NeuroImage: Reports

Introduction Language functional MRI (fMRI) is a valuable tool for presurgical planning in epilepsy. Functional MRI can be challenging in children, and head motion can compromise its utility. The candidacy of patients with ADHD for fMRI is sometimes queried regarding concerns about possible head motion. In 2020, we implemented an fMRI task training program, via telehealth and/or mock MRI. We aimed to determine whether training increased language lateralisation success and/or reduced head motion in all patients, and in those with ADHD. We also aimed to determine whether patients with ADHD exhibited more head motion during fMRI than those without ADHD. Methods We retrospectively identified 223 epilepsy (85%) and other neurosurgery patients, (241 scans including repeats) with language fMRI at Royal Children's Hospital, Melbourne, Australia, 2016-2024. There were 24 individuals with ADHD listed in the Electronic Medical Record, five of whom had diagnoses of both ADHD and autism; and nine with autism. Language lateralisation success was determined by clinician description recorded as left/right/bilateral in the medical record. 99 patients were provided the training including fMRI task practise. Head motion was quantified by maximum Framewise Displacement (FDmax; mm). Results ADHD was associated with lower language lateralisation success. Training was associated with greater language lateralisation success, across all patients, and in those with ADHD. Regarding ADHD and head motion, outliers in FDmax were seen in 5 young patients with ADHD. Data were trimmed to allow separate investigation of FDmax for the sample with and without extremes of head motion. In untrimmed data, FDmax was significantly higher in patients with ADHD than in those without. In trimmed data, FDmax was on average lower in patients with ADHD than those without, however this was not statistically supported. Regarding training and head motion, across all patients, FDmax was significantly lower for scans with training than without. In patients with ADHD, FDmax was on average lower for scans with training, however training was not associated with FDmax. Conclusions Language fMRI training was associated with higher language lateralization success, particularly in patients with ADHD. Training was associated with reduced head motion across all patients. Although some young patients with ADHD had substantial head motion, most in our sample did not move more than those without ADHD. We conclude that the training program increases success of language fMRI, and that an ADHD diagnosis should not be a contraindication to language fMRI.

PURPOSE: The UK7T travelling head dataset was used to characterise the reproducibility of 7T measurements of the susceptibility of the hippocampal subfields, focusing on the Cornu Ammonis (CA1, CA2 and CA3), dentate gyrus (DG), subiculum (SUB), tail of the hippocampus (TAIL) and entorhinal cortex (ERC). METHODS: Susceptibility maps were created from whole-brain 3D single-echo GRE data (TE=20 ms; 0.7 mm isotropic resolution) using Multi-Scale Dipole Inversion. Automatic Segmentation of Hippocampal Subfields (ASHS) was applied to high resolution T1- and T2-weighted images for segmentation. The mean magnetic susceptibility and volume of hippocampal subfields was evaluated in 50 data sets, comprising 5 repeat acquisitions on 10 healthy participants (age 32 + or -6 years; 3 female). RESULTS: Averaging over subjects, susceptibility values spanned an 18ppb range over the hippocampus (ranging from -13.3ppb in DG to 4.7ppb in ERC). Susceptibility values in the larger hippocampal subfields showed a consistent pattern of variation across subjects, being generally more positive in ERC and SUB than in CA1 and more positive in CA1 than in DG and TAIL. The standard deviation of subfield susceptibilities over subjects ranged from 8.2ppb in the TAIL to 1.7ppb in CA1, and the average standard deviation across repeated measurements, which ranges from 1.7 to 4 ppb, was less than half of the inter-participant standard deviation in all subfields. Susceptibility values in the smaller subfields (CA2 and CA3) were more variable, but ICC(2,k) values for all subfields were >0.82. CONCLUSION: The reported data characterises the variation and reproducibility of hippocampal subfield susceptibility measurements at 7T.

