Are photoreceptors in the retina that play a key role in night vision as they are most responsive to dark and light contrast?

AII Amacrine Cells

In the mammalian retina, rod and cone photoreceptors synapse onto largely different bipolar cells, thereby segregating their signals into different vertical streams. Whereas up to 11 different morphological types of cone bipolar cells have been reported, showing both on- and off-center physiology, only a single type of rod bipolar cell exists. It is interesting that the axons of rod bipolar cells do not directly contact ganglion cells but instead contact mainly the small-field, bistratified AII amacrine cell. In turn, AII cells form sign-conserving electrical synapses with the axon terminals of on-center cone bipolar cells and sign-inverting glycinergic chemical synapses with the axon terminals of off-center cone bipolar cells. In this way, both on- and off-center scotopic signals utilize the cone pathways before reaching the ganglion cells and ultimately higher brain centers.

The gap junctions formed between AII cells and the on-center cone bipolar cells form nonrectifying electrical synapses across which the direction of signal flow changes with stimulus intensity. As mentioned above, rod signals generated under dim, scotopic light conditions move from the AII cells to the cone bipolar cells to be distributed to the ganglion cells. In contrast, under bright, photopic conditions, cone signals move in the opposite direction, from cone bipolar cells to the AII amacrine cells. The interconnecting gap junctions thus do double duty as conduits for both rod and cone signals.

The AII amacrine cells also form gap junctions between one another, forming an extensive electrical syncytium. Computational models suggest that this coupling increases the signal-to-noise ratio of AII cell responses by summing synchronous responses and deceasing asynchronous noise. It is interesting that the conductance of these homologous AII cell–AII cell junctions is affected by light via modulation of dopamine release by changes in dark-light adaptation (Figures 6(a)–6(c)). Under dim, rod-mediated light conditions, the relationship between coupling and ambient light intensity has two phases: AII cells are relatively uncoupled in the dark-adapted retina but show a dramatic increase in coupling when dim background stimuli are presented (Figure 6(d)).

What is the function of the light-induced changes in AII cell–AII cell coupling? One idea is that these changes reflect the need for AII cells, as vital elements in the rod pathway, to remain responsive throughout the scotopic-mesopic range. In this scheme, dark adaptation is analogous to starlight conditions, under which rods will only sporadically absorb photons of light. The need, then, is for AII cells to preserve these isolated signals above the background noise. Accordingly, the AII cells are relatively uncoupled in that there are few correlated signals to sum, and so extensive coupling would serve to dissipate and thereby attenuate the few isolated responses rather than enhance them. As dawn approaches, more photons become available. In turn, AII amacrine cells show an increase in coupling, which provides for summation of synchronous activity over a wider area, thus preserving the fidelity of these rod-driven, correlated signals at the expense of spatial acuity. This transition in coupling between dark-adapted retinas and those illuminated with dim background light suggests two basic operating states for AII cells under scotopic/mesopic light conditions: (1) responding to single photon events and (2) summing signals over a relatively large area to sum synchronized events above the background noise. Overall, the AII cell coupling ensures that the most sensitive rod signals are maintained at the ganglion cell level and transmitted to higher brain centers.

2.1 The retina

There are two types of photoreceptors in the retina: cones and rods (Figure 6.3). Cones are color-selective, less sensitive to dim light than rods, and important for detailed color vision in daylight. Each cone contains one of three kinds of photopigments, specialized proteins that are sensitive to different wavelengths of light. These wavelengths roughly correspond to our ability to distinguish red, green, and blue. When light strikes a photopigment molecule, the light energy is absorbed and the molecule then changes shape in a way that modifies the flow of electrical current in that photoreceptor neuron. Cones are densely packed into the fovea, the central part of the retina that we use to look directly at objects to perceive their fine details. In the periphery, cones are more spread out and scattered, which is why objects in the periphery appear blurrier and their colors are less vivid.

