Biology subjects

Klug, S.

Publications and source records attributed to Klug, S..

4 recordsLinked to original sources

bioRxiv2023

Non-invasive assessment of stimulation-specific changes in cerebral glucose metabolism with functional PET

Functional positron emission tomography (fPET) with [18F]FDG allows one to quantify stimulation-induced dynamics in glucose metabolism independent of neurovascular coupling. However, the gold standard for quantification requires arterial blood sampling, which can cause discomfort for the participant and increases complexity of the experimental protocol. These constraints have limited the widespread applicability of fPET, especially in the clinical routine. Therefore, we introduce a novel approach, which enables the assessment of the dynamics in cerebral glucose metabolism without the need for an input function. MethodsWe tested the validity of a mathematical derivation on the basis of two independent data sets (DS). For DS1, 52 healthy volunteers (23.2 {+/-} 3.3 years, 24 females) completed a visuo-spatial motor coordination task (the video game Tetris(R)) and for DS2, 18 healthy participants (24.2 {+/-} 4.3 years, 8 females) performed an eyes-open/finger tapping task, both during a [18F]FDG fPET scan. Task-specific changes in metabolism were assessed with the general linear model (GLM) and cerebral metabolic rate of glucose (CMRGlu) was quantified with the Patlak plot as the reference standard. Simplified outcome parameters, such as GLM beta values of task effects and percent signal change (%SC) of both parameters were estimated. These were compared for task-relevant brain regions and on a whole-brain level. ResultsIn general, we observed higher agreement with the reference standard for DS1 (radiotracer administration as bolus + constant infusion) compared to DS2 (constant infusion only). Across both data sets, strong correlations were found between regional task-specific beta estimates and CMRGlu (r = 0.763...0.912). Additionally, %SC of beta values exhibited excellent agreement with %SC of CMRGlu (r = 0.909...0.999). Average activation maps showed a high spatial similarity between CMRGlu and beta estimates (Dice = 0.870...0.979) as well as %SC (Dice = 0.932...0.997), respectively. ConclusionTask-specific changes in glucose metabolism can be reliably estimated using %SC of GLM beta values, eliminating the need for any blood sampling. This approach streamlines fPET imaging, albeit with the trade-off of being unable to quantify baseline metabolism. The proposed simplification enhances the applicability of fPET, allowing for widespread employment in research settings and clinical investigations. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/558617v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@77faeaorg.highwire.dtl.DTLVardef@fa3495org.highwire.dtl.DTLVardef@926353org.highwire.dtl.DTLVardef@b70da0_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2023

High-temporal resolution functional PET/MRI reveals coupling between human metabolic and hemodynamic brain response

Positron emission tomography (PET) provides precise molecular information on physiological processes, but its low temporal resolution is a major obstacle. Consequently, we characterized the metabolic response of the human brain to working memory performance using an optimized functional PET framework at a temporal resolution of 3 seconds. Consistent with simulated kinetic modeling, we observed a constant increase in the [18F]FDG signal during task execution, followed by a rapid return to baseline after stimulation ceased. The simultaneous acquisition of BOLD fMRI revealed that the temporal coupling between hemodynamic and metabolic signals in the primary motor cortex was related to individual behavioral performance during working memory. Furthermore, task-induced BOLD deactivations in the posteromedial default mode network were accompanied by distinct temporal patterns in glucose metabolism, which depended on the task-positive network metabolic demands. In sum, the proposed approach enables the advancement from parallel to truly synchronized investigation of metabolic and hemodynamic responses during cognitive processing.

neuroscience↗

bioRxiv2022

Metabolic demands of the posteromedial default mode network are shaped by dorsal attention and frontoparietal control networks

Although BOLD signal decreases in the default mode network (DMN) are commonly observed during attention-demanding tasks, their neurobiological underpinnings are not fully understood. Previous work has shown decreases but also increases in glucose metabolism that match with or dissociate from these BOLD signal decreases, respectively. To resolve this discrepancy, we analyzed functional PET/MRI data from 50 healthy subjects during the performance of the visuo-spatial processing game Tetris(R) and combined this with previously published data sets of working memory as well as visual and motor stimulation. Our findings show that the glucose metabolism of the posteromedial DMN is dependent on the metabolic demands of the correspondingly engaged task-positive brain networks. Specifically, the dorsal attention (involved in Tetris(R)) and frontoparietal networks (engaged during working memory) shape the glucose metabolism of the posteromedial DMN in opposing directions. External attention-demanding tasks lead to a downregulation of the posteromedial DMN with consistent decreases in the BOLD signal and glucose metabolism, whereas working memory is subject to metabolically expensive mechanisms of BOLD signal suppression. We suggest that the former finding is mediated by decreased glutamate signaling, while the latter results from active GABAergic inhibition, regulating the competition between self-generated and task-driven internal demands. The results demonstrate that the DMN relates to cognitive processing in a flexible manner and does not always act as a cohesive task-negative network in isolation.

neuroscience↗

bioRxiv2021

Learning induces coordinated neuronal plasticity of metabolic demands and functional brain networks

The neurobiological basis of learning is reflected in adaptations of brain structure, network organization and energy metabolism. However, it is still unknown how different neuroplastic mechanisms act together and if cognitive advancements relate to general or task-specific changes. To address these questions, we tested how hierarchical network interactions contribute to improvements in the performance of a visuo-spatial processing task by employing simultaneous PET/MR neuroimaging before and after a 4-week learning period. We combined functional PET with metabolic connectivity mapping (MCM) to infer directional interactions across brain regions and subsequently performed simulations to disentangle the role of functional network dynamics and glucose metabolism. As a result, learning altered the top-down regulation of the salience network onto the occipital cortex, with increases in MCM at resting-state and decreases during task execution. Accordingly, a higher divergence between resting-state and task-specific effects was associated with better cognitive performance, indicating that these adaptations are complementary and both required for successful skill learning. Simulations further showed that changes at resting-state were dependent on glucose metabolism, whereas those during task performance were driven by functional connectivity between salience and visual networks. Referring to previous work, we suggest that learning establishes a metabolically expensive skill engram at rest, whose retrieval serves for efficient task execution by minimizing prediction errors between neuronal representations of brain regions on different hierarchical levels.

neuroscience↗