Causal interactions between the default mode network and central executive network in patients with major depression

Author(s):  
Jiaming Li ◽  
Jian Liu ◽  
Yufang Zhong ◽  
Huaning Wang ◽  
Baoyu Yan ◽  
...  
2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S10-S10
Author(s):  
Margaret Niznikiewicz ◽  
Kana Okano ◽  
Clemens Bauer ◽  
Paul Nestor ◽  
Elizabetta Del Re ◽  
...  

Abstract Background Auditory hallucinations (AH) are one of the core symptoms of schizophrenia (SZ) and constitute a significant source of suffering and disability. One third of SZ patients experience pharmacology-resistant AH, so an alternative/complementary treatment strategy is needed to alleviate this debilitating condition. In this study, real-time functional Magnetic Resonance Imaging neurofeedback (rt-fMRI NFB), a non-invasive technique, was used to help 10 SZ patients modulate their brain activity in key brain regions belonging to the network involved in the experience of auditory hallucinations. In two experiments we selected two different brain targets. 1. the superior temporal gyrus (STG) and 2. default mode network (DMN)-central executive network (CEN) connectivity. STG is a key area in the neurophysiology of AH. Hyperactivation of the default mode network (DMN) and of the superior temporal gyrus (STG) in SZ has been shown in imaging studies. Furthermore, several studies point to reduced anticorrelation between the DMN and the central executive network (CEN). Finally, DMN hyperconnectivity has been associated with positive symptoms such as AHs while reduced DMN anticorrelations have been associated with cognitive impairment. Methods In the STG-focused NFB experiment, subjects were trained to upregulate the STG activity while listening to their own voice recording and downregulate it while ignoring a stranger’s voice recording in the course of 21 min NFB session. Visual feedback was provided to subjects at the end of each run from their own STG activity in the form of a thermometer. AH were assessed with auditory hallucination scale pre-NFB and within a week after the NFB session. The DMN-CEN focused NFB experiment was conducted about 1 month later to minimize the carry over effects from the STG-focused NFB and was designed to help SZ patients modulate their DMN and CEN networks. DMN and CEN networks were defined individually for each subject. The goal of the task was to increase CEN-DMN anti-correlations. To achieve that patients were provided with meditation strategies to guide their performance. Feedback was provided in the form of a ball that traveled up if the modulation of DMN-CEN connectivity was successful and traveled down if it was not successful. AH measures were taken before the NFB session and within a week after the session. Results In the STG-focused NFB task, significant STG activation reduction was found in the comparison of pre- relative to post-NFB in the condition of ignoring another person’s voice (p<0.05), FWE-TFCE corrected. AH were also significantly reduced (p<0.01). Importantly, significant correlation was found between reductions in the STG activation and AH reductions (r=.83). In the DMN-CEN focused NFB task, significant increase in the anti-correlations between medial prefrontal cortex (mPFC) and dorsolateral prefrontal cortex (DLPFC) (p<0.05) was observed as well as significant reduction in the mPFC-PCC connectivity (p <0.05), in the pre-post NFB comparisons. AH were significantly reduced in post- relative to pre-NFB comparison (p<0.02). Finally, there was a significant correlation between individual scores in mPFC-STG connectivity and AH reductions. Discussion These the two experiments suggest that targeting both the STG BOLD activation and DMN-CEN connectivity in NFB tasks aimed at AH reduction result both in brain changes and in AH reductions. Together, these results provide strong preliminary support for the NFB use as a means to impact brain function leading to reductions in AH in SZ. Importantly, these results suggest that AH result from brain abnormalities in a network of brain regions and that targeting a brain region belonging to this network will lead to AH symptom reduction.


2021 ◽  
Author(s):  
Ganesh B. Chand ◽  
Deepa S. Thakuri ◽  
Bhavin Soni

AbstractNeuroimaging studies suggest that the human brain consists of intrinsically organized large-scale neural networks. Among those networks, the interplay among default-mode network (DMN), salience network (SN), and central-executive network (CEN)has been widely employed to understand the functional interaction patterns in health and diseases. This triple network model suggests that SN causally controls DMN and CEN in healthy individuals. This interaction is often referred to as the dynamic controlling mechanism of SN. However, such interactions are not well understood in individuals with schizophrenia. In this study, we leveraged resting state functional magnetic resonance imaging (fMRI) data of schizophrenia (n = 67) and healthy controls (n = 81) to evaluate the functional interactions among DMN, SN, and CEN using dynamical causal modeling. In healthy controls, our analyses replicated previous findings that SN regulates DMN and CEN activities (Mann-Whitney U test; p < 10−8). In schizophrenia, however, our analyses revealed the disrupted SN-based controlling mechanism on DMN and CEN (Mann-Whitney U test; p < 10−16). These results indicate that the disrupted controlling mechanism of SN on two other neural networks may be a candidate neuroimaging phenotype in schizophrenia.


NeuroImage ◽  
2014 ◽  
Vol 99 ◽  
pp. 180-190 ◽  
Author(s):  
Nia Goulden ◽  
Aygul Khusnulina ◽  
Nicholas J. Davis ◽  
Robert M. Bracewell ◽  
Arun L. Bokde ◽  
...  

2020 ◽  
Author(s):  
Leonardo Tozzi ◽  
Leanne Maree Williams

In this short communication, we test whether patients with major depression and healthy individuals have different functional connectivity within established brain networks. To this end, we leverage a very large multi-site data set of resting state fMRI data (1,300 depressed patients and 1,128 controls) collected by 25 groups. A previous study conducted on this data set compared functional connectivity of the default mode network between the two groups. In our investigation, we performed a meta-analysis across sites quantifying the effects of depression and symptom severity on connectivity of several brain-wide networks beyond the default mode. Running a meta-analysis instead of a mega-analysis also allowed us to calculate effect sizes, heterogeneity and prediction intervals that will be valuable to inform future studies wishing to investigate network functional connectivity in depression. Our results indicate that network connectivity differences between depressed and healthy subjects are consistently small, with confidence intervals almost always encompassing zero, in line with the mixed findings from previous research. Default mode network connectivity differences between depressed patients and controls were exceptionally heterogeneous across sites, suggesting the existence of depression sub-types with normo- and hypo-connected default mode network or a strong impact of clinical confounds on default mode network connectivity. The only networks for which connectivity in depressed individuals was consistently lower than in controls were the somato-motor and visual networks, which could be promising understudied targets for future investigation. Overall, we highlight the need of minimizing heterogeneity in future multi-site studies on functional connectivity in depression and the need for more research on novel taxonomies of mental illness that are robustly anchored in brain function.


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