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Journal of Child Psychology and... Apr 2023Theories of the intergenerational transmission of depression emphasize alterations in emotion processing among offspring of depressed mothers as a key risk mechanism,... (Review)
Review
BACKGROUND
Theories of the intergenerational transmission of depression emphasize alterations in emotion processing among offspring of depressed mothers as a key risk mechanism, raising questions about biological processes contributing to these alterations. The objective of this systematic annual research review was to examine and integrate studies of the associations between maternal depression diagnoses and offspring's emotion processing from birth through adolescence across biological measures including autonomic psychophysiology, electroencephalography (EEG), magnetoencephalography (MEG), event-related potentials (ERP), and structural and functional magnetic resonance imaging (MRI).
METHODS
The review was conducted in accordance with the PRISMA 2020 standards. A systematic search was conducted in PsycInfo and PubMed in 2022 for studies that included, 1) mothers with and without DSM-defined depressive disorders assessed via a clinical or diagnostic interview, and 2) measures of offspring emotion processing assessed at the psychophysiological or neural level between birth and 18 years of age.
RESULTS
Findings from 64 studies indicated that young offspring of mothers with depression histories exhibit heightened corticolimbic activation to negative emotional stimuli, reduced left frontal brain activation, and reduced ERP and mesocorticolimbic responses to reward cues compared to offspring of never-depressed mothers. Further, activation of resting-state networks involved in affective processing differentiate offspring of depressed relative to nondepressed mothers. Some of these alterations were only apparent among youth of depressed mothers exposed to negative environmental contexts or exhibiting current emotional problems. Further, some of these patterns were observable in infancy, reflecting very early emerging vulnerabilities.
CONCLUSIONS
This systematic review provides evidence that maternal depression is associated with alterations in emotion processing across several biological units of analysis in offspring. We present a preliminary conceptual model of the role of deficient emotion processing in pathways from maternal depression to offspring psychopathology and discuss future research avenues addressing limitations of the existing research and clinical implications.
Topics: Female; Adolescent; Humans; Mothers; Depression; Child of Impaired Parents; Emotions; Cerebral Cortex
PubMed: 36511171
DOI: 10.1111/jcpp.13734 -
Pain Jun 2023Reliable and objective biomarkers promise to improve the assessment and treatment of chronic pain. Resting-state electroencephalography (EEG) is broadly available, easy...
Reliable and objective biomarkers promise to improve the assessment and treatment of chronic pain. Resting-state electroencephalography (EEG) is broadly available, easy to use, and cost efficient and, therefore, appealing as a potential biomarker of chronic pain. However, results of EEG studies are heterogeneous. Therefore, we conducted a systematic review (PROSPERO CRD42021272622) of quantitative resting-state EEG and magnetoencephalography (MEG) studies in adult patients with different types of chronic pain. We excluded populations with severe psychiatric or neurologic comorbidity. Risk of bias was assessed using a modified Newcastle-Ottawa Scale. Semiquantitative data synthesis was conducted using modified albatross plots. We included 76 studies after searching MEDLINE, Web of Science Core Collection, Cochrane Central Register of Controlled Trials, and EMBASE. For cross-sectional studies that can serve to develop diagnostic biomarkers, we found higher theta and beta power in patients with chronic pain than in healthy participants. For longitudinal studies, which can yield monitoring and/or predictive biomarkers, we found no clear associations of pain relief with M/EEG measures. Similarly, descriptive studies that can yield diagnostic or monitoring biomarkers showed no clear correlations of pain intensity with M/EEG measures. Risk of bias was high in many studies and domains. Together, this systematic review synthesizes evidence on how resting-state M/EEG might serve as a diagnostic biomarker of chronic pain. Beyond, this review might help to guide future M/EEG studies on the development of pain biomarkers.
