Download Photoreception

Photoreception: The vertebrate retina is a thin sheet of tissue lining the posterior part of the eye. It is highly organized and
consists of several layers of neurons (Fig. 1). The outermost layer comprises photosensitive cells, called photoreceptors. The
photoreceptors are signal transducers; they transduce the absorption of light into an electrical signal. Photoreceptors come in two
flavours: rods and cones.
Rods are exquisitely sensitive to light and can even detect single photons. They allow vision in dim light. In contrast, cones
are less (30-100-fold) sensitive to light than rods. They are used for vision during day light and for colour vision. The
highest density of cones is found in the center of the retina, the area centralis. In humans, in other primates and in some
birds, the very center of the retina is designed as a pit and is called fovea.
Both cell types, rods and cones, consist of four major parts - an outer segment, an inner segment that are connected by a
thin rudimentary cilium, a soma, and an axon with a synaptic region (Fig. 2). The outer segment houses the molecular
components for light absorption and generation of electrical signals. The inner segment harbours the machinery for
protein synthesis and energy production.
Figure 2: Photoreceptor cells.
Schematic drawing of rod and cone photoreceptor cells. The primary events of
photoreception take place in the outer segment of the cell, shown in brown.
The electrical light response is transmitted to other neurons through the synaptic region. The outer segments of rods and
cones are densely packed with stacks of membrane, the discs. The disc membrane harbours the visual pigment, rhodopsin.
The absorption of light triggers a photochemical reaction which isomerizes the chromophore of rhodopsin, 11-cis retinal,
and thereby initiates a sequence of conformational changes in the protein part of the molecule (Fig. 3). One intermediate of
the photochemical cycle of rhodopsin, metarhodopsin II, is formed within a few milliseconds and persists for several
minutes. This activated form of rhodopsin interacts with a trimeric GTP-binding protein, transducin and thereby
promotes the exchange of bound GDP for GTP at the α-subunit of transducin. As a consequence, the α-subunit dissociates
from the βγ-subunits of transducin. Subsequently, the α-subunit of transducin binds to and thereby removes an inhibitory
subunit from a phosphodiesterase (PDE). The PDE hydrolyzes the intracellular messenger of photoreception: cGMP to
GMP.
Figure 3: Photochemistry of rhodopsin.
A) Illumination triggers the isomerization of 11-cis-retinal to all-transretinal.
B) Upon illumination, rhodopsin undergoes a sequence of conformational
changes that produce meta-rhodopsin II, a stable intermediate of the
photocycle that activates the next protein in the transduction cascade,
transducin.
What is the function of cGMP in rod and cone photoreceptors (Fig. 4)? In the dark, the intracellular concentration of
cGMP is high. The second messenger binds to ion channels in the plasma membrane of the photoreceptor cell. These
channels are directly gated open by cGMP and are therefore, referred to as cyclic nucleotide-gated (CNG) ion channels. A
few percent of CNG channels are kept open in the dark by binding of cGMP and allow the influx of ions into the outer
segment. This influx is primarily carried by sodium (Na +) ions, but a small fraction is also carried by Ca 2+ ions. At the same
time K+ ions leave the inner segment through potassium (K+) channels. Due to this circulating current along the rod
photoreceptor, the so-called dark-current, the membrane potential of the photoeceptor cell is slightly depolarized. This
depolarization suffices to release the neurotransmitter glutamate from the synaptic terminal onto postsynaptic cells in the
retina, the horizontal and bipolar cells. Upon illumination, the cGMP is hydrolyzed by the PDE. The cGMP concentration
decreases and CNG channels close. Since current stops flowing into the cell, the cell hyperpolarizes and glutamate release
ceases. The change in neurotransmitter release is registered by bipolar cells, which relay this information onto ganglion
cells. The ganglion cells then convey the information to the brain.
Figure 4: Electrical response of photoreceptors to illumination.
In darkness, CNG channels in the plasma membrane of photoreceptor outer
segments are kept open by cGMP and the cell depolarizes (left). Upon
illumination, CNG channels close and the photoreceptor hyperpolarizes
(right).
Recovery of the photoreceptor from the light response and adjustment of light sensitivity is achieved by several feedback
mechanisms. Ca2+ ions play a major role in recovery and light adaptation. Upon illumination, Ca2+ entry through the CNG
channel ceases, whereas a Na+/Ca2+-K+ exchanger continues to export Ca2+ ions from the cell. The ensuing decrease of the
intracellular Ca2+ concentration triggers recovery and adaptation (Fig. 5). Ca2+ controls the synthesis of cGMP by
guanylate cyclase (GC). The enzymatic activity is controlled by specific Ca 2+-binding proteins (GCAP's). Furthermore,
inactivation of enzymatically active rhodopsin is achieved by phosphorylation through rhodopsin kinase. This process
involves another Ca2+-binding protein: recoverin. Finally, the ligand sensitivity of the CNG channel is controlled by a third
Ca2+-binding protein: calmodulin.
Figure 5: Acivation and recovery of the phototransduction cascade.
Two cycles necessary for transduction and for adaptation control and
fine-tune each other. Through CNG channels, cGMP controls the influx
of Ca2+, at the same time via GCAP and GC, Ca2+ controls the cGMP
concentration.
From: http://www.fz-juelich.de/ibi/ibi-1/Photoreception
Glutamate and glutamate receptors in the vertebrate retina
1. General overview of synaptic transmission.
Cells communicate with each other electrically, through gap junctions, and chemically, using neurotransmitters. Chemical
synaptic transmission allows nerve signals to be exchanged between cells which are electrically isolated from each other.
The chemical messenger, or neurotransmitter, provides a way to send the signal across the extracellular space, from the
presynaptic neuron to the postsynaptic cell. The space is called a cleft and is typically more than 10 nanometers across.
Neurotransmitters are synthesized in the presynaptic cell and stored in vesicles in presynaptic processes, such as the axon
terminal. When the presynaptic neuron is stimulated, calcium channels open and the influx of calcium ions into the axon
terminal triggers a cascade of events leading to the release of neurotransmitter. Once released, the neurotransmitter
diffuses across the cleft and binds to receptors on the postsynaptic cell, allowing the signal to propagate. Neurotransmitter
molecules can also bind onto presynaptic autoreceptors and transporters, regulating subsequent release and clearing excess
neurotransmitter from the cleft. Compounds classified as neurotransmitters have several characteristics in common
(reviewed in Massey, 1990, Erulkar, 1994). Briefly, (1) the neurotransmitter is synthesized, stored, and released from the
presynaptic terminal. (2) Specific neurotransmitter receptors are localized on the postsynaptic cells, and (3) there exists a
mechanism to stop neurotransmitter release and clear molecules from the cleft. Common neurotransmitters in the retina
are glutamate, GABA, glycine, dopamine, and acetylcholine. Neurotransmitter compounds can be small molecules, such as
glutamate and glycine, or large peptides, such as vasoactive intestinal peptide (VIP). Some neuroactive compounds are
amino acids, which also have metabolic functions in the presynaptic cell.
Fig. 1. Structure of the glutamate molecule (39 K jpeg image)
Glutamate (Fig. 1) is believed to be the major excitatory neurotransmitter in the retina. In general, glutamate is
synthesized from ammonium and alpha-ketoglutarate (a component of the Krebs Cycle) and is used in the synthesis of
proteins, other amino acids, and even other neurotransmitters (such as GABA; Stryer, 1988). Though glutamate is present
in all neurons, only a few are glutamatergic, releasing glutamate as their neurotransmitter. Neuroactive glutamate is stored
in synaptic vesicles in presynaptic axon terminals (Fykse and Fonnum, 1996). Glutamate is incorporated into the vesicles
by a glutamate transporter located in the vesicular membrane. This transporter selectively accumulates glutamate through
a sodium-independent, ATP-dependent process (Naito and Ueda, 1983, Tabb and Ueda, 1991, Fykse and Fonnum, 1996),
resulting in a high concentration of glutamate in each vesicle. Neuroactive glutamate is classified as an excitatory amino
acid (EAA) because glutamate binding onto postsynaptic receptors typically stimulates, or depolarizes, the postsynaptic
cells.
2. Histological techniques identify glutamatergic neurons.
Fig. 2. Glutamate immunoreactivity (39 K jpeg image)
Using immunocytochemical techniques, neurons containing glutamate are identified and labeled with a glutamate
antibody. In the retina, photoreceptors, bipolar cells, and ganglion cells are glutamate immunoreactive (Ehinger et al, 1988,
Marc et al., 1990, Van Haesendonck and Missotten, 1990, Kalloniatis and Fletcher, 1993, Yang and Yazulla, 1994, Jojich
and Pourcho, 1996) (Fig. 2). Some horizontal and/or amacrine cells can also display weak
labeling with glutamate antibodies (Ehinger et al., 1988, Marc et al., 1990, Jojich and Pourcho,
1996; Yang, 1996). These neurons are believed to release GABA, not glutamate, as their
neurotransmitter (Yazulla, 1986), suggesting the weak glutamate labeling reflects the pool of
metabolic glutamate used in the synthesis of GABA. This has been supported by the results
from double-labeling studies using antibodies to both GABA and glutamate: glutamatepositive amacrine cells also label with the GABA antibodies (Jojich and Pourcho, 1996, Yang,
1996).
Fig. 3. Autoradiogram of glutamate uptake through glutamate transporters (39 K jpeg image)
Photoreceptors, which contain glutamate, actively take up radiolabeled glutamate from the
extracellular space, as do Muller cells (Fig. 3) (Marc and Lam, 1981; Yang and Wu, 1997).
Glutamate is incorporated into these cell types through a high affinity glutamate transporter located in the plasma
membrane. Glutamate transporters maintain the concentration of glutamate within the synaptic cleft at low levels,
preventing glutamate-induced cell death (Kanai et al., 1994). Though Muller cells take up glutamate, they do not label with
glutamate antibodies (Jojich and Pourcho, 1996). Glutamate incorporated into Muller cells is rapidly broken down into
glutamine, which is then exported from glial cells and incorporated into surrounding neurons (Pow and Crook, 1996).
Neurons can then synthesize glutamate from glutamine (Hertz, 1979, Pow and Crook, 1996).
Thus, histological techniques are used to identify potential glutamatergic neurons by labeling neurons containing
glutamate (through immunocytochemistry) and neurons that take up glutamate (through autoradiography). To determine
if these cell types actually release glutamate as their neurotransmitter, however, the receptors on postsynaptic cells have to
be examined.
3. Glutamate receptors.
Once released from the presynaptic terminal, glutamate diffuses across the cleft and binds onto receptors located on the
dendrites of the postsynaptic cell(s). Multiple glutamate receptor types have been identified. Though glutamate will bind
onto all glutamate receptors, each receptor is characterized by its sensitivity to specific glutamate analogues and by the
features of the glutamate-elicited current. Glutamate receptor agonists and antagonists are structurally similar to
glutamate (Fig. 4), which allows them to bind onto glutamate receptors. These compounds are highly specific and, even in
intact tissue, can be used in very low concentrations because they are poor substrates for glutamate uptake systems
(Tachibana and Kaneko, 1988, Schwartz and Tachibana, 1990).
Fig. 4. Glutamate receptor agonists and antagonists (39 K jpeg image)
Two classes of glutamate receptors (Fig. 5) have been identified: (1) ionotropic glutamate receptors, which directly gate ion
channels, and (2) metabotropic glutamate receptors, which may be coupled to an ion channel or other cellular functions via
an intracellular second messenger cascade. These receptor types are similar in that they both bind glutamate and
glutamate binding can influence the permeability of ion channels. However, there are several differences between the two
classes.
Fig. 5. Ionotropic and metabotropic glutamate receptors and channels (39 K jpeg image)
4. Ionotropic glutamate receptors.
Glutamate binding onto an ionotropic receptor directly influences ion channel activity because the receptor and the ion
channel form one complex (Fig. 5a). These receptors mediate fast synaptic transmission between neurons. Each ionotropic
glutamate receptor, or iGluR, is formed from the co-assembly of individual subunits. The assembled subunits may or may
not be homologous, with the different combinations of subunits resulting in channels with different characteristics
(Keinanen et al., 1990, Verdoorn et al., 1991, Moyner et al., 1992; Nakanishi, 1992, Ozawa and Rossier, 1996).
Fig. 6. Comparison between NMDA and non-NMDA receptors(39 K jpeg image)
Two iGluR types (see Fig. 6) have been identified: (1) NMDA receptors, which bind glutamate and the glutamate analogue
N-Methyl-D-Aspartate (NMDA) and (2) non-NMDA receptors, which are selectively agonized by kainate, AMPA, and
quisqualate, but not NMDA.
