Neuroimage: Reports

ObjectivesMapping the neurobiology of meditation using 3 Tesla functional MRI (fMRI) has burgeoned recently. However, limitations in signal quality and neuroanatomical resolution have impacted reliability and precision of extant findings. Although ultra-high strength 7 Tesla MRI overcomes these limitations, investigation of meditation using 7 Tesla fMRI is still in its infancy. MethodsIn this feasibility study, we scanned 10 individuals who were beginner meditators using 7 Tesla fMRI while they performed focused attention meditation and non-focused rest. We also measured and adjusted the fMRI signal for key physiological differences between meditation and rest. Finally, we explored the 2-week impact of the single fMRI meditation session on mindfulness, anxiety and focused attention attributes. ResultsGroup-level task fMRI analyses revealed significant reductions in activity during meditation relative to rest in Default-mode network hubs, i.e., antero-medial prefrontal and posterior cingulate cortices, precuneus, as well as visual and thalamic regions. These findings survived stringent statistical corrections for fluctuations in physiological responses which demonstrated significant differences (p < 0.05/n, Bonferroni controlled) between meditation and rest. Compared to baseline, State Mindfulness Scale (SMS) scores were significantly elevated (F = 8.16, p<0.05/n, Bonferroni controlled) following the fMRI meditation session, and were closely maintained at 2-week follow up. ConclusionsThis pilot study establishes the feasibility and utility of investigating focused attention meditation using ultra-high strength (7 Tesla) fMRI, by supporting widespread evidence that focused attention meditation attenuates Default-mode activity responsible for self-referential processing. Future functional neuroimaging studies of meditation should control for physiological confounds and include behavioural assessments.

About 11% of the population is left-handed, a significant minority of the potential participant pool for functional MRI (fMRI) studies. However, convention in fMRI research dictates these potential participants be excluded due to the supposition that left-handed (LH) people may have different lateralization of neural functioning than right-handed (RH) people. This difference in lateralization may cause different areas of the brain to be activated by the same task. The current study investigates the lateralization differences between N=49 LH and N=50 RH during encoding and recognition memory tasks for verbal and non-verbal stimuli. Additionally, we measured participants laterality index by administering a semantic fluency task. We found no difference between groups for memory encoding activation for either verbal or non-verbal stimuli. Similarly, we found no group differences for verbal retrieval activation. There were quantitative differences between groups in non-verbal retrieval activation, primarily driven by greater spatial extent of activation in the RH group rather than by differences in lateralization in the LH group. To measure if including LH in fMRI studies would dilute results, we calculated memory effects in a priori regions of interest (ROI) for the RH group only and then examined the effect of substituting in progressively more LH for RH. We found significant memory effects in 14 a priori ROIs, 10 of which retained significant effects when adding LH participants. The remaining ROIs had significant memory-related activation in more than 80% of simulations with statistically likely numbers of LH participants. Taken together, these results indicate that the inclusion of left-handed participants does not have a strong detrimental effect on memory-related fMRI activation. On this basis we advocate for the inclusion of left-handed participants in cognitive neuroscience of memory research.

