Neural representation of the parent–child attachment from infancy to adulthood

Attachment theory is built on the assumption of consistency; the mother–infant bond is thought to underpin the life-long representations individuals construct of attachment relationships. Still, consistency in the individual’s neural response to attachment-related stimuli representing his or her entire relational history has not been investigated. Mothers and children were followed across two decades and videotaped in infancy (3–6 months), childhood (9–12 years) and young adulthood (18–24 years). In adulthood, participants underwent functional magnetic resonance imaging while exposed to videos of own mother–child interactions (Self) vs unfamiliar interactions (Other). Self-stimuli elicited greater activations across preregistered nodes of the human attachment network, including thalamus-to-brainstem, amygdala, hippocampus, anterior cingulate cortex (ACC), insula and temporal cortex. Critically, self-stimuli were age-invariant in most regions of interest despite large variability in social behavior, and Bayesian analysis showed strong evidence for lack of age-related differences. Psycho–physiological interaction analysis indicated that self-stimuli elicited tighter connectivity between ACC and anterior insula, consolidating an interface associating information from exteroceptive and interceptive sources to sustain attachment representations. Child social engagement behavior was individually stable from infancy to adulthood and linked with greater ACC and insula response to self-stimuli. Findings demonstrate overlap in circuits sustaining parental and child attachment and accord with perspectives on the continuity of attachment across human development.     

In search of convergent regional brain abnormality in cognitive emotion regulation: A transdiagnostic neuroimaging meta‐analysis

Ineffective use of adaptive cognitive strategies (e.g., reappraisal) to regulate emotional states is often reported in a wide variety of psychiatric disorders, suggesting a common characteristic across different diagnostic categories. However, the extent of shared neurobiological impairments is incompletely understood. This study, therefore, aimed to identify the transdiagnostic neural signature of disturbed reappraisal using the coordinate‐based meta‐analysis (CBMA) approach. Following the best‐practice guidelines for conducting neuroimaging meta‐analyses, we systematically searched PubMed, ScienceDirect, and Web of Science databases and tracked the references. Out of 1,608 identified publications, 32 whole‐brain neuroimaging studies were retrieved that compared brain activation in patients with psychiatric disorders and healthy controls during a reappraisal task. Then, the reported peak coordinates of group comparisons were extracted and several activation likelihood estimation (ALE) analyses were performed at three hierarchical levels to identify the potential spatial convergence: the global level (i.e., the pooled analysis and the analyses of increased/decreased activations), the experimental‐contrast level (i.e., the analyses of grouped data based on the regulation goal, stimulus valence, and instruction rule) and the disorder‐group level (i.e., the analyses across the experimental‐contrast level focused on increasing homogeneity of disorders). Surprisingly, none of our analyses provided significant convergent findings. This CBMA indicates a lack of transdiagnostic convergent regional abnormality related to reappraisal task, probably due to the complex nature of cognitive emotion regulation, heterogeneity of clinical populations, and/or experimental and statistical flexibility of individual studies.     

Deep‐TOF‐PET: Deep learning‐guided generation of time‐of‐flight from non‐TOF brain PET images in the image and projection domains

We aim to synthesize brain time‐of‐flight (TOF) PET images/sinograms from their corresponding non‐TOF information in the image space (IS) and sinogram space (SS) to increase the signal‐to‐noise ratio (SNR) and contrast of abnormalities, and decrease the bias in tracer uptake quantification. One hundred forty clinical brain ¹⁸F‐FDG PET/CT scans were collected to generate TOF and non‐TOF sinograms. The TOF sinograms were split into seven time bins (0, ±1, ±2, ±3). The predicted TOF sinogram was reconstructed and the performance of both models (IS and SS) compared with reference TOF and non‐TOF. Wide‐ranging quantitative and statistical analysis metrics, including structural similarity index metric (SSIM), root mean square error (RMSE), as well as 28 radiomic features for 83 brain regions were extracted to evaluate the performance of the CycleGAN model. SSIM and RMSE of 0.99 ± 0.03, 0.98 ± 0.02 and 0.12 ± 0.09, 0.16 ± 0.04 were achieved for the generated TOF‐PET images in IS and SS, respectively. They were 0.97 ± 0.03 and 0.22 ± 0.12, respectively, for non‐TOF‐PET images. The Bland & Altman analysis revealed that the lowest tracer uptake value bias (−0.02%) and minimum variance (95% CI: −0.17%, +0.21%) were achieved for TOF‐PET images generated in IS. For malignant lesions, the contrast in the test dataset was enhanced from 3.22 ± 2.51 for non‐TOF to 3.34 ± 0.41 and 3.65 ± 3.10 for TOF PET in SS and IS, respectively. The implemented CycleGAN is capable of generating TOF from non‐TOF PET images to achieve better image quality.     

