To use correlation-based EEG graph, specify --graph_type individual. To use preprocessed Fourier transformed inputs from the above optional preprocessing step, specify --preproc_dir <preproc-dir>.

To create a directed graph in Python for solving problems on LeetCode, you typically represent the graph using data structures such as adjacency lists.

EEGraph is a Python library to model electroencephalograms (EEGs) as graphs, so the connectivity between different brain areas could be analyzed. It has applications in the study of neurologic ...

Or you can take advantage of [Cody Brocious’] work by using his Emotiv Python Library. He sniffed around the data coming in over the USB connection and discovered that it’s encrypted.

With the self-organized graph construction module, the graph structure is dynamically constructed by the corresponding input EEG features. Then, the newly built graphs can be processed by the graph ...

Methods: Leveraging EEG-based hyperscanning technology, we introduced an innovative approach known as the functional graph contrastive learning (fGCL), which extracts subject-invariant representations ...

Alzheimer’s disease (AD) is the leading form of dementia worldwide. AD disrupts neuronal pathways and thus is commonly viewed as a network disorder. Many studies demonstrate the power of functional ...

Electroencephalogram (EEG) is a valuable technique to record brain electrical activity through electrodes placed on the scalp. Analyzing EEG signals contributes to the understanding of neurological ...