Perinatal influences on academic achievement and the developing brain: a scoping systematic review.

Introduction and methods: In this PRISMA-compliant systematic review, we identify and synthesize the findings of research in which neuroimaging and assessments of achievement have been used to examine the relationships among aspects of developmental programming, neurodevelopment, and achievement in reading and mathematics. Results: Forty-seven studies met inclusion criteria. The majority examined the impact of prematurity (n = 32) and prenatal alcohol exposure (n = 13). Several prematurity studies reported a positive correlation between white-matter integrity of callosal fibers and executive functioning and/or achievement, and white matter properties were consistently associated with cognitive and academic performance in preterm and full-term children. Volumetric studies reported positive associations between academic and cognitive abilities and white and gray matter volume in regions such as the insula, putamen, and prefrontal lobes. Functional MRI studies demonstrated increased right-hemispheric language processing among preterm children. Altered activation of the frontoparietal network related to numerical abilities was also reported. Prenatal alcohol exposure studies reported alterations in white matter microstructure linked to deficits in cognitive functioning and academic achievement, including mathematics, reading, and vocabulary skills. Volumetric studies reported reductions in cerebral, cerebellar, and subcortical gray matter volumes associated with decreased scores on measures of executive functioning, attention, working memory, and academic performance. Functional MRI studies demonstrated broad, diffuse activation, reduced activation in canonical regions, and increased activation in non-canonical regions during numeric tasks. Discussion: A preponderance of studies linked prematurity and prenatal alcohol exposure to altered neurodevelopmental processes and suboptimal academic achievement. Limitations and recommendations for future research are discussed. Systematic review registration: Identifier: DOI 10.17605/OSF.IO/ZAN67.

Heading during the season and its potential impact on brain structure and neurocognitive performance in high-level male football players: An observational study.

OBJECTIVES: To investigate potential effects of heading on the neurocognitive performance and the white matter (WM) of the brain in high-level adult male football players. DESIGN: Prospective longitudinal. METHODS: Football players engaging in the highest football leagues in Germany were included. Neurocognitive performance tests and diffusion tensor imaging (DTI) were executed before and after the observation period. Video recordings of each training session and each match play during the observation period were analyzed regarding heading exposure and characteristics. Four DTI measures from tract-based spatial statistics (fractional anisotropy, mean, axial, and radial diffusivity) were investigated. Associations between heading variables and DTI and neurocognitive parameters were tested subsequently. RESULTS: 8052 headers of 22 players (19.9 ±â€¯2.7 years) were documented in a median of 16.9 months. The individual total heading number ranged from 57 to 943 (median: 320.5). Header characteristics differed between training sessions and matches. Neurocognitive performance (n = 22) and DTI measures (n = 14) showed no significant differences from pre- to post-test. After correction for multiple comparisons, no significant correlations with the total heading number were found. However, the change in fractional anisotropy in the splenium of the corpus callosum correlated significantly with the total amount of long-distance headers (Pearson's r = -0.884; p < 0.0001). CONCLUSIONS: Over the median observation period of 16.9 months, DTI measures and neurocognitive performance remained unchanged. To elucidate the meaning of the association between individual change in fractional anisotropy and long-distance headers further investigations with larger samples, longer observations, and various cohorts regarding age and level of play are required.

Implementing ABCD studyⓇ MRI sequences for multi-site cohort studies: Practical guide to necessary steps, preprocessing methods, and challenges.

Large multi-site studies that combine magnetic resonance imaging (MRI) data across research sites present exceptional opportunities to advance neuroscience research. However, scanner or site variability and non-standardised image acquisition protocols, data processing and analysis pipelines can adversely affect the reliability and repeatability of MRI derived brain measures. We implemented a standardised MRI protocol based on that used in the Adolescent Brain Cognition Development (ABCD)Ⓡ study in two sites, and across four MRI scanners. Twice repeated measurements of a single healthy volunteer were obtained in two sites and in four 3T MRI scanners (vendors: Siemens, Philips, and GE). Imaging data included anatomical scans (T1 weighted, T2 weighted), diffusion weighted imaging (DWI) and resting state functional MRI (rs-fMRI). Standardised containerized pipelines were utilised to pre-process the data and different image quality metrics and test-retest variability of different brain metrics were evaluated. The implementation of the MRI protocols was possible with minor adjustments in acquisition (e.g. repetition time (TR), higher b-values) and exporting (DICOM formats) of images due to different technical performance of the scanners. This study provides practical insights into the implementation of standardised sequences and data processing for multisite studies, showcase the benefits of containerised preprocessing tools, and highlights the need for careful optimisation of multisite image acquisition.

