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![Partial regression analysis – baseline exponent and treatment outcome
Partial regression of combined ECT and MST datasets showing a positive trending relationship between patients’ aperiodic exponent at baseline and clinical outcome, as measured by normalized HAM-D (β = 0.30, p = 0.091, 95% CI[−0.05, 0.657]). Here, patients whose baseline aperiodic exponent is lower, visible in a flatter pre-treatment power spectrum, show lower post-treatment symptom severity.](publication/375691138/figure/fig5/AS:11431281205216396@1700154010758/Partial-regression-analysis-baseline-exponent-and-treatment-outcome-Partial-regression.png)
Partial regression analysis – baseline exponent and treatment outcome Partial regression of combined ECT and MST datasets showing a positive trending relationship between patients’ aperiodic exponent at baseline and clinical outcome, as measured by normalized HAM-D (β = 0.30, p = 0.091, 95% CI[−0.05, 0.657]). Here, patients whose baseline aperiodic exponent is lower, visible in a flatter pre-treatment power spectrum, show lower post-treatment symptom severity.
Source publication
Major depressive disorder (MDD) is a leading cause of disability worldwide. One of the most efficacious treatments for treatment-resistant MDD is electroconvulsive therapy (ECT). Recently, magnetic seizure therapy (MST) was developed as an alternative to ECT due to its more favorable side effect profile. While these approaches have been very succes...
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Background
Non-invasive brain stimulation (NIBS) is a promising intervention for treatment-resistant schizophrenia. However, there are multiple available techniques and a comprehensive synthesis of evidence is lacking. Thus, we will conduct a systematic review and network meta-analysis to investigate the comparative efficacy and safety of NIBS tech...
Background and Objectives: Options for treatment-resistant bipolar depression (TRBPD) are limited. Electroconvulsive therapy (ECT) has shown efficacy in TRBPD. However, the cognitive deficits and memory concerns associated with ECT are problematic for a significant number of patients. It remains unclear what the next step is for patients with TRBPD...
Citations
... The emerging evidence from neuroimaging studies also suggests that the therapeutic effects of MST are possibly due to changes produced by MST in regional cerebral blood flow, neurotransmitter levels, and functional neural connectivity patterns [14][15][16]. Functional neuroimaging imaging-based studies have revealed changes in regional brain activity and connectivity patterns following MST, with alterations observed in areas implicated in emotion regulation, reward processing, and cognitive control. MST has been shown to enhance connectivity within the default mode network and favorably modulate activity in the anterior cingulate cortex and dorsolateral prefrontal cortex, and other regions thought to play a critical role in mood regulation and executive functioning. ...
Purpose of Review
This review aims to discuss historical aspects, mechanism of action, safety and efficacy, response predictors, and Magnetic Seizure Therapy (MST) protocol for treating depression. We also discuss the possibility of MST for personalized depression treatment and future directions.
Recent Findings
MST likely has a similar mechanism to the current gold standard neuromodulation treatment of Electroconvulsive Therapy (ECT) but differs in inducing seizures with a more controlled focus and pattern of cortical spread through the application of time-varying magnetic stimulation. The response and remission rates in depression with MST are comparable to ECT, but the cognitive adverse effects are likely to be more favorable with MST.
Summary
Depression is a common mental illness with significant burden globally, and about one-third of patients do not respond to treatment with multiple anti-depressant medications. Neuromodulation is one of the important treatment strategies for the management of depression, and among them MST is emerging as a promising treatment modality for depression. However, further evidence is needed to establish MST as a routine intervention in the clinical setting.
