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Resting-state glutamate level in the anterior cingulate predicts blood-oxygen level-dependent response to cognitive control.

ABSTRACT: The dorsal anterior cingulate cortex (dACC) is a core structure for the governing of cognitive control, and recent studies have shown that interindividual differences in dACC anatomy are associated with corresponding differences in the ability for cognitive control. However, individuals differ not only in anatomical features of dACC, but also exhibit substantial variability regarding the biochemical characteristics of the dACC. In this study, we combined magnetic resonance spectroscopy ((1)H-MRS) and functional magnetic resonance imaging (fMRI), finding that interindividual differences of glutamate levels in the dACC during resting-state predict the strength of the blood-oxygen level-dependent (BOLD) response to a task requiring cognitive control. This relationship was observed in the retrosplenial cortex, the orbitofrontal cortex, the inferior parietal lobe, and the basal ganglia. More specifically, individuals with low resting-state glutamate levels in the dACC showed an increased BOLD response when the task demands were high, whereas high-glutamate individuals showed the opposite pattern of an increased BOLD response when the task demands were low. Thus, we show here that individual variability of glutamate levels is directly related to how the brain implements cognitive control.

SUBMITTER: Falkenberg LE

PROVIDER: S-EPMC3323993 | biostudies-literature | 2012 Mar

REPOSITORIES: biostudies-literature

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Resting-state glutamate level in the anterior cingulate predicts blood-oxygen level-dependent response to cognitive control.

Falkenberg Liv E LE Westerhausen René R Specht Karsten K Hugdahl Kenneth K

Proceedings of the National Academy of Sciences of the United States of America 20120312 13

The dorsal anterior cingulate cortex (dACC) is a core structure for the governing of cognitive control, and recent studies have shown that interindividual differences in dACC anatomy are associated with corresponding differences in the ability for cognitive control. However, individuals differ not only in anatomical features of dACC, but also exhibit substantial variability regarding the biochemical characteristics of the dACC. In this study, we combined magnetic resonance spectroscopy ((1)H-MRS ...[more]

PMID: 22411802

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Project description:BackgroundAberrant activity of the subcallosal cingulate (SCC) is a common theme across pharmacologic treatment efficacy prediction studies. The functioning of the SCC in psychotherapeutic interventions is relatively understudied, as are functional differences among SCC subdivisions. We conducted functional connectivity analyses (rsFC) on resting-state functional magnetic resonance imaging (fMRI) data, collected before and after a course of cognitive behavioral therapy (CBT) in patients with major depressive disorder (MDD), using seeds from three SCC subdivisions.MethodsResting-state data were collected from unmedicated patients with current MDD (Hamilton Depression Rating Scale-17 > 16) before and after 14-sessions of CBT monotherapy. Treatment outcome was assessed using the Beck Depression Inventory (BDI). Rostral anterior cingulate (rACC), anterior subcallosal cingulate (aSCC), and Brodmann's area 25 (BA25) masks were used as seeds in connectivity analyses that assessed baseline rsFC and symptom severity, changes in connectivity related to symptom improvement after CBT, and prediction of treatment outcomes using whole-brain baseline connectivity.ResultsPretreatment BDI negatively correlated with pretreatment rACC ~ dorsolateral prefrontal cortex and aSCC ~ lateral prefrontal cortex rsFC. In a region-of-interest longitudinal analysis, rsFC between these regions increased post-treatment (p < 0.05FDR). In whole-brain analyses, BA25 ~ paracentral lobule and rACC ~ paracentral lobule connectivities decreased post-treatment. Whole-brain baseline rsFC with SCC did not predict clinical improvement.ConclusionsrsFC features of rACC and aSCC, but not BA25, correlated inversely with baseline depression severity, and increased following CBT. Subdivisions of SCC involved in top-down emotion regulation may be more involved in cognitive interventions, while BA25 may be more informative for interventions targeting bottom-up processing. Results emphasize the importance of subdividing the SCC in connectivity analyses.

