IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI)NeurosciencePeer-reviewed journal article
Complexity Measures Of Psychotic Brain Activity In The fMRI Signal
Qiang LiiD, Masoud SerajiiD, Vince D CalhouniD, Armin IrajiiD
Abstract
When viewing the brain as a sophisticated, nonlinear dynamic system, employing complexity measures offers a valuable way to measure the intricate and dynamic aspects of spontaneous psychotic brain activity. These measures can help us identify irregularities and patterns in complex systems. In our study, we utilized fuzzy recurrence plots and sample entropy to evaluate the dynamic characteristics of psychiatric disorders. This assessment focused on understanding the temporal and spatial neural activity patterns, and more specifically, we applied complexity measures to investigate the functional connectivity within the psychotic brain. This involves understanding how different brain regions synchronize their activity, and complexity measures can reveal the patterns of these connections. It provides a means to understand how different brain regions interact and communicate under resting-state abnormal conditions. This study offers evidence demonstrating that fuzzy recurrence plots can serve as descriptors for functional connectivity and discusses their relevance to sample entropy in the context of the psychotic brain. In summary, complexity measures offer valuable insights that enrich our comprehension of atypical brain activity and the complexities present in the psychotic brain1.
- organism: human
- assay: imaging
- research focus: cell-cell communication
- research focus: spatial domain detection
- approach: statistical model
- Citations
- 6
- FWCI
- 4.71
- Field percentile
- top 5%
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