A deep learning based approach identifies regions more relevant than resting‐state networks to the prediction of general intelligence from resting‐state fMRI

Prediction of cognitive ability latent factors such as general intelligence from neuroimaging has elucidated questions pertaining to their neural origins. However, predicting general intelligence from functional connectivity limit hypotheses to that specific domain, being agnostic to time‐distributed features and dynamics. We used an ensemble of recurrent neural networks to circumvent this limitation, bypassing feature extraction, to predict general intelligence from resting‐state functional magnetic resonance imaging regional signals of a large sample (n = 873) of Human Connectome Project adult subjects. Ablating common resting‐state networks (RSNs) and measuring degradation in performance, we show that model reliance can be mostly explained by network size. Using our approach based on the temporal variance of saliencies, that is, gradients of outputs with regards to inputs, we identify a candidate set of networks that more reliably affect performance in the prediction of general intelligence than similarly sized RSNs. Our approach allows us to further test the effect of local alterations on data and the expected changes in derived metrics such as functional connectivity and instantaneous innovations.     

The nature of the self: Neural analyses and heritability estimates of self‐evaluations in middle childhood

How neural correlates of self‐concept are influenced by environmental versus genetic factors is currently not fully understood. We investigated heritability estimates of behavioral and neural correlates of self‐concept in middle childhood since this phase is an important time window for taking on new social roles in academic and social contexts. To do so, a validated self‐concept fMRI task was applied in a twin sample of 345 participants aged between 7 and 9 years. In the self‐concept condition, participants were asked to indicate whether academic and social traits applied to them whereas the control condition required trait categorization. The self‐processing activation analyses (n = 234) revealed stronger medial prefrontal cortex (mPFC) activation for self than for control conditions. This effect was more pronounced for social‐self than academic self‐traits, whereas stronger dorsolateral prefrontal cortex (DLPFC) activation was observed for academic versus social self‐evaluations. Behavioral genetic modeling (166 complete twin pairs) revealed that 25–52% of the variation in academic self‐evaluations was explained by genetic factors, whereas 16–49% of the variation in social self‐evaluations was explained by shared environmental factors. Neural genetic modeling (91 complete twin pairs) for variation in mPFC and anterior prefrontal cortex (PFC) activation for academic self‐evaluations confirmed genetic and unique environmental influences, whereas anterior PFC activation for social self‐evaluations was additionally influenced by shared environmental influences. This indicates that environmental context possibly has a larger impact on the behavioral and neural correlates of social self‐concept at a young age. This is the first study demonstrating in a young twin sample that self‐concept depends on both genetic and environmental factors, depending on the specific domain.     

An event‐based magnetoencephalography study of simulated driving: Establishing a novel paradigm to probe the dynamic interplay of executive and motor function

Magnetoencephalography (MEG) is particularly well‐suited to the study of human motor cortex oscillatory rhythms and motor control. However, the motor tasks studied to date are largely overly simplistic. This study describes a new approach: a novel event‐based simulated drive made operational via MEG compatible driving simulator hardware, paired with differential beamformer methods to characterize the neural correlates of realistic, complex motor activity. We scanned 23 healthy individuals aged 16–23 years (mean age = 19.5, SD = 2.5; 18 males and 5 females, all right‐handed) who completed a custom‐built repeated trials driving scenario. MEG data were recorded with a 275‐channel CTF, and a volumetric magnetic resonance imaging scan was used for MEG source localization. To validate this paradigm, we hypothesized that pedal‐use would elicit expected modulation of primary motor responses beta‐event‐related desynchronization (B‐ERD) and movement‐related gamma synchrony (MRGS). To confirm the added utility of this paradigm, we hypothesized that the driving task could also probe frontal cognitive control responses (specifically, frontal midline theta [FMT]). Three of 23 participants were removed due to excess head motion (>1.5 cm/trial), confirming feasibility. Nonparametric group analysis revealed significant regions of pedal‐use related B‐ERD activity (at left precentral foot area, as well as bilateral superior parietal lobe: p < .01 corrected), MRGS (at medial precentral gyrus: p < .01 corrected), and FMT band activity sustained around planned braking (at bilateral superior frontal gyrus: p < .01 corrected). This paradigm overcomes the limits of previous efforts by allowing for characterization of the neural correlates of realistic, complex motor activity in terms of brain regions, frequency bands and their dynamic temporal interplay.     

