Quantitative and objective diagnosis of color vision deficiencies based on steady-state visual evoked potentials

A novel non-invasive EEG-SSVEP diagnostic tool for color vision deficiency in individuals with locked-in syndrome

Introduction

Color vision deficiency (CVD), a common visual impairment, affects individuals' ability to differentiate between various colors due to malfunctioning or absent color photoreceptors in the retina. Currently available diagnostic tests require a behavioral response, rendering them unsuitable for individuals with limited physical and communication abilities, such as those with locked-in syndrome. This study introduces a novel, non-invasive method that employs brain signals, specifically Steady-State Visually Evoked Potentials (SSVEPs), along with Ishihara plates to diagnose CVD. This method aims to provide an alternative diagnostic tool that addresses the limitations of current tests.

Methods

Electroencephalography (EEG) recordings were obtained from 16 subjects, including 5 with CVD (specifically Deuteranomaly), using channels O1, O2, Pz, and Cz. The subjects were exposed to visual stimuli at frequencies of 15 Hz and 18 Hz to assess the proposed method. The subjects focused on specific visual stimuli in response to questions related to the Ishihara plates. Their responses were analyzed to determine the presence of CVD. Feature extraction was performed using Power Spectral Density (PSD), Canonical Correlation Analysis (CCA), and a combined PSD + CCA, followed by classification to categorize subjects into two classes: normal vision and CVD.

Results

The results indicate that the proposed method effectively diagnoses CVD in individuals with limited communication abilities. The classification accuracy of SSVEP exceeded 75% across the three classifiers: Decision Tree (DT), K-Nearest Neighbors (KNN), and Support Vector Machine (SVM). The SVM classifier demonstrated higher accuracy compared to the other classifiers, exceeding 90%.

Discussion

These observations suggest that the SVM classifier, utilizing the combined feature set of PSD + CCA, may be the most effective in this classification task. These findings demonstrate that the proposed method is an accurate and reliable diagnostic tool for CVD, particularly for individuals unable to communicate.

Chromatic visual evoked potentials: A review of physiology, methods and clinical applications

Objective assessment of the visual system can be performed electrophysiologically using the visual evoked potential (VEP). In many clinical circumstances, this is performed using high contrast achromatic patterns or diffuse flash stimuli. These methods are clinically valuable but they may only assess a subset of possible physiological circuitries within the visual system, particularly those involved in achromatic (luminance) processing. The use of chromatic VEPs (cVEPs) in addition to standard VEPs can inform us of the function or dysfunction of chromatic pathways. The chromatic VEP has been well studied in human health and disease. Yet, to date our knowledge of their underlying mechanisms and applications remains limited. This likely reflects a heterogeneity in the methodology, analysis and conclusions of different works, which leads to ambiguity in their clinical use. This review sought to identify the primary methodologies employed for recording cVEPs. Furthermore cVEP maturation and application in understanding the function of the chromatic system under healthy and diseased conditions are reviewed. We first briefly describe the physiology of normal colour vision, before describing the methodologies and historical developments which have led to our understanding of cVEPs. We thereafter describe the expected maturation of the cVEP, followed by reviewing their application in several disorders: congenital colour vision deficiencies, retinal disease, glaucoma, optic nerve and neurological disorders, diabetes, amblyopia and dyslexia. We finalise the review with recommendations for testing and future directions.

Visual evoked potentials in patients with congenital color vision deficiency

BACKGROUND/AIM

Congenital color vision deficiency (CCVD) is an eye disease characterized by abnormalities in the cone cells in the photoreceptor layer. Visual evoked potentials (VEPs) are electrophysiological tests that physiologically examine the optic nerve, other visual pathways, and the visual cortex. The aim of this research was to determine whether there are VEP abnormalities in CCVD patients.

METHODS

Patients with CCVD and healthy individuals were included in this prospective case-control study. Participants with eye disease or neurodegenerative disease were excluded from the study. Pattern reversal VEP (PVEP), flash VEP (FVEP), and optical coherence tomography were performed on all participants.

RESULTS

Twenty healthy individuals (15 male) and 21 patients with CCVD (18 male) were included in the study. The mean ages of healthy individuals and patients with CCVD were 29.8 ± 9.6 and 31.1 ± 10.9 years (p = 0.804). Retinal nerve fiber layer thickness and central macular thickness values did not differ between the two groups. In PVEP, Right P100, Left N75, P100, N135 values were delayed in CCVD patients compared to healthy individuals (p = 0.001, p = 0.032, p = 0.003, p = 0.032). At least one PVEP and FVEP abnormality was present in nine (42.9%) and six (28.6%) of the patients, respectively. PVEP or FVEP abnormalities were found in 13 (61.9%) of the patients.

CONCLUSION

This study indicated that there may be PVEP and FVEP abnormalities in patients with CCVD.

Fatigue factors and fatigue indices in SSVEP-based brain-computer interfaces: a systematic review and meta-analysis

Background

Fatigue is a serious challenge when applying a steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) in the real world. Many researchers have used quantitative indices to study the effect of visual stimuli on fatigue. According to a wide range of studies in fatigue analysis, there are contradictions and inconsistencies in the behavior of fatigue indicators.

New method

In this study, for the first time, a systematic review and meta-analysis were performed on fatigue indices and fatigue caused by stimulation paradigm. We queried three scientific search engines for studies published between 2000 and 2022. The inclusion criteria were papers investigating mental and visual fatigue from performing a visual task using electroencephalogram (EEG) signals.

Results

Attractiveness and variation are the most effective ways to reduce BCI fatigue. Therefore, zoom motion, Newton's ring motion, and cue patterns reduce fatigue. While the color of the cue could effectively reduce fatigue, its shape and background had no effect on fatigue. Additionally, the questionnaire and quantitative indicators such as frequency indices, signal-to-noise ratio (SNR), SSVEP amplitude, and multiscale entropy were utilized to assess fatigue. Meta-analysis indicated that when a person is fatigued, the spectrum amplitude of alpha, theta, and α + θ / β increase significantly, while SNR and SSVEP amplitude decrease significantly.

Conclusion

The outcomes of this study can be used to design more optimal stimulation protocols that cause less fatigue. Moreover, the level of fatigue can be quantitatively assessed with indicators without the participant's self-reports.