Psilocybin desynchronizes the human brain.

A single dose of psilocybin, a psychedelic that acutely causes distortions of space-time perception and ego dissolution, produces rapid and persistent therapeutic effects in human clinical trials1-4. In animal models, psilocybin induces neuroplasticity in cortex and hippocampus5-8. It remains unclear how human brain network changes relate to subjective and lasting effects of psychedelics. Here we tracked individual-specific brain changes with longitudinal precision functional mapping (roughly 18 magnetic resonance imaging visits per participant). Healthy adults were tracked before, during and for 3 weeks after high-dose psilocybin (25 mg) and methylphenidate (40 mg), and brought back for an additional psilocybin dose 6-12 months later. Psilocybin massively disrupted functional connectivity (FC) in cortex and subcortex, acutely causing more than threefold greater change than methylphenidate. These FC changes were driven by brain desynchronization across spatial scales (areal, global), which dissolved network distinctions by reducing correlations within and anticorrelations between networks. Psilocybin-driven FC changes were strongest in the default mode network, which is connected to the anterior hippocampus and is thought to create our sense of space, time and self. Individual differences in FC changes were strongly linked to the subjective psychedelic experience. Performing a perceptual task reduced psilocybin-driven FC changes. Psilocybin caused persistent decrease in FC between the anterior hippocampus and default mode network, lasting for weeks. Persistent reduction of hippocampal-default mode network connectivity may represent a neuroanatomical and mechanistic correlate of the proplasticity and therapeutic effects of psychedelics.

A somato-cognitive action network alternates with effector regions in motor cortex.

Motor cortex (M1) has been thought to form a continuous somatotopic homunculus extending down the precentral gyrus from foot to face representations1,2, despite evidence for concentric functional zones3 and maps of complex actions4. Here, using precision functional magnetic resonance imaging (fMRI) methods, we find that the classic homunculus is interrupted by regions with distinct connectivity, structure and function, alternating with effector-specific (foot, hand and mouth) areas. These inter-effector regions exhibit decreased cortical thickness and strong functional connectivity to each other, as well as to the cingulo-opercular network (CON), critical for action5 and physiological control6, arousal7, errors8 and pain9. This interdigitation of action control-linked and motor effector regions was verified in the three largest fMRI datasets. Macaque and pediatric (newborn, infant and child) precision fMRI suggested cross-species homologues and developmental precursors of the inter-effector system. A battery of motor and action fMRI tasks documented concentric effector somatotopies, separated by the CON-linked inter-effector regions. The inter-effectors lacked movement specificity and co-activated during action planning (coordination of hands and feet) and axial body movement (such as of the abdomen or eyebrows). These results, together with previous studies demonstrating stimulation-evoked complex actions4 and connectivity to internal organs10 such as the adrenal medulla, suggest that M1 is punctuated by a system for whole-body action planning, the somato-cognitive action network (SCAN). In M1, two parallel systems intertwine, forming an integrate-isolate pattern: effector-specific regions (foot, hand and mouth) for isolating fine motor control and the SCAN for integrating goals, physiology and body movement.

Normalization of cerebral hemodynamics after hematopoietic stem cell transplant in children with sickle cell disease.

Children with sickle cell disease (SCD) demonstrate cerebral hemodynamic stress and are at high risk of strokes. We hypothesized that curative hematopoietic stem cell transplant (HSCT) normalizes cerebral hemodynamics in children with SCD compared with pre-transplant baseline. Whole-brain cerebral blood flow (CBF) and oxygen extraction fraction (OEF) were measured by magnetic resonance imaging 1 to 3 months before and 12 to 24 months after HSCT in 10 children with SCD. Three children had prior overt strokes, 5 children had prior silent strokes, and 1 child had abnormal transcranial Doppler ultrasound velocities. CBF and OEF of HSCT recipients were compared with non-SCD control participants and with SCD participants receiving chronic red blood cell transfusion therapy (CRTT) before and after a scheduled transfusion. Seven participants received matched sibling donor HSCT, and 3 participants received 8 out of 8 matched unrelated donor HSCT. All received reduced-intensity preparation and maintained engraftment, free of hemolytic anemia and SCD symptoms. Pre-transplant, CBF (93.5 mL/100 g/min) and OEF (36.8%) were elevated compared with non-SCD control participants, declining significantly 1 to 2 years after HSCT (CBF, 72.7 mL/100 g per minute; P = .004; OEF, 27.0%; P = .002), with post-HSCT CBF and OEF similar to non-SCD control participants. Furthermore, HSCT recipients demonstrated greater reduction in CBF (-19.4 mL/100 g/min) and OEF (-8.1%) after HSCT than children with SCD receiving CRTT after a scheduled transfusion (CBF, -0.9 mL/100 g/min; P = .024; OEF, -3.3%; P = .001). Curative HSCT normalizes whole-brain hemodynamics in children with SCD. This restoration of cerebral oxygen reserve may explain stroke protection after HSCT in this high-risk patient population.

