Functional neuroimaging studies suggest a dynamic trajectory in Alzheimer’s disease (AD), with early hyperconnectivity followed by hypoconnectivity due to pathologic progression. This study aimed to investigate this hypothesis using neurochemical markers derived from high-field magnetic resonance spectroscopy (MRS). We analyzed data from 126 older adults enrolled in the NeuroMET studies, spanning from normal aging to dementia due to suspected AD. Using ultra-high-field 7 Tesla MRS, we quantified levels of the neurotransmitters glutamate (excitatory) and GABA (inhibitory) in the precentral cortex. Plasma p -Tau181 was used as a proxy for AD pathology, and memory was assessed using the NeuroMET Memory Metric (NMM). A p -Tau181 threshold of >2.08 pg/mL was applied as an estimated marker of amyloid positivity (Aß+). Linear mixed-effects models, adjusted for age at baseline, were used to evaluate associations and interaction effects. Glutamate levels showed a non-linear association with age, decreasing up to around 70 years and increasing thereafter, while GABA levels remained stable (Figure 1A–C). Before reaching the suggested pathological conversion threshold for amyloid positivity, both glutamate and GABA showed a slight, non-significant increase in individuals with higher p -Tau181 levels (Figure 1D–F). Notably, amyloid status moderated the relationship between memory ability and glutamate levels (Figure 1G–I). Among Aß-negative individuals, lower memory ability was associated with elevated glutamate, potentially reflecting a very early compensatory response. Our findings support the hypothesis of a non-linear neurochemical trajectory in aging and early AD pathology. The observed age-dependent fluctuations in glutamate, together with subtle shifts in response to rising plasma p -Tau181, may reflect early pathologic or compensatory mechanisms. The interaction between glutamate and memory ability, particularly in supposedly Aß-negative individuals, suggests that excitatory neurotransmission could transiently support cognitive function in the face of emerging pathology. Notably, the threshold of plasma p -Tau181 used to define amyloid positivity may identify individuals in progressed stages, potentially missing earlier windows of therapeutic opportunity. As potential treatments may have markedly different effects depending on the stage of disease progression, investigating the trajectory of neuronal connectivity and activity is critical.

PURPOSE:To develop and validate a framework for personalized, implant-specific MRI safety assessments using feedback from commercial deep brain stimulation (DBS) systems. To further use this framework to suppress RF-induced heating with minimum compromise in imaging performance. METHODS:Two off-the-shelf DBS implantable pulse generators and a commercial 8-electrode DBS lead were utilized for quantitative safety assessments. In controlled phantom experiments, (i) RF-induced voltages on the DBS lead, and (ii) temperature-dependent admittance/impedance changes in the tissue surrounding the lead's electrodes were quantified. This information was used to suppress implant-related RF heating by calculating implant-friendly imaging modes. Experimental conditions included excitations with different RF transmit coils (8-channel 3 T and 7 T head coils, 2-channel 3 T body coil), over 1000 different exposure scenarios, different implant configurations, and the use of external reference probes ( E $$ E $$ -field and temperature) for validation. Imaging performance of the applied implant-friendly mode was demonstrated in vivo on a 3 T scanner. RESULTS:E $$ E $$ -fields and temperature rises around the tip electrodes could be robustly detected directly from the DBS lead. Both signals quantify the momentary patient hazard. Utilizing these measurements-recorded and wirelessly transmitted by the DBS system-tissue heating was reduced up to 99% for the same transmission power with comparable imaging performance to a conventional imaging mode. CONCLUSION:All the information needed for full in situ control of implant heating in MRI can be read directly from the DBS device. This approach would improve both patient safety and image quality while simultaneously reducing workload and responsibilities of the clinical personnel.

Quantitative MRI has been an active area of research for decades and has produced a huge range of approaches with enormous potential for patient benefit. In many cases, however, there are challenges with reproducibility which have hampered clinical translation. Quantitative MRI is a form of measurement and like any other form of measurement it requires a supporting metrological framework to be fully consistent and compatible with the international system of units. This means not just expressing results in terms of seconds, meters, etc., but demonstrating consistency to their internationally recognized definitions. Such a framework for MRI is not yet complete, but a considerable amount of work has been done internationally towards building one. This article describes the current state of the art for MRI metrology, including a detailed description of metrological principles and how they are relevant to fully quantitative MRI. It also undertakes a gap analysis of where we are versus where we need to be to support reproducibility in MRI. It focusses particularly on the role and activities of national measurement institutes across the globe, illustrating the genuinely international and collaborative nature of the field.