Topics: Adult; Humans; Magnetoencephalography; Chronic Pain; Cross-Sectional Studies; Electroencephalography; Biomarkers
PubMed: 36409624
DOI: 10.1097/j.pain.0000000000002825 -
Journal of Clinical Medicine Sep 2022Swallowing is a complex function that relies on both brainstem and cerebral control. Cerebral neurofunctional evaluations are mostly based on functional magnetic... (Review)
Review
Swallowing is a complex function that relies on both brainstem and cerebral control. Cerebral neurofunctional evaluations are mostly based on functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), performed with the individual laying down; which is a non-ecological/non-natural position for swallowing. According to the PRISMA guidelines, a review of the non-invasive non-radiating neurofunctional tools, other than fMRI and PET, was conducted to explore the cerebral activity in swallowing during natural food intake, in accordance with the PRISMA guidelines. Using Embase and PubMed, we included human studies focusing on neurofunctional imaging during an ecologic swallowing task. From 5948 unique records, we retained 43 original articles, reporting on three different techniques: electroencephalography (EEG), magnetoencephalography (MEG) and functional near infra-red spectroscopy (fNIRS). During swallowing, all three techniques showed activity of the pericentral cortex. Variations were associated with the modality of the swallowing process (volitional or non-volitional) and the substance used (mostly water and saliva). All techniques have been used in both healthy and pathological conditions to explore the precise time course, localization or network structure of the swallowing cerebral activity, sometimes even more precisely than fMRI. EEG and MEG are the most advanced and mastered techniques but fNIRS is the most ready-to-use and the most therapeutically promising. Ongoing development of these techniques will support and improve our future understanding of the cerebral control of swallowing.
PubMed: 36143127
DOI: 10.3390/jcm11185480 -
The Journal of Headache and Pain Aug 2022The diagnosis of migraine is mainly clinical and self-reported, which makes additional examinations unnecessary in most cases. Migraine can be subtyped into chronic (CM)... (Review)
Review
Headache-related circuits and high frequencies evaluated by EEG, MRI, PET as potential biomarkers to differentiate chronic and episodic migraine: Evidence from a systematic review.
BACKGROUND
The diagnosis of migraine is mainly clinical and self-reported, which makes additional examinations unnecessary in most cases. Migraine can be subtyped into chronic (CM) and episodic (EM). Despite the very high prevalence of migraine, there are no evidence-based guidelines for differentiating between these subtypes other than the number of days of migraine headache per month. Thus, we consider it timely to perform a systematic review to search for physiological evidence from functional activity (as opposed to anatomical structure) for the differentiation between CM and EM, as well as potential functional biomarkers. For this purpose, Web of Science (WoS), Scopus, and PubMed databases were screened.
FINDINGS
Among the 24 studies included in this review, most of them (22) reported statistically significant differences between the groups of CM and EM. This finding is consistent regardless of brain activity acquisition modality, ictal stage, and recording condition for a wide variety of analyses. That speaks for a supramodal and domain-general differences between CM and EM that goes beyond a differentiation based on the days of migraine per month. Together, the reviewed studies demonstrates that electro- and magneto-physiological brain activity (M/EEG), as well as neurovascular and metabolic recordings from functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), show characteristic patterns that allow to differentiate between CM and EM groups.
CONCLUSIONS
Although a clear brain activity-based biomarker has not yet been identified to distinguish these subtypes of migraine, research is approaching headache specialists to a migraine diagnosis based not only on symptoms and signs reported by patients. Future studies based on M/EEG should pay special attention to the brain activity in medium and fast frequency bands, mainly the beta band. On the other hand, fMRI and PET studies should focus on neural circuits and regions related to pain and emotional processing.
Topics: Biomarkers; Chronic Disease; Electroencephalography; Headache; Humans; Magnetic Resonance Imaging; Migraine Disorders; Positron-Emission Tomography
PubMed: 35927625
DOI: 10.1186/s10194-022-01465-1 -
Clinical Neurophysiology : Official... Sep 2022Bipolar disorder is characterized by aberrant neurophysiological responses as measured with electroencephalography (EEG) and magnetoencephalography (MEG), including the... (Meta-Analysis)
Meta-Analysis
OBJECTIVE
Bipolar disorder is characterized by aberrant neurophysiological responses as measured with electroencephalography (EEG) and magnetoencephalography (MEG), including the 40-Hz auditory steady-state response (ASSR). 40-Hz ASSR deficits are also found in patients with schizophrenia and may represent a transdiagnostic biomarker of neuronal circuit dysfunction. In this systematic review and meta-analysis, we summarize and evaluate the evidence for 40-Hz ASSR deficits in patients with bipolar disorder.
METHODS
We identified studies from PubMed, EMBASE, and SCOPUS. We assessed the risk of bias, calculated Hedges' g meta-level effect sizes, and investigated small-study effects using funnel plots and Egger regression.
RESULTS
Seven studies, comprising 396 patients with bipolar disorder and 404 healthy controls, were included in the meta-analysis. Studies displayed methodological heterogeneity and an overall high risk of bias. Patients with bipolar disorder showed consistent reductions in 40-Hz ASSR evoked power (Hedges' g = -0.49; 95% confidence intervals [-0.67, -0.31]) and inter-trial phase coherence (ITPC) (Hedges' g = -0.43; 95 %CI [-0.58, -0.29]) compared with healthy controls.
