ArticleFrontiers in neuroengineering2014
Controlling neural network responsiveness: tradeoffs and constraints.
Article in Frontiers in neuroengineering, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed.
- Engineering Neuronal Network Connectivity Through Precise and Scalable Electrical Modulation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Engineered Biological Neural Networks on High Density CMOS Microelectrode Arrays.Frontiers in neuroscience · 2022Article
- Plasticity and Adaptation in Neuromorphic Biohybrid Systems.iScience · 2020Review
- Control of cortical oscillatory frequency by a closed-loop system.Journal of neuroengineering and rehabilitation · 2019Article
- A Biohybrid Setup for Coupling Biological and Neuromorphic Neural Networks.Frontiers in neuroscience · 2019Article
- Development of Cortical Networks under Continuous Stimulation.Frontiers in molecular neuroscience · 2017Article
- Autonomous Optimization of Targeted Stimulation of Neuronal Networks.PLoS computational biology · 2016Article
- Recovery of Dynamics and Function in Spiking Neural Networks with Closed-Loop Control.PLoS computational biology · 2016Article
- A Review of Control Strategies in Closed-Loop Neuroprosthetic Systems.Frontiers in neuroscience · 2016Review
- Closed-Loop Neuroscience and Non-Invasive Brain Stimulation: A Tale of Two Loops.Frontiers in cellular neuroscience · 2016Article
- In vitro studies of neuronal networks and synaptic plasticity in invertebrates and in mammals using multielectrode arrays.Neural plasticity · 2015Review
- Interaction of electrically evoked activity with intrinsic dynamics of cultured cortical networks with and without functional fast GABAergic synaptic transmission.Frontiers in cellular neuroscience · 2015Article
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
In recent years much effort is invested in means to control neural population responses at the whole brain level, within the context of developing advanced medical applications. The tradeoffs and constraints involved, however, remain elusive due to obvious complications entailed by studying whole brain dynamics. Here, we present effective control of response features (probability and latency) of cortical networks in vitro over many hours, and offer this approach as an experimental toy for studying controllability of neural networks in the wider context. Exercising this approach we show that enforcement of stable high activity rates by means of closed loop control may enhance alteration of underlying global input-output relations and activity dependent dispersion of neuronal pair-wise correlations across the network.
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.