While visual working memory (WM) is strongly associated with reductions in occipitoparietal 8-12 Hz alpha power, the role of 4-7 Hz frontal midline theta power is less clear, with both increases and decreases widely reported. Here, we test the hypothesis that this theta paradox can be explained by non-oscillatory, aperiodic neural activity dynamics. Because traditional time-frequency analyses of electroencephalopgraphy (EEG) data conflate oscillations and aperiodic activity, event-related changes in aperiodic activity can manifest as task-related changes in apparent oscillations, even when none are present. Reanalyzing EEG data from two visual WM experiments (n = 74), and leveraging spectral parameterization, we found systematic changes in aperiodic activity with WM load, and we replicated classic alpha, but not theta, oscillatory effects after controlling for aperiodic changes. Aperiodic activity decreased during WM retention, and further flattened over the occipitoparietal cortex with an increase in WM load. After controlling for these dynamics, aperiodic-adjusted alpha power decreased with increasing WM load. In contrast, aperiodic-adjusted theta power increased during WM retention, but because aperiodic activity reduces more, it falsely appears as though theta “oscillatory” power (e.g., bandpower) is reduced. Furthermore, only a minority of participants (31/74) had a detectable degree of theta oscillations. These results offer a potential resolution to the theta paradox where studies show contrasting power changes. We identify novel aperiodic dynamics during human visual WM that mask the potential role that neural oscillations play in cognition and behavior.
Significance statement
Working Memory (WM) is our ability to hold information in mind without it being present in our external environment. Years of research focused on oscillatory brain dynamics to discover the mechanisms of WM. Here, we specifically look at oscillatory and non-oscillatory, aperiodic activity as measured with scalp EEG to test their significance in supporting WM. We challenge earlier findings regarding theta oscillations with our analysis approach, while replicating alpha oscillation findings. Furthermore, aperiodic activity is found to be involved in WM, over frontal regions in a task-general manner, and over anterior regions this activity is reduced with an increase the number of items that are remembered. Thus, we have identified novel aperiodic dynamics during human visual WM.
Electroconvulsive therapy (ECT) is a fast-acting, highly effective, and safe treatment for medication-resistant depression. Historically, the clinical benefits of ECT have been attributed to generating a controlled seizure; however, the underlying neurobiology is understudied and remains largely unresolved. Using optical neuroimaging to probe neural activity and hemodynamics in a mouse model of ECT, we demonstrated that a second brain event follows seizure: cortical spreading depolarization (CSD). We further found that ECT stimulation pulse parameters and electrode configuration directly shaped the wave dynamics of seizure and subsequent CSD. To translate these findings to human patients, we tested for the presence of hemodynamic signatures of post-ictal CSD using non-invasive diffuse optical monitoring of cerebral blood flow and oxygenation during routine ECT treatments. We found evidence that humans generate hyperemic waves after ECT seizure which are highly consistent with CSD. These results challenge a long-held assumption that seizure is the primary outcome of ECT and point to new opportunities for optimizing ECT stimulation parameters to precisely modulate brain activity and treatment outcomes.
In the study of neuro-electrophysiological recordings, aperiodic neural activity – activity with no characteristic frequency – has increasingly become a common feature of study. This interest has rapidly extended to clinical work, with many reports investigating aperiodic activity from patients from a broad range of clinical disorders. This work typically seeks to evaluate aperiodic activity as a putative biomarker relating to diagnosis or treatment response, and/or as a potential marker of underlying physiological activity. There is thus far no clear consensus on if and how aperiodic neural activity relates to clinical disorders, nor on the best practices for how to study it in clinical research. To address this, this systematic literature review, following PRISMA guidelines, examines reports of aperiodic activity in electrophysiological recordings with human patients with psychiatric and/or neurological disorders, finding 143 reports across 35 distinct disorders. Reports within and across disorders are summarized to evaluate current findings and examine what can be learned as pertains to the analysis, interpretations, and overall utility of aperiodic neural activity in clinical investigations. Aperiodic activity is commonly reported to relate to clinical diagnoses, with 31 of 35 disorders reporting a significant effect in diagnostic and/or treatment related studies. However, there is variation in the consistency of results across disorders, with the heterogeneity of patient groups, disease etiologies, and treatment status arising as common themes across different disorders. Overall, the current variability of results, potentially confounding covariates, and limitations in current understanding of aperiodic activity suggests further work is needed before aperiodic activity can be established as a potential biomarker and/or marker of underlying pathological physiology. Finally, a series of recommendations are proposed, based on the findings, limitations, and key discussion topics of the current literature to assist with guiding productive future work on the clinical utility of studying aperiodic neural activity.
