Sparse Functional Identification of Complex Cells from Spike Times and the Decoding of Visual Stimuli.

Aurel A Lazar, Nikul H Ukani, Yiyin Zhou

Abstract read

In one paragraph

Article in Journal of mathematical neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

Sparse identification of contrast gain control in the fruit fly photoreceptor and amacrine cell layer.Journal of mathematical neuroscience · 2020
Article

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Aurel A LazarDepartment of Electrical Engineering, Columbia University, 500 W 120th Street, Mudd 1300, New York, NY, 10027, USA. aurel@ee.columbia.edu.

Nikul H UkaniDepartment of Electrical Engineering, Columbia University, 500 W 120th Street, Mudd 1300, New York, NY, 10027, USA.

Yiyin ZhouDepartment of Electrical Engineering, Columbia University, 500 W 120th Street, Mudd 1300, New York, NY, 10027, USA.

Funding

Air Force Office of Scientific Research FA9550-16-1-0410

6 · The paper itself

Abstract

We investigate the sparse functional identification of complex cells and the decoding of spatio-temporal visual stimuli encoded by an ensemble of complex cells. The reconstruction algorithm is formulated as a rank minimization problem that significantly reduces the number of sampling measurements (spikes) required for decoding. We also establish the duality between sparse decoding and functional identification and provide algorithms for identification of low-rank dendritic stimulus processors. The duality enables us to efficiently evaluate our functional identification algorithms by reconstructing novel stimuli in the input space. Finally, we demonstrate that our identification algorithms substantially outperform the generalized quadratic model, the nonlinear input model, and the widely used spike-triggered covariance algorithm.

Indexed as

Complex cellsDendritic stimulus processorsDuality between decoding and functional identificationEncoding of visual stimuliQuadratic receptive fieldsSparse functional identificationSparse neural decoding

Identifiers

PMID29349664

DOI10.1186/s13408-017-0057-1

PMCPMC5773573

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.