Non-NMDA receptors. Glutamate binding onto a non-NMDA receptor opens non-selective cation channels more
permeable to sodium (Na+) and potassium (K+) ions than calcium (Ca+2) (Mayer and Westbrook, 1987). Glutamate
binding elicits a rapidly activating inward current at membrane potentials negative to 0 mV, and an outward current at
potentials positive to 0 mV. Kainate, quisqualate, and AMPA (alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid)
are the specific agonists at these receptors; CNQX (6-cyano-7-nitroquinoxaline-2,3-dione), NBQX (1,2,3,4-tetrahydro-6nitro-2,3-dione-benzo[f]quinoxaline-7-sulfonamide), and DNQX (6,7-dinitroquinoxaline-2,3-dione) are the antagonists.
Fig. 7. Whole-cell patch clamp to show quisqualate and kainate gated currents(39 K jpeg image)
In retina, non-NMDA receptors have been identified on horizontal cells, OFF-bipolar cells, amacrine cells, and ganglion
cells (see below). Patch clamp recordings (Gilbertson et al., 1991, Zhou et al., 1993, Boos et al., 1993, Cohen and Miller,
1994, Yu and Miller, 1995) indicate that AMPA, quisqualate, and/or kainate application can evoke currents in these cells.
However, the kinetics of the ligand-gated currents differ. AMPA - and quisqualate-elicited currents rapidly desensitize;
whereas, kainate-gated currents do not (Fig. 7a). The desensitization at AMPA/quisqualate receptors can be reduced (Fig.
7b) by adding cyclothiazide (Yamada and Tang, 1993), which stabilizes the receptor in an active (or non-desensitized) state
(Yamada and Tang, 1993, Kessler et al., 1996).
Each non-NMDA receptor is formed from the co-assembly of several subunits (Boulter et al., 1990, Nakanishi et al., 1990,
Nakanishi, 1992). To date, seven subunits (named GluR1 through GluR7) have been cloned (Hollmann et al., 1989, Boulter
et al., 1990, Keinanen et al., 1990, Nakanishi et al., 1990, Bettler et al., 1990, 1992, Egebjerg et al., 1991). Expression of
subunit clones in Xenopus oocytes revealed that GluR5, GluR6, and GluR7 (along with subunits KA1 and KA2) coassemble to form kainate(-preferring) receptors; whereas, GluR1, GluR2, GluR3, and GluR4 are assembled into AMPA(preferring) receptors (Nakanishi, 1992).
NMDA receptors. Glutamate binding onto an NMDA receptor also opens non-selective cation channels, resulting in a
conductance increase. However, the high conductance channel associated with these receptors is more permeable to Ca+2
than Na+ ions (Mayer and Westbrook, 1987) and NMDA-gated currents typically have slower kinetics than kainate- and
AMPA-gated channels. As the name suggests, NMDA is the selective agonist at these receptors. The compounds MK-801,
AP-5 (2-amino-5-phosphonopentanoic acid), and AP-7 (2-amino-7-phosphoheptanoic acid) are NMDA receptor
antagonists.
NMDA receptors are structurally complex, with separate binding sites for glutamate, glycine, magnesium ions (Mg+2), zinc
ions (Zn+2), and a polyamine recognition site (Fig. 6b). There is also an antagonist binding site for PCP and MK-801
(Lodge, 1997). The glutamate, glycine, and magnesium binding sites are important for receptor activation and gating of the
ion channel. In contrast, the zinc and polyamine sites are not needed for receptor activation, but affect the efficacy of the
channel. Zinc blocks the channel in a voltage-independent manner (Westbrook and Mayer, 1987). The polyamine site
(Ransom and Stec, 1988, Williams et al., 1994) binds compounds such as spermine or spermidine, either potentiating
(Ranson and Stec, 1988; Williams et al., 1994) or inhibiting (Williams et al., 1994) the activity of the receptor, depending on
the combination of subunits forming each NMDA receptor (Williams et al., 1994).
To date, five subunits (NR1, NR2a, N2b, N2c, and N2d) of NMDA receptors have been cloned (Moriyoshi et al., 1991, Ikeda
et al., 1992, Katsuwada et al., 1992, Meguro et al., 1992, Ishii et al., 1993). As with non-NMDA receptors, NMDA receptor
subunits can co-assemble as homomers (i.e., five NR1 subunits; Moyner et al., 1992, Moriyoshi et al., 1992) or heteromers
(one NR1 + four NR2 subunits; Meguro et al., 1992, Katsuwada et al., 1992, Moyner et al., 1992, Ishii et al., 1993).
However, all functional NMDA receptors express the NR1 subunit (Moyner et al., 1992, Nakanishi, 1992, Ishii et al., 1993).
Fig. 8. NMDA receptor activation(39 K jpeg image)
The glutamate, glycine, and Mg+2 binding sites confer both ligand-gated and voltage-gated properties onto NMDA
receptors. NMDA receptors are ligand-gated because the binding of glutamate (ligand) is required to activate the channel.
In addition, micromolar concentrations of glycine must also be present (Fig. 8) (Johnson and Ascher, 1987, Kleckner and
Dingledine, 1988). The requirement for both glutamate and glycine makes them co-agonists (Kleckner and Dingledine,
1988) at NMDA receptors.
Mg+2 ions provide a voltage-dependent block of NMDA-gated channels (Nowak et al., 1984). This can be seen in the
current-voltage (I-V) relationship presented in Fig. 9 (from Nowak et al., 1984).
Fig. 9. Mg+2 ions block NMDA receptor channels(39 K jpeg image)
I-V curves plotted from currents recorded in the presence of Mg+2 have a characteristic J-shape (dotted line); whereas, a
linear relationship is calculated in Mg+2-free solutions (solid line). At negative membrane potentials, Mg+2 ions occupy the
binding site causing less current to flow through the channel. As the membrane depolarizes, the Mg+2 block is removed
(Nowak et al., 1984).
Retinal ganglion cells and some amacrine cell types express functional NMDA receptors in addition to non-NMDA
receptors (i.e., Massey and Miller, 1988, 1990, Mittman et al., 1990, Dixon and Copenhagen 1992, Diamond and
Copenhagen, 1993, Cohen and Miller, 1994). The currents elicited through these different iGluR types can be distinguished
pharmacologically. Non-NMDA receptor antagonists block a transient component of the ganglion cell light response;
whereas, NMDA receptor antagonists block a more sustained component (Mittman et al., 1990, Diamond and Copenhagen,
1993, Hensley et al., 1993, Cohen and Miller, 1994). These findings suggest the currents elicited through co-localized
NMDA and non-NMDA receptors mediate differential contributions to the ON- and OFF-light responses observed in
ganglion cells (i.e., Diamond and Copenhagen, 1993).
5. Metabotropic glutamate receptors.
Unlike ionotropic receptors, which are directly linked to an ion channel, metabotropic receptors are coupled to their
associated ion channel through a second messenger pathway. Ligand (glutamate) binding activates a G-protein and
initiates an intracellular cascade (Nestler and Duman, 1994). Metabotropic glutamate receptors (mGluRs) are not coassembled from multiple subunits, but are one polypeptide (Fig. 5b). To date, eight mGluRs (mGluR1-mGluR8) have been
cloned (Houamed et al., 1991, Masu et al., 1991, Abe et al., 1992, Tanabe et al., 1992, Nakajima et al., 1993, Saugstad et al.,
1994, Duvoisin et al., 1995). These receptors are classified into three groups (I, II, and III) based on structural homology,
agonist selectivity, and their associated second messenger cascade (Table 1, end of chapter) (reviewed in Nakanishi, 1994,
Knopfel et al., 1995, Pin and Duvoisin, 1995, Pin and Bockaert, 1995).
In brief, Group I mGluRs (mGluR1 and mGluR5) are coupled to the hydrolysis of fatty acids and the release of calcium
from internal stores. Quisqualate and trans-ACPD are Group I agonists. Group II (mGluR2 and mGluR3) and Group III
(mGluRs 4, 6, 7, and 8) receptors are considered inhibitory because they are coupled to the downregulation of cyclic
nucleotide synthesis (Pin and Duvoisin, 1995). L-CCG-1 and trans-ACPD agonize Group II receptors; L-AP4 (also called
APB) selectively agonizes Group III receptors. In situ hybridization studies have revealed that the mRNAs encoding Group
I, II, and III mGluRs are present in retina (see below); however, with the exception of the APB receptor, the function of all
these receptor types in retina has not been characterized.
APB receptor. In contrast to non-NMDA and NMDA receptors, glutamate binding onto an APB receptor elicits a
conductance decrease (Slaughter and Miller, 1981, Nawy and Copenhagen, 1987, 1990) due to the closure of cGMP-gated
non-selective cation channels (Nawy and Jahr, 1990) (Fig. 10).
Fig. 10.Whole-cell current traces to show kinetics of APB receptor gated currents(39 K jpeg image)
APB application selectively blocks the ON-pathway in the retina (Fig. 11) (Slaughter and Miller, 1981), i.e., ON-bipolar cell
responses and the ON-responses in amacrine cells (Taylor and Wassle, 1995) and ganglion cells (Cohen and Miller, 1994,
Kittila and Massey, 1995, Jin and Brunken, 1996) are eliminated by APB. Experimental evidence (Slaughter and Miller
1981, Massey et al., 1983) suggests the APB receptor is localized to ON-bipolar cell dendrites. Inhibition of amacrine and
ganglion cell light responses, therefore, is due to a decrease in the input from ON-bipolar cells, not a direct effect on
postsynaptic receptors.
Fig. 11. Intracellular recordings to show that APB selectively antagonizes the ON-pathways (39 K jpeg image)
APB (2-amino-4-phosphobutyric acid, also called L-AP4) is the selective agonist for all Group
III mGluRs (mGluR4, 6, 7, and 8). So, which is the APB receptor located on ON-bipolar cell
dendrites? MGluR4, 7, and 8 expression has been observed in both the inner nuclear layer and
the ganglion cell layer (Duvoisin et al., 1995, Hartveit et al., 1995) suggesting these mGluRs are
associated with more than one cell type. In contrast, mGluR6 expression has been localized to
the INL (Nakajima et al., 1993, Hartveit et al., 1995) and the OPL (Nomura et al., 1994) where
bipolar cell somata and dendrites are located. Furthermore, ON-responses are abolished in mice lacking mGluR6
expression (Masu et al., 1995). These mutants also display abnormal ERG b-waves, suggesting an inhibition of the ONretinal pathway at the level of bipolar cells (Masu et al., 1995). Taken together, these findings suggest the APB receptor on
ON-bipolar cells is mGluR6.
6. Glutamate transporters and transporter-like receptors.
Glutamate transporters have been identified on photoreceptors (Marc and Lam, 1981, Tachibana and Kaneko, 1988,
Eliasof and Werblin, 1993) and Muller cells (Marc and Lam, 1981, Yang and Wu, 1997). From glutamate labeling studies,
the average concentration of glutamate in photoreceptors, bipolar cells, and ganglion cells is 5mM (Marc et al. 1990).
Physiological studies using isolated cells indicate that only µM levels of glutamate are required to activate glutamate
receptors (i.e., Aizenman et al., 1988, Zhou et al., 1993, Sasaki and Kaneko, 1996). Thus, the amount of glutamate released
into the synaptic cleft is several orders of magnitude higher than the concentration required to activate most postsynaptic
receptors. High affinity glutamate transporters located on adjacent neurons and surrounding glial cells rapidly remove
glutamate from the synaptic cleft to prevent cell death (Kanai et al., 1994). Five glutamate transporters, EAAT-1 (or
GLAST), EAAT-2 (or GLT-1), EAAT-3 (or EAAC-1), EAAT-4, and EAAT-5, have been cloned (Kanai and Hediger, 1992,
Pines et al., 1992, Fairman et al., 1995, Schultz and Stell, 1996, Arriza et al., 1997, Kanai et al., 1997).
Glutamate transporters are pharmacologically distinct from both iGluRs and mGluRs. L-glutamate, L-aspartate, and Daspartate are substrates for the transporters (Brew and Attwell, 1987, Tachibana and Kaneko, 1988, Eliasof and Werblin,
1993); glutamate receptor agonists (Brew and Attwell, 1987, Tachibana and Kaneko, 1988, Schwartz and Tachibana, 1990,
Eliasof and Werblin, 1993) and antagonists (Barbour et al., 1991, Eliasof and Werblin, 1993) are not. Glutamate uptake
can be blocked by the transporter blockers dihydrokainate (DHKA) and DL-threo-beta-hydroxyaspartate (HA) (Barbour
et al., 1991, Eliasof and Werblin 1993).
