en Other Other پژوهشی Original <span style="font-size:11pt"><span style="line-height:normal"><span style="font-family:Calibri,sans-serif"><i><span new="" roman="" style="font-family:" times="">Autism spectrum disorder (ASD) is consistently associated with abnormal functional connectivity; resting-state fMRI data were obtained from the ABIDE dataset. Dynamic functional connectivity (DFC) was obtained in an autism-specific subnetwork consisting of 17 regions identified from previous static connectivity analyses. Time-varying connectivity matrices were estimated using a sliding window approach, and recurrent connectivity states were identified using a hidden Markov model. Dynamic measures included state occupancy rate, mean dwell time, and edge-level connectivity variability. Compared with controls, individuals with ASD showed a significant decrease in the occupancy of highly integrated connectivity states (ASD: 28.6 &plusmn; 7.4% vs. control: 36.9 &plusmn; 8.1%, p < 0.001) and longer dwell times in poorly integrated connectivity states (ASD: 42.3 &plusmn; 10.2 vs. control: 31.7 &plusmn; 9.5 s, p = 0.002). In contrast, edge-level connectivity variability was significantly increased in ASD, particularly in default mode-limbic connections. Importantly, increased connectivity variability in the default mode network significantly predicted ADOS total scores (&beta; = 0.41), (p = 0.001). These findings suggest a dissociation between reduced network state flexibility and increased moment-to-moment connectivity variability in autism spectrum disorder (ASD).</span></i></span></span></span><br> &nbsp; Autism spectrum disorder, dynamic functional connectivity, network flexibility, connectivity variability, resting-state fMRI. 40 54 http://iors.ir/journal/browse.php?a_code=A-10-6070-3&slc_lang=en&sid=1 Saba Gholami saba.gholami68@yahoo.com 00031947532846003108 00031947532846003108 No Department of Computer Engineering, Ra.C., Islamic Azad University, Rasht, Iran Sara Motamed sara.motamed@iau.ac.ir 00031947532846003109 00031947532846003109 Yes Department of Computer Engineering, FSh.C., Islamic Azad University, Fouman, Iran Elham Askari askary.elham@gmail.com 00031947532846003110 00031947532846003110 No Department of Computer Engineering, FSh.C., Islamic Azad University, Fouman, Iran