Structure-function coupling in highly sampled individual brains.

Structural connectivity (SC) between distant regions of the brain support synchronized function known as functional connectivity (FC) and give rise to the large-scale brain networks that enable cognition and behavior. Understanding how SC enables FC is important to understand how injuries to SC may alter brain function and cognition. Previous work evaluating whole-brain SC-FC relationships showed that SC explained FC well in unimodal visual and motor areas, but only weakly in association areas, suggesting a unimodal-heteromodal gradient organization of SC-FC coupling. However, this work was conducted in group-averaged SC/FC data. Thus, it could not account for inter-individual variability in the locations of cortical areas and white matter tracts. We evaluated the correspondence of SC and FC within three highly sampled healthy participants. For each participant, we collected 78 min of diffusion-weighted MRI for SC and 360 min of resting state fMRI for FC. We found that FC was best explained by SC in visual and motor systems, as well as in anterior and posterior cingulate regions. A unimodal-to-heteromodal gradient could not fully explain SC-FC coupling. We conclude that the SC-FC coupling of the anterior-posterior cingulate circuit is more similar to unimodal areas than to heteromodal areas.

Prenatal exposure to maternal social disadvantage and psychosocial stress and neonatal white matter connectivity at birth.

Early life adversity (social disadvantage and psychosocial stressors) is associated with altered microstructure in fronto-limbic pathways important for socioemotional development. Understanding when these associations begin to emerge may inform the timing and design of preventative interventions. In this longitudinal study, 399 mothers were oversampled for low income and completed social background measures during pregnancy. Measures were analyzed with structural equation analysis resulting in two latent factors: social disadvantage (education, insurance status, income-to-needs ratio [INR], neighborhood deprivation, and nutrition) and psychosocial stress (depression, stress, life events, and racial discrimination). At birth, 289 healthy term-born neonates underwent a diffusion MRI (dMRI) scan. Mean diffusivity (MD) and fractional anisotropy (FA) were measured for the dorsal and inferior cingulum bundle (CB), uncinate, and fornix using probabilistic tractography in FSL. Social disadvantage and psychosocial stress were fitted to dMRI parameters using regression models adjusted for infant postmenstrual age at scan and sex. Social disadvantage, but not psychosocial stress, was independently associated with lower MD in the bilateral inferior CB and left uncinate, right fornix, and lower MD and higher FA in the right dorsal CB. Results persisted after accounting for maternal medical morbidities and prenatal drug exposure. In moderation analysis, psychosocial stress was associated with lower MD in the left inferior CB among the lower-to-higher socioeconomic status (SES) (INR ≥ 200%) group, but not the extremely low SES (INR < 200%) group. Increasing access to social welfare programs that reduce the burden of social disadvantage and related psychosocial stressors may be an important target to protect fetal brain development in fronto-limbic pathways.

Complexity organization of resting-state functional-MRI networks.