Constraining current neuroanatomical models of reading: the view from Arabic.

There is a growing interest in imaging understudied orthographies to unravel their neuronal correlates and their implications for existing computational and neuroanatomical models. Here, we review current brain mapping literature about Arabic words. We first offer a succinct description of some unique linguistic features of Arabic that challenge current cognitive models of reading. We then appraise the existing functional neuroimaging studies that investigated written Arabic word processing. Our review revealed that (1) Arabic is still understudied, (2) the most investigated features concerned the effects of vowelling and diglossia in Arabic reading, (3) findings were not always discussed in the light of existing reading models such as the dual route cascaded, the triangle, and the connectionist dual process models, and (4) current evidence is unreliable when it comes to the exact neuronal pathways that sustain Arabic word processing. Overall, despite the fact that Arabic has some unique linguistic features that challenge and ultimately enrich current reading models, the existing functional neuroimaging literature falls short of offering a reliable evidence about brain networks of Arabic reading. We conclude by highlighting the need for more systematic studies of the linguistic features of Arabic to build theoretical and neuroanatomical models that are concurrently specific and general.

Approaches to supratentorial brain tumours in children.

The differential diagnosis of supratentorial brain tumours in children can be challenging, especially considering the recent changes to the WHO classification of CNS tumours published in 2021. Many new tumour types have been proposed which frequently present in children and young adults and their imaging features are currently being described by the neuroradiology community. The purpose of this article is to provide guidance to residents and fellows new to the field of paediatric neuroradiology on how to evaluate an MRI of a patient with a newly diagnosed supratentorial tumour. Six different approaches are discussed including: 1. Tumour types, briefly discussing the main changes to the recent WHO classification of CNS tumours, 2. Patient age and its influence on incidence rates of specific tumour types, 3. Growth patterns, 4. Tumour location and how defining the correct location helps in narrowing down the differential diagnoses and 5. Imaging features of the tumour on DWI, SWI, FLAIR and post contrast sequences.

The neural network of sensory attenuation: A neuroimaging meta-analysis.

Sensory attenuation refers to the reduction in sensory intensity resulting from self-initiated actions compared to stimuli initiated externally. A classic example is scratching oneself without feeling itchy. This phenomenon extends across various sensory modalities, including visual, auditory, somatosensory, and nociceptive stimuli. The internal forward model proposes that during voluntary actions, an efferent copy of the action command is sent out to predict sensory feedback. This predicted sensory feedback is then compared with the actual sensory feedback, leading to the suppression or reduction of sensory stimuli originating from self-initiated actions. To further elucidate the neural mechanisms underlying sensory attenuation effect, we conducted an extensive meta-analysis of functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) studies. Utilizing activation likelihood estimation (ALE) analysis, our results revealed significant activations in a prominent cluster encompassing the right superior temporal gyrus (rSTG), right middle temporal gyrus (rMTG), and right insula when comparing external-generated with self-generated conditions. Additionally, significant activation was observed in the right anterior cerebellum when comparing self-generated to external-generated conditions. Further analysis using meta-analytic connectivity modeling (MACM) unveiled distinct brain networks co-activated with the rMTG and right cerebellum, respectively. Based on these findings, we propose that sensory attenuation arises from the suppression of reflexive inputs elicited by self-initiated actions through the internal forward modeling of a cerebellum-centered action prediction network, enabling the "sensory conflict detection" regions to effectively discriminate between inputs resulting from self-induced actions and those originating externally.

High-Speed Clearing and High-Resolution Staining for Analysis of Various Markers for Neurons and Vessels.

