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It has been a clinically important, long-standing challenge to accurately localize epileptogenic focus in drug-resistant focal epilepsy because more intensive intervention to the detected focus, including resection neurosurgery, can provide significant seizure reduction. In addition to neurophysiological examinations, neuroimaging plays a crucial role in the detection of focus by providing morphological and neuroanatomical information. On the other hand, epileptogenic lesions in the brain may sometimes show only subtle or even invisible abnormalities on conventional MRI sequences, and thus, efforts have been made for better visualization and improved detection of the focus lesions. Recent advance in neuroimaging has been attracting attention because of the potentials to better visualize the epileptogenic lesions as well as provide novel information about the pathophysiology of epilepsy. While the progress of newer neuroimaging techniques, including the non-Gaussian diffusion model and arterial spin labeling, could non-invasively detect decreased neurite parameters or hypoperfusion within the focus lesions, advances in analytic technology may also provide usefulness for both focus detection and understanding of epilepsy. There has been an increasing number of clinical and experimental applications of machine learning and network analysis in the field of epilepsy. This review article will shed light on recent advances in neuroimaging for focal epilepsy, including both technical progress of images and newer analytical methodologies and discuss about the potential usefulness in clinical practice.

Although there is recent evidence that cells from the peripheral immune system can gain access to the central nervous system in certain conditions such as multiple sclerosis, their role has not been assessed in psychosis. Here, we aimed to explore whether blood cell count was associated with brain volume and/or clinical symptomatology. A total of 218 participants (137 first-episode psychosis patients [FEP] and 81 healthy controls [HC]) were included in the study. For each participant, a T1 structural image was acquired, from which brain tissue volumes were calculated. We found that, in FEP, neutrophil count was associated with reduced gray matter (GM) volume (β = -0.117, P < .001) and increased cerebrospinal fluid volume (β = 0.191, P = .007). No associations were observed in HC. GM reduction was generalized but more prominent in certain regions, notably the thalamus, the anterior insula, and the left Heschl's gyrus, among many others. Neutrophil count was also associated with the total PANSS score (β = 0.173, P = .038), including those items assessing hallucinations (β = 0.182, P = .028) and avolition (β = 0.197, P = .018). Several confounders, such as antipsychotic medication, body mass index, and smoking, were controlled for. Overall, the present study may represent the first indirect evidence of brain tissue loss associated with neutrophils in psychosis, and lends support to the hypothesis of a dysregulated immune system. Higher neutrophil count was also associated with more severe clinical symptomatology, which renders it a promising indicator of schizophrenia severity and could even give rise to new therapies.

ObjectivesTo investigate whether longitudinal structural network efficiency is associated with cognitive decline and whether baseline network efficiency predicts mortality in cerebral small vessel disease (SVD).MethodsA prospective, single-centre cohort consisting of 277 non-demented individuals with SVD was conducted. In 2011 and 2015, all participants were scanned with MRI and underwent neuropsychological assessment. We computed network properties using graph theory from probabilistic tractography and calculated changes in psychomotor speed and overall cognitive index. Multiple linear regressions were performed, while adjusting for potential confounders. We divided the group into mild-to-moderate white matter hyperintensities (WMH) and severe WMH group based on median split on WMH volume.ResultsThe decline in global efficiency was significantly associated with a decline in psychomotor speed in the group with severe WMH (β=0.18, p=0.03) and a trend with change in cognitive index (β=0.14, p=0.068), which diminished after adjusting for imaging markers for SVD. Baseline global efficiency was associated with all-cause mortality (HR per decrease of 1 SD 0.43, 95% CI 0.23 to 0.80, p=0.008, C-statistic 0.76).ConclusionDisruption of the network efficiency, a metric assessing the efficiency of network information transfer, plays an important role in explaining cognitive decline in SVD, which was however not independent of imaging markers of SVD. Furthermore, baseline network efficiency predicts risk of mortality in SVD that may reflect the global health status of the brain in SVD. This emphasises the importance of structural network analysis in the context of SVD research and the use of network measures as surrogate markers in research setting.

The preschool years represent a time of expansive mental growth, with the initial expression of many psychological abilities that will continue to be refined into young adulthood. Likewise, brain development during this age is characterized by its “blossoming” nature, showing some of its most dynamic and elaborative anatomical and physiological changes. In this article, we review human brain development during the preschool years, sampling scientific evidence from a variety of sources. First, we cover neurobiological foundations of early postnatal development, explaining some of the primary mechanisms seen at a larger scale within neuroimaging studies. Next, we review evidence from both structural and functional imaging studies, which now accounts for a large portion of our current understanding of typical brain development. Within anatomical imaging, we focus on studies of developing brain morphology and tissue properties, including diffusivity of white matter fiber tracts. We also present new data on changes during the preschool years in cortical area, thickness, and volume. Physiological brain development is then reviewed, touching on influential results from several different functional imaging and recording modalities in the preschool and early school-age years, including positron emission tomography (PET), electroencephalography (EEG) and event-related potentials (ERP), functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG), and near-infrared spectroscopy (NIRS). Here, more space is devoted to explaining some of the key methodological factors that are required for interpretation. We end with a section on multimodal and multidimensional imaging approaches, which we believe will be critical for increasing our understanding of brain development and its relationship to cognitive and behavioral growth in the preschool years and beyond.

