Functional Connectivity In Major Depression Research Articles

A comparative study of interhemispheric functional connectivity in major depression and schizophrenia

BackgroundMajor depressive disorder (MDD) and schizophrenia (SZ) are serious psychiatric disorders that, despite exhibiting different diagnostic criteria, exhibit significant overlap regarding the biological and clinical features of affected patients. While prior evidence has shown that interhemispheric functional connectivity (FC) is abnormal in MDD and SZ, the particular similarities and differences that unify and characterize MDD and SZ regarding these interhemispheric FC patterns remain to be characterized. This study was thus designed to conduct an in-depth analysis of MDD- and SZ-related patterns of interhemispheric FC. MethodsThis study enrolled MDD patients, SZ patients, and normal control (NC) individuals (n = 36 each). Resting-state functional MRI (rs-fMRI) studies of these patients were conducted, after which voxel-mirrored homotopic connectivity (VMHC) was used to analyze the preprocesses rs-fMRI data. The VMHC values in these different values were then compared through one-way ANOVAs and post hoc analyses. ResultsSignificant differences were observed in both the striatum and middle frontal gyrus (MFG) when comparing these three groups. Through pairwise comparisons, MDD patients but not SZ patients exhibited reduced MFG VMHC values relative to the NC individuals. Conversely, striatum VMHC values significantly increased in SZ patients relative to NC individuals and MDD patients. ConclusionThese results support the interhemispheric functional disconnection hypothesis as a basis for the pathogenesis of MDD and SZ. The observed differences in interhemispheric FC in the MFG and striatum of MDD and SZ patients will offer a neuroimaging basis that can aid in the differential diagnosis of these debilitating conditions.

Resting-state functional connectivity graph-properties correlate with bipolar disorder-risk in young medication-free depressed subjects: Bipolar-risk Resting State Functional Connectivity in Major Depression

BackgroundMajor Depressive Disorder (MDD) is frequently associated with risk factors for the development of Bipolar Disorder (BD). Using graph theory, we investigated brain network properties associated with BD risk factors in young MDD subjects. MethodsResting-state fMRI was acquired from a large cohort (N= 104) of medication-free currently depressed participants (25 BD depression (BDD), 79 MDD). Lifetime mania symptom count (LMSC), current Young Mania Rating Scale (YMRS) score, and family history of mood disorders (FHMD) were examined as BD risk factors. Functional connectivity matrices from 280 regions of interests (ROIs) were first entered into the Network Based Statistic (NBS) toolbox to identify connections that varied with each risk factor. Next, within the correlated network for each risk factor, global and nodal graph properties for the top five linked nodes were calculated. Last, using identified graph properties, machine learning classification (MLC) between BDD, MDD with BD risk factors (MDD+), and without BD risk factors (MDD-) was conducted. ResultsLMSC positively correlated with left lateral orbitofrontal cortex (LOFC) Communication Efficiency and with left middle temporal Eigenvector Centrality. Current YMRS score positively correlated with right amygdala Communication Efficiency and Closeness Centrality. FHMD positively correlated with right insula Eigenvector Centrality. Acceptable MLC accuracy was seen between BDD and MDD- using middle temporal Eigenvector Centrality, whereas moderate accuracy was seen between MDD+ and MDD- using OFC Communication Efficiency. LimitationAlthough participants were medication-free, they were not medication-naïve. ConclusionFunctional connectome graph properties may serve as BD vulnerability biomarkers in young individuals with MDD.

Effects of Serial Ketamine Infusions on Corticolimbic Functional Connectivity in Major Depression

BackgroundKetamine is a highly effective antidepressant for patients with treatment-resistant major depressive disorder (MDD). Resting-state functional magnetic resonance imaging studies show disruptions of functional connectivity (FC) between limbic regions and resting-state networks (RSNs) in MDD, including the default mode network, central executive network (CEN), and salience network (SN). Here, we investigated whether serial ketamine treatments change FC between limbic structures and RSNs. MethodsPatients with MDD (n = 44) were scanned at baseline (time 1 [T1]) and 24 hours after the first (T2) and fourth (T3) infusions of ketamine. Healthy control subjects (n = 50) were scanned at baseline, with a subgroup (n = 17) being rescanned at 2 weeks. Limbic regions included the amygdala and hippocampus, and RSNs included the default mode network, CEN, and SN. ResultsKetamine increased right amygdala FC to the right CEN (p = .05), decreased amygdala FC to the left CEN (p = .005) at T2 versus T1 (p = .015), which then increased at T3 versus T2 (p = .002), and decreased left amygdala FC to the SN (p = .016). Decreased left amygdala to SN FC at T2 predicted improvements in anxiety at T3 (p = .006). Ketamine increased right hippocampus FC to the left CEN (p = .001), and this change at T2 predicted decreased anhedonia at T3 (p = .005). ConclusionsKetamine modulates FC between limbic regions and RSNs implicated in MDD. Increases in FC between limbic regions and the CEN suggest that ketamine may be involved in restoring top-down control of emotion processing. FC decreases between the left amygdala and SN suggest that ketamine may ameliorate MDD-related dysconnectivity in these circuits. Early FC changes between limbic regions and RSNs may be predictive of clinical improvements.