Fig. 12 Glutamate transporters in Muller cells are electrogenic (39 K jpeg image)
Glutamate transporters incorporate glutamate into Muller cells along with the co-transport of three Na+ ions (Brew and
Attwell, 1987, Barbour et al., 1988) and the antiport of one K+ ion (Barbour et al., 1988, Bouvier et al., 1992) and either
one OH- or one HCO3- ion (Bouvier et al., 1992) (Fig. 12). The excess sodium ions generate a net positive inward current
which drives the transporter (Brew and Attwell, 1987, Barbour et al., 1988). More recent findings indicate a glutamateelicited chloride current is also associated with some transporters (Eliasof and Jahr, 1996, Arriza et al., 1997).
It should be noted that the glutamate transporters located in the plasma membrane of neuronal and glial cells (discussed in
this section) are different from the glutamate transporters located on synaptic vesicles within presynaptic terminals (see
section 1). The transporters in the plasma membrane transport glutamate in a Na+- and voltage-dependent manner
independent of chloride (Brew and Attwell, 1987, Barbour et al., 1988, Kanai et al., 1994). L-glutamate, L-aspartate, and
D-aspartate are substrates for these transporters (i.e., Brew and Attwell, 1987). In contrast, the vesicular transporter
selectively concentrates glutamate into synaptic vesicles in a Na+-independent, ATP-dependent manner (Naito and Ueda,
1983, Tabb and Ueda, 1991, Fykse and Fonnum, 1996) that requires chloride (Tabb and Ueda, 1991, Fykse and Fonnum,
1996).
Glutamate receptors with transporter-like pharmacology have been described in photoreceptors (Picaud et al., 1995a, b,
Grant and Werblin, 1996) and ON-bipolar cells (Grant and Dowling 1995, 1996). These receptors are coupled to a chloride
current. The pharmacology of these receptors is similar to that described for glutamate transporters, as the glutamateelicited current is (1) dependent upon external Na+, (2) reduced by transporter blockers, and (3) insensitive to glutamate
agonists and antagonists. However, altering internal Na+ concentration does not change the reversal potential (Picaud et
al., 1995b) or the amplitude (Grant and Werblin, 1995, Grant and Dowling, 1996) of the glutamate-elicited current,
suggesting the receptor is distinct from glutamate transporters. At the photoreceptor terminals, the glutamate-elicited
chloride current may regulate membrane potential and subsequent voltage-gated channel activity (i.e., Picaud et al.,
1995a). Postsynaptically, this receptor is believed to mediate conductance changes underlying photoreceptor input to ONcone bipolar cells (Grant and Dowling, 1995).
7. Localization of glutamate receptor types in the retina.
Fig. 13. The types of neurons in the vertebrate retina (39 K jpeg image)
Photoreceptor, bipolar, ganglion cells comprise the vertical transduction pathway in the retina. This pathway is modulated
by lateral inputs from horizontal cells in the distal retina and amacrine cells in the proximal retina (Fig. 13). As described
in the previous sections, photoreceptor, bipolar, and ganglion cells show glutamate immunoreactivity. Glutamate responses
have been electrically characterized in horizontal and bipolar cells, which are postsynaptic to photoreceptors, and in
amacrine and ganglion cells, which are postsynaptic to bipolar cells. Taken together, these results suggest glutamate is the
neurotransmitter released by neurons in the vertical pathway. Recent in situ hybridization and immunocytochemical
studies have localized the expression of iGluR subunits, mGluRs, and glutamate transporter proteins in the retina. These
findings are summarized below.
8. Retinal neurons expressing ionotropic glutamate receptors.
Fig.14. Whole-cell currents in OFF bipolar cells (59 K jpeg
image)
Fig. 15. Whole-cell currents in horizontal cells (59 K jpeg
image)
In both higher and lower vertebrates, electrophysiological recording techniques have identified ionotropic glutamate
receptors on the neurons comprising the OFF-pathway (Table 2, end of chapter). In the distal retina, OFF-bipolar cells
(Fig. 14) (Euler et al., 1996, Sasaki and Kaneko, 1996, Hartveit, 1997) and horizontal cells (Fig. 15) (Yang and Wu, 1991,
Zhou et al., 1993, Kriaj et al., 1994) respond to kainate, AMPA, and quisqualate application, but not NMDA nor APB.
(However, NMDA receptors have been identified on catfish horizontal cells (OÕDell and Christensen, 1989, Eliasof and
Jahr, 1997) and APB-induced hyperpolarizations have been reported in some fish horizontal cells (Nawy et al., 1989,
Takahashi and Copenhagen, 1992, Furukawa et al., 1997)).
Non-NMDA agonists also stimulate both amacrine cells (Fig. 16a) (Massey and Miller, 1988, Dixon and Copenhagen, 1992,
Boos et al., 1993) and ganglion cells (Fig. 16b) (Mittman et al., 1990, Diamond and Copenhagen, 1993, Hensley et al., 1993,
Cohen and Miller, 1994, Yu and Miller, 1995). Ganglion cells responses to NMDA have been observed (Massey and Miller,
1988, 1990, Mittman et al., 1990, Diamond and Copenhagen, 1993, Cohen and Miller, 1994); whereas, NMDA responses
have been recorded in only some types of amacrine cells (Massey and Miller, 1988, Dixon and Copenhagen, 1992, Boos et
al., 1993, but see Hartveit and Veruki, 1997).
Fig. 16. Glutamate receptors on amacrine and ganglion cells (39 K jpeg image)
Consistent with this physiological data, antibodies to the different non-NMDA receptor subunits differentially label all
retinal layers (Table 3, end of chapter; Hartveit et al., 1994, Peng et al., 1995, Hughes, 1997, Pourcho et al., 1997) and
mRNAs encoding the different non-NMDA iGluR subunits are similarly expressed (Hughes et al., 1992, Hamassaki-Britto
et al., 1993, Brandstatter et al., 1994). In contrast, mRNAs encoding NMDA subunits are expressed predominantly in the
proximal retina, where amacrine and ganglion cells are located (INL, IPL, GCL; Table 3) (Brandstatter et al., 1994,
Hartveit et al., 1994), though mRNA encoding the NR2a subunit (Hartveit et al., 1994) has been observed in the OPL and
antibodies to the NR2d (Wenzel et al., 1997) and the NR1 subunits (Hughes, 1997) label rod bipolar cells.
9. Retinal neurons expressing metabotropic glutamate receptors.
All metabotropic glutamate receptors, except mGluR3, have been identified in retina either through antibody staining
(Peng et al., 1995, Brandstatter et al., 1996, Koulen et al., 1997, Pourcho et al., 1997) or in situ hybridization (Nakajima et
al., 1993, Duvoisin et al., 1995, Hartveit et al., 1995). MGluRs are differentially expressed throughout the retina,
specifically in the outer plexiform layer, inner nuclear layer, inner plexiform layer, and the ganglion cell layer (Table 4,
end of chapter). Though different patterns of mGluR expression have been observed in the retina, only the APB receptor
on ON-bipolar cells has been physiologically examined.
10. Retinal neurons expressing glutamate transporters.
The glutamate transporters GLAST, EAAC1, and GLT-1have been identified in retina (Table 5, end of chapter). GLAST
(L-glutamate/L-aspartate transporter) immunoreactivity is found in all retinal layers (Otori et al. 1994), but not in
neuronal tissue. GLAST is localized to Muller cell membranes (Otori et al. 1994, Derouiche and Rauen, 1995, Rauen et al.,
1996, Lehre et al., 1997). In contrast, EAAC-1 (excitatory amino acid carrier-1) antibodies do not label Muller cells or
photoreceptors. EAAC-1 immunoreactivity is observed in ganglion and amacrine cells in chicken, rat, goldfish, and turtle
retinas. In addition, bipolar cells positive labeled with EAAC-1 antibody in lower vertebrates and immunopositive
horizontal cells were observed in rat (Schultz and Stell, 1996). GLT-1 (glutamate transporter-1) proteins have been
identified in monkey (Grunert et al., 1994), rat (Rauen et al., 1996), and rabbit (Massey et al., 1997) bipolar cells. In
addition, a few amacrine cells were weakly labeled with the GLT-1 antibody in rat (Rauen et al., 1996), as were
photoreceptor terminals in rabbit (Massey et al., 1997).
11. Summary and conclusions.
Fig. 17. The ribbon glutamatergic synapse in the retina (39 K jpeg image)
Histological analyses of presynaptic neurons and physiological recordings from postsynaptic cells suggest photoreceptor,
bipolar, and ganglion cells release glutamate as their neurotransmitter. Multiple glutamate receptor types are present in
the retina. These receptors are pharmacologically distinct and differentially distributed. IGluRs directly gate ion channels
and mediate rapid synaptic transmission through either kainate/AMPA or NMDA receptors. Glutamate binding onto
iGluRs opens cation channels, depolarizing the postsynaptic cell membrane. Neurons within the OFF-pathway (horizontal
cells, OFF-bipolar cells, amacrine cells, and ganglion cells) express functional iGluRs. MGluRs are coupled to G-proteins.
Glutamate binding onto mGluRs can have a variety of effects depending on the second messenger cascade to which the
receptor is coupled. The APB receptor, found on ON-bipolar cell dendrites, is coupled to the synthesis of cGMP. At these
receptors, glutamate decreases cGMP formation leading to the closure of ion channels. Glutamate transporters, found on
glial and photoreceptor cells, are also present at glutamatergic synapses (Fig. 17). Transporters remove excess glutamate
from the synaptic cleft to prevent neurotoxicity. Thus, postsynaptic responses to glutamate are determined by the
distribution of receptors and transporters at a glutamatergic synapses which, in retina, determine the conductance
mechanisms underlying visual information processing within the ON- and OFF-pathways.
12. References.
Abe, T., Sugihara, H., Nawa, H., Shigemoto, R., Mizuno, N., and Nakanishi, S. (1992) Molecular characterization of a novel
metabotropic glutamate receptor mGluR5 coupled to inositol phosphate/Ca+2 signal transduction. J. Biol. Chem., 267,
13361-13368.
Aizenman, E., Frosch, M.P., and Lipton, S.A. (1988) Responses mediated by excitatory amino acid receptors in solitary
retinal ganglion cells from rat. J. Physiol., 396, 75-91.
Arriza, J.L., Eliasof, S., Kavanaugh, M.P., and Amara, S.G. (1997) Excitatory amino acid transporter 5, a retinal
glutamate transporter coupled to a chloride conductance. Proc. Natl. Acad. Sci., 94, 4155-4160.
Barbour, B., Brew, H., and Attwell, D. (1988) Electrogenic glutamate uptake in glial cells is activated by intracellular
potassium. Nature, 335, 433-435.
Barbour, B., Brew, H., and Attwell, D. (1991) Electrogenic uptake of glutamate and aspartate into glial cells isolated from
the salamander (Ambystoma) retina. J. Physiol., 436, 169-193.
Bettler, B., Boulter, J., Hermans-Borgmeyer, I., OÕShea-Greenfield, A., Deneris, E.S., Moll, C., Borgmeyer, U., Hollmann,
M., and Heinemann, S. (1990) Cloning of a novel glutamate receptor subunit, GluR5: expression in the nervous system
during development. Neuron, 5, 583-595.
Bettler, B., Egebjerg, J., Sharma, G., Pecht, G., Hermans-Borgmeyer, I., Moll, C., Stevens, C.F., and Heinemann, S. (1992)
Cloning of a putative glutamate receptor: a low affinity kainate-binding subunit. Neuron, 8, 257-265.
Boos, R., Schneider, H., and Wassle, H. (1993) Voltage- and transmitter-gated currents of AII amacrine cells in a slice
preparation of the rat retina. J. Neurosci., 13, 2874-2888.
Boulter, J., Hollmann, M., OÕShea-Greenfield, A., Hartley, M., Deneris, E., Maron, C., and Heinemann, S. (1990)
Molecular cloning and functional expression of glutamate receptor subunit genes. Science, 249, 1033-1037.
Bouvier, M., Szatkowski, M., Amato, A., and Attwell, D. (1992) The glial cell glutamate uptake carrier countertransports
pH-changing ions. Nature, 360, 471-474.
Brandstatter, J.H., Hartveit, E., Sasso-Pognetto, M., and Wassle, H. (1994) Expression of NMDA and high-affinity kainate
receptor subunit mRNAs in the adult rat retina. Eur. J. Neurosci., 6, 1100-1112.
