White matter degeneration revealed by fiber‐specific analysis relates to recovery of hand function after stroke

Recent developments of higher‐order diffusion‐weighted imaging models have enabled the estimation of specific white matter fiber populations within a voxel, addressing limitations of traditional imaging markers of white matter integrity. We applied fixel based analysis (FBA) to investigate the evolution of fiber‐specific white matter changes in a prospective study of stroke patients and upper limb motor deficit over 1 year after stroke. We studied differences in fiber density and macrostructural changes in fiber cross‐section. Motor function was assessed by grip strength. We conducted a whole‐brain analysis of fixel metrics and predefined corticospinal tract (CST) region of interest in relation to changes in motor functions. In 30 stroke patients (mean age 62.3 years, SD ±16.9; median NIHSS 4, IQR 2–5), whole‐brain FBA revealed progressing loss of fiber density and cross‐section in the ipsilesional corticospinal tract and long‐range fiber tracts such as the superior longitudinal fascicle and trans‐callosal tracts extending towards contralesional white matter tracts. Lower FBA metrics measured at the brainstem section of the CST 1 month after stroke were significantly associated with lower grip strength 3 months (p = .009, adjusted R ² = 0.259) and 1 year (T4: p < .001, adj. R ² = 0.515) after stroke. Compared to FA, FBA metrics showed a comparably strong association with grip strength at later time points. Using FBA, we demonstrate progressive fiber‐specific white matter loss after stroke and association with functional motor outcome. Our results promote the application of fiber‐specific analysis to detect secondary neurodegeneration after stroke in relation to clinical recovery.     

Coherent neural oscillations inform early stroke motor recovery

Neural oscillations may contain important information pertaining to stroke rehabilitation. This study examined the predictive performance of electroencephalography‐derived neural oscillations following stroke using a data‐driven approach. Individuals with stroke admitted to an inpatient rehabilitation facility completed a resting‐state electroencephalography recording and structural neuroimaging around the time of admission and motor testing at admission and discharge. Using a lasso regression model with cross‐validation, we determined the extent of motor recovery (admission to discharge change in Functional Independence Measurement motor subscale score) prediction from electroencephalography, baseline motor status, and corticospinal tract injury. In 27 participants, coherence in a 1–30 Hz band between leads overlying ipsilesional primary motor cortex and 16 leads over bilateral hemispheres predicted 61.8% of the variance in motor recovery. High beta (20–30 Hz) and alpha (8–12 Hz) frequencies contributed most to the model demonstrating both positive and negative associations with motor recovery, including high beta leads in supplementary motor areas and ipsilesional ventral premotor and parietal regions and alpha leads overlying contralesional temporal–parietal and ipsilesional parietal regions. Electroencephalography power, baseline motor status, and corticospinal tract injury did not significantly predict motor recovery during hospitalization (R ² = 0–6.2%). Findings underscore the relevance of oscillatory synchronization in early stroke rehabilitation while highlighting contributions from beta and alpha frequency bands and frontal, parietal, and temporal–parietal regions overlooked by traditional hypothesis‐driven prediction models.     

Early motor network connectivity after stroke: An interplay of general reorganization and state‐specific compensation

Motor recovery after stroke relies on functional reorganization of the motor network, which is commonly assessed via functional magnetic resonance imaging (fMRI)‐based resting‐state functional connectivity (rsFC) or task‐related effective connectivity (trEC). Measures of either connectivity mode have been shown to successfully explain motor impairment post‐stroke, posing the question whether motor impairment is more closely reflected by rsFC or trEC. Moreover, highly similar changes in ipsilesional and interhemispheric motor network connectivity have been reported for both rsFC and trEC after stroke, suggesting that altered rsFC and trEC may capture similar aspects of information integration in the motor network reflecting principle, state‐independent mechanisms of network reorganization rather than state‐specific compensation strategies. To address this question, we conducted the first direct comparison of rsFC and trEC in a sample of early subacute stroke patients (n = 26, included on average 7.3 days post‐stroke). We found that both rsFC and trEC explained motor impairment across patients, stressing the clinical potential of fMRI‐based connectivity. Importantly, intrahemispheric connectivity between ipsilesional M1 and premotor areas depended on the activation state, whereas interhemispheric connectivity between homologs was state‐independent. From a mechanistic perspective, our results may thus arise from two distinct aspects of motor network plasticity: task‐specific compensation within the ipsilesional hemisphere and a more fundamental form of reorganization between hemispheres.     