To improve reliability of metabolite quantification at both, 3 T and 7 T, we propose a novel parametrized macromolecules quantification model (PRaMM) for brain 1H MRS, in which the ratios of macromolecule peak intensities are used as soft constraints. Full- and metabolite-nulled spectra were acquired in three different brain regions with different ratios of grey and white matter from six healthy volunteers, at both 3 T and 7 T. Metabolite-nulled spectra were used to identify highly correlated macromolecular signal contributions and estimate the ratios of their intensities. These ratios were then used as soft constraints in the proposed PRaMM model for quantification of full spectra. The PRaMM model was validated by comparison with a single-component macromolecule model and a macromolecule subtraction technique. Moreover, the influence of the PRaMM model on the repeatability and reproducibility compared with those other methods was investigated. The developed PRaMM model performed better than the two other approaches in all three investigated brain regions. Several estimates of metabolite concentration and their Cramér-Rao lower bounds were affected by the PRaMM model reproducibility, and repeatability of the achieved concentrations were tested by evaluating the method on a second repeated acquisitions dataset. Although the observed effects on both metrics were not significant, the fit quality metrics were improved for the PRaMM method (p ≤ 0.0001). Minimally detectable changes are in the range 0.5-1.9 mM, and the percentage coefficients of variations are lower than 10% for almost all the clinically relevant metabolites. Furthermore, potential overparameterization was ruled out. Here, the PRaMM model, a method for an improved quantification of metabolites, was developed, and a method to investigate the role of the MM background and its individual components from a clinical perspective is proposed.

Adolescence is a crucial period for physical and psychological development. The impact of negative life events represents a risk factor for the onset of neuropsychiatric disorders. This study aims to investigate the relationship between negative life events and structural brain connectivity, considering both graph theory and connectivity strength. A group (n = 487) of adolescents from the IMAGEN Consortium was divided into Low and High Stress groups. Brain networks were extracted at an individual level, based on morphological similarity between grey matter regions with regions defined using an atlas-based region of interest (ROI) approach. Between-group comparisons were performed with global and local graph theory measures in a range of sparsity levels. The analysis was also performed in a larger sample of adolescents (n = 976) to examine linear correlations between stress level and network measures. Connectivity strength differences were investigated with network-based statistics. Negative life events were not found to be a factor influencing global network measures at any sparsity level. At local network level, between-group differences were found in centrality measures of the left somato-motor network (a decrease of betweenness centrality was seen at sparsity 5%), of the bilateral central visual and the left dorsal attention network (increase of degree at sparsity 10% at sparsity 30% respectively). Network-based statistics analysis showed an increase in connectivity strength in the High stress group in edges connecting the dorsal attention, limbic and salience networks. This study suggests negative life events alone do not alter structural connectivity globally, but they are associated to connectivity properties in areas involved in emotion and attention.

BACKGROUND:Associations between longitudinal changes of plasma biomarkers and cerebral magnetic resonance (MR)-derived measurements in Alzheimer's disease (AD) remain unclear. METHODS:In a study population (n = 127) of healthy older adults and patients within the AD continuum, we examined associations between longitudinal plasma amyloid beta 42/40 ratio, tau phosphorylated at threonine 181 (p-tau181), glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), and 7T structural and functional MR imaging and spectroscopy using linear mixed models. RESULTS:Increases in both p-tau181 and GFAP showed the strongest associations to 7T MR-derived measurements, particularly with decreasing parietal cortical thickness, decreasing connectivity of the salience network, and increasing neuroinflammation as determined by MR spectroscopy (MRS) myo-inositol. DISCUSSION:Both plasma p-tau181 and GFAP appear to reflect disease progression, as indicated by 7T MR-derived brain changes which are not limited to areas known to be affected by tau pathology and neuroinflammation measured by MRS myo-inositol, respectively. HIGHLIGHTS:This study leverages high-resolution 7T magnetic resonance (MR) imaging and MR spectroscopy (MRS) for Alzheimer's disease (AD) plasma biomarker insights. Tau phosphorylated at threonine 181 (p-tau181) and glial fibrillary acidic protein (GFAP) showed the largest changes over time, particularly in the AD group. p-tau181 and GFAP are robust in reflecting 7T MR-based changes in AD. The strongest associations were for frontal/parietal MR changes and MRS neuroinflammation.