Moderate-to-severe traumatic brain injury (msTBI) is recognized as a chronic and evolving neurological condition characterized by progressive structural brain changes and persistent cognitive impairment. While prior studies have demonstrated widespread atrophy following msTBI, less is known regarding the longitudinal trajectory of gray matter (GM) changes during recovery and post-rehabilitation. The current study used longitudinal voxel-based morphometry (VBM) to characterize GM volume changes over a period of 9 months, in individuals with msTBI relative to healthy controls (HC). Associations between regional GM volume and neuropsychological functioning were examined. Twenty-eight participants (14 msTBI, 14 HC) completed MRI and neuropsychological assessments across three timepoints spanning outpatient rehabilitation and follow-up. Longitudinal VBM analyses revealed significant group and time interactions within subcortical and limbic regions. Relative to HC, individuals with msTBI showed lower GM volume in these regions at baseline, with trajectories that converged toward HC values (right hippocampus) or increased relative to HC over the rehabilitation period (bilateral pulvinar), whereas the right amygdala and inferior cerebellar vermis remained persistently reduced. Significant longitudinal improvements in memory and psychomotor speed during the rehabilitation period were demonstrated in msTBI. Greater (preserved) GM volume within the right hippocampus, thalamus, and bilateral pulvinar was associated with better performance across measures of verbal memory, processing speed, executive functioning, and cognitive flexibility. These findings suggest that msTBI is associated with dynamic structural brain changes involving subcortical, limbic, and cerebellar networks, and that the rehabilitation period was accompanied by relative volumetric stabilization in these regions and by meaningful cognitive improvement.

Background: The Western Aphasia Battery-Revised (WAB-R) Aphasia Quotient is the most widely used standardized post-stroke aphasia measure; its conventional 93.8 cutoff has limited sensitivity to mild residual impairment. Beyond the cutoff, it offers limited objective discourse assessment, no action-naming assessment, and naming tests limited to very common objects. Aims: We sought short tests capturing subtle aphasia in patients recovered above the WAB-R threshold, then its demographic and lesion correlates. Methods & Procedures: Sixty-seven patients with acute left-hemisphere ischemic stroke completed acute structural MRI and a 12-month language battery comprising the WAB-R, Boston Naming Test (BNT), Hopkins Action Naming Assessment (HANA), and Modern Cookie Theft (MCT) picture description. Hierarchical logistic (binary deficit) and linear (control-referenced composite z-score) regressions evaluated acute aphasia history, sex, education, age, acute depression (PHQ-9), and residualized regional lesion load. Outcomes & Results: Of 67 participants, 45 (67%) recovered above the WAB-R threshold. Of these, 18 (40%) had residual deficits on at least one supplemental test ("subtle aphasia"). BNT plus MCT content-unit count captured all 18 (100%); HANA added none beyond these two. The binary model discriminated deficit from no-deficit at AUC = 0.80 (95% CI [0.70, 1.00]); higher education significantly lowered deficit odds (OR = 0.80/year, 95% CI [0.64, 1.00], p = .049). On the continuous composite, acute PHQ-9 independently predicted 12-month outcome ({beta} = -0.13 per point, 95% CI [-0.22, -0.04], p = .006, cumulative R-squared = 0.38). Applying the Senthilkumar et al. (2026) stricter cutoff (WAB-AQ [≥] 96.7) reclassified 12 of 45 (27%) out of recovery, capturing 8 of 18 (44%) subtle-aphasia patients. Composite residualized lesion load did not differentiate the groups when adjusted. Conclusions: Above the WAB-R recovery threshold, subtle aphasia is present on the BNT or MCT in ~40%, with higher education associated with lower odds at 12 months; acute depression emerged as a candidate correlate but did not survive removal of a single high-influence observation, warranting replication in larger samples. Regional lesion variables informative at greater stroke severity contribute little as large lesions cluster in the persistently aphasic group, reducing lesion variance within the recovered subgroup and its discrimination of subtle deficits. This adds to evidence that clinicians should not infer complete language recovery from the WAB-AQ alone, and that identifying residual deficits may require greater investment in behavioral assessment and consideration of alternative WAB-AQ cutoffs. Structural anatomical information, by contrast, appears to add little discriminative value at the upper performance range.