Mutation‐related magnetization‐transfer,not axon density,drives white matter differences in premanifest Huntington disease: Evidence from in vivo ultra‐strong gradient MRI

White matter (WM) alterations have been observed in Huntington disease (HD) but their role in the disease‐pathophysiology remains unknown. We assessed WM changes in premanifest HD by exploiting ultra‐strong‐gradient magnetic resonance imaging (MRI). This allowed to separately quantify magnetization transfer ratio (MTR) and hindered and restricted diffusion‐weighted signal fractions, and assess how they drove WM microstructure differences between patients and controls. We used tractometry to investigate region‐specific alterations across callosal segments with well‐characterized early‐ and late‐myelinating axon populations, while brain‐wise differences were explored with tract‐based cluster analysis (TBCA). Behavioral measures were included to explore disease‐associated brain‐function relationships. We detected lower MTR in patients'' callosal rostrum (tractometry: p = .03; TBCA: p = .03), but higher MTR in their splenium (tractometry: p = .02). Importantly, patients'' mutation‐size and MTR were positively correlated (all p‐values < .01), indicating that MTR alterations may directly result from the mutation. Further, MTR was higher in younger, but lower in older patients relative to controls (p = .003), suggesting that MTR increases are detrimental later in the disease. Finally, patients showed higher restricted diffusion signal fraction (FR) from the composite hindered and restricted model of diffusion (CHARMED) in the cortico‐spinal tract (p = .03), which correlated positively with MTR in the posterior callosum (p = .033), potentially reflecting compensatory mechanisms. In summary, this first comprehensive, ultra‐strong gradient MRI study in HD provides novel evidence of mutation‐driven MTR alterations at the premanifest disease stage which may reflect neurodevelopmental changes in iron, myelin, or a combination of these.     

Intermittent theta burst stimulation over the parietal cortex has a significant neural effect on working memory

The crucial role of the parietal cortex in working memory (WM) storage has been identified by fMRI studies. However, it remains unknown whether repeated parietal intermittent theta‐burst stimulation (iTBS) can improve WM. In this within‐subject randomized controlled study, under the guidance of fMRI‐identified parietal activation in the left hemisphere, 22 healthy adults received real and sham iTBS sessions (five consecutive days, 600 pulses per day for each session) with an interval of 9 months between the two sessions. Electroencephalography signals of each subject before and after both iTBS sessions were collected during a change detection task. Changes in contralateral delay activity (CDA) and K‐score were then calculated to reflect neural and behavioral WM improvement. Repeated‐measures ANOVA suggested that real iTBS increased CDA more than the sham one (p = .011 for iTBS effect). Further analysis showed that this effect was more significant in the left hemisphere than in the right hemisphere (p = .029 for the hemisphere‐by‐iTBS interaction effect). Pearson correlation analyses showed significant correlations for two conditions between CDA changes in the left hemisphere and K score changes (ps <.05). In terms of the behavioral results, significant K score changes after real iTBS were observed for two conditions, but a repeated‐measures ANOVA showed a nonsignificant main effect of iTBS (p = .826). These results indicate that the current iTBS protocol is a promising way to improve WM capability based on the neural indicator (CDA) but further optimization is needed to produce a behavioral effect.     

