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This review systematically analyzes potential biomarker candidates for post‐traumatic epilepsy (PTE) in humans who have experienced moderate to severe traumatic brain injury (TBI). Focusing on biomarkers across biofluid‐based protein, genetic, neuroimaging, and neurophysiological categories, this review distinguishes between TBI patients who develop PTE and those who do not. The review adheres to established methodologies outlined in the Cochrane Handbook for Systematic Reviews of Interventions. Data presentation follows the Meta‐analyses of Observational Studies (MOOSE) and Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) guidelines. Medline, Embase, and Web of Science were systematically searched and yielded 7538 records, of which 18 met inclusion criteria (moderate–severe TBI in humans, follow‐up of at least 6 months, and no prior history of epilepsy). The review aggregates data from 15 cohort and 3 case–control studies (risk of bias was assessed using the Newcastle‐Ottawa Scale). Statistically significant biomarkers were identified, with neurophysiological biomarkers showing the strongest effect size in a two‐study meta‐analysis. PTE, a severe long‐term outcome of TBI affecting 2% to 53% of individuals with TBI, lacks validated biomarkers for forecasting development, crucial for designing preventive clinical trials. A multimodal approach, integrating biofluid‐based protein, genetic, neuroimaging, and neurophysiological data, offers a promising strategy to enhance the predictability of PTE development and, potentially, its treatment. The study's protocol is registered in the International Prospective Register of Systematic Reviews PROSPERO (Registration ID: CRD42023470245). [ABSTRACT FROM AUTHOR]

Background Objective Methods Results Conclusion Understanding the neural mechanisms underlying migraine and other primary headache disorders is critical for the development of long‐term cures. Magnetoencephalography (MEG), an imaging modality that measures neuronal currents and cortical excitability with high temporal and superior spatial resolution, has been increasingly used in neurological research. Initial MEG studies showed promise in directly recording cortical spreading depression—a cortical correlate of migraine with aura. However, lately MEG technology has highly evolved with greater potential to reveal underlying pathophysiology of migraine and primary headache disorders, and aid in the identification of biomarkers.To systematically review the use of MEG in migraine and other primary headache disorders and summarize findings.We conducted a systematic search and selection of MEG studies in migraine and primary headache disorders from inception until June 8, 2023, in Medline, Embase, Cochrane, and Scopus databases. Peer‐reviewed English articles reporting the use of MEG for clinical or research purposes in migraine and primary headache disorders were selected.We found 560 articles and included 38 in this review after screening. Twelve studies investigated resting‐state, while others investigated a sensory modality using an evoked or event‐related paradigm with a total of 35 cohort and 3 case studies. Thirty‐two studies focused exclusively on migraine, while the rest reported other primary headache disorders.The findings show an evolution of MEG from a 7‐ to a 306‐channel system and analysis evolving from sensor‐level evoked responses to more advanced source‐level connectivity measures. A relatively few MEG studies portrayed migraine and primary headache disorders as a sensory abnormality, especially of the visual system. We found heterogeneity in the datasets, data reporting standards (due to constantly evolving MEG technology and analysis methods), and patient characteristics. Studies were inadequately powered and there was no evidence of blinding procedures to avoid selection bias in case–control studies, which could have led to false‐positive findings. More studies are needed to investigate the affective–cognitive aspects that exacerbate pain and disability in migraine and primary headache disorders. [ABSTRACT FROM AUTHOR]

Aim Methods Results Conclusion Immune dysregulation and delayed onset of sleep wake cycling (SWC) are associated with worse outcome in neonatal encephalopathy (NE), however the association between sleep and immune dysfunction in NE remains unclear. Aimed to evaluate association of sleep and systemic inflammation with outcomes in NE.Amplitude‐integrated electroencephalography (aEEG) recordings were collected on infants undergoing therapeutic hypothermia (TH). Duration to onset of (SWC) and sleep quality (SQ) were examined. Blood samples collected during the first 2 days of life. Thirteen pro‐ and anti‐inflammatory serum cytokines were quantified. Adverse outcome defined as death or abnormal MRI brain.Earlier onset of SWC and better SQ had less adverse outcomes. SQ provided better prognostic value and showed better interobserver agreement compared to duration to SWC. Better SQ associated with lower cytokines EPO and interleukin (IL)‐1β. In infants with unfavourable outcome, shorter duration to SWC was associated with higher EPO and better SQ was associated with lower TNF‐α.Earlier onset of SWC or better SQ showed less systemic inflammation and fewer adverse outcomes. SQ during TH provided better prognostic information than time of onset of SWC. Modulation of circadian rhythm in infants with NE may have an immunomodulatory role, leading to improved outcomes. [ABSTRACT FROM AUTHOR]

Background: Freezing of gait is one of the most disturbing motor symptoms of Parkinson's disease (PD). However, the effective connectivity between key brain hubs that are associated with the pathophysiological mechanism of freezing of gait remains elusive. Objective: The aim of this study was to identify effective connectivity underlying freezing of gait. Methods: This study applied spectral dynamic causal modeling (DCM) of resting‐state functional magnetic resonance imaging in dedicated regions of interest determined using a data‐driven approach. Results: Abnormally increased functional connectivity between the bilateral dorsolateral prefrontal cortex (DLPFC) and the bilateral mesencephalic locomotor region (MLR) was identified in freezers compared with nonfreezers. Subsequently, spectral DCM analysis revealed that increased top‐down excitatory effective connectivity from the left DLPFC to bilateral MLR and an independent self‐inhibitory connectivity within the left DLPFC in freezers versus nonfreezers (>99% posterior probability) were inversely associated with the severity of freezing of gait. The lateralization of these effective connectivity patterns was not attributable to the initial dopaminergic deficit nor to structural changes in these regions. Conclusions: We have identified novel effective connectivity and an independent self‐inhibitory connectivity underlying freezing of gait. Our findings imply that modulating the effective connectivity between the left DLPFC and MLR through neurostimulation or other interventions could be a target for reducing freezing of gait in PD. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

The neuroimaging basis of intelligence remains elusive; however, there is a growing body of research employing connectome‐based predictive modeling to estimate individual intelligence scores, aiming to identify the optimal set of neuroimaging features for accurately predicting an individual's cognitive abilities. Compared to adults, the disparities in cognitive performance among children and adolescents are more likely to captivate individuals' interest and attention. Limited research has been dedicated to exploring neuroimaging markers of intelligence specifically in the pediatric population. In this study, we utilized resting‐state functional magnetic resonance imaging (fMRI) and intelligence quotient (IQ) scores of 170 healthy children and adolescents obtained from a public database to identify brain functional connectivity markers associated with individual intellectual behavior. Initially, we extracted and summarized relevant resting‐state features from whole‐brain or functional network connectivity that were most pertinent to IQ scores. Subsequently, these features were employed to establish prediction models for both performance and verbal IQ scores. Within a 10‐fold cross‐validation framework, our findings revealed that prediction models based on whole‐brain functional connectivity effectively predicted performance IQ scores(R=0.35,P=2.2×10−4) but not verbal IQ scores(R=0.12,P=0.20). Results of prediction models based on brain functional network connectivity further demonstrated the exceptional predictive ability of the default mode network (DMN) and fronto‐parietal task control network (FTPN) for performance IQ scores (R=0.71,P=2.2×10−18). The above findings have also been validated using an independent dataset. Our findings suggest that the performance IQ of children and adolescents primarily relies on the connectivity of brain regions associated with DMN and FTPN. Moreover, variations in intellectual performance during childhood and adolescences are closely linked to alterations in brain functional network connectivity. Our findings suggest that the performance IQ of children and adolescents primarily relies on the connectivity of brain regions associated with DMN and FTPN. Moreover, variations in intellectual performance during childhood and adolescences are closely linked to alterations in brain functional network connectivity. [ABSTRACT FROM AUTHOR]

Background: Progressive supranuclear palsy (PSP) is a progressive atypical parkinsonian condition that results in severe disability. There are few studies of PSP in patients of non‐white European ancestry. Objectives: We aim to perform deep phenotyping in a South Asian PSP cohort to uncover possible ethnic differences in disease characteristics. Methods: Consecutive PSP patients had their clinical records reviewed for clinical features operationalized in the Movement Disorder Society (MDS)‐PSP diagnostic criteria and relevant investigations, including imaging and genetic tests. Clinical variables were summarized by descriptive statistics and Kaplan–Meier curves were generated for survival analysis. Results: Twenty‐seven patients, comprising Indians (78%), Pakistanis (11%) and Sri Lankans (11%) were included. Mean age of symptom onset was 63.8 ± 7.0 years and 22% of patients had an early age of onset (<60 years). The most common presenting symptom was parkinsonism (56%), followed by cognitive dysfunction (37%), falls (33%) and dysarthria (26%). The predominance types at final review were distributed across PSP‐RS (67%), PSP‐PGF (15%), PSP‐P (15%) and PSP‐F (4%). Atypical clinical features like cerebellar signs (33%), REM‐sleep behavior disorder (RBD) (55%), visual hallucinations (22%), and a family history of parkinsonism (20%) were evident in a proportion of patients. Conclusions: We present a South Asian cohort of PSP patients with a higher than previously reported percentages of early‐onset disease, family history and atypical clinical manifestations. These patients do not fit easily into the PSP phenotypes defined by the current MDS criteria. Dedicated clinicopathological and genetic tests are needed in this population to dissect the pathogenesis of clinically‐defined PSP. [ABSTRACT FROM AUTHOR]

