| Locked-In Syndrome (LiS) is a rare neurological condition that confines individuals to a state of preserved awareness but near-total physical paralysis, rendering conventional communication impossible. There is currently no cure to LiS hence restoring interaction for such patients requires brain-computer interfaces (BCIs) that are capable of translating neural activity into interpretable outputs without relying on motor control. In this work, we propose a multimodal BCI framework that enables expressive communication through independent EEG and fMRI decoding pipelines. EEG signals have high temporal resolution, which facilitates near real-time conversion of brain activity into text or simple images. In contrast, fMRI has high spatial resolution, which helps create clearer and more detailed images of what the brain is imagining. In cohesion, these modalities provide two complementary paths to decode both linguistic and visual representations using a non-invasive communication interface that bridges thought with digital output. The proposed approach illustrates how multimodal neural decoding is used to enable more effective and personalized communication in persons suffering from Locked-In Syndrome. |
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