The age‐related changes in 40 Hz Auditory Steady‐State Response and sustained Event‐Related Fields to the same amplitude‐modulated tones in typically developing children: A magnetoencephalography study

Recent studies have revealed that gamma‐band oscillatory and transient evoked potentials may change with age during childhood. It is hypothesized that these changes can be associated with a maturation of GABAergic neurotransmission and, subsequently, the age‐related changes of excitation–inhibition balance in the neural circuits. One of the reliable paradigms for investigating these effects in the auditory cortex is 40 Hz Auditory Steady‐State Response (ASSR), where participants are presented with the periodic auditory stimuli. It is known that such stimuli evoke two types of responses in magnetoencephalography (MEG)—40 Hz steady‐state gamma response (or 40 Hz ASSR) and auditory evoked response called sustained Event‐Related Field (ERF). Although several studies have been conducted in children, focusing on the changes of 40 Hz ASSR with age, almost nothing is known about the age‐related changes of the sustained ERF to the same periodic stimuli and their relationships with changes in the gamma strength. Using MEG, we investigated the association between 40 Hz steady‐state gamma response and sustained ERF response to the same stimuli and also their age‐related changes in the group of 30 typically developing 7‐to‐12‐year‐old children. The results revealed a tight relationship between 40 Hz ASSR and ERF, indicating that the age‐related increase in strength of 40 Hz ASSR was associated with the age‐related decrease of the amplitude of ERF. These effects were discussed in the light of the maturation of the GABAergic system and excitation–inhibition balance development, which may contribute to the changes in ASSR and ERF.     

Hypoxic glioma‐derived extracellular vesicles harboring MicroRNA‐10b‐5p enhance M2 polarization of macrophages to promote the development of glioma

IntroductionThe delivery of biomolecules by tumor cell‐secreted extracellular vesicles (EVs) is linked to the development of glioma. Here, the present study was implemented to explore the functional significance of hypoxic glioma cell‐derived EVs carrying microRNA‐10b‐5 (miR‐10b‐5p) on glioma with the involvement of polarization of M2 macrophages.MethodsEVs were isolated from hypoxia‐stimulated glioma cells, and their role in polarization of M2 macrophages was studied by co‐culturing with macrophages. miR‐10b‐5p expression in glioma tissues, glioma‐derived EVs, and macrophages co‐cultured with EVs was characterized. Interaction among miR‐10b‐5p, NEDD4L, and PIK3CA was analyzed. The macrophages or glioma cells were transfected with overexpressing plasmid or shRNA to study the effects of miR‐10b‐5p/NEDD4L/PIK3CA on M2 macrophage polarization, and glioma cell proliferation, migration, and invasion in vitro and in vivo. ResultsPromotive role of hypoxia‐stimulated glioma‐derived EVs in macrophage M2 polarization was confirmed. Elevation of miR‐10b‐5p occurred in glioma tissues, glioma‐derived EVs and macrophages co‐cultured with EVs, and stimulated M2 polarization of macrophages. NEDD4L was a target gene of miR‐10b‐5p. Overexpression of NEDD4L could inhibit PI3K/AKT pathway through increase in ubiquitination and degradation of PIK3CA. Hypoxic glioma‐derived EVs harboring upregulated miR‐10b‐5p triggered an M2 phenotype in macrophages as well as enhanced aggressive tumor biology of glioma cells via inhibition of PIK3CA/PI3K/AKT pathway by targeting NEDD4L.ConclusionsIn summary, miR‐10b‐5p delivered by hypoxic glioma‐derived EVs accelerated macrophages M2 polarization to promote the progression of glioma via NEDD4L/PIK3CA/PI3K/AKT axis.     

