Research reportAbnormal neural activity in the patients with remitted geriatric depression: A resting-state functional magnetic resonance imaging study
Introduction
Depression is one of the most common mental disorders in the elderly. It is associated with a decline in both well-being and daily functioning and with a high risk of functional impairment, a high risk of mortality, and a high rate of service utilization (Taki et al., 2005).
Positron emission tomography (PET) and event-related functional magnetic resonance imaging (fMRI) studies have consistently reported abnormal activation in first episode or naive patient with major depressive disorder (MDD), with predominantly decreased activation of cortical regions including the dorsolateral prefrontal cortex (Anand and Shekhar, 2003, Ketter, 1996, Mayberg et al., 1999) and anterior cingulate cortex (Drevets et al., 1997), but increased activation of limbic regions such as medial thalamus, striatum, and amygdala (Mayberg et al., 1999, Drevets, 2000, Sheline et al., 2001, Siegle et al., 2002). In contrast, there is less consensus on the changes in functional brain activity in remitted depression. PET studies in remitted depression have also demonstrated abnormalities of focal metabolism, specifically increased metabolism in anterior cingulate, orbitofrontal cortex, and medial thalamus during tryptophan depletion (Neumeister et al., 2004) and reduced metabolism in the pregenual anterior cingulate during induced sadness (Liotti et al., 2002). These studies suggested that metabolic activity of several regions may serve as “signatures” not merely of a depressive “state”, but of a depressive “trait”.
In the first resting-state fMRI study, Biswal et al. (1995) found that low-frequency fluctuation was highly synchronous among motor cortices of healthy human, concluding that the low-frequency fluctuation of blood flow and oxygenation was indeed a neurophysiological index. Since then, resting-state fMRI is being increasingly widely researched in the human brain function and dysfunction. Most of these studies, however, have used functional connectivity analysis, measuring the correlation coefficients of all brain areas with a predefined region of interest (Greicius et al., 2007). An area showing abnormal functional connectivity with other areas may not be necessarily abnormal itself. Therefore, it is important to investigate the regional activity.
The assessment of regional homogeneity (ReHo), a data-driven method, assumes that a given voxel is temporally similar to its neighbors. It measures the ReHo of the time series of the regional blood oxygen level-dependent (BOLD) signal. Therefore, ReHo reflects the temporal homogeneity of the regional BOLD signal rather than its density. As the BOLD signal of fMRI may reflect neural activity (Logothetis et al., 2001), abnormal ReHo is possibly relevant to the changes of temporal aspects of neural activity in the regional brain, and thus ReHo may be used to detect the brain regions with abnormal activity. To update, The ReHo method has been used to explore regional neural activity pattern in the resting state in only four papers, including healthy volunteers (Zang et al., 2004), schizophrenia (Liu et al., 2006, Shi et al., 2007) and attention deficit hyperactivity disorder (ADHD) (Cao et al., 2006). Liu et al. (2006) reported that decreased ReHo was found in many brain areas in schizophrenic patients by using resting-state fMRI. Cao et al. (2006) indicated that boys with ADHD showed decreased regional homogeneity in the frontal–striatal–cerebellar circuits, but increased regional homogeneity mainly in the occipital cortex. Together, the two studies suggested that the ReHo approach could be potentially useful in revealing the pathophysiology of psychiatric disorders in the resting state. As yet there has been no report of regional neural activity pattern in MDD by resting-state fMRI with ReHo method. The aim of this study is to explore the regional brain activity of patients with remitted geriatric depression by using resting-state fMRI with ReHo method.
Section snippets
Subjects
A total of 18 patients (8 men and 10 female; average age 67.2 ± 7.3 years) were recruited from the Affiliated Brain Hospital of Nanjing Medical University, China, from January 2007 to June 2007. All patients met the following inclusion criteria: (1) all patients were interviewed in a semistructured interview included in the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I), Clinician Version (First et al., 1997), by two trained and senior psychiatrists (Y Yuan and J You), and
Results
There were no significant differences in age, sex distribution, years of education, scores for HDRS, MMSE, Clock drawing test and Digit span test between the RGD patients and healthy controls (all P > 0.05). However, The RGD patients performed significantly worse in the delayed recall of RAVLT, Trail Making Test A and B (seconds) when compared to the control group (P < 0.001, P < 0.05 and P < 0.05, respectively) (see Table 1).
As compared with healthy controls, the decreased ReHo regions in RGD included
Discussion
The major finding of the present study is the demonstration that abnormal brain activity might be widely distributed in the RGD patients during the resting state. Decreased ReHo is distributed over the frontal, temporal, parietal and occipital lobes, but it is increased mainly in the putamen, frontal and parietal lobes.
In the past decade, functional imaging studies about depression have consistently demonstrated regional blood flow and metabolic abnormalities. Most investigators have reported a
Conclusion
Our resting-state fMRI study shows that an abnormal brain activity of RGD patients might occur in the resting state. The results indicate that, relative to healthy controls, patients with RGD have an atypical pattern of brain activity in the resting state and the ReHo may be potentially helpful in understanding the pathophysiology of executive function in RGD. Further work is needed to determine how these changes contribute to executive function of RGD.
Role of the funding source
This research was partly supported by the National Basic Research Program of China (973 Program) (No. 2007CB512308 Zhang Zhijun), National Hi-Tech Research and Development Program of China (863 Program) (No. 2007AA0200Z435 Zhang Zhijun).
Conflict of interest
No conflict declared.
Acknowledgment
This research was partly supported by the National Basic Research Program of China (973 Program) (No. 2007CB512308 Zhang Zhijun), National Hi-Tech Research and Development Program of China (863 Program) (No. 2007AA0200Z435 Zhang Zhijun). The authors wish to express their appreciation to Professors Zang Yufeng and Zhu Chaozhe, of Beijing Normal University for technical support and advice, thanks for Dr. Zhu Wanlin at Institute of Automation, Chinese Academy of Sciences, providing a
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