CONCLUSIONS
Our meta-analysis provides evidence that 40-Hz ASSRs are reduced in patients with bipolar disorder compared with healthy controls.
SIGNIFICANCE
Future large-scale studies are warranted to link 40-Hz ASSR deficits to clinical features and developmental trajectories.
Topics: Acoustic Stimulation; Bipolar Disorder; Electroencephalography; Evoked Potentials, Auditory; Humans; Magnetoencephalography; Schizophrenia
PubMed: 35853310
DOI: 10.1016/j.clinph.2022.06.014 -
Neuroscience and Biobehavioral Reviews Jul 2022Cross-frequency coupling (CFC), an electrophysiologically derived measure of oscillatory coupling in the brain, is believed to play a critical role in neuronal... (Review)
Review
Cross-frequency coupling (CFC), an electrophysiologically derived measure of oscillatory coupling in the brain, is believed to play a critical role in neuronal computation, learning and communication. It has received much recent attention in the study of both health and disease. We searched for literature that studied CFC during resting state and task-related activities during electroencephalography and magnetoencephalography in psychiatric disorders. Thirty-eight studies were identified, which included attention-deficit hyperactivity disorder, Alzheimer's dementia, autism spectrum disorder, bipolar disorder, depression, obsessive compulsive disorder, social anxiety disorder and schizophrenia. The systematic review was registered with PROSPERO (ID#CRD42021224188). The current review indicates measurable differences exist between CFC in disease states vs. healthy controls. There was variance in CFC at different regions of the brain within the same psychiatric disorders, perhaps this could be explained by the mechanisms and functionality of CFC. There was heterogeneity in methodologies used, which may lead to spurious CFC analyses. Going forward, standardized methodologies need to be established and utilized in further research to understand the neuropathophysiology associated with psychiatric disorders.
Topics: Autism Spectrum Disorder; Brain; Electroencephalography; Humans; Neurons; Obsessive-Compulsive Disorder
PubMed: 35569580
DOI: 10.1016/j.neubiorev.2022.104690 -
Data in Brief Dec 2021This article describes source data from a systematic review and meta-analysis of electroencephalography (EEG) and magnetoencephalography (MEG) studies investigating...
This article describes source data from a systematic review and meta-analysis of electroencephalography (EEG) and magnetoencephalography (MEG) studies investigating functional connectivity in idiopathic generalized epilepsy. Data selection, analysis and reporting was performed according to PRISMA guidelines. Eligible studies for review were identified from human case-control, and cohort studies. Twenty-two studies were included in the review. Extracted descriptive data included sample characteristics, acquisition of EEG or MEG recordings and network construction. Reported differences between IGE and control groups in functional connectivity or network metrics were extracted as the main outcome measure. Qualitative group differences in functional connectivity were synthesized through narrative review. Meta-analysis was performed for group-level, quantitative estimates of common network metrics clustering coefficient, path length, mean degree and nodal strength. Six studies were included in the meta-analysis. Risk of bias was assessed across all studies. Raw and synthesized data for included studies are reported, alongside effect size and heterogeneity statistics from meta-analyses. Network neurosciences is a rapidly expanding area of research, with significant potential for clinical applications in epilepsy. This data article provides novel, statistical estimates of brain network differences from patients with IGE relative to healthy controls, across the existing literature. Increasing data accessibility supports study replication and improves study comparability for future reviews, enabling a better understanding of network characteristics in IGE.
PubMed: 34934781
DOI: 10.1016/j.dib.2021.107665 -
Epilepsy & Behavior : E&B Oct 2021For idiopathic generalized epilepsies (IGE), brain network analysis is emerging as a biomarker for potential use in clinical care. To determine whether people with IGE... (Review)
Review
For idiopathic generalized epilepsies (IGE), brain network analysis is emerging as a biomarker for potential use in clinical care. To determine whether people with IGE show alterations in resting-state brain connectivity compared to healthy controls, and to quantify these differences, we conducted a systematic review and meta-analysis of EEG and magnetoencephalography (MEG) functional connectivity and network studies. The review was conducted according to PRISMA guidelines. Twenty-two studies were eligible for inclusion. Outcomes from individual studies supported hypotheses for interictal, resting-state brain connectivity alterations in IGE patients compared to healthy controls. In contrast, meta-analysis from six studies of common network metrics clustering coefficient, path length, mean degree and nodal strength showed no significant differences between IGE and control groups (effect sizes ranged from -0.151 -1.78). The null findings of the meta-analysis and the heterogeneity of the included studies highlights the importance of developing standardized, validated methodologies for future research. Network neuroscience has significant potential as both a diagnostic and prognostic biomarker in epilepsy, though individual variability in network dynamics needs to be better understood and accounted for.