BACKGROUND: Tissue clearing enables deep imaging in various tissues by increasing the transparency of tissues, but there were limitations of immunostaining of the large-volume tissues such as the whole brain. METHODS: Here, we cleared and immune-stained whole mouse brain tissues using a novel clearing technique termed high-speed clearing and high-resolution staining (HCHS). We observed neural structures within the cleared brains using both a confocal microscope and a light-sheet fluorescence microscope (LSFM). The reconstructed 3D images were analyzed using a computational reconstruction algorithm. RESULTS: Various neural structures were well observed in three-dimensional (3D) images of the cleared brains from Gad-green fluorescent protein (GFP) mice and Thy 1-yellow fluorescent protein (YFP) mice. The intrinsic fluorescence signals of both transgenic mice were preserved after HCHS. In addition, large-scale 3D imaging of brains, immune-stained by the HCHS method using a mild detergent-based solution, allowed for the global topological analysis of several neuronal markers such as c-Fos, neuronal nuclear protein (NeuN), Microtubule-associated protein 2 (Map2), Tuj1, glial fibrillary acidic protein (GFAP), and tyrosine hydroxylase (TH) in various anatomical regions in the whole mouse brain tissues. Finally, through comparisons with various existing tissue clearing methodologies such as CUBIC, Visikol, and 3DISCO, it was confirmed that the HCHS methodology results in relatively less tissue deformation and higher fluorescence retention. CONCLUSION: In conclusion, the development of 3D imaging based on novel tissue-clearing techniques (HCHS) will enable detailed spatial analysis of neural and vascular networks present within the brain.

Gray matter alterations in Huntington's disease: A meta-analysis of VBM neuroimaging studies.

Increasing neuroimaging studies have attempted to identify biomarkers of Huntington's disease (HD) progression. Here, we conducted voxel-based meta-analyses of voxel-based morphometry (VBM) studies on HD to investigate the evolution of gray matter volume (GMV) alterations and explore the effects of genetic and clinical features on GMV changes. A systematic review was performed to identify the relevant studies. Meta-analyses of whole-brain VBM studies were performed to assess the regional GMV changes in all HD mutation carriers, in presymptomatic HD (pre-HD), and in symptomatic HD (sym-HD). A quantitative comparison was performed between pre-HD and sym-HD. Meta-regression analyses were used to explore the effects of genetic and clinical features on GMV changes. Twenty-eight studies were included, comparing a total of 1811 HD mutation carriers [including 1150 pre-HD and 560 sym-HD] and 969 healthy controls (HCs). Pre-HD showed decreased GMV in the bilateral caudate nuclei, putamen, insula, anterior cingulate/paracingulate gyri, middle temporal gyri, and left dorsolateral superior frontal gyrus compared with HCs. Compared with pre-HD, GMV decrease in sym-HD extended to the bilateral median cingulate/paracingulate gyri, Rolandic operculum and middle occipital gyri, left amygdala, and superior temporal gyrus. Meta-regression analyses found that age, mean lengths of CAG repeats, and disease burden were negatively associated with GMV atrophy of the bilateral caudate and right insula in all HD mutation carriers. This meta-analysis revealed the pattern of GMV changes from pre-HD to sym-HD, prompting the understanding of HD progression. The pattern of GMV changes may be biomarkers for disease progression in HD.

Pontocerebellar Hypoplasia Type 9: A Case Study Highlighting Distinctive Magnetic Resonance Imaging Features.

Pontocerebellar hypoplasia type 9 (PCH9) is a rare, autosomal, recessive, neurodevelopmental disorder caused by a mutation in the AMPD2 gene. Despite its rarity, it presents distinctive clinical and neuroradiological features. Diagnosing it is challenging yet crucial for appropriate management. We describe a 21-month-old boy with clinical and neuroradiological manifestations of the diagnosis, including characteristic signs such as an eight-configured midbrain and hypoplasia of the brainstem and cerebellar structures. Genetic evaluation confirmed homozygous missense mutations in the AMPD2 gene. This case highlights the pathognomonic neuroradiological features of pontocerebellar hypoplasia type 9 that point toward diagnosis.