Rods contain a different photopigment that is much more sensitive to low levels of light. Rods are important for night vision. We rely on seeing with our rods once our eyes have adapted to the darkness (dark adaptation). Curiously, there are no rods in the fovea, only cones, and the proportion of rods increases in the periphery. This is why you may have noticed when gazing at the night sky that a very faint star may be easier to see if you look slightly off to one side.

The signals from photoreceptors are processed by a collection of intermediary neurons, bipolar cells, horizontal cells, and amacrine cells, before they reach the ganglion cells, the final processing stage in the retina before signals leave the eye. The actual cell bodies of ganglion cells are located in the retina, but these cells have long axons that leave the retina at the blind spot and form the optic nerve. Each ganglion cell receives excitatory inputs from a collection of rods and cones; this distillation of information forms a receptive field. Ganglion cells at the fovea receive information from only a small number of cones, while ganglion cells in the periphery receive inputs from many rods (sometimes thousands). With so many rods providing converging input to a single ganglion cell, if any one of these rods is activated by photons of light, this may activate the cell, which increases the likelihood of being able to detect dim, scattered light. However, this increase in sensitivity to dim light is achieved at the cost of poorer resolution; rods provide more sensitivity but also a “blurrier” picture than the sharp daytime image provided by cone vision.

Retinal ganglion cells receive both excitatory and inhibitory inputs from bipolar neurons, and the spatial pattern of these inputs determines the cell's receptive field (Figure 6.4a). A neuron's receptive field refers to the portion of the visual field that can activate or strongly inhibit the response of that cell. Retinal ganglion neurons have center-surround receptive fields. For example, a cell with an on-center off-surround receptive field will respond strongly if a spot of light is presented at the center of the receptive field. As that spot of light is enlarged, responses will increase up to the point where light begins to spread beyond the boundaries of the on-center region. After that, the response of the ganglion cell starts to decline as the spot of light gets bigger and stimulates more and more of the surrounding off-region. (A cell with an off-center on-surround receptive field will respond best to a dark spot presented in the center of the receptive field.)

How can the behavior of retinal ganglion cells be understood? A key concept is that of lateral inhibition (Kuffler, 1953). Lateral inhibition means that the activity of a neuron may be inhibited by inputs coming from neurons that respond to neighboring regions of the visual field. For example, the retinal ganglion cell in Figure 6.4b receives excitatory inputs from cells corresponding to the on-center region and inhibitory inputs from the off-center region. The strengths of these excitatory and inhibitory inputs are usually balanced, so if uniform light is presented across both on- and off-regions, the neuron will not respond to uniform illumination.

Lateral inhibition is important for enhancing the neural representation of edges, regions of an image where the light intensity sharply changes. These sudden changes indicate the presence of possible contours, features, shapes, or objects in any visual scene, whereas uniform parts of a picture are not particularly informative or interesting. Figure 6.5 shows a picture of the fox in original form and after using a computer to filter out just the edges (right picture) so the regions in black show where ganglion cells would respond most strongly to the image. Lateral inhibition also leads to more efficient neural representation because only the neurons corresponding to the edge of a stimulus will fire strongly; other neurons with receptive fields that lie in a uniform region do not. Because the firing of neurons takes a lot of metabolic energy, this is much more efficient. This is an example of efficient neural coding; only a small number of neurons need to be active at any time to represent a particular visual stimulus.

Lateral inhibition also helps to ensure that the brain responds in a similar way to an object or a visual scene on a cloudy day and on a sunny day. Changes in the absolute level of brightness won't affect the pattern of activity on the retina very much at all; it is the relative brightness of objects that matters most. An example of this is if you see a friend wearing a red shirt. The absolute level of brightness of that shirt when you see your friend outside your house on a sunny day versus inside your house in a sheltered room will differ, but this will not affect the pattern of activity on the retina. On the other hand, the relative brightness of the shirt compared to other nearby objects or the background scene will make a difference on the retinal activity. Finally, lateral inhibition at multiple levels of visual processing, including the retina, lateral geniculate nucleus and visual cortex, may lead to interesting visual illusions such as the Hermann grid illusion (Figure 6.6).

