Decoding Semantics from Dynamic Brain Activation Patterns: From Trials to Task in EEG/MEG Source Space

Area of Science:

• Neuroscience
• Cognitive Neuroscience
• Brain Imaging

Background:

• The temporal dynamics and network dependencies of semantic processing remain unclear.
• Understanding how the brain processes word meaning and task demands is crucial.

Purpose of the Study:

• To decode task and stimulus information from source-localized EEG/MEG data.
• To investigate the temporal dynamics of the semantic brain network.

Main Methods:

• Source space decoding of EEG/MEG data during lexical decision and semantic decision tasks.
• Analysis of five semantic categories across multiple brain regions of interest (ROIs).
• Comparison of ROI-by-ROI and combined-ROI decoding approaches.

Main Results:

• Task information was decoded across all ROIs early (50-100 ms).
• Semantic word category was decoded later (250-500 ms) in specific ROIs (lATL, rATL, PTC, IFG).
• Task effects are widely distributed, while stimulus effects are more focal.

Conclusions:

• The semantic network is broadly distributed, with bilateral anterior temporal lobes playing a key role.
• Different decoding methods are optimal for task versus stimulus information.
• Task demands influence semantic processing across the network from early stages.