IntroductionFunctional magnetic resonance imaging (fMRI) is widely used to study neural processes of behavior, but evaluations of test-retest reliability (TRR) of task-related blood-oxygen-level-dependent (BOLD) responses are scarce for many cognitive tasks. Such information is particularly important for longitudinal and intervention research. The ability to learn associations between choices and outcomes across decision stages is crucial for daily behavior. We assessed the measurement reliability of behavioral performance and fMRI BOLD signals during value-based sequential decision making to evaluate the TRR of task-relevant regions for future research on non-invasive brain stimulations. MethodsTwenty healthy adults (22 to 40 years) completed two task-fMRI sessions that were at least 2 weeks apart. During scanning, participants performed two variants of a three-stage Markov decision task with conditions varied in temporal contingency (immediate vs. delayed) and magnitude of choice outcomes (high vs. low). Both sessions were conducted under sham tDCS via a focal 3 x 1 montage targeting left dorsolateral prefrontal cortex (DLPFC). The TRR was assessed using intraclass correlation coefficients (ICC) with a two-way mixed-effects consistency model for decision performance and task-related fMRI signals at voxel-wise level and summarized in key regions defined by the extended Human Connectome Project atlas (HCPex). ResultsDecision performance was lower with delayed than immediate outcomes (p < 0.001). Higher outcome magnitude improved performance (p < 0.001). Decision performance increased across learning bins (p < 0.001). The behavioral TRR was in the moderate to good level (ICC(3,1) = 0.742 for accuracy; ICC(3,1) = 0.801 for reaction time). At the whole-brain level, contrasting brain activities in delayed with immediate condition revealed suprathreshold cluster peaks in several frontal-parietal (e.g., bilateral orbitofrontal, bilateral dorsolateral prefrontal, and medial parietal cortices) and striatal regions (e.g., bilateral putamen). Voxel-wise ICCs revealed variable but partly good-to-excellent TRR across task-relevant regions, with stronger reliability in several striatal, orbitofrontal, and left dorsolateral prefrontal parcels, and more variable reliability across anterior cingulate and medial prefrontal parcels. ConclusionThese results from a 2-session tDCS sham-sham stimulation study establish the validity of using the three-stage Markov decision task in future studies about intervention effects on the frontal-parietal-striatal network.

AIMChildren born preterm (PT) experience perinatal white matter injury and later reading deficits at school age. We used two complementary neuroimaging modalities to determine if reading skills would be associated with contemporaneous white matter properties in school-aged PT children. METHODIn 8-year-old PT children (N=29), we measured diffusivity (fractional anisotropy, FA), from diffusion MRI, and myelin content (relaxation rate, R1) from quantitative relaxometry. We assessed reading (Grays Oral Reading Test, Fifth Edition) in each child. Whole-brain deterministic tractography coupled with automatic segmentation and quantification were applied to extract FA and R1 along four tracts and assess their statistical association with reading scores. RESULTSReading-FA correlations were not significant along the four analyzed tracts. Reading-R1 correlations were significantly positive in portions of the left superior longitudinal fasciculus, right uncinate fasciculus, and left inferior longitudinal fasciculus. FA positively correlated with R1 in limited areas of reading-R1 associations, but did not contribute to the variance in reading scores. INTERPRETATIONCombining complementary neuroimaging approaches identified relations between reading and white matter properties not found using a single MRI measure. Associations of reading skills and white matter properties may vary across white matter tracts and metrics in PT children. What this paper adds{blacksquare} Preterm childrens reading was associated with white matter myelin content. {blacksquare}Preterm childrens reading was not associated with white matter diffusivity.

Two decades of research have provided evidence for gray matter volume (GMV) differences in developmental dyslexia (or reading disability, RD) in the left perisylvian cortex. However, there are concerns about result inconsistencies, likely attributable to small sample sizes, lenient statistical thresholds, and insufficient accounting for demographic variables and global GMV (Ramus et al., 2018). To address these concerns, we conducted a Discovery and Replication Study (N=262) using data from the Adolescent Brain Cognitive Development Study. We found GMV differences between the RD and Control Groups did not replicate across the Discovery and Replication Studies using voxel-based morphometry (VBM) in Statistical Parametric Mapping (SPM), and that a more conservative threshold yielded far fewer results. We then conducted Reproducibility Studies and first found that when using surface-based morphometry in FreeSurfer instead of VBM, the Discovery and the Replication Study results again failed to converge. Second, we combined all groups in a factorial VBM/SPM analysis and the interaction analysis provided quantitative confirmation for diverging between-group difference results across the two studies. Third, we tested for the role of covariates of no interest and found that when total GMV is not controlled for, this divergence dissipates and group differences in RD (main effect of Reading Ability) are amplified. In conclusion, replication of GMV differences in RD is low, even when using large, well-matched groups, and analyses approaches play a modulating role. As such, results from prior studies using lenient statistical thresholds and not accounting for total GMV should therefore be viewed with caution.