PubMed: 34607215
DOI: 10.1016/j.yebeh.2021.108336 -
Alzheimer's Research & Therapy Sep 2021An increase in lifespan in our society is a double-edged sword that entails a growing number of patients with neurocognitive disorders, Alzheimer's disease being the...
BACKGROUND
An increase in lifespan in our society is a double-edged sword that entails a growing number of patients with neurocognitive disorders, Alzheimer's disease being the most prevalent. Advances in medical imaging and computational power enable new methods for the early detection of neurocognitive disorders with the goal of preventing or reducing cognitive decline. Computer-aided image analysis and early detection of changes in cognition is a promising approach for patients with mild cognitive impairment, sometimes a prodromal stage of Alzheimer's disease dementia.
METHODS
We conducted a systematic review following PRISMA guidelines of studies where machine learning was applied to neuroimaging data in order to predict whether patients with mild cognitive impairment might develop Alzheimer's disease dementia or remain stable. After removing duplicates, we screened 452 studies and selected 116 for qualitative analysis.
RESULTS
Most studies used magnetic resonance image (MRI) and positron emission tomography (PET) data but also magnetoencephalography. The datasets were mainly extracted from the Alzheimer's disease neuroimaging initiative (ADNI) database with some exceptions. Regarding the algorithms used, the most common was support vector machine with a mean accuracy of 75.4%, but convolutional neural networks achieved a higher mean accuracy of 78.5%. Studies combining MRI and PET achieved overall better classification accuracy than studies that only used one neuroimaging technique. In general, the more complex models such as those based on deep learning, combined with multimodal and multidimensional data (neuroimaging, clinical, cognitive, genetic, and behavioral) achieved the best performance.
CONCLUSIONS
Although the performance of the different methods still has room for improvement, the results are promising and this methodology has a great potential as a support tool for clinicians and healthcare professionals.
Topics: Alzheimer Disease; Brain; Cognitive Dysfunction; Disease Progression; Humans; Machine Learning; Magnetic Resonance Imaging; Neuroimaging
PubMed: 34583745
DOI: 10.1186/s13195-021-00900-w -
NeuroImage. Clinical 2021Magnetoencephalography (MEG), allows for a high degree temporal and spatial accuracy in recording cortical oscillatory activity and evoked fields. To date, no review has... (Review)
Review
INTRODUCTION
Magnetoencephalography (MEG), allows for a high degree temporal and spatial accuracy in recording cortical oscillatory activity and evoked fields. To date, no review has been undertaken to synthesise all MEG studies in Multiple Sclerosis (MS). We undertook a Systematic Review of the utility of MEG in MS.
METHODS
We identified MEG studies carried out in MS using EMBASE, Medline, Cochrane, TRIP and Psychinfo databases. We included original research articles with a cohort of minimum of five multiple sclerosis patients and quantifying of at least one MEG parameter. We used a modified version of the JBI (mJBI) for case-control studies to assess for risk of bias.
RESULTS
We identified 30 studies from 13 centres involving at least 433 MS patients and 347 controls. We found evidence that MEG shows perturbed activity (most commonly reduced power modulations), reduced connectivity and association with altered clinical function in Multiple Sclerosis. Specific replicated findings were decreased motor induced responses in the beta band, diminished increase of gamma power after visual stimulation, increased latency and reduced connectivity for somatosensory evoked fields. There was an association between upper alpha connectivity and cognitive measures in people with MS. Overall studies were of moderate quality (mean mJBI score 6.7).
DISCUSSION
We find evidence for the utility of MEG in Multiple Sclerosis. Event-related designs are of particular value and show replicability between centres. At this stage, it is not clear whether these changes are specific to Multiple Sclerosis or are also observable in other diseases. Further studies should look to explore cognitive control in more depth using in-task designs and undertake longitudinal studies to determine whether these changes have prognostic value.
Topics: Case-Control Studies; Cohort Studies; Humans; Magnetoencephalography; Multiple Sclerosis; Photic Stimulation
PubMed: 34537682
DOI: 10.1016/j.nicl.2021.102814