نشریه علمی مهندسی پزشکی زیستی

Dynamic Causal Modelling among Default Mode Network and Salience Network related to IQ

Document Type : Full Research Paper

Authors

1 Ph.D. Student, Institute for Cognitive Science Studies, Tehran, Iran

2 Professor, Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran

3 Associate Professor, Department of Electrical and Computer Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran

4 Assistant Professor, Institute for Cognitive Science Studies, Tehran, Iran

Abstract
Intelligence Quotient (IQ) is of interest to researchers. In this research, 100 unrelated young healthy subjects randomly selected from the 1200 HCP dataset (54 women and 46 men), with an average age of 28 years (age range from 22 to 35 years), were used. Each person has participated in Raven test. Based on the results of the Raven's test, each person is placed in one of the three groups: high intelligence, normal intelligence, and low intelligence. In the next step, using the resting-state functional magnetic resonance imaging (rsfMRI) data of these subjects and the spectral dynamic causal modeling algorithm implemented in the SPM12 package in MATLAB, two brain networks named the default mode network (DMN) and the salient network (SN) have been investigated. For each of the three groups mentioned above, a connection model was obtained. The obvious difference in the DMN network is as follows: there is no connection from PCC to RIPC in people with high intelligence in the obtained model. In contrast, there is an excitatory connection in the other two groups. Specifically, the LIPC to RIPC connection is inhibitory in people with high intelligence, but it is excitatory in the other two groups. Additionally, the connection between mPFC and RIPC is inhibitory in the group with high and average intelligence, while there is no connection in the group of people with low intelligence. After obtaining the model, ANOVA test with p-value<0.05 was used to check the difference. In the SN network, this significant difference was revealed on 6 edges of 169 edges, which were: rMCC-rvIPFC, rInsula-rvIPFC, rInsula-rPutamen, rInsula-lIPG, lIPG-rSFG, lIPG-rSFG.  

Keywords

Subjects


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Volume 17, Issue 3
Autumn 2023
Pages 195-207

  • Receive Date 23 December 2023
  • Revise Date 26 July 2024
  • Accept Date 19 August 2024