Glutamatergic correlates of gamma-band oscillatory activity during cognition: a concurrent ER-MRS and EEG study

Frequency specific synchronisation of neuronal firing within the gamma-band (30-70 Hz) appears to be a fundamental correlate of both basic sensory and higher cognitive processing. In-vitro studies suggest that the neurochemical basis of gamma-band oscillatory activity is based on interactions between excitatory (i.e. glutamate) and inhibitory (i.e. GABA) neurotransmitter concentrations. However, the nature of the relationship between excitatory neurotransmitter concentration and changes in gamma band activity in humans remains undetermined. Here, we examine the links between dynamic glutamate concentration and the formation of functional gamma-band oscillatory networks. Using concurrently acquired event-related magnetic resonance spectroscopy and electroencephalography, during a repetition-priming paradigm, we demonstrate an interaction between stimulus type (object vs. abstract pictures) and repetition in evoked gamma-band oscillatory activity, and find that glutamate levels within the lateral occipital cortex, differ in response to these distinct stimulus categories. Importantly, we show that dynamic glutamate levels are related to the amplitude of stimulus evoked gamma-band (but not to beta, alpha or theta or ERP) activity. These results highlight the specific connection between excitatory neurotransmitter concentration and amplitude of oscillatory response, providing a novel insight into the relationship between the neurochemical and neurophysiological processes underlying cognition

In vivo functional neurochemistry of human cortical cholinergic function during visuospatial attention

Cortical acetylcholine is involved in key cognitive processes such as visuospatial attention. Dysfunction in the cholinergic system has been described in a number of neuropsychiatric disorders. Levels of brain acetylcholine can be pharmacologically manipulated, but it is not possible to directly measure it in vivo in humans. However, key parts of its biochemical cascade in neural tissue, such as choline, can be measured using magnetic resonance spectroscopy (MRS). There is evidence that levels of choline may be an indirect but proportional measure of acetylcholine availability in brain tissue. In this study, we measured relative choline levels in the parietal cortex using functional (event-related) MRS (fMRS) during performance of a visuospatial attention task, with a modelling approach verified using simulated data. We describe a task-driven interaction effect on choline concentration, specifically driven by contralateral attention shifts. Our results suggest that choline MRS has the potential to serve as a proxy of brain acetylcholine function in humans

Frontal GABA Levels Change during Working Memory

Functional neuroimaging metrics are thought to reflect changes in neurotransmitter flux, but changes in neurotransmitter levels have not been demonstrated in humans during a cognitive task, and the relationship between neurotransmitter dynamics and hemodynamic activity during cognition has not yet been established. We evaluate the concentration of the major inhibitory (GABA) and excitatory (glutamate + glutamine: Glx) neurotransmitters and the cerebral perfusion at rest and during a prolonged delayed match-to-sample working memory task. Resting GABA levels in the dorsolateral prefrontal cortex correlated positively with the resting perfusion and inversely with the change in perfusion during the task. Further, only GABA increased significantly during the first working memory run and then decreased continuously across subsequent task runs. The decrease of GABA over time was paralleled by a trend towards decreased reaction times and higher task accuracy. These results demonstrate a link between neurotransmitter dynamics and hemodynamic activity during working memory, indicating that functional neuroimaging metrics depend on the balance of excitation and inhibition required for cognitive processing

Classification of first-episode psychosis using cortical thickness: a large multicenter MRI study

Machine learning classifications of first-episode psychosis (FEP) using neuroimaging have predominantly analyzed brain volumes. Some studies examined cortical thickness, but most of them have used parcellation approaches with data from single sites, which limits claims of generalizability. To address these limitations, we conducted a large-scale, multi-site analysis of cortical thickness comparing parcellations and vertex-wise approaches. By leveraging the multi-site nature of the study, we further investigated how different demographical and site-dependent variables affected predictions. Finally, we assessed relationships between predictions and clinical variables. 428 subjects (147 females, mean age 27.14) with FEP and 448 (230 females, mean age 27.06) healthy controls were enrolled in 8 centers by the ClassiFEP group. All subjects underwent a structural MRI and were clinically assessed. Cortical thickness parcellation (68 areas) and full cortical maps (20,484 vertices) were extracted. Linear Support Vector Machine was used for classification within a repeated nested cross-validation framework. Vertex-wise thickness maps outperformed parcellation-based methods with a balanced accuracy of 66.2% and an Area Under the Curve of 72%. By stratifying our sample for MRI scanner, we increased generalizability across sites. Temporal brain areas resulted as the most influential in the classification. The predictive decision scores significantly correlated with age at onset, duration of treatment, and positive symptoms. In conclusion, although far from the threshold of clinical relevance, temporal cortical thickness proved to classify between FEP subjects and healthy individuals. The assessment of site-dependent variables permitted an increase in the across-site generalizability, thus attempting to address an important machine learning limitation