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eeg-dyad-cebra-pipeline

Contrasting Neural Dynamics in Interacting Dyads using CEBRA Methodology. Develops a PyTorch pipeline (NT-Xent) to map 64-channel EEG spectral features from Speaker-Listener interactions. Identifies low-dimensional latent parameters that robustly differentiate Neurotypical from Clinical dyad populations (e.g., ASD).

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Contrasting Neural Dynamics in Interacting Dyads using CEBRA Methodology. Develops a PyTorch pipeline (NT-Xent) to map 64-channel EEG spectral features from Speaker-Listener interactions. Identifies low-dimensional latent parameters that robustly differentiate Neurotypical from Clinical dyad populations (e.g., ASD).

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