Recent neuroimaging studies showed that in addition to the dorsolateral prefrontal cortex (dlPFC), the posterior parietal cortex (PPC) plays a significant role in higher cognitive processes such as executive functions. In this study we aimed to explore the neural underpinnings of executive function of updating by exploring the effects of transcranial direct current stimulation (tDCS) over dlPFC and PCC. Nineteen healthy right-handed participants took part in a cross-over sham-controlled experiment. All participants underwent three tDCS conditions (active tDCS over the left dlPFC; active tDCS over the left PPC; and sham) in counterbalanced order. Following tDCS participants completed the keep-track task, with parallel forms being used in different test-sessions. As a control measure, we used a choice reaction time task. Results showed no significant effects of tDCS regardless of the localization of stimulation. Our results are in contrast with results of other studies exploring prefrontal tDCS effects on updating and do not allow for deriving conclusions about the role of the left PPC in the ability to update information in working memory.

BackgroundNormal brain function requires a dynamic balance between inhibition and excitation. While magnetic resonance spectroscopy (MRS) quantifies the chief inhibitory and excitatory neurometabolites, GABA and glutamate-glutamine (Glx), the combination of transcranial magnetic stimulation and electroencephalography (TMS-EEG) provides a complementary measure of cortical inhibition-excitation dynamics via transcranial evoked potentials (TEPs). However, the relationship between neurometabolite concentrations and TEPs is unclear. ObjectiveTo characterize the relationship between neurometabolite concentrations and TEPs, as a function of TEP component, TMS pulse type, brain region, neurometabolite, and MRS brain state. MethodsTwenty-five young healthy adults completed a 4-day protocol. Sessions 1 and 2 involved screening, anatomical MRI, and functional MRI localization of DLPFC. In session 3, single- and paired-pulse TMS-EEG were applied over SM1 and DLPFC. Session 4 included resting-state and motor-task-related MRS of SM1 and DLPFC. ResultsIn SM1, task-related GABAergic tone strongly predicted early to mid-latency TEPs. In DLPFC, local early to mid-latency TEPs showed no relationship to neurometabolites, whereas late and global TEP outcomes revealed some links. The later N100 TEP was the only component consistently modulated by paired-pulse TMS. Task-related MRS measures consistently outperformed resting-state measures in predicting TEPs for SM1, while the opposite was true for DLPFC. ConclusionsSingle-pulse TEPs reliably index the local inhibitory tone in SM1, with limited added value from paired-pulse paradigms. These findings support the use of single-pulse TEPs as accessible markers of cortical inhibition, especially for SM1, and may inform biomarkers and strategies for individualized neuromodulation. Key point summaryO_LINormal brain function relies on a balance between inhibition and excitation, yet the relationship between local cortical neurometabolite levels and cortical excitability in humans remains poorly understood. C_LIO_LIWe measured inhibitory and excitatory neurometabolites using magnetic resonance spectroscopy and assessed cortical excitability responses to non-invasive stimulation using combined transcranial magnetic stimulation - electroencephalography (TMS-EEG). C_LIO_LIIn the primary sensorimotor cortex (SM1), local cortical responses to stimulation were best explained by inhibitory GABA levels during motor task performance. In the dorsolateral prefrontal cortex (DLPFC), global cortical responses were best predicted by resting-state neurometabolite levels. C_LIO_LIOverall, paired-pulse TMS paradigms offered little additional value over single-pulse paradigms for informing on neurometabolite levels. C_LIO_LIBy demonstrating region- and state-dependent links between neurometabolite levels and cortical excitability, our findings position TMS-EEG as an accessible biomarker of cortical inhibition, particularly in SM1. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC="FIGDIR/small/701225v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@132b3faorg.highwire.dtl.DTLVardef@1c5ebeeorg.highwire.dtl.DTLVardef@1048a75org.highwire.dtl.DTLVardef@11e1a4f_HPS_FORMAT_FIGEXP M_FIG C_FIG Abstract figure legendThe left panel provides a stepwise overview of the study protocol, including (i) participant screening, (ii) functional and anatomical magnetic resonance imaging (MRI) scanning for individualization purposes, (iii) single- and paired-pulse transcranial magnetic stimulation-electroencephalography (TMS-EEG), and (iv) magnetic resonance spectroscopy (MRS) acquired at rest and during a bimanual motor task. The middle and right panels show the grand-average EEG responses to single-pulse TMS over the sensorimotor cortex (SM1, red) and dorsolateral prefrontal cortex (DLPFC, blue), respectively. The topographical maps below each EEG response depict the averaged scalp distributions corresponding to each canonical transcranial evoked potential. Per region, the top left illustration shows the group-level MRS voxel placement, whereas the top right illustration shows the simulated TMS-induced electric fields. While early to mid-latency local cortical responses were best predicted by task-related GABAergic inhibition in SM1, global cortical responses following DLPFC stimulation were best predicted by resting-state neurometabolite levels.