Intracranial and subcortical volumes in adolescents with early‐onset psychosis: A multisite mega‐analysis from the ENIGMA consortium

Early‐onset psychosis disorders are serious mental disorders arising before the age of 18 years. Here, we investigate the largest neuroimaging dataset, to date, of patients with early‐onset psychosis and healthy controls for differences in intracranial and subcortical brain volumes. The sample included 263 patients with early‐onset psychosis (mean age: 16.4 ± 1.4 years, mean illness duration: 1.5 ± 1.4 years, 39.2% female) and 359 healthy controls (mean age: 15.9 ± 1.7 years, 45.4% female) with magnetic resonance imaging data, pooled from 11 clinical cohorts. Patients were diagnosed with early‐onset schizophrenia (n = 183), affective psychosis (n = 39), or other psychotic disorders (n = 41). We used linear mixed‐effects models to investigate differences in intracranial and subcortical volumes across the patient sample, diagnostic subgroup and antipsychotic medication, relative to controls. We observed significantly lower intracranial (Cohen''s d = −0.39) and hippocampal (d = −0.25) volumes, and higher caudate (d = 0.25) and pallidum (d = 0.24) volumes in patients relative to controls. Intracranial volume was lower in both early‐onset schizophrenia (d = −0.34) and affective psychosis (d = −0.42), and early‐onset schizophrenia showed lower hippocampal (d = −0.24) and higher pallidum (d = 0.29) volumes. Patients who were currently treated with antipsychotic medication (n = 193) had significantly lower intracranial volume (d = −0.42). The findings demonstrate a similar pattern of brain alterations in early‐onset psychosis as previously reported in adult psychosis, but with notably low intracranial volume. The low intracranial volume suggests disrupted neurodevelopment in adolescent early‐onset psychosis.     

Physiological instability is linked to mortality in primary central nervous system lymphoma: A case–control fMRI study

Primary central nervous system lymphoma (PCNSL) is an aggressive brain disease where lymphocytes invade along perivascular spaces of arteries and veins. The invasion markedly changes (peri)vascular structures but its effect on physiological brain pulsations has not been previously studied. Using physiological magnetic resonance encephalography (MREG_BOLD) scanning, this study aims to quantify the extent to which (peri)vascular PCNSL involvement alters the stability of physiological brain pulsations mediated by cerebral vasculature. Clinical implications and relevance were explored. In this study, 21 PCNSL patients (median 67y; 38% females) and 30 healthy age‐matched controls (median 63y; 73% females) were scanned for MREG_BOLD signal during 2018–2021. Motion effects were removed. Voxel‐by‐voxel Coefficient of Variation (CV) maps of MREG_BOLD signal was calculated to examine the stability of physiological brain pulsations. Group‐level differences in CV were examined using nonparametric covariate‐adjusted tests. Subject‐level CV alterations were examined against control population Z‐score maps wherein clusters of increased CV values were detected. Spatial distributions of clusters and findings from routine clinical neuroimaging were compared [contrast‐enhanced, diffusion‐weighted, fluid‐attenuated inversion recovery (FLAIR) data]. Whole‐brain mean CV was linked to short‐term mortality with 100% sensitivity and 100% specificity, as all deceased patients revealed higher values (n = 5, median 0.055) than surviving patients (n = 16, median 0.028) (p < .0001). After adjusting for medication, head motion, and age, patients revealed higher CV values (group median 0.035) than healthy controls (group median 0.024) around arterial territories (p ≤ .001). Abnormal clusters (median 1.10 × 10⁵mm³) extended spatially beyond FLAIR lesions (median 0.62 × 10⁵mm³) with differences in volumes (p = .0055).     