Background and Aims: The brain age gap (BAG), calculated as the difference between a machine learning model‐based predicted brain age and chronological age, has been increasingly investigated in psychiatric disorders. Tobacco and alcohol use are associated with increased BAG; however, no studies have compared global and regional BAG across substances other than alcohol and tobacco. This study aimed to compare global and regional estimates of brain age in individuals with substance use disorders and healthy controls. Design: This was a cross‐sectional study. Setting: This is an Enhancing Neuro Imaging through Meta‐Analysis Consortium (ENIGMA) Addiction Working Group study including data from 38 global sites. Participants: This study included 2606 participants, of whom 1725 were cases with a substance use disorder and 881 healthy controls. Measurements: This study used the Kaufmann brain age prediction algorithms to generate global and regional brain age estimates using T1 weighted magnetic resonance imaging (MRI) scans. We used linear mixed effects models to compare global and regional (FreeSurfer lobestrict output) BAG (i.e. predicted minus chronological age) between individuals with one of five primary substance use disorders as well as healthy controls. Findings Alcohol use disorder (β = −5.49, t = −5.51, p < 0.001) was associated with higher global BAG, whereas amphetamine‐type stimulant use disorder (β = 3.44, t = 2.42, p = 0.02) was associated with lower global BAG in the separate substance‐specific models. Conclusions: People with alcohol use disorder appear to have a higher brain‐age gap than people without alcohol use disorder, which is consistent with other evidence of the negative impact of alcohol on the brain. [ABSTRACT FROM AUTHOR]

Introduction/Aims: Myotonia is a key symptom of myotonic dystrophies (DM), and its quantification is challenging. This exploratory study evaluated the utility of tissue Doppler ultrasound (TDU) to assess myotonia in DM. Methods: Twelve DM patients (seven type‐1 DM [DM1] and five type‐2 DM [DM2]) and 20 age‐matched healthy subjects were included in this cross‐sectional study. After measuring cross‐sectional areas of the flexor digitorum superficialis (FDS) and extensor digitorum communis (EDC) muscles in a resting state, muscle contraction/relaxation time, time to peak tissue velocity, peak tissue velocity and velocity gradients of these muscles were measured via TDU while performing forced fist unclenching after fist closure. Additionally, grip strength, Medical Research Council Sum score and patient‐reported myotonia severity scores were assessed. Results: DM1 and DM2 patients had a lower grip strength than healthy subjects (p =.0001/p =.002). Patient‐reported myotonia did not differ between DM1 and DM2 patients. DM1 patients revealed FDS and EDC atrophy compared to DM2 patients and healthy subjects (p =.003/p =.004). TDU revealed prolonged muscle contraction and relaxation times in both DM subtypes, with prolonged time to reach FDS peak relaxation velocity and altered peak FDS relaxation velocity only in DM1 patients (p =.03/p =.003). Peak FDS relaxation velocity correlated inversely with C(C)TG repeat numbers in DM patients. Sensitivity of TDU parameters to detect myotonic dystrophy varied between 50% and 75%, with a specificity of 95%. Discussion: Our exploratory study suggests that TDU could serve as a novel tool to quantify myotonia in DM patients, but larger follow‐up studies are warranted to validate its diagnostic accuracy. [ABSTRACT FROM AUTHOR]

Cognitive impairments, which can be caused by neurodegenerative and cerebrovascular disease, represent a growing global health crisis with far‐reaching implications for individuals, families, healthcare systems, and economies worldwide. Notably, neurodegenerative‐induced cognitive impairment often presents a different pattern and severity compared to cerebrovascular‐induced cognitive impairment. With the development of computational technology, machine learning techniques have developed rapidly, which offers a powerful tool in radiomic analysis, allowing a more comprehensive model that can handle high‐dimensional, multivariate data compared to the traditional approach. Such models allow the prediction of the disease development, as well as accurately classify disease from overlapping symptoms, therefore facilitating clinical decision making. This review will focus on the application of machine learning‐based radiomics on cognitive impairment caused by neurogenerative and cerebrovascular disease. Within the neurodegenerative category, this review primarily focuses on Alzheimer's disease, while also covering other conditions such as Parkinson's disease, Lewy body dementia, and Huntington's disease. In the cerebrovascular category, we concentrate on poststroke cognitive impairment, including ischemic and hemorrhagic stroke, with additional attention given to small vessel disease and moyamoya disease. We also review the specific challenges and limitations when applying machine learning radiomics, and provide our suggestion to overcome those limitations towards the end, and discuss what could be done for future clinical use. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusions Adolescence is a critical developmental period for the study of anorexia nervosa (AN), an illness characterized by extreme restriction of food intake. The maturation of the reward system during adolescence combined with recent neurobiological models of AN led to the hypothesis that early on in illness, restrictive food choices would be associated with activity in nucleus accumbens reward regions, rather than caudate regions identified among adults with AN.Healthy adolescents (HC, n = 41) and adolescents with AN or atypical AN (atypAN, n = 76) completed a Food Choice Task during fMRI scanning. Selection of high‐fat foods and choice‐related activation in nucleus accumbens and anterior caudate regions‐of‐interest (ROIs) were compared between individuals with AN/atypAN and HC. Associations were examined between choice‐related activation and choice preferences among the AN group. Exploratory analyses examined associations between choice‐related activation and psychological assessments among the patient group.Adolescents with AN or atypAN selected fewer high‐fat foods than HC (t = −5.92, p < .001). Counter to predictions, there were no significant group differences in choice‐related activation in the ROIs. Among individuals with AN or atypAN, choice‐related neural activity in the anterior caudate was significantly negatively associated with high‐fat food selections in the task (r = −.32, p = .024). In exploratory analyses, choice‐related anterior caudate activation was positively associated with psychological measures of illness severity among patients (p's < .05, uncorrected).In this large cohort of adolescents with AN/atypAN, there was no evidence of altered reward system engagement during food choice. While there was no group difference in choice‐related caudate activation, the associations with choices and psychological measures continue to suggest that this neural region is implicated in illness. Longitudinal analyses will clarify whether neural variability relates to longer‐term course. [ABSTRACT FROM AUTHOR]

Objective Methods Results Significance High‐field magnetic resonance imaging (MRI) is a standard in the diagnosis of epilepsy. However, high costs and technical barriers have limited adoption in low‐ and middle‐income countries. Even in high‐income nations, many individuals with epilepsy face delays in undergoing MRI. Recent advancements in ultra‐low‐field (ULF) MRI technology, particularly the development of portable scanners, offer a promising solution to the limited accessibility of MRI. In this study, we present and evaluate the imaging capability of ULF MRI in detecting structural abnormalities typically associated with epilepsy and compare it to high‐field MRI at 3 T.Data collection was conducted within 3 consecutive weeks at the University Hospital Bonn. Inclusion criteria were a minimum age of 18 years, diagnosed epilepsy, and clinical high‐field MRI with abnormalities. We used a .064 T Swoop portable MR Imaging System. Both high‐field MRI and ULF MRI scans were evaluated independently by two experienced neuroradiologists as part of their clinical routine, comparing pathology detection and diagnosis completeness.Twenty‐three individuals with epilepsy were recruited. One subject presented with a dual pathology. Across the entire cohort, in 17 of 24 (71%) pathologies, an anomaly colocalizing with the actual lesion was observed on ULF MRI. For 11 of 24 (46%) pathologies, the full diagnosis could be made based on ULF MRI. Tumors and posttraumatic lesions could be diagnosed best on ULF MRI, whereas cortical dysplasia and other focal pathologies were the least well diagnosed.This single‐center series of individuals with epilepsy demonstrates the feasibility and utility of ULF MRI for the field of epileptology. Its integration into epilepsy care offers transformative potential, particularly in resource‐limited settings. Further research is needed to position ULF MRI within imaging modalities in the diagnosis of epilepsy. [ABSTRACT FROM AUTHOR]

Optoacoustic imaging offers label‐free multi‐parametric characterization of cerebrovascular morphology and hemodynamics at depths and spatiotemporal resolution unattainable with optical microscopy. Effective imaging depth can greatly be enhanced by employing photons in the second near‐infrared (NIR‐II) window. However, diminished absorption by hemoglobin along with a lack of suitable contrast agents hinder an efficient application of the technique in this spectral range. Herein, copper sulfide (CuS) micro‐ and nano‐formulations for multi‐scale optoacoustic imaging in the NIR‐II window are introduced. Dynamic contrast enhancement induced by intravenously administered CuS nanoparticles facilitated visualization of blood perfusion in murine cerebrovascular networks. The individual calcium carbonate microparticles carrying CuS are further shown to generate sufficient responses to enable super‐resolution microvascular imaging and blood flow velocity mapping with localization optoacoustic tomography. [ABSTRACT FROM AUTHOR]

