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Archives of Clinical Neuropsychology :... Oct 2021Cognitive reserve (CR) is the capacity to adapt to (future) brain damage without any or only minimal clinical symptoms. The underlying neuroplastic mechanisms remain...
OBJECTIVE
Cognitive reserve (CR) is the capacity to adapt to (future) brain damage without any or only minimal clinical symptoms. The underlying neuroplastic mechanisms remain unclear. Electrocorticography (ECOG), electroencephalography (EEG), and magnetoencephalography (MEG) may help elucidate the brain mechanisms underlying CR, as CR is thought to be related to efficient utilization of remaining brain resources. The purpose of this systematic review is to collect, evaluate, and synthesize the findings on neural correlates of CR estimates using ECOG, EEG, and MEG.
METHOD
We examined articles that were published from the first standardized definition of CR. Eleven EEG and five MEG cross-sectional studies met the inclusion criteria: They concerned original research, analyzed (M)EEG in humans, used a validated CR estimate, and related (M)EEG to CR. Quality assessment was conducted using an adapted form of the Newcastle-Ottawa scale. No ECOG study met the inclusion criteria.
RESULTS
A total of 1383 participants from heterogeneous patient, young and older healthy groups were divided into three categories by (M)EEG methodology: Eight (M)EEG studies employed event-related fields or potentials, six studies analyzed brain oscillations at rest (of which one also analyzed a cognitive task), and three studies analyzed brain connectivity. Various CR estimates were employed and all studies compared different (M)EEG measures and CR estimates. Several associations between (M)EEG measures and CR estimates were observed.
CONCLUSION
Our findings support that (M)EEG measures are related to CR estimates, particularly in healthy individuals. However, the character of this relationship is dependent on the population and task studied, warranting further studies.
Topics: Brain; Brain Mapping; Cognitive Reserve; Cross-Sectional Studies; Electroencephalography; Humans; Magnetoencephalography; Neuropsychological Tests
PubMed: 33522563
DOI: 10.1093/arclin/acaa132 -
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 -
Progress in Neuro-psychopharmacology &... Apr 2023There are growing application of machine learning models to study the intricacies of non-linear and non-stationary characteristics of electroencephalography (EEG) and... (Review)
Review
There are growing application of machine learning models to study the intricacies of non-linear and non-stationary characteristics of electroencephalography (EEG) and magnetoencephalography (MEG) data in neurobiologically complex and heterogeneous conditions such as autism spectrum disorder (ASD). Such tools have potential diagnostic applications, and given the highly heterogeneous presentation of ASD, might prove fruitful in early detection and therefore could facilitate very early intervention. We conducted a systematic review (PROSPERO ID#CRD42021257438) by searching PubMed, EMBASE, and PsychINFO for machine learning approaches for EEG and MEG analyses in ASD. Thirty-nine studies were identified, of which the majority (18) used support vector machines for classification; other successful methods included deep learning. Thirty-seven studies were found to employ EEG and two were found to employ MEG. This systematic review indicate that machine learning methods can be used to classify ASD, predict ASD diagnosis in high-risk infants as early as 3 months of age, predict ASD symptom severity, and classify states of cognition in ASD with high accuracy. Replication studies testing validity, reproducibility and generalizability in tandem with randomized controlled trials in ASD populations will likely benefit the field.
Topics: Infant; Humans; Magnetoencephalography; Autism Spectrum Disorder; Reproducibility of Results; Electroencephalography; Machine Learning
PubMed: 36574922
DOI: 10.1016/j.pnpbp.2022.110705 -
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 -
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 -
Brain Topography Mar 2023Background Magnetoencephalography (MEG) and electroencephalography (EEG) record two main types of data: continuous measurements at rest or during sleep, and... (Review)
Review
Background Magnetoencephalography (MEG) and electroencephalography (EEG) record two main types of data: continuous measurements at rest or during sleep, and event-related potentials/evoked magnetic fields (ERPs/EMFs) that involve specific and repetitive tasks. In this systematic review, we summarized longitudinal studies on recovery from post-stroke aphasia that used continuous or event-related temporal imaging (EEG or MEG). Methods We searched PubMed and Scopus for English articles published from 1950 to May 31, 2022. Results 34 studies were included in this review: 11 were non-interventional studies and 23 were clinical trials that used specific rehabilitation methods, neuromodulation, or drugs. The results of the non-interventional studies suggested that poor language recovery was associated with slow-wave activity persisting over time. The results of some clinical trials indicated that behavioral improvements were correlated with significant modulation of the N400 component. Discussion Compared with continuous EEG, ERP/EMF may more reliably identify biomarkers of therapy-induced effects. Electrophysiology should be used more often to explore language processes that are impaired after a stroke, as it may highlight treatment challenges for patients with post-stroke aphasia.