Identifying a whole‐brain connectome‐based model in drug‐naïve Parkinson's disease for predicting motor impairment

Identifying a whole‐brain connectome‐based predictive model in drug‐naïve patients with Parkinson''s disease and verifying its predictions on drug‐managed patients would be useful in determining the intrinsic functional underpinnings of motor impairment and establishing general brain–behavior associations. In this study, we constructed a predictive model from the resting‐state functional data of 47 drug‐naïve patients by using a connectome‐based approach. This model was subsequently validated in 115 drug‐managed patients. The severity of motor impairment was assessed by calculating Unified Parkinson''s Disease Rating Scale Part III scores. The predictive performance of model was evaluated using the correlation coefficient (r _true) between predicted and observed scores. As a result, a connectome‐based model for predicting individual motor impairment in drug‐naïve patients was identified with significant performance (r _true = .845, p < .001, p _permu = .002). Two patterns of connection were identified according to correlations between connection strength and the severity of motor impairment. The negative motor‐impairment‐related network contained more within‐network connections in the motor, visual‐related, and default mode networks, whereas the positive motor‐impairment‐related network was constructed mostly with between‐network connections coupling the motor‐visual, motor‐limbic, and motor‐basal ganglia networks. Finally, this predictive model constructed around drug‐naïve patients was confirmed with significant predictive efficacy on drug‐managed patients (r = .209, p = .025), suggesting a generalizability in Parkinson''s disease patients under long‐term drug influence. In conclusion, this study identified a whole‐brain connectome‐based model that could predict the severity of motor impairment in Parkinson''s patients and furthers our understanding of the functional underpinnings of the disease.     

Deep transfer learning of structural magnetic resonance imaging fused with blood parameters improves brain age prediction

Machine learning has been applied to neuroimaging data for estimating brain age and capturing early cognitive impairment in neurodegenerative diseases. Blood parameters like neurofilament light chain are associated with aging. In order to improve brain age predictive accuracy, we constructed a model based on both brain structural magnetic resonance imaging (sMRI) and blood parameters. Healthy subjects (n = 93; 37 males; aged 50–85 years) were recruited. A deep learning network was firstly pretrained on a large set of MRI scans (n = 1,481; 659 males; aged 50–85 years) downloaded from multiple open‐source datasets, to provide weights on our recruited dataset. Evaluating the network on the recruited dataset resulted in mean absolute error (MAE) of 4.91 years and a high correlation (r = .67, p <.001) against chronological age. The sMRI data were then combined with five blood biochemical indicators including GLU, TG, TC, ApoA1 and ApoB, and 9 dementia‐associated biomarkers including ApoE genotype, HCY, NFL, TREM2, Aβ40, Aβ42, T‐tau, TIMP1, and VLDLR to construct a bilinear fusion model, which achieved a more accurate prediction of brain age (MAE, 3.96 years; r = .76, p <.001). Notably, the fusion model achieved better improvement in the group of older subjects (70–85 years). Extracted attention maps of the network showed that amygdala, pallidum, and olfactory were effective for age estimation. Mediation analysis further showed that brain structural features and blood parameters provided independent and significant impact. The constructed age prediction model may have promising potential in evaluation of brain health based on MRI and blood parameters.     

Financial decision‐making and self‐awareness for financial decision‐making is associated with white matter integrity in older adults

Financial decision‐making (FDM) and awareness of the integrity of one''s FDM abilities (or financial awareness) are both critical for preventing financial mistakes. We examined the white matter correlates of these constructs and hypothesized that the tracts connecting the temporal–frontal regions would be most strongly correlated with both FDM and financial awareness. Overall, 49 healthy older adults were included in the FDM analysis and 44 in the financial awareness analyses. The Objective Financial Competency Assessment Inventory was used to measure FDM. Financial awareness was measured by integrating metacognitive ratings into this inventory and was calculated as the degree of overconfidence or underconfidence. Diffusion tensor imaging data were processed with Tracts Constrained by Underlying Anatomy distributed as part of the FreeSurfer analytic suite, which produced average measures of fractional anisotropy and mean diffusivity in 18 white matter tracts along with the overall tract average. As expected, FDM showed the strongest negative associations with average mean diffusivity measure of the superior longitudinal fasciculus ‐temporal (SLFT; r = −.360, p = .011) and ‐parietal (r = −.351, p = .014) tracts. After adjusting for FDM, only the association between financial awareness and average mean diffusivity measure of the right SLFT (r = .310, p = .046) was significant. Overlapping white matter tracts were involved in both FDM and financial awareness. More importantly, these preliminary findings reinforce emerging literature on a unique role of right hemisphere temporal connections in supporting financial awareness.     