Entropy measures are increasingly being used to analyze the structure of neural activity observed by functional magnetic resonance imaging (fMRI), with resting-state networks (RSNs) being of interest for their reproducible descriptions of the brain's functional architecture. Temporal correlations have shown a dichotomy among these networks: those that engage with the environment, known as extrinsic, which include the visual and sensorimotor networks; and those associated with executive control and self-referencing, known as intrinsic, which include the default mode network and the frontoparietal control network. While these inter-voxel temporal correlations enable the assessment of synchrony among the components of individual networks, entropic measures introduce an intra-voxel assessment that quantifies signal features encoded within each blood oxygen level-dependent (BOLD) time series. As a result, this framework offers insights into comprehending the representation and processing of information within fMRI signals. Multiscale entropy (MSE) has been proposed as a useful measure for characterizing the entropy of neural activity across different temporal scales. This measure of temporal entropy in BOLD data is dependent on the length of the time series; thus, high-quality data with fine-grained temporal resolution and a sufficient number of time frames is needed to improve entropy precision. We apply MSE to the Midnight Scan Club, a highly sampled and well-characterized publicly available dataset, to analyze the entropy distribution of RSNs and evaluate its ability to distinguish between different functional networks. Entropy profiles are compared across temporal scales and RSNs. Our results have shown that the spatial distribution of entropy at infra-slow frequencies (0.005-0.1 Hz) reproduces known parcellations of RSNs. We found a complexity hierarchy between intrinsic and extrinsic RSNs, with intrinsic networks robustly exhibiting higher entropy than extrinsic networks. Finally, we found new evidence that the topography of entropy in the posterior cerebellum exhibits high levels of entropy comparable to that of intrinsic RSNs.

Structural Changes in Brain White Matter Tracts Associated With Overactive Bladder Revealed by Diffusion Tensor Magnetic Resonance Imaging: Findings From a Symptoms of Lower Urinary Tract Dysfunction Research Network Cross-Sectional Case-Control Study.

PURPOSE: Our objective was to investigate structural changes in brain white matter tracts using diffusion tensor imaging (DTI) in patients with overactive bladder (OAB). MATERIALS AND METHODS: Treatment-seeking OAB patients and matched controls enrolled in the cross-sectional case-control LURN (Symptoms of Lower Urinary Tract Dysfunction Research Network) Neuroimaging Study received a brain DTI scan. Microstructural integrity of brain white matter was assessed using fractional anisotropy (FA) and mean diffusivity. OAB and urgency urinary incontinence (UUI) symptoms were assessed using the OAB Questionnaire Short-Form and International Consultation on Incontinence Questionnaire-Urinary Incontinence. The Lower Urinary Tract Symptoms Tool UUI questions and responses were correlated with FA values. RESULTS: Among 221 participants with evaluable DTI data, 146 had OAB (66 urinary urgency-only without UUI, 80 with UUI); 75 were controls. Compared with controls, participants with OAB showed decreased FA and increased mean diffusivity, representing greater microstructural abnormalities of brain white matter tracts among OAB participants. These abnormalities occurred in the corpus callosum, bilateral anterior thalamic radiation and superior longitudinal fasciculus tracts, and bilateral insula and parahippocampal region. Among participants with OAB, higher OAB Questionnaire Short-Form scores were associated with decreased FA in the left inferior fronto-occipital fasciculus, P < .0001. DTI differences between OAB and controls were driven by the urinary urgency-only (OAB-dry) but not the UUI (OAB-wet) subgroup. CONCLUSIONS: Abnormalities in microstructural integrity in specific brain white matter tracts were more frequent in OAB patients. More severe OAB symptoms were correlated with greater degree of microstructural abnormalities in brain white matter tracts in patients with OAB. TRIAL REGISTRATION: ClinicalTrials.gov: NCT02485808.

Predicting post-surgical functional status in high-grade glioma with resting state fMRI and machine learning.