Conclusion As recently as the 1980s, it was not uncommon for paediatric surgeons to operate on infants without anaesthesia. Today, the same omission would be considered criminal malpractice, and there is an increased concern with the possibility of consciousness in the earliest stage of human infancy. This concern reflects a more general trend that has characterised science since the early 1990s of taking consciousness seriously. While this attitude shift has opened minds towards the possibility that our earliest experiences predate our first memories, convincing demonstrations of infant consciousness remain challenging given that infants cannot report on their experiences. Furthermore, while many behavioural and neural markers of consciousness that do not rely on language have been validated in adults, no one specific marker can be confidently translated to infancy. For this reason, we have proposed the ‘cluster‐based’ approach, in which a consensus of evidence across many markers, all pointing towards the same developmental period, could be used to argue convincingly for the presence of consciousness.We review the most promising markers for early consciousness, arguing that consciousness is likely to be in place by 5 months of age if not earlier. [ABSTRACT FROM AUTHOR]

Neuroimaging studies in rapid eye movement sleep behavior disorder (RBD) can inform fundamental questions about the pathogenesis of Parkinson's disease (PD). Across modalities, functional magnetic resonance imaging (fMRI) may be better suited to identify changes between neural networks in the earliest stages of Lewy body diseases when structural changes may be subtle or absent. This review synthesizes the findings from all fMRI studies of RBD to gain further insight into the pathophysiology and progression of Lewy body diseases. A total of 32 studies were identified using a systematic review conducted according to PRISMA guidelines between January 2000 to February 2024 for original fMRI studies in patients with either isolated RBD (iRBD) or RBD secondary to PD. Common functional alterations were detectable in iRBD patients compared with healthy controls across brainstem nuclei, basal ganglia, frontal and occipital lobes, and whole brain network measures. Patients with established PD and RBD demonstrated decreased functional connectivity across the whole brain and brainstem nuclei, but increased functional connectivity in the cerebellum and frontal lobe compared with those PD patients without RBD. Finally, longitudinal changes in resting state functional connectivity were found to track with disease progression. Currently, fMRI studies in RBD have demonstrated early signatures of neurodegeneration across both motor and non‐motor pathways. Although more work is needed, such findings have the potential to inform our understanding of disease, help to distinguish between prodromal PD and prodromal dementia with Lewy bodies, and support the development of fMRI‐based outcome measures of phenoconversion and progression in future disease modifying trials. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

Laryngeal dystonia (LD) is an isolated, task‐specific, focal dystonia characterized by intermittent spasms of laryngeal muscles impairing speech production. Although recent studies have demonstrated neural alterations in LD, the consistency of findings across studies is not well‐established, limiting their translational applicability. We conducted a systematic literature search to identify studies reporting stereotactic coordinates of peak structural and functional abnormalities in LD patients compared to healthy controls, followed by a coordinate‐based activation likelihood estimation meta‐analysis. A total of 21 functional and structural neuroimaging studies, including 31 experiments in 521 LD patients and 448 healthy controls, met the study inclusion criteria. The multimodal meta‐analysis of these studies identified abnormalities in the bilateral primary motor cortices, the left inferior parietal lobule and striatum, the right insula, and the supplementary motor area in LD patients compared to healthy controls. The meta‐analytical findings reinforce the current view of dystonia as a neural network disorder and consolidate evidence for future investigations probing these targets with new therapies. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Neuroanatomical normative modeling captures individual variability in Alzheimer's disease (AD). Here we used normative modeling to track individuals' disease progression in people with mild cognitive impairment (MCI) and patients with AD. METHODS: Cortical and subcortical normative models were generated using healthy controls (n ≈ 58k). These models were used to calculate regional z scores in 3233 T1‐weighted magnetic resonance imaging time‐series scans from 1181 participants. Regions with z scores < –1.96 were classified as outliers mapped on the brain and summarized by total outlier count (tOC). RESULTS: tOC increased in AD and in people with MCI who converted to AD and also correlated with multiple non‐imaging markers. Moreover, a higher annual rate of change in tOC increased the risk of progression from MCI to AD. Brain outlier maps identified the hippocampus as having the highest rate of change. DISCUSSION: Individual patients' atrophy rates can be tracked by using regional outlier maps and tOC. Highlights: Neuroanatomical normative modeling was applied to serial Alzheimer's disease (AD) magnetic resonance imaging (MRI) data for the first time.Deviation from the norm (outliers) of cortical thickness or brain volume was computed in 3233 scans.The number of brain‐structure outliers increased over time in people with AD.Patterns of change in outliers varied markedly between individual patients with AD.People with mild cognitive impairment whose outliers increased over time had a higher risk of progression from AD. [ABSTRACT FROM AUTHOR]

The COVID pandemic has shown that when the research community comes together, we can conquer the most complex biomedical challenges. Collaboration and teamwork among federal agencies, private organizations, and researchers have been crucial in the development of vaccines and therapeutics against COVID. Possibly the first example of such cross‐functional collaboration is the Alzheimer's Disease Neuroimaging Initiative (ADNI), the largest and longest continually monitored Alzheimer's study. ADNI was designed and operated as a public‐private partnership, managed by the Foundation for the National Institutes of Health. This article shows how recent successes in the Alzheimer's field are directly a result of ADNI's open and transparent sharing of knowledge, expertise, and resources, which have allowed researchers to advance their understanding of Alzheimer's and tackle challenges in a relatively short period of time. ADNI's approach to open‐source innovation also served as a model for addressing other complex diseases and led to numerous collaborative research initiatives. Highlights: The Alzheimer's Disease Neuroimaging Initiative (ADNI) was designed, structured, and operated as a public‐private partnership, managed by the Foundation for the National Institutes of Health.The recent successes in the Alzheimer's field are directly a result of ADNI's efforts.Open and transparent sharing of knowledge, expertise, and resources allowed researchers to advance their understanding of Alzheimer's and tackle challenges in a relatively short period of time. [ABSTRACT FROM AUTHOR]

Background: Pathophysiological changes of Huntington's disease (HD) can precede symptom onset by decades. Robust imaging biomarkers are needed to monitor HD progression, especially before the clinical onset. Purpose: To investigate iron dysregulation and microstructure alterations in subcortical regions as HD imaging biomarkers, and to associate such alterations with motor and cognitive impairments. Study Type: Prospective. Population: Fourteen individuals with premanifest HD (38.0 ± 11.0 years, 9 females; far‐from‐onset N = 6, near‐onset N = 8), 21 manifest HD patients (49.1 ± 12.1 years, 11 females), and 33 age‐matched healthy controls (43.9 ± 12.2 years, 17 females). Field Strength/Sequence: 7 T, T1‐weighted imaging, quantitative susceptibility mapping, and diffusion tensor imaging. Assessment: Volume, susceptibility, fractional anisotropy (FA), and mean diffusivity (MD) within subcortical brain structures were compared across groups, used to establish HD classification models, and correlated to clinical measures and cognitive assessments. Statistical Tests: Generalized linear model, multivariate logistic regression, receiver operating characteristics with the area under the curve (AUC), and likelihood ratio test comparing a volumetric model to one that also includes susceptibility and diffusion metrics, Wilcoxon paired signed‐rank test, and Pearson's correlation. A P‐value <0.05 after Benjamini–Hochberg correction was considered statistically significant. Results: Significantly higher striatal susceptibility and FA were found in premanifest and manifest HD preceding atrophy, even in far‐from‐onset premanifest HD compared to controls (putamen susceptibility: 0.027 ± 0.022 vs. 0.018 ± 0.013 ppm; FA: 0.358 ± 0.048 vs. 0.313 ± 0.039). The model with additional susceptibility, FA, and MD features showed higher AUC compared to volume features alone when differentiating premanifest HD from HC (0.83 vs. 0.66), and manifest from premanifest HD (0.94 vs. 0.83). Higher striatal susceptibility significantly correlated with cognitive deterioration in HD (executive function: r = −0.600; socioemotional function: r = −0.486). Data Conclusion: 7 T MRI revealed iron dysregulation and microstructure alterations with HD progression, which could precede volume loss, provide added value to HD differentiation, and might be associated with cognitive changes. Evidence Level: 2 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

