A Point Process Model for Auditory Neurons Considering Both Their Intrinsic Dynamics and the Spectrotemporal Properties of an Extrinsic Signal
We propose a point process model of spiking activity from auditory neurons. The model takes account of the neuron's intrinsic dynamics as well as the spectrotemporal properties of an input stimulus. A discrete Volterra expansion is used to derive the form of the conditional intensity function....
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| Format: | Article |
| Language: | en_US |
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Institute of Electrical and Electronics Engineers (IEEE)
2014
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| Online Access: | http://hdl.handle.net/1721.1/86313 https://orcid.org/0000-0003-2668-7819 https://orcid.org/0000-0003-1349-9608 |
| _version_ | 1811071855988047872 |
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| author | Plourde, Eric Delgutte, Bertrand Brown, Emery N. |
| author2 | Harvard University--MIT Division of Health Sciences and Technology |
| author_facet | Harvard University--MIT Division of Health Sciences and Technology Plourde, Eric Delgutte, Bertrand Brown, Emery N. |
| author_sort | Plourde, Eric |
| collection | MIT |
| description | We propose a point process model of spiking activity from auditory neurons. The model takes account of the neuron's intrinsic dynamics as well as the spectrotemporal properties of an input stimulus. A discrete Volterra expansion is used to derive the form of the conditional intensity function. The Volterra expansion models the neuron's baseline spike rate, its intrinsic dynamics-spiking history-and the stimulus effect which in this case is the analog of the spectrotemporal receptive field (STRF). We performed the model fitting efficiently in a generalized linear model framework using ridge regression to address properly this ill-posed maximum likelihood estimation problem. The model provides an excellent fit to spiking activity from 55 auditory nerve neurons. The STRF-like representation estimated jointly with the neuron's intrinsic dynamics may offer more accurate characterizations of neural activity in the auditory system than current ones based solely on the STRF. |
| first_indexed | 2024-09-23T08:57:07Z |
| format | Article |
| id | mit-1721.1/86313 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T08:57:07Z |
| publishDate | 2014 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/863132022-09-26T09:24:30Z A Point Process Model for Auditory Neurons Considering Both Their Intrinsic Dynamics and the Spectrotemporal Properties of an Extrinsic Signal Plourde, Eric Delgutte, Bertrand Brown, Emery N. Harvard University--MIT Division of Health Sciences and Technology Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences Massachusetts Institute of Technology. Research Laboratory of Electronics Plourde, Eric Delgutte, Bertrand Brown, Emery N. We propose a point process model of spiking activity from auditory neurons. The model takes account of the neuron's intrinsic dynamics as well as the spectrotemporal properties of an input stimulus. A discrete Volterra expansion is used to derive the form of the conditional intensity function. The Volterra expansion models the neuron's baseline spike rate, its intrinsic dynamics-spiking history-and the stimulus effect which in this case is the analog of the spectrotemporal receptive field (STRF). We performed the model fitting efficiently in a generalized linear model framework using ridge regression to address properly this ill-posed maximum likelihood estimation problem. The model provides an excellent fit to spiking activity from 55 auditory nerve neurons. The STRF-like representation estimated jointly with the neuron's intrinsic dynamics may offer more accurate characterizations of neural activity in the auditory system than current ones based solely on the STRF. 2014-05-01T13:07:50Z 2014-05-01T13:07:50Z 2011-02 Article http://purl.org/eprint/type/JournalArticle 0018-9294 1558-2531 http://hdl.handle.net/1721.1/86313 Plourde, Eric, Bertrand Delgutte, and Emery N Brown. “A Point Process Model for Auditory Neurons Considering Both Their Intrinsic Dynamics and the Spectrotemporal Properties of an Extrinsic Signal.” IEEE Trans. Biomed. Eng. 58, no. 6 (n.d.): 1507–1510. https://orcid.org/0000-0003-2668-7819 https://orcid.org/0000-0003-1349-9608 en_US http://dx.doi.org/10.1109/tbme.2011.2113349 IEEE Transactions on Biomedical Engineering Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) PMC |
| spellingShingle | Plourde, Eric Delgutte, Bertrand Brown, Emery N. A Point Process Model for Auditory Neurons Considering Both Their Intrinsic Dynamics and the Spectrotemporal Properties of an Extrinsic Signal |
| title | A Point Process Model for Auditory Neurons Considering Both Their Intrinsic Dynamics and the Spectrotemporal Properties of an Extrinsic Signal |
| title_full | A Point Process Model for Auditory Neurons Considering Both Their Intrinsic Dynamics and the Spectrotemporal Properties of an Extrinsic Signal |
| title_fullStr | A Point Process Model for Auditory Neurons Considering Both Their Intrinsic Dynamics and the Spectrotemporal Properties of an Extrinsic Signal |
| title_full_unstemmed | A Point Process Model for Auditory Neurons Considering Both Their Intrinsic Dynamics and the Spectrotemporal Properties of an Extrinsic Signal |
| title_short | A Point Process Model for Auditory Neurons Considering Both Their Intrinsic Dynamics and the Spectrotemporal Properties of an Extrinsic Signal |
| title_sort | point process model for auditory neurons considering both their intrinsic dynamics and the spectrotemporal properties of an extrinsic signal |
| url | http://hdl.handle.net/1721.1/86313 https://orcid.org/0000-0003-2668-7819 https://orcid.org/0000-0003-1349-9608 |
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