Multiple sites within Germany operate human MRI systems with magnetic fields either at 7 Tesla or 9.4 Tesla. In 2013, these sites formed a network to facilitate and harmonize the research being conducted at the different sites and make this technology available to a larger community of researchers and clinicians not only within Germany, but also worldwide. The German Ultrahigh Field Imaging (GUFI) network has defined a strategic goal to establish a 14 Tesla whole-body human MRI system as a national research resource in Germany as the next progression in magnetic field strength. This paper summarizes the history of this initiative, the current status, the motivation for pursuing MR imaging and spectroscopy at such a high magnetic field strength, and the technical and funding challenges involved. It focuses on the scientific and science policy process from the perspective in Germany, and is not intended to be a comprehensive systematic review of the benefits and technical challenges of higher field strengths.

Purpose: To investigate a novel reduced RF heating method for imaging in the presence of active implanted medical devices (AIMDs) which employs a sensor-equipped implant that provides wireless feedback. Methods: The implant, consisting of a generator case and a lead, measures RF-induced E-fields at the implant tip using a simple sensor in the generator case and transmits these values wirelessly to the MR scanner. Based on the sensor signal alone, parallel transmission (pTx) excitation vectors were calculated to suppress tip heating and maintain image quality. A sensor-based imaging metric was introduced to assess the image quality. The methodology was studied at 7T in testbed experiments, and at a 3T scanner in an ASTM phantom containing AIMDs instrumented with six realistic deep brain stimulation (DBS) lead configurations adapted from patients.Results: The implant successfully measured RF-induced E-fields (Pearson correlation coefficient squared [R-2] = 0.93) and temperature rises (R-2 = 0.95) at the implant tip. The implant acquired the relevant data needed to calculate the pTx excitation vectors and transmitted them wirelessly to the MR scanner within a single shot RF sequence (<60 ms). Temperature rises for six realistic DBS lead configurations were reduced to 0.03-0.14 K for heating suppression modes compared to 0.52-3.33 K for the worst-case heating, while imaging quality remained comparable (five of six lead imaging scores were =0.80/1.00) to conventional circular polarization (CP) images.Conclusion: Implants with sensors that can communicate with an MR scanner can substantially improve safety for patients in a fast and automated manner, easing the current burden for MR personnel.

Introduction: The hippocampus is the most prominent single region of interest (ROI) for the diagnosis and prediction of Alzheimer's disease (AD). However, its suitability in the earliest stages of cognitive decline, i.e., subjective cognitive decline (SCD), remains uncertain which warrants the pursuit of alternative or complementary regions. The amygdala might be a promising candidate, given its implication in memory as well as other psychiatric disorders, e.g. depression and anxiety, which are prevalent in SCD. In this 7 tesla (T) magnetic resonance imaging (MRI) study, we aimed to compare the contribution of volumetric measurements of the hippocampus, the amygdala, and their respective subfields, for early diagnosis and prediction in an AD-related study population.Methods: Participants from a longitudinal study were grouped into SCD (n = 29), mild cognitive impairment (MCI, n = 23), AD (n = 22) and healthy control (HC, n = 31). All participants underwent 7T MRI at baseline and extensive neuropsychological testing at up to three visits (baseline n = 105, 1-year n = 78, 3-year n = 39). Analysis of covariance (ANCOVA) was used to assess group differences of baseline volumes of the amygdala and the hippocampus and their subfields. Linear mixed models were used to estimate the effects of baseline volumes on yearly changes of a z-scaled memory score. All models were adjusted to age, sex and education.Results: Compared to the HC group, individuals with SCD showed smaller amygdala ROI volumes (range across subfields-11% to-1%), but not hippocampus ROI volumes (-2% to 1%) except for the hippocampus-amygdalatransition-area (-7%). However, cross-sectional associations between baseline memory and volumes were smaller for amygdala ROIs (std. ss [95% CI] ranging between 0.16 [0.08; 0.25] and 0.46 [0.31; 0.60]) than hippocampus ROIs (between 0.32 [0.19; 0.44] and 0.53 [0.40; 0.67]). Further, the association of baseline volumes with yearly memory change in the HC and SCD groups was similarly weak for amygdala ROIs and hippocampus ROIs. In the MCI group, volumes of amygdala ROIs were associated with a relevant yearly memory decline [95% CI] ranging between-0.12 [-0.24; 0.00] and-0.26 [-0.42;-0.09] for individuals with 20% smaller volumes than the HC group. However, effects were stronger for hippocampus ROIs with a corresponding yearly memory decline ranging between-0.21 [-0.35;-0.07] and-0.31 [-0.50;-0.13].Conclusion: Volumes of amygdala ROIs, as determined by 7T MRI, might contribute to objectively and non invasively identify patients with SCD, and thus aid early diagnosis and treatment of individuals at risk to develop dementia due to AD, however associations with other psychiatric disorders should be evaluated in further studies. The amygdala's value in the prediction of longitudinal memory changes in the SCD group remains questionable. Primarily in patients with MCI, memory decline over 3 years appears to be more strongly associated with volumes of hippocampus ROIs than amygdala ROIs.

