Haziel Rynjah, M. Optom.
Assistant Professor, University of Science and Technology, Baridua, India
Our ability to perceive and interact with our surroundings is influenced by colour vision, a fundamental aspect of human visual perception.(1) The accurate colour discrimination supports daily activities and professional tasks, from identifying traffic signals to differentiating pathological signs in clinical imaging. (2) Colour Vision Deficiency (CVD) has a major impact on academic performance, career prospects, and quality of life.(3)
The goal is to close the gap between new developments in colour vision research and clinical knowledge. It emphasises the current research directions, clinical implications, diagnostic techniques, and physiological foundation of optometry and visual science.
Understanding the Physiology of Colour Vision
Cone photoreceptors in the retina, more especially the short (S), medium (M), and long (L) wavelength cones, allow the brain to perceive colour vision. (3,4) The brain uses the differential stimulation of these cones to interpret colour, and each type is sensitive to distinct regions of the light spectrum.(4)
Colour Vision Deficiencies typically arise from genetic anomalies affecting the opsin genes that encode for these cone pigments. Red-green deficiencies (protan and deutan types) are X-linked and are the most prevalent, as shown in Table 1, whereas blue-yellow deficiency (tritan type) is rare and autosomal. (5,6) Below mentioned table presents the inheritance pattern of X-linked red-green colour blindness..
No | Name | Age | City |
---|---|---|---|
1 | Asha | 25 | Delhi |
2 | Rohit | 30 | Mumbai |
3 | Meera | 28 | Bangalore |
Table 1: Inheritance Pattern of X-linked Red-Green Colour Blindness where Normal Father (XY) × Carrier Mother (XᴄX)
Image Courtesy: Created by Author
Offspring | Probability |
---|---|
Carrier Daughter (XcX) | 50% |
Normal Son (XY) | 50% |
Table 2: Inheritance Pattern of X-linked Red-Green Colour Blindness where Colourblind Father (XᴄY) × Normal Mother (XX)
Image Courtesy: Created by Author
Offspring | Probability |
---|---|
Normal Son (XY) | 25% |
Colourblind Son (XcY) | 25% |
Carrier Daughter (XcX) | 25% |
Colourblind Daughter (XcXc) | 25% |
Table 3: Inheritance Pattern of X-linked Red-Green Colour Blindness where Colourblind Father (XᴄY) × Carrier Mother (XᴄX)
Image Courtesy: Created by Author
Diagnostic Tools and Clinical Relevance
Early detection of CVD is essential in clinical practice, especially in children and people whose careers may depend on their ability to perceive colour accurately. Colour vision tests that are frequently used include:
- Ishihara Plates: These are used to screen red-green deficiencies. (7)
- Hardy-Rand-Rittler (HRR) Test: The test can identify deficiencies that are blue-yellow and red-green.
- Farnsworth D-15 and Farnsworth-Munsell 100 Hue Test: Help determine the kind and degree of colour discrimination impairment. (8)
- Anomaloscopes: Regarded as the gold standard for identifying and classifying CVD types. (8)
In addition to providing diagnoses, optometrists are essential in counselling patients regarding coping mechanisms, educational accommodations, and occupational considerations.
Figure 1: Colour vision testing
Recent Research and Advances
Modern research in colour vision explores a variety of topics, including:
- Genetic Therapy: Early studies show potential in correcting red-green deficiencies using gene therapy in animal models. (6)
- Adaptive Lenses and Filters: Specialised lenses (e.g., EnChroma, VINO) claim to enhance contrast and colour discrimination, though their clinical efficacy remains debated. (9)
- Neurological Studies: Advances in functional MRI and electrophysiology allow researchers to study cortical colour processing and adaptation mechanisms in the brain. (10)
- Artificial Intelligence: Machine learning models are now being used to simulate and detect colour vision anomalies, aiding in faster screening and personalised care. (11)
Conclusion
Colour vision is a complex, multi-faceted aspect of human sight that extends beyond simple colour naming. For optometrists and vision scientists, understanding its physiological basis, clinical assessment tools, and the latest research developments is essential for providing holistic care. (1,11) With growing research in genetics, technology, and neuro-visual processing, the landscape of colour vision science continues to evolve, offering both challenges and opportunities in clinical practice. (9) As we continue to explore new frontiers in visual perception, staying informed about colour vision perspectives not only enhances clinical outcomes but also contributes to inclusive and adaptive care in the modern optometric setting.
References
- Simunovic, M. P. (2010). Colour vision deficiency. Eye, 24(5), 747-755.
- Martínez-Domingo, M. Á., Valero, E. M., Gomez-Robledo, L., Huertas, R., & Hernandez-Andres, J. (2020). Spectral filter selection for increasing chromatic diversity in CVD subjects. Sensors, 20(7), 2023.
- Jacobs, G. H. (1993). The distribution and nature of colour vision among the mammals. Biological Reviews of the Cambridge Philosophical Society, 68(3), 413-471.
- Nathans, J. (1999). The evolution and physiology of human color vision: insights from molecular genetic studies of visual pigments. Neuron, 24(2), 299-312.
- Davidoff, C., Neitz, M., & Neitz, J. (2016). Genetic testing as a new standard for clinical diagnosis of color vision deficiencies. Translational vision science & technology, 5(5), 2-2.
- Deeb, S. S. (2004). Molecular genetics of color-vision deficiencies. Visual neuroscience, 21(3), 191-196.
- Hathibelagal, A. R. (2024). Color Vision. In Ophthalmic Diagnostics: Technology, Techniques, and Clinical Applications (pp. 101-112). Singapore: Springer Nature Singapore.
- Marechal, M., Delbarre, M., Tesson, J., Lacambre, C., Lefebvre, H., & Froussart-Maille, F. (2018). Color vision tests in pilots’ medical assessments. Aerospace Medicine and Human Performance, 89(8), 737-743.
- Huchzermeyer, C., Kremers, J., & Barbur, J. (2016). Color vision in clinical practice. In Human color vision (pp. 269-315). Cham: Springer International Publishing.
- Tobimatsu, S., Celesia, G. G., Haug, B. A., Onofrj, M., Sartucci, F., & Porciatti, V. (2000). Recent advances in clinical neurophysiology of vision. Supplements to Clinical neurophysiology, 53, 312-322.
- Bitkina, O. V., Park, J., & Ryu, D. H. (2024). Color Vision Deficiency Recognition Based on Eye-Tracking Metrics Using Machine Learning Approaches. International Journal of Human–Computer Interaction, 1-15.
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