Association of the loudness dependence of auditory evoked potentials with clinical changes to repetitive transcranial magnetic stimulation in patients with depression

Efficacy of non-invasive brain stimulation and neuronavigation for major depressive disorder: a systematic review and meta-analysis

INTRODUCTION

Repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS) are increasingly used for major depressive disorder (MDD). Most tDCS and rTMS studies target the left dorsolateral prefrontal cortex, either with or without neuronavigation. We examined the effect of rTMS and tDCS, and the added value of neuronavigation in the treatment of MDD.

METHODS

A search on PubMed, Embase, and Cochrane databases for rTMS or tDCS randomized controlled trials of MDD up to 1 February 2023, yielded 89 studies. We then performed meta-analyses comparing tDCS efficacy to non-neuronavigated rTMS, tDCS to neuronavigated rTMS, and neuronavigated rTMS to non-neuronavigated rTMS. We assessed the significance of the effect in subgroups and in the whole meta-analysis with a z-test and subgroup differences with a chi-square test.

RESULTS

We found small-to-medium effects of both tDCS and rTMS on MDD, with a slightly greater effect from rTMS. No significant difference was found between neuronavigation and non-neuronavigation.

CONCLUSION

Although both tDCS and rTMS are effective in treating MDD, many patients do not respond. Additionally, current neuronavigation methods are not significantly improving MDD treatment. It is therefore imperative to seek personalized methods for these interventions.

Affective disorders and the loudness dependence of the auditory evoked potential: Serotonin and beyond

Identifying additional noninvasive biomarkers for affective disorders, such as unipolar major depressive disorder (MDD) and bipolar disorder (BD), could aid in the diagnosis and treatment of these prevalent and debilitating neuropsychiatric conditions. One such candidate biomarker is the loudness dependence of the auditory evoked potential (LDAEP), an event-related potential that measures responsiveness of the auditory cortex to different intensities of sound. The LDAEP has been associated with MDD and BD, including therapeutic response to particular classes of antidepressant drugs, while also correlating with several other neuropsychiatric disorders. It has been suggested that increased values of the LDAEP indicate low central serotonergic neurotransmission, further implicating this EEG measure in depression. Here, we briefly review the literature on the LDAEP in affective disorders, including its association with serotonergic signaling, as well as with that of other neurotransmitters such as dopamine. We summarize key findings on the LDAEP and the genetics of these neurotransmitters, as well as prediction of response to particular classes of antidepressants in MDD, including SSRIs versus noradrenergic agents. The possible relationship between this EEG measure and suicidality is addressed. We also briefly analyze acute pharmacologic studies of serotonin and/or dopamine precursor depletion and the LDAEP. In conclusion, the existing literature suggests that serotonin and norepinephrine may modulate the LDAEP in an opposing manner, and that this event-related marker may be of use in predicting response to chronic treatment with particular pharmacologic agents in the context of affective disorders, such as MDD and BD, including in the presence of suicidality.

Machine learning-based classification using electroencephalographic multi-paradigms between drug-naïve patients with depression and healthy controls

BACKGROUND

Electroencephalography (EEG) is a supplementary diagnostic tool in psychiatry but lacks practical usage. EEG has demonstrated inconsistent diagnostic ability because major depressive disorder (MDD) is a heterogeneous psychiatric disorder with complex pathologies. In clinical psychiatry, it is essential to detect these complexities using multiple EEG paradigms. Though the application of machine learning to EEG signals in psychiatry has increased, an improvement in its classification performance is still required clinically. We tested the classification performance of multiple EEG paradigms in drug-naïve patients with MDD and healthy controls (HCs).

METHODS

Thirty-one drug-naïve patients with MDD and 31 HCs were recruited in this study. Resting-state EEG (REEG), the loudness dependence of auditory evoked potentials (LDAEP), and P300 were recorded for all participants. Linear discriminant analysis (LDA) and support vector machine (SVM) classifiers with t-test-based feature selection were used to classify patients and HCs.

RESULTS

The highest accuracy was 94.52 % when 14 selected features, including 12 P300 amplitudes (P300A) and two LDAEP features, were layered. The accuracy was 90.32 % when a SVM classifier for 30 selected features (14 P300A, 14 LDAEP, and 2 REEG) was layered in comparison to each REEG, P300A, and LDAEP, the best accuracies of which were 71.57 % (2-layered with LDA), 87.12 % (1-layered with LDA), and 83.87 % (6-layered with SVM), respectively.

LIMITATIONS

The present study was limited by small sample size and difference in formal education year.

CONCLUSIONS

Multiple EEG paradigms are more beneficial than a single EEG paradigm for classifying drug-naïve patients with MDD and HCs.

Association between daily dose and efficacy of rTMS over the left dorsolateral prefrontal cortex in depression: A meta-analysis

Repetitive transcranial magnetic stimulation (rTMS) is a well-established, safe, and effective brain stimulation technique for depression; however, uniform parameters have not been used in clinical practice. The aim of this study was to identify the parameters that affect rTMS effectiveness and ascertain the range in which that parameter has optimal efficacy. A meta-analysis of sham-controlled trials using rTMS delivered over the left dorsolateral prefrontal cortex (DLPFC) in depression was conducted. In the meta-regression and subgroup analyses, all rTMS stimulation parameters were extracted and their association with efficacy was investigated. Of the 17,800 references, 52 sham-controlled trials were included. Compared to sham controls, our results demonstrated a significant improvement in depressive symptoms at the end of treatment. According to the results of meta-regression, the number of pulses and sessions per day correlated with rTMS efficacy; however, the positioning method, stimulation intensity, frequency, number of treatment days, and total pulses did not. Furthermore, subgroup analysis revealed that the efficacy was correspondingly better in the group with higher daily pulses. In clinical practice, increasing the number of daily pulses and sessions may improve the effectiveness of rTMS.