To protect implant carriers in MRI from excessive radiofrequency (RF) heating it has previously been suggested to assess that hazard via sensors on the implant. Other work recommended parallel transmission (pTx) to actively mitigate implant-related heating. Here, both ideas are integrated into one comprehensive safety concept where native pTx safety (without implant) is ensured by state-of-the-art field simulations and the implant-specific hazard is quantified in situ using physical sensors. The concept is demonstrated by electromagnetic simulations performed on a human voxel model with a simplified spinal-cord implant in an eight-channel pTx body coil at 3 T . To integrate implant and native safety, the sensor signal must be calibrated in terms of an established safety metric (e.g., specific absorption rate [SAR]). Virtual experiments show that E -field and implant-current sensors are well suited for this purpose, while temperature sensors require some caution, and B 1 probes are inadequate. Based on an implant sensor matrix Q s , constructed in situ from sensor readings, and precomputed native SAR limits, a vector space of safe RF excitations is determined where both global (native) and local (implant-related) safety requirements are satisfied. Within this safe-excitation subspace, the solution with the best image quality in terms of B 1 + magnitude and homogeneity is then found by a straightforward optimization algorithm. In the investigated example, the optimized pTx shim provides a 3-fold higher mean B 1 + magnitude compared with circularly polarized excitation for a maximum implant-related temperature increase ∆ T imp ≤ 1 K . To date, sensor-equipped implants interfaced to a pTx scanner exist as demonstrator items in research labs, but commercial devices are not yet within sight. This paper aims to demonstrate the significant benefits of such an approach and how this could impact implant-related RF safety in MRI. Today, the responsibility for safe implant scanning lies with the implant manufacturer and the MRI operator; within the sensor concept, the MRI manufacturer would assume much of the operator's current responsibility.

Previous research has suggested an association between living environment during the first 15 years of life and brain structure. More precisely, urbanicity during upbringing has been shown to be negatively related to prefrontal cortex grey matter. The present study focusses instead on the current living environment of 677 younger adults recruited from different cities across Europe. We observed a positive association between amount of tree cover density, in a radius of 500m around the current home address and grey matter volume in right orbitofrontal cortex (rOFC). Of note, the volume of the rOFC cluster identified, showed a positive association with cognitive performance in the Wechsler Adult Intelligence Scale, namely in the verbal and spatial ability domain (Vocabulary, Block Design), and a negative association with both, self-reported and behavioural markers of impulsivity (delay discounting). Moreover, rOFC volume showed a negative association with self-reported alcohol use problems. The data provide strong evidence in favour of a link between geographical features of the current living environment (particularly trees) and brain structure above and beyond childhood and upbringing. Interestingly, the respective brain correlates are associated with cognitive, behavioural and personality characteristics which have been considered as risk factors for several psychiatric disorders. Environmental neuroscience may in the long run provide a knowledge base for evidence-based urban landscape planning to facilitate mental health.

Phantom realization represents an important activity for the development and validation of advanced MR-based quantitative imaging techniques such as Magnetic Resonance Fingerprinting or Electrical Properties Tomography. In this regard, phantoms represent a reliable ground truth with the requirement that the sought properties are properly characterised in the variety of conditions at which the phantoms will be finally deployed. In this abstract, measurements of the electrical properties of two different gel-based tissue-mimicking materials are presented as a function of their temperature. A linear dependence with positive (negative) slope between temperature and electrical conductivity (relative permittivity) is observed.

