ReviewBrain informatics2021
Methods for inferring neural circuit interactions and neuromodulation from local field potential and electroencephalogram measures.
Review in Brain informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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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
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review of Aperiodic Neural Activity in Clinical Investigations.The European journal of neuroscience · 2025Pooled it
- A Framework Integrating Spiking Cortical Circuit Modeling and Simulation-Based Inference to Probe Biomarkers of Cortical Dysfunction in Alzheimer's Disease.Interdisciplinary sciences, computational life sciences · 2026Article
- A Python toolbox for neural circuit parameter inference.NPJ systems biology and applications · 2025Article
- Cross-Modal Representational Knowledge Distillation for Enhanced Spike-Informed LFP Modeling.Advances in neural information processing systems · 2025Article
- Machine learning-based ABA treatment recommendation and personalization for autism spectrum disorder: an exploratory study.Brain informatics · 2022Article
- Methods for inferring neural circuit interactions and neuromodulation from local field potential and electroencephalogram measures.Brain informatics · 2021Review
- Combining aperiodic 1/f slopes and brain simulation: An EEG/MEG proxy marker of excitation/inhibition imbalance in Alzheimer's disease.Alzheimer's & dementia (Amsterdam, Netherlands)Article
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
Electrical recordings of neural mass activity, such as local field potentials (LFPs) and electroencephalograms (EEGs), have been instrumental in studying brain function. However, these aggregate signals lack cellular resolution and thus are not easy to be interpreted directly in terms of parameters of neural microcircuits. Developing tools for a reliable estimation of key neural parameters from these signals, such as the interaction between excitation and inhibition or the level of neuromodulation, is important for both neuroscientific and clinical applications. Over the years, we have developed tools based on neural network modeling and computational analysis of empirical data to estimate neural parameters from aggregate neural signals. This review article gives an overview of the main computational tools that we have developed and employed to invert LFPs and EEGs in terms of circuit-level neural phenomena, and outlines future challenges and directions for future research.
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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.