PURPOSE: High-grade glioma (HGG) is the most common and deadly malignant glioma of the central nervous system. The current standard of care includes surgical resection of the tumor, which can lead to functional and cognitive deficits. The aim of this study is to develop models capable of predicting functional outcomes in HGG patients before surgery, facilitating improved disease management and informed patient care. METHODS: Adult HGG patients (N = 102) from the neurosurgery brain tumor service at Washington University Medical Center were retrospectively recruited. All patients completed structural neuroimaging and resting state functional MRI prior to surgery. Demographics, measures of resting state network connectivity (FC), tumor location, and tumor volume were used to train a random forest classifier to predict functional outcomes based on Karnofsky Performance Status (KPS < 70, KPS ≥ 70). RESULTS: The models achieved a nested cross-validation accuracy of 94.1% and an AUC of 0.97 in classifying KPS. The strongest predictors identified by the model included FC between somatomotor, visual, auditory, and reward networks. Based on location, the relation of the tumor to dorsal attention, cingulo-opercular, and basal ganglia networks were strong predictors of KPS. Age was also a strong predictor. However, tumor volume was only a moderate predictor. CONCLUSION: The current work demonstrates the ability of machine learning to classify postoperative functional outcomes in HGG patients prior to surgery accurately. Our results suggest that both FC and the tumor's location in relation to specific networks can serve as reliable predictors of functional outcomes, leading to personalized therapeutic approaches tailored to individual patients.

Maturation of large-scale brain systems over the first month of life.

The period immediately after birth is a critical developmental window, capturing rapid maturation of brain structure and a child's earliest experiences. Large-scale brain systems are present at delivery, but how these brain systems mature during this narrow window (i.e. first weeks of life) marked by heightened neuroplasticity remains uncharted. Using multivariate pattern classification techniques and functional connectivity magnetic resonance imaging, we detected robust differences in brain systems related to age in newborns (n = 262; R2 = 0.51). Development over the first month of life occurred brain-wide, but differed and was more pronounced in brain systems previously characterized as developing early (i.e. sensorimotor networks) than in those characterized as developing late (i.e. association networks). The cingulo-opercular network was the only exception to this organizing principle, illuminating its early role in brain development. This study represents a step towards a normative brain "growth curve" that could be used to identify atypical brain maturation in infancy.

Parallel hippocampal-parietal circuits for self- and goal-oriented processing.

The hippocampus is critically important for a diverse range of cognitive processes, such as episodic memory, prospective memory, affective processing, and spatial navigation. Using individual-specific precision functional mapping of resting-state functional MRI data, we found the anterior hippocampus (head and body) to be preferentially functionally connected to the default mode network (DMN), as expected. The hippocampal tail, however, was strongly preferentially functionally connected to the parietal memory network (PMN), which supports goal-oriented cognition and stimulus recognition. This anterior-posterior dichotomy of resting-state functional connectivity was well-matched by differences in task deactivations and anatomical segmentations of the hippocampus. Task deactivations were localized to the hippocampal head and body (DMN), relatively sparing the tail (PMN). The functional dichotomization of the hippocampus into anterior DMN-connected and posterior PMN-connected parcels suggests parallel but distinct circuits between the hippocampus and medial parietal cortex for self- versus goal-oriented processing.

Predicting survival in glioblastoma with multimodal neuroimaging and machine learning.

PURPOSE: Glioblastoma (GBM) is the most common and aggressive malignant glioma, with an overall median survival of less than two years. The ability to predict survival before treatment in GBM patients would lead to improved disease management, clinical trial enrollment, and patient care. METHODS: GBM patients (N = 133, mean age 60.8 years, median survival 14.1 months, 57.9% male) were retrospectively recruited from the neurosurgery brain tumor service at Washington University Medical Center. All patients completed structural neuroimaging and resting state functional MRI (RS-fMRI) before surgery. Demographics, measures of cortical thickness (CT), and resting state functional network connectivity (FC) were used to train a deep neural network to classify patients based on survival (< 1y, 1-2y, >2y). Permutation feature importance identified the strongest predictors of survival based on the trained models. RESULTS: The models achieved a combined cross-validation and hold out accuracy of 90.6% in classifying survival (< 1y, 1-2y, >2y). The strongest demographic predictors were age at diagnosis and sex. The strongest CT predictors of survival included the superior temporal sulcus, parahippocampal gyrus, pericalcarine, pars triangularis, and middle temporal regions. The strongest FC features primarily involved dorsal and inferior somatomotor, visual, and cingulo-opercular networks. CONCLUSION: We demonstrate that machine learning can accurately classify survival in GBM patients based on multimodal neuroimaging before any surgical or medical intervention. These results were achieved without information regarding presentation symptoms, treatments, postsurgical outcomes, or tumor genomic information. Our results suggest GBMs have a global effect on the brain's structural and functional organization, which is predictive of survival.