Transcranial photobiomodulation (PBM) is an emerging non-invasive brain stimulation method that is thought to increase neural metabolism by stimulating ATP production by the mitochondria. However, the mechanisms of action and the effects on the human brain are still unclear. In the present study, we investigated the potential of this method to enhance Blood Oxygen Level Dependent (BOLD) responses during the execution of a motor task in young and aged participants. Sixty young and aged participants were included in this single-blinded, sham-controlled, randomised, crossover study. They underwent an fMRI recording before and after 24-min stimulation with a 80-LEDs helmet emitting transcranially red and near infrared light. Post vs Pre BOLD signal was compared between PBM and SHAM, in each group. At baseline, aged participants showed reduced BOLD signal compared to young ones, in key regions of the sensorimotor processing, principally the left primary motor cortex and striatum. Transcranial PBM did not have a real impact in the young group. However in aged participants it increased BOLD signal in some regions that were underactivated compared to the young group at baseline. In particular, regional analysis showed increased BOLD response in the left primary motor cortex, and right dorsal and ventral premotor regions and striatum. These results suggest that transcranial PBM can increase fMRI BOLD activity in the task-related regions, particularly in aged subjects. Further research are needed to distinguish neural from vascular effects in transcranial PBM.

Verbal fluency (VF) tasks are widely used to differentiate patients with cognitive impairment from healthy controls, but total word count produced during these tasks becomes unreliable when patients and controls exhibit comparable proficiency. This study examined, in detail, whether item-level and sequential properties of words produced during a VF task could reliably differentiate high-proficiency patients indistinguishable from controls by word count alone. Seventy-seven native Mandarin Chinese speakers (38 controls and 39 patients with mild cognitive impairment or mild dementia) completed a semantic VF task. Participants were subdivided by proficiency into four groups: high-proficiency controls (HC), low-proficiency controls (LC), high-proficiency patients (HP), and low-proficiency patients (LP). The LC and HP subgroups were matched on semantic fluency scores and thus provided a key focus for the investigation. We examined item-level properties (word frequency, contextual diversity, semantic diversity, surprisal) and sequential properties (positional frequency variation) of the words produced. Significant group differences emerged across item-level psycholinguistic properties, though these were primarily driven by the LP group, with no reliable differentiation between LC and HP. Crucially, positional frequency variation distinguished LC from HP. LC participants began their lists with high-frequency words followed by a systematic decline, whereas HP patients produced words within a consistently narrow frequency band throughout. These findings indicate that item-level psycholinguistic properties alone are insufficient to differentiate HP from LC, whereas sequential word frequency variation provides a potential index of cognitive impairment, reflecting underlying differences in semantic retrieval and memory organisation. Future work with larger samples is needed to validate generalisability.

Objective: Aftereffects of 1 Hz repetitive transcranial magnetic stimulation (rTMS) often differ within and between subjects and thus show low reliability. In this study we investigated the mean and individual aftereffects of 1 Hz rTMS using two opposing current directions, their reliability and potential influences of current direction, participants' sex and state on cortical excitability modulations. Methods: Thirteen healthy, right-handed participants underwent four experimental sessions separated by at least 7 days receiving 2000 pulses of suprathreshold 1 Hz rTMS over the primary motor cortex per session. Two sessions were conducted with an induced current direction of anterior-posterior - posterior-anterior (AP-PA) and two sessions with a PA-AP current direction. Before and after rTMS, 100 single TMS pulses were administered with the respective current direction and electromyography was recorded from the first dorsal interosseous. Questionnaires on demographic data and subjective ratings were completed during the experiment. Results: Linear mixed effect model analysis revealed that 1 Hz rTMS induced an excitatory aftereffect when applied with the PA-AP current direction, and no aftereffect with AP-PA. There was a substantial interindividual variability with only three subjects showing an inhibition to 1 Hz rTMS overall. Also, current direction was the only predictor of rTMS aftereffect. Reliability values of these aftereffects were in the poor to moderate range. Conclusions: Current direction plays a crucial role in determining 1 Hz rTMS aftereffects. Reliability was found to be moderate at best. Additional to current direction, more factors need to be considered to tailor the 1 Hz rTMS aftereffects individually.

