Cognitive challenges and brain structure variations are common in autism spectrum disorder (ASD) but are rarely explored in middle-to-old aged autistic adults. Cognitive deficits that overlap between young autistic individuals and elderlies with dementia raise an important question: does compromised cognitive ability and brain structure during early development drive autistic adults to be more vulnerable to pathological aging conditions, or does it protect them from further decline? To answer this question, we have synthesized current theoretical models of aging in ASD and conducted a systematic literature review (Jan 1, 1980 - Feb 29, 2024) and meta-analysis to summarize empirical studies on cognitive and brain deviations in middle-to-old aged autistic adults. We explored findings that support different aging theories in ASD and addressed study limitations and future directions. This review sheds light on the poorly understood consequences of aging question raised by the autism community to pave the way for future studies to identify sensitive and reliable measures that best predict the onset, progression, and prognosis of pathological aging in ASD.

Internet Gaming Disorder (IGD) is an emerging public health concern; effective treatments are still under development. This mini-review focuses on summarizing the main scientific evidence from psychological, pharmacological, brain imaging, and emerging treatment approaches for IGD. We searched PubMed and Scopus databases using keywords related to IGD and treatment. Cognitive behavioral therapy (CBT) is the most extensively researched psychological treatment for IGD, supported by several randomized controlled trials (RCTs). Other promising approaches include mindfulness, relapse prevention, abstinence protocols, and family therapy. Pharmacological treatments like bupropion and escitalopram have shown benefits, especially when IGD is comorbid with conditions like major depressive disorder. However, the quality of evidence is moderate for psychological interventions but low to moderate for pharmacological approaches. Emerging treatments such as transcranial direct current stimulation (tDCS), repetitive transcranial magnetic stimulation (rTMS), and electro-acupuncture have demonstrated efficacy in reducing IGD symptoms and modulating brain activity. Brain imaging techniques like functional magnetic resonance imaging (fMRI) have provided insights into the neural mechanisms underlying IGD and treatment effects, although these studies lack randomized controlled designs. While multimodal approaches show promise, larger, well-designed RCTs are needed to establish effective IGD treatments.

The prenatal and neonatal periods are two of the most important developmental stages of the human brain. It is therefore crucial to understand normal brain development and how early connections are established during these periods, in order to advance the state of knowledge on altered brain development and eventually identify early brain markers of neurodevelopmental disorders and diseases. In this systematic review (Prospero ID: CRD42024511365), we compiled resting state functional magnetic resonance imaging (fMRI) studies in healthy fetuses and neonates, in order to outline the main characteristics of typical development of the functional brain connectivity during the prenatal and neonatal periods. A systematic search of five databases identified a total of 12 573 articles. Of those, 28 articles met pre-established selection criteria based determined by the authors after surveying and compiling the major limitations reported within the literature. Inclusion criteria were: (1) resting state studies; (2) presentation of original results; (3) use of fMRI with minimum one Tesla; (4) a population ranging from 20 weeks of GA to term birth (around 37-42 weeks of PMA); (5) singleton pregnancy with normal development (absence of any complications known to alter brain development). Exclusion criteria were: (1) preterm studies; (2) post-mortem studies; (3) clinical or pathological studies; (4) twin studies; (5) papers with a sole focus on methodology (i.e. focused on tool and analysis development); (6) volumetric studies; (7) activation map studies; (8) cortical analysis studies; (9) conference papers. A risk of bias assessment was also done to evaluate each article\'s methodological rigor. 1877 participants were included across all the reviewed articles. Results consistently revealed a developmental gradient of increasing functional brain connectivity from posterior to anterior regions and from proximal-to-distal regions. A decrease in local small-world organization shortly after birth was also observed; small-world characteristics were present in fetuses and newborns, but appeared weaker in the latter group. Also, the posterior-to-anterior gradient could be associated with earlier development of the sensorimotor networks in the posterior regions while more complex higher-order networks (e.g. attention-related) mature later in the anterior regions. The main limitations of this systematic review stem from the inherent limitations of functional imaging in fetuses, mainly: unevenly distributed populations and limited sample sizes; fetal movements in the womb and other imaging obstacles; and a large voxel resolution when imaging a small brain. Another limitation specific to this review is the relatively small number of included articles compared to very a large search result, which may have led to relevant articles having been overlooked.