Ten years of enhancing neuro‐imaging genetics through meta‐analysis: An overview from the ENIGMA Genetics Working Group

Here we review the motivation for creating the enhancing neuroimaging genetics through meta‐analysis (ENIGMA) Consortium and the genetic analyses undertaken by the consortium so far. We discuss the methodological challenges, findings, and future directions of the genetics working group. A major goal of the working group is tackling the reproducibility crisis affecting “candidate gene” and genome‐wide association analyses in neuroimaging. To address this, we developed harmonized analytic methods, and support their use in coordinated analyses across sites worldwide, which also makes it possible to understand heterogeneity in results across sites. These efforts have resulted in the identification of hundreds of common genomic loci robustly associated with brain structure. We have found both pleiotropic and specific genetic effects associated with brain structures, as well as genetic correlations with psychiatric and neurological diseases.     

Deep‐learning based fully automatic segmentation of the globus pallidus interna and externa using ultra‐high 7 Tesla MRI

Deep brain stimulation (DBS) surgery has been shown to dramatically improve the quality of life for patients with various motor dysfunctions, such as those afflicted with Parkinson''s disease (PD), dystonia, and essential tremor (ET), by relieving motor symptoms associated with such pathologies. The success of DBS procedures is directly related to the proper placement of the electrodes, which requires the ability to accurately detect and identify relevant target structures within the subcortical basal ganglia region. In particular, accurate and reliable segmentation of the globus pallidus (GP) interna is of great interest for DBS surgery for PD and dystonia. In this study, we present a deep‐learning based neural network, which we term GP‐net, for the automatic segmentation of both the external and internal segments of the globus pallidus. High resolution 7 Tesla images from 101 subjects were used in this study; GP‐net is trained on a cohort of 58 subjects, containing patients with movement disorders as well as healthy control subjects. GP‐net performs 3D inference in a patient‐specific manner, alleviating the need for atlas‐based segmentation. GP‐net was extensively validated, both quantitatively and qualitatively over 43 test subjects including patients with movement disorders and healthy control and is shown to consistently produce improved segmentation results compared with state‐of‐the‐art atlas‐based segmentations. We also demonstrate a postoperative lead location assessment with respect to a segmented globus pallidus obtained by GP‐net.     

Spinal microglial β‐endorphin signaling mediates IL‐10 and exenatide‐induced inhibition of synaptic plasticity in neuropathic pain

AimThis study aimed to investigate the regulation of pain hypersensitivity induced by the spinal synaptic transmission mechanisms underlying interleukin (IL)‐10 and glucagon‐like peptide 1 receptor (GLP‐1R) agonist exenatide‐induced pain anti‐hypersensitivity in neuropathic rats through spinal nerve ligations.MethodsNeuropathic pain model was established by spinal nerve ligation of L5/L6 and verified by electrophysiological recording and immunofluorescence staining. Microglial expression of β‐endorphin through autocrine IL‐10‐ and exenatide‐induced inhibition of glutamatergic transmission were performed by behavioral tests coupled with whole‐cell recording of miniature excitatory postsynaptic currents (mEPSCs) and miniature inhibitory postsynaptic currents (mIPSCs) through application of endogenous and exogenous IL‐10 and β‐endorphin.ResultsIntrathecal injections of IL‐10, exenatide, and the μ‐opioid receptor (MOR) agonists β‐endorphin and DAMGO inhibited thermal hyperalgesia and mechanical allodynia in neuropathic rats. Whole‐cell recordings of bath application of exenatide, IL‐10, and β‐endorphin showed similarly suppressed enhanced frequency and amplitude of the mEPSCs in the spinal dorsal horn neurons of laminae II, but did not reduce the frequency and amplitude of mIPSCs in neuropathic rats. The inhibitory effects of IL‐10 and exenatide on pain hypersensitive behaviors and spinal synaptic plasticity were totally blocked by pretreatment of IL‐10 antibody, β‐endorphin antiserum, and MOR antagonist CTAP. In addition, the microglial metabolic inhibitor minocycline blocked the inhibitory effects of IL‐10 and exenatide but not β‐endorphin on spinal synaptic plasticity.ConclusionThis suggests that spinal microglial expression of β‐endorphin mediates IL‐10‐ and exenatide‐induced inhibition of glutamatergic transmission and pain hypersensitivity via presynaptic and postsynaptic MORs in spinal dorsal horn.     