Amygdala functional connectivity in major depression - disentangling markers of pathology, risk and resilience.

Limbic-cortical imbalance is an established model for the neurobiology of major depressive disorder (MDD), but imaging genetics studies have been contradicting regarding potential risk and resilience mechanisms. Here, we re-assessed previously reported limbic-cortical alterations between MDD relatives and controls in combination with a newly acquired sample of MDD patients and controls, to disentangle pathology, risk, and resilience. We analyzed functional magnetic resonance imaging data and negative affectivity (NA) of MDD patients (n = 48), unaffected first-degree relatives of MDD patients (n = 49) and controls (n = 109) who performed a faces matching task. Brain response and task-dependent amygdala functional connectivity (FC) were compared between groups and assessed for associations with NA. Groups did not differ in task-related brain activation but activation in the superior frontal gyrus (SFG) was inversely correlated with NA in patients and controls. Pathology was associated with task-independent decreases of amygdala FC with regions of the default mode network (DMN) and decreased amygdala FC with the medial frontal gyrus during faces matching, potentially reflecting a task-independent DMN predominance and a limbic-cortical disintegration during faces processing in MDD. Risk was associated with task-independent decreases of amygdala-FC with fronto-parietal regions and reduced faces-associated amygdala-fusiform gyrus FC. Resilience corresponded to task-independent increases in amygdala FC with the perigenual anterior cingulate cortex (pgACC) and increased FC between amygdala, pgACC, and SFG during faces matching. Our results encourage a refinement of the limbic-cortical imbalance model of depression. The validity of proposed risk and resilience markers needs to be tested in prospective studies. Further limitations are discussed.

Striatal dopamine deficits predict reductions in striatal functional connectivity in major depression: a concurrent 11C-raclopride positron emission tomography and functional magnetic resonance imaging investigation

Major depressive disorder (MDD) is characterized by the altered integration of reward histories and reduced responding of the striatum. We have posited that this reduced striatal activation in MDD is due to tonically decreased stimulation of striatal dopamine synapses which results in decremented propagation of information along the cortico-striatal-pallido-thalamic (CSPT) spiral. In the present investigation, we tested predictions of this formulation by conducting concurrent functional magnetic resonance imaging (fMRI) and 11C-raclopride positron emission tomography (PET) in depressed and control (CTL) participants. We scanned 16 depressed and 14 CTL participants with simultaneous fMRI and 11C-raclopride PET. We estimated raclopride binding potential (BPND), voxel-wise, and compared MDD and CTL samples with respect to BPND in the striatum. Using striatal regions that showed significant between-group BPND differences as seeds, we conducted whole-brain functional connectivity analysis using the fMRI data and identified brain regions in each group in which connectivity with striatal seed regions scaled linearly with BPND from these regions. We observed increased BPND in the ventral striatum, bilaterally, and in the right dorsal striatum in the depressed participants. Further, we found that as BPND increased in both the left ventral striatum and right dorsal striatum in MDD, connectivity with the cortical targets of these regions (default-mode network and salience network, respectively) decreased. Deficits in stimulation of striatal dopamine receptors in MDD could account in part for the failure of transfer of information up the CSPT circuit in the pathophysiology of this disorder.

Dynamic Resting-State Functional Connectivity in Major Depression

Dynamic Resting-State Functional Connectivity in Major Depression

Dynamic Resting-State Functional Connectivity in Major Depression.

Major depressive disorder (MDD) is characterized by abnormal resting-state functional connectivity (RSFC), especially in medial prefrontal cortical (MPFC) regions of the default network. However, prior research in MDD has not examined dynamic changes in functional connectivity as networks form, interact, and dissolve over time. We compared unmedicated individuals with MDD (n=100) to control participants (n=109) on dynamic RSFC (operationalized as SD in RSFC over a series of sliding windows) of an MPFC seed region during a resting-state functional magnetic resonance imaging scan. Among participants with MDD, we also investigated the relationship between symptom severity and RSFC. Secondary analyses probed the association between dynamic RSFC and rumination. Results showed that individuals with MDD were characterized by decreased dynamic (less variable) RSFC between MPFC and regions of parahippocampal gyrus within the default network, a pattern related to sustained positive connectivity between these regions across sliding windows. In contrast, the MDD group exhibited increased dynamic (more variable) RSFC between MPFC and regions of insula, and higher severity of depression was related to increased dynamic RSFC between MPFC and dorsolateral prefrontal cortex. These patterns of highly variable RSFC were related to greater frequency of strong positive and negative correlations in activity across sliding windows. Secondary analyses indicated that increased dynamic RSFC between MPFC and insula was related to higher levels of recent rumination. These findings provide initial evidence that depression, and ruminative thinking in depression, are related to abnormal patterns of fluctuating communication among brain systems involved in regulating attention and self-referential thinking.

