Effects of transcranial direct current stimulation and transcranial random noise stimulation on working memory and task-related EEG in major depressive disorder.

OBJECTIVE: To compare effects of transcranial direct current stimulation (tDCS) and transcranial random noise stimulation with a direct-current offset (tRNS + DC-offset) on working memory (WM) performance and task-related electroencephalography (EEG) in individuals with Major Depressive Disorder (MDD). METHODS: Using a sham-controlled, parallel-groups design, 49 participants with MDD received either anodal tDCS (N = 16), high-frequency tRNS + DC-offset (N = 16), or sham stimulation (N = 17) to the left dorsolateral prefrontal cortex (DLPFC) for 20-minutes. The Sternberg WM task was completed with concurrent EEG recording before and at 5- and 25-minutes post-stimulation. Event-related synchronisation/desynchronisation (ERS/ERD) was calculated for theta, upper alpha, and gamma oscillations during WM encoding and maintenance. RESULTS: tDCS significantly increased parieto-occipital upper alpha ERS/ERD during WM maintenance, observed on EEG recorded 5- and 25-minutes post-stimulation. tRNS + DC-offset did not significantly alter WM-related oscillatory activity when compared to sham stimulation. Neither tDCS nor tRNS + DC-offset improved WM performance to a significantly greater degree than sham stimulation. CONCLUSIONS: Although tDCS induced persistent effects on WM-related oscillatory activity, neither tDCS nor tRNS + DC-offset enhanced WM performance in MDD. SIGNIFICANCE: This reflects the first sham-controlled comparison of tDCS and tRNS + DC-offset in MDD. These findings directly contrast with evidence of tRNS-induced enhancements in WM in healthy individuals.

Introducing RELAX: An automated pre-processing pipeline for cleaning EEG data - Part 1: Algorithm and application to oscillations.

OBJECTIVE: Electroencephalographic (EEG) data are often contaminated with non-neural artifacts which can confound experimental results. Current artifact cleaning approaches often require costly manual input. Our aim was to provide a fully automated EEG cleaning pipeline that addresses all artifact types and improves measurement of EEG outcomes METHODS: We developed RELAX (the Reduction of Electroencephalographic Artifacts). RELAX cleans continuous data using Multi-channel Wiener filtering [MWF] and/or wavelet enhanced independent component analysis [wICA] applied to artifacts identified by ICLabel [wICA_ICLabel]). Several versions of RELAX were compared using three datasets (N = 213, 60 and 23 respectively) against six commonly used pipelines across a range of artifact cleaning metrics, including measures of remaining blink and muscle activity, and the variance explained by experimental manipulations after cleaning. RESULTS: RELAX with MWF and wICA_ICLabel showed amongst the best performance at cleaning blink and muscle artifacts while preserving neural signal. RELAX with wICA_ICLabel only may perform better at differentiating alpha oscillations between working memory conditions. CONCLUSIONS: RELAX provides automated, objective and high-performing EEG cleaning, is easy to use, and freely available on GitHub. SIGNIFICANCE: We recommend RELAX for data cleaning across EEG studies to reduce artifact confounds, improve outcome measurement and improve inter-study consistency.

RELAX part 2: A fully automated EEG data cleaning algorithm that is applicable to Event-Related-Potentials.

OBJECTIVE: Electroencephalography (EEG) is often used to examine neural activity time-locked to stimuli presentation, referred to as Event-Related Potentials (ERP). However, EEG is influenced by non-neural artifacts, which can confound ERP comparisons. Artifact cleaning reduces artifacts, but often requires time-consuming manual decisions. Most automated methods filter frequencies <1 Hz out of the data, so are not recommended for ERPs (which contain frequencies <1 Hz). Our aim was to test the RELAX (Reduction of Electroencephalographic Artifacts) pre-processing pipeline for use on ERP data. METHODS: The cleaning performance of multiple versions of RELAX were compared to four commonly used EEG cleaning pipelines across both artifact cleaning metrics and the amount of variance in ERPs explained by different conditions in a Go-Nogo task. Results RELAX with Multi-channel Wiener Filtering (MWF) and wavelet-enhanced independent component analysis applied to artifacts identified with ICLabel (wICA_ICLabel) cleaned data most effectively and produced amongst the most dependable ERP estimates. RELAX with wICA_ICLabel only or MWF_only may detect effects better for some ERPs. CONCLUSIONS: RELAX shows high artifact cleaning performance even when data is high-pass filtered at 0.25 Hz (applicable to ERP analyses). SIGNIFICANCE: RELAX is easy to implement via EEGLAB in MATLAB and freely available on GitHub. Given its performance and objectivity we recommend RELAX to improve artifact cleaning and consistency across ERP research.

Transcranial random noise stimulation is more effective than transcranial direct current stimulation for enhancing working memory in healthy individuals: Behavioural and electrophysiological evidence.

BACKGROUND: Transcranial direct current stimulation (tDCS) has been shown to improve working memory (WM) performance in healthy individuals, however effects tend to be modest and variable. Transcranial random noise stimulation (tRNS) can be delivered with a direct-current offset (DC-offset) to induce equal or even greater effects on cortical excitability than tDCS. To-date, no research has directly compared the effects of these techniques on WM performance or underlying neurophysiological activity. OBJECTIVE: To compare the effects of anodal tDCS, tRNS + DC-offset, or sham stimulation over the left dorsolateral prefrontal cortex (DLPFC) on WM performance and task-related EEG oscillatory activity in healthy adults. METHODS: Using a between-subjects design, 49 participants were allocated to receive either anodal tDCS (N = 16), high-frequency tRNS + DC-offset (N = 16), or sham stimulation (N = 17) to the left DLPFC. Changes in WM performance were assessed using the Sternberg WM task completed before and 5- and 25-min post-stimulation. Event-related synchronisation/desynchronisation (ERS/ERD) of oscillatory activity was analysed from EEG recorded during WM encoding and maintenance. RESULTS: tRNS induced more pronounced and consistent enhancements in WM accuracy when compared to both tDCS and sham stimulation. Improvements in WM performance following tRNS were accompanied by increased theta ERS and diminished gamma ERD during WM encoding, which were significantly greater than those observed following anodal tDCS or sham stimulation. CONCLUSIONS: These findings demonstrate the potential of tRNS + DC-offset to modulate cognitive and electrophysiological measures of WM and raise the possibility that tRNS + DC-offset may be more effective and reliable than tDCS for enhancing WM performance in healthy individuals.

Individuals with depression display abnormal modulation of neural oscillatory activity during working memory encoding and maintenance.

PURPOSE: To investigate neural oscillatory activity supporting working memory (WM) processing in depressed individuals and healthy controls. METHODS: Forty-six participants with Major Depressive Disorder (MDD) and 41 healthy controls balanced on age, gender, and WM ability completed a Sternberg verbal WM task with concurrent electroencephalography recording. Oscillatory activity was calculated for upper alpha, theta, and gamma frequency bands during WM encoding and maintenance. RESULTS: WM performance did not differ between groups. When compared to healthy controls, depressed individuals displayed reduced frontal-midline theta power and increased occipital upper alpha power during WM encoding, and reductions in frontal-midline theta power and occipital gamma and upper alpha power during WM maintenance. Higher depression severity was associated with greater reductions upper alpha and gamma power during WM maintenance. CONCLUSIONS: Depressed individuals displayed prominent alterations in oscillatory activity during WM encoding and maintenance, indicating that the neural processes which support WM processing are altered in MDD even when no cognitive impairments are observed.