Background: The ability to remember object locations in real life is a fundamental cognitive process that supports goal-directed behavior and is particularly vulnerable to aging and neurodegenerative disease. Despite a growing body of functional magnetic resonance imaging (fMRI) research on object-location memory (OLM), the neural substrates of establishing and retrieving location information are largely unknown. Objective: This systematic review and coordinate-based meta-analysis aimed to identify brain regions consistently activated during OLM in healthy adults, primarily for encoding and - on an exploratory basis - for retrieval, and to characterize age-related differences in OLM-related neural activity. Methods: A systematic search was conducted across three databases (PubMed, PsycInfo, Cochrane Library) up to February 2026. Studies employing task-based fMRI during the encoding and retrieval of object-location associations in healthy adults were eligible. Age-related differences in OLM-related brain activity were examined via narrative synthesis. An activation likelihood estimation (ALE) meta-analysis was performed on studies reporting stereotactic peak coordinates. The review was pre-registered on PROSPERO (CRD420251023695). Results: Twenty-one studies comprising 637 participants were included in the systematic review, with 12 studies being eligible for the encoding ALE meta-analysis. The retrieval ALE meta-analysis was not possible due to the limited number of included studies and reported foci. The systematic review indicated that OLM encoding consistently recruited bilateral fusiform gyri and parahippocampal cortices, with additional engagement of parietal and prefrontal regions across individual studies, whereas OLM retrieval recruited mainly the hippocampus and precuneus. The coordinate-based ALE meta-analysis revealed two significant clusters of activation during OLM encoding: a left-lateralized cluster encompassing the fusiform gyrus, parahippocampal gyrus, and inferior temporal gyrus (peak MNI: -28, -38, -16), and a right-hemisphere cluster spanning the parahippocampal gyrus and fusiform gyrus (peak MNI: 30, -46, -16). Age-related differences, based on a small number of studies with direct age comparison, pointed toward reduced activity in posterior cortical regions coupled with increased activity in prefrontal and midline regions. Additionally, younger adults showed greater hippocampal activation for successful than unsuccessful spatial retrieval, whereas older adults showed the opposite pattern. Conclusion: The systematic review and meta-analysis identify the fusiform gyri and parahippocampal cortices as the most reliably activated regions during OLM encoding, locating OLM formation primarily within the ventral visual-to-medial-temporal processing stream. Retrieval additionally engaged the hippocampus and precuneus, consistent with their established roles in episodic memory. Age-related differences included reduced posterior cortical encoding activity in older adults, a reversal of the hippocampal activation pattern during retrieval, and weaker suppression of midline regions during task performance. The identified encoding pathway may inform targeted network-level interventions such as non-invasive brain stimulation to counteract cognitive decline in aging and neurodegenerative disease.

Disruptions in somatosensory processing have been observed in cognitive impairment (CI), suggesting that alterations in sensory processing may emerge earlier during cognitive decline than previously recognized. Somatosensory gating (SG) is an automatic inhibitory mechanism that protects neural resources by suppressing responses to redundant, non-behaviorally relevant stimuli. Prior work has demonstrated exaggerated gamma SG and response amplitudes in the primary somatosensory cortex (S1) of individuals with Alzheimer's disease-confirmed pathology, and these effects were masked by variability in attention/executive function performance. However, whether similar relationships are present during earlier stages of cognitive decline, such as CI, remains unclear. Herein, 63 cognitively healthy older adults (CH; mean age = 59.9 {+/-} 8.6 years) and 32 individuals with CI (mean age = 62.4 {+/-} 8.8 years) underwent magnetoencephalography (MEG) while completing a paired-pulse SG paradigm designed to probe inhibitory sensory processing. MEG oscillatory responses were source-imaged using a beamformer. Time series data were extracted from the peak voxel to quantify oscillatory dynamics and SG. Neuropsychological testing was conducted to assess attention/executive function. After controlling for attention/executive function variance, exaggerated gamma SG was observed in adults with CI compared with CH adults (p < 0.05). Additionally, adults with CI exhibited increased beta peak frequency following the second stimulation (p < 0.01) and a group-by-age interaction for theta SG in S1 (p < 0.05). Together, these results suggest somatosensory abnormalities are present in earlier stages of cognitive decline and highlight a dynamic interaction between sensory processing and cognitive systems during this decline.

