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.

Capsular bag distention syndrome after combined cataract-lens implant surgery and Ahmed valve implantation.

PURPOSE: To describe the capsular bag distention syndrome after combined cataract extraction with posterior lens implant and aqueous drainage device. METHODS: Case report. RESULTS: A persistently shallow anterior chamber and low intraocular pressure developed after combined cataract extraction with posterior chamber lens implant and Ahmed aqueous drainage device. An optically empty space between the lens implant and posterior capsule was detected 18 days after surgery. The anterior chamber deepened within minutes after Nd:YAG posterior capsulotomy. CONCLUSION: The capsular bag distention syndrome needs to be included in the differential diagnosis of shallow anterior chamber with low intraocular pressure after combined cataract extraction and glaucoma valve implant surgery.

Corneal topography in cataract surgery.

Keratometry and videokeratography are the most important means of evaluating induced corneal changes after surgery and have comparable sensitivities in the paracentral region of the cornea. When cataract surgery is planned, corneal topography can be used preoperatively in the calculation of IOL power, particularly in difficult cases, such as in patients who have undergone corneal refractive surgery or penetrating keratoplasty. A study published in the past year suggests that the mean power in ring 3 of the Tomey TMS-1 videokeratoscope (Cambridge, MA) appears to give the most accurate estimate of corneal power for the calculation of IOL power after radial keratotomy. In the case of PRK, traditional methods of determining the corneal power can lead to great amounts of anisometropia. Further research is needed to develop more accurate methods of calculating IOL power after PRK. Videokeratography can also be used before cataract surgery in planning the location and size of the incision. In general, smaller temporal incisions result in less astigmatism than do larger superior incisions. Postoperatively, videokeratography can be used to detect tight sutures, torsion of the wound, internal wound gape, and irregular astigmatism, as well as to guide suture removal or in cases where best-corrected visual acuity is not adequate and there are no other obvious causes for poor vision to determine if corneal irregularities are present.