Neuroimaging biomarkers for predicting stroke outcomes: A systematic review.

Background and Aims: Stroke is a prominent cause of long-term adult impairment globally and a significant global health issue. Only 14% of stroke survivors achieve full recovery, while 25% to 50% require varying degrees of support, and over half become dependent. The aftermath of a stroke brings profound changes to an individual's life, with early choices significantly impacting their quality of life. This review aims to establish the efficacy of neuroimaging data in predicting long-term outcomes and recovery rates following a stroke. Methods: A scientific literature search was conducted using the Centre of Reviews and Dissemination (CRD) criteria and PRISMA guidelines for a combined meta-narrative and systematic quantitative review. The methodology involved a structured search in databases like PubMed and The Cochrane Library, following inclusion and exclusion criteria to identify relevant studies on neuroimaging biomarkers for stroke outcome prediction. Data collection utilized the Microsoft Edge Zotero plugin, with quality appraisal conducted via the CASP checklist. Studies published from 2010 to 2024, including observational, randomized control trials, case reports, and clinical trials. Non-English and incomplete studies were excluded, resulting in the identification of 11 pertinent articles. Data extraction emphasized study methodologies, stroke conditions, clinical parameters, and biomarkers, aiming to provide a thorough literature overview and evaluate the significance of neuroimaging biomarkers in predicting stroke recovery outcomes. Results: The results of this systematic review indicate that integrating advanced neuroimaging methods with highly successful reperfusion therapies following a stroke facilitates the diagnosis of the condition and assists in improving neurological impairments resulting from stroke. These measures reduce the possibility of death and improve the treatment provided to stroke patients. Conclusion: These findings highlight the crucial role of neuroimaging in advancing our understanding of post-stroke outcomes and improving patient care.

SuperAging functional connectomics from resting-state functional MRI.

Understanding the relationship between functional connectivity (FC) of higher-order neurocognitive networks and age-related cognitive decline is a complex and evolving field of research. Decreases in FC have been associated with cognitive decline in persons with Alzheimer's disease and related dementias (ADRD). However, the contributions of FC have been less straightforward in typical cognitive aging. Some investigations suggest relatively robust FC within neurocognitive networks differentiates unusually successful cognitive aging from average aging, while others do not. Methodologic limitations in data processing and varying definitions of 'successful aging' may have contributed to the inconsistent results to date. The current study seeks to address previous limitations by optimized MRI methods to examine FC in the well-established SuperAging phenotype, defined by age and cognitive performance as individuals 80 and older with episodic memory performance equal to or better than 50-to-60-year-olds. Within- and between-network FC of large-scale neurocognitive networks were compared between 24 SuperAgers and 16 cognitively average older-aged control (OACs) with stable cognitive profiles using resting-state functional MRI (rs-fMRI) from a single visit. Group classification was determined based on measures of episodic memory, executive functioning, verbal fluency and picture naming. Inclusion criteria required stable cognitive status across two visits. First, we investigated the FC within and between seven resting-state networks from a common atlas parcellation. A separate index of network segregation was also compared between groups. Second, we investigated the FC between six subcomponents of the default mode network (DMN), the neurocognitive network commonly associated with memory performance and disrupted in persons with ADRD. For each analysis, FCs were compared across groups using two-sample independent t-tests and corrected for multiple comparisons. There were no significant between-group differences in demographic characteristics including age, sex and education. At the group-level, within-network FC, between-network FC, and segregation measurements of seven large-scale networks, including subcomponents of the DMN, were not a primary differentiator between cognitively average aging and SuperAging phenotypes. Thus, FC within or between large-scale networks does not appear to be a primary driver of the exceptional memory performance observed in SuperAgers. These results have relevance for differentiating the role of FC changes associated with cognitive aging from those associated with ADRD.

Enhancing Alzheimer's disease diagnosis and staging: a multistage CNN framework using MRI.