Functional connectivity in major depression: Increased phase synchronization between frontal cortical EEG-source estimates

Structural and metabolic alterations in prefrontal brain areas, including the subgenual (SGPFC), medial (MPFC) and dorsolateral prefrontal cortex (DLPFC), have been shown in major depressive disorder (MDD). Still it remains largely unknown how brain connectivity within these regions is altered at the level of neuronal oscillations. Therefore, the goal was to analyze prefrontal electroencephalographic phase synchronization in MDD and its changes after antidepressant treatment. In 60 unmedicated patients and 60 healthy controls (HC), a 15-min resting electroencephalogram (EEG) was recorded in subjects at baseline and in a subgroup of patients after 2 weeks of antidepressant medication. EEG functional connectivity between the SGPFC and the MPFC/DLPFC was assessed with eLORETA (low resolution brain electromagnetic tomography) by means of lagged phase synchronization. At baseline, patients revealed increased prefrontal connectivity at the alpha frequency between the SGPFC and the left DLPFC/MPFC. After treatment, an increased connectivity between the SGPFC and the right DLPFC/MPFC at the beta frequency was found for MDD. A positive correlation was found for baseline beta connectivity and reduction in scores on the Hamilton depression rating scale. MDD is characterized by increased EEG functional connectivity within frontal brain areas. These EEG markers of disturbed neuronal communication might have potential value as biomarkers.

Functional connectivity in major depression: Increased phase synchronization between frontal cortical EEG-source estimates

Structural and metabolic alterations in prefrontal brain areas, including the subgenual (SGPFC), medial (MPFC) and dorsolateral prefrontal cortex (DLPFC), have been shown in major depressive disorder (MDD). Still it remains largely unknown how brain connectivity within these regions is altered at the level of neuronal oscillations. Therefore, the goal was to analyze prefrontal electroencephalographic phase synchronization in MDD and its changes after antidepressant treatment. In 60 unmedicated patients and 60 healthy controls (HC), a 15-min resting electroencephalogram (EEG) was recorded in subjects at baseline and in a subgroup of patients after 2 weeks of antidepressant medication. EEG functional connectivity between the SGPFC and the MPFC/DLPFC was assessed with eLORETA (low resolution brain electromagnetic tomography) by means of lagged phase synchronization. At baseline, patients revealed increased prefrontal connectivity at the alpha frequency between the SGPFC and the left DLPFC/MPFC. After treatment, an increased connectivity between the SGPFC and the right DLPFC/MPFC at the beta frequency was found for MDD. A positive correlation was found for baseline beta connectivity and reduction in scores on the Hamilton depression rating scale. MDD is characterized by increased EEG functional connectivity within frontal brain areas. These EEG markers of disturbed neuronal communication might have potential value as biomarkers.

Differences in functional connectivity in major depression versus bipolar II depression

BackgroundObjective methods of differentiating unipolar versus bipolar depression would enhance our ability to treat these disorders by providing more accurate diagnoses. One first step towards developing diagnostic methodology is determining whether brain function as assessed by functional MRI (fMRI) and functional connectivity analyses might differentiate the two disorders. MethodsFourteen subjects with bipolar II depression and 26 subjects with recurrent unipolar depression were studied using fMRI and functional connectivity analyses. ResultsThe first key finding of this study was that functional connectivity of the right posterior cingulate cortex differentiates bipolar II and unipolar depression. Additionally, results suggest that functional connectivity of this region is associated with suicidal ideation and depression severity in unipolar but not bipolar II depression. LimitationsThe primary limitation is the relatively small sample size, particularly for the correlational analyses. ConclusionsThe functional connectivity of right posterior cingulate cortex may differential unipolar from bipolar II depression. Further, connectivity of this region may be associated with depression severity and suicide risk in unipolar but not bipolar depression.