Purpose: To develop a new sequence to simultaneously acquire Cartesian sodium (23Na) MRI and accelerated Cartesian single (SQ) and triple quantum (TQ) sodium MRI of in vivo human brain at 7 T by leveraging two dedicated low‐rank reconstruction frameworks. Theory and Methods: The Double Half‐Echo technique enables short echo time Cartesian 23Na MRI and acquires two k‐space halves, reconstructed by a low‐rank coupling constraint. Additionally, three‐dimensional (3D) 23Na Multi‐Quantum Coherences (MQC) MRI requires multi‐echo sampling paired with phase‐cycling, exhibiting a redundant multidimensional space. Simultaneous Autocalibrating and k‐Space Estimation (SAKE) were used to reconstruct highly undersampled 23Na MQC MRI. Reconstruction performance was assessed against five‐dimensional (5D) CS, evaluating structural similarity index (SSIM), root mean squared error (RMSE), signal‐to‐noise ratio (SNR), and quantification of tissue sodium concentration and TQ/SQ ratio in silico, in vitro, and in vivo. Results: The proposed sequence enabled the simultaneous acquisition of fully sampled 23Na MRI while leveraging prospective undersampling for 23Na MQC MRI. SAKE improved TQ image reconstruction regarding SSIM by 6% and reduced RMSE by 35% compared to 5D CS in vivo. Thanks to prospective undersampling, the spatial resolution of 23Na MQC MRI was enhanced from 8×8×15$$ 8\times 8\times 15 $$ mm3 to 8×8×8$$ 8\times 8\times 8 $$ mm3 while reducing acquisition time from 2×31$$ 2\times 31 $$ min to 2×23$$ 2\times 23 $$ min. Conclusion: The proposed sequence, coupled with low‐rank reconstructions, provides an efficient framework for comprehensive whole‐brain sodium MRI, combining TSC, T2*, and TQ/SQ ratio estimations. Additionally, low‐rank matrix completion enables the reconstruction of highly undersampled 23Na MQC MRI, allowing for accelerated acquisition or enhanced spatial resolution. [ABSTRACT FROM AUTHOR]

Neonatal infection with herpes simplex virus (HSV) is associated with significant morbidity, high mortality, and long‐term neurological sequelae. We report the clinical case of an infant with HSV encephalitis, where the initial diagnosis was established based on cranial ultrasound (CUS) findings. These findings revealed localized, asymmetrically distributed hyperechoic areas in the parenchyma and signs of brain swelling. CUS dynamics on days 7 and 14 after the onset of clinical symptoms demonstrated multiple subcortical and perivascular zones of encephalomalacia in the right hemisphere, accompanied by ex vacuo ventricular dilatation. The cerebellum, left basal ganglia, and left hemisphere appeared to be less affected by the pathological process. [ABSTRACT FROM AUTHOR]

Summary This study aimed to examine the improvement in performance and functional magnetic resonance imaging correlates of motor learning after a daytime nap versus a period of resting wakefulness among individuals with traumatic brain injury. A sample of 32 individuals with traumatic brain injury was randomly assigned to a Sleep (N = 17) or Wake (N = 15) group after a period of training on a motor sequential learning task. A 45‐min nap opportunity was provided for the Sleep group, while the Wake group watched a documentary for 45 min. Performance at the end of training was compared with their performance after the nap or wake intervention. Before and after the intervention, the motor sequential learning task was completed in the magnetic resonance imaging scanner to examine the relationship between change in performance and neural activation. Participants in the Sleep group showed significant gains from the end of training to after the intervention, whereas the Wake group did not. The functional magnetic resonance imaging results showed that relative to the Wake group, the Sleep group showed significantly decreased activation post‐intervention in the anterior cingulate/paracingulate, cerebellum, cuneus/precuneus, and inferior parietal lobule including angular and supramarginal gyri. Importantly, across both groups, increased task performance at post‐intervention was associated with decreased activation in the anterior cingulate/paracingulate and cerebellum. This study demonstrated the enhancing effect of a nap on motor learning performance in a sample of individuals with traumatic brain injury, with patterns of neural activation suggesting that the sequence was more automatized in the Sleep group. Strategic placement of a nap after an intense period of motor learning in the medical rehabilitation setting may have important implications for maximizing recovery after traumatic brain injury. [ABSTRACT FROM AUTHOR]

In recent years, many neuroimaging studies have applied artificial intelligence (AI) to facilitate existing challenges in Parkinson's disease (PD) diagnosis, prognosis, and intervention. The aim of this systematic review was to provide an overview of neuroimaging‐based AI studies and to assess their methodological quality. A PubMed search yielded 810 studies, of which 244 that investigated the utility of neuroimaging‐based AI for PD diagnosis, prognosis, or intervention were included. We systematically categorized studies by outcomes and rated them with respect to five minimal quality criteria (MQC) pertaining to data splitting, data leakage, model complexity, performance reporting, and indication of biological plausibility. We found that the majority of studies aimed to distinguish PD patients from healthy controls (54%) or atypical parkinsonian syndromes (25%), whereas prognostic or interventional studies were sparse. Only 20% of evaluated studies passed all five MQC, with data leakage, non‐minimal model complexity, and reporting of biological plausibility as the primary factors for quality loss. Data leakage was associated with a significant inflation of accuracies. Very few studies employed external test sets (8%), where accuracy was significantly lower, and 19% of studies did not account for data imbalance. Adherence to MQC was low across all observed years and journal impact factors. This review outlines that AI has been applied to a wide variety of research questions pertaining to PD; however, the number of studies failing to pass the MQC is alarming. Therefore, we provide recommendations to enhance the interpretability, generalizability, and clinical utility of future AI applications using neuroimaging in PD. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

Alcohol exposure affects brain structure, but the extent to which its effects differ across development remains unclear. Several countries are considering changes to recommended guidelines for alcohol consumption, so high‐quality evidence is needed. Many studies have been conducted among small samples, but recent efforts have been made to acquire large samples to characterize alcohol's effects on the brain on a population level. Several large‐scale consortia have acquired such samples, but this evidence has not been synthesized across the lifespan. We conducted a systematic review of large‐scale neuroimaging studies examining effects of alcohol exposure on brain structure at multiple developmental stages. We included studies with an alcohol‐exposed sample of at least N = 100 from the following consortia: ABCD, ENIGMA, NCANDA, IMAGEN, Framingham Offspring Study, HCP and UK BioBank. Twenty‐seven studies were included, examining prenatal (N = 1), adolescent (N = 9), low‐to‐moderate‐level adult (N = 11) and heavy adult (N = 7) exposure. Prenatal exposure was associated with greater brain volume at ages 9–10, but contemporaneous alcohol consumption during adolescence and adulthood was associated with smaller volume/thickness. Both low‐to‐moderate consumption and heavy consumption were characterized by smaller volume and thickness in frontal, temporal and parietal regions, and reductions in insula, cingulate and subcortical structures. Adolescent consumption had similar effects, with less consistent evidence for smaller cingulate, insula and subcortical volume. In sum, prenatal exposure was associated with larger volume, while adolescent and adult alcohol exposure was associated with smaller volume and thickness, suggesting that regional patterns of effects of alcohol are similar in adolescence and adulthood. This systematic review of large‐scale neuroimaging studies examining the effects of alcohol exposure on brain structure across multiple developmental stages showed that adult alcohol consumption was characterized by smaller volume and thickness in frontal, temporal, and parietal regions, and reductions in insula, cingulate, and subcortical structures. Adolescent alcohol consumption had similar effects, but with less consistent evidence for smaller cingulate, insula, and subcortical volume. This suggests that regional patterns of effects of alcohol are similar in adolescence and adulthood. [ABSTRACT FROM AUTHOR]

Pelizaeus‐Merzbacher disease (PMD) is a rare childhood hypomyelinating leukodystrophy. Quantification of the pronounced myelin deficit and delineation of subtle myelination processes are of high clinical interest. Quantitative magnetic resonance imaging (qMRI) techniques can provide in vivo insights into myelination status, its spatial distribution, and dynamics during brain maturation. They may serve as potential biomarkers to assess the efficacy of myelin‐modulating therapies. However, registration techniques for image quantification and statistical comparison of affected pediatric brains, especially those of low or deviant image tissue contrast, with healthy controls are not yet established. This study aimed first to develop and compare postprocessing pipelines for atlas‐based quantification of qMRI data in pediatric patients with PMD and evaluate their registration accuracy. Second, to apply an optimized pipeline to investigate spatial myelin deficiency using myelin water imaging (MWI) data from patients with PMD and healthy controls. This retrospective single‐center study included five patients with PMD (mean age, 6 years ± 3.8) who underwent conventional brain MRI and diffusion tensor imaging (DTI), with MWI data available for a subset of patients. Three methods of registering PMD images to a pediatric template were investigated. These were based on (a) T1‐weighted (T1w) images, (b) fractional anisotropy (FA) maps, and (c) a combination of T1w, T2‐weighted, and FA images in a multimodal approach. Registration accuracy was determined by visual inspection and calculated using the structural similarity index method (SSIM). SSIM values for the registration approaches were compared using a t test. Myelin water fraction (MWF) was quantified from MWI data as an assessment of relative myelination. Mean MWF was obtained from two PMDs (mean age, 3.1 years ± 0.3) within four major white matter (WM) pathways of a pediatric atlas and compared to seven healthy controls (mean age, 3 years ± 0.2) using a Mann–Whitney U test. Our results show that visual registration accuracy estimation and computed SSIM were highest for FA‐based registration, followed by multimodal, and T1w‐based registration (SSIMFA = 0.67 ± 0.04 vs. SSIMmultimodal = 0.60 ± 0.03 vs. SSIMT1 = 0.40 ± 0.14). Mean MWF of patients with PMD within the WM pathways was significantly lower than in healthy controls MWFPMD = 0.0267 ± 0.021 vs. MWFcontrols = 0.1299 ± 0.039. Specifically, MWF was measurable in brain structures known to be myelinated at birth (brainstem) or postnatally (projection fibers) but was scarcely detectable in other brain regions (commissural and association fibers). Taken together, our results indicate that registration accuracy was highest with an FA‐based registration pipeline, providing an alternative to conventional T1w‐based registration approaches in the case of hypomyelinating leukodystrophies missing normative intrinsic tissue contrasts. The applied atlas‐based analysis of MWF data revealed that the extent of spatial myelin deficiency in patients with PMD was most pronounced in commissural and association and to a lesser degree in brainstem and projection pathways. [ABSTRACT FROM AUTHOR]