2.1 The Retina

There are two types of photoreceptors in the retina: cones and rods (Fig. 4.3). Cones are color selective, less sensitive to dim light than rods, and important for detailed color vision in daylight. Each cone contains one of the three kinds of photopigments, specialized proteins that are sensitive to different wavelengths of light. These wavelengths roughly correspond to our ability to distinguish red, green, and blue. When light strikes a photopigment molecule, the light energy is absorbed and the molecule then changes shape in a way that modifies the flow of electrical current in that photoreceptor neuron. Cones are densely packed into the fovea, the central part of the retina that we use to look directly at objects to perceive their fine details. In the periphery, cones are more spread out and scattered, which is why objects in the periphery appear blurrier and their colors are less vivid.

Rods contain a different photopigment that is much more sensitive to low levels of light. Rods are important for night vision. We rely on seeing with our rods once our eyes have adapted to the darkness (dark adaptation). Curiously, there are no rods in the fovea, only cones, and the proportion of rods increases in the periphery. This is why you may have noticed when gazing at the night sky that a very faint star may be easier to see if you look slightly off to one side.

There are far more rods in the retina than cones, with roughly 120 million rods distributed throughout the retina except for the fovea, and 6–7 million cones that are concentrated in that fovea.

The signals from photoreceptors are processed by a collection of intermediary neurons, bipolar cells, horizontal cells, and amacrine cells, before they reach the ganglion cells, the final processing stage in the retina before the signals leave the eye. The actual cell bodies of ganglion cells are located in the retina, but these cells have long axons that leave the retina at the blind spot and form the optic nerve. Each ganglion cell receives excitatory inputs from a collection of rods and cones; this distillation of information forms a receptive field. Ganglion cells at the fovea receive information from only a small number of cones, whereas ganglion cells in the periphery receive inputs from many rods (sometimes thousands). With so many rods providing converging input to a single ganglion cell, if any one of these rods is activated by photons of light, this may activate the ganglion cell, which increases the likelihood of being able to detect dim, scattered light. However, this increase in sensitivity to dim light is achieved at the cost of poorer resolution; rods provide not only more sensitivity but also a “blurrier” picture than the sharp daytime image provided by cone vision.

Retinal ganglion cells receive both excitatory and inhibitory inputs from bipolar neurons, and the spatial pattern of these inputs determines the cell's receptive field (Fig. 4.4A). A neuron's receptive field refers to the portion of the visual field that can activate or strongly inhibit the response of that cell. Retinal ganglion neurons have center-surround receptive fields. For example, a cell with an on-center off-surround receptive field will respond strongly if a spot of light is presented at the center of the receptive field. As that spot of light is enlarged, responses will increase up to the point where light begins to spread beyond the boundaries of the on-center region. After that, the response of the ganglion cell starts to decline as the spot of light gets bigger and stimulates more and more of the surrounding off-region. Similarly, a cell with an off-center on-surround receptive field will respond best to a dark spot presented in the center of the receptive field.

How can the behavior of retinal ganglion cells be understood? A key concept is that of lateral inhibition (Kuffler, 1953). Lateral inhibition means that the activity of a neuron may be inhibited by inputs coming from neurons that respond to neighboring regions of the visual field. For example, the retinal ganglion cell in Fig. 4.4B receives excitatory inputs from cells corresponding to the on-center region and inhibitory inputs from the off-center region. The strengths of these excitatory and inhibitory inputs are usually balanced, so if uniform light is presented across both on- and off-regions, the neuron will not respond to uniform illumination.

Lateral inhibition is important for enhancing the neural representation of edges, regions of an image where the light intensity sharply changes. These sudden changes indicate the presence of possible contours, features, shapes, or objects in any visual scene, whereas uniform parts of a picture are not particularly informative or interesting. Fig. 4.5 shows a picture of a fox in original form and after using a computer to filter out just the edges (right picture) so that the regions in black show where ganglion cells would respond most strongly to the image. Lateral inhibition also leads to more efficient neural representation because only the neurons corresponding to the edge of a stimulus will fire strongly; other neurons with receptive fields that lie in a uniform region do not. Because the firing of neurons takes a lot of metabolic energy, this is much more efficient. This is an example of efficient neural coding; only a small number of neurons need to be active at any time to represent a particular visual stimulus.

