ArticleProceedings of the National Academy of Sciences of the United States of America2017
Balanced excitation and inhibition are required for high-capacity, noise-robust neuronal selectivity.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers, 1 of them a synthesis that pooled 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.
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
59 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Cortical control of chandelier cells in neural codes.Frontiers in cellular neuroscience · 2022Pooled it
- Critical neuronal avalanches arise from excitation-inhibition balanced spontaneous activity.iScience · 2026Article
- Viscoelastic nanomechanical devices for neuromorphic information processing.Science advances · 2026Article
- APP family in inhibitory neurons controls inhibitory recruitment and short-term plasticity in the hippocampus.Molecular brain · 2026Article
- From cortical and white matter structure to meaning: a brain-constrained neural network of semantic grounding in action and perception.Frontiers in human neuroscience · 2026Article
- Interactions between long- and short-term synaptic plasticity transform temporal neural representations into spatial.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Two-factor synaptic consolidation reconciles robustness with pruning and homeostatic scaling.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Ventral striatal astrocytes contribute to reinforcement learning.bioRxiv : the preprint server for biology · 2025Article
- Article
- Interleaving asynchronous and synchronous activity in balanced cortical networks with short term synaptic depression.Nature communications · 2025Article
- The dorsal column nuclei encode and transmit the network signatures of mechanical allodynia.Cell reports · 2025Article
- Sparse Learning Enabled by Constraints on Connectivity and Function.Physical review letters · 2025Article
- Rhythmic circuit function is more robust to changes in synaptic than intrinsic conductances.eLife · 2025Article
- Article
- Level of M1 GABAB predicts micro offline consolidation of motor learning during wakefulness.NPJ science of learning · 2025Article
- Associations Among EEG Aperiodic Slope, Infant Temperament, and Maternal Anxiety/Depression Symptoms in Infancy.Psychophysiology · 2025Article
- Inhibitory plasticity supports replay generalization in the hippocampus.Nature neuroscience · 2024Article
- Sub-threshold neuronal activity and the dynamical regime of cerebral cortex.Nature communications · 2024Article
- Spiking attractor model of motor cortex explains modulation of neural and behavioral variability by prior target information.Nature communications · 2024Article
- Early excitatory-inhibitory cortical modifications following skill learning are associated with motor memory consolidation and plasticity overnight.Nature communications · 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
3 authors.
Funding
Abstract
Neurons and networks in the cerebral cortex must operate reliably despite multiple sources of noise. To evaluate the impact of both input and output noise, we determine the robustness of single-neuron stimulus selective responses, as well as the robustness of attractor states of networks of neurons performing memory tasks. We find that robustness to output noise requires synaptic connections to be in a balanced regime in which excitation and inhibition are strong and largely cancel each other. We evaluate the conditions required for this regime to exist and determine the properties of networks operating within it. A plausible synaptic plasticity rule for learning that balances weight configurations is presented. Our theory predicts an optimal ratio of the number of excitatory and inhibitory synapses for maximizing the encoding capacity of balanced networks for given statistics of afferent activations. Previous work has shown that balanced networks amplify spatiotemporal variability and account for observed asynchronous irregular states. Here we present a distinct type of balanced network that amplifies small changes in the impinging signals and emerges automatically from learning to perform neuronal and network functions robustly.
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.