ArticleNeuroImage2023
Time-Lagged Multidimensional Pattern Connectivity (TL-MDPC): An EEG/MEG pattern transformation based functional connectivity metric.
Article in NeuroImage, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Controlled Semantic Cognition: Precision Recordings Converge With in Silico Experiments to Reveal the Inner Workings of the Anterior Temporal Lobe Hub.Neurobiology of language (Cambridge, Mass.) · 2026Review
- Building blocks of functional connectivity measures for aperiodic electrophysiological brain signals.Neuroimage. Reports · 2025Article
- Linear and nonlinear multidimensional functional connectivity methods reveal similar networks for semantic processing in EEG/MEG data.Frontiers in human neuroscience · 2025Article
- A bicoherence approach to analyze multi-dimensional cross-frequency coupling in EEG/MEG data.Scientific reports · 2024Article
- Decoding Semantics from Dynamic Brain Activation Patterns: From Trials to Task in EEG/MEG Source Space.eNeuro · 2024Article
- Recurrent connectivity supports higher-level visual and semantic object representations in the brain.Communications biology · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Functional and effective connectivity methods are essential to study the complex information flow in brain networks underlying human cognition. Only recently have connectivity methods begun to emerge that make use of the full multidimensional information contained in patterns of brain activation, rather than unidimensional summary measures of these patterns. To date, these methods have mostly been applied to fMRI data, and no method allows vertex-to-vertex transformations with the temporal specificity of EEG/MEG data. Here, we introduce time-lagged multidimensional pattern connectivity (TL-MDPC) as a novel bivariate functional connectivity metric for EEG/MEG research. TL-MDPC estimates the vertex-to-vertex transformations among multiple brain regions and across different latency ranges. It determines how well patterns in ROI X at time point t
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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.