Abstract
Response properties of sensory neurons are commonly described using receptive fields. This description may be formalized in a model that operates with a small set of linear filters whose outputs are nonlinearly combined to determine the instantaneous firing rate. Spike-triggered average and covariance analyses can be used to estimate the filters and nonlinear combination rule from extracellular experimental data. We describe this methodology, demonstrating it with simulated model neuron examples that emphasize practical issues that arise in experimental situations.
| Original language | English (US) |
|---|---|
| Article number | 13 |
| Pages (from-to) | 484-507 |
| Number of pages | 24 |
| Journal | Journal of vision |
| Volume | 6 |
| Issue number | 4 |
| DOIs | |
| State | Published - Jul 17 2006 |
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Keywords
- Characterization
- Neural response
- Nonlinear
- Receptive field
- Reverse correlation
- Spike-triggered analysis
ASJC Scopus subject areas
- Ophthalmology
Cite this
Spike-triggered neural characterization. / Schwartz, Odelia; Pillow, Jonathan W.; Rust, Nicole C.; Simoncelli, Eero.
In: Journal of vision, Vol. 6, No. 4, 13, 17.07.2006, p. 484-507.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Spike-triggered neural characterization
AU - Schwartz, Odelia
AU - Pillow, Jonathan W.
AU - Rust, Nicole C.
AU - Simoncelli, Eero
PY - 2006/7/17
Y1 - 2006/7/17
N2 - Response properties of sensory neurons are commonly described using receptive fields. This description may be formalized in a model that operates with a small set of linear filters whose outputs are nonlinearly combined to determine the instantaneous firing rate. Spike-triggered average and covariance analyses can be used to estimate the filters and nonlinear combination rule from extracellular experimental data. We describe this methodology, demonstrating it with simulated model neuron examples that emphasize practical issues that arise in experimental situations.
AB - Response properties of sensory neurons are commonly described using receptive fields. This description may be formalized in a model that operates with a small set of linear filters whose outputs are nonlinearly combined to determine the instantaneous firing rate. Spike-triggered average and covariance analyses can be used to estimate the filters and nonlinear combination rule from extracellular experimental data. We describe this methodology, demonstrating it with simulated model neuron examples that emphasize practical issues that arise in experimental situations.
KW - Characterization
KW - Neural response
KW - Nonlinear
KW - Receptive field
KW - Reverse correlation
KW - Spike-triggered analysis
UR - http://www.scopus.com/inward/record.url?scp=33746478189&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33746478189&partnerID=8YFLogxK
U2 - 10.1167/6.4.13
DO - 10.1167/6.4.13
M3 - Article
VL - 6
SP - 484
EP - 507
JO - Journal of vision
JF - Journal of vision
SN - 1534-7362
IS - 4
M1 - 13
ER -