Combined Cognitive Training and Vortioxetine Mitigates Age-Related Declines in Functional Brain Network Integrity.

OBJECTIVE: Age-related cognitive decline is common and potentially modifiable with cognitive training. Combining cognitive training with pro-cognitive medication offers an opportunity to modify brain networks to mitigate age-related cognitive decline. We tested the hypothesis that the efficacy of cognitive training could be amplified by combining it with vortioxetine, a pro-cognitive and pro-neuroplastic multimodal antidepressant. METHODS: We evaluated the effects of 6 months of computerized cognitive training plus vortioxetine (versus placebo) on resting state functional connectivity in older adults (age 65+) with age-related cognitive decline. We first evaluated the association of functional connectivity with age and cognitive performance (N = 66). Then we compared the effects of vortioxetine plus cognitive training versus placebo plus cognitive training on connectivity changes over the training period (n = 20). RESULTS: At baseline, greater age was significantly associated with lower within-network strength and network segregation, and poorer cognitive function. Cognitive training plus vortioxetine over 6 months positively impacted the relationship between age to mean network segregation. These effects were not observed in the placebo group. In contrast, vortioxetine did not modify the relationship of age to change in mean within-network strength. Exploratory analyses identified the cingulo-opercular network as the network most affected by cognitive training plus vortioxetine. CONCLUSION: This preliminary study provides evidence that combining cognitive training with pro-cognitive medication may modulate the effects of aging on functional brain networks. Results indicate that for older adults experiencing age-related cognitive decline, vortioxetine has a potentially beneficial effect on the correspondence between aging and functional brain network segregation. These results await replication in a larger sample.

Individual-specific functional connectivity of the amygdala: A substrate for precision psychiatry.

The amygdala is central to the pathophysiology of many psychiatric illnesses. An imprecise understanding of how the amygdala fits into the larger network organization of the human brain, however, limits our ability to create models of dysfunction in individual patients to guide personalized treatment. Therefore, we investigated the position of the amygdala and its functional subdivisions within the network organization of the brain in 10 highly sampled individuals (5 h of fMRI data per person). We characterized three functional subdivisions within the amygdala of each individual. We discovered that one subdivision is preferentially correlated with the default mode network; a second is preferentially correlated with the dorsal attention and fronto-parietal networks; and third subdivision does not have any networks to which it is preferentially correlated relative to the other two subdivisions. All three subdivisions are positively correlated with ventral attention and somatomotor networks and negatively correlated with salience and cingulo-opercular networks. These observations were replicated in an independent group dataset of 120 individuals. We also found substantial across-subject variation in the distribution and magnitude of amygdala functional connectivity with the cerebral cortex that related to individual differences in the stereotactic locations both of amygdala subdivisions and of cortical functional brain networks. Finally, using lag analyses, we found consistent temporal ordering of fMRI signals in the cortex relative to amygdala subdivisions. Altogether, this work provides a detailed framework of amygdala-cortical interactions that can be used as a foundation for models relating aberrations in amygdala connectivity to psychiatric symptoms in individual patients.

Accuracy and reliability of diffusion imaging models.

Diffusion imaging aims to non-invasively characterize the anatomy and integrity of the brain's white matter fibers. We evaluated the accuracy and reliability of commonly used diffusion imaging methods as a function of data quantity and analysis method, using both simulations and highly sampled individual-specific data (927-1442 diffusion weighted images [DWIs] per individual). Diffusion imaging methods that allow for crossing fibers (FSL's BedpostX [BPX], DSI Studio's Constant Solid Angle Q-Ball Imaging [CSA-QBI], MRtrix3's Constrained Spherical Deconvolution [CSD]) estimated excess fibers when insufficient data were present and/or when the data did not match the model priors. To reduce such overfitting, we developed a novel Bayesian Multi-tensor Model-selection (BaMM) method and applied it to the popular ball-and-stick model used in BedpostX within the FSL software package. BaMM was robust to overfitting and showed high reliability and the relatively best crossing-fiber accuracy with increasing amounts of diffusion data. Thus, sufficient data and an overfitting resistant analysis method enhance precision diffusion imaging. For potential clinical applications of diffusion imaging, such as neurosurgical planning and deep brain stimulation (DBS), the quantities of data required to achieve diffusion imaging reliability are lower than those needed for functional MRI.