This study investigated the hemispheric contributions of the inferior frontal gyrus (IFG) to word production across constrained and unconstrained tasks. In the present study, we used focal ring transcranial direct current stimulation (tDCS) in a sham-controlled, double-blind design, combined with a Picture-Word Interference (PWI) task and a picture description task. Fifty-four healthy young adults completed both tasks within the same stimulation sessions, receiving anodal stimulation over either the left or right IFG. Following task-specific data exclusions, 52 participants were included in each of the two task analyses. In the PWI task, categorically related distractors produced semantic interference and associatively related distractors facilitated naming in response times, consistent with previous findings. Stimulation did not affect response times. In error rates, the two stimulation sites modulated the associative effect in opposite directions. Anodal stimulation of the left IFG enhanced the associative advantage in error rates, whereas anodal stimulation of the right IFG produced the opposite pattern. In the picture description task, anodal stimulation of the right IFG increased speech rate, producing significant effects on words per minute, unpruned words per minute, and syllables per minute. No equivalent effects emerged in the left IFG group. Lexical diversity and utterance length were unaffected by stimulation. Taken together, these findings provide convergent evidence for a hemispheric dissociation in word production. The right IFG appears to contribute to the regulation of speech output and the control of distractor interference, whereas the left IFG appears to support the retrieval and selection of word meanings.

Background: Net Water Uptake (NWU) is a non-contrast CT (NCCT) biomarker of early cerebral edema in ischemic stroke, calculated from attenuation differences between ischemic and contralateral non-ischemic brain regions. Manual NWU quantification is labor-intensive and prone to inter-operator variability, limiting clinical uptake and research scalability. We developed and internally validated a fully automated NWU evaluation pipeline. Methods: We analyzed 24-hour follow-up NCCT scans from the AcT (Alteplase compared to Tenecteplase) trial. Infarcts were automatically obtained by segmentation framework based on a synchronous image-label diffusion probability model. The images and extracted infarcts were registered to the standard MNI152 space, allowing us to mirror the infarct onto the contralateral hemisphere symmetrically, regardless of size or tilt angle. Subsequently, the mirrored region was inversely transformed to return to its original space. Voxels outside the range of 20-80 Hounsfield Units (HU) were excluded to remove non-parenchymal tissue. Automated NWU was computed as the percentage difference in mean HU between infarct and mirrored contralateral regions. The agreement with manually determined NWU was evaluated using Pearson correlation, mean absolute error (MAE), and Bland-Altman analysis. Results: Of 1,327 patients in the trial, 298 (22.5%) met predefined imaging-quality criteria for the manual validation analysis, including well-aligned raw NCCT scans in the axial plane and clear parenchymal infarct segmentations. Automated 24-hour NWU showed excellent agreement with manual measurements (r = 0.99). Mean absolute error was 0.18% (95% CI: 0.01-0.46). Bland-Altman analysis demonstrated minimal bias (0.09%) and satisfactory limits of agreement (-4.05% to +4.24%). Ninety-nine percent of cases fell within {+/-}5% of the manually determined value. Conclusions: Our automated mirrored segmentation pipeline enables accurate and reproducible NWU quantification from routine 24-hour NCCT scans, matching expert manual measurements with minimal bias.