Topics: Humans; Male; Female; Electroencephalography; Evoked Potentials; Aphasia; Stroke; Magnetoencephalography
PubMed: 36749552
DOI: 10.1007/s10548-023-00941-4 -
Biological Psychiatry May 2023Predictive models in neuroimaging are increasingly designed with the intent to improve risk stratification and support interventional efforts in psychiatry. Many of... (Review)
Review
Predictive models in neuroimaging are increasingly designed with the intent to improve risk stratification and support interventional efforts in psychiatry. Many of these models have been developed in samples of children school-aged or older. Nevertheless, despite growing evidence that altered brain maturation during the fetal, infant, and toddler (FIT) period modulates risk for poor mental health outcomes in childhood, these models are rarely implemented in FIT samples. Applications of predictive modeling in children of these ages provide an opportunity to develop powerful tools for improved characterization of the neural mechanisms underlying development. To facilitate the broader use of predictive models in FIT neuroimaging, we present a brief primer and systematic review on the methods used in current predictive modeling FIT studies. Reflecting on current practices in more than 100 studies conducted over the past decade, we provide an overview of topics, modalities, and methods commonly used in the field and under-researched areas. We then outline ethical and future considerations for neuroimaging researchers interested in predicting health outcomes in early life, including researchers who may be relatively new to either advanced machine learning methods or using FIT data. Altogether, the last decade of FIT research in machine learning has provided a foundation for accelerating the prediction of early-life trajectories across the full spectrum of illness and health.
Topics: Child; Child, Preschool; Humans; Infant; Machine Learning; Neuroimaging
PubMed: 36759257
DOI: 10.1016/j.biopsych.2022.10.014 -
Journal of Affective Disorders Jun 2024Electrophysiologic measures provide an opportunity to inform mechanistic models and possibly biomarker prediction of response. Serotonergic psychedelics (SPs) (i.e.,... (Review)
Review
Spectral signatures of psilocybin, lysergic acid diethylamide (LSD) and ketamine in healthy volunteers and persons with major depressive disorder and treatment-resistant depression: A systematic review.
BACKGROUND
Electrophysiologic measures provide an opportunity to inform mechanistic models and possibly biomarker prediction of response. Serotonergic psychedelics (SPs) (i.e., psilocybin, lysergic acid diethylamide (LSD)) and ketamine represent new investigational and established treatments in mood disorders respectively. There is a need to better characterize the mechanism of action of these agents.
METHODS
We conducted a systematic review investigating the spectral signatures of psilocybin, LSD, and ketamine in persons with major depressive disorder (MDD), treatment-resistant depression (TRD), and healthy controls.
RESULTS
Ketamine and SPs are associated with increased theta power in persons with depression. Ketamine and SPs are also associated with decreased spectral power in the alpha, beta and delta bands in healthy controls and persons with depression. When administered with SPs, theta power was increased in persons with MDD when administered with SPs. Ketamine is associated with increased gamma band power in both healthy controls and persons with MDD.
LIMITATIONS
The studies included in our review were heterogeneous in their patient population, exposure, dosing of treatment and devices used to evaluate EEG and MEG signatures. Our results were extracted entirely from persons who were either healthy volunteers or persons with MDD or TRD.
CONCLUSIONS
Extant literature evaluating EEG and MEG spectral signatures indicate that ketamine and SPs have reproducible effects in keeping with disease models of network connectivity. Future research vistas should evaluate whether observed spectral signatures can guide further discovery of therapeutics within the psychedelic and dissociative classes of agents, and its prediction capability in persons treated for depression.
Topics: Humans; Psilocybin; Ketamine; Lysergic Acid Diethylamide; Depressive Disorder, Major; Depression; Healthy Volunteers; Hallucinogens
PubMed: 38570038
DOI: 10.1016/j.jad.2024.03.165 -
Journal of the Academy of... 2022Traumatic brain injury (TBI) can precipitate new-onset psychiatric symptoms or worsen existing psychiatric conditions. To elucidate specific mechanisms for this... (Review)
Review
BACKGROUND
Traumatic brain injury (TBI) can precipitate new-onset psychiatric symptoms or worsen existing psychiatric conditions. To elucidate specific mechanisms for this interaction, neuroimaging is often used to study both psychiatric conditions and TBI. This systematic review aims to synthesize the existing literature of neuroimaging findings among patients with anxiety after TBI.
METHODS
We conducted a Preferred Reporting Items for Systematic Review and Meta-Analyses-compliant literature search via PubMed (MEDLINE), PsychINFO, EMBASE, and Scopus databases before May, 2019. We included studies that clearly defined TBI, measured syndromal anxiety as a primary outcome, and statistically analyzed the relationship between neuroimaging findings and anxiety symptoms.
RESULTS
A total of 5982 articles were retrieved from the systematic search, of which 65 studied anxiety and 13 met eligibility criteria. These studies were published between 2004 and 2017, collectively analyzing 764 participants comprised of 470 patients with TBI and 294 non-TBI controls. Imaging modalities used included magnetic resonance imaging, functional magnetic resonance imaging, diffusion tensor imaging, electroencephalogram, magnetic resonance spectrometry, and magnetoencephalography. Eight of 13 studies presented at least one significant finding and together reflect a complex set of changes that lead to anxiety in the setting of TBI. The left cingulate gyrus in particular was found to be significant in 2 studies using different imaging modalities. Two studies also revealed perturbances in functional connectivity within the default mode network.
CONCLUSIONS
This is the first systemic review of neuroimaging changes associated with anxiety after TBI, which implicated multiple brain structures and circuits, such as the default mode network. Future research with consistent, rigorous measurements of TBI and syndromal anxiety, as well as attention to control groups, previous TBIs, and time interval between TBI and neuroimaging, are warranted. By understanding neuroimaging correlates of psychiatric symptoms, this work could inform future post-TBI screening and surveillance, preventative efforts, and early interventions to improve neuropsychiatric outcomes.
Topics: Anxiety; Brain Injuries, Traumatic; Diffusion Tensor Imaging; Humans; Magnetic Resonance Imaging; Neuroimaging
PubMed: 34534701
DOI: 10.1016/j.jaclp.2021.09.001 -
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