The Association Between Sample and Treatment Characteristics and the Efficacy of Repetitive Transcranial Magnetic Stimulation in Depression: A Meta-analysis and Meta-regression of Sham-controlled Trials

BACKGROUND

Repetitive transcranial magnetic stimulation (rTMS) is a form of non-invasive neuromodulation that is increasingly used to treat major depressive disorder (MDD). However, treatment with rTMS could be optimized by identifying optimal treatment parameters or characteristics of patients that are most likely to benefit. This meta-analysis and meta-regression aims to identify sample and treatment characteristics that are associated with change in depressive symptom level, treatment response and remission.

METHODS

The databases PubMed, Embase, Web of Science and Cochrane library were searched for randomized controlled trials (RCTs) reporting on the therapeutic efficacy of high-frequent, low-frequent, or bilateral rTMS for MDD compared to sham. Study and sample characteristics as well as rTMS parameters and outcome variables were extracted. Effect sizes were calculated for change in depression score and risk ratios for response and remission.

RESULTS

Sixty-five RCTs with a total of 2982 subjects were included in this meta-analysis. Active rTMS resulted in a larger depressive symptom reduction than sham protocol (Hedges' g = -0.791 95% CI -0.977; -0.605). Risk ratios for response and remission were 2.378 (95% CI 1.882; 3.005) and 2.450 (95% CI 1.779; 3.375), respectively. We found no significant association between sample and treatment parameters and rTMS efficacy.

CONCLUSIONS

rTMS is an efficacious treatment for MDD. No associations between sample or treatment characteristics and efficacy were found, for which we caution that publication bias, heterogeneity and lack of consistency in the definition of remission might bias these latter null findings. Our results are clinically relevant and support the use of rTMS as a non-invasive and effective treatment option for depression.

Association between the loudness dependence of auditory evoked potentials and age in patients with schizophrenia and depression

Objective

Although serotonergic dysfunction is significantly associated with major depressive disorder (MDD) and schizophrenia (SCZ), comparison of serotonergic dysfunction in both diseases has received little attention. Serotonin hypotheses have suggested diminished and elevated serotonin activity in MDD and SCZ, respectively. However, the foundations underlying these hypotheses are unclear regarding changes in serotonin neurotransmission in the aging brain. The loudness dependence of auditory evoked potentials (LDAEP) reflects serotonin neurotransmission. The present study compared the LDAEP between patients with SCZ or MDD and healthy controls (HCs). We further examined whether age was correlated with the LDAEP and clinical symptoms.

Methods

This prospective clinical study included 105 patients with SCZ (n = 54) or MDD (n = 51). Additionally, 35 HCs were recruited for this study. The LDAEP was measured on the midline channels via 62 electroencephalography channels.

Results

Patients with SCZ or MDD showed a significantly smaller mean LDAEP than those in HCs. The LDAEP was positively correlated with age in patients with SCZ or MDD.

Conclusions

Changes in central serotonergic activity could be indicated by evaluating the LDAEP in patients with SCZ or MDD. Age-related reductions in serotonergic activity may be screened using the LDAEP in patients with SCZ or MDD.

Does the Loudness Dependence of Auditory Evoked Potential Predict Response to Selective Serotonin Reuptake Inhibitors?: A Meta-analysis

Objective

Loudness of dependence of the auditory evoked potential (LDAEP) is an electroencephalogram-based measure that represents amplitude changes of auditory evoked potentials in primary auditory cortex. Several narrative reviews argued that pre-treatment LDAEP values predict responses to selective serotonin reuptake inhibitors (SSRIs). This study aims to quantify the overall relationship between baseline LDAEP values and treatment response to SSRIs in patients with depression and generalized anxiety disorders, evidenced by clinical symptoms reductions, across multiple studies.

Methods

In our meta-analysis, seven articles with a total sample of 241 patients were included.

Results

Our results showed that stronger baseline LDAEP values predicted favorable response to SSRIs for depression and anxiety, with a moderate effect size.

Conclusion

The current results support the idea that LDAEP is a promising biomarker for SSRIs treatment prediction in patients with depression and generalized anxiety disorder.

An Update on Repetitive Transcranial Magnetic Stimulation for the Treatment of Major Depressive Disorder

Repetitive transcranial magnetic stimulation (rTMS) has emerged as an evidenced-based treatment for major depression that does not respond to standard first-line therapies. The majority of data support the use of high-frequency (10 Hz) treatment delivered to the left dorsolateral prefrontal cortex. Intermittent theta burst stimulation is a new emerging treatment that reduces the time required to deliver treatment and can increase capacity and access to this treatment. This review will comprehensively cover recent advancements in the field of rTMS for depression, including stimulation parameters and targets aimed at enhancing outcomes. In addition, efforts to use modern neuroscience tools to personalize this treatment and optimize outcomes will be reviewed.