Background Vascular depression is regarded as a subtype of late-life depression characterized by a distinct clinical presentation and an association with cerebrovascular damage. Although the term is commonly used in research settings, widely accepted diagnostic criteria are lacking and vascular depression is absent from formal psychiatric manuals such as the Diagnostic and Statistical Manual of Mental Disorders, 5 th edition – a fact that limits its use in clinical settings. Magnetic resonance imaging (MRI) techniques, showing a variety of cerebrovascular lesions, including extensive white matter hyperintensities, subcortical microvascular lesions, lacunes, and microinfarcts, in patients with late life depression, led to the introduction of the term “MRI-defined vascular depression”. Discussion This diagnosis, based on clinical and MRI findings, suggests that vascular lesions lead to depression by disruption of frontal–subcortical–limbic networks involved in mood regulation. However, despite multiple MRI approaches to shed light on the spatiotemporal structural changes associated with late life depression, the causal relationship between brain changes, related lesions, and late life depression remains controversial. While postmortem studies of elderly persons who died from suicide revealed lacunes, small vessel, and Alzheimer-related pathologies, recent autopsy data challenged the role of these lesions in the pathogenesis of vascular depression. Current data propose that the vascular depression connotation should be reserved for depressed older patients with vascular pathology and evident cerebral involvement. Based on current knowledge, the correlations between intra vitam neuroimaging findings and their postmortem validity as well as the role of peripheral markers of vascular disease in late life depression are discussed. Conclusion The multifold pathogenesis of vascular depression as a possible subtype of late life depression needs further elucidation. There is a need for correlative clinical, intra vitam structural and functional MRI as well as postmortem MRI and neuropathological studies in order to confirm the relationship between clinical symptomatology and changes in specific brain regions related to depression. To elucidate the causal relationship between regional vascular brain changes and vascular depression, animal models could be helpful. Current treatment options include a combination of vasoactive drugs and antidepressants, but the outcomes are still unsatisfying.

Determination of sensitive and specific markers of very early AD progression is intended to aid researchers and clinicians to develop new treatments and monitor their effectiveness, as well as to lessen the time and cost of clinical trials. Magnetic Resonance (MR)-related biomarkers have been recently identified by the use of machine learning methods for the in vivo differential diagnosis of AD. However, the vast majority of neuroimaging papers investigating this topic are focused on the difference between AD and patients with mild cognitive impairment (MCI), not considering the impact of MCI patients who will (MCIc) or not convert (MCInc) to AD. Morphological T1-weighted MRIs of 137 AD, 76 MCIc, 134 MCInc, and 162 healthy controls (CN) selected from the Alzheimer's disease neuroimaging initiative (ADNI) cohort, were used by an optimized machine learning algorithm. Voxels influencing the classification between these AD-related pre-clinical phases involved hippocampus, entorhinal cortex, basal ganglia, gyrus rectus, precuneus, and cerebellum, all critical regions known to be strongly involved in the pathophysiological mechanisms of AD. Classification accuracy was 76% AD vs. CN, 72% MCIc vs. CN, 66% MCIc vs. MCInc (nested 20-fold cross validation). Our data encourage the application of computer-based diagnosis in clinical practice of AD opening new prospective in the early management of AD patients.

Creativity is a vast construct, seemingly intractable to scientific inquiry-perhaps due to the vague concepts applied to the field of research. One attempt to limit the purview of creative cognition formulates the construct in terms of evolutionary constraints, namely that of blind variation and selective retention (BVSR). Behaviorally, one can limit the \"blind variation\" component to idea generation tests as manifested by measures of divergent thinking. The \"selective retention\" component can be represented by measures of convergent thinking, as represented by measures of remote associates. We summarize results from measures of creative cognition, correlated with structural neuroimaging measures including structural magnetic resonance imaging (sMRI), diffusion tensor imaging (DTI), and proton magnetic resonance spectroscopy (1H-MRS). We also review lesion studies, considered to be the \"gold standard\" of brain-behavioral studies. What emerges is a picture consistent with theories of disinhibitory brain features subserving creative cognition, as described previously (Martindale, 1981). We provide a perspective, involving aspects of the default mode network (DMN), which might provide a \"first approximation\" regarding how creative cognition might map on to the human brain.

