Modulation of default-mode network activity by acute tryptophan depletion is associated with mood change: A resting state functional magnetic resonance imaging study
ABSTRACT Recently, resting-state fMRI (R-fMRI) has attracted interest based on its ability to detect the default mode network. We examined the effect of acute tryptophan depletion (ATD) on the fractional amplitude of low-frequency fluctuation (fALFF) during the resting state, and the correlation between changes of mood and fALFF following ATD. We manipulated the central serotonergic levels of 21 right-handed healthy males (mean age=21.57±1.83 years) following ATD. A within-subjects, double-blind, placebo-controlled, and counter-balanced design was employed. Following ATD or sham depletion, subjects completed the Profile of Mood States (POMS) and underwent 5-min R-fMRI scans. Our findings show that the fALFF of the middle orbitofrontal cortex and precuneus was significantly decreased and the fALFF of the superior parietal lobule, paracentral lobule and precentral gyrus was significantly increased after ATD. The fALFF of the orbitofrontal cortex was negatively correlated with depressive mood. The fALFF of the superior parietal lobule was positively correlated with anger-hostility and the fALFF of the paracentral lobule was negatively correlated with vigor-activity. The middle orbitofrontal cortex plays a key role in serotonin depletion-induced brain changes and individual differences in depressive mood change. These results serve to further elucidate the mechanism of ATD-induced relapse in remitted MDD patients.
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ABSTRACT: Behavioral studies have suggested a low-frequency (0.05 Hz) fluctuation of sustained attention on the basis of the intra-individual variability of reaction-time. Conventional task designs for functional magnetic resonance imaging (fMRI) studies are not appropriate for frequency analysis. The present study aimed to propose a new paradigm, real-time finger force feedback (RT-FFF), to study the brain mechanisms of sustained attention and neurofeedback. We compared the low-frequency fluctuations in both behavioral and fMRI data from 38 healthy adults (19 males; mean age, 22.3 years). Two fMRI sessions, in RT-FFF and sham finger force feedback (S-FFF) states, were acquired (TR 2 s, Siemens Trio 3-Tesla scanner, 8 min each, counter-balanced). Behavioral data of finger force were obtained simultaneously at a sampling rate of 250 Hz. Frequency analysis of the behavioral data showed lower amplitude in the low-frequency band (0.004-0.104 Hz) but higher amplitude in the high-frequency band (27.02-125 Hz) in the RT-FFF than the S-FFF states. The mean finger force was not significantly different between the two states. fMRI data analysis showed higher fractional amplitude of low-frequency fluctuation (fALFF) in the S-FFF than in the RT-FFF state in the visual cortex, but higher fALFF in RT-FFF than S-FFF in the middle frontal gyrus, the superior frontal gyrus, and the default mode network. The behavioral results suggest that the proposed paradigm may provide a new approach to studies of sustained attention. The fMRI results suggest that a distributed network including visual, motor, attentional, and default mode networks may be involved in sustained attention and/or real-time feedback. This paradigm may be helpful for future studies on deficits of attention, such as attention deficit hyperactivity disorder and mild traumatic brain injury.Neuroscience Bulletin 08/2012; 28(4):456-67. DOI:10.1007/s12264-012-1254-2 · 1.83 Impact Factor
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ABSTRACT: A fundamental component of brain development is the formation of large-scale networks across the cortex. One such network, the default network, undergoes a protracted development, displaying weak connectivity in childhood that strengthens in adolescence and becomes most robust in adulthood. Little is known about the genetic contributions to default network connectivity in adulthood or during development. Alterations in connectivity between posterior and frontal portions of the default network have been associated with several psychological disorders, including anxiety, autism spectrum disorders, schizophrenia, depression, and attention-deficit/hyperactivity disorder. These disorders have also been linked to variants of the serotonin transporter linked polymorphic region (5-HTTLPR). The LA allele of 5-HTTLPR results in higher serotonin transporter expression than the S allele or the rarer LG allele. 5-HTTLPR may influence default network connectivity, as the superior medial frontal region has been shown to be sensitive to changes in serotonin. Also, serotonin as a growth factor early in development may alter large-scale networks such as the default network. The present study examined the influence of 5-HTTLPR variants on connectivity between the posterior and frontal structures and its development in a cross-sectional study of 39 healthy children and adolescents. We found that children and adolescents homozygous for the S allele (S/S, n=10) showed weaker connectivity in the superior medial frontal cortex compared to those homozygous for the LA allele (LA/LA, n=13) or heterozygotes (S/LA, S/LG, n=16). Moreover, there was an age-by-genotype interaction, such that those with LA/LA genotype had the steepest age-related increase in connectivity between the posterior hub and superior medial frontal cortex, followed by heterozygotes. In contrast, individuals with the S/S genotype had the least age-related increase in connectivity strength. This preliminary report expands our understanding of the genetic influences on the development of large-scale brain connectivity and lays down the foundation for future research and replication of the results with a larger sample.NeuroImage 02/2012; 59(3):2760-70. DOI:10.1016/j.neuroimage.2011.10.030 · 6.13 Impact Factor
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ABSTRACT: A lot of functional magnetic resonance imaging (fMRI) studies have indicated that Granger causality analysis (GCA) is a suitable method to reveal causal effect among brain regions. Based on another MATLAB GUI toolkit, Resting State fMRI Data Analysis Toolkit (REST), we implemented GCA on MATLAB as a graphical user interface (GUI) toolkit. This toolkit, namely REST-GCA, could output both the residual-based F and the signed-path coefficient. REST-GCA also intergrates a programme that could transform the distribution of residual-based F to approximately normal distribution and then permit parametric statistical inference at group level. Using REST-GCA, we tested the causal effect of the right frontal-insular cortex (rFIC) onto each voxel in the whole brain, and vice versa, each voxel in the whole brain on the rFIC, in a voxel-wise way in a resting-state fMRI dataset from 30 healthy college students. Using Jarque-Bera goodness-of-fit test and the Lilliefors goodness-of-fit test, we found that the transformation from F to F' and the further standardization from F' to Z score substantially improved the normality. The results of one sample t-tests on Z score showed bi-directional positive causal effect between rFIC and the dorsal anterior cingulate cortex (dACC). One sample t-tests on the signed-path coefficients showed positive causal effect from rFIC to dACC but negative from dACC to rFIC. All these results indicate that REST-GCA may be useful toolkit for caudal analysis of fMRI data.Journal of neuroscience methods 01/2012; 203(2):418-26. DOI:10.1016/j.jneumeth.2011.10.006 · 1.96 Impact Factor