Few studies have examined the association between conduct problems and cerebral cortical development. Herein, we characterize the association between age-related brain change and conduct problems in a large longitudinal, community-based sample of adolescents. 1,039 participants from the IMAGEN study possessed psychopathology and surface-based morphometric data at study baseline (M = 14.42 years, SD = 0.40; 559 females) and 5-year follow-up. Self-reports of conduct problems were obtained using the Strengths and Diffi-culties Questionnaire (SDQ). Vertex-level linear mixed effects models were implemented using the Matlab toolbox, SurfStat. To investigate the extent to which cortical thickness maturation was qualified by dimensional measures of conduct problems, we tested for an interaction between age and SDQ Conduct Problems (CP) score. There was no main effect of CP score on cortical thickness; however, a significant "Age by CP" interaction was revealed in bilateral insulae, left inferior frontal gyrus, left rostral anterior cingulate, left posterior cingulate, and bilateral inferior parietal cortices. Across regions, follow-up analysis revealed higher levels of CP were associated with accelerated age-related thinning. Findings were not meaningfully altered when controlling for alcohol use, co-occurring psychopathology, and socioeconomic status. Results may help to further elucidate neuro-developmental patterns linking adolescent conduct problems with adverse adult outcomes.

Blood-based biomarkers (BBM) have shown promising potential in diagnosis and prognosis of patients affected by Alzheimer’s disease (AD) pathology. This observational study analyzed the cross-sectional relation between BBMs and disease relevant outcomes (e.g., cognition, imaging modalities). The study sample comprised individuals with subjective cognitive decline (N = 35), mild cognitive impairment (N = 30), dementia due to suspected AD (N = 27) and healthy controls (N = 35). Data for the following measures were assessed: 1) AD-related BBMs measured in plasma on Simoa: amyloid beta ratio 42/40 (Ab42/40), tau phosphorylated at threonine-181 (p-Tau 181), glial fibrilic acid protein (GFAP), and neurofilament light chain (NfL), 2) several cognitive parameters, 3) structural volumes, functional connectivity and brain metabolite concentrations measured by 7T magnetic resonance imaging (MRI) and spectroscopy (MRS), and 4) concentrations of general blood count. Linear mixed models were used to assess associations between the AD-related BBMs (1) and the other measures (2 to 4). While none of the associations between Ab42/40 and the AD-related outcome measures reached significance (p > 0.05), higher concentrations of p-Tau 181, GFAP and NfL were associated with lower values for MMSE, memory and executive function and parietal cortical thickness, as well as higher concentrations of MRS Myo-inositol and blood creatinine (figure 1). Additionally, GFAP and NfL were associated with lower MRS N-Acetylaspartic acid (NAA), and GFAP was associated with smaller hippocampus volume. Beta-coefficients and p-values for all associations are provided in table 1. Unlike Ab42/40, abnormal concentrations of p-Tau 181, GFAP and NfL showed strong and robust associations to other AD-related outcome measures making them a better target for screening, diagnosis and possibly prognosis for individuals with AD.

Recent studies proposed a general psychopathology factor underlying common comorbidities among psychiatric disorders. However, its neurobiological mechanisms and generalizability remain elusive. In this study, we used a large longitudinal neuroimaging cohort from adolescence to young adulthood (IMAGEN) to define a neuropsychopathological (NP) factor across externalizing and internalizing symptoms using multitask connectomes. We demonstrate that this NP factor might represent a unified, genetically determined, delayed development of the prefrontal cortex that further leads to poor executive function. We also show this NP factor to be reproducible in multiple developmental periods, from preadolescence to early adulthood, and generalizable to the resting-state connectome and clinical samples (the ADHD-200 Sample and the STRATIFY & ESTRA Project). In conclusion, we identify a reproducible and general neural basis underlying symptoms of multiple mental health disorders, bridging multidimensional evidence from behavioral, neuroimaging and genetic substrates. These findings may help to develop new therapeutic interventions for psychiatric comorbidities.

