ReviewFrontiers in psychology2022
How can artificial neural networks approximate the brain?
Review in Frontiers in psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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.
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.
Who cites it
12 citing papers in PubMed.
- Development of digital hardware for a spiking image recognition network employing a novel burst-based reinforcement learning approach.Scientific reports · 2025Article
- Machine Learning-Driven Paradigm for Polymer Aging Lifetime Prediction: Integrating Multi-Mechanism Coupling and Cross-Scale Modeling.Polymers · 2025Review
- Mapping EEG Metrics to Human Affective and Cognitive Models: An Interdisciplinary Scoping Review from a Cognitive Neuroscience Perspective.Biomimetics (Basel, Switzerland) · 2025Review
- Cardiac Heterogeneity Prediction by Cardio-Neural Network Simulation.Neuroinformatics · 2025Article
- Harnessing nanotechnology for stem-cell therapies: revolutionizing neurodegenerative disorder treatments - a state-of-the-art update.Frontiers in pharmacology · 2025Review
- The calcitron: A simple neuron model that implements many learning rules via the calcium control hypothesis.PLoS computational biology · 2025Article
- Neuroscientific insights about computer vision models: a concise review.Biological cybernetics · 2024Review
- Predictive model of in-hospital mortality in liver cirrhosis patients with hyponatremia: an artificial neural network approach.Scientific reports · 2024Article
- Being in Virtual Reality and Its Influence on Brain Health-An Overview of Benefits, Limitations and Prospects.Brain sciences · 2024Review
- Artificial Intelligence in Endodontics: A Scoping Review.Iranian endodontic journal · 2024Article
- Why medical professionals must learn mathematics and computing?Pakistan journal of medical sciences · 2024Article
- The artificial intelligence and machine learning in lung cancer immunotherapy.Journal of hematology & oncology · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The article reviews the history development of artificial neural networks (ANNs), then compares the differences between ANNs and brain networks in their constituent unit, network architecture, and dynamic principle. The authors offer five points of suggestion for ANNs development and ten questions to be investigated further for the interdisciplinary field of brain simulation. Even though brain is a super-complex system with 10
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.