Evidence map›Paper›PMID 38045255›Full record

ArticlebioRxiv : the preprint server for biology2023

Compact deep neural network models of visual cortex.

Benjamin R Cowley, Patricia L Stan, Jonathan W Pillow, Matthew A Smith

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Benjamin R CowleyCold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.ORCID 0000-0003-2681-2448
Patricia L StanNeuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
Jonathan W PillowPrinceton Neuroscience Institute, Princeton University, Princeton, NJ, USA.ORCID 0000-0002-3638-8831
Matthew A SmithNeuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA.ORCID 0000-0003-1192-9942

Funding

Subcortical Neural Coding and DynamicsU19NS104648 · NINDS · PRINCETON UNIVERSITY · PI BRODY, CARLOS D · 2017 to 2021
$15.3M
Interdisciplinary Visual Sciences (IVS) Traininig ProgramT32EY017271 · NEI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Marlene Behrmann, Paul R. Kinchington · 2008 to 2026
$3.6M
Dissecting Sensorimotor Pathways Underlying Social Interactions: Models, Circuits, and BehaviorR01NS104899 · NINDS · PRINCETON UNIVERSITY · PI BIALEK, WILLIAM, MURTHY, MALA · 2018 to 2022
$2.4M
CRCNS: Modulating Neural Population Interactions between Cortical AreasR01MH118929 · NIMH · CARNEGIE-MELLON UNIVERSITY · PI SMITH, MATTHEW A, YU, BYRON M. · 2018 to 2022
$1.7M
Dynamic population codes for perceptionR01EY029250 · NEI · CARNEGIE-MELLON UNIVERSITY · PI SMITH, MATTHEW A · 2020 to 2023
$1.3M
Real-time statistical algorithms for controlling neural dynamics and behaviorR01EB026946 · NIBIB · STATE UNIVERSITY NEW YORK STONY BROOK · PI PARK, IL MEMMING, PILLOW, JONATHAN WILLIAM · 2018 to 2020
$1.1M
Neuronal population dynamics within and across cortical areasR01EB026953 · NIBIB · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI DOIRON, BRENT D., SMITH, MATTHEW A · 2018 to 2020
$1.0M
The influence of task context on neural population activity during natural scene discriminationF31EY031975 · NEI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI STAN, PATRICIA LENA · 2021 to 2022
$93k
NEI NIH HHS F31 EY031975NEI NIH HHS R01 EY029250NEI NIH HHS T32 EY017271NIBIB NIH HHS R01 EB026946NIBIB NIH HHS R01 EB026953NIMH NIH HHS R01 MH118929NINDS NIH HHS R01 NS104899NINDS NIH HHS U19 NS104648
6 · The paper itself

Abstract

A powerful approach to understanding the computations carried out in visual cortex is to develop models that predict neural responses to arbitrary images. Deep neural network (DNN) models have worked remarkably well at predicting neural responses [1, 2, 3], yet their underlying computations remain buried in millions of parameters. Have we simply replaced one complicated system

Identifiers

PMID38045255
PMCPMC10690296

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.