Similarity between structural and proxy estimates of brain connectivity.

Functional magnetic resonance and diffusion weighted imaging have so far made a major contribution to delineation of the brain connectome at the macroscale. While functional connectivity (FC) was shown to be related to structural connectivity (SC) to a certain degree, their spatial overlap is unknown. Even less clear are relations of SC with estimates of connectivity from inter-subject covariance of regional F18-fluorodeoxyglucose uptake (FDGcov) and grey matter volume (GMVcov). Here, we asked to what extent SC underlies three proxy estimates of brain connectivity: FC, FDGcov and GMVcov. Simultaneous PET/MR acquisitions were performed in 56 healthy middle-aged individuals. Similarity between four networks was assessed using Spearman correlation and convergence ratio (CR), a measure of spatial overlap. Spearman correlation coefficient was 0.27 for SC-FC, 0.40 for SC-FDGcov, and 0.15 for SC-GMVcov. Mean CRs were 51% for SC-FC, 48% for SC-FDGcov, and 37% for SC-GMVcov. These results proved to be reproducible and robust against image processing steps. In sum, we found a relevant similarity of SC with FC and FDGcov, while GMVcov consistently showed the weakest similarity. These findings indicate that white matter tracts underlie FDGcov to a similar degree as FC, supporting FDGcov as estimate of functional brain connectivity.

Adaptive working memory training does not produce transfer effects in cognition and neuroimaging.

Despite growing interest in cognitive interventions from academia and industry, it remains unclear if working memory (WM) training, one of the most popular cognitive interventions, produces transfer effects. Transfer effects are training-induced gains in performance in untrained cognitive tasks, while practice effects are improvements in trained task. The goal of this study was to evaluate potential transfer effects by comprehensive cognitive testing and neuroimaging. In this prospective, randomized-controlled, and single-blind study, we administered an 8-week n-back training to 55 healthy middle-aged (50-64 years) participants. State-of-the-art multimodal neuroimaging was used to examine potential anatomic and functional changes. Relative to control subjects, who performed non-adaptive WM training, no near or far transfer effects were detected in experimental subjects, who performed adaptive WM training. Equivalently, no training-related changes were observed in white matter integrity, amplitude of low frequency fluctuations, glucose metabolism, functional and metabolic connectivity. Exploratory within-group comparisons revealed some gains in transfer tasks, which, however, cannot be attributed to an increased WM capacity. In conclusion, WM training produces transfer effects neither at the cognitive level nor in terms of neural structure or function. These results speak against a common view that training-related gains reflect an increase in underlying WM capacity. Instead, the presently observed practice effects may be a result of optimized task processing strategies, which do not necessarily engage neural plasticity.

Neuronal efficiency following n-back training task is accompanied by a higher cerebral glucose metabolism.

Recent functional magnetic resonance imaging (fMRI) studies revealed lower neural activation during processing of an n-back task following working memory training, indicating a training-related increase in neural efficiency. In the present study, we asked if the training induced regional neural activation is accompanied by changes in glucose consumption. An active control and an experimental group of healthy middle-aged volunteers conducted 32 sessions of visual and verbal n-back trainings over 8 weeks. We analyzed data of 52 subjects (25 experimental and 27 control group) for practice effects underlying verbal working memory task and 50 subjects (24 experimental and 26 control group) for practice effects underlying visual WM task. The samples of these two tasks were nearly identical (data of 47 subjects were available for both verbal and visual tasks). Both groups completed neuroimaging sessions at a hybrid PET/MR system before and after training. Each session included criterion task fMRI and resting state positron emission tomography with FDG (FDG-PET). As reported previously, lower neural activation following n-back training was found in regions of the fronto-parieto-cerebellar circuitry during a verbal n-back task. Notably, these changes co-occurred spatially with a higher relative FDG-uptake. Decreased neural activation within regions of the fronto-parietal network during visual n-back task did not show co-occurring changes in relative FDG-uptake. There was no direct association between neuroimaging and behavioral measures, which could be due to the inter-subjects' variability in reaching capacity limits. Our findings provide new details for working memory training induced neural efficiency on a molecular level by integrating FDG-PET and fMRI measures.

Mapping covariance in brain FDG uptake to structural connectivity.

PURPOSE: Inter-subject covariance of regional 18F-fluorodeoxyglucose (FDG) PET measures (FDGcov) as proxy of brain connectivity has been gaining an increasing acceptance in the community. Yet, it is still unclear to what extent FDGcov is underlied by actual structural connectivity via white matter fiber tracts. In this study, we quantified the degree of spatial overlap between FDGcov and structural connectivity networks. METHODS: We retrospectively analyzed neuroimaging data from 303 subjects, both patients with suspected neurodegenerative disorders and healthy individuals. For each subject, structural magnetic resonance, diffusion tensor imaging, and FDG-PET data were available. The images were spatially normalized to a standard space and segmented into 62 anatomical regions using a probabilistic atlas. Sparse inverse covariance estimation was employed to estimate FDGcov. Structural connectivity was measured by streamline tractography through fiber assignment by continuous tracking. RESULTS: For the whole brain, 55% of detected connections were found to be convergent, i.e., present in both FDGcov and structural networks. This metric for random networks was significantly lower, i.e., 12%. Convergent were 80% of intralobe connections and only 30% of interhemispheric interlobe connections. CONCLUSION: Structural connectivity via white matter fiber tracts is a relevant substrate of FDGcov, underlying around a half of connections at the whole brain level. Short-range white matter tracts appear to be a major substrate of intralobe FDGcov connections.