Theories of adolescent development suggest that elevated neural sensitivity to social evaluation confers tradeoffs for adolescents' wellbeing, promoting adaptation to changing social contexts but increasing risk for emotional distress and depression. This study investigated whether the association between neural processing of peer feedback and depressive symptoms depends on teacher‐reported executive function (EF) ability in adolescent girls. Girls showed activation to negative and positive peer feedback in regions implicated in social–emotional processing that interacted with EF to predict depressive symptoms. Specifically, activation predicted more depression in youth with poorer EF but less depression in youth with better EF, suggesting that the impact of increased social sensitivity may depend on youths' ability to regulate this sensitivity in adaptive ways. [ABSTRACT FROM AUTHOR]

Intracranial and spinal subdural empyema was presumptively diagnosed in a 2-yearold golden retriever secondary to periorbital abscesses. The patient initially presented to the referring veterinarian for right eye conjunctivitis, intermittent left head turn and reluctance to eat on the left side. The patient then suffered neck trauma from a rope, developing neck pain, left-sided conscious proprioceptive deficits and rightsided Horner's syndrome. Most signs resolved with medical management at the referring veterinarian, but neck pain persisted. Severe acute neurological deterioration occurred before presentation at our hospital, culminating in decerebrate rigidity and opisthotonos. Neurological exam revealed multifocal intracranial disease. Magnetic resonance imaging showed periorbital abscesses and extensive intracranial and cervical spinal subdural empyema. The owners elected for euthanasia and declined postmortem examination. Cerebrospinal fluid sampled immediately postmortem confirmed empyema. This is the first report of a presumed case of intracranial and cervical spine subdural empyema caused by periorbital abscesses in a dog. [ABSTRACT FROM AUTHOR]

We report on a previously healthy zoo specimen of an adult budgerigar (Melopsittacus undulatus, obtainedwithpermission fromSouthwick'sZoo) founddeceased in its enclosure. To assess cause of death and ensure the absence of an infectious neoplasia, we used an integrated multiscale brain-imaging workflow, previously only used on mammals. The specimen was imaged with microcomputed tomography before and after enhancing soft-tissue contrast with diffusible iodine-based contrast-enhanced microcomputed tomography. Scans revealed an orbital blowout fracture and an unidentified large mass across majority of the diencephalon, striatum and midbrain caudal to the right orbit. After destaining, neural pathohistology confirmed the mass as a brain haemorrhage with no evidence of neoplasia or inflammation. We conclude that this specimen died of head trauma, likely from a head-on collision within its enclosure. This multiscale imaging workflow (diffusible iodine-based contrast-enhanced microcomputed tomography followed by destaining and pathohistology) can improve our evaluation of differential diagnoses in avian specimens. [ABSTRACT FROM AUTHOR]

Purpose: To assess the impact of different B0 shimming algorithms on MRS. Methods: B0 field maps and single‐voxel MR spectroscopy were acquired in the prefrontal cortex of five volunteers at 3 T using five different B0 shimming approaches. B0 shimming was achieved using Siemens' proprietary shim algorithm, in addition to the Pseudo‐Inverse (PI), Quadratic Programming (QuadProg), Least Squares (LSq), and Gradient optimization (Grad) algorithms. The standard deviation of the shimmed B0 field, as well as the SNR and FWHM of the measured metabolites, was used to evaluate the performance of each B0 shimming algorithm. Results: Compared to Siemens's shim, significant reductions (p < 0.01) in the standard deviation of the B0 field distribution within the MRS voxel were observed for the PI, QuadProg, and Grad algorithms (3.8 Hz, 7.3 Hz, and 3.9 Hz respectively, compared to 11.5 Hz for Siemens), but not for the LSq (12.9 Hz) algorithm. Moreover, significantly increased SNR and reduced FWHM for the N‐acetylaspartate metabolite were consistent with the improvement in B0 homogeneity for the aforementioned shimming algorithms. Conclusion: Here, we demonstrate that the choice of B0 shimming algorithm can have a significant impact on the quality of MR spectra and that significant improvements in spectrum quality could be achieved by using alternatives to the default vendor approach. [ABSTRACT FROM AUTHOR]

Background and Purpose: Obstructive sleep apnea is associated with increased dementia risk. Nocturnal hypoxemia, which can be more severe during rapid eye movement (REM) sleep, may be a key mechanism. This study examines how REM hypoxemia affects memory and explores whether hippocampal vulnerability to hypoxemia mediates this effect in older adults at risk for dementia. Methods: Older adults aged ≥50 years (N = 338) with subjective or mild cognitive impairment (i.e., objective impairment) underwent neuropsychological, mood, and medical assessment, magnetic resonance imaging scanning (n = 135), and overnight polysomnography. Verbal learning and memory were assessed with the Rey Auditory Verbal Learning Test. REM sleep hypoxemia was measured using the Oxygen Desaturation Index‐3% (REM‐ODI). Hippocampal subfield (CA1, CA3, subiculum, and dentate gyrus) volumes were derived from T1 and high‐resolution hippocampus T2 scans. We determined whether the relationship between REM‐ODI and learning and memory was mediated by hippocampal subfield volume. Analyses were repeated in non‐REM sleep to determine whether the effects were REM‐specific. Results: Although there was not a direct effect of REM‐ODI on verbal learning (p > 0.05) or memory (p > 0.05), mediation analyses showed a significant indirect effect of high REM‐ODI on poorer verbal learning (β = −0.09, 95% confidence interval [CI] = −0.238 to −0.005) and memory (β = −0.100, 95% CI = −0.255 to −0.005), which was mediated by CA1 volume. These associations were absent in non‐REM sleep (p > 0.05). Conclusions: Hypoxemia during REM sleep may impair memory in people at risk for dementia by reducing CA1 hippocampal volume. Research is needed to explore whether interventions targeting REM sleep hypoxemia are protective against memory decline. [ABSTRACT FROM AUTHOR]

Background and Purpose: Myoclonus dystonia due to a pathogenic variant in SGCE (MYC/DYT‐SGCE) is a rare condition involving a motor phenotype associating myoclonus and dystonia. Dysfunction within the networks relying on the cortex, cerebellum, and basal ganglia was presumed to underpin the clinical manifestations. However, the microarchitectural abnormalities within these structures and related pathways are unknown. Here, we investigated the microarchitectural brain abnormalities related to the motor phenotype in MYC/DYT‐SGCE. Methods: We used neurite orientation dispersion and density imaging, a multicompartment tissue model of diffusion neuroimaging, to compare microarchitectural neurite organization in MYC/DYT‐SGCE patients and healthy volunteers (HVs). Neurite density index (NDI), orientation dispersion index (ODI), and isotropic volume fraction (ISOVF) were derived and correlated with the severity of motor symptoms. Fractional anisotropy (FA) and mean diffusivity (MD) derived from the diffusion tensor approach were also analyzed. In addition, we studied the pathways that correlated with motor symptom severity using tractography analysis. Results: Eighteen MYC/DYT‐SGCE patients and 24 HVs were analyzed. MYC/DYT‐SGCE patients showed an increase of ODI and a decrease of FA within their motor cerebellum. More severe dystonia was associated with lower ODI and NDI and higher FA within motor cerebellar cortex, as well as with lower NDI and higher ISOVF and MD within the corticopontocerebellar and spinocerebellar pathways. No association was found between myoclonus severity and diffusion parameters. Conclusions: In MYC/DYT‐SGCE, we found microstructural reorganization of the motor cerebellum. Structural change in the cerebellar afferent pathways that relay inputs from the spinal cord and the cerebral cortex were specifically associated with the severity of dystonia. [ABSTRACT FROM AUTHOR]

