Viewing the Visual System from Shaky Ground

Gianni M. Castiglione, Ph.D.

Our sensory systems for sight, smell, and hearing which most of us take for granted every second of every day are underlain by an incredibly complex biological reality that we don’t truly understand. What we do know however, has the capacity to present such interesting and fundamental questions that it must not remain bottled up within experts and inaccessible to non-specialists.

Consider the visual system, which evolved in its first form approximately 420 million years ago (MYA) within a series of long dead ancestral vertebrates that had a basic camera-type eye to navigate their complex world [1]. Interestingly, the eye as an evolutionary innovation has been proposed as a causative factor in the Cambrian explosion [2], where later spatial complexity and the need for navigation in free-swimming organisms [3], together with pressures to detect prey/avoid predators [4] drove its further evolution. There has been a lot of time since then for this system to specialize into all the different colours, shapes and appearances we came to know as children. Yet, all vertebrate eyes share a remarkable level of common detail, the most basic of which are its functions to transmit and focus light onto the retina- an incredibly dense nerve cell layer at the back of the eye that acts as a light receiver. This neuron web forms the retinal circuit, aptly named since within it neuronal cells amplify, extract and compress light signals into different salt concentrations, also known as electro-chemistry (think ‘batteries’). This electric signal is eventually transmitted to the optic nerve, which signals to the midbrain and thalamus, then onto to the cerebral cortex [5]. The first-layer of circuitry within your eyes is not just an electrical system connected to the grid inside your head: each neuronal connection within the retina computationally processes visual information by using logic gates of wet flesh, not dry silicon.

Six cell classes comprise the retinal circuits: primary photoreceptors (rods and cones), bipolar cells, amacrine cells, horizontal cells, Müller cells and ganglion cells [6,7], arranged into ordered layers. Counter-intuitively, the cone and rod photoreceptors functioning primarily in day-light and dim-light, respectively, are located in the layer furthest away from incoming light, despite being the site where the light signal is first detected [8]. Also striking is that in response to light, all vertebrate photoreceptors decrease their release of neurotransmitter that is constantly flowing in the dark without stimulus [9]. This is done by increasing their negative charge through changing the salt concentrations within the cell [10]. The genius of this circuitry is that the next layer (horizontal and bipolar cells) detecting this decreased flow of neurotransmitter [6] exists in two different basic forms, changing their electric charge to either become more negative (OFF-channel) or more positive (ON-channel), depending on the where they are within the retinal circuitry [11,12]. This computer chip at the back of your eyes not only detects day-light visual signals but funnels them into the OFF- and ON-center channel pathways [13], thereby forming a circuit that relies on different concentrations of salty water to conduct complex processing of light signals before they’re passed on to your brain. The details are extremely intricate and they facilitate many processes, but one essential calculation is done by the ON-channels signalling when incoming light is brighter than background, and OFF-channels signalling when incoming light is darker than background [14].

These and other visual inputs sent to the cerebral cortex are determined by these computations in this first layer, similar to how base-layer code provides input for a complex operating system, determining the entire functioning (and therefore disease-state) of the computer. Therefore, hundreds of millions of years before humans ‘invented’ math, logic, and computer circuits, natural selection was already exploiting these concepts to help you form the ability to contrast different light intensities

The computer analogy is very useful for scientists to make sense of the retina, enabling the creation of cures for retinal diseases [15,16]. However, many of these are underlain by mutations that disrupt the molecular details of the visual system [17–19], where the distinction between chemistry and biology blurs. It is becoming increasingly obvious that these finer details operate under rules more in line with quantum mechanics, rather than electrochemistry and computer circuitry. An accompanying digest will explain how, when it comes to the visual system, this new reality is breaking down the utility of the computer analogy. This challenges us to more accurately understand our world by resisting the attractive, but misleading promises of explanatory models we may find familiar. 


Many of the scientists who pioneered this work have described it in excellent detail here:

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2.        Parker AR. On the origin of optics. Opt Laser Technol. Elsevier; 2011;43: 323–329. doi:10.1016/j.optlastec.2008.12.020

3.        Plotnick RE, Dornbos SQ, Chen J. Information landscapes and sensory ecology of the Cambrian Radiation. Paleobiology. 2010;36: 303–317.

4.        Lacalli TC. New perspectives on the evolution of protochordate sensory and locomotory systems, and the origin of brains and heads. Philos Trans R Soc Lond B Biol Sci. 2001;356: 1565–1572. doi:10.1098/rstb.2001.0974

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9.        Yau KW, Hardie RC. Phototransduction Motifs and Variations. Cell. 2009;139: 246–264. doi:10.1016/j.cell.2009.09.029

10.      Trifonov YA. Study of synaptic transmission between the photoreceptor and the horizontal cell using electrical stimulation of the retina. Biofizika. 1968;10: 673–680.

11.      Werblin FS, Berkeley UC. Information Processing in the Retina. 2010; 372–378.

12.      Kaneko A. Physiological and Morphological Identification of Horizontal, Bipolar and Amacrine Cells in Goldfish Retina. J Physiol. 1970;297: 623–633.

13.      Nelson R, Kolb H. Synaptic patterns and response properties of bipolar and ganglion cells in the cat retina. Vision Res. 1983;23: 1183–1195. doi:10.1016/0042-6989(83)90032-9

14.      Kuffler SW. Discharge Patterns and Functional Organization of Mammalian Retina. J Neurophysiol. 1953;16: 37–68. Available: neuroscience BBB 217/kuffler_53.pdf%5Cn

15.      Berger W, Kloeckener-Gruissem B, Neidhardt J. The molecular basis of human retinal and vitreoretinal diseases. Prog Retin Eye Res. Elsevier Ltd; 2010;29: 335–75. doi:10.1016/j.preteyeres.2010.03.004

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17.      Rivolta C, Sharon D, DeAngelis MM, Dryja TP. Retinitis pigmentosa and allied diseases: numerous diseases, genes, and inheritance patterns. Hum Mol Genet. 2002;11: 1219–27. Available:

18.      Nishiguchi KM, Tearle RG, Liu YP, Oh EC, Miyake N, Benaglio P, et al. Whole genome sequencing in patients with retinitis pigmentosa reveals pathogenic DNA structural changes and NEK2 as a new disease gene. Proc Natl Acad Sci U S A. 2013;110: 16139–44. doi:10.1073/pnas.1308243110

19.      Morrow JM, Castiglione GM, Dungan SZ, Tang PL, Bhattacharyya N, Hauser FE, et al. An experimental comparison of human and bovine rhodopsin provides insight into the molecular basis of retinal disease. FEBS Lett. 2017;. doi:10.1002/1873-3468.12637