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

Godbersen, Godber Mathis; Klug, Sebastian; Wadsak, Wolfgang; Pichler, Verena; Raitanen, Julia; Rieckmann, Anna; Jonasson, Lars; Cocchi, Luca; Breakspear, Michael; Hacker, Marcus; Lanzenberger, Rupert; Hahn, Andreas

doi:10.1101/2022.08.12.503715

Cited by 3 publications

(12 citation statements)

References 52 publications

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“…The timeseries was denoised using the default CONN pipeline, regressing out the potential confounding from white matter and CSF. A low pass filter (.0625 Hz) was applied to filter out high frequency noise in the PET signal [62]. Regions of interest were generated for 106 cortical and subcortical regions of the Harvard Oxford atlas, excluding the cerebellum.…”

Section: Metabolic Connectomesmentioning

confidence: 99%

Metabolic connectivity in ageing.

Deery,

Liang,

Siddiqui

et al. 2024

Preprint

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Information transfer across the brain has a high energetic cost and requires the efficient use of glucose. Positron emission tomography (PET) studies have shown that ageing is associated with a decline in regional rates of cerebral glucose metabolism. However, until recently, it has not been possible to measure the timecourse of molecular activity within an individual using PET, preventing the study of metabolic network connectivity across the brain. Here we report the results of the first high temporal resolution functional PET study examining metabolic connectivity and cognitive function in ageing. The metabolic connectomes of 40 younger (mean age 27.9 years; range 20-42) and 46 older (mean 75.8; 60-89) adults were characterised by high connectivity strength in the frontal, temporal, motor, parietal and medial cortices. Ageing was associated with lower global integration of metabolic hub regions, indicating disrupted information transfer across the metabolic network in older adults. In younger adults, a high proportion of glucose was used to support hubs in the frontal regions. Older adults had a smaller energy budget in comparison to younger adults, and older adults used a higher proportion of energy to support mostly posterior hub regions. This difference in the metabolic network topology in older adults was associated with worse cognitive performance. We conclude that ageing is associated with reduced metabolic connectivity, an altered metabolic network topology and a high glucose cost in hub regions. Our results highlight the fundamental role that metabolism plays in supporting information transfer in the brain and the unique insights that metabolic connectivity provides into the ageing brain.

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Section: Metabolic Connectomesmentioning

confidence: 99%

Metabolic connectivity in ageing.

Deery,

Liang,

Siddiqui

et al. 2024

Preprint

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“…To assess the spatial overlap between changes in the BOLD signal and metabolic demands as induced by the 2-back working memory task, a statistical conjunction analysis was carried out in SPM12 [27]. BOLD and K i maps were individually z-scored and included in a one-way ANOVA with each modality representing a "group" and an additional factor accounting for the different scanners (i.e., PET/MR vs. separate PET/CT and MRI).…”

Section: Spatial Conjunction Of Task-specific Neuronal Activationmentioning

confidence: 99%

“…For completeness and comparison with previous work [12,27], inference was also computed at p < 0.05 FWE-corrected cluster level after an initial voxel threshold of p < 0.001 uncorrected.…”

Section: Spatial Conjunction Of Task-specific Neuronal Activationmentioning

confidence: 99%

“…First, separate maps with a negative BOLD response and a positive metabolic response during the 2-back working memory task were computed (p < 0.05 FWE-corrected cluster level following p < 0.001 uncorrected voxel level). Specific attention was given to the PCC, as we recently showed an opposite influence of the FPN and DAN metabolism onto the PCC [27]. Thus, the difference in task-specific K i between FPN and DAN during the 2-back working memory condition was computed.…”

Section: Analyses Of the Posterior Cingulate Cortex (Pcc)mentioning

confidence: 99%

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

Hahn,

Reed,

Vraka

et al. 2023

Eur J Nucl Med Mol Imaging

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Purpose 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 (fPET) framework at a temporal resolution of 3 s. Methods Thirty-five healthy volunteers underwent fPET with [18F]FDG bolus plus constant infusion, 19 of those at a hybrid PET/MRI scanner. During the scan, an n-back working memory paradigm was completed. fPET data were reconstructed to 3 s temporal resolution and processed with a novel sliding window filter to increase signal to noise ratio. BOLD fMRI signals were acquired at 2 s. Results 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. These task-specific changes were robustly observed in brain regions involved in working memory processing. 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 were dependent on the metabolic demands of the corresponding task-positive networks. Conclusions In sum, the proposed approach enables the advancement from parallel to truly synchronized investigation of metabolic and hemodynamic responses during cognitive processing. This allows to capture unique information in the temporal domain, which is not accessible to conventional PET imaging.

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“…This includes the quantification of metabolic responses or neurotransmitter signaling during cognitive processing by the recently introduced framework of functional PET (fPET) [5,6]. Using [ 18 F]2-fluoro-2-deoxy-D-glucose ([ 18 F]FDG) the approach has successfully identified task-relevant brain networks [3,7] and revealed decoupling of glucose metabolism and hemodynamic signals [8,9]. Furthermore, fPET has been utilized to quantify reward-specific changes in dopamine synthesis using 6- 18 F-fluoro-l-dopa (6-[ 18 F]FDOPA) [10].…”

Section: Introductionmentioning

confidence: 99%

Validation of cardiac image derived input functions for functional PET quantification

Reed,

Handschuh,

Schmidt

et al. 2023

Preprint

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Functional PET (fPET) is a novel technique for studying dynamic changes in brain metabolism and neurotransmitter signaling. Accurate measurement of the arterial input function (AIF) is crucial for quantification of fPET but traditionally requires invasive arterial blood sampling. While, image-derived input functions (IDIF) offer a non-invasive alternative, they are afflicted by drawbacks stemming from limited spatial resolution and field of view. Therefore, we conceptualized and validated a scan protocol for brain fPET quantified with cardiac IDIF.Twenty healthy individuals underwent fPET/MR scans using [18F]FDG or 6-[18F]FDOPA, with bed motion shuttling between the thorax and brain to capture cardiac IDIF and brain task- induced changes, respectively. Each session included arterial and venous blood sampling for IDIF validation, and participants performed a monetary incentive delay task. IDIFs from fixed- size regions of the left ventricle, ascending and descending aorta, and a composite of all 3 blood pools (3VOI) plus venous blood data (3VOIVB) were compared to the AIF. Quantitative task-specific images from both tracers were compared to assess the performance of each input function.For both radiotracer cohorts, moderate to high agreement was found between IDIFs and AIF in terms of area under the curve (r = 0.64 – 0.89) and quantified outcome parameters (CMRGlu and Ki(r)=0.84–0.99). The agreement further increased for composite IDIFs 3VOI and 3VOIVB for AUC(r)=0.87–0.93) and outcome parameters (r=0.96–0.99). Both methods showed equivalent quantitative values and high spatial overlap with AIF-derived measurements.Our proposed protocol enables accurate non-invasive estimation of the input function with full quantification of task-specific changes, addressing the limitations of IDIF for brain imaging by sampling larger blood pools over the thorax. These advancements increase applicability to virtually any PET scanner and to clinical research settings by reducing experimental complexity and increasing patient comfort.Graphical Abstract

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

Cited by 3 publications

References 52 publications

Metabolic connectivity in ageing.

Metabolic connectivity in ageing.

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

Validation of cardiac image derived input functions for functional PET quantification

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