Static versus Functional PET: Making Sense of Metabolic Connectivity.

Recently, Jamadar et al. (2021, Metabolic and hemodynamic resting-state connectivity of the human brain: a high-temporal resolution simultaneous BOLD-fMRI and FDG-fPET multimodality study. Cereb Cortex. 31(6), 2855-2867) compared the patterns of brain connectivity or covariance as obtained from 3 neuroimaging measures: 1) functional connectivity estimated from temporal correlations in the functional magnetic resonance imaging blood oxygen level-dependent signal, metabolic connectivity estimated, 2) from temporal correlations in 16-s frames of dynamic [18F]-fluorodeoxyglucose-positron emission tomography (FDG-PET), which they designate as functional FDG-PET (fPET), and 3) from intersubject correlations in static FDG-PET images (sPET). Here, we discuss a number of fundamental issues raised by the Jamadar study. These include the choice of terminology, the interpretation of cross-modal findings, the issue of group- to single-subject level inferences, and the meaning of metabolic connectivity as a biomarker. We applaud the methodological approach taken by the authors, but wish to present an alternative perspective on their findings. In particular, we argue that sPET and fPET can both provide valuable information about brain connectivity. Certainly, resolving this conundrum calls for further experimental and theoretical efforts to advance the developing framework of PET-based brain connectivity indices.

Working memory task induced neural activation: A simultaneous PET/fMRI study.

PURPOSE: Positron emission tomography (PET) with [18F]fluorodeoxyglucose (FDG) is a powerful method for mapping cerebral glucose metabolism as a proxy of neural activity, assuming a steady-state during the recording interval. We asked if a clinical FDG-PET imaging protocol might also capture changes in neural activity associated with performance of a working memory (WM) task. METHODS: To test this concept, we examined hybrid PET/MR data for FDG-PET and simultaneous functional magnetic resonance imaging (fMRI) in a sample of healthy volunteers. The PET image acquisition started 30 min after a bolus injection of approximately 100 MBq FDG, and the WM task was undertaken starting at approximately 60 min post-injection. We reconstructed FDG-PET sum images corresponding to baseline (44-60 min p.i.) and WM tasks (63- 71 min p.i.), each with intensity scaling to the corresponding global mean. RESULTS: Compared to the baseline resting condition, relative FDG uptake increased during WM task performance in brain regions previously associated with WM. Furthermore, these metabolically active regions partly overlapped with the regions showing task-dependent increases in BOLD signal in simultaneous fMRI. CONCLUSION: We find evidence for WM task-induced neural activation using a clinical FDG-PET imaging protocol. These findings encourage the development of dedicated protocols for tracking neural correlates of cognitive function.

Cortical and subcortical responsiveness to intensive adaptive working memory training: An MRI surface-based analysis.

Working memory training (WMT) has been shown to have effects on cognitive performance, the precise effects and the underlying neurobiological mechanisms are, however, still a matter of debate. In particular, the impact of WMT on gray matter morphology is still rather unclear. In the present study, 59 healthy middle-aged participants (age range 50-65 years) were pseudo-randomly single-blinded allocated to an 8-week adaptive WMT or an 8-week nonadaptive intervention. Before and after the intervention, high resolution magnetic resonance imaging (MRI) was performed and cognitive test performance was assessed in all participants. Vertex-wise cortical volume, thickness, surface area, and cortical folding was calculated. Seven subcortical volumes of interest and global mean cortical thickness were also measured. Comparisons of symmetrized percent change (SPC) between groups were conducted to identify group by time interactions. Greater increases in cortical gyrification in bilateral parietal regions, including superior parietal cortex and inferior parietal lobule as well as precuneus, greater increases in cortical volume and thickness in bilateral primary motor cortex, and changes in surface area in bilateral occipital cortex (medial and lateral occipital cortex) were detected in WMT group after training compared to active controls. Structural training-induced changes in WM-related regions, especially parietal regions, might provide a better brain processing environment for higher WM load.

Integrity of Neurocognitive Networks in Dementing Disorders as Measured with Simultaneous PET/Functional MRI.