Lateral inhibition also helps to ensure that the brain responds in a similar way to an object or a visual scene on a cloudy day and on a sunny day. Changes in the absolute level of brightness will not affect the pattern of activity on the retina very much at all; it is the relative brightness of objects that matters most. An example of this is you see a friend wearing a red shirt. The absolute level of brightness of that shirt when you see your friend outside your house on a sunny day versus inside your house in a sheltered room will differ, but this will not affect the pattern of activity on the retina. On the other hand, the relative brightness of the shirt compared with other nearby objects or the background scene will make a difference on the retinal activity. Finally, lateral inhibition at multiple levels of visual processing, including the retina, lateral geniculate nucleus (LGN), and visual cortex, may lead to interesting visual illusions such as the Hermann grid illusion (Fig. 4.6). We will discuss more about this type of illusion in Section 3.

Rods

The ONL contains photoreceptor cell bodies, both rods and cones.45 Even in the cone-dominated human retina, rods far outnumber cones, by a factor of 20 : 1, so they account for most of the ONL except at the fovea. The human retina contains approximately 100 million rods, and they pool signals to provide high sensitivity for dark-adapted vision, say starlight, which appears monochromatic. A lack of color vision is the hallmark of rod-mediated vision. Rods are absent within 350 µm of the fovea but reach a peak density in an annular region at about 20° eccentricity (Fig. 15.3). This does not match the area of maximum scotopic acuity, which occurs around 5°,60 so it has been suggested that another component of the rod pathway, such as the AII amacrine cells, present at a much lower density, forms a bottleneck to limit acuity61,62 (see below).

Rod and Cone Pathways in the Fish Retina

As shown in Figure 1, rod signals can reach ganglion cells through at least two separate pathways in all vertebrate species that have both rods and cones. First, rod input can reach ganglion cells through cones. In both mammalian and nonmammalian retinas, rods and cones are anatomically connected or coupled by gap junctions, a type of electrical synapse at which rod input can enter the cone circuit and thereby reach ganglion cells. Although it was thought that rod–cone electrical coupling is relatively weak, recent evidence has demonstrated that rod–cone coupling in both fish and mice is strong at night, but weak during the day due to the action of the retinal clock.

Second, rod input can reach ganglion cells through bipolar cell pathways that do not involve cones. Rods signal bipolar cells at chemical synapses in all vertebrates. In fish, these bipolar cells also receive synaptic contact from cones and, thus, are called mixed rod–cone bipolar cells (Figure 1). In contrast, in mammals, bipolar cells that receive rod input do not receive cone input. Individual ganglion cells in both fish and mammals can be driven by signals from both the rod and cone systems. In fish, mixed rod–cone bipolar cells synapse directly onto ganglion cells, whereas in mammals, rod bipolar cells do not directly synapse onto ganglion cells but instead provide indirect rod input to ganglion cells through AII amacrine cells, which then signal cone bipolar cells.

15.8 Retina

The retina consists of photoreceptor cells in contact with a complex network of neurons and nerve fibers which are connected to the brain via the optic nerve (see Fig. 15.7). Light absorbed by the photoreceptors produces nerve impulses that travel along the neural network and then through the optic nerve into the brain. The photoreceptors are located behind the neural network, so the light must pass through this cell layer before it reaches the photoreceptors.

There are two types of photoreceptor cells in the retina: cones and rods. The cones are responsible for sharp color vision in daylight. The rods provide vision in dim light.

Near the center of the retina is a small depression about 0.3 mm in diameter which is called the fovea. It consists entirely of cones packed closely together. Each cone is about 0.002 mm (2μm) in diameter. Most detailed vision is obtained on the part of the image that is projected on the fovea. When the eye scans a scene, it projects the region of greatest interest onto the fovea.