This study addresses the pervasive and debilitating impact of Alzheimer's disease (AD) on individuals and society, emphasizing the crucial need for timely diagnosis. We present a multistage convolutional neural network (CNN)-based framework for AD detection and sub-classification using brain magnetic resonance imaging (MRI). After preprocessing, a 26-layer CNN model was designed to differentiate between healthy individuals and patients with dementia. After detecting dementia, the 26-layer CNN model was reutilized using the concept of transfer learning to further subclassify dementia into mild, moderate, and severe dementia. Leveraging the frozen weights of the developed CNN on correlated medical images facilitated the transfer learning process for sub-classifying dementia classes. An online AD dataset is used to verify the performance of the proposed multistage CNN-based framework. The proposed approach yielded a noteworthy accuracy of 98.24% in identifying dementia classes, whereas it achieved 99.70% accuracy in dementia subclassification. Another dataset was used to further validate the proposed framework, resulting in 100% performance. Comparative evaluations against pre-trained models and the current literature were also conducted, highlighting the usefulness and superiority of the proposed framework and presenting it as a robust and effective AD detection and subclassification method.

Anorexia Nervosa Across the Lifespan: A Review of Recent Literature.

In this review, the authors provide an update on the understanding of anorexia nervosa (AN) across the lifespan. Focusing on key pieces of literature from the past 5 years, this review summarizes recent updates to DSM-5 within the domain of AN, including the addition of a new AN diagnosis: atypical anorexia. Additional sections covered in this review include improvements in the epidemiological understanding of AN across the developmental spectrum, treatment approaches that have been established as gold standard as well as new directions recently explored in treatment, and recent advancements in the biopsychosocial underpinnings of AN. Altogether, although this review captures several advancements in the field's overall conceptualization of AN, several key areas of treatment and diagnostic capacity continue to require additional focus and research.

Repeat traumatic brain injury exacerbates acute thalamic hyperconnectivity in humans.

Repeated mild traumatic brain injury is of growing interest regarding public and sporting safety and is thought to have greater adverse or cumulative neurological effects when compared with single injury. While epidemiological links between repeated traumatic brain injury and outcome have been investigated in humans, exploration of its mechanistic substrates has been largely undertaken in animal models. We compared acute neurological effects of repeat mild traumatic brain injury (n = 21) to that of single injury (n = 21) and healthy controls (n = 76) using resting-state functional MRI and quantified thalamic functional connectivity, given previous identification of its prognostic potential in human mild traumatic brain injury and rodent repeat mild traumatic brain injury. Acute thalamocortical functional connectivity showed a rank-based trend of increasing connectivity with number of injuries, at local and global scales of investigation. Thus, history of as few as two previous injuries can induce a vulnerable neural environment of exacerbated hyperconnectivity, in otherwise healthy individuals from non-specialist populations. These results further establish thalamocortical functional connectivity as a scalable marker of acute injury and long-term neural dysfunction following mild traumatic brain injury.

Mental state decoders: game-changers or wishful thinking?

Decoding mental and perceptual states using fMRI has become increasingly popular over the past two decades, with numerous highly-cited studies published in high-profile journals. Nevertheless, what have we learned from these decoders? In this opinion, we argue that fMRI-based decoders are not neurophysiologically informative and are not, and likely cannot be, applicable to real-world decision-making. The former point stems from the fact that decoding models cannot disentangle neural mechanisms from their epiphenomena. The latter point stems from both logical and ethical constraints. Constructing decoders requires precious time and resources that should instead be directed toward scientific endeavors more likely to yield meaningful scientific progress.

Association between caregiver and infant visual neurocognition.