ObjectiveMindfulness meditation is associated with functional brain changes in regions subserving higher order cognitive processes such as attention. However, no research to date has causally probed these areas in meditators using combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG). This study aimed to investigate whether cortical reactivity to TMS differs in a community sample of experienced mindfulness meditators when compared to matched controls MethodsTMS was applied to the left and right dorsolateral prefrontal cortices (DLPFC) of 19 controls and 15 meditators while brain responses were measured using EEG. TMS-evoked potentials (P60 and N100) were analysed, and exploratory analyses using the whole EEG scalp field were performed to test whether TMS-evoked global neural response strength or the distribution of neural activity differed between groups. ResultsMeditators were found to have statistically larger P60/N100 ratios in response to left and right hemisphere DLPFC stimulation compared to controls (pFDR = 0.004, BF10 > 39). No differences were observed in P60 or N100 amplitudes when examined in isolation. We also found preliminary evidence for differences in the distribution of neural activity 269-332ms post stimulation. ConclusionThese findings demonstrate differences in cortical reactivity to TMS in meditators. Differences in the distribution of neural activity approximately 300ms following stimulation suggest differences in cortico-subcortical reverberation in meditators that may be indicative of greater inhibitory activity in frontal regions. This research contributes to our current understanding of the neurophysiology of mindfulness and highlights opportunities for further exploration into the mechanisms underpinning the benefits of mindfulness meditation.

Frontotemporal Dementia (FTD) is a neurodegenerative disorder characterized by extensive atrophy in the frontal and temporal lobes of the brain as well as high cerebrovascular burden. While anatomical Magnetic Resonance Imaging (MRI) is well established for quantifying brain atrophy in FTD, the variability in (pre-)processing methods limits the generalizability and comparability of findings. This study systematically compared the robustness and sensitivity of multiple widely used neuroimaging metrics, namely Deformation-Based Morphometry (DBM), Voxel-Based Morphometry (VBM), Cortical Thickness (CT), and segmentation-based grey matter Volumes, in detecting atrophy across FTD subtypes. We processed 732 T1-weighted MRI scans from 156 participants with FTD and 139 healthy controls from the Frontotemporal Lobar Degeneration Neuroimaging Initiative using our in-house pipeline PELICAN (Dadar et al., 2025) for volumetric measures and FreeSurfer version 7 (Fischl, 2012) for CT and grey matter segmentations. Visual quality control using consistent quality control images at each step of the pipelines revealed significantly higher failure rates for CT (38.52%) and FreeSurfer segmentations (23.63%) relative to PELICANs volumetric measures (2.04% DBM, 3.05% VBM). Failure rates differed between FTD subtypes and were related to pathological burden. Particularly for FreeSurfer, errors occurred predominantly in regions with high prevalence of atrophy and White Matter Hyperintensities. In PELICAN, the addition of a FTD-specific template as an intermediate step during nonlinear registration decreased the failure rates in this step in the FTD population. We then applied linear regression models to assess each metrics sensitivity in detecting cross-sectional differences between FTD groups controls as well as linear mixed-effects models to determine which method is most sensitive to longitudinal anatomical changes. While CT yielded effect sizes comparable to VBM and DBM when analyzing the same subset of successfully processed scans, VBM and DBM demonstrated enhanced power to detect effects due to lower failure rates and higher participant retention in the full sample. Overall, we demonstrate that image processing methodology and pipeline selection profoundly influences effect sizes and statistical power to detect meaningful between-group differences or longitudinal changes. Volumetric measures (DBM and VBM) yielded sufficiently robust pipeline outcomes to maintain adequate statistical power for capturing atrophy patterns after quality control procedures.