Hemispheric lateralization and its origins have been of great interest in neuroscience for over a century. The left-right asymmetry in cortical thickness may stem from differential maturation of the cerebral cortex in the two hemispheres. Here, we investigated the spatial pattern of hemispheric differences in cortical thinning during adolescence, and its relationship with the density of neurotransmitter receptors and homotopic functional connectivity. Using longitudinal data from IMAGEN study (N = 532), we found that many cortical regions in the frontal and temporal lobes thinned more in the right hemisphere than in the left. Conversely, several regions in the occipital and parietal lobes thinned less in the right (vs. left) hemisphere. We then revealed that regions thinning more in the right (vs. left) hemispheres had higher density of neurotransmitter receptors and transporters in the right (vs. left) side. Moreover, the hemispheric differences in cortical thinning were predicted by homotopic functional connectivity. Specifically, regions with stronger homotopic functional connectivity showed a more symmetrical rate of cortical thinning between the left and right hemispheres, compared with regions with weaker homotopic functional connectivity. Based on these findings, we suggest that the typical patterns of hemispheric differences in cortical thinning may reflect the intrinsic organization of the neurotransmitter systems and related patterns of homotopic functional connectivity.

For simultaneous multi-voxel spectroscopy (sMVS), it is necessary to optimize the B 0 shimming and the B 1 + adjustment simultaneously for two voxels. The impact of these adjustments on the smallest possible distance for simultaneous two-voxel MRS acquisitions is determined by Bloch simulations, and the influence on the spectral quality is assessed for three different brain regions. To this end, the previously introduced 2 spin-echo full-intensity acquired localization (2SPECIAL) sequence and the voxel-GeneRalized Autocalibrating Partial Parallel Acquisition (vGRAPPA) decomposition algorithm are utilized to simultaneously acquire and retrospectively decompose in vivo brain 1 H-MRS data from two voxels at short echo times at 7T.

A long T2 relaxation time can reflect oedema, and myocardial inflammation when combined with increased plasma troponin levels. Cardiovascular magnetic resonance (CMR) T2 mapping therefore has potential to provide a key diagnostic and prognostic biomarkers. However, T2 varies by scanner, software, and sequence, highlighting the need for standardization and for a quality assurance system for T2 mapping in CMR. To fabricate and assess a phantom dedicated to the quality assurance of T2 mapping in CMR. A T2 mapping phantom was manufactured to contain 9 T1 and T2 (T1|T2) tubes to mimic clinically relevant native and post-contrast T2 in myocardium across the health to inflammation spectrum (i.e., 43–74 ms) and across both field strengths (1.5 and 3 T). We evaluated the phantom’s structural integrity, B0 and B1 uniformity using field maps, and temperature dependence. Baseline reference T1|T2 were measured using inversion recovery gradient echo and single-echo spin echo (SE) sequences respectively, both with long repetition times (10 s). Long-term reproducibility of T1|T2 was determined by repeated T1|T2 mapping of the phantom at baseline and at 12 months. The phantom embodies 9 internal agarose-containing T1|T2 tubes doped with nickel di-chloride (NiCl2) as the paramagnetic relaxation modifier to cover the clinically relevant spectrum of myocardial T2. The tubes are surrounded by an agarose-gel matrix which is doped with NiCl2 and packed with high-density polyethylene (HDPE) beads. All tubes at both field strengths, showed measurement errors up to ≤ 7.2 ms [< 14.7

Leveraging ~10 years of prospective longitudinal data on 704 participants, we examined the effects of adolescent versus young adult cannabis initiation on MRI-assessed cortical thickness development and behavior. Data were obtained from the IMAGEN study conducted across eight European sites. We identified IMAGEN participants who reported being cannabis-naïve at baseline and had data available at baseline, 5-year, and 9-year follow-up visits. Cannabis use was assessed with the European School Survey Project on Alcohol and Drugs. T1-weighted MR images were processed through the CIVET pipeline. Cannabis initiation occurring during adolescence (14–19 years) and young adulthood (19–22 years) was associated with differing patterns of longitudinal cortical thickness change. Associations between adolescent cannabis initiation and cortical thickness change were observed primarily in dorso- and ventrolateral portions of the prefrontal cortex. In contrast, cannabis initiation occurring between 19 and 22 years of age was associated with thickness change in temporal and cortical midline areas. Follow-up analysis revealed that longitudinal brain change related to adolescent initiation persisted into young adulthood and partially mediated the association between adolescent cannabis use and past-month cocaine, ecstasy, and cannabis use at age 22. Extent of cannabis initiation during young adulthood (from 19 to 22 years) had an indirect effect on psychotic symptoms at age 22 through thickness change in temporal areas. Results suggest that developmental timing of cannabis exposure may have a marked effect on neuroanatomical correlates of cannabis use as well as associated behavioral sequelae. Critically, this work provides a foundation for neurodevelopmentally informed models of cannabis exposure in humans.