Evidence map›Paper›PMID 30441667›Full record

ArticleAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference2018

Point Process Filtering Estimates of Branching Rate for Neural Dendritic Morphology Generation.

Zane Z Chou, Gene J Yu, Theodore W Berger

Abstract read
In one paragraph

Article in Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2018. 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

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.

Zane Z Chou
Gene J Yu
Theodore W Berger

Funding

TrainingP41EB001978 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI KHOO, MICHAEL C K · 2003 to 2017
$18.1M
Predictive modeling of bioelectric activity on mammalian multilayered neuronal stU01GM104604 · NIGMS · UNIVERSITY OF UTAH · PI BERGER, THEODORE W., LAZZI, GIANLUCA · 2012 to 2016
$2.8M
PREDICTIVE MODELING OF BIOELECTRIC ACTIVITY ON MAMMALIAN MULTILAYERED NEURONAL STRUCTURES IN THE PRESENCE OF SUPRAPHYSIOLOGICAL ELECTRIC FIELDSU01EB025830 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI BERGER, THEODORE W., LAZZI, GIANLUCA · 2018 to 2021
$2.7M
NIBIB NIH HHS P41 EB001978NIBIB NIH HHS U01 EB025830NIGMS NIH HHS U01 GM104604
6 · The paper itself

Abstract

Current parametric approaches to dendritic morphology generation are limited in their ability to replicate realistic branching. A non-parametric approach applying a point process filter and the expectation-maximization algorithm offers a data-based solution that estimates the dendritic branching rate based on observations of bifurcation events in real neurons. Point processes can then be simulated using this branching rate estimate to indicate when a generated morphology should branch. Morphologies generated using this technique match both basic and emergent property distributions of the real neurons used as input into the algorithm. Further refinement of branching angles will allow for a flexible tool to generate realistic morphologies of a variety of neuronal stereotypes.

Indexed as

Computer SimulationDendritesAlgorithmsHumansNeurons

Identifiers

PMID30441667
PMCPMC6453578

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

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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.