Temporal and spectral characteristics of dynamic functional connectivity between resting-state networks reveal information beyond static connectivity
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'These data are the residual time-series from the 6 ROI's used in the paper, which have undergone the pre-processing steps as described in the 'Image acquisition and pre-processing' section of the paper' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Anticorrelation","Connectomics","Default mode network","Dynamic functional connectivity","Functional magnetic resonance imaging","Resting-state","Spectral analysis","Temporal Lobe Epilepsy"]} <|eot_id|>
 Here is the Description of a dataset. Description:'These data are the residual time-series from the 6 ROI's used in the paper, which have undergone the pre-processing steps as described in the 'Image acquisition and pre-processing' section of the paper' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
These data are the residual time-series from the 6 ROI's used in the paper, which have undergone the pre-processing steps as described in the 'Image acquisition and pre-processing' section of the paper
Anticorrelation; Connectomics; Default mode network; Dynamic functional connectivity; Functional magnetic resonance imaging; Resting-state; Spectral analysis; Temporal Lobe Epilepsy