Very preterm (VPT) young adolescents are at high risk of executive, behavioural and socio-emotional difficulties. Previous research has shown significant evidence of the benefits of mindfulness-based intervention (MBI) on these abilities. This study aims to assess the association between the effects of MBI on neurobehavioral functioning and changes in white-matter microstructure in VPT young adolescents who completed an 8-week MBI program. Neurobehavioural assessments and multi-shell diffusion MRI were performed before and after MBI in 32 VPT young adolescents. Combined diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) measures were extracted on well-defined white matter tracts (TractSeg). A multivariate data-driven approach (partial least squares correlation) was used to explore associations between MBI-related changes on neurobehavioural measures and microstructural changes. Our finding showed an enhancement of global executive functioning after MBI that was associated with a general pattern of significant increase in fractional anisotropy (FA) and decrease in axonal dispersion (ODI) in white-matter tracts involved in executive processes. Young VPT adolescents with lower gestational age at birth showed the greatest gain in white-matter microstructural changes after MBI. HighlightsO_LIVery preterm adolescents (VPT) completed an 8-week mindfulness-based intervention (MBI) C_LIO_LIImprovement in overall executive functioning was observed after MBI C_LIO_LIExecutive gain was associate with white-matter microstructural changes C_LIO_LIThe increase in microstructural properties was in tracts involved in executive processes C_LIO_LIVPT with lower gestational age show bigger gains in microstructural changes C_LI CRediT rolesVanessa Siffredi: Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Project administration; Software; Visualization; Writing - original draft; Writing - review & editing - Maria Chiara Liverani: Conceptualization; Data curation; Investigation; Methodology; Project administration; Writing - review & editing. - Dimitri Van De Ville: Methodology; Resources; Software; Supervision; Writing - review & editing. - Lorena Freitas: Data curation; Investigation; Writing - review & editing. - Cristina Borradori Tolsa: Conceptualization; Funding acquisition; Investigation; Project administration; Resources; Supervision; Validation; Writing - review & editing. - Petra Susan Huppi: Conceptualization; Funding acquisition; Methodology; Project administration; Resources; Supervision; Validation; Writing - review & editing. -Russia Ha-Vinh Leuchter: Conceptualization; Funding acquisition; Investigation; Methodology; Project administration; Resources; Supervision; Validation; Writing - review & editing.

Background and HypothesisTraditional fMRI analyses often ignore regions that fail to reach statistical significance, assuming they are biologically unimportant. We tested the accuracy of this assumption using causal discovery based-analysis that go beyond associations/correlations to test the causality of one regions influence over the other. We hypothesized that the network of statistically significant (active network, AN) and non-significant regions (silent network, SN) causally interact and their features will causally influence psychopathology severity and working memory performance. Study DesignWe examined AN and SN during N-BACK task on 25 FHR and 37 controls. Clusters with significantly different activations were juxtaposed to 360 Glasser atlas parcellations. The PC algorithm for causal discovery was implemented. Connectivity of regions with the highest alpha-centrality (HAC) were examined. ResultsSeventy-seven Glasser regions were in the AN and the rest were silent nodes. Two regions showed HAC for FHR and HC. Among controls, one HAC region was silent (auditory association cortex) and the other one was active (insula). Among FHR, both were silent nodes (early auditory cortex). These HAC regions in both groups had bidirectional directed edges between each other forming a reciprocal circuit whose edge-weights causally "increased" magical ideation severity. ConclusionCausal connectivity between SN and AN suggests that the statistically non-significant and significant regions influence each other. Our findings question the merit of ignoring statistically non-significant regions and exclusively including statistically significant regions in the pathophysiological models. Our study suggests that causality analysis should receive greater attention.