Whole brain resting-state analysis reveals decreased functional connectivity in major depression

Recently, both increases and decreases in resting-state functional connectivity have been found in major depression. However, these studies only assessed functional connectivity within a specific network or between a few regions of interest, while comorbidity and use of medication was not always controlled for. Therefore, the aim of the current study was to investigate whole-brain functional connectivity, unbiased by a priori definition of regions or networks of interest, in medication-free depressive patients without comorbidity. We analyzed resting-state fMRI data of 19 medication-free patients with a recent diagnosis of major depression (within 6 months before inclusion) and no comorbidity, and 19 age- and gender-matched controls. Independent component analysis was employed on the concatenated data sets of all participants. Thirteen functionally relevant networks were identified, describing the entire study sample. Next, individual representations of the networks were created using a dual regression method. Statistical inference was subsequently done on these spatial maps using voxel-wise permutation tests. Abnormal functional connectivity was found within three resting-state networks in depression: (1) decreased bilateral amygdala and left anterior insula connectivity in an affective network, (2) reduced connectivity of the left frontal pole in a network associated with attention and working memory, and (3) decreased bilateral lingual gyrus connectivity within ventromedial visual regions. None of these effects were associated with symptom severity or gray matter density. We found abnormal resting-state functional connectivity not previously associated with major depression, which might relate to abnormal affect regulation and mild cognitive deficits, both associated with the symptomatology of the disorder.

Reduced Functional Connectivity in Major Depression: a Whole Brain Study of Multiple Resting-State Networks

I. M. Veer, C. F. Beckmann, E. Baerends, M. J. van Tol, L. Ferrarini, J. R. Milles, D. J. Veltman, A. Aleman, M. A. van Buchem, N. J. van der Wee, and S. A. Rombouts Leiden Institute for Brain and Cognition (LIBC), Leiden, Netherlands, Department of Radiology, Leiden University Medical Center (LUMC), Leiden, Netherlands, FMRIB, University of Oxford, Oxford, United Kingdom, Department of Clinical Neuroscience, Imperial College London, London, United Kingdom, Department of Psychiatry, Leiden University Medical Center (LUMC), Leiden, Netherlands, Department of Radiology, Division of Image Processing, Leiden University Medical Center (LUMC), Leiden, Netherlands, Department of Psychiatry, Free University Medical Center (VUMC), Amsterdam, Netherlands, BCN Neuroimaging Center, University of Groningen, Groningen, Netherlands

Impaired functional connectivity at EEG alpha and theta frequency bands in major depression.

Recent reports on functional brain imaging in major depression have lead to an assumption that observed psychopathology might be related to an altered brain functional connectivity. Our hypothesis was that an increase in brain functional connectivity occurs in major depression. As a measure of functional connectivity, the electroencephalogram (EEG) structural synchrony approach was used in 12 medication-free depressive outpatients and 10 control subjects. Differences in the number and strength of structurally synchronized EEG patterns were compared between groups. In depressive patients the number and strength of short cortex functional connections were significantly larger for the left than for the right hemisphere, while the number and strength of long functional connections were significantly larger for the right than for the left hemisphere. Some of the functional connections were positively correlated with the severity of depression, thus being predictive. These were short-range anterior, posterior, and left hemisphere functional connections for the alpha frequency band and short-range anterior functional connections for the theta frequency band. The topology of the most representative functional connections among all patients with major depression indicated that the right anterior and left posterior brain parts may discriminate depressive patients from healthy controls. The obtained data support our hypothesis that there is an increase in brain functional connectivity in major depression. This finding was interpreted within the semantic framework, where different specialization of left (monosemantic context) and right (polysemantic context) hemispheres is functionally insufficient in patients with depression.

Resting-State Functional Connectivity in Major Depression: Abnormally Increased Contributions from Subgenual Cingulate Cortex and Thalamus

Positron emission tomography (PET) studies of major depression have revealed resting-state abnormalities in the prefrontal and cingulate cortices. Recently, fMRI has been adapted to examine connectivity within a specific resting-state neural network--the default-mode network--that includes medial prefrontal and anterior cingulate cortices. The goal of this study was to examine resting-state, default-mode network functional connectivity in subjects with major depression and in healthy controls. Twenty-eight subjects with major depression and 20 healthy controls underwent 5-min fMRI scans while resting quietly. Independent component analysis was used to isolate the default-mode network in each subject. Group maps of the default-mode network were compared. A within-group analysis was performed in the depressed group to explore effects of depression refractoriness on functional connectivity. Resting-state subgenual cingulate and thalamic functional connectivity with the default-mode network were significantly greater in the depressed subjects. Within the depressed group, the length of the current depressive episode correlated positively with functional connectivity in the subgenual cingulate. This is the first study to explore default-mode functional connectivity in major depression. The findings provide cross-modality confirmation of PET studies demonstrating increased thalamic and subgenual cingulate activity in major depression. Further, the within-subject connectivity analysis employed here brings these previously isolated regions of hypermetabolism into the context of a disordered neural network. The correlation between refractoriness and subgenual cingulate functional connectivity within the network suggests that a quantitative, resting-state fMRI measure could be used to guide therapy in individual subjects.