Task‐related neural mechanisms of persecutory ideation in schizophrenia and community monozygotic twin‐pairs

Perceptions of spiteful behavior are common, distinct from rational fear, and may undergird persecutory ideation. To test this hypothesis and investigate neural mechanisms of persecutory ideation, we employed a novel economic social decision‐making task, the Minnesota Trust Game (MTG), during neuroimaging in patients with schizophrenia (n = 30) and community monozygotic (MZ) twins (n = 38; 19 pairs). We examined distinct forms of mistrust, task‐related brain activation and connectivity, and investigated relationships with persecutory ideation. We tested whether co‐twin discordance on these measurements was correlated to reflect a common source of underlying variance. Across samples persecutory ideation was associated with reduced trust only during the suspiciousness condition, which assessed spite sensitivity given partners had no monetary incentive to betray. Task‐based activation contrasts for specific forms of mistrust were limited and unrelated to persecutory ideation. However, task‐based connectivity contrasts revealed a dorsal cingulate anterior insula network sensitive to suspicious mistrust, a left frontal–parietal (lF‐P) network sensitive to rational mistrust, and a ventral medial/orbital prefrontal (vmPFC/OFC) network that was sensitive to the difference between these forms of mistrust (all p < .005). Higher persecutory ideation was predicted only by reduced connectivity between the vmPFC/OFC and lF‐P networks (p = .005), which was only observed when the intentions of the other player were relevant. Moreover, co‐twin differences in persecutory ideation predicted co‐twin differences in both spite sensitivity and in vmPFC/OFC–lF‐P connectivity. This work found that interconnectivity may be particularly important to the complex neurobiology underlying persecutory ideation, and that unique environmental variance causally linked persecutory ideation, decision‐making, and brain connectivity.     

Pre‐supplementary motor network connectivity and clinical outcome of magnetic stimulation in obsessive–compulsive disorder

A large proportion of patients with obsessive–compulsive disorder (OCD) respond unsatisfactorily to pharmacological and psychological treatments. An alternative novel treatment for these patients is repetitive transcranial magnetic stimulation (rTMS). This study aimed to investigate the underlying neural mechanism of rTMS treatment in OCD patients. A total of 37 patients with OCD were randomized to receive real or sham 1‐Hz rTMS (14 days, 30 min/day) over the right pre‐supplementary motor area (preSMA). Resting‐state functional magnetic resonance imaging data were collected before and after rTMS treatment. The individualized target was defined by a personalized functional connectivity map of the subthalamic nucleus. After treatment, patients in the real group showed a better improvement in the Yale–Brown Obsessive Compulsive Scale than the sham group (F _1,35 = 6.0, p = .019). To show the neural mechanism involved, we identified an “ideal target connectivity” before treatment. Leave‐one‐out cross‐validation indicated that this connectivity pattern can significantly predict patients'' symptom improvements (r = .60, p = .009). After real treatment, the average connectivity strength of the target network significantly decreased in the real but not in the sham group. This network‐level change was cross‐validated in three independent datasets. Altogether, these findings suggest that personalized magnetic stimulation on preSMA may alleviate obsessive–compulsive symptoms by decreasing the connectivity strength of the target network.     

Improving the efficacy and reliability of rTMS language mapping by increasing the stimulation frequency