BackgroundThe effects of tDCS at the prefrontal cortex are often investigated using cognitive paradigms, particularly working memory tasks. However, the neural basis for the neuromodulatory cognitive effects of tDCS, including which subprocesses are affected by stimulation, is not completely understood. AimsWe investigated the effects of tDCS on working memory task-related spectral activity during and after tDCS to gain better insights into the neurophysiological changes associated with stimulation. MethodsWe reanalysed data from 100 healthy participants grouped by allocation to receive either Sham (0 mA, 0.016 mA, and 0.034 mA) or Active (1 mA or 2 mA) stimulation during a 3-back task. Electroencephalography (EEG) data was used to analyse event-related spectral power in frequency bands associated with working memory performance. ResultsFrontal theta event-related synchronisation (ERS) was significantly reduced post-tDCS in the active group. Participants receiving active tDCS had slower response times following tDCS compared to Sham, suggesting interference with practice effects associated with task repetition. Theta ERS was not significantly correlated with response times or accuracy. ConclusionstDCS reduced frontal theta ERS post-stimulation, suggesting a selective disruption to working memory cognitive control and maintenance processes. These findings suggest that tDCS selectively affects specific subprocesses during working memory, which may explain heterogenous behavioural effects.

Low statistical power remains a persistent concern in functional magnetic resonance imaging (fMRI) research, largely due to small sample sizes. Although prior work has documented gradual increases in sample size over time, it remains unclear whether structural factors in the publication process are associated with study design characteristics such as sample size. This review addresses this gap by analyzing a large sample of fMRI studies to assess how institutional prestige, journal impact factor, and journal review practices are associated with sample size. We analyzed articles published in 2021-2024 reporting new fMRI data collection in adult humans and including a measure of memory. We found studies with specialized populations, such as patient populations, had smaller sample sizes, as did studies with task-based designs compared to resting-state designs. We also found larger sample sizes were associated with journals with a double-blind review process. Institutional prestige was positively associated with sample size such that more highly ranked institutions tended to have larger samples, but there was no interaction between review type (single-vs. double-blind) and prestige, indicating this difference is not likely due to reviewer bias. Journal impact factor was not associated with sample size, however institutional prestige score predicted journal impact factor. These results suggest structural factors at the institutional level likely have a stronger influence on published study sample size than reviewer practices or biases.

BackgroundThe "brain signature of cognition" concept has garnered interest as a data-driven, exploratory approach to better understand key brain regions involved in specific cognitive functions, with the potential to maximally characterize brain substrates of clinical outcomes. However, to be a robust brain phenotype, the signature approach requires a statistical foundation showing that model performance replicates across a variety of cohorts. Here, we outline a procedure that provides this foundation for a signature models of two memory-related behavioral domains. MethodIn each of two independent data cohorts, we derived regional brain gray matter thickness associations for neuropsychological and everyday cognition memory, testing for replicability. In each cohort we computed regional association to outcome in 40 randomly selected "discovery subsets" of size N = 400; we generated spatial overlap frequency maps and selected high-frequency regions as "consensus" signature masks for each cohort. We tested replicability by comparing cohort-based consensus model fits in all discovery sets. We tested explanatory power in each full cohort, compare signature model fits with competing "standard" models of each outcome. ResultSpatial replications produced strongly convergent consensus signature regions derived from UCD and ADNI. Consensus model fits were highly correlated in 40 random subsets of each cohort indicating high replicability. In comparisons over each full cohort, signature models outperformed other models with one exception. ConclusionMultiple random model generations, followed by consensus selection of regional brain substrates, produced signature models that replicated model fits to outcome and outperformed other commonly used measures. Robust biomarkers of cognition and everyday function may be achievable by this method. FundingThis project was funded by R01 AG052132 (NIH/NIA)