Background. Scores on neuropsychological assessments are typically corrected for the influences of age, education, and gender (AEG). However, other demographic factors, such as crystallized ability and race/ethnicity, independently affect test performance. As a result, standard scores systematically over- or under-classify impairment in patients whose demographic profile differs from that of the reference population. Methods. We developed a Comprehensive (C-) model scoring algorithm that added vocabulary, age-squared, race/ethnicity, Latino background, a coarse socioeconomic status proxy, computer use, and daily prescription medications to the standard AEG predictor pool. The model was developed using data from 1,914 community-dwelling adults assessed with the California Cognitive Assessment Battery (CCAB; Woods et al., 2024). For each of 118 individual cognitive measures, stability-selection LASSO identified robust predictors in 300 random 80/20 splits retained at >=80% frequency and then estimated mean coefficients and confidence intervals in 1,000 bootstrap OLS samples. Cross-sample frozen-coefficient validation was used to evaluate scoring model generalization in two subgroups: Group 1 (n = 1,033, older, first enrolled cohort) and Group 2 (n = 881, a recently recruited younger cohort). Results. Stability selection retained a mean of 2.81 predictors per measure (range 1-6). Compared to the AEG model, the C-model approximately doubled variance explained (r2 = 0.50 vs 0.25; mean across cognitive domains r2 = 0.32 vs 0.18) and outperformed AEG in 98.8% of individual measures with non-trivial demographic signal. Racial disparities in MCI classification (the bottom-7th-percentile) were substantially reduced: Black-vs-White ratios fell from 5.6 (AEG) to 1.8 (C). Conversely, sensitivity was improved in individuals with elevated premorbid function: MCI classification ratios in low-vs-high vocabulary quartiles fell from 11.3 to 2.1. AIC favored the C-model in 88.1% of measures (mean delta-AIC = -167), ruling out overfitting. Frozen-coefficient validation preserved the C-model's r2 advantage in every cognitive domain. Conclusions. By correcting scores for race, premorbid cognitive functioning (vocabulary), and other demographic predictors, the C-model explains substantially more variance than the AEG model, reduces racial bias, and increases sensitivity to cognitive decline in high-functioning participants. C and AEG models can be used in parallel: model concordance increases diagnostic confidence, while disagreement carries diagnostic information.

Purpose: {beta}-hydroxybutyrate (BHB), a ketone body and alternative cerebral energy substrate, can be measured in vivo using J-difference edited proton magnetic resonance spectroscopy (1H-MRS). Oral ketone supplementation with substrates such as the ketone monoester (R)-3-hydroxybutyl-(R)-3-hydroxybutyrate (KME) and 1,3-butanediol (BD) have gained attention as a mechanism to elevate circulating BHB and induce ketosis without dietary restrictions. Elevated brain ketone availability is of growing therapeutic interest as a strategy to support neuronal energetics in conditions such as epilepsy, neurodegenerative disease, and alcohol use disorder (AUD). However, both pathways introduce BD into the bloodstream, which crosses the blood-brain barrier. Critically, BD exhibits a spectral signature that closely resembles the prominent BHB peak in JDE-MR spectroscopic imaging (MRSI), identified in a pilot AUD study. Methods: Two separate JDE-MRSI acquisitions tailored for BHB and BD editing were implemented, exploiting frequency separation between the BHB (4.14ppm) and BD (3.95ppm) coupling partners of the observed 1.2ppm resonance to independently quantify each metabolite. Results: Brain BD concentrations (0.25-0.58mM) were comparable to or exceeded corresponding BHB concentrations (0.20-0.27mM) in all volunteers after consumption of a single dose of the KME, indicating that BD constitutes a major fraction of the signal conventionally attributed to BHB. Combined BHB+BD concentrations (~0.45-0.85mM) were consistent with brain BHB values reported in prior studies employing similar doses of the KME, indicating that those measurements likely reflect a combined BHB+BD signal. Conclusions: Separate quantification of the two metabolites is important for interpreting brain ketone studies and for understanding the full pharmacology of KME supplementation.

Acute ischemic stroke (AIS) is a leading cause of disability and death while effective treatment requires quick and accurate diagnosis. Non-contrast CT (NCCT) is widely used in the initial screening of AIS, but stroke detection is challenging because early changes on NCCT are subtle or indistinguishable. Using hyperacute NCCTs as inputs and diffusion-weighted MRI as ground truth, we trained a deep learning algorithm to classify patients with AIS and segment the stroke lesions. We hypothesized that this approach would accurately detect hyperacute tissue density changes on NCCT. For the classification task, our ResNet50 model delivered the best performance (with 98.5% accuracy, 97.4% precision, and 100% recall on an evaluation set). Classification performance remained strong when restricted to lesions smaller than 5 mL, which constituted the majority of our evaluation cases. For the segmentation task accomplished using a range of U-Net architectures, performance was acceptable for large lesions and declined sharply for smaller lesions. Together, these findings demonstrate the feasibility of deep learning for AIS detection and represent a step towards faster triage and treatment for stroke patients.