Brandstatter, J.H., Koulen, P., Kuhn, R., van der Putten, H., and Wassle, H. (1996) Compartmental localization of a
metabotropic glutamate receptor (mGluR7): two different active sites at a retinal synapse. J. Neurosci., 16, 4749-4756.
Brew, H. and Attwell, D. (1987) Electrogenic glutamate uptake is a major current carrier in the membrane of axolotl
retinal glial cells. Nature, 327, 707-709.
Cohen, E.D. and Miller, R.F. (1994) The role of NMDA and non-NMDA excitatory amino acid receptors in the functional
organization of primate retinal ganglion cells. Vis. Neurosci., 11, 317-332.
Derouiche, A. and Rauen, T. (1995) Coincidence of L-glutamate/L-aspartate transporter (GLAST) and glutamine
synthetase (GS) immunoreactions in retinal glia: evidence for coupling of GLAST and GS in transmitter clearance. J.
Neurosci. Res., 42, 131-143.
Diamond, J.A. and Copenhagen, D.R. (1993) The contribution of NMDA and non-NMDA receptors to the light-evoked
input-output characteristics of retinal ganglion cells. Neuron, 11, 725-738.
Dixon, D.B. and Copenhagen, D.R. (1992) Two types of glutamate receptors differentially excite amacrine cells in the tiger
salamander retina. J. Physiol., 449, 589-606.
Duvoisin, R.M., Zhang, C., and Ramonell, K. (1995). A novel metabotropic glutamate receptor expressed in the retina and
olfactory bulb. J. Neurosci., 15, 3075-3083.
Egebjerg, J., Bettler, B., Hermans-Borgmeyer, I., and Heinemann, S. (1991) Cloning of a cDNA for a glutamate receptor
subunit activated by kainate but not AMPA. Nature, 351, 745-748.
Ehinger, B., Ottersen, O.P., Storm-Mathisen, J., and Dowling, J.E. (1988) Bipolar cells in the turtle retina are strongly
immunoreactive for glutamate. Proc. Natl. Acad. Sci., 85, 8321-8325.
Eliasof, S. and Jahr, C.E. (1996) Retinal glial cell glutamate transporter is coupled to an anionic conductance. Proc. Natl.
Acad. Sci., 93, 4153-4158.
Eliasof, S. and Jahr, C.E. (1997) Rapid AMPA receptor desensitization in catfish cone horizontal cells. Vis. Neurosci., 14,
13-18.
Eliasof, S. and Werblin, F. (1993) Characterization of the glutamate transporter in retinal cones of the tiger salamander. J.
Neurosci., 13, 402-411.
Erulkar, S.D. (1994) Chemically mediated synaptic transmission: an overview, pp. 181-208 In Basic Neurochemistry, 5th
ed. Siegel, G.J., Agranoff, B.J., Albers, R.W., and Molinoff, P.B. (eds). Raven Press, New York.
Euler, T., Schneider, H., and Wassle, H. (1996) Glutamate responses of bipolar cells in a slice preparation of the rat retina.
J. Neurophysiol., 16, 2934-2994.
Fairman, W.A., Vandengerg, R.J., Arriza, J.L., Kavanaugh, M.P., and Amara, S.G. (1995) An excitatory amino-acid
transporter with properties of a ligand-gated chloride channel. Nature, 375, 599-603.
Furukawa, T., Yamada, K.M., Petruv, R., Djamgoz, M.B.A., and Yasui, S. (1997) Nitric oxide, 2-amino-4-phosphobutyric
acid and light/dark adaptation modulate short-wavelength-sensitive synaptic transmission to retinal horizontal cells.
Neurosci. Res., 27, 65-74.
Fykse, E.M. and Fonnum, F. (1996) Amino acid neurotransmission: dynamics of vesicular uptake. Neurochem. Res., 21,
1053-1060.
Gilbertson, T.A., Scobey, R., and Wilson, M. (1991) Permeation of calcium ions through non-NMDA glutamate channels in
retinal bipolar cells. Science, 251, 1613-1615.
Grant, G.B. and Dowling, J.E. (1995) A glutamate-activated chloride current in cone-driven ON bipolar cells of the white
perch retina. J. Neurosci., 15, 3852-3862.
Grant, G.B. and Dowling, J.E. (1996) ON bipolar cell responses in the teleost retina are generated by two distinct
mechanisms. J. Neurophysiol., 76, 3842-3849.
Grant, G.B. and Werblin, F.S. (1996) A glutamate-elicited chloride current with transporter-like properties in rod
photoreceptors of the tiger salamander. Vis. Neurosci., 13, 135-144.
Grunert, U., Martin, P.R., and Wassle, H. (1994) Immunocytochemical analysis of bipolar cells in the Macaque monkey
retina. J. Comp. Neurol., 348, 607-627.
Hamassaki-Britto, D.E., Hermans-Borgmeyer, I., Heinemann, S., and Hughes, T.E. (1993) Expression of glutamate
receptor genes in the mammalian retina: the localization of GluR1 through GluR7 mRNAs. J. Neurosci., 13, 1888-1898.
Hartveit, E. (1997) Functional organization of cone bipolar cells in the rat retina. J. Neurophysiol., 77, 1716-1730.
Hartveit, E., Brandstatter, J.H., Sasso-Pognetto, M., Laurie, D.J., Seeburgh, P.H., and Wassle, H. (1994) Localization and
developmental expression of the NMDA receptor subunit NR2A in the mammalian retina. J. Comp. Neurol., 348, 570-582.
Hartveit, E., Brandsttter, J.H., Enz, R., and Wassle, H. (1995) Expression of the mRNA of seven metabotropic glutamate
receptors (mGluR1 to 7) in the rat retina. An in situ hybridization study on tissue section and isolated cells. Eur. J.
Neurosci., 7, 1472-1483.
Hartveit, E. and Veruki, M.L. (1997) AII amacrine cells express functional NMDA receptors. Neuroreport,8, 1219-1223.
Hensley, S.H., Yang, X.-L., and Wu, S.M. (1993) Identification of glutamate receptor subtypes mediating inputs to bipolar
cells and ganglion cells in the tiger salamander retina. J. Neurophysiol., 69, 2099-2107.
Hertz, L. (1979) Functional interactions between neurons and astrocytes I. Turnover and metabolism of putative amino
acid transmitters. Progr. Neurobiol., 13, 277-323.
Hirano, A.A. and MacLeish, P.R. (1991) Glutamate and 2-amino-4-phosphobutyric acid evoke an increase in potassium
conductance in retinal bipolar cells. Proc. Natl. Acad. Sci., 88, 805-809.
Hollmann, M., OÕShea-Greenfield, A., Rogers, S.W., and Heinemann, S. (1989) Cloning by functional expression of a
member of the glutamate receptor family. Nature, 342, 643-648.
Houamed, K.M., Kuijper, J.L., Gilbert, T.L., Haldeman, B.A., OÕHara, P.J., Mulvihill, E.R., Almers, W., and Hagen, F.S.
(1991) Cloning, expression, and gene structure of a G protein-coupled glutamate receptor from rat brain. Science, 252,
1318-1321.
Hughes, T.E. (1997) Are there ionotropic glutamate receptors on the rod bipolar cell of the mouse retina? Vis. Neurosci.,
14, 103-109.
Hughes, T.E., Hermans-Borgmeyer, I., and Heinemann, S. (1992) Differential expression of glutamate receptor genes
(GluR1-5) in the rat retina. Vis. Neurosci., 8, 49-55.
Ikeda, K., Nagasawa, M., Mori, H., Araki, K., Sakimura, K., Watanabe, M., Inoue, Y., and Mishina, M. (1992) Cloning and
expression of the ,4 subunit of the NMDA receptor channel. FEBS Lett., 313, 34-38.
Ishii, T., Moriyoshi, K., Sugihara, H., Sakurada, K., Kadotani, H., Yokoi, M., Akazawa, C., Shigemoto, R., Mizuno, N.,
Masu, M., and Nakanishi, S. (1993) Molecular characterization of the family of N-methyl-D-aspartate receptor subunits. J.
Biol. Chem., 268, 2836-2843.
Jahr, C.E. and Lester, R.A. (1992) Synaptic excitation mediated by glutamate-gated ion channels. Curr. Opin. Neurobiol.,
2, 270-274.
Jin, X.T. and Brunken, W.J. (1996) A differential effect of APB on ON- and OFF-center ganglion cells in the dark adapted
rabbit retina. Brain Res., 708, 191-196.
Johnson, J.W. and Ascher, P. (1987) Glycine potentiates the NMDA response in cultured mouse brain neurons. Nature,
325, 529-531.
Jojich, L. and Pourcho, R.G. (1996) Glutamate immunoreactivity in the cat retina: a Quantitative study. Vis. Neurosci., 13,
117-133.
Kalloniatis, M. and Fletcher, E.L. (1993) Immunocytochemical localization of the amino acid neurotransmitters in the
chicken retina. J. Comp. Neurol., 336, 174-193.
Kanai, Y. and Hediger, M.A. (1992) Primary structure and functional characterization of a high-affinity glutamate
transporter. Nature, 360, 467-471.
Kanai, Y., Smith, C.P., and Hediger, M.A. (1994) A new family of neurotransmitter transporters: the high-affinity
glutamate transporters. FASEB J., 8, 1450-1459.
Kanai, Y., Trotti, D., Nussberger, S., and Hediger, M.A. 1997. The high-affinity glutamate transporter family, structure,
function, and physiological relevance, pp. 171-213. In M.E.A. Reith (ed) Neurotransmitter transporters: structure,
function, and regulation, Humana Press, Totowa, NJ.
Kandel, E.R., Schwartz, J.H., and Jessell, T.M. (1991) Principles of neuroscience, 3rd ed. Elsevier Publishing Co, New
York.
Katsuwada, T., Kashiwabuchi, N., Mori, H., Sakimura, K., Kushiya, E., Araki, K., Megure, H., Masaki, H., Kumanishi, T.,
Arakawa, M., and Mishina, M. (1992) Molecular diversity of the NMDA receptor channel. Nature, 358, 36-41.
Keinanen, K., Wisden, W., Sommer, B., Werner, P., Herb, A., Versoorn, T.A., Sakmann, B., and Seeburg, P.H. (1990) A
family of AMPA-selective glutamate receptors. Science, 249, 556-560.
Kessler, M., Arai, A., Quan, A., and Lynch, G. (1996) Effect of cyclothiazide on binding properties of AMPA-type
glutamate receptors: lack of competition between cyclothiazide and GYKI 52466. Molecular Pharmacology, 49, 123-131.
Kittila, C.A. and Massey, S.C. (1995) Effect of ON pathway blockade on directional selectively in the rabbit retina. J.
Neurophysiol., 73, 703-712.
Kleckner, N.W. and Dingledine, R. (1988) Requirement for glycine activation of NMDA-receptors expressed in Xenopus
oocytes. Science, 241, 835-837.
Knopfel,T., Kuhn, R., and Allgeier, H. (1995) Metabotropic glutamate receptors: novel targets for drug development. J.
Med Chem., 38, 1417-1426.
Koulen, P., Kuhn, R., Wassle, H., and Brandstatter, J.H. (1997) Group I metabotropic glutamate receptors mGluR1" and
mGluR5a: localization in both synaptic layers of the rat retina. J. Neurosci., 17, 2200-2211.
Kriaj, D., Akopian, A., and Witkovsky, P. (1994) The effects of L-glutamate, AMPA, quisqualate, and kainate on retinal
horizontal cells depend on adaptational state: implications for rod-cone interactions. J. Neurosci., 14, 5661-5671.
Lehre, K.P., Davanger, S., and Danbolt, N.C. (1997) Localization of the glutamate transporter protein GLAST in rat
retina. Brain Res., 744, 129-137.
Lodge, D. (1997) Subtypes of glutamate receptors. Historical perspectives on their pharmacological differentiation, pp. 138 In The ionotropic glutamate receptors, Monaghan, D.T. and Weinhold, R.J. (eds), Humana Press, New Jersey.
Marc, R.E. and Lam, D.M.K. (1981) Uptake of aspartic and glutamic acid by photoreceptors in goldfish retina. Proc. Natl.
Acad. Sci., 78, 7185-7189.
Marc, R.E, Liu, W.-L.S., Kalloniatis, M., Raiguel, S.F., and Van Haesendonck, E. (1990) Patterns of glutamate
immunoreactivity in the goldfish retina. J. Neurosci., 10, 4006-4034.