Functional analysis of missense DARS2 variants in siblings with leukoencephalopathy with brain stem and spinal cord involvement and lactate elevation.

Biallelic pathogenic variants in the nuclear gene DARS2 (MIM# 610956), encoding the mitochondrial enzyme aspartyl-tRNA synthetase (MT-ASPRS) cause leukoencephalopathy with Brain Stem and Spinal Cord Involvement and Lactate Elevation (LBSL) (MIM# 611105), a neurometabolic disorder characterized by progressive ataxia, spasticity, developmental arrest or regression and characteristic brain MRI findings. Most patients exhibit a slowly progressive disease course with motor deterirartion that begins in childhood or adolescence, but can also occasionaly occur in adulthood. More severe LBSL presentations with atypical brain MRI findings have been recently described. Baker's yeast orthologue of DARS2, MSD1, is required for growth on oxidative carbon sources. A yeast with MSD1 knockout (msd1Δ) demonstrated a complete lack of oxidative growth which could be rescued by wild-type MSD1 but not MSD1 with pathogenic variants. Here we reported two siblings who exhibited developmental regression and ataxia with different age of onset and phenotypic severity. Exome sequencing revealed 2 compound heterozygous missense variants in DARS2: c.473A>T (p.Glu158Val) and c.829G>A (p.Glu277Lys); this variant combination has not been previously reported. The msd1Δ yeast transformed with plasmids expressing p.Glu259Lys, equivalent to human p.Glu277Lys, showed complete loss of oxidative growth and oxygen consumption, while the strain carrying p.Gln137Val, equivalent to human p.Glu158Val, showed a significant reduction of oxidative growth, but a residual ability to grow was retained. Structural analysis indicated that p.Glu158Val may interfere with protein binding of tRNAAsp, while p.Glu277Lys may impact both homodimerization and catalysis of MT-ASPRS. Our data illustrate the utility of yeast model and in silico analysis to determine pathogenicity of DARS2 variants, expand the genotypic spectrum and suggest intrafamilial variability in LBSL.

Deep learning resting state functional magnetic resonance imaging lateralization of temporal lobe epilepsy.

OBJECTIVE: Localization of focal epilepsy is critical for surgical treatment of refractory seizures. There remains a great need for noninvasive techniques to localize seizures for surgical decision-making. We investigate the use of deep learning using resting state functional magnetic resonance imaging (RS-fMRI) to identify the hemisphere of seizure onset in temporal lobe epilepsy (TLE) patients. METHODS: A total of 2132 healthy controls and 32 preoperative TLE patients were studied. All participants underwent structural MRI and RS-fMRI. Healthy control data were used to generate training samples for a three-dimensional convolutional neural network (3DCNN). RS-fMRI was synthetically altered in randomly lateralized regions in the healthy control participants. The model was then trained to classify the hemisphere containing synthetic noise. Finally, the model was tested on TLE patients to assess its performance for detecting biological seizure onset zones, and gradient-weighted class activation mapping (Grad-CAM) identified the strongest predictive regions. RESULTS: The 3DCNN classified healthy control hemispheres known to contain synthetic noise with 96% accuracy, and TLE hemispheres clinically identified to be seizure onset zones with 90.6% accuracy. Grad-CAM identified a range of temporal, frontal, parietal, and subcortical regions that were strong anatomical predictors of the seizure onset zone, and the resting state networks that colocalized with Grad-CAM results included default mode, medial temporal, and dorsal attention networks. Lastly, in an analysis of a subset of patients with postsurgical outcomes, the 3DCNN leveraged a more focal set of regions to achieve classification in patients with Engel Class >I compared to Engel Class I. SIGNIFICANCE: Noninvasive techniques capable of localizing the seizure onset zone could improve presurgical planning in patients with intractable epilepsy. We have demonstrated the ability of deep learning to identify the correct hemisphere of the seizure onset zone in TLE patients using RS-fMRI with high accuracy. This approach represents a novel technique of seizure lateralization that could improve preoperative surgical planning.

