About this Research Topic
Neuropsychiatric disorders have a huge impact on individuals, families and societies. However, the neuropathology underlying cognitive deficits in neuropsychiatric disorders remains unclear. Resting-state functional connectivity provides a powerful way to investigate functional alterations underlying cognitive deficits in neuropsychiatric disorders. Traditional FC analysis measures the correlations of signals with an assumption that functional connectivity remains constant during the observation period. In recent years, several studies have demonstrated the feasibility of dynamic methods in characterization of functional brain changes, such as dynamic functional connectivity investigating by the sliding window method. However, window size, window stepsize and window type are open areas of research and an important parameter to capture the resting-state FC dynamics.
Thus, this Research Topic focuses on the recent developments in dynamic methods and models based on resting-state fMRI, and their applications in neuropsychiatric disorders. Studies using other dynamic methods (e.g., regression-based dynamic method other than sliding window method) and other dynamic metrics (e.g., dynamic ReHo or ALFF other than functional connectivity) are also within the scope of this Research Topic. Researchers in this field are warmly welcomed to contribute an original article, technical and methodological report, or review article to this Research Topic.
This Research Topic will synthesize present knowledge about cognitive deficits and explore neuropathological mechanisms underlying cognitive deficits by using different brain imaging methods, and thus new methods may be developed. This topic will also address important conceptual and methodological questions. Clinicians will be benefit from this topic in regard to theoretical, experimental and clinical questions related to the nature, origins and functions of cognitive deficits in neuropsychiatric disorders.
Keywords: Structural MRI, functional MRI, cognitive deficits, depression, anxiety
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