Massey, S.C. (1990) Cell types using glutamate as a neurotransmitter in the vertebrate retina. Progr. Retinal Res., 9, 399425.
Massey, S.C., Koomen, J.M., Liu, S., Lehre, K.P., and Danbolt, N.C. (1997) Distribution of the glutamate transporter GLT1 in the rabbit retina. Invest. Ophthal. Vis. Sci., 38, S689.
Massey, S.C. and Miller, R.F. (1988) Glutamate receptors of ganglion cells in the rabbit retina: evidence for glutamate as a
bipolar cell transmitter. J. Physiol., 405, 635-655.
Massey, S.C. and Miller, R.F. (1990) N-Methyl-D-Aspartate receptors of ganglion cells in rabbit retina. J. Neurophysiol.,
63, 16-30.
Massey, S.C., Redburn, D.A., and Crawford, M.L.J. (1983) The effects of 2-amino-4-phosphobutyric acid (APB) on the
ERG and ganglion cell discharge of rabbit retina. Vision Res., 23, 1607-1613.
Masu, M., Tanabe, Y., Tsuchida, K., Shigemoto, R., and Nakanishi, S. (1991) Sequence and expression of a metabotropic
glutamate receptor. Nature, 349, 760-765.
Masu, M., Iwakabe, H., Tagawa, Y., Miyoshi, T., Yamashita, M., Fukuda, Y., Sasaki, H., Hiroi, K., Nakamura, Y.,
Shigemoto, R., Takada, M., Nakamura, K., Makao, K., Katsuki, M., and Nakanishi, S. (1995) Specific deficit of the ON
response in visual transmission by targeted disruption of the mGluR6 gene. Cell, 80, 757-765.
Mayer, M.L. and Westbrook, G.L. (1987) Permeation and block of N-Methyl-D-Aspartic acid receptor channels by
divalent cations in mouse cultured central neurones. J. Physiol., 394, 501-527.
Meguro, H., Mori, H., Araki, K., Kushiya, E., Kutsuwada, T., Yamazaki, M., Kumanishi, T., Arakawa, M., Sakimura, K.,
and Mishina, M. (1992) Functional characterization of a heteromeric NMDA receptor channel expressed from cloned
cDNAs. Nature, 357, 70-74.
Mittman, S., Taylor, W.R., and Copenhagen, D.R. (1990) Concomitant activation of two types of glutamate receptor
mediates excitation of salamander retinal ganglion cells. J. Physiol., 428, 175-197.
Moyner, H., Sprengel, R., Schoepfer, R., Herb, A., Higuchi, M., Lorneli, H., Burnashev, N., Sakmann, B., and Seeburg,
P.H. (1992) Heteromeric NMDA receptors: molecular and functional distinction of subtypes. Science, 256, 1217-1221.
Moriyoshi, K., Masu, M., Ishii, T., Shigemoto, R., Mizuno, N., and Nakanishi, S. (1991) Molecular cloning and
characterization of the rat NMDA receptor. Nature, 354, 31-37.
Naito, S. and Ueda, T. (1983) Adenosine triphosphate-dependent uptake of glutamate into Protein I-associated synaptic
vesicles. J. Biol. Chem., 258, 696-699.
Nakajima, Y., Iwakabe, H., Akazawa, C., Nawa, H., Shigemoto, R., Mizuno, N., and Nakanishi, S. (1993) Molecular
characterization of a novel retinal metabotropic glutamate receptor mGluR6 with a high agonist selectively for L-2-amino4-phosphobutyrate. J. Biol. Chem., 268, 11868-11873.
Nakanishi, S. (1992) Molecular diversity of glutamate receptors and implications for brain function. Science, 258, 597-603.
Nakanishi, S. (1994) Metabotropic glutamate receptors: synaptic transmission, modulation, and plasticity. Neuron, 13,
1031-1037.
Nakanishi, N., Schneider, N.A., and Axel, R. (1990) A family of glutamate receptor genes: evidence for the formation of
heteromultimeric receptors with distinct channel properties. Neuron, 5, 569-581.
Nawy, S. and Copenhagen, D.R. (1987) Multiple classes of glutamate receptor on depolarizing bipolar cells in retina.
Nature, 325, 56-58.
Nawy, S. and Copenhagen, D.R. (1990) Intracellular cesium separates two glutamate conductances in retinal bipolar cells
of goldfish. Vision Res., 30, 967-972.
Nawy, S. and Jahr, C.E. (1990) Suppression by glutamate of cGMP-activated conductance in retinal bipolar cells. Nature,
346, 269-271.
Nawy, S.E., Sie, A., and Copenhagen, D.R. (1989) The glutamate analog 2-amino-4-phosphobutyrate antagonizes synaptic
transmission from cones to horizontal cells in the goldfish retina. Proc. Natl. Acad. Sci., 86, 1726-1730.
Nestler, E.J. and Duman, E.S. (1994) G proteins and cyclic nucleotides in the nervous system, pp. 429-448 In Basic
Neurochemistry, 5th ed. Siegel, G.J., Agranoff, B.W., Albers, R.W., and Molinoff, P.B. (eds). Raven Press, New York.
Nomura, A., Shigemoto, R., Nakamura, Y., Okamoto, N., Mizuno, N., and Nakanishi, S. (1994) Developmentally regulated
postsynaptic localization of a metabotropic glutamate receptor in rat bipolar cells. Cell, 77, 361-369.
Nowak, L., Bregestovski, P., Ascher, P., Herbet, A., and Prochiantz, A. (1984) Magnesium gates glutamate-activated
channels in mouse central neurones. Nature, 307, 462-465.
OÕDell, T.J. and Christensen, B.N. (1989) Horizontal cells isolated from catfish retina contain two types of excitatory
amino acid receptors. J. Neurophysiol., 61, 1097-1109.
Otori, Y., Shimada, S., Tanaka, T., Ishimoto, I., Tana, Y. and Tohyama, M. (1994) Marked increase in glutamate-aspartate
transporter (GLAST/GluT-1) mRNA following transient retinal ischemia. Mol. Brain Res., 27, 310-314.
Ozawa, S. and Rossier, J. (1996) Molecular basis for functional differences of AMPA-subtype glutamate receptors. News
Physiol Soc., 11, 77-82.
Peng, Y.W., Blackstone, C.D., Huganir, R.L., and Yau, K.W. (1995) Distribution of glutamate receptor subtypes in the
vertebrate retina. Neurosci., 66, 483-497.
Picaud, S., Larsson, H.P., Wellis, D.P., Lecar, H., and Werblin, F. (1995a). Cone photoreceptors respond to their own
glutamate release in the tiger salamander. Proc. Natl. Acad. Sci., 92, 9417-9421.
Picaud, S.A., Larsson, H.P., Grant, G.B., Lecar, H., and Werblin, F.S. (1995b) Glutamate-gated chloride channel with
glutamate-transporter-like properties in cone photoreceptors of the tiger salamander. J. Neurophysiol., 74, 1760-1771.
Pin, J.P. and Bockaert, J. (1995) Get receptive to metabotropic glutamate receptors. Curr. Opin. Neurobiol., 5, 342-349.
Pin, J.P. and Duvoisin, R. (1995) Review: Neurotransmitter receptors I: The metabotropic glutamate receptors: structure
and functions. Neuropharmacol., 34, 1-26.
Pines, G., Danbolt, N.C., Bjoras, M., Zhang, Y., Bendahan, A., Eide, L., Koepsell, H., Storm-Mathisen, J., Seeberg, E., and
Kanner, B.I. (1992) Cloning and expression of a rat brain L-glutamate transporter. Nature, 360, 464-467.
Pourcho, R.G., Cai, W., and Qin, P. (1997) Glutamate receptor subunits in cat retina: light and electron microscopic
observations. Invest. Ophthal. Vis. Sci., 38, S46.
Pow, D.V. and Crook, D.R. (1996) Direct immunocytochemical evidence for the transfer of glutamine from glial cells to
neurons: use of specific antibodies directed against the D-stereoisomers of glutamate and glutamine. Neurosci., 70, 295-302.
Ransom, R.W. and Stec, N.L. (1988) Cooperative modulation of [3H}MK-801 binding to the N-Methyl-D-Aspartate
receptor-ion channel complex by L-glutamate, glycine, and polyamines. J. Neurochem., 51, 830-836.
Rauen, T., Rothstein, J.F., and Wassle, H. (1996) Differential expression of three glutamate transporter subtypes in the rat
retina. Cell Tissue Res., 286, 325-336.
Sasaki, T. and Kaneko, A. (1996) L-glutamate-induced responses in OFF-type bipolar cells of the cat retina. Vision Res.,
36, 787-795.
Saugstad, J.A., Kinzie, J.M., Mulvihill, E.R., Segerson, T.P., and Westbrook, G.L. (1994) Cloning and expression of a new
member of the L-2-amino-4-phosphobutyric acid-sensitive class of metabotropic glutamate receptors. Mol. Pharmacol., 45,
367-372.
Schultz, K. and Stell, W.K. (1996) Immunocytochemical localization of the high-affinity glutamate transporter, EAAC1, in
the retina of representative vertebrate species. Neurosci. Lett., 211, 191-194.
Schwartz, E.A. and Tachibana, M. (1990) Electrophysiology of glutamate and sodium co-transport in a glial cell of the
salamander retina. J. Physiol., 426, 43-80.
Slaughter, M.M. and Miller, R.F. (1981) 2-amino-4-phosphobutyric acid: a new pharmacological tool for retina research.
Science, 211, 182-184.
Slaughter, M.M. and Miller, R.F. (1983) The role of excitatory amino acid transmitters in the mudpuppy retina: an
analysis with kainic acid and N-methyl aspartate. J. Neurosci., 3, 1701-1711.
Stryer, L. (1988) Biochemistry, 3rd edition. W.H. Freeman and Co. New York.
Tabb, J.S. and Ueda, T. (1991) Phylogenetic studies on the synaptic vesicle glutamate transporter. J. Neurosci., 11, 18221828.
Tachibana, M. and Kaneko, A. (1988) L-glutamate-induced depolarization in solitary photoreceptors: a process that may
contribute to the interaction between photoreceptors in situ. Proc. Natl. Acad. Sci., 85, 5315-5319.
Takahashi, K.-I. and Copenhagen, D.R. (1992) APB suppresses synaptic input to retinal horizontal cells in fish: a direct
action on horizontal cells modulated by intracellular pH. J. Neurophysiol., 67, 1633-1642.
Tanabe, Y., Masu, M., Ishii, T., Shigemoto, R., and Nakanishi, S. (1992) A family of metabotropic glutamate receptors.
Neuron, 8, 169-179.
Taylor, W.R. and Wassle, H. (1995) Receptive field properties of starburst cholinergic amacrine cells in the rabbit retina.
Eur. J. Neurosci., 7, 2308-2321.
Van Haesendonck, E. and Missotten, L. (1990) Glutamate-like immunoreactivity in the retina of a marine teleost, the
dragonet. Neurosci. Lett., 111, 281-286.
Verdoorn, T.A., Burnashev, N., Monyer, H., Seeburg, P.H., and Sakmann, B. (1991) Structural determinants of ion flow
through recombinant glutamate receptor channels. Science, 252, 1715-1718.
Wenzel, A., Benke, D., Mohler, H., and Fritschy, J.-M. (1997) N-methyl-D-aspartate receptors containing the NR2D
subunit in the retina are selectively expressed in rod bipolar cells. Neuroscience, 78, 1105-1112.
Westbrook, G.L. and Mayer, M.L. (1987) Micromolar concentrations of Zn+2 antagonize NMDA and GABA responses of
hippocampal neurons. Nature, 328, 640-643.
Williams, K., Zappia, A.M., Pritchett, D.B., Shen, Y.M., and Molinoff, P.B. (1994) Sensitivity of the N-Methyl-D-Aspartate
receptor to polyamines is controlled by NR2 subunits. Mol. Pharmacol., 45, 803-809.
Yamada, K.A. and Tang, C.-M. (1993) Benzothiadiazides inhibit rapid glutamate receptor desensitization and enhance
glutamatergic synaptic currents. J. Neurosci., 13, 3904-3915.
Yang, C.-Y. (1996) Glutamate immunoreactivity in the tiger salamander retina differentiates between GABA immunoreactive and glycine-immunoreactive amacrine cells. J. Neurocytol., 25, 391-403.
Yang, C.-Y. and Yazulla, S. (1994). Glutamate-, GABA-, and GAD-immunoreactivities co-localize in bipolar cells of tiger
salamander retina. Vis. Neurosci., 11, 1193-1203.
