Structural MRI Studies Research Articles

Longitudinal structural and perfusion MRI enhanced by machine learning outperforms standalone modalities and radiological expertise in high-grade glioma surveillance

PurposeSurveillance of patients with high-grade glioma (HGG) and identification of disease progression remain a major challenge in neurooncology. This study aimed to develop a support vector machine (SVM) classifier, employing combined longitudinal structural and perfusion MRI studies, to classify between stable disease, pseudoprogression and progressive disease (3-class problem).MethodsStudy participants were separated into two groups: group I (total cohort: 64 patients) with a single DSC time point and group II (19 patients) with longitudinal DSC time points (2-3). We retrospectively analysed 269 structural MRI and 92 dynamic susceptibility contrast perfusion (DSC) MRI scans. The SVM classifier was trained using all available MRI studies for each group. Classification accuracy was assessed for different feature dataset and time point combinations and compared to radiologists’ classifications.ResultsSVM classification based on combined perfusion and structural features outperformed radiologists’ classification across all groups. For the identification of progressive disease, use of combined features and longitudinal DSC time points improved classification performance (lowest error rate 1.6%). Optimal performance was observed in group II (multiple time points) with SVM sensitivity/specificity/accuracy of 100/91.67/94.7% (first time point analysis) and 85.71/100/94.7% (longitudinal analysis), compared to 60/78/68% and 70/90/84.2% for the respective radiologist classifications. In group I (single time point), the SVM classifier also outperformed radiologists’ classifications with sensitivity/specificity/accuracy of 86.49/75.00/81.53% (SVM) compared to 75.7/68.9/73.84% (radiologists).ConclusionOur results indicate that utilisation of a machine learning (SVM) classifier based on analysis of longitudinal perfusion time points and combined structural and perfusion features significantly enhances classification outcome (p value= 0.0001).

Hierarchical Cluster Analysis for Gray Matter and Symptom Subtype in Schizophrenia

Schizophrenia is a severe mental illness characterized by cognitive, behavioral, and emotional dysfunction. The Positive and Negative Syndrome Scale (PANSS) assesses severity of three categories of symptoms associated with schizophrenia: positive symptoms, negative symptoms, and general psychopathology. Numerous structural MRI studies have found gray matter reduction in the frontal and temporal lobes, thalamus, and cerebellum in schizophrenia. However, a multilevel association between gray matter and symptom presentation phenotypes has not fully been explored.

Variations in structural MRI quality significantly impact commonly used measures of brain anatomy

Subject motion can introduce noise into neuroimaging data and result in biased estimations of brain structure. In-scanner motion can compromise data quality in a number of ways and varies widely across developmental and clinical populations. However, quantification of structural image quality is often limited to proxy or indirect measures gathered from functional scans; this may be missing true differences related to these potential artifacts. In this study, we take advantage of novel informatic tools, the CAT12 toolbox, to more directly measure image quality from T1-weighted images to understand if these measures of image quality: (1) relate to rigorous quality-control checks visually completed by human raters; (2) are associated with sociodemographic variables of interest; (3) influence regional estimates of cortical surface area, cortical thickness, and subcortical volumes from the commonly used Freesurfer tool suite. We leverage public-access data that includes a community-based sample of children and adolescents, spanning a large age-range (N = 388; ages 5–21). Interestingly, even after visually inspecting our data, we find image quality significantly impacts derived cortical surface area, cortical thickness, and subcortical volumes from multiple regions across the brain (~ 23.4% of all areas investigated). We believe these results are important for research groups completing structural MRI studies using Freesurfer or other morphometric tools. As such, future studies should consider using measures of image quality to minimize the influence of this potential confound in group comparisons or studies focused on individual differences.

Longitudinal assessment of NREM sleep EEG in typically developing and medication-free ADHD adolescents: first year results