•Little is known about the effects of pregnancy and childbirth on the female brain.•Altogether there are 12 longitudinal neuroimaging studies which address this topic.•Several neuroanatomical changes seem to take place during pregnancy and postpartum.•A few studies suggest tissue decreases during pregnancy.•Most studies indicate tissue increases during postpartum. Pregnancy and giving birth are exceptional states in a woman's life for many reasons. While the effects of pregnancy and childbirth on the female body are obvious, less is known about their impact on the female brain, especially in humans. The scientific literature is still sparse but we have identified 12 longitudinal neuroimaging studies conducted in women whose brains were scanned before pregnancy, during pregnancy, and/or after giving birth. This review summarizes and discusses the reported neuroanatomical changes during pregnancy, postpartum, and beyond. Some studies suggest that pregnancy is mainly associated with tissue decreases, and a few studies suggest that this tissue loss is mostly permanent. In contrast, the majority of studies seems to indicate that the postpartum period is accompanied by substantial tissue increases throughout the entire brain. Future research is clearly warranted to replicate and extend the current findings, while addressing various limitations and shortcomings of existing studies.

Alcohol use disorder (AUD) and cannabis use disorder (CUD) are associated with brain alterations particularly involving fronto‐cerebellar and meso‐cortico‐limbic circuitry. However, such abnormalities have additionally been reported in other psychiatric conditions, and until recently there has been few large‐scale investigations to compare such findings. The current study uses the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) consortium method of standardising structural brain measures to quantify case–control differences and to compare brain‐correlates of substance use disorders with those published in relation to other psychiatric disorders. Using the ENIGMA protocols, we report effect sizes derived from a meta‐analysis of alcohol (seven studies, N = 798, 54% are cases) and cannabis (seven studies, N = 447, 45% are cases) dependent cases and age‐ and sex‐matched controls. We conduct linear analyses using harmonised methods to process and parcellate brain data identical to those reported in the literature for ENIGMA case–control studies of major depression disorder (MDD), schizophrenia (SCZ) and bipolar disorder so that effect sizes are optimally comparable across disorders. R elationships between substance use disorder diagnosis and subcortical grey matter volumes and cortical thickness were assessed with intracranial volume, age and sex as co‐variates . After correcting for multiple comparisons, AUD case–control meta‐analysis of subcortical regions indicated significant differences in the thalamus, hippocampus, amygdala and accumbens, with effect sizes (0.23) generally equivalent to, or larger than |0.23| those previously reported for other psychiatric disorders (except for the pallidum and putamen). On measures of cortical thickness, AUD was associated with significant differences bilaterally in the fusiform gyrus, inferior temporal gyrus, temporal pole, superior frontal gyrus, and rostral and caudal anterior cingulate gyri. Meta‐analysis of CUD case–control studies indicated reliable reductions in amygdala, accumbens and hippocampus volumes, with the former effect size comparable to, and the latter effect size around half of that reported for alcohol and SCZ. CUD was associated with lower cortical thickness in the frontal regions, particularly the medial orbitofrontal region, but this effect was not significant after correcting for multiple testing. This study allowed for an unbiased cross‐disorder comparison of brain correlates of substance use disorders and showed alcohol‐related brain anomalies equivalent in effect size to that found in SCZ in several subcortical and cortical regions and significantly greater alterations than those found in MDD in several subcortical and cortical regions. Although modest, CUD results overlapped with findings reported for AUD and other psychiatric conditions, but appear to be most robustly related to reduce thickness of the medial orbitofrontal cortex. We compared the impact of alcohol and cannabis use disorders to other major psychiatric conditions using standardised objectively brain derived metrics. Through a meta‐analytic cross‐disorder framework, comparable and unique volumetric variations were observed in participants with addiction.

There is evidence that diffusion-weighted imaging (DWI) is able to detect tissue alterations following mild traumatic brain injury (mTBI) that may not be observed on conventional neuroimaging; however, findings are often inconsistent between studies. This systematic review assesses patterns of differences in DWI metrics between those with and without a history of mTBI. A PubMed literature search was performed using relevant indexing terms for articles published prior to May 14, 2020. Findings were limited to human studies using DWI in mTBI. Articles were excluded if they were not full-length, did not contain original data, if they were case studies, pertained to military populations, had inadequate injury severity classification, or did not report post-injury interval. Findings were reported independently for four subgroups: acute/subacute pediatric mTBI, acute/subacute adult mTBI, chronic adult mTBI, and sport-related concussion, and all DWI acquisition and analysis methods used were included. Patterns of findings between studies were reported, along with strengths and weaknesses of the current state of the literature. Although heterogeneity of sample characteristics and study methods limited the consistency of findings, alterations in DWI metrics were most commonly reported in the corpus callosum, corona radiata, internal capsule, and long association pathways. Many acute/subacute pediatric studies reported higher FA and lower ADC or MD in various regions. In contrast, acute/subacute adult studies most commonly indicate lower FA within the context of higher MD and RD. In the chronic phase of recovery, FA may remain low, possibly indicating overall demyelination or Wallerian degeneration over time. Longitudinal studies, though limited, generally indicate at least a partial normalization of DWI metrics over time, which is often associated with functional improvement. We conclude that DWI is able to detect structural mTBI-related abnormalities that may persist over time, although future DWI research will benefit from larger samples, improved data analysis methods, standardized reporting, and increasing transparency.