Yang, J.H. and Wu, S.M. (1997) Characterization of glutamate transporter function in the tiger salamander retina. Vision
Res.,37, 827-838.
Yang, X.-L. and Wu, S.M. (1991) Coexistence and function of glutamate receptor subtypes in the horizontal cells of the
tiger salamander retina. Vis. Neurosci., 7, 377-382.
Yazulla, S. (1986) GABAergic neurons in the retina. Progr. Retinal Res., 5, 1-52.
Yu, W. and Miller, R.F. (1995) NBQX, an improved non-NMDA antagonist studied in retinal ganglion cells. Brain Res.,
692, 190-194.
Zhou, Z.J., Fain, G.L., and Dowling, J.E. (1993) The excitatory and inhibitory amino acid receptors on horizontal cells
isolated from the white perch retina. J. Neurophysiol., 70, 8-19.
Table 1
Metabotropic glutamate receptor groups (from Pin and Duvoisin, 1995).
group mGluR
agonist(s)
intracellular pathway
I
mGluR1, mGluR5
quisqualate,
ACPD
increase phospholipase C activity, increase cAMP levels,
increase protein kinase A activity
II
mGluR2, mGluR3
L-CCG-1,
ACPD
decrease cAMP levels
III
mGluR4, mGluR6.
mGluR7, mGluR8
L-AP4 (APB)
decrease cAMP or cGMP levels
Table 2
Glutamate receptor types on retinal neurons, electrophysiological measurements.
retinal cell type
non-NMDA
receptor
NMDA
receptor
mGluR
photoreceptors
OFF-bipolar
cells
ON-bipolar
cells
references
++ (cones)
Eliasof & Werblin,
salamander 1993; Picaud et al.,
1995b
++ (rods)
salamander Grant & Werblin, 1996
++
mudpuppy
Slaughter & Miller,
1981, 1983
++
cat
Sasaki & Kaneko, 1996
++
salamander Hensley et al., 1993
++
rat
Euler et al., 1996
++
mudpuppy
Slaughter & Miller,
1983
mudpuppy
Slaughter & Miller,
1981, 1983
white
perch
Grant & Dowling,
1995, 1996
++(APB)
salamander
Hirano & MacLeish,
1991
++(L-AP4)
salamander Hensley et al., 1993
++(AP-4)
rat
++(APB
and
cGMP)
salamander Nawy & Jahr, 1990
++(APB
and
cGMP)
cat
de la Villa et al., (1995)
white
perch
Zhou et al., 1993
mudpuppy
Slaughter & Miller,
1983
++
++(APB)
++(APB)
horizontal cells ++
++
++
++
amacrine cells
Glutamate receptor
with transporter-like species
pharmacology
salamander
++
++(AII)
++
++
++
Euler et al., 1996
Yang & Wu, 1991
catfish
O'Dell & Christensen,
1989; Eliasof & Jahr,
1997
rat
Boos et al., 1993
mudpuppy Slaughter & Miller,
1983
ganglion cells
++
++
rabbit
Massey & Miller, 1988
++
++
rat
Hartveit & Veruki,
1997
++ (transient ++
& sustained (transient
AC)
AC)
salamander
Dixon & Copenhagen,
1992
++
++
Diamond &
Copenhagen, 1993;
salamander
Mittman et al., 1990;
Hensley et al., 1993
++
++
primates
Cohen & Miller, 1994
++
++
rat
Aizenman et al., 1988
++
++
mudpuppy
Slaughter & Miller,
1983
++
++
cat
Cohen et al., 1994
++
++
rabbit
Massey & Miller, 1988;
1990
Table 3
Ionotropic glutamate receptor expression in retinal neurons and retinal layers, immunocytochemistry and in situ
hybridization.
retinal cell type
or layer
non-NMDA receptor subunits
photoreceptors
OPL
NMDA receptor subunits
species
references
GluR6/7 (single cone outer
segments)
goldfish
Peng et al., 1995
GluR1 (cone pedicles)
cat
Pourcho et al.,
1997
GluR2, GluR2/3, GluR6/7
rat
Peng et al., 1995
cat
Hartveit et al.,
1994
GluR2, GluR2/3
(photoreceptors)
goldfish
Peng et al., 1995
GluR2 (Mb cells)
goldfish
Peng et al., 1995
GluR2, GluR2/3
rat
Peng et al., 1995
NR2D (RBC)
rat
Wenzel et al.,
1997
NR1 (RBC)
rat
Hughes, 1997
rat
Hughes et al.,
1992
NR2A (punctate)
bipolar cells
GluR2 and/or GluR4
GluR2 (RBC)
horizontal cells
INL
GluR6/7
goldfish
Peng et al., 1995
GluR2/3
cat
Pourcho et al.,
1997
GluR2/3, GluR6/7
rat
Peng et al., 1995
rat
Hartveit et al.,
1994
GluR1, 2, 5 > GluR4 (outer
third), GluR1, 2, 5 (middle
third), GluR1-5 (inner third)
rat
Hughes et al.
1992
GluR1-7
rat, cat
HamassakiBritto et al.,
1993
NR2A(inner)
NR1 (homogenous), NR2A-B
KA2 (homogenous), GluR6
(inner third, patchy), NR2C rat
(inner), GluR7 (inner two thirds)
(inner two-thirds)
Brandstatter et
al., 1994
GluR1, GluR2/3, GluR6/7
rat
Peng et al., 1995
NR2A
rat, cat,
rabbit,
monkey
Hartveit et al.,
1994
NR2A-C
rat
Brandstatter et
al., 1994
GluR2/3
cat
Pourcho et al.,
1997
GluR1, GluR2/3
rat
Peng et al., 1995
ganglion cells
GluR1
rat
Peng et al., 1995
GCL
GluR2/3, GluR6/7
rat
Peng et al., 1995
GluR1-5
rat
Hughes et al.,
1992
GluR1-7
rat, cat
HamassakiBritto et al.,
1993
rat
Brandstatter et
al., 1994
rat
Peng et al., 1995
IPL
amacrine cells
GluR6
GluR6-7, KA2
Muller cells
GluR4
NR1, NR2A-C
Table 4
Metabotropic glutamate receptor expression in retinal neurons and retinal layers, immunocytochemistry and in situ
hybridization.
retinal cell type
Group 1
or layer
OPL
Group II
mGluR1alpha, mGluR5a
(RBC dendrites)
Koulen et al.,
1997
mGluR6 (RBC dendrites)
rat
Nomura et al.,
1994
mGluR8
mouse
Duvoisin et al.,
1995
mGluR6
rat
Nakajima et al.,
1993
mGluR6 (RBC), mGluR7
(BC), mGluR4,7 (AC)
rat
Hartveit et al.,
1995
rat
Peng et al., 1995
rat
Brandstatter et
al., 1996
mGluR1alpha, mGluR5a
(AC dendrites)
rat
Koulen et al.,
1997
mGluR1alpha
rat
Peng et al., 1995
cat
Pourcho et al.,
1997
rat
Peng et al., 1995
mouse
Duvoisin et al.,
1995
cat
Pourcho et al.,
1997
rat
Hartveit et al.,
1995
mGluR5 (BC, HC),
mGluR1 (AC)
mGluR2
(AC)
mGluR1alpha
mGluR7 (CBC terminals; AC
dendrites; few GC dendrites)
amacrine cells
mGluR1alpha
ganglion cells
species references
rat
INL
IPL
Group III
mGluR2/3
mGluR1alpha
GCL
mGluR8
mGluR1alpha
mGluR2/3
mGluR1
mGluR2
mGluR4, 7
Table 5
Glutamate transporters in retinal neurons and retinal layers, immunocytochemical localizations.
retinal cell
type
EAACGLAST GLT-1
1
+ (cone soma to
pedicles)
photoreceptors
OPL
++
species
reference
rabbit
Massey et al., 1997
rat
Rauen et al., 1996
++ (rod spherules >
rabbit
cone pedicles)
rat
Schultz & Stell, 1996; Rauen et
al., 1996
++ (2 types of
CBCs)
rabbit
Massey et al., 1997
++
rat
Rauen et al., 1996
turtle, salamander
Schultz & Stell, 1996
++ (DB2, flat
midget bipolar
cells)
monkey
Grunert et al., 1994
++ (diffuse)
rabbit
Massey et al., 1997
++
rat
Rauen et al., 1996
goldfish, salamander,
turtle, chicken, rat
Schultz & Stell, 1996
rat
Rauen et al., 1996
horizontal cells ++
bipolar cells
++
(faint)
++
IPL
++
++
amacrine cells ++
++
++
ganglion cells
Muller cells
Massey et al., 1997
Schultz & Stell, 1996
++
chicken, rat, goldfish,
turtle
Schultz & Stell, 1996
++
rat
Rauen et al., 1996
rat
Rauen et al., 1996; Lehre et al.,
1997; Deroiche & Rauen, 1995
++
Color Vision by Peter Gouras
1. Introduction.
Fig. 1. Geometric drawing with 15 or more colors (59
K jpeg image)
Fig. 2. Geometric drawing in black and white and shades of gray
(59 K jpeg image)
Color vision is known best by man's perception of it. It creates a unique dimension to sight that is impossible to appreciate
by any non-visual means. It depends on wavelength more than on the energy of light but it is an illusion of reality resulting
from a comparison of the responses of nerve cells in our brain. Color and all vision are in a sense illusory depending only
on messages that pass between millions of neurons that reside within the darkness of our skull. These visual messages allow
us to project ourselves into a universe that would be unknown to us without vision.
Much is known about human color vision both subjectively and quantitatively from the fields of physics, psychology and
physiology. Physiology attempts to explain color vision by the responses of neurons. This is the ultimate step in
understanding color and eventually perhaps in constructing machines that will see a similar universe of colors.
Fig. 3. The visual pathways from retina to visual cortex of the human brain (98 K jpeg image)
Linking subjective human experience with single neural responses, however, has many pitfalls. Most of the information
comes from electrophysiological recordings from neurons at the peripheral levels of vision, the retina and the lateral
geniculate nucleus of monkeys, while subjective human experience involves the entire brain (Fig. 3). There are vast areas of
the visual brain, especially cerebral cortex, that remain relatively uncharted because they are so unresponsive in
anesthetized monkeys. But it is only in these centers that the subjective experience of color occurs. Therefore, we have to
use our imagination to extrapolate from the early stages in vision at the retinal level to explain the physiology of color
vision at higher levels in our brain. This is where the major difficulty lies. It will ultimately be resolved by new techniques
that allow examination of the awake, perceiving human brain.
I start by presenting my ideas on how human color vision has evolved from a primative divariant system and go on to
consider the transmission of hue, form and contrast in parallel streams from the retina to the cerebral cortex. I suggest
neural circuitry underlying the perception of color in the retina, lateral geniculate and striate cortex and beyond.
2. The Evolution of Vision
Vision must have started with organisms detecting the difference between light and dark. Molecular genetics reveals that
this began in broad daylight with cone photoreceptors (Bowmaker, 1998), a hypothesis suggested earlier by the
comparative anatomist, Gordon Walls (1942). Under these conditions shadows must have been the main stimuli for
detecting movements and objects. A shadow depolarizes, i.e. activates, a cone, which releases a neurotransmitter that
depolarizes second order retinal neurons, bipolar cells, called off-center bipolars and horizontal cells. The reappearance of
light by movement hyperpolarizes the cones. This stops the release of the transmitter, which in turn stops, i.e.
hyperpolarizes, the off-bipolars and horizontal cells. This also disinhibits a parallel system of bipolars, called on-bipolars.
Disinhibition occurs because the same transmitter released by the cone inhibits the on- and excites the off-bipolars. Onand off- cone bipolars have different receptors for the same transmitter (see chapter on the Outer plexiform layer). This
push-pull arrangement of on and off -bipolars (Fig. 4) provides the main input to the brain about the visual universe. One
channel signals darkness; the other signals lightness.
Fig. 4. The push-pull arrangement of on- and off-bipolar cells (59 K jpeg image)
In order for cones to function under the enormous changes in ambient light in sunlit scenes, they must regulate their
sensitivity. This has evolved within the biochemistry underlying phototransduction (Fig. 5). Light absorbed by a protein
(opsin from the Greek word to see) coupled to the 11-cis isomer of retinaldehyde activates the opsin, which in turn activates
another protein, transducin. This in turn activates an enzyme, phosphodiesterase that breaks down a cyclic nucleotide to
close the cone's membrane to depolarizing ions. This chain of reactions amplifies the light signal. A shadow reverses this
process opening the membrane to depolarizing ions. The brighter the ambient light, the briefer is the phototransduction
reaction and the faster is it reversed by a shadow. This increased speed of the amplification process reduces sensitivity but
quickens the response. This is an important part of visual adaptation, which allows cones to function over a large range of
light energy. In addition, there is also negative feedback mediated by horizontal cells that antagonize the responses of
cones.