Functional MRI (fMRI) studies have reported altered integrity of large-scale neurocognitive networks (NCNs) in dementing disorders. However, findings on the specificity of these alterations in patients with Alzheimer disease (AD) and behavioral-variant frontotemporal dementia (bvFTD) are still limited. Recently, NCNs have been successfully captured using PET with 18F-FDG. Methods: Network integrity was measured in 72 individuals (38 male) with mild AD or bvFTD, and in healthy controls, using a simultaneous resting-state fMRI and 18F-FDG PET. Indices of network integrity were calculated for each subject, network, and imaging modality. Results: In either modality, independent-component analysis revealed 4 major NCNs: anterior default-mode network (DMN), posterior DMN, salience network, and right central executive network (CEN). In fMRI data, the integrity of the posterior DMN was found to be significantly reduced in both patient groups relative to controls. In the AD group the anterior DMN and CEN appeared to be additionally affected. In PET data, only the integrity of the posterior DMN in patients with AD was reduced, whereas 3 remaining networks appeared to be affected only in patients with bvFTD. In a logistic regression analysis, the integrity of the anterior DMN as measured with PET alone accurately differentiated between the patient groups. A correlation between indices of 2 imaging modalities was low overall. Conclusion: FMRI and 18F-FDG PET capture partly different aspects of network integrity. A higher disease specificity for NCNs as derived from PET data supports metabolic connectivity imaging as a promising diagnostic tool.

Neural and Behavioral Effects of an Adaptive Online Verbal Working Memory Training in Healthy Middle-Aged Adults.

Neural correlates of working memory (WM) training remain a matter of debate, especially in older adults. We used functional magnetic resonance imaging (fMRI) together with an n-back task to measure brain plasticity in healthy middle-aged adults following an 8-week adaptive online verbal WM training. Participants performed 32 sessions of this training on their personal computers. In addition, we assessed direct effects of the training by applying a verbal WM task before and after the training. Participants (mean age 55.85 ± 4.24 years) were pseudo-randomly assigned to the experimental group (n = 30) or an active control group (n = 27). Training resulted in an activity decrease in regions known to be involved in verbal WM (i.e., fronto-parieto-cerebellar circuitry and subcortical regions), indicating that the brain became potentially more efficient after the training. These activation decreases were associated with a significant performance improvement in the n-back task inside the scanner reflecting considerable practice effects. In addition, there were training-associated direct effects in the additional, external verbal WM task (i.e., HAWIE-R digit span forward task), and indicating that the training generally improved performance in this cognitive domain. These results led us to conclude that even at advanced age cognitive training can improve WM capacity and increase neural efficiency in specific regions or networks.

Multisensory integration processing during olfactory-visual stimulation-An fMRI graph theoretical network analysis.

In this study, we aimed to understand how whole-brain neural networks compute sensory information integration based on the olfactory and visual system. Task-related functional magnetic resonance imaging (fMRI) data was obtained during unimodal and bimodal sensory stimulation. Based on the identification of multisensory integration processing (MIP) specific hub-like network nodes analyzed with network-based statistics using region-of-interest based connectivity matrices, we conclude the following brain areas to be important for processing the presented bimodal sensory information: right precuneus connected contralaterally to the supramarginal gyrus for memory-related imagery and phonology retrieval, and the left middle occipital gyrus connected ipsilaterally to the inferior frontal gyrus via the inferior fronto-occipital fasciculus including functional aspects of working memory. Applied graph theory for quantification of the resulting complex network topologies indicates a significantly increased global efficiency and clustering coefficient in networks including aspects of MIP reflecting a simultaneous better integration and segregation. Graph theoretical analysis of positive and negative network correlations allowing for inferences about excitatory and inhibitory network architectures revealed-not significant, but very consistent-that MIP-specific neural networks are dominated by inhibitory relationships between brain regions involved in stimulus processing.

Hippocampal, amygdala and nucleus accumbens volume in first-episode schizophrenia patients and individuals at high familial risk: A cross-sectional comparison.

It is unknown whether brain changes occur prior to onset of schizophrenia or after it develops. Prospective familial high risk studies provide a good method to investigate this. In the Edinburgh High Risk Study, structural MRI scans of 150 young individuals at familial high risk of schizophrenia, 34 patients with first-episode schizophrenia and 36 matched controls were obtained. Of the high risk participants with scans suitable for analysis, 17 developed schizophrenia after the scans were taken, whilst 57 experienced isolated or sub-clinical psychotic symptoms, and 70 remained well. We used Freesurfer to extract volumetric measurements of the hippocampus, amygdala and nucleus accumbens with the aim of assessing whether any alterations found were present in all those at high risk, or selectively in the high risk cohort based on future clinical outcome, or only in those experiencing their first-episode of psychosis. We found no significant differences in any examined regions between controls and those at high risk, or between those at high risk who later developed schizophrenia and those who remained well. However, patients with first-episode schizophrenia demonstrated significant volumetric reductions in the bilateral hippocampus, left amygdala, and right nucleus accumbens compared to high risk individuals and healthy controls, which were not significantly associated with the intake of anti-psychotic medication or duration of illness. We found that patients had significantly smaller left amygdalae and bilateral hippocampus compared to HR[ill]. Our findings suggest that volumetric reductions of the hippocampus, amygdala and nucleus accumbens occur early in the first-episode of psychosis. The apparent absence of high risk versus control differences we found using Freesurfer is at odds with our previous studies conducted on the same sample, and possible methodological reasons for these apparent discrepancies are discussed.