Autism Spectrum Disorder (ASD) is an early onset neurodevelopmental disorder characterized by impaired social interaction and communication, and repetitive patterns of behavior. Family studies show that ASD is highly heritable, and hundreds of genes have previously been implicated in the disorder; however, the etiology is still not fully clear. Brain imaging and electroencephalography (EEG) are key techniques that study alterations in brain structure and function. Combined with genetic analysis, these techniques have the potential to help in the clarification of the neurobiological mechanisms contributing to ASD and help in defining novel therapeutic targets. To further understand what is known today regarding the impact of genetic variants in the brain alterations observed in individuals with ASD, a systematic review was carried out using Pubmed and EBSCO databases and following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. This review shows that specific genetic variants and altered patterns of gene expression in individuals with ASD may have an effect on brain circuits associated with face processing and social cognition, and contribute to excitation-inhibition imbalances and to anomalies in brain volumes.

OBJECTIVE: To determine if children with neonatal cholestatic liver disease had concurrent and later findings on brain imaging studies that could be attributed and the cholestasis to contribute to the understanding of the impaired neuropsychological development.
METHODS: Ovid MEDLINE and EMBASE were searched on July 21, 2022, and updated on March 26, 2023. Studies with children under 18 years of age with neonatal cholestasis and a brain scan at the time of diagnosis or later in life were included. Excluded studies were non-English, non-human, reviews or conference abstracts. Data were extracted on demographics, brain imaging findings, treatment and outcome. The results were summarised by disease categories. Risk of bias was assessed using JBI critical appraisal tools.
RESULTS: The search yielded 12 011 reports, of which 1261 underwent full text review and 89 were eligible for inclusion. Haemorrhage was the most common finding, especially in children with bile duct obstruction, including biliary atresia. Some findings were resolved after liver transplantation.
CONCLUSIONS: Children with neonatal cholestasis had changes in brain imaging, which might play a role in impaired neuropsychological development, but longitudinal clinical research with structured assessment is needed to better qualify the aetiology of the impairment.

This systematic review with a meta-analysis aimed to identify the altered brain structure and function in carpal tunnel syndrome (CTS) by summarizing the literature about magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), and magnetoencephalography (MEG) outcomes compared to healthy controls (HC). CTS is the most common nerve entrapment in the arm associated with altered peripheral and central nociceptive system. PRISMA guidelines were used to report the outcomes. Six databases were searched for relevant literature (Web of Science, Scopus, PubMed, Sage, EBSCO host, and Cochrane). Eligible studies comparing MRI, fMRI, and MEG findings in people with CTS (present for at least 2 months) and HC through the following parameters: (1) interdigit cortical separation distance, (2) white and grey matter changes, (3) peak latency of M20 wave and recovery function of N20 from the somatosensory cortex (SI), and (4) surface area of activated digit cortical representation. The results from different studies were pooled and a meta-analysis was done. From 17 included, there was a significant reduction of interdigit cortical separation distance of index-middle and index-little fingers in the CTS (SMD = - 0.869, 95% CI (- 1.325, - 0.413), p-value = 0.000) and (SMD = - 0.79, 95% CI (- 1.217, - 0.364), p-value = 0.000), respectively. Middle-little fingers interdigit separation showed no difference (SMD = - 0.2, 95% CI (- 0.903, 1.309), p-value = 0.718). There is evidence supporting the altered brain structure and function in CTS as evidenced by reduction of interdigit cortical separation distance, and excessive blurring and disinhibition of SI, with low resting state functional connectivity. Thus, centrally directed therapeutic approaches might complement peripheral treatments.

