electrocorticography
PulseAugur coverage of electrocorticography — every cluster mentioning electrocorticography across labs, papers, and developer communities, ranked by signal.
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New deep learning models decode visual perception from brain activity
Researchers have developed new deep learning approaches for decoding visual semantic information from brain activity. One study utilizes an end-to-end Transformer-based deep learning framework with electrocorticography …
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New research explores EEG-to-Text feasibility and human brain's next-word prediction
Researchers are exploring the feasibility of translating brain signals into text, particularly using electroencephalography (EEG). Two studies investigate how next-word predictability influences human brain responses du…
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New framework improves Parkinson's classification using ECoG and EEG data
Researchers have developed a new swap-adversarial framework designed to improve the accuracy of Parkinson's disease classification using electrocorticography (ECoG) and electroencephalography (EEG) data. This framework …
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Meta AI's Brain2Qwerty v2 decodes brain activity to text with 61% accuracy
Meta AI has developed Brain2Qwerty v2, an advanced system that decodes brain activity into text using non-invasive recordings. This new version achieves a 61% word accuracy rate, a significant improvement over previous …
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New toolbox automates feature selection for brain-computer interfaces
Researchers have developed BCI-sift, a new Python toolbox designed to automate feature selection for Brain-Computer Interface (BCI) applications. This tool integrates various optimization algorithms to identify the most…
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fMRI data enhances prediction models for faster brain signals
Researchers have developed a novel method to improve brain activity prediction by fine-tuning language encoding models using fMRI data. Despite fMRI's significantly lower temporal resolution compared to ECoG, models tra…