ObjectiveClinical observation and structural MRI studies suggest that delayed brain maturation is a major cause of attention deficit hyperactivity disorder (ADHD). Sleep electroencephalogram (EEG) which exhibits major changes across adolescence provides an opportunity to investigate brain electrophysiology evidence for maturational delay. We present data from an ongoing longitudinal study of sleep EEG in medication-free ADHD and typically developing adolescents to investigate brain electrophysiological evidence for this maturational delay. MethodsNine adolescents diagnosed with ADHD (combined presentation, DSM-V criteria, mean age 12.39 ± 0.61 years, 2 females), and nine typically developing controls (12.08 ± 0.35 years, 4 females) were recruited. Subjects underwent an adaptation night and all night polysomnography twice yearly at the Laboratory. ResultsBasic sleep structure did not differ between the ADHD and control groups. In addition, we found no group differences on delta power (p = 0.77), but found a possible trend toward higher theta power (p = 0.057) for the ADHD group. The decline of standardized delta power across the 4 non-rapid eye movement (NREM) periods differed by group (p < 0.05) with the percent delta power in the first NREM period being lower in the ADHD group. ConclusionsOur data support the preponderant evidence that basic sleep structure is unaltered with ADHD. Our data do suggest altered sleep homeostatic recuperative processes in ADHD. The theta findings from the first two recordings are suggestive of a maturational delay associated with ADHD, but follow-up data-points are needed.

Replicability, Repeatability, and Long-term Reproducibility of Cerebellar Morphometry

To identify robust and reproducible methods of cerebellar morphometry that can be used in future large-scale structural MRI studies, we investigated the replicability, repeatability, and long-term reproducibility of three fully automated software tools: FreeSurfer, CEREbellum Segmentation (CERES), and automatic cerebellum anatomical parcellation using U-Net with locally constrained optimization (ACAPULCO). Replicability was defined as computational replicability, determined by comparing two analyses of the same high-resolution MRI data set performed with identical analysis software and computer hardware. Repeatability was determined by comparing the analyses of two MRI scans of the same participant taken during two independent MRI sessions on the same day for the Kirby-21 study. Long-term reproducibility was assessed by analyzing two MRI scans of the same participant in the longitudinal OASIS-2 study. We determined percent difference, the image intraclass correlation coefficient, the coefficient of variation, and the intraclass correlation coefficient between two analyses. Our results show that CERES and ACAPULCO use stochastic algorithms that result in surprisingly high differences between identical analyses for ACAPULCO and small differences for CERES. Changes between two consecutive scans from the Kirby-21 study were less than ± 5% in most cases for FreeSurfer and CERES (i.e., demonstrating high repeatability). As expected, long-term reproducibility was lower than repeatability for all software tools. In summary, CERES is an accurate, as demonstrated before, and reproducible tool for fully automated segmentation and parcellation of the cerebellum. We conclude with recommendations for the assessment of replicability, repeatability, and long-term reproducibility in future studies on cerebellar structure.

Tractographic studies in the human brain at the norm and the paranoid schizophrenia

This study is part of a large interdisciplinary project to create objective criteria for building a classification system for a polymorphic schizophrenic disease characterized by disorders of thinking and perception. Within the framework of the project, for the first time in patients with schizophrenia with hallucinatory-delusional syndrome, neuropsychological testing, complete structural (morphometry and tractography) and functional MRI studies involving a detailed clinical study, determination of the patient’s immunological and genetic status are simultaneously performed. On the basis of a comprehensive analysis of MRI data, it is planned to determine the key architecture of the neural networks of the brain producing the disease, to assess the success of disease therapy and to determine the targets of subsequent therapy based on the application of the method of transcranial magnetic stimulation. This paper presents the primary results of work on the study of the difference between the structural connectomes of schizophrenic patients and the norm. The work is of a search and preliminary nature. As a result of the work, the possibility of classifying the disease was shown and the key structural links for it were identified.

Hypothalamus and amygdala functional connectivity at rest in narcolepsy type 1

Introductionfunctional and structural MRI studies suggest that the orexin (hypocretin) deficiency in the dorso-lateral hypothalamus of narcoleptic patients would influence both brain metabolism and perfusion and would cause reduction in cortical grey matter. Previous fMRI studies have mainly focused on cerebral functioning during emotional processing. The aim of the present study was to explore the hemodynamic behaviour of spontaneous BOLD fluctuation at rest in patients with Narcolepsy type 1 (NT1) close to disease onset. MethodsFifteen drug naïve children/adolescents with NT1 (9 males; mean age 11.7 ± 3 years) and fifteen healthy children/adolescents (9 males; mean age 12.4 ± 2.8 years) participated in an EEG-fMRI study in order to investigate the resting-state functional connectivity of hypothalamus and amygdala. Functional images were acquired on a 3 T system. Seed-based functional connectivity analyses were performed using SPM12. Regions of Interest were the lateral hypothalamus and the amygdala. Resultscompared to controls, NT1 patients showed decreased functional connectivity between the lateral hypothalamus and the left superior parietal lobule, the hippocampus and the parahippocampal gyrus. Decreased functional connectivity was detected between the amygdala and the post-central gyrus and several occipital regions, whereas it was increased between the amygdala and the inferior frontal gyrus, claustrum, insula, and putamen. Conclusionin NT1 patients the abnormal connectivity between the hypothalamus and brain regions involved in memory consolidation during sleep, such as the hippocampus, may be linked to the loss of orexin containing neurons in the dorsolateral hypothalamus. Moreover, also functional connectivity of the amygdala seems to be influenced by the loss of orexin-containing neurons. Therefore, we can hypothesize that dysfunctional interactions between regions subserving the maintenance of arousal, memory and emotional processing may contribute to the main symptom of narcolepsy.

