Limits...
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

(a) Component 12 (IC12), one of the affective networks, in the control group; (b) IC12 in the depression group. To show the voxels in the cerebellum, (a) and (b) were based on threshold of Z > 2.3, P < 0.001 without cluster correction. (c) Regions within IC12 which showed significantly increased activity in the depression group (all patients) related to the control group; (d) regions within IC12 which showed significantly increased activity in subjects remitted from depression (part of patients in the depression group) related to the controls. (c) and (d) were based on threshold of Z > 2.3, P < 0.05 with cluster correction.
© Copyright Policy - open-access
Related In: Results  -  Collection


getmorefigures.php?uid=PMC4477114&req=5

fig3: (a) Component 12 (IC12), one of the affective networks, in the control group; (b) IC12 in the depression group. To show the voxels in the cerebellum, (a) and (b) were based on threshold of Z > 2.3, P < 0.001 without cluster correction. (c) Regions within IC12 which showed significantly increased activity in the depression group (all patients) related to the control group; (d) regions within IC12 which showed significantly increased activity in subjects remitted from depression (part of patients in the depression group) related to the controls. (c) and (d) were based on threshold of Z > 2.3, P < 0.05 with cluster correction.

Mentions: When comparing each individual network between patients and controls using two-sample t-tests, we found significantly increased IC12 (one of the affective networks, ANs) activity specifically in the cerebellar vermis in the depression group relative to the control group. In fact, the cerebellar vermis was not represented in the IC12 when we use the threshold of Z > 2.3, P < 0.05 with cluster correction. However, the IC12 of the depressed group did have a cluster in the cerebellar vermis when using the threshold of Z > 2.3, P < 0.001 without cluster correction (Figure 3).


Altered Synchronizations among Neural Networks in Geriatric Depression.

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

(a) Component 12 (IC12), one of the affective networks, in the control group; (b) IC12 in the depression group. To show the voxels in the cerebellum, (a) and (b) were based on threshold of Z > 2.3, P < 0.001 without cluster correction. (c) Regions within IC12 which showed significantly increased activity in the depression group (all patients) related to the control group; (d) regions within IC12 which showed significantly increased activity in subjects remitted from depression (part of patients in the depression group) related to the controls. (c) and (d) were based on threshold of 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

fig3: (a) Component 12 (IC12), one of the affective networks, in the control group; (b) IC12 in the depression group. To show the voxels in the cerebellum, (a) and (b) were based on threshold of Z > 2.3, P < 0.001 without cluster correction. (c) Regions within IC12 which showed significantly increased activity in the depression group (all patients) related to the control group; (d) regions within IC12 which showed significantly increased activity in subjects remitted from depression (part of patients in the depression group) related to the controls. (c) and (d) were based on threshold of Z > 2.3, P < 0.05 with cluster correction.
Mentions: When comparing each individual network between patients and controls using two-sample t-tests, we found significantly increased IC12 (one of the affective networks, ANs) activity specifically in the cerebellar vermis in the depression group relative to the control group. In fact, the cerebellar vermis was not represented in the IC12 when we use the threshold of Z > 2.3, P < 0.05 with cluster correction. However, the IC12 of the depressed group did have a cluster in the cerebellar vermis when using the threshold of Z > 2.3, P < 0.001 without cluster correction (Figure 3).

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