Mega‐analysis methods in ENIGMA: The experience of the generalized anxiety disorder working group

The ENIGMA group on Generalized Anxiety Disorder (ENIGMA‐Anxiety/GAD) is part of a broader effort to investigate anxiety disorders using imaging and genetic data across multiple sites worldwide. The group is actively conducting a mega‐analysis of a large number of brain structural scans. In this process, the group was confronted with many methodological challenges related to study planning and implementation, between‐country transfer of subject‐level data, quality control of a considerable amount of imaging data, and choices related to statistical methods and efficient use of resources. This report summarizes the background information and rationale for the various methodological decisions, as well as the approach taken to implement them. The goal is to document the approach and help guide other research groups working with large brain imaging data sets as they develop their own analytic pipelines for mega‐analyses.     

Response inhibition results in the emotional devaluation of faces: neural correlates as revealed by fMRI

Although it is well established that prior experience with faces determines their subsequent social-emotional evaluation, recent work shows that top-down inhibitory mechanisms, including response inhibition, can lead to social devaluation after even a single, brief exposure. These rapidly induced effects indicate interplay among perceptual, attentional, response-selection and social-emotional networks; yet, the brain mechanisms underlying this are not well understood. This study used functional magnetic resonance imaging (fMRI) to investigate the neural mechanism mediating the relationship between inhibitory control and emotional devaluation. Participants performed two tasks: (i) a Go/No-Go task in response to faces and (ii) a trustworthiness rating task involving the previously seen faces. No-Go faces were rated as significantly less trustworthy than Go faces. By examining brain activations during Task 1, behavioral measures and brain activations obtained in Task 2 could be predicted. Specifically, activity in brain areas during Task 1 associated with (i) executive control and response suppression (i.e. lateral prefrontal cortex) and (ii) affective responses and value representation (i.e. orbitofrontal cortex), systematically covaried with behavioral ratings and amygdala activity obtained during Task 2. The present findings offer insights into the neural mechanisms linking inhibitory processes to affective responses.     

BESST (Bochum Emotional Stimulus Set)—A pilot validation study of a stimulus set containing emotional bodies and faces from frontal and averted views

This article introduces the freely available Bochum Emotional Stimulus Set (BESST), which contains pictures of bodies and faces depicting either a neutral expression or one of the six basic emotions (happiness, sadness, fear, anger, disgust, and surprise), presented from two different perspectives (0° frontal view vs. camera averted by 45° to the left). The set comprises 565 frontal view and 564 averted view pictures of real-life bodies with masked facial expressions and 560 frontal and 560 averted view faces which were synthetically created using the FaceGen 3.5 Modeller. All stimuli were validated in terms of categorization accuracy and the perceived naturalness of the expression. Additionally, each facial stimulus was morphed into three age versions (20/40/60 years). The results show high recognition of the intended facial expressions, even under speeded forced-choice conditions, as corresponds to common experimental settings. The average naturalness ratings for the stimuli range between medium and high.     

Phenotypic expansion of KCNH1 ‐associated disorders to include isolated epilepsy and its associations with genotypes and molecular sub‐regional locations

PurposeGenotype‐phenotypic correlation of KCNH1 variant remains elusive. This study aimed to expand the phenotypic spectrum of KCNH1 and explore the correlations between epilepsy and molecular sub‐regional locations.MethodsWe performed whole‐exome sequencing in a cohort of 98 patients with familiar febrile seizure (FS) or epilepsy with unexplained etiologies. The damaging effects of variants were predicted by protein modeling and multiple in silico tools. All reported patients with KCNH1 pathogenic variants with detailed neurological phenotypes were analyzed to evaluate the genotype‐phenotype correlation.ResultsTwo novel KCNH1 variants were identified in three cases, including two patients with FS with inherited variant (p.Ile113Thr) and one boy with epilepsy with de novo variant (p.Arg357Trp). Variant Ile113Thr was located within the eag domain, and variant p.Arg357Trp was located in transmembrane domain 4 of KCNH1, respectively. Two patients experienced refractory status epilepticus (SE), of which one patient died of acute encephalopathy induced by SE. Further analysis of 30 variants in 51 patients demonstrated that de novo variants were associated with epileptic encephalopathy, while mosaic/somatic or germline variants cause isolated epilepsy/FS. All hotspot variants associated with epileptic encephalopathy clustered in transmembrane domain (S4 and S6), while those with isolated epilepsy/seizures or TBS/ZLS without epilepsy were scattered in the KCNH1.ConclusionsWe found two novel missense variants of KCNH1 in three individuals with isolated FS/epilepsy. Variants in the KCNH1 cause a spectrum of epileptic disorders ranging from a benign form of genetic isolated epilepsy/FS to intractable form of epileptic encephalopathy. The genotypes and variant locations help explaining the phenotypic variation of patients with KCNH1 variant.     