The region around the fovea contains both cones and rods. The structure of the retina becomes more coarse away from the fovea. The proportion of cones decreases until, near the edge, the retina is composed entirely of rods. In the fovea, each cone has its own path to the optic nerve. This allows the perception of details in the image projected on the fovea. Away from the fovea, a number of receptors are attached to the same nerve path. Here the resolution decreases, but the sensitivity to light and movement increases.

With the structure of the retina in mind, let us examine how we view a scene from a distance of about 2 m. From this distance, at any one instant, we can see most distinctly an object only about 4 cm in diameter. An object of this size is projected into an image about the size of the fovea.

Objects about 20 cm in diameter are seen clearly but not with complete sharpness. The periphery of large objects appears progressively less distinct. Thus, for example, if we focus on a person’s face 2 m away, we can see clearly the facial details, but we can pick out most clearly only a subsection about the size of the mouth. At the same time, we are aware of the person’s arms and legs, but we cannot detect, for example, details about the person’s shoes.

II.D.1 Optic Nerve

Cranial nerve II is composed of the distal parts of the axonal processes of retinal ganglion cells. These axons course caudally and medially from the retina to the optic chiasm, where some decussate (cross over) to the opposite side. The proximal parts of these same axons are then called the optic tract as they continue caudally and laterally from the chiasm to sites in the diencephalon and midbrain.

The retinal ganglion cells receive input from retinal bipolar cells, which in turn receive input from the receptor cells of the retina (rods and cones). Rods are predominantly located in the peripheral parts of the retina, whereas cones are densely packed in the central part of the retina, particularly within the fovea. Rods transduce light stimuli of a broad range of wavelengths, whereas cones are of three types for color vision, each transducing a different part of the spectrum. The transduction process is a complex series of biochemical events initiated by the absorption of a photon by pigment within the receptor cells. The visual world topologically maps in precise order onto the retina, and this map is preserved throughout the system.

The retinal bipolar neurons correspond to the bipolar neurons that lie within the ganglia of other sensory cranial nerve components in terms of their relative position in the sensory pathway. The retinal ganglion cells are the first-order multipolar neurons of the pathway. At the optic chiasm, optic nerve fibers that arise from retinal ganglion cells in the nasal (medial) retina decussate, whereas axons from retinal ganglion cells in the temporal (lateral) retina do not. The net result is that the axons in the optic tract on the right side, for example, receive input that initiates from stimuli in the left half of the visual world. Thus, the right brain “sees” the left visual world and vice versa.

The optic tract projects to multiple sites in the diencephalon and midbrain. The major visual pathway for conscious vision is to neocortex via the dorsal lateral geniculate nucleus in the dorsal thalamus. This nucleus contains two large-celled (magnocellular) layers; they receive input relayed from rods via ganglion cells in the peripheral parts of the retina that conveys the general location of stimuli and their motion. It also contains four small-celled (parvicellular) layers that receive fine form and color input from cones. The dorsal lateral geniculate nucleus projects to primary (striate) cortex, which lies in the caudal and medial part of the occipital lobe. The spatial information from retinal ganglion cells via the magnocellular layers of the dorsal lateral geniculate nucleus is relayed from striate cortex via multiple synapses predominantly to posterior parietal cortex, which is involved in spatial cortical functions, whereas the form and color information via the parvicellular geniculate layers is likewise relayed predominantly to inferotemporal cortex, which is involved in numerous complex functions including the visual recognition of objects and individuals.

Midbrain visual projections are to the superficial layers of the rostral part of the midbrain roof, the superior colliculus, in which visual information is mapped in register with similar maps of somatosensory and auditory space that are projected into its deeper layers. The superior colliculus visual input is relayed to part of the pulvinar in the dorsal thalamus, which in turn projects to extrastriate visual cortical areas, which border the primary visual cortex in the occipital lobe. The midbrain visual pathway is concerned with the spatial orientation of the visual world.

