ArticleeLife2021
Spike frequency adaptation supports network computations on temporally dispersed information.
Article in eLife, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- A Reconfigurable Memristive Spiking Neuron Enabling Advanced Neuromorphic Computing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Neural timescales from a computational perspective.Nature neuroscience · 2026Review
- Article
- Adaptation modulates effective connectivity and network stability.Frontiers in computational neuroscience · 2026Article
- SpikeAEC: a neuromodulation-based spiking controller for explore-exploit balancing in mobile robots.Frontiers in neurorobotics · 2026Article
- Dysregulated cortical excitability and tau phosphorylation in a β3 integrin mouse model of autism.Brain : a journal of neurology · 2025Article
- In Search of Transcriptomic Correlates of Neuronal Firing-Rate Adaptation across Subtypes, Regions and Species: A Patch-seq Analysis.bioRxiv : the preprint server for biology · 2025Article
- Advancing spatio-temporal processing through adaptation in spiking neural networks.Nature communications · 2025Article
- Neuropeptide-Dependent Spike Time Precision and Plasticity in Circadian Output Neurons.The European journal of neuroscience · 2025Article
- Recurrent neural networks with transient trajectory explain working memory encoding mechanisms.Communications biology · 2025Article
- Neural heterogeneity enables adaptive encoding of time sequences.Communications physics · 2025Article
- Neural networks with optimized single-neuron adaptation uncover biologically plausible regularization.PLoS computational biology · 2024Article
- Spiking attractor model of motor cortex explains modulation of neural and behavioral variability by prior target information.Nature communications · 2024Article
- Fast learning without synaptic plasticity in spiking neural networks.Scientific reports · 2024Article
- Temporal dendritic heterogeneity incorporated with spiking neural networks for learning multi-timescale dynamics.Nature communications · 2024Article
- Exploring neural oscillations during speech perception via surrogate gradient spiking neural networks.Frontiers in neuroscience · 2024Article
- Co-learning synaptic delays, weights and adaptation in spiking neural networks.Frontiers in neuroscience · 2024Article
- SpikingJelly: An open-source machine learning infrastructure platform for spike-based intelligence.Science advances · 2023Article
- A neuromorphic physiological signal processing system based on VONature communications · 2023Article
- Heterogeneity in Neuronal Dynamics Is Learned by Gradient Descent for Temporal Processing Tasks.Neural computation · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
For solving tasks such as recognizing a song, answering a question, or inverting a sequence of symbols, cortical microcircuits need to integrate and manipulate information that was dispersed over time during the preceding seconds. Creating biologically realistic models for the underlying computations, especially with spiking neurons and for behaviorally relevant integration time spans, is notoriously difficult. We examine the role of spike frequency adaptation in such computations and find that it has a surprisingly large impact. The inclusion of this well-known property of a substantial fraction of neurons in the neocortex - especially in higher areas of the human neocortex - moves the performance of spiking neural network models for computations on network inputs that are temporally dispersed from a fairly low level up to the performance level of the human brain.
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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.