Evidence map›Paper›PMID 39567436›Full record

ArticleAnnals of the New York Academy of Sciences2024

Neuromorphic engineering: Artificial brains for artificial intelligence.

Johannes Leugering

Abstract read
In one paragraph

Article in Annals of the New York Academy of Sciences, 2024. 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.

  1. Neuromorphic engineering: Artificial brains for artificial intelligence.Annals of the New York Academy of Sciences · 2024
    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

1 author.

Johannes LeugeringInstitute for Neural Computation, University of California San Diego, La Jolla, California, USA.ORCID 0000-0003-0956-4139

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neuromorphic engineering is a research discipline that tries to bridge the gaps between neuroscience and engineering, cognition and algorithms, and natural and artificial intelligence. Neuromorphic engineering promises revolutionary breakthroughs that could rapidly advance our understanding of the brain and pave the way toward more human-like and sustainable artificial intelligence. But first, it will have to find its way out of the laboratory.

Indexed as

Artificial IntelligenceBrainAlgorithmsCognitionHumansNeural Networks, ComputerNeurosciencesAIarchitecturecomputationneuromorphic engineering

Identifiers

PMID39567436
PMCPMC11668493

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.