Damage to the retina or optic pathway causes loss of vision in part or all of visual space (the visual field) depending on the location and extent of the lesion. Although damage to the retina or optic nerve results in blindness for the eye on the same side, damage located in the thalamocortical part of the pathway causes a deficit for the visual field on the opposite side. Damage to the central part of the optic chiasm, as can occur with a pituitary gland tumor in that region, causes “tunnel vision”—loss of the peripheral parts of the visual field on both sides.

1 Synthesis, degradation and secretion of cGMP

Like occurs with others nucleotides (e.g., ATP), when GTP is cycled (cGMP) becomes into an important second messenger involved in numerous cell signaling pathways downstream the activation of different receptors and stimulus. In its own biochemical route, cGMP is synthetized intracellularly by guanylyl-cyclases and degraded by phosphodiesterases, although certain amount is secreted, generating a extracellular pool of cGMP.

Guanylyl-cyclases (GCs) are the enzymes that catalyze the conversion of GTP into cGMP. They are expressed in almost all cell types and their family include cytoplasmic or soluble (sGC) and membrane or particulated (pGC) isoforms which are activated by different kind of stimulus.

There are seven mammalian pGC isoforms (pGC-A to pGC-G) and they all are receptor-like dimeric transmembrane proteins. The principal ligands for pGC-A are atrial and brain natriuretic peptides (ANP and BNP), while pGC-B is mainly activated by C-type natriuretic peptide (CNP). pGC-C and pGC-D responds to other peptides such as guanylin, while the ligand for pGC-E, F, and G are still unknown. Nevertheless, it has been shown that GC-E and GC-F are activated in a Ca2 +-dependent manner by intracellular GC activating proteins, the GCAPs 1 and 2, and GC-G seems to be sensitive to CO2 and low temperatures (Kuhn, 2016). Interestingly, although pGC-B is the main isoform expressed in brain (Schulz et al., 1989), it is predominant in neurons while pGC-A seems to be more important in astrocytes (Sumners & Tang, 1992). Moreover, pGC-D, E and F have been identified specifically in olfactory epithelium, retina rods and cones and retina rods respectively.

Regarding to the sGC, it appears in the cytoplasm of almost all mammalian cell types and it consists on a heterodimeric protein formed by two subunits, α and β, with many different isotypes distributed in diverse tissues. In the brain, the most usual subunits combination is α1β1. The main activator of sGC is nitric oxide (NO), a freely diffusible intercellular signaling gas (Domek-Łopacińska & Strosznajder, 2005). Additionally, carbon monoxide can activate it too, though with less effectivity than NO, and protoporphyrin IX (PPIX), a heme precursor naturally synthesized from glycine, activates sGC in a NO-like manner (Lucas et al., 2000).

The relevance of cGMP for several physiology processes demands a tight control of its intracellular concentration. The phosphodiesterases (PDE) are in the opposite side to the GCs in the cGMP life cycle, since these enzymes degrade cGMP linearizing the molecule into GMP. It has been described 11 families: PDE1, 2, 3, 10, and 11 can hydrolyse cGMP together with cAMP (Cyclic Adenosine-Monophosphate) and some of them are expressed in brain (Kuhn, 2016), but only PDE5, 6 and 9, whose activation is directly modulated by intracellular cGMP levels themselves, specifically hydrolyse cGMP (Francis, Blount, & Corbin, 2011). cGMP binds directly to PDE5 promoting its activation by PKA (protein kinase A) or PKG-mediated phosphorylation (Corbin & Francis, 1999). Both PDE5 and PDE9 are expressed in different brain areas including the hippocampus (Saavedra, Giralt, Arumí, Alberch, & Pérez-Navarro, 2013; Van Staveren et al., 2003), while PDE6 is only expressed in retina (Bischoff, 2004) and it plays a key role in phototransduction, as it will be pointed later.