The goal of this study was to investigate a relatively unstudied memory condition for paradoxical combinations of item + source memory confidence responses, which challenged the conventional views of the memory processes supporting item and source memory judgments. We studied instances in which people provided accurate source memory judgments (conventionally ascribed as representing recollection) after having first produced low- confidence item recognition hits for the same items (conventionally thought to reflect familiarity-based processing). This paradoxical combination does not fit traditional accounts of being recollection (because it had low-confidence recognition) nor accounts of familiarity (since it had accurate source memory), and event-related potentials (ERPs) were used to adjudicate which processes support these kinds of memories. ERP results were unlike the conventional ERP effects of memory, lacking both an FN400 and the parietal old-new effect (LPC), and instead exhibited a significant negative-going ERP effect occurring later in time (800-1200ms) in central-parietal sites. Behavioral measures of response times revealed a crossover interaction: low confident recognition hits were slower during recognition but faster during source memory when compared to the opposite pattern seen for instances of high confident hits. Results provide a comprehensive characterization of the individual variability of the FN400 and LPC effects of memory, while adding the behavioral and physiological characterization of a late negative-going ERP effect for accurate source memory without recollection. Conclusions indicated that episodic context could be retrieved independently from recollection, while suggesting a role for a process of context familiarity that is independent from item-familiarity. HighlightsO_LIRecollection is often defined as remembering the source or context of information C_LIO_LIPrior work used ERPs to identify times when source memory did not have recollection C_LIO_LICurrent work replicated ERPs with added response times and measures of variance C_LIO_LIRecollection was not evident in certain source memories, which had a negative ERP C_LIO_LIRecollection is independent of context and is more than just remembering sources C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=182 SRC="FIGDIR/small/339697v1_ufig1.gif" ALT="Figure 1"> View larger version (69K): org.highwire.dtl.DTLVardef@4926f8org.highwire.dtl.DTLVardef@9d87d4org.highwire.dtl.DTLVardef@40a701org.highwire.dtl.DTLVardef@9460f1_HPS_FORMAT_FIGEXP M_FIG C_FIG

The present study characterized associations among brain metabolite levels, applying bivariate and multivariate (i.e., factor analysis) statistical methods to tCr-referenced estimates of the major PRESS 1H-MRS metabolites (i.e., tNAA/tCr, tCho/tCr, mI/tCr, Glx/tCr), acquired from medial parietal lobe in a large (n=299), well-characterized international cohort of healthy volunteers (Povazan et al., 2020). Results supported the hypothesis that 1H-MRS-measured metabolite estimates are moderately intercorrelated (Mr = 0.42, SDr = 0.11, ps < 0.001), with more than half (i.e., 57%) of the total variability in metabolite estimates common to (i.e., shared by) all metabolites. Older age was significantly associated with lower levels of common metabolite variance (CMV; {beta} = -0.09, p = 0.048), despite not being associated with levels of any individual metabolite. Holding CMV levels constant, females had significantly lower levels of total choline (i.e., unique metabolite variance or UMV; {beta} = -0.19, p < 0.001), mirroring significant bivariate correlations between sex and total choline reported previously. If replicated, these results would suggest that applied 1H-MRS researchers should shift their analytical framework from examining bivariate associations between individual metabolites and specialty-dependent (e.g., clinical, research) variables of interest (e.g., using t-tests) to examining multi-variable (i.e., covariate) associations between multiple metabolites and specialty-dependent variables of interest (e.g., using multiple regression). Without this shift, clear interpretation of associations of 1H-MRS metabolites with specialty-dependent variables of interest may not be possible.

IntroductionTrait mindfulness refers to ones disposition or tendency to pay attention to their experiences in the present moment, in a non-judgmental and accepting way. Trait mindfulness has been robustly associated with positive mental health outcomes, but its neural underpinnings are poorly understood. Prior resting-state fMRI studies have associated trait mindfulness with within- and between-network connectivity of the default-mode (DMN), fronto-parietal (FPN), and salience networks. However, it is unclear how generalizable the findings are, how they relate to different components of trait mindfulness, and how other networks and brain areas may be involved. MethodsTo address these gaps, we conducted the largest resting-state fMRI study of trait mindfulness to-date, consisting of a pre-registered connectome predictive modeling analysis in 367 adults across three samples collected at different sites. ResultsIn the model-training dataset, we did not find connections that predicted overall trait mindfulness, but we identified neural models of two mindfulness subscales, Acting with Awareness and Non-judging. Models included both positive networks (sets of pairwise connections that positively predicted mindfulness with increasing connectivity) and negative networks, which showed the inverse relationship. The Acting with Awareness and Non-judging positive network models showed distinct network representations involving FPN and DMN, respectively. The negative network models, which overlapped significantly across subscales, involved connections across the whole brain with prominent involvement of somatomotor, visual and DMN networks. Only the negative networks generalized to predict subscale scores out-of-sample, and not across both test datasets. Predictions from both models were also negatively correlated with predictions from a well-established mind-wandering connectome model. ConclusionsWe present preliminary neural evidence for a generalizable connectivity models of trait mindfulness based on specific affective and cognitive facets. However, the incomplete generalization of the models across all sites and scanners, limited stability of the models, as well as the substantial overlap between the models, underscores the difficulty of finding robust brain markers of mindfulness facets.