Disentangling neurodegeneration subtypes of Alzheimer’s disease using data‐driven methods

AbstractBackgroundResearch on understanding heterogeneity in Alzheimer’s disease (AD) has traditionally relied on ‘a priori’ categorizations of recognized clinical or pathologic disease variants. More recently, application of clustering methods to high‐dimensional spatial features from neuroimaging data has allowed data‐driven discovery of AD subtypes based on differentiated regional patterns of neurodegeneration.MethodsWe provide an up‐to‐date review of structural MRI studies that leveraged data‐driven approaches to examine heterogeneity in regional neurodegeneration patterns among AD patients. Findings will be discussed in relation to different families of clustering methods employed across studies. We further present primary data from our ongoing studies characterizing AD neurodegeneration subtypes by means of FDG‐PET as a potentially more sensitive molecular imaging marker of neurodegenerative processes.ResultsData‐driven studies across multiple independent cohorts and employed methodologies provide converging evidence for the existence of distinct MRI atrophy subtypes that broadly resemble the differentiation into atypical medial temporal‐ vs neocortical‐predominant patterns characterizing established neuropathological subtypes. These studies not only allowed for a regionally more detailed characterization of the respective atrophy patterns, but also pointed to the existence of more differentiated atrophy profiles within these broad subtype categories. Concordantly, our cluster analyses of FDG‐PET data confirmed a broad distinction into AD subtypes characterized by medial temporal/limbic‐ vs neocortical‐predominant hypometabolism, and at a higher resolution further distinguished a rare frontal variant from the typical temporo‐parietal neocortical pattern (Fig‐1). In a pilot imaging‐pathologic association study based on ante‐mortem FDG‐PET of 34 pathologic AD cases, the neocortical‐predominant subtype was more likely to have neocortical tau Braak stage VI and to have higher CERAD ratings of cortical neuritic plaques, whereas Thal amyloid phase and diffuse plaque ratings did not differ from the limbic‐predominant subtype. The limbic‐predominant subtype had a higher burden of comorbid cerebrovascular disease, but TDP‐43 or Lewy body comorbidity did not differ significantly between subtypes.ConclusionsData‐driven approaches applied to neuroimaging data can give an unbiased and regionally detailed estimate of the distinct neurodegeneration subtypes present among AD dementia patients. Methodological consensus on the optimal clustering techniques and input features is needed to define the most robust subtype‐defining neurodegeneration patterns to be used for patient stratification.

Hippocampal subfield alterations in schizophrenia: A selective review of structural MRI studies

Abstract The hippocampus plays a crucial role in the psychophysiology of schizophrenia. The past few years have seen a rapid growth in studies of hippocampal subfield anatomy using MRI-based volumetry, with exciting new findings particularly in studies of schizophrenia. As findings varied across studies, and given limitations to conducting a meta-analysis at this time based on the number of available studies and their variability in methods, we conducted a literature review to investigate whether volume alterations of hippocampal subfields in schizophrenia are shared across subfields or specific in terms of severity and location, and their relation to genetic and clinical features. Current studies show that severity and location of subfield volume changes are related to risk for schizophrenia, discrimination of psychiatric disorders, severity of psychotic symptoms and cognitive dysfunction, duration of illness, and treatment response. These diverse findings indicate that MRI-based hippocampal subfield volume measurements are a promising clinically-relevant biomarker for future schizophrenia research.

Gray matter changes in chronic heavy cannabis users: a voxel-level study using multivariate pattern analysis approach.