Efflux of cGMP from the cytoplasmic compartments where it is synthetized to the extracellular liquid is an alternative to PDE action in order to control intracellular cGMP levels. Secretion of cGMP has been well demonstrated in the cardiovascular system, gastrointestinal tract, kidney, airways, blood cells, genital tract and, importantly for this chapter, also in the brain (Sager, 2004). cGMP release from neural and glial cells has been described as a consequence of diverse events, such us natriuretic peptides treatments, inflammatory stimuli, depolarization, glutamate receptors activation and GC-stimulating drugs. In cultures of neurally derived glioma (C6-2B) and pheochromocytoma (PC-12) cells, treatment with atrial natriuretic factors (ANFs) stimulates cGMP release (Fiscus, Robles, Waldman, & Murad, 1987) and so does CNP in cortical cultured rat astrocytes (Touyz, Picard, Schiffrin, & Deschepper, 1997). In both cerebellar, cortical and hippocampal cultured rat astrocytes, cGMP secretion is also induced by treatment with the pro-inflammatory cytokine interleukin-1-β (IL-1β) (Pedraza, Baltrons, & Garcı´a, A., 2001). In primary cultures of cerebellar neurons, addition of glutamate increases intracellular cGMP up to a limit. Then, additional cGMP is released to the extracellular fluid. Montoliu, Llansola, Kosenko, Corbalán, and Felipo (1999) showed that high levels of intracellular cGMP are neurotoxic while increasing extracellular cGMP prevents glutamate neurotoxicity (Montoliu et al., 1999). In several more advanced experiments in cerebellum, increases in cGMP release mediated by both depolarizing and GC-stimulating drugs have been described in ex vivo rat slices (Tjörnhammar, Lazaridis, & Bartfai, 1986).

It has also been shown that chemical stimulation of glutamate receptors results in an increase of extracellular levels of cGMP in rat cerebellar cortex by a microdialysis-based in vivo approach (Luo, Leung, & Vincent, 1994). Extracellular cGMP is also increased in cerebellum in vivo, as assessed by microdialysis in freely moving rats by stimulation of NMDA receptors (Hermenegildo, 1998; Hermenegildo, Monfort, & Felipo, 2000) or of AMPA or metabotropic glutamate receptors (Boix, Llansola, Cabrera-Pastor, & Felipo, 2011) with a differential effect for different AMPA receptor subtypes (Cabrera-Pastor, Llansola, Reznikov, Boix, & Felipo, 2012).

Several of the studies above have shown that cGMP transport to the extracellular liquid is obstructed by organic anions transporters inhibitors (Pedraza et al., 2001; Tjörnhammar et al., 1986; Touyz, Picard, Schiffrin, & Deschepper, 2002). Since the pharmacology of cGMP secretion shows ATP-Binding-Cassette subfamily C (ABCC) ATPases characteristics, several multidrug resistance proteins (MRP) have emerged as plausible mediators of cGMP active transport through the plasmatic membrane (Sager, 2004). However, up to now all the evidences come from in vitro studies. Transfection of hamster lung fibroblasts with human MRP5 (ABCC5) cDNA showed high cGMP secretion from MRP5 overexpressing cells that can be regulated by PDE modulators (Jedlitschky, Burchell, & Keppler, 2000). MRP5 could be the main candidate to modulate brain extracellular cGMP levels since there are high transcription levels of this transporter both in rodents (Roberts et al., 2008; Soontornmalai, Vlaming, & Fritschy, 2006) and human brains (Nies et al., 2004), being localized in neurons, astrocytes and endothelium. Regarding MRP4 (ABCC4), its cGMP transport capacity was demonstrated using vesicles prepared from insect cells transfected with human MRP4 (Chen, Lee, & Kruh, 2001) but it is expressed predominantly in prostate and kidney (Dallas, Miller, & Bendayan, 2006; Klaassen & Aleksunes, 2010) and only slightly in choroid plexus and brain endothelium (Nies et al., 2004; Roberts et al., 2008). Finally, transfection of human MRP8 (ABCC11) in pig kidney epithelial cells demonstrated its ability to transport cGMP (Guo et al., 2003). No rodent orthologue has been reported and its expression in human brain is restricted to white matter axons (Bortfeld et al., 2006). This three ABCC transporters show different cGMP transport affinities and selectivity. MRP5 is a selective high affinitive transporter for cGMP while MRP4 and MRP8 are non-selective low affinitive transporters for cGMP (Sager & Ravna, 2009), which means that they also transport cAMP.