Background: Movement disorders such as Parkinson's disease are associated with structural and functional changes in specific brain regions. Advanced magnetic resonance imaging (MRI) techniques combined with machine learning (ML) are promising tools for identifying imaging biomarkers and patterns associated with these disorders. Purpose/Hypothesis: We aimed to systematically identify the brain regions most commonly affected in movement disorders using ML approaches applied to structural and functional MRI data. We searched the PubMed and Scopus databases using relevant keywords up to June 2023 for studies that used ML approaches to detect brain regions associated with movement disorders using MRI data. Study Type: A systematic review and diagnostic meta‐analysis. Population/Subjects: Sixty‐seven studies with 6,285 patients were included. Field Strength/Sequence: Studies utilizing 1.5T or 3T MR scanners and the acquisition of diffusion tensor imaging (DTI), structural MRI (sMRI), functional MRI (fMRI), or a combination of these were included. Assessment: The authors independently assessed the study quality using the CLAIM and QUADAS‐2 criteria and extracted data on diagnostic accuracy measures. Statistical Tests: Sensitivity, specificity, accuracy, and area under the curve were pooled using random‐effects models. Q statistics and the I2 index were used to evaluate heterogeneity, and Begg's funnel plot was used to identify publication bias. Results: sMRI showed the highest sensitivity (93%) and mixed modalities had the highest specificity (90%) for detecting regional abnormalities. sMRI had a 94% sensitivity for identifying subcortical changes. The support vector machine (93%) and logistic regression (91%) models exhibited high diagnostic accuracies. Data Conclusion: The combination of advanced MR neuroimaging techniques and ML is a promising approach for identifying brain biomarkers and affected regions in movement disorders with subcortical structures frequently implicated. Structural MRI, in particular, showed strong performance. Level of Evidence: 1 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

Among the approximately 20 million patients with drug‐resistant epilepsy (DRE) worldwide, the vast majority can benefit from surgery to minimize seizure reduction and neurological impairment. Precise preoperative localization of epileptogenic zone (EZ) and complete resection of the lesions can influence the postoperative prognosis. However, precise localization of EZ is difficult, and the structural and functional alterations in the brain caused by DRE vary by etiology. Neuroimaging has emerged as an approach to identify the seizure‐inducing structural and functional changes in the brain, and magnetic resonance imaging (MRI) and positron emission tomography (PET) have become routine noninvasive imaging tools for preoperative evaluation of DRE in many epilepsy treatment centers. Multimodal neuroimaging offers unique advantages in detecting EZ, especially in improving the detection rate of patients with negative MRI or PET findings. This approach can characterize the brain imaging characteristics of patients with DRE caused by different etiologies, serving as a bridge between clinical and pathological findings and providing a basis for individualized clinical treatment plans. In addition to the integration of multimodal imaging modalities and the development of special scanning sequences and image post‐processing techniques for early and precise localization of EZ, the application of deep machine learning for extracting image features and deep learning‐based artificial intelligence have gradually improved diagnostic efficiency and accuracy. These improvements can provide clinical assistance for precisely outlining the scope of EZ and indicating the relationship between EZ and functional brain areas, thereby enabling standardized and precise surgery and ensuring good prognosis. However, most existing studies have limitations imposed by factors such as their small sample sizes or hypothesis‐based study designs. Therefore, we believe that the application of neuroimaging and post‐processing techniques in DRE requires further development and that more efficient and accurate imaging techniques are urgently needed in clinical practice. Level of Evidence: 5 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

Deployment of new, more portable, and less costly neuroimaging technologies such as portable magnetoencephalography, electroencephalography, positron emission tomography, functional near‐infrared spectroscopy, high‐density diffuse optical tomography, and magnetic resonance imaging is advancing rapidly. Given this trajectory toward increasing use of neuroimaging outside the hospital, we sought to identify ethical, legal, and societal implications (ELSI) of these new technologies by understanding the perspectives of those scientists and engineers developing and implementing portable neuroimaging technologies in the United States, Europe, and Asia. Based on a literature review, we identified and contacted 19 potential interviewees and then conducted 11 semi‐structured interviews in English by Zoom. Analysis of the interviews revealed key themes and ELSI issues. Developers reported that without proper ELSI guidance, portable and accessible neuroimaging technology could be misused, fail to comply with applicable regulation and policy, and ultimately fall short in its mission to provide neuroimaging for the world. Our interviews suggested that ELSI guidance should address differences between imaging modalities because they vary in capability, limitations, and likelihood of generating incidental findings. [ABSTRACT FROM AUTHOR]

Electroencephalography (EEG) is a technique for non‐invasively measuring neuronal activity in the human brain using electrodes placed on the participant's scalp. With the advancement of digital technologies, EEG analysis has evolved over time from the qualitative analysis of amplitude and frequency modulations to a comprehensive analysis of the complex spatiotemporal characteristics of the recorded signals. EEG is now considered a powerful tool for measuring neural processes in the same time frame in which they happen (i.e. the subsecond range). However, it is commonly argued that EEG suffers from low spatial resolution, which makes it difficult to localize the generators of EEG activity accurately and reliably. Today, the availability of high‐density EEG (hdEEG) systems, combined with methods for incorporating information on head anatomy and sophisticated source‐localization algorithms, has transformed EEG into an important neuroimaging tool. hdEEG offers researchers and clinicians a rich and varied range of applications. It can be used not only for investigating neural correlates in motor and cognitive neuroscience experiments, but also for clinical diagnosis, particularly in the detection of epilepsy and the characterization of neural impairments in a wide range of neurological disorders. Notably, the integration of hdEEG systems with other physiological recordings, such as kinematic and/or electromyography data, might be especially beneficial to better understand the neuromuscular mechanisms associated with deconditioning in ageing and neuromotor disorders, by mapping the neurokinematic and neuromuscular connectivity patterns directly in the brain. [ABSTRACT FROM AUTHOR]

Computationally expensive data processing in neuroimaging research places demands on energy consumption—and the resulting carbon emissions contribute to the climate crisis. We measured the carbon footprint of the functional magnetic resonance imaging (fMRI) preprocessing tool fMRIPrep, testing the effect of varying parameters on estimated carbon emissions and preprocessing performance. Performance was quantified using (a) statistical individual‐level task activation in regions of interest and (b) mean smoothness of preprocessed data. Eight variants of fMRIPrep were run with 257 participants who had completed an fMRI stop signal task (the same data also used in the original validation of fMRIPrep). Some variants led to substantial reductions in carbon emissions without sacrificing data quality: for instance, disabling FreeSurfer surface reconstruction reduced carbon emissions by 48%. We provide six recommendations for minimising emissions without compromising performance. By varying parameters and computational resources, neuroimagers can substantially reduce the carbon footprint of their preprocessing. This is one aspect of our research carbon footprint over which neuroimagers have control and agency to act upon. [ABSTRACT FROM AUTHOR]

Background: Using 11C‐(R)‐PK11195‐PET, we found increased microglia activation in isolated REM sleep behavior disorder (iRBD) patients. Their role remains to be clarified. Objectives: The objective is to assess relationships between activated microglia and progression of nigrostriatal dysfunction in iRBD. Methods: Fifteen iRBD patients previously scanned with 11C‐(R)‐PK11195 and 18F‐DOPA‐PET underwent repeat 18F‐DOPA‐PET after 3 years. 18F‐DOPA Ki changes from baseline were evaluated with volumes‐of‐interest and voxel‐based analyses. Results: Significant 18F‐DOPA Ki reductions were found in putamen and caudate. Reductions were larger and more widespread in patients with increased nigral microglia activation at baseline. Left nigral 11C‐(R)‐PK11195 binding at baseline was a predictor of 18F‐DOPA Ki reduction in left caudate (coef = −0.0426, P = 0.016). Conclusions: Subjects with increased baseline 11C‐(R)‐PK11195 binding have greater changes in nigrostriatal function, suggesting a detrimental rather than protective effect of microglial activation. Alternatively, both phenomena occur in patients with prominent nigrostriatal dysfunction without a causative link. The clinical and therapeutic implications of these findings need further elucidation. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

Aim: Physical activity (PA) is a key component for brain health and Reserve, and it is among the main dementia protective factors. However, the neurobiological mechanisms underpinning Reserve are not fully understood. In this regard, a noradrenergic (NA) theory of cognitive reserve (Robertson, 2013) has proposed that the upregulation of NA system might be a key factor for building reserve and resilience to neurodegeneration because of the neuroprotective role of NA across the brain. PA elicits an enhanced catecholamine response, in particular for NA. By increasing physical commitment, a greater amount of NA is synthetised in response to higher oxygen demand. More physically trained individuals show greater capabilities to carry oxygen resulting in greater Vo2max – a measure of oxygen uptake and physical fitness (PF). Methods: We hypothesized that greater Vo2max would be related to greater Locus Coeruleus (LC) MRI signal intensity. In a sample of 41 healthy subjects, we performed Voxel‐Based Morphometry analyses, then repeated for the other neuromodulators as a control procedure (Serotonin, Dopamine and Acetylcholine). Results: As hypothesized, greater Vo2max related to greater LC signal intensity, and weaker associations emerged for the other neuromodulators. Conclusion: This newly established link between Vo2max and LC–NA system offers further understanding of the neurobiology underpinning Reserve in relationship to PA. While this study supports Robertson's theory proposing the upregulation of the NA system as a possible key factor building Reserve, it also provides ground for increasing LC–NA system resilience to neurodegeneration via Vo2max enhancement. [ABSTRACT FROM AUTHOR]

