ArticlePloS one2014
Selectivity and sparseness in randomly connected balanced networks.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 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
37 citing papers in PubMed.
- Structure, disorder, and dynamics in task-trained recurrent neural circuits.bioRxiv : the preprint server for biology · 2026Article
- Effective computations for hippocampal place cell phenomena in sparse untrained random networks.bioRxiv : the preprint server for biology · 2025Article
- Interleaving asynchronous and synchronous activity in balanced cortical networks with short term synaptic depression.Nature communications · 2025Article
- Article
- Circuit-Based Understanding of Fine Spatial Scale Clustering of Orientation Tuning in Mouse Visual Cortex.bioRxiv : the preprint server for biology · 2025Article
- Fast updating feedback from piriform cortex to the olfactory bulb relays multimodal identity and reward contingency signals during rule-reversal.Nature communications · 2025Article
- Geometry and dynamics of representations in a precisely balanced memory network related to olfactory cortex.eLife · 2025Article
- The spinal premotor network driving scratching flexor and extensor alternation.bioRxiv : the preprint server for biology · 2025Article
- Sub-threshold neuronal activity and the dynamical regime of cerebral cortex.Nature communications · 2024Article
- Remapping revisited: how the hippocampus represents different spaces.Nature reviews. Neuroscience · 2024Review
- Article
- Do Place Cells Dream of Deceptive Moves in a Signaling Game?Neuroscience · 2023Review
- Fast updating feedback from piriform cortex to the olfactory bulb relays multimodal reward contingency signals during rule-reversal.bioRxiv : the preprint server for biology · 2023Article
- Distributing task-related neural activity across a cortical network through task-independent connections.Nature communications · 2023Article
- Article
- Theory of hierarchically organized neuronal oscillator dynamics that mediate rodent rhythmic whisking.Neuron · 2022Article
- A cerebellum inspired spiking neural network as a multi-model for pattern classification and robotic trajectory prediction.Frontiers in neuroscience · 2022Article
- What is the dynamical regime of cerebral cortex?Neuron · 2021Review
- Article
- Randomly connected networks generate emergent selectivity and predict decoding properties of large populations of neurons.PLoS computational biology · 2020Article
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
Neurons in sensory cortex show stimulus selectivity and sparse population response, even in cases where no strong functionally specific structure in connectivity can be detected. This raises the question whether selectivity and sparseness can be generated and maintained in randomly connected networks. We consider a recurrent network of excitatory and inhibitory spiking neurons with random connectivity, driven by random projections from an input layer of stimulus selective neurons. In this architecture, the stimulus-to-stimulus and neuron-to-neuron modulation of total synaptic input is weak compared to the mean input. Surprisingly, we show that in the balanced state the network can still support high stimulus selectivity and sparse population response. In the balanced state, strong synapses amplify the variation in synaptic input and recurrent inhibition cancels the mean. Functional specificity in connectivity emerges due to the inhomogeneity caused by the generative statistical rule used to build the network. We further elucidate the mechanism behind and evaluate the effects of model parameters on population sparseness and stimulus selectivity. Network response to mixtures of stimuli is investigated. It is shown that a balanced state with unselective inhibition can be achieved with densely connected input to inhibitory population. Balanced networks exhibit the "paradoxical" effect: an increase in excitatory drive to inhibition leads to decreased inhibitory population firing rate. We compare and contrast selectivity and sparseness generated by the balanced network to randomly connected unbalanced networks. Finally, we discuss our results in light of experiments.
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.