Project Repository
The project repository contains code & data related to this project: https://github.com/TomDonoghue/AperiodicClinical
Cognitive symptoms in Parkinson’s disease are common and can significantly affect patients’ quality of life. Therefore, there is an urgent clinical need to identify a signature derived from behavioral and/or neuroimaging indicators that could predict which patients are at increased risk for early and rapid cognitive decline. Recently, converging evidence identified that aperiodic activity of the EEG reflects meaningful physiological information associated with age, development, cognitive and perceptual states or pathologies. In this study, we aimed to investigate aperiodic activity in Parkinson’s disease during cognitive control and characterize its possible association with behavior.
Here, we recorded high-density EEG in 30 healthy controls and 30 Parkinson’s disease patients during a Simon task. We analyzed task-related behavioral data in the context of the activation-suppression model and extracted aperiodic parameters (offset, exponent) at both scalp and source levels.
Our results showed lower behavioral performances in cognitive control as well as higher offsets in patients in the parieto-occipital areas, suggesting increased excitability in Parkinson’s disease. A small congruence effect on aperiodic parameters in pre- and post-central brain areas was also found, possibly associated with task execution. Significant differences in aperiodic parameters between the resting state, pre- and post-stimulus phases were seen across the whole brain, which confirmed that the observed changes in aperiodic activity are linked to task execution. No correlation was found between aperiodic activity and behavior or clinical features.
Our findings provide evidence that EEG aperiodic activity in Parkinson’s disease is characterized by greater offsets, and that aperiodic parameters differ depending on arousal state. However, our results do not support the hypothesis that the behavior-related differences observed in Parkinson’s disease are related to aperiodic changes. Overall, this study highlights the importance of considering aperiodic activity contributions in brain disorders and further investigating the relationship between aperiodic activity and behavior.
Introduction
Both ketamine (KET) and medial prefrontal cortex (mPFC) deep brain stimulation (DBS) are emerging therapies for treatment-resistant depression, yet our understanding of their electrophysiological mechanisms and biomarkers is incomplete. This study investigates aperiodic and periodic spectral parameters, and the signal complexity measure sample entropy, within mPFC local field potentials (LFP) in a chronic corticosterone (CORT) depression model after ketamine and/or mPFC DBS.
Methods
Male rats were intraperitoneally administered CORT or vehicle for 21 days. Over the last 7 days, animals receiving CORT were treated with mPFC DBS, KET, both, or neither; then tested across an array of behavioral tasks for 9 days.
Results
We found that the depression-like behavioral and weight effects of CORT correlated with a decrease in aperiodic-adjusted theta power (5–10 Hz) and an increase in sample entropy during the administration phase, and an increase in theta peak frequency and a decrease in the aperiodic exponent once the depression-like phenotype had been induced. The remission-like behavioral effects of ketamine alone correlated with a post-treatment increase in the offset and exponent, and decrease in sample entropy, both immediately and up to eight days post-treatment. The remission-like behavioral effects of mPFC DBS alone correlated with an immediate decrease in sample entropy, an immediate and sustained increase in low gamma (20–50 Hz) peak width and aperiodic offset, and sustained improvements in cognitive function. Failure to fully induce remission-like behavior in the combinatorial treatment group correlated with a failure to suppress an increase in sample entropy immediately after treatment.
Conclusion
Our findings therefore support the potential of periodic theta parameters as biomarkers of depression-severity; and periodic low gamma parameters and cognitive measures as biomarkers of mPFC DBS treatment efficacy. They also support sample entropy and the aperiodic spectral parameters as potential cross-modal biomarkers of depression severity and the therapeutic efficacy of mPFC DBS and/or ketamine. Study of these biomarkers is important as objective measures of disease severity and predictive measures of therapeutic efficacy can be used to personalize care and promote the translatability of research across studies, modalities, and species.