Effects of Mindfulness Training and Exercise on Cognitive Function in Older Adults: A Randomized Clinical Trial.

Importance: Episodic memory and executive function are essential aspects of cognitive functioning that decline with aging. This decline may be ameliorable with lifestyle interventions. Objective: To determine whether mindfulness-based stress reduction (MBSR), exercise, or a combination of both improve cognitive function in older adults. Design, Setting, and Participants: This 2 × 2 factorial randomized clinical trial was conducted at 2 US sites (Washington University in St Louis and University of California, San Diego). A total of 585 older adults (aged 65-84 y) with subjective cognitive concerns, but not dementia, were randomized (enrollment from November 19, 2015, to January 23, 2019; final follow-up on March 16, 2020). Interventions: Participants were randomized to undergo the following interventions: MBSR with a target of 60 minutes daily of meditation (n = 150); exercise with aerobic, strength, and functional components with a target of at least 300 minutes weekly (n = 138); combined MBSR and exercise (n = 144); or a health education control group (n = 153). Interventions lasted 18 months and consisted of group-based classes and home practice. Main Outcomes and Measures: The 2 primary outcomes were composites of episodic memory and executive function (standardized to a mean [SD] of 0 [1]; higher composite scores indicate better cognitive performance) from neuropsychological testing; the primary end point was 6 months and the secondary end point was 18 months. There were 5 reported secondary outcomes: hippocampal volume and dorsolateral prefrontal cortex thickness and surface area from structural magnetic resonance imaging and functional cognitive capacity and self-reported cognitive concerns. Results: Among 585 randomized participants (mean age, 71.5 years; 424 [72.5%] women), 568 (97.1%) completed 6 months in the trial and 475 (81.2%) completed 18 months. At 6 months, there was no significant effect of mindfulness training or exercise on episodic memory (MBSR vs no MBSR: 0.44 vs 0.48; mean difference, -0.04 points [95% CI, -0.15 to 0.07]; P = .50; exercise vs no exercise: 0.49 vs 0.42; difference, 0.07 [95% CI, -0.04 to 0.17]; P = .23) or executive function (MBSR vs no MBSR: 0.39 vs 0.31; mean difference, 0.08 points [95% CI, -0.02 to 0.19]; P = .12; exercise vs no exercise: 0.39 vs 0.32; difference, 0.07 [95% CI, -0.03 to 0.18]; P = .17) and there were no intervention effects at the secondary end point of 18 months. There was no significant interaction between mindfulness training and exercise (P = .93 for memory and P = .29 for executive function) at 6 months. Of the 5 prespecified secondary outcomes, none showed a significant improvement with either intervention compared with those not receiving the intervention. Conclusions and Relevance: Among older adults with subjective cognitive concerns, mindfulness training, exercise, or both did not result in significant differences in improvement in episodic memory or executive function at 6 months. The findings do not support the use of these interventions for improving cognition in older adults with subjective cognitive concerns. Trial Registration: ClinicalTrials.gov Identifier: NCT02665481.

Functional Connectivity Decreases with Metabolic Stress in Sickle Cell Disease.

OBJECTIVE: Children with sickle cell disease (SCD) experience cognitive deficits even when unaffected by stroke. Using functional connectivity magnetic resonance imaging (MRI) as a potential biomarker of cognitive function, we tested our hypothesis that children with SCD would have decreased functional connectivity, and that children experiencing the greatest metabolic stress, indicated by elevated oxygen extraction fraction, would have the lowest connectivity. METHODS: We prospectively obtained brain MRIs and cognitive testing in healthy controls and children with SCD. RESULTS: We analyzed data from 60 participants (20 controls and 40 with sickle cell disease). There was no difference in global cognition or cognitive subdomains between cohorts. However, we found decreased functional connectivity within the sensory-motor, lateral sensory-motor, auditory, salience, and subcortical networks in participants with SCD compared with controls. Further, as white matter oxygen extraction fraction increased, connectivity within the visual (p = 0.008, parameter estimate = -0.760 [95% CI = -1.297, -0.224]), default mode (p = 0.012, parameter estimate = -0.417 [95% CI = -0.731, -0.104]), and cingulo-opercular (p = 0.009, parameter estimate = -0.883 [95% CI = -1.517, -0.250]) networks decreased. INTERPRETATION: We conclude that there is diminished functional connectivity within these anatomically contiguous networks in children with SCD compared with controls, even when differences are not seen with cognitive testing. Increased white matter oxygen extraction fraction was associated with decreased connectivity in select networks. These data suggest that elevated oxygen extraction fraction and disrupted functional connectivity are potentially presymptomatic neuroimaging biomarkers for cognitive decline in SCD. ANN NEUROL 2020;88:995-1008.

