Default mode network shows alterations for low-frequency fMRI fluctuations in euthymic bipolar disorder

2021 ◽  
Author(s):  
Marco Marino ◽  
Zaira Romeo ◽  
Alessandro Angrilli ◽  
Ilaria Semenzato ◽  
Angela Favaro ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Default Mode Network ◽  
Low Frequency ◽  
Default Mode

S85. Individual Functional Abnormalities in the Default-Mode Network Predict Symptom Severity in Bipolar Disorder

2019 ◽  
Vol 85 (10) ◽  
pp. S330
Author(s):  
Gaelle Doucet ◽  
Delfina Janiri ◽  
David Glahn ◽  
Sophia Frangou
Keyword(s):  
Bipolar Disorder ◽  
Default Mode Network ◽  
Symptom Severity ◽  
Default Mode

scholarly journals Abnormal Spontaneous Brain Activity and Functional Connectivity of the Default Mode Network in Patients with Bipolar Disorder

2021 ◽  
Author(s):  
Lei Zhao ◽  
Qijing Bo ◽  
Zhifang Zhang ◽  
Feng Li ◽  
Yuan Zhou ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Functional Connectivity ◽  
Default Mode Network ◽  
Resting State ◽  
Brain Activity ◽  
Seed Region ◽  
Potential Candidate ◽  
Neural Basis ◽  
Default Mode ◽  
Spontaneous Brain Activity

Abstract Background: No consistent evidence on the specific brain regions is available in the default mode network (DMN), which show abnormal spontaneous activity in bipolar disorder (BD). We aim to identify this region that is particularly impaired in patients with BD by using several different indices measuring spontaneous brain activity and then investigate its functional connectivity (FC).Methods: A total of 56 patients with BD and 71 healthy controls (HC) underwent resting-state functional magnetic resonance imaging. Three commonly used functional indices were used to identify the brain region showing abnormal spontaneous brain activity in BD. Then, this region served as the seed region for resting-state FC analysis to identify its functional networks altered in BD.Results: The BD group exhibited decreased fALFF, ReHo, and DC values in the left precuneus. The BD group had decreased rsFC within the DMN, indicated by decreased resting-state FC within the left precuneus and between the left precuneus and the medial prefrontal cortex. The BD group had decreased negative connectivity between the left precuneus and the left putamen, extending to the left insula.Conclusions: The findings provide convergent evidence for the abnormalities in the DMN of BD, particularly located in the left precuneus. Decreased FC within the DMN and the disruptive anticorrelation between the DMN and the salience network are found in BD. These findings suggest that the DMN is a key aspect for understanding the neural basis of BD, and the altered functional patterns of DMN may be a potential candidate biomarker of BD.

scholarly journals Default mode network abnormalities in bipolar disorder and schizophrenia

2010 ◽  
Vol 183 (1) ◽  
pp. 59-68 ◽  
Author(s):  
Dost Öngür ◽  
Miriam Lundy ◽  
Ian Greenhouse ◽  
Ann K. Shinn ◽  
Vinod Menon ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Default Mode Network ◽  
Default Mode

scholarly journals Frequency-Specific Changes in the Fractional Amplitude of the Low-Frequency Fluctuations in the Default Mode Network in Medication-Free Patients With Bipolar II Depression: A Longitudinal Functional MRI Study

2021 ◽  
Vol 11 ◽  
Author(s):  
Jun Zhou ◽  
Xiaoqian Ma ◽  
Chunwang Li ◽  
Aijun Liao ◽  
Zihao Yang ◽  
...  
Keyword(s):  
Default Mode Network ◽  
Rating Scale ◽  
Low Frequency ◽  
Anterior Cingulate ◽  
Depression Symptoms ◽  
Superior Frontal Gyrus ◽  
Default Mode ◽  
Bipolar Ii ◽  
Frequency Fluctuations

