ReviewNature2022
Dendrocentric learning for synthetic intelligence.
Review in Nature, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
What it found
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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.
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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.
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Who cites it
29 citing papers in PubMed.
- Towards neuromorphic neurotechnologies: integrating brain-inspired computing with brain-computer interfaces.npj biomedical innovations · 2026Review
- Voltage dynamics of cortical dendrites in vivo.Nature neuroscience · 2026Article
- Homeostatic dendritic neuron based on co-integrated volatile and non-volatile memristors for neuromorphic processing.Nature communications · 2026Article
- Higher-order neuromorphic Ising machines-autoencoders and Fowler-Nordheim annealers are all you need for scalability.Nature communications · 2026Article
- Brain-inspired energy efficient technologies for next-generation artificial intelligence.Biological cybernetics · 2026Review
- Plastic Arbor: A modern simulation framework for synaptic plasticity-From single synapses to networks of morphological neurons.PLoS computational biology · 2026Article
- A dendrite-resolved,bioRxiv : the preprint server for biology · 2026Article
- A deterministic neuromorphic architecture with scalable time synchronization.Nature communications · 2025Article
- Exploiting neuro-inspired dynamic sparsity for energy-efficient intelligent perception.Nature communications · 2025Review
- Ripple contributions to human memory: making the spiking content count.Nature reviews. Neuroscience · 2025Review
- A neuromorphic processor with on-chip learning for beyond-CMOS device integration.Nature communications · 2025Article
- Artificial intelligence meets brain theory (again).Biological cybernetics · 2025Review
- Neuron-astrocyte associative memory.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Attention to memory content enhances single-unit spike sequence fidelity in the human anterior temporal lobe.Current biology : CB · 2025Article
- Dendritic excitations govern back-propagation via a spike-rate accelerometer.Nature communications · 2025Article
- Memristive Ion Dynamics to Enable Biorealistic Computing.Chemical reviews · 2025Review
- Neuromorphic computing at scale.Nature · 2025Review
- Evaluation of fluxon synapse device based on superconducting loops for energy efficient neuromorphic computing.Frontiers in neuroscience · 2025Article
- Article
- Focal seizures induce spatiotemporally organized spiking activity in the human cortex.Nature communications · 2024Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence now advances by performing twice as many floating-point multiplications every two months, but the semiconductor industry tiles twice as many multipliers on a chip every two years. Moreover, the returns from tiling these multipliers ever more densely now diminish because signals must travel relatively farther and farther. Although travel can be shortened by stacking tiled multipliers in a three-dimensional chip, such a solution acutely reduces the available surface area for dissipating heat. Here I propose to transcend this three-dimensional thermal constraint by moving away from learning with synapses to learning with dendrites. Synaptic inputs are not weighted precisely but rather ordered meticulously along a short stretch of dendrite, termed dendrocentric learning. With the help of a computational model of a dendrite and a conceptual model of a ferroelectric device that emulates it, I illustrate how dendrocentric learning artificial intelligence-or synthetic intelligence for short-could run not with megawatts in the cloud but rather with watts on a smartphone.
Identifiers
36450907What 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.