Neuroimaging data acquired using multiple scanners or protocols are increasingly available. However, such data exhibit technical artifacts across batches which introduce confounding and decrease reproducibility. This is especially true when multi‐batch data are analyzed using complex downstream models which are more likely to pick up on and implicitly incorporate batch‐related information. Previously proposed image harmonization methods have sought to remove these batch effects; however, batch effects remain detectable in the data after applying these methods. We present DeepComBat, a deep learning harmonization method based on a conditional variational autoencoder and the ComBat method. DeepComBat combines the strengths of statistical and deep learning methods in order to account for the multivariate relationships between features while simultaneously relaxing strong assumptions made by previous deep learning harmonization methods. As a result, DeepComBat can perform multivariate harmonization while preserving data structure and avoiding the introduction of synthetic artifacts. We apply this method to cortical thickness measurements from a cognitive‐aging cohort and show DeepComBat qualitatively and quantitatively outperforms existing methods in removing batch effects while preserving biological heterogeneity. Additionally, DeepComBat provides a new perspective for statistically motivated deep learning harmonization methods. [ABSTRACT FROM AUTHOR]

Background: Dysfunction in the autonomic nervous system is common throughout many functional gastrointestinal diseases (FGIDs) that have been historically difficult to treat. In recent years, transcutaneous vagal nerve stimulation (tVNS) has shown promise for improving FGID symptoms. However, the brain effects of tVNS remain unclear, which we investigated by neuroimaging meta‐analysis. Methods: A total of 157 studies were identified, 4 of which were appropriate for inclusion, encompassing 60 healthy human participants. Using activation likelihood analysis estimation, we statistically quantified functional brain activity changes across three domains: (1) tVNS vs. null stimulation, (2) tVNS vs. sham stimulation, and (3) sham stimulation vs. null stimulation. Key Results: tVNS significantly increased activity in the insula, anterior cingulate, inferior and superior frontal gyri, caudate and putamen, and reduced activity in the hippocampi, occipital fusiform gyri, temporal pole, and middle temporal gyri, when compared to null stimulation (all corrected p < 0.005). tVNS increased activity in the anterior cingulate gyrus, left thalamus, caudate, and paracingulate gyrus and reduced activity in right thalamus, posterior cingulate cortex, and temporal fusiform cortex, when compared to sham stimulation (all corrected p < 0.005). Sham stimulation significantly increased activity in the insula and reduced activity in the posterior cingulate and paracingulate gyrus (all corrected p < 0.001), when contrasted to null stimulation. Conclusions: Brain effects of tVNS localize to regions associated with both physiological autonomic regulation and regions whose activity is modulated across numerous FGIDs, which may provide a neural basis for efficacy of this treatment. Functional activity differences between sham and null stimulation illustrate the importance of robust control procedures for future trials. [ABSTRACT FROM AUTHOR]

Background and purpose: The Mediterranean diet (MedDiet) has been associated with reduced dementia incidence in several studies. It is important to understand if diet is associated with brain health in midlife, when Alzheimer's disease and related dementias are known to begin. Methods: This study used data from the PREVENT dementia programme. Three MedDiet scores were created (the Pyramid, Mediterranean Diet Adherence Screener [MEDAS] and MEDAS continuous) from a self‐reported food frequency questionnaire. Primary outcomes were hippocampal volume and cube‐transformed white matter hyperintensity volume. Secondary outcomes included cornu ammonis 1 and subiculum hippocampal subfield volumes, cortical thickness and measures of cognition. Sex‐stratified analyses were run to explore differential associations between diet and brain health by sex. An exploratory path analysis was conducted to study if any associations between diet and brain health were mediated by cardiovascular risk factors for dementia. Results: In all, 504 participants were included in this analysis, with a mean Pyramid score of 8.10 (SD 1.56). There were no significant associations between any MedDiet scoring method and any of the primary or secondary outcomes. There were no differences by sex in any analyses and no significant mediation between the Pyramid score and global cognition by cardiovascular risk factors. Conclusions: Overall, this study did not find evidence for an association between the MedDiet and either neuroimaging or cognition in a midlife population study. Future work should investigate associations between the MedDiet and Alzheimer's disease and related dementias biomarkers as well as functional neuroimaging in a midlife population. [ABSTRACT FROM AUTHOR]

The revised reinforcement sensitivity theory (RST) proposes that neurobiological systems control behavior: the fight‐flight‐freeze (FFFS) for avoidance of threat; behavioral approach/activation (BAS) for approach to rewards; and behavioral inhibition (BIS) for conflict resolution when avoidance and approach are possible. Neuroimaging studies have confirmed some theoretical associations between brain structures and the BAS and BIS; however, little representative population data are available for the FFFS. We investigated the neural correlates of the revised RST in a sample of 404 middle‐aged adults (Mage = 47.18 (SD = 1.38); 54.5% female). Participants underwent structural magnetic resonance imaging and completed health questionnaires and the BIS/BAS/FFFS scales. We used multiple regression analyses to investigate the association between scale scores and volumes of a priori theoretically linked regions of interest while controlling for sex, age, intracranial volume, and cardio‐metabolic variables; and conducted exploratory analyses on cortical thickness. The BIS was negatively associated with hippocampus laterality. At standard significance levels, the fear component of the FFFS was positively associated with anterior cingulate cortex; the BAS was positively associated with bilateral caudate; and the BIS was positively associated with posterior cingulate cortex volume. Furthermore, these neurobiological systems showed distinct patterns of association with cortical thickness though future work is needed. Our results showed that the neurobiological systems of the revised RST characterized in rodents can also be identified in the human brain. The revised Reinforcement Sensitivity Theory provides a comprehensive integration of neurobiology and behavior to help understand individual differences in physical and mental health, yet efforts to study the link between brain and behavior have been hampered due to inadequate measures. Using a revised and validated questionnaire, we showed that brain structure volume and cortical thickness differences are associated with each of the proposed neurobiological systems of the revised Reinforcement Sensitivity Theory. [ABSTRACT FROM AUTHOR]

Background: Although the World Health Organization recommends visible and clear warning labels about the risks of alcohol consumption on containers and advertising, many of the currently used labels are too small to be visible. This study investigated the brain activity (using fMRI) and alcohol consumption intentions of French young men exposed to two warning formats displayed on alcoholic beverage advertisements: a small Text‐only Alcohol Warning (TAW) currently used in many countries, and a larger text‐and‐picture alcohol warning (PAW). Methods: Seventy‐four eligible 18–25‐year‐old male drinkers completed a face‐to‐face individual visit with a physician expert in addiction medicine. This was followed by the fMRI session during which they viewed 288 stimuli [96 alcohol advertisements with TAWs, the same 96 advertisements with PAWs, and 96 water advertisements (controls)] for 3 s each. If the advertisement made participants want ("yes")/do not want ("no") to consume the product, they pressed the corresponding button (self‐report responses). The number of "yes" responses was compared between advertisement types with a paired sample t‐test. Whole‐brain and region‐of‐interest (ROI) analyses of the fMRI data were performed. Results: Whole‐brain BOLD fMRI highlighted contrasting effects of PAWs and TAWs. Compared with TAWs, PAWs elicited more activation in the precuneus, angular gyrus, occipital, frontal and temporal areas, and less activation in the nucleus accumbens, ventral tegmental areas, and putamen areas (regions of the reward circuit). The ROI analysis confirmed less activation in the reward circuit (left and right ventral tegmental areas, left and right nucleus accumbens) when viewing PAWs than TAWs. Analysis of the self‐report responses indicated that the desire to consume the advertised alcohol product was lower when PAWs were viewed (compared with TAWs) (T = 8.18, p < 10−11). Conclusions: This is the first fMRI study to assess the effect of different alcohol warning formats. Our findings show that compared with TAWs, stronger PAWs in advertisements elicited less activity in key regions of the reward system. This suggests that the effects may influence the desire to consume alcohol products (self‐report response analysis). These results could help policymakers who are interested in developing more effective labeling measures that target young people. [ABSTRACT FROM AUTHOR]