Recent structural MRI studies on gray matter (GM) volumes using group-level mass-univariate statistical analysis suggest that chronic and heavy cannabis exposure may affect brain region-based morphology. In this prospective study, we use a multivariate pattern analysis approach to investigate the voxel-level change of GM densities in chronic heavy cannabis users. Principal component analysis and linear support vector machine are used in this study, resulting in an 88.1% separation between chronic heavy cannabis users (N = 20) and non-cannabis healthy controls (HCs, N = 22) through leave-one-out cross-validation. The model's discriminative pattern showed that GM density decreases in the part of middle frontal gyrus, inferior frontal gyrus, middle temporal gyrus, inferior temporal gyrus and left occipital lobe in heavy cannabis users with respect to HCs and increases in the part of lentiform nucleus, left cerebellum and right parietal lobe. These results suggest that GM densities alteration has taken place on chronic heavy cannabis users compared with HCs at voxel level.

Differentiating bipolar disorder from unipolar depression in youth: A systematic literature review of neuroimaging research studies

Differentiating bipolar disorder from unipolar depression is one of the most difficult clinical questions posed in pediatric psychiatric practices, as misdiagnosis can lead to severe repercussions for the affected child. This study aimed to examine the existing literature that investigates brain differences between bipolar and unipolar mood disorders in children directly, across all neuroimaging modalities. We performed a systematic literature search through PubMed, PsycINFO, Embase, and Medline databases with defined inclusion and exclusion criteria. Nine research studies were included in the systematic qualitative review, including three structural MRI studies, five functional MRI studies, and one MR spectroscopy study. Relevant variables were extracted and brain differences between bipolar and unipolar mood disorders in children as well as healthy controls were qualitatively analyzed. Across the nine studies, our review included 228 subjects diagnosed with bipolar disorder, 268 diagnosed with major depressive disorder, and 299 healthy controls. Six of the reviewed studies differentiated between bipolar and unipolar mood disorders. Differentiation was most commonly found in the anterior cingulate cortex (ACC), insula, and dorsal striatum (putamen and caudate) brain areas. Despite its importance, the current neuroimaging literature on this topic is scarce and presents minimal generalizability.

Brain Metabolism and Structure in Chronic Migraine

The purpose of this paper is to review and synthesize current literature in which neurochemical and structural brain imaging were used to investigate chronic migraine (CM) pathophysiology and to further discuss the clinical implications. Spectroscopic and structural MRI studies have shown the presence of both impaired metabolism and structural alterations in the brain of CM patients. Metabolic changes in key brain regions support the notion of altered energetics and homeostasis as part of CM pathophysiology. Furthermore, CM, like other chronic pain disorders, may undergo structural reorganization in pain-related brain regions following near persistent endogenous painful input. Finally, both imaging techniques may provide potential biomarkers of disease state and progression and may help guide novel therapeutic interventions or strategies. Spectroscopic and structural MRI have revealed novel aspects of CM pathophysiology. Findings from the former support the metabolic theory of migraine pathogenesis.

Using structural and functional MRI as a neuroimaging technique to investigate chronic fatigue syndrome/myalgic encephalopathy: a systematic review

ObjectiveThis systematic review aims to synthesise and evaluate structural MRI (sMRI) and functional MRI (fMRI) studies in chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME).MethodsWe systematically searched Medline and Ovid and included articles...

Sample size evolution in neuroimaging research: An evaluation of highly-cited studies (1990–2012) and of latest practices (2017–2018) in high-impact journals

We evaluated 1038 of the most cited structural and functional (fMRI) magnetic resonance brain imaging papers (1161 studies) published during 1990–2012 and 270 papers (300 studies) published in top neuroimaging journals in 2017 and 2018. 96% of highly cited experimental fMRI studies had a single group of participants and these studies had median sample size of 12, highly cited clinical fMRI studies (with patient participants) had median sample size of 14.5, and clinical structural MRI studies had median sample size of 50. The sample size of highly cited experimental fMRI studies increased at a rate of 0.74 participant/year and this rate of increase was commensurate with the median sample sizes of neuroimaging studies published in top neuroimaging journals in 2017 (23 participants) and 2018 (24 participants). Only 4 of 131 papers in 2017 and 5 of 142 papers in 2018 had pre-study power calculations, most for single t-tests and correlations. Only 14% of highly cited papers reported the number of excluded participants whereas 49% of papers with their own data in 2017 and 2018 reported excluded participants. Publishers and funders should require pre-study power calculations necessitating the specification of effect sizes. The field should agree on universally required reporting standards. Reporting formats should be standardized so that crucial study parameters could be identified unequivocally.

The protective role of Neuregulin1-ErbB4 signaling in a chronic social defeat stress model.