Repetitive TMS (rTMS) with a frequency of 5–10 Hz is widely used for language mapping. However, it may be accompanied by discomfort and is limited in the number and reliability of evoked language errors. We, here, systematically tested the influence of different stimulation frequencies (i.e., 10, 30, and 50 Hz) on tolerability, number, reliability, and cortical distribution of language errors aiming at improved language mapping. 15 right‐handed, healthy subjects (m = 8, median age: 29 yrs) were investigated in two sessions, separated by 2–5 days. In each session, 10, 30, and 50 Hz rTMS were applied over the left hemisphere in a randomized order during a picture naming task. Overall, 30 Hz rTMS evoked significantly more errors (20 ± 12%) compared to 50 Hz (12 ± 8%; p <.01), whereas error rates were comparable between 30/50 and 10 Hz (18 ± 11%). Across all conditions, a significantly higher error rate was found in Session 1 (19 ± 13%) compared to Session 2 (13 ± 7%, p <.05). The error rate was poorly reliable between sessions for 10 (intraclass correlation coefficient, ICC = .315) and 30 Hz (ICC = .427), whereas 50 Hz showed a moderate reliability (ICC = .597). Spatial reliability of language errors was low to moderate with a tendency toward increased reliability for higher frequencies, for example, within frontal regions. Compared to 10 Hz, both, 30 and 50 Hz were rated as less painful. Taken together, our data favor the use of rTMS‐protocols employing higher frequencies for evoking language errors reliably and with reduced discomfort, depending on the region of interest.     

Spectroscopy of reperfused tissue after stroke reveals heightened metabolism in patients with good clinical outcomes

The aim of acute stroke treatment is to reperfuse the penumbra. However, not all posttreatment reperfusion is associated with a good outcome. Recent arterial spin labeling (ASL) studies suggest that patients with hyperperfusion after treatment have a better clinical recovery. This study aimed to determine whether there was a distinctive magnetic resonance spectroscopy (MRS) metabolite profile in hyperperfused tissue after stroke reperfusion therapy. We studied 77 ischemic stroke patients 24 hours after treatment using MRS (single voxel spectroscopy, point resolved spectroscopy, echo time 30 ms), ASL, and diffusion-weighted imaging (DWI). Magnetic resonance spectroscopy voxels were placed in cortical tissue that was penumbral on baseline perfusion imaging but had reperfused at 24 hours (and did not progress to infarction). Additionally, 20 healthy age matched controls underwent MRS. In all, 24 patients had hyperperfusion; 36 had reperfused penumbra without hyperperfusion, and 17 were excluded due to no reperfusion. Hyperperfusion was significantly related to better 3-month clinical outcome compared with patients without hyperperfusion (P=0.007). Patients with hyperperfusion showed increased glutamate (P<0.001), increased N-Acetylaspartate (NAA) (P=0.038), and increased lactate (P<0.002) in reperfused tissue compared with contralateral tissue and healthy controls. Hyperperfused tissue has a characteristic metabolite signature, suggesting that it is more metabolically active and perhaps more capable of later neuroplasticity.     

The sexual brain,genes, and cognition: A machine‐predicted brain sex score explains individual differences in cognitive intelligence and genetic influence in young children

Sex impacts the development of the brain and cognition differently across individuals. However, the literature on brain sex dimorphism in humans is mixed. We aim to investigate the biological underpinnings of the individual variability of sexual dimorphism in the brain and its impact on cognitive performance. To this end, we tested whether the individual difference in brain sex would be linked to that in cognitive performance that is influenced by genetic factors in prepubertal children (N = 9,658, ages 9–10 years old; the Adolescent Brain Cognitive Development study). To capture the interindividual variability of the brain, we estimated the probability of being male or female based on the brain morphometry and connectivity features using machine learning (herein called a brain sex score). The models accurately classified the biological sex with a test ROC–AUC of 93.32%. As a result, a greater brain sex score correlated significantly with greater intelligence (p _fdr < .001, ηp2 = .011–.034; adjusted for covariates) and higher cognitive genome‐wide polygenic scores (GPSs) (p _fdr < .001, ηp2 < .005). Structural equation models revealed that the GPS‐intelligence association was significantly modulated by the brain sex score, such that a brain with a higher maleness score (or a lower femaleness score) mediated a positive GPS effect on intelligence (indirect effects = .006–.009; p = .002–.022; sex‐stratified analysis). The finding of the sex modulatory effect on the gene–brain–cognition relationship presents a likely biological pathway to the individual and sex differences in the brain and cognitive performance in preadolescence.     

