When Do Microcircuits Produce Beyond-Pairwise Correlations?
Describing the collective activity of neural populations is a daunting task. Recent empirical studies in retina, however, suggest a vast simplification in how multi-neuron spiking occurs: the activity patterns of retinal ganglion cell populations under some conditions are nearly completely captured...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2014-02-01
|
| Series: | Frontiers in Computational Neuroscience |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fncom.2014.00010/full |
| _version_ | 1818290695041974272 |
|---|---|
| author | Andrea Katherine Barreiro Julijana eGjorgjieva Fred eRieke Eric eShea-Brown |
| author_facet | Andrea Katherine Barreiro Julijana eGjorgjieva Fred eRieke Eric eShea-Brown |
| author_sort | Andrea Katherine Barreiro |
| collection | DOAJ |
| description | Describing the collective activity of neural populations is a daunting task. Recent empirical studies in retina, however, suggest a vast simplification in how multi-neuron spiking occurs: the activity patterns of retinal ganglion cell populations under some conditions are nearly completely captured by pairwise interactions among neurons. In other circumstances, higher-order statistics are required and appear to be shaped by input statistics and intrinsic circuit mechanisms.<br/><br/>Here, we study the emergence of higher-order interactions in a model of the retinal ganglion cell (RGC) circuit in which correlations are generated by common input. We quantify the impact of higher-order interactions by comparing the responses of mechanistic circuit models vs. null descriptions in which all higher-than-pairwise correlations have been accounted for by lower order statistics; these are known as pairwise maximum entropy models. We find that over a broad range of stimuli, output spiking patterns are surprisingly well captured by the pairwise model.<br/><br/>To understand this finding, we study an analytically tractable simplification of the RGC model. We find that in the simplified model, bimodal input signals produce larger deviations from pairwise predictions than unimodal inputs. The characteristic light filtering properties of the upstream RGC circuitry suppress bimodality in light stimuli, thus removing a powerful source of higher-order interactions. This provides a novel explanation for the surprising empirical success of pairwise models. |
| first_indexed | 2024-12-13T02:32:15Z |
| format | Article |
| id | doaj.art-201cac2605de4c51b81b117f1ae46df8 |
| institution | Directory Open Access Journal |
| issn | 1662-5188 |
| language | English |
| last_indexed | 2024-12-13T02:32:15Z |
| publishDate | 2014-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Computational Neuroscience |
| spelling | doaj.art-201cac2605de4c51b81b117f1ae46df82022-12-22T00:02:29ZengFrontiers Media S.A.Frontiers in Computational Neuroscience1662-51882014-02-01810.3389/fncom.2014.0001061336When Do Microcircuits Produce Beyond-Pairwise Correlations?Andrea Katherine Barreiro0Julijana eGjorgjieva1Fred eRieke2Eric eShea-Brown3Southern Methodist UniversityHarvard UniversityUniversity of WashingtonUniversity of WashingtonDescribing the collective activity of neural populations is a daunting task. Recent empirical studies in retina, however, suggest a vast simplification in how multi-neuron spiking occurs: the activity patterns of retinal ganglion cell populations under some conditions are nearly completely captured by pairwise interactions among neurons. In other circumstances, higher-order statistics are required and appear to be shaped by input statistics and intrinsic circuit mechanisms.<br/><br/>Here, we study the emergence of higher-order interactions in a model of the retinal ganglion cell (RGC) circuit in which correlations are generated by common input. We quantify the impact of higher-order interactions by comparing the responses of mechanistic circuit models vs. null descriptions in which all higher-than-pairwise correlations have been accounted for by lower order statistics; these are known as pairwise maximum entropy models. We find that over a broad range of stimuli, output spiking patterns are surprisingly well captured by the pairwise model.<br/><br/>To understand this finding, we study an analytically tractable simplification of the RGC model. We find that in the simplified model, bimodal input signals produce larger deviations from pairwise predictions than unimodal inputs. The characteristic light filtering properties of the upstream RGC circuitry suppress bimodality in light stimuli, thus removing a powerful source of higher-order interactions. This provides a novel explanation for the surprising empirical success of pairwise models.http://journal.frontiersin.org/Journal/10.3389/fncom.2014.00010/fullRetinal Ganglion CellsComputational modelscorrelationsmaximum entropy distributionstimulus-driven |
| spellingShingle | Andrea Katherine Barreiro Julijana eGjorgjieva Fred eRieke Eric eShea-Brown When Do Microcircuits Produce Beyond-Pairwise Correlations? Frontiers in Computational Neuroscience Retinal Ganglion Cells Computational models correlations maximum entropy distribution stimulus-driven |
| title | When Do Microcircuits Produce Beyond-Pairwise Correlations? |
| title_full | When Do Microcircuits Produce Beyond-Pairwise Correlations? |
| title_fullStr | When Do Microcircuits Produce Beyond-Pairwise Correlations? |
| title_full_unstemmed | When Do Microcircuits Produce Beyond-Pairwise Correlations? |
| title_short | When Do Microcircuits Produce Beyond-Pairwise Correlations? |
| title_sort | when do microcircuits produce beyond pairwise correlations |
| topic | Retinal Ganglion Cells Computational models correlations maximum entropy distribution stimulus-driven |
| url | http://journal.frontiersin.org/Journal/10.3389/fncom.2014.00010/full |
| work_keys_str_mv | AT andreakatherinebarreiro whendomicrocircuitsproducebeyondpairwisecorrelations AT julijanaegjorgjieva whendomicrocircuitsproducebeyondpairwisecorrelations AT frederieke whendomicrocircuitsproducebeyondpairwisecorrelations AT ericesheabrown whendomicrocircuitsproducebeyondpairwisecorrelations |