Major depressive disorder (MDD) is a highly prevalent debilitating psychiatric disease and a serious public health problem worldwide. Brain structural MRI and postmortem studies on patients with depression have revealed changes in the anatomy and functionality in various brain regions, including the amygdala, thalamus, hippocampus, and prefrontal cortex (PFC). The alterations in these brain regions could be a result, in part, of the dysregulation of the neurotrophic factors. Neuregulin1 (NRG1) is one of the neurotrophic factors, and our previous study showed that the NRG1-ErbB4 signaling pathway plays a critical role in epilepsy. In this study, we established a chronic social defeat stress (CSDS) model to investigate the role of the NRG1-ErbB4 signaling pathway in depression-like behaviors. In CSDS mice, we found that the NRG1 protein expression levels were significantly decreased both in the medial prefrontal cortex (mPFC) and hippocampus, while phosphorylated ErbB4 only decreased in the mPFC. In addition, lateral ventricle NRG1 administration significantly rescued depression-like behaviors in the susceptible group. The current study suggests that the NRG1-ErbB4 signaling pathway may exert a protective role in MDD.

Neural correlates of meditation a review of structural and functional MRI studies

Here, we review the neurophysiological and neuroimaging changes that mediation induces in structural and functional MRI. The available evidence from structural studies suggests that mediation impacts neuronal plasticity and the functional MRI suggest that there are changes in gray and white matter in subjects who meditate. FMRI studies show that meditation is associated with decreased activity of default mode network and activation of brain regions involved in cognitive and emotional control. Together, the available imaging techniques have revealed that rather than impacting specific brain regions, meditation causes structural and functional changes in large-scale brain networks.

The atypical social brain network in autism: advances in structural and functional MRI studies.

To review advances in structural and functional MRI studies regarding the neural underpinnings of social atypicalities in autism spectrum disorder (ASD). According to the hypothesis that the social brain network, which includes brain regions, such as the amygdala and superior temporal sulcus, may be atypical in ASD, recent structural MRI studies have identified regional gray matter volume abnormalities in the social brain regions in ASD groups compared with the typically developing groups. Studies evaluating gray matter volume covariance and white matter volume/integrity suggested network-level abnormalities associated with the social brain regions. Recent functional MRI studies assessing resting-state neural activity showed reduced functional connectivity among the social brain regions in individuals with ASD compared with typically developing groups. Similarly, task-based functional MRI studies recently revealed a reduction in regional activity and intraregional functional coupling in the social brain regions during the processing of social stimuli in individuals with ASD. These structural and functional MRI studies provide supportive evidence for the hypothesis that an atypical social brain network underlies behavioral social problems in ASD.

Abnormal hippocampal structure and function in juvenile myoclonic epilepsy and unaffected siblings.

Juvenile myoclonic epilepsy is the most common genetic generalized epilepsy syndrome, characterized by a complex polygenetic aetiology. Structural and functional MRI studies demonstrated mesial or lateral frontal cortical derangements and impaired fronto-cortico-subcortical connectivity in patients and their unaffected siblings. The presence of hippocampal abnormalities and associated memory deficits is controversial, and functional MRI studies in juvenile myoclonic epilepsy have not tested hippocampal activation. In this observational study, we implemented multi-modal MRI and neuropsychological data to investigate hippocampal structure and function in 37 patients with juvenile myoclonic epilepsy, 16 unaffected siblings and 20 healthy controls, comparable for age, gender, handedness and hemispheric dominance as assessed with language laterality indices. Automated hippocampal volumetry was complemented by validated qualitative and quantitative morphological criteria to detect hippocampal malrotation, assumed to represent a neurodevelopmental marker. Neuropsychological measures of verbal and visuo-spatial learning and an event-related verbal and visual memory functional MRI paradigm addressed mesiotemporal function. We detected a reduction of mean left hippocampal volume in patients and their siblings compared with controls (P < 0.01). Unilateral or bilateral hippocampal malrotation was identified in 51% of patients and 50% of siblings, against 15% of controls (P < 0.05). For bilateral hippocampi, quantitative markers of verticalization had significantly larger values in patients and siblings compared with controls (P < 0.05). In the patient subgroup, there was no relationship between structural measures and age at disease onset or degree of seizure control. No overt impairment of verbal and visual memory was identified with neuropsychological tests. Functional mapping highlighted atypical patterns of hippocampal activation, pointing to abnormal recruitment during verbal encoding in patients and their siblings [P < 0.05, familywise error (FWE)-corrected]. Subgroup analyses indicated distinct profiles of hypoactivation along the hippocampal long axis in juvenile myoclonic epilepsy patients with and without malrotation; patients with malrotation also exhibited reduced frontal recruitment for verbal memory, and more pronounced left posterior hippocampal involvement for visual memory. Linear models across the entire study cohort indicated significant associations between morphological markers of hippocampal positioning and hippocampal activation for verbal items (all P < 0.05, FWE-corrected). We demonstrate abnormalities of hippocampal volume, shape and positioning in patients with juvenile myoclonic epilepsy and their siblings, which are associated with reorganization of function and imply an underlying neurodevelopmental mechanism with expression during the prenatal stage. Co-segregation of abnormal hippocampal morphology in patients and their siblings is suggestive of a genetic imaging phenotype, independent of disease activity, and can be construed as a novel endophenotype of juvenile myoclonic epilepsy.