3.1 Basic Visibility

In discussing driving and vision, a distinction should be made between sensation and perception. To see an object, light receptors in an observer’s eye must generate sufficient neural energy to signal the object’s presence. This initial transduction of light energy to neural activity is principally the domain of sensation. However, even when adequate sensory registration of an object occurs, whether an object is actually seen and recognized also depends on the context of the visual scene and the knowledge, readiness, and experience of the observer. For example, objects are more quickly and reliably detected in an uncluttered scene than in a cluttered one; expected objects are more quickly and reliably detected than unexpected ones. Perception concerns what a person finally sees after registering sensory input.

Considering sensation first, if the receptors in the eye are insensitive to a stimulus, there is nothing for the perceptual system to interpret. The light sensitivity of the eye is dynamic and is influenced by the response characteristics and distributions of two classes of photoreceptors in the retina—rods and cones. Rods are more sensitive than cones and enable vision under low light levels, but they are disabled under bright conditions. Rods are absent in the central fovea of the retina, and rod-mediated vision is monochromatic. Cones are less sensitive to light than rods and are active under bright viewing conditions. They are densest in the central fovea and decline in number toward the periphery; there are three classes of cones with differing sensitivities to wavelengths of light, enabling color vision. To partially distinguish these differences in the response of the eye, vision has been identified as scotopic (monochromatic, rod-mediated vision) at low light levels (less than about 0.1 cd/m2), photopic (chromatic, cone-mediated vision) at high light levels (greater than about 3 cd/m2), and mesopic (a mixture of scotopic and photopic vision) at light levels in between. Light levels for nighttime driving conditions are generally in the mesopic range, although many objects illuminated by headlamps are in the photopic range, and unlit objects are in the scotopic range.

The implications for night driving are that objects that are looked at directly (i.e., exclusively with cones in the central fovea) require at least 3 cd/m2 to be seen clearly. Consequently, most objects require supplemental illumination to be seen with the same clarity as in daylight. One solution would be to flood the roadway with as much light as possible. However, such a strategy is both impractical and potentially disruptive to other road users, who may be temporarily blinded or discomforted by the light. Low-beam headlamp designs address this problem by distributing light about the roadway in a way that attempts to balance the vehicle operator’s illumination needs with the need to minimize glare to other road users. Light is aimed down, below the horizon, and to the right side of the road. This limits forward seeing distance and, particularly at high speed, leaves little time to respond to an obstacle in the roadway. A second, switched, high-beam system in intended to address this limitation by sending more light down the roadway. In theory, the driver switches between the two beam systems as the driving conditions require. In practice, it was found that only about less than half of the drivers in a Michigan study used their high-beam headlamps when they should.

Perhaps this happens because low-beam headlamps appear to provide sufficient illumination on modern roadways, which are marked by reflectorized lane striping and other supporting illumination. Drivers may not be aware that there is a visibility problem at all, judging their visual competence by their ability to maintain lane position. Unfortunately, while a driver’s steering and lane-keeping abilities appear to suffer little under low-beam illumination, detection of unreflectorized, low-contrast objects appears to be selectively degraded. Leibowitz, Owens, and Tyrrell have suggested that this situation leads drivers to routinely overdrive their headlamps. That is, their effective stopping distance exceeds their seeing distance. Consistent with this view is the fact that drivers involved in fatal nighttime pedestrian crashes often report not seeing the pedestrians at all.

A variety of countermeasures have been devised to extend a driver’s basic visual sensory capabilities while holding the problem of glare at bay. such countermeasures include night-vision systems that render the invisible infrared radiation reflected or emitted by a roadway object as a visible image on a display, methods of adaptively redistributing the light from headlamps to optimize visibility in a variety of driving conditions, and more widespread use of reflectorized clothing. At the same time, countermeasures to address the problem of glare appear to dominate the discussion of roadway visibility, perhaps because there is more public awareness of glare than of poor visibility.

7.2.1 Oxidoreductase