synaptic plasticity is the ability of a synaptic connection to change in strength and is believed to be the basis for learning and memory. Currently, two types of synaptic plasticity exist. First is the spike-timing-dependent-plasticity (STDP), a timing-based protocol that suggests that the efficacy of synaptic connections is modulated by the relative timing between presynaptic and postsynaptic stimuli. The second type is the Bienenstock-Cooper-Munro (BCM) learning rule, a classical ratebased protocol which states that the rate of presynaptic stimulation modulates the synaptic strength. Several theoretical models were developed to explain the two forms of plasticity but none of these models came close in identifying the biophysical mechanism of plasticity. Other studies focused instead on developing neuromorphic systems of synaptic plasticity. These systems used simple curve fitting methods that were able to reproduce some types of STDP but still failed to shed light on the biophysical basis of STDP. Furthermore, none of these neuromorphic systems were able to reproduce the various forms of STDP and relate them to the BCM rule. However, a recent discovery resulted in a new unified model that explains the general biophysical process governing synaptic plasticity using fundamental ideas regarding the biochemical reactions and kinetics within the synapse. This brilliant model considers all types of STDP and relates them to the BCM rule, giving us a fresh new approach to construct a unique system that overcomes all the challenges that existing neuromorphic systems faced. Here, we propose a novel analog verylarge- scale-integration (aVLSI) circuit that successfully and accurately captures the whole picture of synaptic plasticity based from the results of this latest unified model. Our circuit was tested for all types of STDP and for each of these tests, our design was able to reproduce the results predicted by the new-found model. Two inputs are required by the system, a glutamate signal that carries information about the presynaptic stimuli and a dendritic action potential signal that contains information about the postsynaptic stimuli. These two inputs give rise to changes in the excitatory postsynaptic current which represents the modifiable synaptic efficacy output. Finally, we also present several techniques and alternative circuit designs that will further improve the performance of our neuromorphic system. by Joshua Jen C. Monzon. M.Eng. 2010-04-28T17:12:56Z 2010-04-28T17:12:56Z 2008 2008 Thesis http://hdl.handle.net/1721.1/54636 603548441 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 64 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Monzon, Joshua Jen C Analog VLSI circuit design of spike-timing-dependent synaptic plasticity |
| title | Analog VLSI circuit design of spike-timing-dependent synaptic plasticity |
| title_full | Analog VLSI circuit design of spike-timing-dependent synaptic plasticity |
| title_fullStr | Analog VLSI circuit design of spike-timing-dependent synaptic plasticity |
| title_full_unstemmed | Analog VLSI circuit design of spike-timing-dependent synaptic plasticity |
| title_short | Analog VLSI circuit design of spike-timing-dependent synaptic plasticity |
| title_sort | analog vlsi circuit design of spike timing dependent synaptic plasticity |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/54636 |
| work_keys_str_mv | AT monzonjoshuajenc analogvlsicircuitdesignofspiketimingdependentsynapticplasticity |