Electroconvulsive therapy changes the regional resting state function measured by regional homogeneity (ReHo) and amplitude of low frequency fluctuations (ALFF) in elderly major depressive disorder patients: An exploratory study

Abstract Background To explore the differences in the fractional amplitude of low-frequency fluctuations (fALFF) at the whole-brain level between young adults with major depressive disorder (MDD) and those with Subclinical depression (SD). Methods Thirty-nine first-episode MDD patients, 30 SD subjects, and 37 healthy controls (HCs) were recruited. All participants underwent resting-state fMRI (Rs-fMRI) scans on a 3T MR scanner. We used the fALFF to explore spontaneous neuronal activity between groups. Results Significant differences in the fALFF were observed among the three groups. Compared with the HCs, an increased fALFF was found in the left cerebellum in MDD patients. When MDD patients were compared with SD subjects, we observed increased fALFF values in the bilateral fusiform gyrus and decreased fALFF values in the right inferior frontal gyrus, right superior frontal gyrus, right middle frontal gyrus, left cuneus and right precuneus. Compared with the HCs, the SD group demonstrated increased fALFF values in the precuneus. Additionally, a positive correlated was revealed between the fALFF values and Hamilton Anxiety Scale (HAMA)score in the right fusiform gyrus in MDD patients. Moreover, the fALFF value were negatively correlated with the Beck Depression Inventory (BDI) score in the right inferior frontal gyrus and with the age in the left fusiform gyrus in SD subjects. Conclusions Our findings suggest that alterations of cognitive and executive networks, default mode networks and visual recognition circuits may contribute to the different neural mechanisms between MDD and SD in young adult subjects.

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Reproducibility of functional brain alterations in major depressive disorder: evidence from a multisite resting-state functional MRI study with 1,434 individuals

10.1101/524496 ◽

2019 ◽

Author(s):

Mingrui Xia ◽

Tianmei Si ◽

Xiaoyi Sun ◽

Qing Ma ◽

Bangshan Liu ◽

...

Keyword(s):

Major Depressive Disorder ◽

Depressive Disorder ◽

Functional Mri ◽

Resting State ◽

Disease Onset ◽

Low Frequency ◽

Clinical Variable ◽

Major Depressive ◽

Global Signal ◽

Mri Study

AbstractResting-state functional MRI (R-fMRI) studies have demonstrated widespread alterations in brain function in patients with major depressive disorder (MDD). However, a clear and consistent conclusion regarding a repeatable pattern of MDD-relevant alterations is still limited due to the scarcity of large-sample, multisite datasets. Here, we address this issue by including a large R-fMRI dataset with 1,434 participants (709 patients with MDD and 725 healthy controls) from five centers in China. Individual functional activity maps that represent very local to long-range connections are computed using the amplitude of low-frequency fluctuations, regional homogeneity and distance-related functional connectivity strength. The reproducibility analyses involve different statistical strategies, global signal regression, across-center consistency, clinical variables, and sample size. We observed significant hypoactivity in the orbitofrontal, sensorimotor, and visual cortices and hyperactivity in the frontoparietal cortices in MDD patients compared to the controls. These alterations are not affected by different statistical analysis strategies, global signal regression and medication status and are generally reproducible across centers. However, these between-group differences are partially influenced by the episode status and the age of disease onset in patients, and the brain-clinical variable relationship exhibits poor cross-center reproducibility. Bootstrap analyses reveal that at least 400 subjects in each group are required to replicate significant alterations (an extent threshold of P<.05 and a height threshold of P<.001) at 50% reproducibility. Together, these results highlight reproducible patterns of functional alterations in MDD and relevant influencing factors, which provides crucial guidance for future neuroimaging studies of this disorder.

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Alterations in amplitude of low frequency fluctuation in treatment‐naïve major depressive disorder measured with resting‐state fMRI

Human Brain Mapping ◽

10.1002/hbm.22526 ◽

2014 ◽

Vol 35 (10) ◽

pp. 4979-4988 ◽

Cited By ~ 73

Author(s):

Jie Liu ◽

Ling Ren ◽

Fay Y. Womer ◽

Jue Wang ◽

Guoguang Fan ◽

...

Keyword(s):

Major Depressive Disorder ◽

Depressive Disorder ◽

Resting State ◽

Low Frequency ◽

Resting State Fmri ◽

Frequency Fluctuation ◽

Major Depressive ◽

Treatment Naïve

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Modulation of functional network properties in major depressive disorder following electroconvulsive therapy (ECT): a resting-state EEG analysis

Scientific Reports ◽

10.1038/s41598-020-74103-y ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Aron T. Hill ◽

Itay Hadas ◽

Reza Zomorrodi ◽

Daphne Voineskos ◽

Faranak Farzan ◽

...

Keyword(s):

Major Depressive Disorder ◽

Depressive Disorder ◽

Electroconvulsive Therapy ◽

Resting State ◽

Spectral Power ◽

Clustering Coefficient ◽

Treatment Resistant ◽

Open Label ◽

Major Depressive ◽

Characteristic Path Length

Abstract Electroconvulsive therapy (ECT) is a highly effective neuromodulatory intervention for treatment-resistant major depressive disorder (MDD). Presently, however, understanding of its neurophysiological effects remains incomplete. In the present study, we utilised resting-state electroencephalography (RS-EEG) to explore changes in functional connectivity, network topology, and spectral power elicited by an acute open-label course of ECT in a cohort of 23 patients with treatment-resistant MDD. RS-EEG was recorded prior to commencement of ECT and again within 48 h following each patient’s final treatment session. Our results show that ECT was able to enhance connectivity within lower (delta and theta) frequency bands across subnetworks largely confined to fronto-central channels, while, conversely, more widespread subnetworks of reduced connectivity emerged within faster (alpha and beta) bands following treatment. Graph-based topological analyses revealed changes in measures of functional segregation (clustering coefficient), integration (characteristic path length), and small-world architecture following ECT. Finally, post-treatment enhancement of delta and theta spectral power was observed, which showed a positive association with the number of ECT sessions received. Overall, our findings indicate that RS-EEG can provide a sensitive measure of dynamic neural activity following ECT and highlight network-based analyses as a promising avenue for furthering mechanistic understanding of the effects of convulsive therapies.

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