Fast periodic visual stimulation (FPVS) has recently demonstrated an ability to index multiple cognitive domains such as facial expression processing, working memory, and more recently, semantic categorization in just a few minutes of recording time. The present work investigates the effects of low semantic distance and how this modulates semantic categorization responses. Twenty-seven healthy young adults completed an FPVS oddball paradigm in order to determine whether comparing fruits and vegetables of the same color would elicit semantic categorization responses. Strong oddball responses were observed up to the 10th frequency harmonic, and responses showed statistically significant right occipito-temporal lateralization that was not present in a low-level color change condition completed by participants and is opposite the pattern observed in recent word-based semantic categorization FPVS studies. The findings suggest that image-based FPVS paradigms should be investigated further as candidate tools to study conditions that affect semantic categorization such as Alzheimers disease.

Disordered eating attitudes exist on a continuum that extends well below clinical diagnostic thresholds, yet the cognitive correlates of this non-clinical variation remain incompletely understood. Previous research linking executive functioning to disordered eating in non-clinical samples has relied almost exclusively on self-report questionnaire measures of executive function, which show weak correspondence with performance-based assessments. This methodological reliance leaves open the question of how objective executive performance relates to eating behavior across the spectrum. The present study addressed this gap by examining the association between performance-based measures of executive function and disordered eating attitudes in a non-clinical sample of 243 university students via an online experiment, using a dimensional approach consistent with the Research Domain Criteria framework. Participants completed established neurocognitive tasks covering three executive function domains: working memory was assessed with Digit Span and an N-back task, inhibitory control with a Go/No-Go task, and cognitive flexibility with the Card Sorting Task. Disordered eating attitudes were indexed using the EAT-26 total score and its subscales. A notable correlation was identified between cognitive flexibility and disordered eating attitudes, while working memory and inhibitory control exhibited no such association. Overall, our findings provide evidence for associations between executive functioning and disordered eating attitudes in a non-clinical sample.

Purpose: To investigate sex differences in cerebral blood flow through densely parcellated cortical and subcortical regions using explainable artificial intelligence methods and identify neurobiologically interpretable perfusion biomarkers. Methods: High-resolution pseudo-continuous arterial spin labelling (1.875 mm x 1.875 mm x 3 mm) and structural MRI data were curated from 215 healthy young adults (150 females, 95 males; age 18-30 years) from the publicly available I See your Brains (ISYB) dataset. Cerebral blood flow was quantified using atlas-based regional analysis with the Brainnetome Atlas (246 regions) and optimized registration procedures. Sex classification employed diverse machine learning paradigms including linear classifiers, ensemble methods, and kernel-based approaches for regional CBF features, with deep convolutional neural networks (CNN) applied to whole-brain 3D imaging data. Model interpretability was achieved using SHapley Additive exPlanations (SHAP), computed over an ensemble of 500 logistic regression models (100 iterations x 5-fold cross-validation). Regions appearing among the top 20% of discriminative features more than 289 times were considered statistically significant using binomial testing. GradCAM was used to obtain class-specific attribution maps from the CNN model. Results: Perfusion-based features demonstrated superior sex classification performance compared to structural morphometry. Regional CBF analysis using logistic regression achieved 91 +/- 2% balanced accuracy and 0.95 +/- 0.05 ROC-AUC, substantially outperforming morphometric features (85 +/- 8% balanced accuracy, 0.88 +/- 0.06 ROC-AUC). Deep learning classification of 3D CBF maps achieved a performance of 92 +/- 5% balanced accuracy, 0.92 +/- 0.05 ROC-AUC. SHAP analysis identified 30 statistically significant aggregation-agnostic CBF-based biomarker regions using regional CBF, predominantly involving frontoparietal control networks (27%) and default mode networks (17%). Grad-CAM revealed that the 3D CNN model primarily focused on regions within the frontal lobe. Morphometry-based analysis identified 28 discriminative regions with markedly different anatomical distribution (r = 0.21) emphasizing visual (32%) and default mode (14%) networks. Conclusion: Cerebral blood flow patterns provide highly sensitive and biologically interpretable markers of sex differences in young adult brain. The identification of robust perfusion biomarkers through explainable AI demonstrates the clinical potential of ASL imaging for precision medicine applications in neuroscience. We establish a methodological framework for investigating sex-specific brain physiology using non-invasive neuroimaging.