Fig. 5. The phototransduction cascade in rod or cone outer segments (59 K jpeg image)
In a world seen by only one type of cone, objects appear lighter or darker but not in color. Whether an object is light or
dark depends on a comparison between the light energy it reflects and that reflected by its background. The brighter the
background, the darker the object appears. The darker the background, the lighter the object appears. Absolute energy is
sacrificed for relative energy, which is all that is necessary for survival.
3. Color Vision
Inhabiting a world in which an organism can only distinguish light and dark without color is a handicap. Therefore early
in the evolution of vision, color must have appeared. For this, two different types of cones were necessary, one responding
best to one part and a second responding best to another part of the visible spectrum, i.e. sunlight. By this means the brain
can compare two signals to distinguish color. Again the brain senses relative rather than absolute differences, in this case of
wavelengths rather than energies of light.
Fig. 6. The wavelength sensitivities of the different photoreceptor types in the vertebrate retina. Blue-violet and yellowgreen wavelengths maximally stimulate the two cone types in the divariant mammalian retina (59 K jpeg image)
A second cone system evolved that was most sensitive to the short wavelength region of the visible spectrum, the region we
call bluish-violet (Fig. 6). The output of these cones could be compared with the earlier long wave cones that evolved to
detect light and dark, and are most sensitive to the yellow-green part of the spectrum (Fig. 6). The spectral sensitivity of a
cone is determined by the absorption spectrum of its opsin. The further apart these absorption spectra are, the greater is
the potential color contrast (see later Fig. 12). Why not use a red rather than a yellow-green sensitive opsin? There are
diminishing returns in using red opsins, probably due to their lower quantal energies. Why not use an ultra-violet opsin?
Ultra-violet light is strongly absorbed by the cornea and lens before it reaches the retina and exhibits much chromatic
aberration. If these structures are comparatively small as in mice, an ultra-violet cone becomes more tractable.
With two different spectral images of an object and/or its background, the brain can derive differences that are impossible
to detect with only one spectral image. Now the brain can distinguish objects, which are not just lighter or darker than
their background but have as new attribute, color. An object is uniquely white, gray or black if the two different cone
mechanisms are affected equally by the reflected energy of the object and its background. If an inequality exists between
the two cone mechanisms, detecting the light reflected by either the object or its background, the brain will see color,
making the object or its background appear different than white, gray or black. Objects can have the same brightness as
their backgrounds but stand out because of this inequality. This is a powerful way to see objects in a world where most
things reflect about the same light as their background.
Nature uses these two cone mechanisms differently. The long wave cones are the sole determinant of light and dark. The
short wave cones are only used for color contrast. This strategy minimizes chromatic aberration. For this reason there are
about ten times as many long than short wave sensitive cones in most retinas. In the human central fovea there are very
few short wave cones and borders are detected by brightness alone.
4. Chromatic versus Achromatic Contrast
To distinguish light and dark as well as color, two parallel neural circuits are used in visual cortex. One depends only on
long wave cones; it detects differences that depend on light energy. This system is responsible for distinguishing light and
dark, i.e. achromatic contrast. The second depends on both long and short wave cones; it compares the response of both
cone systems to the same stimulus. This system is responsible for chromatic contrast. Together both systems are
responsible for color vision.
To distinguish light from dark, neighboring groups of long wave cones are compared for borders of energy contrast; these
borders are assembled in the brain as an object (Fig. 7, left). This comparison can involve single neighboring cones or rows
of cones at the minimum angle of visual resolution. In the fovea this is a micron, about 1/200th of a degree.
Fig. 7. Neural circuits for Achromatic contrast and Chromatic contrast (59 K jpeg image)
For chromatic contrast, the brain compares the responses of a group of long wave cones with a group of short wave cones
in the same retinal area by taking the difference between them (Fig. 7, right). It would be ambiguous to compare only one
cone with a neighboring cone because a difference between the two could be caused by energy rather than wavelength
gradients. In order to prevent this ambiguity, groups of cones are compared. Such a group of cones can be considered a
unit area of chromatic space to distinguish it from a unit area of achromatic space, which in the fovea is a single cone.
Therefore achromatic space is more finely divided than chromatic space (Mullen, 1985).
For spatial contrast, the long and short wave cone difference is compared with a difference signal derived from
neighboring groups of cones. This creates borders of chromatic (wavelength) contrast. The brain combines borders of
chromatic and achromatic contrast to detect objects.
5. Divariant Mammalian Color Vision
About 2% of human males have only two types of cones; long and short wave sensitive. This is a two-variable, i.e.
divariant, color vision system similar to many other mammals, such as dogs and cats.
Both the achromatic and chromatic contrast signals are transmitted by long wave cones via the same channels of bipolar
and ganglion cells (Fig. 8, left). Small, slowly conducting bipolar and ganglion cells transmit tonic signals of the long wave
cones to the brain. One channel is excited by an increment of light absorption by long wave cones; this is an on-channel.
Another channel is excited by a decrement of light absorption by long wave cones; this is an off-channel. In the brain both
signals are processed by two separate circuits, one of which extracts achromatic and the other chromatic contrast. For
achromatic contrast, signals of neighboring tonic long wave cone channels are compared. For chromatic contrast signals
from groups of long wave cone channels are compared with those of short wave cone channels.
Fig. 8. Neural circuits for the tonic signals of the long wave cones (59 K jpeg image)
The short wave cones transmit their signals by another tonic system of bipolar and ganglion cells (Fig. 8, right). In this case
there are only short wave cone on-channels, presumably because these cones are only involved in chromatic and not in
achromatic contrast. In addition these ganglion cells receive and excitatory input from long wave cone off-bipolars. This
increases their sensitivity to successive chromatic contrast, i.e. short wave following long wave light.
For chromatic contrast the brain makes two comparisons. It compares the short and long wave cone signals in the same
retinal area and then compares this with neighboring areas to detect borders of chromatic contrast.
There is a separate fast, phasic system of larger bipolars and ganglion cells that also transmits signals
from long wave cones to the brain (Fig. 9). This system is not as highly developed in the fovea as the tonic
system and has a lower spatial resolution. It appears to play no role in color vision. It has a high
sensitivity to achromatic contrast (Kaplan and Shapley, 1986) and is sensitive to slow movements
(unpublished results). Evidence exists that it contributes to luminance (Lee et al, 1990).
Fig. 9. Neural circuits for the phasic signals of the long wave cones (59 K jpeg image)
6. Simultaneous Contrast
An object's achromatic contrast and brightness depends entirely on the difference between the light it reflects and the light
reflected by its surround. Color also depends on simultaneous contrast of wavelength rather than energy contrast. Edwin
Land demonstrated the importance of simultaneous contrast in color vision by showing that color depends on the light
reflected from the surround of an object. He proposed a model in which the comparison of one cone system with another,
needed to arrive at a decision for color, occurs after an object's brightness has been established separately for each cone
mechanism. He used the term lightness to describe the brightness of such a monochrome (monocone) image (Land, 1986).
Fig.10. The retinex model of Edwin Land (59 K jpeg image)
Figure 10 illustrates the reasoning behind his retinex (retino-cortex) model. Two projectors cast light on a screen. One
transmits white light; the other transmits only long wavelength light. A shadow (arrow) is cast on the screen by blocking
the long wave projector (Fig. 10A left). The illumination seen by the two cone systems is shown on the right. The short
wave cones see 100% of the white light but 0% of the long wave light. The long wave system sees 100% of the white light
and 100% of the long wave light except in the area of the shadow where it sees about 1% of the scattered light. When both
projectors are on, the long wave cones detect about 101% of the light from the shadow and 200% from its surround.
Therefore the shadow is relatively dark to the long wave cones (Fig. 10A). The retinal area of the shadow seen by the short
wave cones absorbs the same light as its surround; therefore it is not dark to these cones. Because the shadow is darker to
the long than the short wave cone system, it has a bluish color. This occurs even though more light energy is absorbed from
the shadow by the long than the short wave cones.
It is the relative long wavelength gradient of the shadow that determines its color. This decrease in the lightness image of
the long wave cones compared to the short wave cones makes the shadow of the arrow, blue (Fig. 10B). Land's algorithm,
which computes the lightness of an object for each cone mechanism before comparing these values for color predicts the
appearance of colors in a natural scene (Vitek, 1997).
Accordingly, the comparison of the short and long wave cone systems, necessary for color vision, should occur after the
normalization for lightness has been established within each cone system. This requires independent processing of the tonic
long and short wave cone images before they are compared. In divariant subjects, the long wave cone system is absolutely
independent of the short wave cones and therefore satisfies this requirement (Fig.8). The short wave cone system transmits
a signal that is relatively independent of the long wave cone system (Fig. 8). It receives input from long wave cone offbipolars but this only augments its response to short wave light.
How are these separate cone images normalized? Figure 11 provides a reasonable scheme. It is based on so called doubleopponent neurons, found in the visual cortex of primates (Michael, 1977). Double-opponent neurons have spatial
antagonism between the same cone mechanism mediating the center and surround of their receptive field, something not
seen strongly at the level of the retina or geniculate. In this model, long wave cones, responding to the object, excite the
neuron and long wave cones, responding to its background, inhibit the neuron. This inhibition normalizes the responses
over space because it creates a difference between the responses of different retinal areas, eliminating absolute values
(Ratliff, 1960).
After normalization chromatic contrast is achieved by two comparisons. One occurs between neurons reflecting the
lightness images of these two cone systems in the same area of space, antagonistically interacting with each other to create
neurons responsive to the difference between the two. A second comparison involves this difference signal being compared
with those of neighboring areas of visual space to detect simultaneous chromatic contrast.
Fig.11A shows how a neuron responding to yellow is formed. B. How a neurons responding to blue is formed. C. System of
neurons responding to white and D. system of neurons responding to black (59 K jpeg image)
Figure 11A suggests how a neuron responding to yellow could be formed. It receives an excitatory, normalized input from
the long wave cone on- system and an inhibitory input from a normalized short wave on-system. Figure 11B shows a
neuron that responds only to blue. It receives an excitatory, normalized input from the short-wave on-system and a
normalized, inhibitory input from the long wave cone on-system. The long and the short wave cone systems are compared
by subtraction. One difference creates a neuron that is excited by ³yellow²(Fig. 11A). The converse creates a neuron excited
by blue (Fig. 11B). These neurons are most sensitive to simultaneous color contrast, the former to yellow on a blue
background, the latter to blue on a yellow background. These responses resist changes in the spectral composition of the
illuminant, i.e. they show color constancy. They are sensitive to wavelength rather than energy contrast.
White, gray or black is seen when there is no chromatic (wavelength) contrast, i.e. as in a black and white photograph (Fig.
2). The yellow and blue neurons are silent. Another set of neurons is responding. Pure white requires both the long wave
and the short wave cone systems to be responding equally. Therefore the long wave on- and the short wave on-systems
must both be excited. Black requires both of these systems to be silent and the long wave cone off-system to be excited.
There must be separate systems of neurons responding to white (Fig. 11C) and black (Fig. 11D). If both are excited
simultaneously, the sensation must be gray.
7. Trivariant Human Color Vision
Normal human color vision depends on three not two cone mechanisms. This adds an additional dimension to color vision
creating reds and greens. To do this nature splits the long wave system into two similar systems with slightly different
spectral sensitivities with relatively similar opsins (Fig. 12) (Nathans et al., 1986) but the same neural machinery duplicated
in parallel circuits. One cone opsin is most sensitive to yellow-green and the other to yellow-red. This splits the brightest
and yellow part of the visible spectrum into two color bands, one green and the other red. This red-green system works in
parallel with that for blue-yellow.
Fig.12. The closely related molecular structure of the cone opsins. The blue-cone opsin compared with rhodopsin. The blue
cone opsin compared with the green opsin and the minimal difference between the red and green cone opsins. The pink
filled circles represent amino acid substitutions between these molecules. The open circles indicate identical amino acids.
Adapted from Nathans et al., 1986 (59 K jpeg image)
The splitting of the long wave cone channel into two creates four longer wave channels in the tonic system, two for reddishyellow and two for greenish-yellow sensitive on- and off-signals (Fig. 13A). The phasic system, which plays no role in color
vision mixes both cones in the same on- or off-bipolar cell and retains its original two channels (Figure 13B). In visual
cortex, the signals from the tonic reddish-yellow or long wave sensitive (L-) cone and greenish-yellow or middle wave
sensitive (M-) cone channels are again used to detect achromatic (energy) and chromatic (wavelength) contrast (Fig. 14A
and B).
