ArticleNature machine intelligence2020
Rapid online learning and robust recall in a neuromorphic olfactory circuit.
Article in Nature machine intelligence, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 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
44 citing papers in PubMed.
- Tailoring Chemiresistive Nanomaterials Toward Integrated Circuit Compatible Fabrication of Gas Sensors.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- Boosting Artificial Olfaction: Visual Cues-Enhanced Gas Classification by a Bimodal Neuromorphic Device.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- Neural rhythms as priors of speech computations.Patterns (New York, N.Y.) · 2026Article
- Neuromorphic Devices and Computing for Sensing, Memory, and Control.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Realization of the Bienenstock-Cooper-Munro rule in a single memristor.Nature communications · 2026Article
- Spike-Driven Neuromorphic Sensing for Energy-Proportional Indoor Air Quality Monitoring in Multi-Zone IoT-Enabled Smart Building Environments.Sensors (Basel, Switzerland) · 2026Article
- Cross-modal applications of a neuromorphic olfactory learning algorithm.bioRxiv : the preprint server for biology · 2026Article
- A highly energy-efficient multi-core neuromorphic architecture for training deep spiking neural networks.Nature communications · 2026Article
- Programmable ferroelectric rectifier for reliable and efficient neuromorphic crossbar array.Nature communications · 2026Article
- Biologically grounded neocortex computational primitives implemented on neuromorphic hardware improve vision transformer performance.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Research on parallel computing of the olfactory neural network based on multithreading.Scientific reports · 2025Article
- Efficient and robust temporal processing with neural oscillations modulated spiking neural networks.Nature communications · 2025Article
- Odor encoding by fine-timescale spike synchronization patterns in the olfactory bulb.Journal of neurophysiology · 2025Article
- Heterogeneous quantization regularizes spiking neural network activity.Scientific reports · 2025Article
- Optimizing Sensor Placement for Event Detection: A Case Study in Gaseous Chemical Detection.Sensors (Basel, Switzerland) · 2025Article
- A simple model for Behavioral Time Scale Synaptic Plasticity (BTSP) provides content addressable memory with binary synapses and one-shot learning.Nature communications · 2025Article
- The backpropagation algorithm implemented on spiking neuromorphic hardware.Nature communications · 2024Article
- Monolithically integrated neuromorphic electronic skin for biomimetic radiation shielding.Science advances · 2024Article
- Robust compression and detection of epileptiform patterns in ECoG using a real-time spiking neural network hardware framework.Nature communications · 2024Article
- Coherent olfactory bulb gamma oscillations arise from coupling independent columnar oscillators.Journal of neurophysiology · 2024Article
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
Abstract
We present a neural algorithm for the rapid online learning and identification of odourant samples under noise, based on the architecture of the mammalian olfactory bulb and implemented on the Intel Loihi neuromorphic system. As with biological olfaction, the spike timing-based algorithm utilizes distributed, event-driven computations and rapid (one-shot) online learning. Spike timing-dependent plasticity rules operate iteratively over sequential gamma-frequency packets to construct odour representations from the activity of chemosensor arrays mounted in a wind tunnel. Learned odourants then are reliably identified despite strong destructive interference. Noise resistance is further enhanced by neuromodulation and contextual priming. Lifelong learning capabilities are enabled by adult neurogenesis. The algorithm is applicable to any signal identification problem in which high-dimensional signals are embedded in unknown backgrounds.
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.