Introduction: Narrative recall is widely used to detect cognitive impairment, but dominant instruments carry proprietary restrictions. The Craft Story 21 (CS), the non-proprietary NACC UDS4 standard, is not available standalone. Here, we validate the freely available Puppy Escape (PE). Methods: 346 participants (153 cognitively normal, 106 subjective cognitive impairment, 87 mild cognitive impairment) completed PE and CS. Analyses evaluated convergent and criterion validity, MCI-vs-control discrimination, and incremental validity. Results: PE and CS converged (r=.43-.47) and were equivalent on 10/12 neuropsychological measures. PE Delayed discriminated MCI from controls (d=1.03; ROC-AUC equal to CS, DeLong p=.510) and added variance beyond CS (R2=+.054, p<.001). Automated subscores revealed MCI deficits in location, action, and name content. PE-18 short form retained discrimination (d=1.02) with 18 items. Discussion: PE matched CS across all validation domains and captured complementary diagnostic information. PE and PE-18 are available via online registration explicitly permitting industry-sponsored research and fee-for-service clinical use.

Background: Corticospinal tract (CST) damage is a major cause of post-stroke motor deficits. However, it remains unclear which estimates of CST damage best predict motor recovery, especially regarding different aspects of motor control. While conventional CST-lesion metrics offer superior feasibility, data-driven machine learning (ML) approaches may better capture patients propensity for task-specific recovery with important implication for their use as future clinical biomarkers. Methods: Providing the first direct longitudinal comparison of these approaches based exclusively on CST-lesion patterns, we evaluated six conventional CST-lesion metrics and a voxel-wise ML approach using clinical MRI data from 127 acute ischemic stroke patients. Acute impairment and outcome (>3 months post-stroke) were assessed for basal and complex motor functions. Conventional CST-lesion metrics and ML were used to predict task-specific motor impairment and outcome. Results: All conventional CST-lesion metrics correlated significantly with both acute impairment and motor outcome across motor domains, with metrics weighted for CST narrowing and tract probability performing best. However, predictive performance for unseen patients was low. ML outperformed conventional markers in predicting acute impairment across motor domains and basal motor outcome, but failed to predict complex motor outcome. Topographically, predictive voxels clustered within and above the posterior limb of the internal capsule, with distinct CST subregions associated with basal versus complex motor impairment, consistent with a task-specific somatotopic organization. Conclusions: The predictive utility of CST biomarkers was task- and timepoint-dependent. While ML may improve predictive performance, complex motor outcome remained difficult to predict, likely reflecting greater reliance on distributed cortical reorganization beyond the CST. By revealing task-specific CST subregions, voxel-wise ML provides an anatomically informed foundation for future predictive models. Such future models should combine CST biomarkers with measures of broader motor network integrity to enable individualized prognosis tailored to specific motor domains and recovery stages.

Acute kidney injury (AKI) is common among neonates in the intensive care unit and has been linked to abnormal neurodevelopment, yet long-term effects on brain structure remain uncharacterized. In this secondary analysis, we compared brain white matter integrity, measured by fractional anisotropy (FA) on 3T MRI, in children ages 5 to 12 years born preterm with (n=5) versus without (n=10) a history of neonatal AKI. Contrary to our hypothesis, children with prior neonatal AKI showed higher FA across seven white matter regions in unadjusted analyses. After adjustment for sex, birth weight, and age at MRI, the AKI group retained significantly greater FA in the corticospinal tract ({beta}=0.7, 95% CI 0.09-1.31) and superior frontooccipital fasciculus ({beta}=0.68, 95% CI 0.02-1.34). Because elevated FA may reflect compensatory glial responses rather than improved neurological function, these findings suggest neonatal AKI may have lasting, complex effects on white matter microstructure. Larger studies pairing neuroimaging with neurocognitive assessment are needed.