Background: The effect of imaging selection modality on endovascular thrombectomy (EVT) clinical outcomes in patients with acute ischemic stroke due to large vessel occlusion (AIS‐LVO) remains unclear. This study aims to compare post‐EVT outcomes in patients with AIS‐LVO who underwent basic imaging (computed tomography with or without computed tomography angiography) and advanced imaging (computed tomography perfusion or magnetic resonance imaging) in early and late time windows. Method: A systematic literature search was conducted on PubMed, Cochrane Library, and Embase databases from inception until June 10, 2023. Studies investigating the relationship between the imaging selection modality and post‐EVT outcomes in patients with AIS‐LVO were retrieved. A random‐effects model was used to pool the effect estimates of successful reperfusion, symptomatic intracranial hemorrhage (sICH), functional independence, and mortality. The meta‐analysis was performed using Review Manager software v.4.3, and the outcomes were assessed using odds ratios (ORs) and 95% confidence intervals (CIs). Result: A total of 13 non‐randomized observational studies, comprising 19,694 patients, were included in this meta‐analysis. In the early time windows, AIS‐LVO patients receiving advanced imaging demonstrated a higher likelihood of functional independence (OR, 1.25, 95% CI, 1.08–1.46) and a lower risk of mortality (OR,.73 95% CI,.61–.86) compared to those receiving basic imaging. In the extended time windows, AIS‐LVO patients undergoing advanced imaging had a lower mortality rate (OR,.79, 95% CI,.68–.92). Regardless of the time of onset, there were no significant differences between the two groups in terms of sICH or successful reperfusion. Conclusion: Advanced imaging combined with EVT may achieve better clinical outcomes in patients with AIS‐LVO. Further high‐quality studies are needed to validate these findings. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Higher neuroticism might be associated with dementia risk. Here we investigated modification by genetic predisposition to dementia, mediation by mental health and vascular conditions, neuroimaging outcomes, and cognitive function. METHODS: Cox proportional‐hazards models were used to assess the association between neuroticism score and incident dementia over up to 15 years in 1,74,164 participants. Cross‐sectional analyses on dementia‐related neuroimaging outcomes and cognitive function were conducted in 39,459 dementia‐free participants. RESULTS: Higher neuroticism was associated with an 11% higher risk of incident dementia, especially vascular dementia (15% higher risk), regardless of genetic predisposition to dementia. Mental and vascular conditions mediated the association of neuroticism with all‐cause dementia and vascular dementia. Neuroticism was associated with higher cerebrovascular pathology, lower gray matter volume, and worse function across multiple cognitive domains. DISCUSSION: Neuroticism could represent a risk factor for dementia, and vascular and mental health might drive these associations. Highlights: Neuroticism was associated with an increased risk of incident all‐cause dementia, particularly vascular dementia.Associations were not modified by genetic predisposition to dementia.Associations were largely mediated by mental and vascular conditions.Neuroticism was associated with increased cerebrovascular pathology and lower gray matter volume.Neuroticism was associated with worse function across multiple cognitive domains. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Older Black adults are at risk of cerebral small vessel disease (CSVD), which contributes to dementia risk. Two subtypes of CSVD, arteriolosclerosis and ischemic lacunar infarcts, have been independently linked to lower cognition and higher dementia risk, but their combined effects on cognition in older Black adults are unclear. METHODS: Mixed models were used to examine the associations of in vivo measures of arteriolosclerosis (ARTS) and ischemic lacunar infarcts to cognitive level and change in 370 older Black adults without dementia. RESULTS: Modeled together, higher ARTS load accounted for lower levels of global cognition, episodic memory, semantic memory, and perceptual speed, whereas higher infarct load accounted for lower levels of working memory. There were no associations with rate of cognitive change. DISCUSSION: Both arteriolosclerosis and ischemic infarcts impact the cognitive health of older Black adults, but arteriolosclerosis affects cognition more broadly and offers promise as an in vivo biomarker of dementia risk. Highlights: Older Black adults are at risk of cerebral small vessel disease (CSVD) and dementia.Examined magnetic resonance imaging‐derived measure of arteriolosclerosis (ARTS), infarcts, and cognition.ARTS load was widely associated with lower cognition after adjusting for infarct load.Infarct load was specifically associated with lower complex attention.More within‐Black in vivo studies of CSVD subtypes and cognition are needed. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Amyloid positron emission tomography (PET) acquisition timing impacts quantification. METHODS: In florbetaben (FBB) PET scans of 245 adults with and without cognitive impairment, we investigated the impact of post‐injection acquisition time on Centiloids (CLs) across five reference regions. CL equations for FBB were derived using standard methods, using FBB data collected between 90 and 110 min with paired Pittsburgh compound B data. Linear mixed models and t‐tests evaluated the impact of acquisition time on CL increases. RESULTS: CL values increased significantly over the scan using the whole cerebellum, cerebellar gray matter, and brainstem as reference regions, particularly in amyloid‐positive individuals. In contrast, CLs based on white matter–containing reference regions decreased across the scan. DISCUSSION: The quantification of CLs in FBB PET imaging is influenced by both the overall scan acquisition time and the choice of reference region. Standardized acquisition protocols or the application of acquisition time–specific CL equations should be implemented in clinical protocols. Highlights: Acquisition timing affects florbetaben positron emission tomography (PET) scan quantification, especially in amyloid‐positive participants.The impact of acquisition timing on quantification varies across common reference regions.Consistent acquisitions and/or appropriate post‐injection adjustments are needed to ensure comparability of PET data. [ABSTRACT FROM AUTHOR]

Objectives: Neuroimaging studies have advanced our understanding of the intricate central nervous system control network governing lower urinary tract (LUT) function, shedding light on mechanisms for urine storage and voiding. However, a lack of consensus in methodological approaches hinders the comparability of results among research groups and limits the translation of this knowledge to clinical applications, emphasizing the need for standardized methodologies and clinical utilization guidelines. Methods: This paper reports the discussions of a workshop at the 2023 meeting of the International Consultation on Incontinence Research Society, which reviewed uncertainties and research priorities to progress the field of neuroimaging in LUT control and dysfunction. Results: Neuroimaging holds great potential for improving our understanding of LUT control and pathophysiological conditions. To date, functional neuroimaging techniques have not yet achieved sufficient strength to make a direct clinical impact. Potential approaches that can improve the clinical utilization of neuroimaging were discussed and research questions proposed. Conclusions: Neuroimaging offers a valuable tool for investigating LUT control, but it's essential to acknowledge the potential for oversimplification when interpreting brain activity due to the complex neural processing and filtering of sensory information. Moreover, technical limitations pose challenges in assessing key brain stem and spinal cord centers, particularly in cases of neurological dysfunction, highlighting the need for more reliable imaging of these centers to advance our understanding of LUT function and dysfunction. [ABSTRACT FROM AUTHOR]

Purpose: Gene‐expression reporter systems, such as green fluorescent protein, have been instrumental to understanding biological processes in living organisms at organ system, tissue, cell, and molecular scales. More than 30 years of work on developing MRI‐visible gene‐expression reporter systems has resulted in a variety of clever application‐specific methods. However, these techniques have not yet been widely adopted, so a general‐purpose expression reporter is still required. Here, we demonstrate that the manganese ion transporter Zip14 is an in vivo MRI‐visible, flexible, and robust gene‐expression reporter to meet this need. Methods: Plasmid constructs consisting of a cell type–specific promoter, gene coding for human Zip14, and a histology‐visible tag were packaged into adeno‐associated viruses. These viruses were intracranially injected into the mouse brain. Serial in vivo MRI was performed using a vendor‐supplied 3D‐MPRAGE sequence. No additional contrast agents were administered. Animals were sacrificed after the last imaging timepoint for immunohistological validation. Results: Neuron‐specific overexpression of Zip14 produced substantial and long‐lasting changes in MRI contrast. Using appropriate viruses enabled both anterograde and retrograde neural tracing. Expression of Zip14 in astrocytes also enabled MRI of glia populations in the living mammalian brain. Conclusions: The flexibility of this system as an MRI‐visible gene‐expression reporter will enable many applications of serial, high‐resolution imaging of gene expression for basic science and therapy development. [ABSTRACT FROM AUTHOR]

A new automated radiosynthesis of [11C]2‐(2,6‐difluoro‐4‐((2‐(N‐methylphenylsulfonamido)ethyl)thio)phenoxy)acetamide ([11C]K2), a radiopharmaceutical for the glutamate α‐amino‐3‐hydroxy‐5‐methyl‐4‐isoxazole propionic acid (AMPA) receptor, is reported. Although manual syntheses have been described, these are unsuitable for routine production of larger batches of [11C]K2 for (pre)clinical PET imaging applications. To meet demands for the imaging agent from our functional neuroimaging collaborators, herein, we report a current good manufacturing practice (cGMP)‐compliant synthesis of [11C]K2 using a commercial synthesis module. The new synthesis is fully automated and has been validated for clinical use. The total synthesis time is 33 min from end of bombardment, and the production method provides 2.66 ± 0.3 GBq (71.9 ± 8.6 mCi) of [11C]K2 in 97.7 ± 0.5% radiochemical purity and 754.1 ± 231.5 TBq/mmol (20,382.7 ± 6256.1 Ci/mmol) molar activity (n = 3). Batches passed all requisite quality control testing confirming suitability for clinical use. [ABSTRACT FROM AUTHOR]

Despite the increased brilliance of the new generation synchrotron sources, there is still a challenge with high‐resolution scanning of very thick and absorbing samples, such as a whole mouse brain stained with heavy elements, and, extending further, brains of primates. Samples are typically cut into smaller parts, to ensure a sufficient X‐ray transmission, and scanned separately. Compared with the standard tomography setup where the sample would be cut into many pillars, the laminographic geometry operates with slab‐shaped sections significantly reducing the number of sample parts to be prepared, the cutting damage and data stitching problems. In this work, a laminography pipeline for imaging large samples (>1 cm) at micrometre resolution is presented. The implementation includes a low‐cost instrument setup installed at the 2‐BM micro‐CT beamline of the Advanced Photon Source. Additionally, sample mounting, scanning techniques, data stitching procedures, a fast reconstruction algorithm with low computational complexity, and accelerated reconstruction on multi‐GPU systems for processing large‐scale datasets are presented. The applicability of the whole laminography pipeline was demonstrated by imaging four sequential slabs throughout an entire mouse brain sample stained with osmium, in total generating approximately 12 TB of raw data for reconstruction. [ABSTRACT FROM AUTHOR]