BACKGROUND: Pediatric headache is a common cause of pediatric emergency department (ED) visits, and 8.8% of cases require imaging. Alarmingly, 12.5% of imaged cases have a pathologic cause. A pediatric patient with a complicated medical history presented to the pediatric ED with multiple cerebral abscesses. The possible causes and contributors to this rare cause of pediatric headache and a review of pediatric headache emergency management are presented.Case Presentation: A 12-year-old male patient with a complex medical and surgical history, including post-repair pulmonary valve stenosis, visited the pediatric ED for intractable and worsening left frontoparietal headache, refractory to ibuprofen, for 6 days. A physical examination revealed severe photophobia and restlessness secondary to severe head pain. Non-contrast brain computed tomography demonstrated two round, bilateral, parietal hypodense lesions with surrounding vasogenic edema. The lesions were consistent with abscesses on magnetic resonance imaging. Eventually, the patient underwent successful surgical abscess drainage and made a full recovery. The patient was lost to follow-up; therefore, no causative bacterial species was determined.
CONCLUSIONS: Managing pediatric headache in emergency settings requires a robust history and physical examination. Cerebral abscesses are an infrequent but fatal cause of pediatric headache and therefore should be considered among the differential diagnoses.

In advancing our understanding of tinnitus, some of the more impactful contributions in the past two decades have come from human brain imaging studies, specifically the idea of both auditory and extra-auditory neural networks that mediate tinnitus. These networks subserve both the perception of tinnitus and the psychological reaction to chronic, continuous tinnitus. In this article, we review particular studies that report on the nodes and links of such neural networks and their inter-network connections. Innovative neuroimaging tools have contributed significantly to the increased understanding of anatomical and functional connections of attention, emotion-processing, and default mode networks in adults with tinnitus. We differentiate between the neural correlates of tinnitus and those of comorbid hearing loss; surprisingly, tinnitus and hearing loss when they co-occur are not necessarily additive in their impact and, in rare cases, additional tinnitus may act to mitigate the consequences of hearing loss alone on the brain. The scale of tinnitus severity also appears to have an impact on brain networks, with some of the alterations typically attributed to tinnitus reaching significance only in the case of bothersome tinnitus. As we learn more about comorbid conditions of tinnitus, such as depression, anxiety, hyperacusis, or even aging, their contributions to the network-level changes observed in tinnitus will need to be parsed out in a manner similar to what is currently being done for hearing loss or severity. Together, such studies advance our understanding of the heterogeneity of tinnitus and will lead to individualized treatment plans.

Mesoscale microscopy images of the brain contain a wealth of information which can help us understand the working mechanisms of the brain. However, it is a challenging task to process and analyze these data because of the large size of the images, their high noise levels, the complex morphology of the brain from the cellular to the regional and anatomical levels, the inhomogeneous distribution of fluorescent labels in the cells and tissues, and imaging artifacts. Due to their impressive ability to extract relevant information from images, deep learning algorithms are widely applied to microscopy images of the brain to address these challenges and they perform superiorly in a wide range of microscopy image processing and analysis tasks. This article reviews the applications of deep learning algorithms in brain mesoscale microscopy image processing and analysis, including image synthesis, image segmentation, object detection, and neuron reconstruction and analysis. We also discuss the difficulties of each task and possible directions for further research.

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are two commonly used non-invasive techniques for measuring brain activity in neuroscience and brain-computer interfaces (BCI).Objective. In this review, we focus on the use of EEG and fMRI in neurofeedback (NF) and discuss the challenges of combining the two modalities to improve understanding of brain activity and achieve more effective clinical outcomes. Advanced technologies have been developed to simultaneously record EEG and fMRI signals to provide a better understanding of the relationship between the two modalities. However, the complexity of brain processes and the heterogeneous nature of EEG and fMRI present challenges in extracting useful information from the combined data.Approach. We will survey existing EEG-fMRI combinations and recent studies that exploit EEG-fMRI in NF, highlighting the experimental and technical challenges.Main results. We made a classification of the different combination of EEG-fMRI for NF, we provide a review of multimodal analysis methods for EEG-fMRI features. We also survey the current state of research on EEG-fMRI in the different existing NF paradigms. Finally, we also identify some of the remaining challenges in this field.Significance. By exploring EEG-fMRI combinations in NF, we are advancing our knowledge of brain function and its applications in clinical settings. As such, this review serves as a valuable resource for researchers, clinicians, and engineers working in the field of neural engineering and rehabilitation, highlighting the promising future of EEG-fMRI-based NF.