Elucidating the structural–functional connectome of language in glioma‐induced aphasia using nTMS and DTI

Glioma‐induced aphasia (GIA) is frequently observed in patients with newly diagnosed gliomas. Previous studies showed an impact of gliomas not only on local brain regions but also on the functionality and structure of brain networks. The current study used navigated transcranial magnetic stimulation (nTMS) to localize language‐related regions and to explore language function at the network level in combination with connectome analysis. Thirty glioma patients without aphasia (NA) and 30 patients with GIA were prospectively enrolled. Tumors were located in the vicinity of arcuate fasciculus‐related cortical and subcortical regions. The visualized ratio (VR) of each tract was calculated based on their respective fractional anisotropy (FA) and maximal FA. Using a thresholding method of each tract at 25% VR and 50% VR, DTI‐based tractography was performed to construct structural brain networks for graph‐based connectome analysis, containing functional data acquired by nTMS. The average degree of left hemispheric networks (M _left) was higher in the NA group than in the GIA group for both VR thresholds. Differences of global and local efficiency between 25% and 50% VR thresholds were significantly lower in the NA group than in the GIA group. Aphasia levels correlated with connectome properties in M _left and networks based on positive nTMS mapping regions (M _pos). A more substantial relation to language performance was found in M _pos and M _left compared to the network of negative mapping regions (M _neg). Gliomas causing deterioration of language are related to various cerebral networks. In NA patients, mainly M _neg was impacted, while M _pos was impacted in GIA patients.     

Mindfulness‐based cognitive therapy on bereavement grief: Alterations of resting‐state network connectivity associate with changes of anxiety and mindfulness

Bereavement, the experience of losing a loved one, is one of the most catastrophic but inevitable events in life. It causes grief and intense depression‐like sadness. Recent studies have revealed the effectiveness and proficiency of mindfulness‐based cognitive therapy (MBCT) in emotional regulation among bereavement populations. MBCT improves the well‐being of the bereaved by enhancing cognitive performances. Regarding the neural correlates of bereavement grief, previous studies focused on the alleviation of emotion–cognition interferences at specific brain regions. Here, we hypothesized that the bereavement grief fundamentally triggers global alterations in the resting‐state brain networks and part of the internetwork connectivity could be reformed after MBCT intervention. We recruited 19 bereaved individuals who participated the 8‐week MBCT program. We evaluated (a) the large‐scale changes in brain connectivity affected by the MBCT program; as well as (b) the association between connectivity changes and self‐rated questionnaire. First, after MBCT, the bereaved individuals showed the reduction of the internetwork connectivity in the salience, default‐mode and fronto‐parietal networks in the resting state but not under emotional arousal, implying the alleviated attention to spontaneous mind wandering after MBCT. Second, the alterations of functional connectivity between subcortical (e.g., caudate) and cortical networks (e.g., cingulo‐opercular/sensorimotor) were associated with the changes of the mindfulness scale, the anxiety and the emotion regulation ability. In summary, MBCT could enhance spontaneous emotion regulation among the bereaved individuals through the internetwork reorganizations in the resting state.     

The development of neural responses to emotional faces: A review of evidence from event-related potentials during early and middle childhood

Facial emotion processing (FEP) develops throughout childhood and provides crucial social information necessary for the interpretation and prediction of others’ behaviour. This systematic review, which includes a meta-regression component, sought to explore the development of FEP event-related potentials (P100, N170, and late positive potential [LPP]) in children aged three to twelve years. Thirty-four studies, representing data from 1511 children, were included in the review. The combination of meta-regression and systematic review suggest that P100 amplitude decreases with increasing age in response to emotional facial stimuli. P100 latency may show a gradual decrease around the age of ten. In terms of the N170, it is suggested that amplitude follows a non-linear trend with age, and latency may decrease in early childhood before plateauing during middle childhood. Of note, review of the literature indicates that substantial methodological differences and high levels of heterogeneity exist. We suggest future research considers these results within the context of emotion-specific development, whilst also acknowledging how this may relate to individual social functioning skills across early-to-middle childhood.