Heterogeneous gain distributions in neural networks I:The stationary case
We study heterogeneous distribution of gains in neural fields using techniques of quantum mechanics by exploiting a relationship of our model and the time-independent Schr\"{o}dinger equation. We show that specific relationships between the connectivity kernel and the gain of the population can...
Saved in:
| Main Authors | , , |
|---|---|
| Format | Journal Article |
| Language | English |
| Published |
02.02.2017
|
| Subjects | |
| Online Access | Get full text |
Cover
Loading…
| Abstract | We study heterogeneous distribution of gains in neural fields using
techniques of quantum mechanics by exploiting a relationship of our model and
the time-independent Schr\"{o}dinger equation. We show that specific
relationships between the connectivity kernel and the gain of the population
can explain the behavior of the neural field in simulations. In particular, we
show this relationships for the gating of activity between two regions (step
potential), the propagation of activity throughout another region (barrier)
and, most importantly, the existence of bumps in gain-contained regions (gain
well). Our results constitute specific predictions that can be tested in vivo
or in vitro. |
|---|---|
| AbstractList | We study heterogeneous distribution of gains in neural fields using
techniques of quantum mechanics by exploiting a relationship of our model and
the time-independent Schr\"{o}dinger equation. We show that specific
relationships between the connectivity kernel and the gain of the population
can explain the behavior of the neural field in simulations. In particular, we
show this relationships for the gating of activity between two regions (step
potential), the propagation of activity throughout another region (barrier)
and, most importantly, the existence of bumps in gain-contained regions (gain
well). Our results constitute specific predictions that can be tested in vivo
or in vitro. |
| Author | Rodriguez, Alejandro Jimenez Ceballos, Juan Carlos Cordero Sanchez, Nestor E |
| Author_xml | – sequence: 1 givenname: Alejandro Jimenez surname: Rodriguez fullname: Rodriguez, Alejandro Jimenez – sequence: 2 givenname: Juan Carlos Cordero surname: Ceballos fullname: Ceballos, Juan Carlos Cordero – sequence: 3 givenname: Nestor E surname: Sanchez fullname: Sanchez, Nestor E |
| BackLink | https://doi.org/10.48550/arXiv.1702.00687$$DView paper in arXiv |
| BookMark | eNotj8tOwzAURL2ABRQ-gBX-gQQ_4jhmhyqgkSqxyT66da6LRbGR7fD4e9LC6kij0WjOJTkLMSAhN5zVTacUu4P07T9rrpmoGWs7fUH6DRZMcY8B45zpHnygk88l-d1cfAyZLkHAOcFhQfmK6S3T_n54RZoLHBuQfqiFjFfk3MEh4_U_V2R4ehzWm2r78tyvH7YVtFpXzc5KsE4L0QiFiAa4NhyVBGmatp3aqeksdhwkOmMcg04I5hRHZoVjysoVuf2bPbmMH8m_Lw_Go9N4cpK_QFpJuQ |
| ContentType | Journal Article |
| Copyright | http://arxiv.org/licenses/nonexclusive-distrib/1.0 |
| Copyright_xml | – notice: http://arxiv.org/licenses/nonexclusive-distrib/1.0 |
| DBID | ALC GOX |
| DOI | 10.48550/arxiv.1702.00687 |
| DatabaseName | arXiv Quantitative Biology arXiv.org |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: GOX name: arXiv.org url: http://arxiv.org/find sourceTypes: Open Access Repository |
| DeliveryMethod | fulltext_linktorsrc |
| ExternalDocumentID | 1702_00687 |
| GroupedDBID | ALC GOX |
| ID | FETCH-LOGICAL-a677-4bc3acf722425eee9a1791e53a39466d6d48ce81a3ef99f0a8220f51e0c2f05c3 |
| IEDL.DBID | GOX |
| IngestDate | Mon Jan 08 05:48:54 EST 2024 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-a677-4bc3acf722425eee9a1791e53a39466d6d48ce81a3ef99f0a8220f51e0c2f05c3 |
| OpenAccessLink | https://arxiv.org/abs/1702.00687 |
| ParticipantIDs | arxiv_primary_1702_00687 |
| PublicationCentury | 2000 |
| PublicationDate | 2017-02-02 |
| PublicationDateYYYYMMDD | 2017-02-02 |
| PublicationDate_xml | – month: 02 year: 2017 text: 2017-02-02 day: 02 |
| PublicationDecade | 2010 |
| PublicationYear | 2017 |
| Score | 1.6568754 |
| SecondaryResourceType | preprint |
| Snippet | We study heterogeneous distribution of gains in neural fields using
techniques of quantum mechanics by exploiting a relationship of our model and
the... |
| SourceID | arxiv |
| SourceType | Open Access Repository |
| SubjectTerms | Quantitative Biology - Neurons and Cognition |
| Title | Heterogeneous gain distributions in neural networks I:The stationary case |
| URI | https://arxiv.org/abs/1702.00687 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwdV07TwMxDLbaTiwIBKg8lYH1xF1yeRwbQpQWCViK1K3KJT7EckW9gsq_x747BAtLBscZYg-fHTufAS45JUCF_HJPSx6jTrx2WVJm6ArtbPAp_0Z-fDLTl_xhoRcDED9_Yfx6-_bZ8QOXzVVmWz5N4-wQhlJyy9b986IrTrZUXL3-rx7FmK3oD0hM9mC3j-7ETeeOfRhgfQCzKbecrMhTSGm2eKVcXETmq-1HTTWCBMwrSSfrriu7EbNrcqBoukK5X3-JQHBzCPPJ3fx2mvQTDBJvrE3yMigfKis5rkfEwjMZKGrlFdO6RxNzF9BlXmFVFFXqCa3TSmeYBlmlOqgjGNWrGscgkDI1mYZQZCHmqjSkrp03pvCmiqWVxzBu771870gqlmySZWuSk_-3TmFHMkxxF7I8g9Fm_YHnBLKb8qK19Dda7316 |
| link.rule.ids | 228,230,780,885 |
| linkProvider | Cornell University |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Heterogeneous+gain+distributions+in+neural+networks+I%3AThe+stationary+case&rft.au=Rodriguez%2C+Alejandro+Jimenez&rft.au=Ceballos%2C+Juan+Carlos+Cordero&rft.au=Sanchez%2C+Nestor+E&rft.date=2017-02-02&rft_id=info:doi/10.48550%2Farxiv.1702.00687&rft.externalDocID=1702_00687 |