ReviewNature biomedical engineering2025
Harnessing electroencephalography connectomes for cognitive and clinical neuroscience.
Review in Nature biomedical engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- The Relationship Between the Functional Integration and Topological Complexity of Human Electroencephalographic (EEG) Signals: Three Moderating Factors.Brain sciences · 2026Article
- Individualized prediction of heroin cue-induced craving using task-based EEG functional connectivity.NPJ digital medicine · 2026Article
- Bidirectional Mamba-2 boosts EEG super-resolution via regression and diffusion.Bioinformatics (Oxford, England) · 2026Article
- A Holistic and Dynamic Network-Level View of the Autonomic Nervous System.Annual review of biomedical engineering · 2026Review
- The Perioperative Neurocognitive Disorder Prediction Based on AI-Assisted EEG Dynamic Features in Anesthetized Mice.Diagnostics (Basel, Switzerland) · 2026Article
- Artificial intelligence-enabled "inherited noninvasive intracellular recording" for prolonged monitoring of cardiac action potentials.Science advances · 2026Article
- Mapping EEG Metrics to Human Affective and Cognitive Models: An Interdisciplinary Scoping Review from a Cognitive Neuroscience Perspective.Biomimetics (Basel, Switzerland) · 2025Review
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
Abstract
Electroencephalography (EEG) connectomes offer powerful tools for studying brain connectivity and advancing our understanding of brain function and dysfunction in both healthy and pathological conditions. Celebrating the 100th anniversary of EEG discovery, this Perspective explores the frontiers of EEG-based brain connectivity in basic and translational neuroscience research. We review new concepts, emerging analysis frameworks and significant advances in harnessing EEG connectomes. We suggest that leveraging machine learning approaches may offer promising paths to maximize the strengths of EEG connectomes. We also discuss how combined EEG connectome and neuromodulation provide a personalized and adaptive closed-loop paradigm to promote neuroplasticity and treat dysfunctional brains. We further address the limitations and challenges of the current methodology and touch on important issues regarding research rigour and clinical viability for translational impact.
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.