Hydroxyurea reduces cerebral metabolic stress in patients with sickle cell anemia.

Chronic transfusion therapy (CTT) prevents stroke in selected patients with sickle cell anemia (SCA). We have shown that CTT mitigates signatures of cerebral metabolic stress, reflected by elevated oxygen extraction fraction (OEF), which likely drives stroke risk reduction. The region of highest OEF falls within the border zone, where cerebral blood flow (CBF) nadirs; OEF in this region was reduced after CTT. The neuroprotective efficacy of hydroxyurea (HU) remains unclear. To test our hypothesis that patients receiving HU therapy have lower cerebral metabolic stress compared with patients not receiving disease-modifying therapy, we prospectively obtained brain magnetic resonance imaging scans with voxel-wise measurements of CBF and OEF in 84 participants with SCA who were grouped by therapy: no disease-modifying therapy, HU, or CTT. There was no difference in whole-brain CBF among the 3 cohorts (P = .148). However, whole-brain OEF was significantly different (P < .001): participants without disease-modifying therapy had the highest OEF (median 42.9% [interquartile range (IQR) 39.1%-49.1%]), followed by HU treatment (median 40.7% [IQR 34.9%-43.6%]), whereas CTT treatment had the lowest values (median 35.3% [IQR 32.2%-38.9%]). Moreover, the percentage of white matter at highest risk for ischemia, defined by OEF greater than 40% and 42.5%, was lower in the HU cohort compared with the untreated cohort (P = .025 and P = .034 respectively), but higher compared with the CTT cohort (P = .018 and P = .029 respectively). We conclude that HU may offer neuroprotection by mitigating cerebral metabolic stress in patients with SCA, but not to the same degree as CTT.

Surgery requiring general anesthesia in preterm infants is associated with altered brain volumes at term equivalent age and neurodevelopmental impairment.

BACKGROUND: The aim of the study was to describe and contrast the brain development and outcome among very preterm infants that were and were not exposed to surgery requiring general anesthesia prior to term equivalent age (TEA). METHODS: Preterm infants born ≤30 weeks' gestation who did (n = 25) and did not (n = 59) have surgery requiring general anesthesia during the preterm period were studied. At TEA, infants had MRI scans performed with measures of brain tissue volumes, cortical surface area, Gyrification Index, and white matter microstructure. Neurodevelopmental follow-up with the Bayley Scales of Infant and Toddler Development, Third Edition was undertaken at 2 years of corrected age. Multivariate models, adjusted for clinical and social risk factors, were used to compare the groups. RESULTS: After controlling for clinical and social variables, preterm infants exposed to surgical anesthesia demonstrated decreased relative white matter volumes at TEA and lower cognitive and motor composite scores at 2-year follow-up. Those with longer surgical exposure demonstrated the greatest decrease in white matter volumes and lower cognitive and motor outcomes at age 2 years. CONCLUSIONS: Very preterm infants who required surgery during the preterm period had lower white mater volumes at TEA and worse neurodevelopmental outcome at age 2 years. IMPACT: In very preterm infants, there is an association between surgery requiring general anesthesia during the preterm period and reduced white mater volume on MRI at TEA and lower cognitive and motor composite scores at age 2 years. It is known that the very preterm infant's brain undergoes rapid growth during the period corresponding to the third trimester. The current study suggests an association between surgery requiring general anesthesia during this period and worse outcomes.