Project description:Progressive loss of brain tissue is seen in some patients with schizophrenia and might be caused by increased levels of glutamate and resting cerebral blood flow (rCBF) alterations. Animal studies suggest that the normalisation of glutamate levels decreases rCBF and prevents structural changes in hippocampus. However, the relationship between glutamate and rCBF in anterior cingulate cortex (ACC) of humans has not been studied in the absence of antipsychotics and illness chronicity. Ketamine is a noncompetitive N-methyl-D-aspartate receptor antagonist that transiently induces schizophrenia-like symptoms and neurobiological disturbances in healthy volunteers (HVs). Here, we used S-ketamine challenge to assess if glutamate levels were associated with rCBF in ACC in 25 male HVs. Second, we explored if S-ketamine changed the neural activity as reflected by rCBF alterations in thalamus (Thal) and accumbens that are connected with ACC. Glutamatergic metabolites were measured in ACC with magnetic resonance (MR) spectroscopy and whole-brain rCBF with pseudo-continuous arterial spin labelling on a 3-T MR scanner before, during, and after infusion of S-ketamine (total dose 0.375 mg/kg). In ACC, glutamate levels were associated with rCBF before (p < 0.05) and immediately following S-ketamine infusion (p = 0.03), but not during and after. S-Ketamine increased rCBF in ACC (p < 0.001) but not the levels of glutamate (p = 0.96). In subcortical regions, S-ketamine altered rCBF in left Thal (p = 0.03). Our results suggest that glutamate levels in ACC are associated with rCBF at rest and in the initial phase of an increase. Furthermore, S-ketamine challenge transiently induces abnormal activation of ACC and left Thal that both are implicated in the pathophysiology of schizophrenia. Future longitudinal studies should investigate if increased glutamate and rCBF are related to the progressive loss of brain tissue in initially first-episode patients.

Project description:Functional magnetic resonance imaging (fMRI) has become one of the primary tools used for noninvasively measuring brain activity in humans. For the most part, the blood oxygen level-dependent (BOLD) contrast is used, which reflects the changes in hemodynamics associated with active brain tissue. The main advantage of the BOLD signal is that it is relatively easy to measure and thus is often used as a proxy for comparing brain function across population groups (i.e., control vs. patient). However, it is particularly weighted toward veins whose structural architecture is known to vary considerably across the brain. This makes it difficult to interpret whether differences in BOLD between cortical areas reflect true differences in neural activity or vascular structure. We therefore investigated how regional variations of vascular density (VAD) relate to the amplitude of resting-state and task-evoked BOLD signals. To address this issue, we first developed an automated method for segmenting veins in images acquired with susceptibility-weighted imaging, allowing us to visualize the venous vascular tree across the brain. In 19 healthy subjects, we then applied voxel-based morphometry (VBM) to T1-weighted images and computed regional measures of gray matter density (GMD). We found that, independent of spatial scale, regional variations in resting-state and task-evoked fMRI amplitudes were better correlated to VAD compared to GMD. Using a general linear model (GLM), it was observed that the bulk of regional variance in resting-state activity could be modeled by VAD. Cortical areas whose resting-state activity was most suppressed by VAD correction included Cuneus, Precuneus, Culmen, and BA 9, 10, and 47. Taken together, our results suggest that resting-state BOLD signals are significantly related to the underlying structure of the brain vascular system. Calibrating resting BOLD activity by venous structure may result in a more accurate interpretation of differences observed between cortical areas and/or individuals.

Project description:Resting-state blood-oxygen-level-dependent (BOLD) signal acquired through functional magnetic resonance imaging is a proxy of neural activity and a key mechanism for assessing neurological conditions. Therefore, practical tools to filter out artefacts that can compromise the assessment are required. On the one hand, a variety of tailored methods to preprocess the data to deal with identified sources of noise (e.g., head motion, heart beating, and breathing, just to mention a few) are in place. But, on the other hand, there might be unknown sources of unstructured noise present in the data. Therefore, to mitigate the effects of such unstructured noises, we propose a model-based filter that explores the statistical properties of the underlying signal (i.e., long-term memory). Specifically, we consider autoregressive fractional integrative process filters. Remarkably, we provide evidence that such processes can model the signals at different regions of interest to attain stationarity. Furthermore, we use a principled analysis where a ground-truth signal with statistical properties similar to the BOLD signal under the injection of noise is retrieved using the proposed filters. Next, we considered preprocessed (i.e., the identified sources of noise removed) resting-state BOLD data of 98 subjects from the Human Connectome Project. Our results demonstrate that the proposed filters decrease the power in the higher frequencies. However, unlike the low-pass filters, the proposed filters do not remove all high-frequency information, instead they preserve process-related higher frequency information. Additionally, we considered four different metrics (power spectrum, functional connectivity using the Pearson's correlation, coherence, and eigenbrains) to infer the impact of such filter. We provided evidence that whereas the first three keep most of the features of interest from a neuroscience perspective unchanged, the latter exhibits some variations that could be due to the sporadic activity filtered out.

Dataset Information

Resting-state glutamate level in the anterior cingulate predicts blood-oxygen level-dependent response to cognitive control.

Publications

Resting-state glutamate level in the anterior cingulate predicts blood-oxygen level-dependent response to cognitive control.

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