Background: Adolescence is a critical period of neurodevelopment with the emergence of chronic medical conditions and increasing exposure to long-term medications. P-tau217 is a sensitive blood-based biomarker of neuropathology in older adults, yet its developmental behavior and susceptibility to common clinical factors in youth are unclear. Here we tested whether p-tau217 varies with age, comorbidity, or medication use during adolescence; and whether collection method (venous vs Tasso+ capillary) yields comparable concentrations. Methods: In an adolescent cohort, plasma p-tau217 was measured by Simoa-X. Paired venous and Tasso+ capillary samples were also analyzed from adult volunteers for methodological comparison Results: In adolescents (n=41; mean age 16{+/-}2.6 years), p-tau217 did not correlate with age or BMI z-score and did not differ by psychiatric, cardiometabolic, or gastrointestinal comorbidity, nor by corresponding medication use. In contrast, p-tau217 concentrations were >10-fold higher in Tasso+ capillary plasma than venous plasma, a discordance replicated in paired adult samples. Conclusion: Plasma p-tau217 appears physiologically stable across common clinical variables in adolescence, but highly sensitive to biospecimen collection method. Venous and Tasso+ capillary plasma should not be directly compared or pooled until methodological differences are resolved. These data provide a developmental baseline and critical methodological caution for pediatric neuroscience and decentralized biomarker studies.

The Val66Met single nucleotide polymorphism (SNP) has previously been reported to impact performance on recognition memory tasks. Whether the two subprocesses of recognition--familiarity and recollection--are differentially impacted by the Val66Met SNP remains unknown. Using event-related potentials (ERPs) recorded during a source memory task, we attempted to dissociate these two subprocesses. Behaviourally, we used participants scores on an item-recognition subtask as a measure of familiarity, and participants scores on a source-recognition subtask as a measure of recollection. Our findings reveal that Val/Val individuals outperform Met allele carriers on the item-but not the source-recognition task. Electrophysiologically, we were interested in the N400, an early frontal component previously linked to familiarity, and the late positive complex (LPC), a posterior component linked to recollection. We found evidence for Val/Val individuals having larger amplitudes of the LPC compared to Met allele carriers, and evidence for no difference in the N400 amplitudes of these groups. Based on the lack of dissociation between familiarity- and recollection-specific ERPs at the LPC time window, we argue that our behavioural and ERP results might reflect better item-recognition for Val/Val individuals compared to Met allele carriers. We further suggest that both these results reflect differences related to familiarity, rather than recollection.

BackgroundPerforming fMRI scans of children can be a difficult task, as participants tend to move while being scanned. Head motion represents a significant confound in functional magnetic resonance imaging (fMRI) connectivity analyses, and methods to limit the impact of movement on data quality are needed. One approach has been to use shorter MRI protocols, though this potentially reduces the reliability of the results. ObjectiveHere we describe steps we have taken to limit head motion in an ongoing fMRI study of children undergoing a 60 minute MRI scan protocol. Specifically, we have used a mock scan protocol that trains participants to lie still while being scanned. We provide a detailed protocol and describe other in-scanner measures we have implemented, including an incentive system and the use of a weighted blanket. Materials and methodsParticipants who received a formal mock scan (n = 12) were compared to participants who had an informal mock scan (n = 7). A replication group of participants (n = 16), including five with autism spectrum disorder, who received a formal mock scan were also compared to the informal mock scan group. The primary measure of interest was the mean frame-to-frame displacement across eight functional runs during the fMRI protocol. ResultsParticipants in the formal mock scan and replication group tended to exhibit more low-motion functional scans than the informal mock scan group (P < 0.05). Across different functional scan conditions (i.e. while watching movie clips, performing an attention task, and during resting-state scans), effect sizes tended to be large (Hedges g > 0.8). ConclusionResults indicate that with appropriate measures, it is possible to achieve low-motion fMRI data in younger participants undergoing a long scan protocol.