Posterior fossa syndrome and increased mean diffusivity in the olivary bodies.

Posterior fossa syndrome (PFS) is a common postoperative complication following resection of posterior fossa tumors in children. It typically presents 1 to 2 days after surgery with mutism, ataxia, emotional lability, and other behavioral symptoms. Recent structural MRI studies have found an association between PFS and hypertrophic olivary degeneration, which is detectable as T2 hyperintensity in the inferior olivary nuclei (IONs) months after surgery. In this study, the authors investigated whether immediate postoperative diffusion tensor imaging (DTI) of the ION can serve as an early imaging marker of PFS. The authors retrospectively reviewed pediatric brain tumor patients treated at their institution, Lucile Packard Children's Hospital at Stanford, from 2004 to 2016. They compared the immediate postoperative DTI studies obtained in 6 medulloblastoma patients who developed PFS to those of 6 age-matched controls. Patients with PFS had statistically significant increased mean diffusivity (MD) in the left ION (1085.17 ± 215.51 vs 860.17 ± 102.64, p = 0.044) and variably increased MD in the right ION (923.17 ± 119.2 vs 873.67 ± 60.16, p = 0.385) compared with age-matched controls. Patients with PFS had downward trending fractional anisotropy (FA) in both the left (0.28 ± 0.06 vs 0.23 ± 0.03, p = 0.085) and right (0.29 ± 0.06 vs 0.25 ± 0.02, p = 0.164) IONs compared with age-matched controls, although neither of these values reached statistical significance. Increased MD in the ION is associated with development of PFS. ION MD changes may represent an early imaging marker of PFS.

Socioeconomic status and brain structure and functions: A critical review

The socioeconomic status (SES) of individuals has an enormous impact on their mental health (e.g., cognitive function and emotional well-being). Given that the brain is the biological basis of cognition and emotion, understanding the relationship between SES and brain structure and function may help to alleviate the negative impact of SES on the mental health of individuals. Over the past two decades, cognitive neuroscientists have explored the relationship between SES and the brain using state-of-the-art brain imaging techniques, such as event-related potential (ERP) and (functional) magnetic resonance imaging (fMRI/MRI). While some studies have found that SES indices were related to brain structure and function, other studies have reported negative results. Therefore, it is crucial to evaluate the existing literature critically. The current paper reviewed studies that explored the relationship between SES and brain structure as well as those investigating the relationship between SES and brain function. For both lines of research, we organized studies around both cognition and emotion. Our review has the following findings. First, structural MRI studies suggest that SES level may be related to the hippocampus and frontal lobe, which are considered responsible for memory and executive function, and the amygdala, anterior cingulate cortex (ACC) and insular cortex, which are involved in emotional processing. Second, fMRI studies found that individuals (especially children) from different SES backgrounds had similar behavioral performances on cognitive tasks (e.g., executive function, memory, learning, mathematics, language, etc.) but their brain activities showed different patterns. fMRI studies also revealed that, compared to individuals from high SES backgrounds, individuals from low SES backgrounds may be more sensitive to negative emotions and have different neurobiological mechanisms of emotion regulation. These findings are consistent with the fact that people with low SES are more vulnerable to mental disorders. However, the field faces several challenges that might severely undermine the credibility of its findings: the complexity and flexibility of measuring SES, the complexity and flexibility of measuring brain structure and function, and the complexity of the possible paths by which SES can affect the brain. To overcome these challenges, we suggest that future studies should measure more SES indices, be transparent and open as to the brain data analyses, and consider the interaction between SES and brain development and the proximal factors through which SES interacts with the brain. Finally, researchers from different countries may also consider the relative SES among nations and adopt a multisite approach to study the relationship between SES and the brain. By deepening the understanding of the relationship between SES and the brain, cognitive neuroscience may contribute to creating a healthy and fair society.