Increasing nodal vulnerability and nodal efficiency implied recovery time prolonging in patients with supplementary motor area syndrome

Supplementary motor area (SMA) syndrome is a surgery‐related complication that commonly occurs after removing SMA glioma, and needs weeks to recover. However, susceptible factors of patients suffering from SMA syndrome remain unknown. Graphic theory was applied to reveal topological properties of sensorimotor network (SMN) by processing resting‐state functional magnetic resonance images in 66 patients with SMA gliomas. Patients were classified into SMA and non‐SMA groups based on whether they suffered from SMA syndrome. We collected recovery time and used causal mediation analysis to find association between topological properties and recovery time. Compared with the non‐SMA group, higher vulnerability (left: p = .0018; right: p = .0033) and lower fault tolerance (left: p = .0022; right: p = .0248) of the whole SMN were found in the SMA group. Moreover, higher nodal properties of lesional‐hemispheric cingulate cortex (nodal efficiency: left, p = .0389; right, p = .0169; nodal vulnerability: left, p = .0185; right, p = .0085) and upper limb region of primary motor cortex (PMC; nodal efficiency: left, p = .0132; right, p = .0001; nodal vulnerability: left, p = .0091; right, p = .0209) were found in the SMA group. Nodal efficiency and nodal vulnerability of cingulate cortex and upper limb region of PMC were important predictors for SMA syndrome occurring and recovery time prolonging. Neurosurgeons should carefully deal with upper limb region of PMC and cingulate cortex, and protect them if these two region were unnecessary to damage during SMA glioma resection.     

The additive impact of cardio‐metabolic disorders and psychiatric illnesses on accelerated brain aging

Severe mental illnesses (SMI) including major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia spectrum disorder (SSD) elevate accelerated brain aging risks. Cardio‐metabolic disorders (CMD) are common comorbidities in SMI and negatively impact brain health. We validated a linear quantile regression index (QRI) approach against the machine learning “BrainAge” index in an independent SSD cohort (N = 206). We tested the direct and additive effects of SMI and CMD effects on accelerated brain aging in the N = 1,618 (604 M/1,014 F, average age = 63.53 ± 7.38) subjects with SMI and N = 11,849 (5,719 M/6,130 F; 64.42 ± 7.38) controls from the UK Biobank. Subjects were subdivided based on diagnostic status: SMI+/CMD+ (N = 665), SMI+/CMD− (N = 964), SMI−/CMD+ (N = 3,765), SMI−/CMD− (N = 8,083). SMI (F = 40.47, p = 2.06 × 10⁻¹⁰) and CMD (F = 24.69, p = 6.82 × 10⁻⁷) significantly, independently impacted whole‐brain QRI in SMI+. SSD had the largest effect (Cohen’s d = 1.42) then BD (d = 0.55), and MDD (d = 0.15). Hypertension had a significant effect on SMI+ (d = 0.19) and SMI− (d = 0.14). SMI effects were direct, independent of MD, and remained significant after correcting for effects of antipsychotic medications. Whole‐brain QRI was significantly (p < 10⁻¹⁶) associated with the volume of white matter hyperintensities (WMH). However, WMH did not show significant association with SMI and was driven by CMD, chiefly hypertension (p < 10⁻¹⁶). We used a simple and robust index, QRI, the demonstrate additive effect of SMI and CMD on accelerated brain aging. We showed a greater effect of psychiatric illnesses on QRI compared to cardio‐metabolic illness. Our findings suggest that subjects with SMI should be among the targets for interventions to protect against age‐related cognitive decline.     

