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Altered Synchronizations among Neural Networks in Geriatric Depression.

Wang L, Chou YH, Potter GG, Steffens DC - Biomed Res Int (2015)

Bottom Line: We compared the resting-state activities between the two groups in the default-mode, central executive, attention, salience, and affective networks as well as correlations among these networks.Those depressed patients with lower executive function has greater synchronization between the salience network with the executive and affective networks.Our results demonstrate the effectiveness of the between-network analyses in examining neural models for geriatric depression.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychiatry, University of Connecticut Health Center, 263 Farmington, CT 06119, USA ; Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA ; Brain Imaging and Analysis Center, Duke University, Durham, NC, USA.

ABSTRACT
Although major depression has been considered as a manifestation of discoordinated activity between affective and cognitive neural networks, only a few studies have examined the relationships among neural networks directly. Because of the known disconnection theory, geriatric depression could be a useful model in studying the interactions among different networks. In the present study, using independent component analysis to identify intrinsically connected neural networks, we investigated the alterations in synchronizations among neural networks in geriatric depression to better understand the underlying neural mechanisms. Resting-state fMRI data was collected from thirty-two patients with geriatric depression and thirty-two age-matched never-depressed controls. We compared the resting-state activities between the two groups in the default-mode, central executive, attention, salience, and affective networks as well as correlations among these networks. The depression group showed stronger activity than the controls in an affective network, specifically within the orbitofrontal region. However, unlike the never-depressed controls, geriatric depression group lacked synchronized/antisynchronized activity between the affective network and the other networks. Those depressed patients with lower executive function has greater synchronization between the salience network with the executive and affective networks. Our results demonstrate the effectiveness of the between-network analyses in examining neural models for geriatric depression.

No MeSH data available.


Related in: MedlinePlus

Upper: the IC18 in the control group (a) and depression group. (b) Lower: the regions within IC18 that revealed significantly increased activity in the depressed patients than controls (c) and in the actively depressed patients than the remitted patients (d) (Z > 2.3, P < 0.05 with cluster correction).
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fig6: Upper: the IC18 in the control group (a) and depression group. (b) Lower: the regions within IC18 that revealed significantly increased activity in the depressed patients than controls (c) and in the actively depressed patients than the remitted patients (d) (Z > 2.3, P < 0.05 with cluster correction).

Mentions: Given the fact that we had a fair number of patients in a remitted state, we suspected that the reason that we did not find a significant correlation between neural activity and depression severity might be because their relationship is nonlinear; that is, it might be a depression-state dependent rather than a linear relationship. Therefore, we subsequently examined the differences in neural networks and interactions of networks between the remitted versus the actively depressed groups and between the remitted versus the control groups. As shown in Figures 3(c) and 3(d), the increased cerebellar vermis activity shown in the pooled depression group relative to controls was mainly driven by the remitted group in comparison with controls. The increased cerebellar vermis activity was not found in the actively depressed group in comparison with the control group. Instead, we found significantly increased resting activity of IC18 (another AN) in the left orbitofrontal cortex and ventromedial prefrontal cortex in the actively depressed group compared with both the control group and the remitted patient group (Figure 6). Therefore, we believe the increased orbitofrontal cortex of AN should be a depression-state effect.


Altered Synchronizations among Neural Networks in Geriatric Depression.

Wang L, Chou YH, Potter GG, Steffens DC - Biomed Res Int (2015)

Upper: the IC18 in the control group (a) and depression group. (b) Lower: the regions within IC18 that revealed significantly increased activity in the depressed patients than controls (c) and in the actively depressed patients than the remitted patients (d) (Z > 2.3, P < 0.05 with cluster correction).
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4477114&req=5

fig6: Upper: the IC18 in the control group (a) and depression group. (b) Lower: the regions within IC18 that revealed significantly increased activity in the depressed patients than controls (c) and in the actively depressed patients than the remitted patients (d) (Z > 2.3, P < 0.05 with cluster correction).
Mentions: Given the fact that we had a fair number of patients in a remitted state, we suspected that the reason that we did not find a significant correlation between neural activity and depression severity might be because their relationship is nonlinear; that is, it might be a depression-state dependent rather than a linear relationship. Therefore, we subsequently examined the differences in neural networks and interactions of networks between the remitted versus the actively depressed groups and between the remitted versus the control groups. As shown in Figures 3(c) and 3(d), the increased cerebellar vermis activity shown in the pooled depression group relative to controls was mainly driven by the remitted group in comparison with controls. The increased cerebellar vermis activity was not found in the actively depressed group in comparison with the control group. Instead, we found significantly increased resting activity of IC18 (another AN) in the left orbitofrontal cortex and ventromedial prefrontal cortex in the actively depressed group compared with both the control group and the remitted patient group (Figure 6). Therefore, we believe the increased orbitofrontal cortex of AN should be a depression-state effect.

Bottom Line: We compared the resting-state activities between the two groups in the default-mode, central executive, attention, salience, and affective networks as well as correlations among these networks.Those depressed patients with lower executive function has greater synchronization between the salience network with the executive and affective networks.Our results demonstrate the effectiveness of the between-network analyses in examining neural models for geriatric depression.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychiatry, University of Connecticut Health Center, 263 Farmington, CT 06119, USA ; Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA ; Brain Imaging and Analysis Center, Duke University, Durham, NC, USA.

ABSTRACT
Although major depression has been considered as a manifestation of discoordinated activity between affective and cognitive neural networks, only a few studies have examined the relationships among neural networks directly. Because of the known disconnection theory, geriatric depression could be a useful model in studying the interactions among different networks. In the present study, using independent component analysis to identify intrinsically connected neural networks, we investigated the alterations in synchronizations among neural networks in geriatric depression to better understand the underlying neural mechanisms. Resting-state fMRI data was collected from thirty-two patients with geriatric depression and thirty-two age-matched never-depressed controls. We compared the resting-state activities between the two groups in the default-mode, central executive, attention, salience, and affective networks as well as correlations among these networks. The depression group showed stronger activity than the controls in an affective network, specifically within the orbitofrontal region. However, unlike the never-depressed controls, geriatric depression group lacked synchronized/antisynchronized activity between the affective network and the other networks. Those depressed patients with lower executive function has greater synchronization between the salience network with the executive and affective networks. Our results demonstrate the effectiveness of the between-network analyses in examining neural models for geriatric depression.

No MeSH data available.


Related in: MedlinePlus