Objective: This study aimed to examine the treatment-related changes of the fractional amplitude of low-frequency fluctuations (fALFF) in the default mode network (DMN) across different bands after the medication-free patients with bipolar II depression received a 16-week treatment of escitalopram and lithium.Methods: A total of 23 medication-free patients with bipolar II depression and 29 healthy controls (HCs) were recruited. We evaluated the fALFF values of slow 4 (0.027–0.073 Hz) band and slow 5 (0.01–0.027 Hz) band of the patients and compared the results with those of the 29 HCs at baseline. After 16-week treatment of escitalopram with lithium, the slow 4 and slow 5 fALFF values of the patients were assessed and compared with the baselines of patients and HCs. The depressive symptoms of bipolar II depression in patients were assessed with a 17-item Hamilton Depression Rating Scale (HDRS) before and after treatment.Results: Treatment-related effects showed increased slow 5 fALFF in cluster D (bilateral medial superior frontal gyrus, bilateral superior frontal gyrus, right middle frontal gyrus, and bilateral anterior cingulate), cluster E (bilateral precuneus/posterior cingulate, left cuneus), and cluster F (left angular, left middle temporal gyrus, left superior temporal gyrus, and left supramarginal gyrus) in comparison with the baseline of the patients. Moreover, a positive association was found between the increase in slow 5 fALFF values (follow-up value minus the baseline values) in cluster D and the decrease in HDRS scores (baseline HDRS scores minus follow-up HDRS scores) at follow-up, and the same association between the increase in slow 5 fALFF values and the decrease in HDRS scores was found in cluster E.Conclusions: The study reveals that the hypoactivity of slow 5 fALFF in the DMN is related to depression symptoms and might be corrected by the administration of escitalopram with lithium, implying that slow 5 fALFF of the DMN plays a key role in bipolar depression.

Brain functional changes in first-degree relatives of patients with bipolar disorder: evidence for default mode network dysfunction

2016 ◽  
Vol 46 (12) ◽  
pp. 2513-2521 ◽  
Author(s):  
S. Alonso-Lana ◽  
M. Valentí ◽  
A. Romaguera ◽  
C. Sarri ◽  
S. Sarró ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Prefrontal Cortex ◽  
Medial Prefrontal Cortex ◽  
Default Mode Network ◽  
Healthy Controls ◽  
Whole Brain ◽  
Default Mode ◽  
Functional Changes ◽  
Significant Difference ◽  
Bipolar Patients

BackgroundRelatively few studies have investigated whether relatives of patients with bipolar disorder show brain functional changes, and these have focused on activation changes. Failure of de-activation during cognitive task performance is also seen in the disorder and may have trait-like characteristics since it has been found in euthymia.MethodA total of 20 euthymic patients with bipolar disorder, 20 of their unaffected siblings and 40 healthy controls underwent functional magnetic resonance imaging during performance of the n-back working memory task. An analysis of variance (ANOVA) was fitted to individual whole-brain maps from each set of patient–relative–matched pair of controls. Clusters of significant difference among the groups were used as regions of interest to compare mean activations/de-activations between them.ResultsA single cluster of significant difference among the three groups was found in the whole-brain ANOVA. This was located in the medial prefrontal cortex, a region of task-related de-activation in the healthy controls. Both the patients and their siblings showed significantly reduced de-activation compared with the healthy controls in this region, but the failure was less marked in the relatives.ConclusionsFailure to de-activate the medial prefrontal cortex in both euthymic bipolar patients and their unaffected siblings adds to evidence for default mode network dysfunction in the disorder, and suggests that it may act as a trait marker.

scholarly journals Rest-fMRI Based Comparison Study between Autism Spectrum Disorder and Typically Control Using Graph Frequency Bands

2021 ◽  
Author(s):  
Alireza Talesh Jafadideh ◽  
Babak Mohammadzadeh Asl
Keyword(s):  
Autism Spectrum Disorder ◽  
Signal Processing ◽  
Default Mode Network ◽  
High Frequency ◽  
Low Frequency ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Default Mode ◽  
Frequency Bands ◽  
The Brain

AbstractGraph signal processing is a subset of signal processing enabling the analysis of functional magnetic resonance imaging (fMRI) data in brain topological domain. One of the most important and highly interested tool of GSP is graph Fourier transform (GFT) by which brain signals can be analyzed in different graph frequency bands. In this paper, the resting-state fMRI (rfMRI) data is analyzed using GFT tool in order to discover new knowledge about the autism spectrum disorder (ASD) and find features discriminating between ASD and typically control (TC) subjects. For ASD group, the signal concentration in both low and high frequency bands is decreased by increasing the age in most of the brain well-known networks. The ASD in comparison to TC shows less intention for changing the signal concentration level when the level is very low or very high. In graph low frequency band, increasing the age is along with increasing the segregation and integration of brain ROIs respectively for ASD and TC. Also, in this band, the brain ROIs integration of ASD is more than TC. By increasing the age, the auditory network of ASD subjects shows increasing segregation and integration in graph low and high frequency bands, respectively. The reduced segregation of default mode network in ASD is happened in graph middle and higher frequency bands. The functional connectivity analysis between low and high frequency signals shows that some of the high frequency ROIs have connections with all low frequency ROIs so that the most of these connections are dramatically and significantly different between ASD and TC. By analyzing the local vertex frequency spectrum (LVFS) of ASD and TC at different states, it is seen these groups show contradictory behaviors with respect to each other in brain default mode network in two states. The results of different scenarios at different graph frequency bands demonstrate that using functional and structural data together can provide powerful tool for recognizing the ASD or even other brain disorders.

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