Intelligence,educational attainment,and brain structure in those at familial high‐risk for schizophrenia or bipolar disorder

First‐degree relatives of patients diagnosed with schizophrenia (SZ‐FDRs) show similar patterns of brain abnormalities and cognitive alterations to patients, albeit with smaller effect sizes. First‐degree relatives of patients diagnosed with bipolar disorder (BD‐FDRs) show divergent patterns; on average, intracranial volume is larger compared to controls, and findings on cognitive alterations in BD‐FDRs are inconsistent. Here, we performed a meta‐analysis of global and regional brain measures (cortical and subcortical), current IQ, and educational attainment in 5,795 individuals (1,103 SZ‐FDRs, 867 BD‐FDRs, 2,190 controls, 942 schizophrenia patients, 693 bipolar patients) from 36 schizophrenia and/or bipolar disorder family cohorts, with standardized methods. Compared to controls, SZ‐FDRs showed a pattern of widespread thinner cortex, while BD‐FDRs had widespread larger cortical surface area. IQ was lower in SZ‐FDRs (d = −0.42, p = 3 × 10⁻⁵), with weak evidence of IQ reductions among BD‐FDRs (d = −0.23, p = .045). Both relative groups had similar educational attainment compared to controls. When adjusting for IQ or educational attainment, the group‐effects on brain measures changed, albeit modestly. Changes were in the expected direction, with less pronounced brain abnormalities in SZ‐FDRs and more pronounced effects in BD‐FDRs. To conclude, SZ‐FDRs and BD‐FDRs show a differential pattern of structural brain abnormalities. In contrast, both had lower IQ scores and similar school achievements compared to controls. Given that brain differences between SZ‐FDRs and BD‐FDRs remain after adjusting for IQ or educational attainment, we suggest that differential brain developmental processes underlying predisposition for schizophrenia or bipolar disorder are likely independent of general cognitive impairment.     

Distributed functional connectivity predicts neuropsychological test performance among older adults

Neuropsychological test is an essential tool in assessing cognitive and functional changes associated with late‐life neurocognitive disorders. Despite the utility of the neuropsychological test, the brain‐wide neural basis of the test performance remains unclear. Using the predictive modeling approach, we aimed to identify the optimal combination of functional connectivities that predicts neuropsychological test scores of novel individuals. Resting‐state functional connectivity and neuropsychological tests included in the OASIS‐3 dataset (n = 428) were used to train the predictive models, and the identified models were iteratively applied to the holdout internal test set (n = 216) and external test set (KSHAP, n = 151). We found that the connectivity‐based predicted score tracked the actual behavioral test scores (r = 0.08–0.44). The predictive models utilizing most of the connectivity features showed better accuracy than those composed of focal connectivity features, suggesting that its neural basis is largely distributed across multiple brain systems. The discriminant and clinical validity of the predictive models were further assessed. Our results suggest that late‐life neuropsychological test performance can be formally characterized with distributed connectome‐based predictive models, and further translational evidence is needed when developing theoretically valid and clinically incremental predictive models.     

Cerebral haemodynamics with head position changes post-ischemic stroke: A systematic review and meta-analysis

The effects of upright postures on the cerebral circulation early post-ischemic stroke are not fully understood. We conducted a systematic review and meta-analysis to investigate the effects of head positioning on cerebral haemodynamics assessed by imaging methods post-ischemic stroke. Of the 21 studies included (n = 529), 15 used transcranial Doppler. Others used near-infrared, diffuse correlation spectroscopy and nuclear medicine modalities. Most tested head positions between 0° and 45°. Seventeen studies reported changes in CBF parameters (increase at lying-flat or decrease at more upright) in the ischaemic hemisphere with position change. However, great variability was found and risk of bias was high in many studies. Pooled data of two studies ≤24 h (n = 28) showed a mean increase in cerebral blood flow (CBF) velocity of 8.5 cm/s in the ischaemic middle cerebral artery (95%CI,−2.2–19.3) from 30° to 0°. The increase found ≤48 h (n = 50) was of 2.3 cm/s (95%CI,−4.6–9.2), while ≤7 days (n = 38) was of 8.4 cm/s (95%CI, 1.8–15). Few very early studies (≤2 days) tested head positions greater than 30° and were unable to provide information about the response of acute stroke patients to upright postures (sitting, standing). These postures are part of current clinical practice and knowledge on their effects on cerebral haemodynamics is required.