scholarly journals Exploring concomitant neuroimaging and genetic alterations in patients with and patients without auditory verbal hallucinations: A pilot study and mini review

2020 ◽  
Vol 48 (7) ◽  
pp. 030006051988485
Author(s):  
Haiping Yu ◽  
Wang Ying ◽  
Gang Li ◽  
Xiaodong Lin ◽  
Deguo Jiang ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Pilot Study ◽  
Functional Connectivity ◽  
Diagnostic Accuracy ◽  
High Throughput Sequencing ◽  
Parietal Lobe ◽  
Genetic Alterations ◽  
Functional Connectivity Density ◽  
Auditory Verbal Hallucinations ◽  
T Values

Objective To explore concomitant neuroimaging and genetic alterations in patients with schizophrenia with or without auditory verbal hallucinations (AVHs), and to discuss the use of pattern recognition techniques in the development of an objective index that may improve diagnostic accuracy and treatment outcomes for schizophrenia. Methods The pilot study included patients with schizophrenia with AVHs (SCH-AVH group) and without AVHs (SCH-no AVH group). High throughput sequencing (HTS) was performed to explore RNA networks. Global functional connectivity density (gFCD) analysis was performed to assess functional connectivity (FC) alterations of the default mode network (DMN). Quantitative long noncoding (lnc) RNA and mRNA expression data were related to peak T values of gFCDs using Pearson’s correlation coefficient analysis. Results Compared with the SCH-no AVH group ( n = 5), patients in the SCH-AVH group ( n = 5) exhibited differences in RNA expression in RNA networks that were related to AVH severity, and displayed alterations in FC (reflected by gFCD differences) within the DMN (posterior cingulate and dorsal-medial prefrontal cortex), and in the right parietal lobe, left occipital lobe, and left temporal lobe. Peak lncRNA expression values were significantly related to peak gFCD T values within the DMN. Conclusion Among patients with schizophrenia, there are concomitant FC and genetic expression alterations associated with AVHs. Data from pattern recognition studies may inform the development of an objective index aimed at improving early diagnostic accuracy and treatment planning for patients with schizophrenia with and without AVHs.

Dynamic Changes in the Mental Rotation Network Revealed by Pattern Recognition Analysis of fMRI Data

2009 ◽  
Vol 21 (5) ◽  
pp. 890-904 ◽  
Author(s):  
Janaina Mourao-Miranda ◽  
Christine Ecker ◽  
Joao R. Sato ◽  
Michael Brammer
Keyword(s):  
Pattern Recognition ◽  
Functional Connectivity ◽  
Mental Rotation ◽  
Temporal Dynamics ◽  
Parietal Lobe ◽  
Time Window ◽  
Support Vector ◽  
Dynamic Changes ◽  
Angular Disparity ◽  
Spatio Temporal

We investigated the temporal dynamics and changes in connectivity in the mental rotation network through the application of spatio-temporal support vector machines (SVMs). The spatio-temporal SVM [Mourao-Miranda, J., Friston, K. J., et al. (2007). Dynamic discrimination analysis: A spatial-temporal SVM. Neuroimage, 36, 88–99] is a pattern recognition approach that is suitable for investigating dynamic changes in the brain network during a complex mental task. It does not require a model describing each component of the task and the precise shape of the BOLD impulse response. By defining a time window including a cognitive event, one can use spatio-temporal fMRI observations from two cognitive states to train the SVM. During the training, the SVM finds the discriminating pattern between the two states and produces a discriminating weight vector encompassing both voxels and time (i.e., spatio-temporal maps). We showed that by applying spatio-temporal SVM to an event-related mental rotation experiment, it is possible to discriminate between different degrees of angular disparity (0° vs. 20°, 0° vs. 60°, and 0° vs. 100°), and the discrimination accuracy is correlated with the difference in angular disparity between the conditions. For the comparison with highest accuracy (0° vs. 100°), we evaluated how the most discriminating areas (visual regions, parietal regions, supplementary, and premotor areas) change their behavior over time. The frontal premotor regions became highly discriminating earlier than the superior parietal cortex. There seems to be a parcellation of the parietal regions with an earlier discrimination of the inferior parietal lobe in the mental rotation in relation to the superior parietal. The SVM also identified a network of regions that had a decrease in BOLD responses during the 100° condition in relation to the 0° condition (posterior cingulate, frontal, and superior temporal gyrus). This network was also highly discriminating between the two conditions. In addition, we investigated changes in functional connectivity between the most discriminating areas identified by the spatio-temporal SVM. We observed an increase in functional connectivity between almost all areas activated during the 100° condition (bilateral inferior and superior parietal lobe, bilateral premotor area, and SMA) but not between the areas that showed a decrease in BOLD response during the 100° condition.

Abnormal white matter functional connectivity density in antipsychotic-naive adolescents with schizophrenia

2021 ◽  
Vol 132 (5) ◽  
pp. 1025-1032
Author(s):  
Xiao Wang ◽  
Wei Liao ◽  
Shaoqiang Han ◽  
Fengmei Lu ◽  
Zongling He ◽  
...  
Keyword(s):  
White Matter ◽  
Functional Connectivity ◽  
Functional Connectivity Density
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