Previous work has shown that caregiver attention shapes visual cognition in infants through dyadic interactions. Is this association measurable when visual cognition is objectively measured in caregivers and infants using comparable experimental paradigms? In the current study, we presented infants (N = 86) and caregivers (N = 78) with age-specific variants of the same preferential looking visual cognition task to investigate whether caregiver visual cognition was associated with their infants' visual cognition. In each trial of the task, two side-by-side flashing displays of coloured shapes were presented. On the 'unchanging' side, the colours of the shapes remained the same. On the 'changing' side, the colour of one shape changed after each flash. Load was varied by changing the number of shapes across trials (low, medium, and high loads). We extracted looking dynamics using video recordings and brain function using functional near-infrared spectroscopy as both infants and caregivers engaged with the task. Change preference (CP) score, which represented the amount of time spent looking at the changing side divided by the total looking duration, showed a load-dependent modulation for both infants and caregivers. Both groups showed the highest CP scores at the low load. Further, higher caregiver CP scores was associated with higher infant CP scores at the low load. Both infants and caregivers engaged canonical regions of the fronto-parietal network involved in visual cognition. Critically, higher caregiver CP scores were associated with greater activation in the left superior parietal lobule in younger infants, a region involved in allocating visuo-spatial attention and working memory maintenance. Further, there was spatial overlap between performance-dependent regions in the right parietal cortex in caregivers and younger infants. Our findings provide first evidence of a heritability-related visual neurocognitive association between caregivers and their children in the first year of life.

Shared and distinct aberrations in frontal-striatal system functional patterns among patients with irritable bowel syndrome and major depressive disorder.

BACKGROUND: Considering the high comorbidity, shared risk factors, and genetic pathways between irritable bowel syndrome (IBS) and major depressive disorder (MDD), we hypothesized that there would be both shared and disorder-specific alterations in brain function. METHODS: A total of 39 IBS patients, 39 MDD patients, and 40 healthy controls (HCs) were enrolled and matched for sex, age, and educational level. All subjects underwent resting-state functional MRI. The clinical variables of anxiety, depression, gastrointestinal symptoms and alexithymia were recorded. The 12 subregions of the striatum were employed as seeds to assess their functional connectivity (FC) with every voxel throughout the whole brain. RESULTS: Compared to HC, IBS and MDD patients exhibited aberrant frontal-striatal circuitry. We observed a common decrease in FC between the dorsal striatum and regions of the hippocampus, sensorimotor cortex, and prefrontal cortex (PFC) in both IBS and MDD patients. Patients with IBS exhibited disorder-specific decreases in FC within the striatum, along with reduced connectivity between the ventral striatum and sensorimotor cortex. In contrast, MDD patients showed disorder-specific hyperconnectivity in the medial PFC-limbic system. Receiver operating characteristic curve analysis showed that frontal-striatal FC values could serve as transdiagnostic markers of IBS and MDD. Within the IBS group, striatal connectivity was not only negatively associated with weekly abdominal pain days but also negatively correlated with the levels of anxiety and alexithymia. CONCLUSIONS: This exploratory analysis indicated that patients with IBS and MDD exhibited both shared and disorder-specific frontal-striatal circuit impairments, potentially explaining both comorbidity and distinct phenotypes.

Esketamine in depression: putative biomarkers from clinical research.

The discovery of racemic (R, S)-ketamine as a rapid-acting antidepressant and the subsequent FDA approval of its (S)-enantiomer, esketamine, for treatment-resistant depression (TRD) are significant advances in the development of novel neuropsychiatric therapeutics. Esketamine is now recognized as a powerful tool for addressing persistent symptoms of TRD compared to traditional oral antidepressants. However, research on biomarkers associated with antidepressant response to esketamine has remained sparse and, to date, has been largely extrapolated from racemic ketamine studies. Genetic, proteomic, and metabolomic profiles suggest that inflammation and mitochondrial function may play a role in esketamine's antidepressant effects, though these preliminary results require verification. In addition, neuroimaging research has consistently implicated the prefrontal cortex, striatum, and anterior cingulate cortex in esketamine's effects. Esketamine also shows promise in perioperative settings for reducing depression and anxiety, and these effects appear to correlate with increased peripheral biomarkers such as brain-derived neurotrophic factor and serotonin. Further indications are likely to be identified with the continued repurposing of racemic ketamine, providing further opportunity for biomarker study and mechanistic understanding of therapeutic effects. Novel methodologies and well-designed biomarker-focused clinical research trials are needed to more clearly elucidate esketamine's therapeutic actions as well as biologically identify those most likely to benefit from this agent, allowing for the improved personalization of antidepressant treatment.