Fig. 13. The different circuits for Tonic and Phasic
pathways through the retina (59 K jpeg image)
Fig. 14. The signals from the tonic reddish-yellow or long wave
sensitive (L-) cone and greenish-yellow or middle wave sensitive
(M-) cone channels are used to detect A. achromatic and B.
chromatic (wavelength) contrast in the cortex (59 K jpeg image)
Trivariance allows the mixing of these parallel red-green and blue-yellow systems to produce non-spectral colors of
magenta (red and blue) or cyan (green and blue) (Fig. 15).
Fig.15. Trivariance of the primate fovea compared with divariance of the normal mammalian retina (59 K jpeg image)
Trivariance introduces a second comparison of cone signals, in this case between the two long wave cone systems to create
red-green contrast. It occurs in parallel with the divariant comparison of short and long wave cones; in this case both long
wave cones are compared to the short wave cones for blue-yellow contrast. If there is a significant difference between the
signals of the two long wave cone systems, there will be a hue difference of red or green. If there is no difference between
the signals of the two long wave cone systems, the detector will default to the divariant comparison. If there is no difference
for the divariant comparison, the signal will appear white, gray or black. It is important to realize that the absorption
spectrum of the reddish-yellow cone opsin is not only more sensitive to long wave (red) light but also more sensitive to short
wavelength (violet) light than the greenish-yellow cone opsin This gives a reddish color to short wavelengths.
8. Hue, Saturation and Brightness
Color is complex because it depends on more than wavelength contrasts alone (Kaiser & Boynton, 1996). This was
appreciated in the 19th century by psychologists who defined the terms hue, saturation and brightness to define color. Hue
defines the wavelength contrast aspect of color, such as yellow or blue and red or green. Saturation defines the mixing of
hue with white, gray or black. A saturated color has strong hue with little or no white, i.e. blood red. An unsaturated color
has its hue washed away by white, i.e. pink. It is reasonable to assume that the independent responsiveness of parallel
circuits is responsible for the mixing of hue with white, black or gray. A third quality of color is brightness, which is less
obvious than the other two. Yellow and white tend to be bright and blue and black tend to be dark. This difference appears
to track the on- and off-systems of the long wave cones. Whenever the on-system is responsive, yellows and whites are likely
to be perceived and they tend to be bright. Whenever the off-system is active, blacks and blues are likely to be perceived
and they tend to be dark. In addition other qualities of the image such as texture or gloss contribute to color as in gold and
silver.
The Opponent Color Theory of the 19th century physiologist Ewald Hering (Hering, 1964; Hurvich, 1981) derived by the
analysis of subjective human color vision is in general correct, although the idea of opponent colors was described earlier
by Goethe and Schoepenhauer. Certain colors are not perceived together, i.e. they do not mix. We never see bluish-yellows
or reddish-greens. This is consonant with the neural comparisons described previously. The yellow detector is always
inactive when the blue detector is active and vice versa. A similar situation occurs for the neurons responding to red or
green.
Hering's theory was brilliant but it was proposed when little was known about the anatomy and physiology of the retina.
Hering and his school (Ladd-Franklin, 1929) considered that the antagonism between colors occurred in the retina. We
now know that color vision is established not in the retina but in visual cortex. The arrangement resembles stereoscopic
vision, which is also established in visual cortex, where common signals from each eye are used by different neural circuits
to sample objects at different distances in space.
Early recordings of the responses of single neurons in primate retina and geniculate nucleus revealed cells excited by red
and inhibited by green light or vice versa (Fig. 17) (Wiesel and Hubel, 1966; Gouras, 1968). These were thought to be the
red/green opponent color channel of Hering. Cells were also detected that were excited by blue and inhibited by yellow
light or the converse (Fig. 17). These were thought to be the blue/yellow channel of Hering. In addition there were cells
which were excited or inhibited by all wavelengths. These were thought to be Hering's white/black channel (DeValois et al.,
1966). Now almost half a century later, this view appears to be a misconception. We shall here consider why.
10. Hering Red-Green Channel in the Retina
The cells excited by red and inhibited by green light or the converse, which were considered to be Hering's red-green
channel, are comprised of four different types of cells. Two sets are on- and two sets are off-center cells. One set has L-cone
on- or off- centers and another has M-cone on- or off-centers. The cells with L-cone centers receive antagonistic signals
from M-cones in the surround of their receptive field. The cells with M-cone centers receive antagonistic signals from Lcones in the surround of their receptive field. The strength of this cone-cone antagonism varies considerably.
Fig. 17. Color opponent receptive field structure of
primate tonic ganglion cells (59 K jpeg image)
Fig. 18. Electrophysiological recordings from color and spatially
opponent midget ganglion cell in the monkey retina (59 K jpeg
image)
The first problem with these cells being Hering's red-green opponent channel is that the opponency depends on the
geometry of stimulation. Large spots resemble an opponent channel but small spots centered on their receptive field do not,
i.e. there is no opponency. The antagonistic surround signal requires more spatial summation than the center mechanism
(Fig. 18). A second problem is that a cell with a green sensitive off-center is supposed to be contributing to the sensation of
red as much as a cell with a red sensitive on-center. These two cells, which are logically transmitting opposite signals about
local brightness, seem inappropriately labeled as a single Hering red-green channel.
A third problem arises when one compares the excitation and inhibition these cells receive from the opposing cone
mechanisms. Only a fraction are actually inhibited by red and excited by green light or the converse. Many are excited
more by yellow or white light than other colors, which is not really a Hering red-green channel.
Fig.19. The wiring of red and green color and spatially opponent midget ganglion cells of the monkey fovea (59 K jpeg
image)
There is additional complexity to the L- and M- tonic cone system. It is generally agreed that these cells comprise the
midget ganglion cells of the fovea. These retinal ganglion cells receive a direct input from a midget bipolar cell, which
receives its input from a single L- or M-cone. The cone antagonism is thought to come indirectly through horizontal and
amacrine cells (Fig. 19). There is evidence that the cone antagonism mediated by horizontal cells comes from both L- and
M-cones (Dacey, 1996), which is also inconsistent with a Hering red-green opponent channel.
A rival view discounts any role of midget ganglion cells in color vision (Rodieck, 1998; Dacey, 1996). This hypothesis rests
on evidence of the existence of a small number of geniculate cells that have coextensive receptive fields with L-cones
exciting and M-cones inhibiting or the converse (Wiesel & Hubel, 1966). This result has been difficult to confirm. These
cells lack the geometry problem mentioned previously because the red-green opponency does not vary with stimulus size.
Coextensive L- and M-cone opponent cells have also been reported to be in the intercalated layers (koniocellular layers) of
the geniculate and to project to the areas of visual cortex where double opponent color cells are located (see later figures
25, 26 and 27). These results also need confirmation.
Some support for this hypothesis comes from recordings in the peripheral retina of midget-like ganglion cells, where Land M- cones are synergistic rather than antagonistic (Dacey and Lee, 1997). This result has been taken to imply that the
midget system plays no role in color vision. Another interpretation is that the antagonistic organization of midget ganglion
cells is lost outside the fovea because peripheral 'midgets' are not truly midget ganglion cells at all: they receive more than
one midget bipolar input and multiple cone inputs (Kolb et al., 1998). So trivariance, may be lost in the peripheral retina.
I believe that all L- and M- tonic cells contribute to color vision but they are not the red-green opponent channels of
Hering. I suggest that the antagonism these cells show between L-and M- cone mechanisms is a spectral filter, narrowing
the spectral band to which they respond best. This resembles oil droplets located in the cones of certain diurnal vertebrates
like birds, reptiles (Fig. 20) and fishes. Oil droplets narrow the action spectrum of the cones, increasing color contrast.
Long wave cones become longer wave selective; middle wavelength cones become more middle wavelength selective. This
phenomenon makes the monochrome retinex image even more monochrome.
Fig. 20. Wholemount view of the turtle retina showing the characteristic oil droplets within the different spectral types of
cones (59 K jpeg image)
11. Hering Blue-Yellow Channel in the Retina
Some cells excited by blue and inhibited by yellow light or the converse were considered to be Hering's blue-yellow
channel. This view is also being challenged nowadays.
The first problem is that most of these cells are excited by light stimulation of short wave cones, either as blue or white
light. The Hering blue-yellow channel should not be responsive to white light. The excitation these cells receive from L- and
M- off bipolars contributes to successive contrast but exerts little inhibition on the short wave cone signals.
A second problem is their polarity. There are many more excited than inhibited by short wave cones. Malpeli and Schiller
(1978) and Gouras and Zrenner (1981) have concluded that retinal and geniculate cells inhibited by short wave cones do
not exist. This view is contested by Lee et al. (1987) who have tried carefully to detect cells inhibited by short wave cones.
This is not an easy task because cells in the tonic L-and M-cone system can be inhibited by blue and excited by yellow light.
In order to eliminate this possibility, Lee et al. (1987) used stimuli, which changed along a tritanopic axis of color space, to
which only short wave cones respond. They found cells inhibited by this stimulus. However, macular pigments or other
factors could cause their stimuli to miss the tritanopic axis of primate color space thus weakening their conclusion.
Fig. 21. Intracellular responses of the blue-yellow ganglion cell of the primate retina (Dacey and Lee., 1994) (59 K jpeg
image)
Anatomy has revealed that the short wave cone excitatory signal uses a unique bistratified retinal ganglion cell organized
to be excited by short wave cones absorbing light and excited by off-responses of longer wave cones (Fig. 21); the converse
has not been found. The three dimensional structure of the short wave cone synaptic pedicle reveals a synaptic
organization that resembles rod spherules more than longer wave cone pedicles (see chapter on S-cone pathways). The Scone bipolar dendrites have contacts with S-cones resembling those of on-bipolars of rods. The existence of short wave cone
specific off-bipolars is therefore questionable (Kolb et al , 1997).
Electroretinography also suggests that in contrast to the L- and M-cones, there is no evidence of a short wave cone offbipolar response (Evers & Gouras, 1986).
The short wave on-channel in primate retina is briefly inhibited when a long wave field is turned off, making a blue flash
transiently disappear to an observer. This phenomenon was discovered psychophysically by Stiles (1949) and confirmed by
Mollon and Polden (1977). This phenomenon is also seen in retinal ganglion cells mediating the excitatory signal of short
wave cones (Gouras, 1968), providing a unique psychological marker for the human short wave cone system. A yellow flash
does not disappear when a blue adapting field is turned off, which might be expected if there were symmetrical short wave
inhibitory-long wave excitory cells. This too supports the absence of a short wave cone off-channel.
Short wave cones have little impact on brightness but have a strong influence on color. If there were short wave cone offbipolars, they should be logically related to signaling darkness. This would conflict with the L- and M-cones, which signal
darkness when their off-bipolar system goes off. In the presence of yellow light the short wave cone off-bipolars would go
off when the long wave cone on-bipolars go on. On this reasoning short wave cone off- channels are inappropriate.
12. Hering White-Black Channel in the Retina
Although these sensations are opposite in nature, they are not opponent as blue and yellow or red and green colors are. The
intermediary sensation of gray is a mixture of black and white. The reason for this is that no antagonism occurs between
cone mechanisms for the establishment of white and black. These sensations depend on antagonism in space but not among
cones. It is not a wavelength but an energy comparison. White or gray depends on all cone mechanisms absorbing light and
for pure white or gray this absorption rate must be relatively equal. If the short wave channel is not active, the whites and
grays become yellowish, greenish or reddish.
The early recordings of single retinal and geniculate neurons in monkeys revealed a subset of cells that were either excited
or inhibited by all wavelengths. These were considered to represent the white and black channels of Hering. At that time,
there was no distinction between tonic (parvo) and phasic (magno) systems. The idea that these cells reflect the perception
of white and black is incorrect because they respond to all colors, not just white or black. The perception of white and
black occurs in the visual cortex, where simultaneous contrast occurs. I suggest that pure white occurs when the
normalized images of the three cone on-systems are equal for the object. Pure black occurs when the normalized L-and Mcone off -systems are equally excited and the short wave cone on-system is silent in the representation of the object in the
cortex.
13. Retinal Interneurons
The horizontal and amacrine cells represent laterally interacting elements in the retina. In general they are inhibitory
(antagonistic) in their neural interactions. There are exceptions, notably the rod amacrine cell, which transmits rod signals
to bipolars and ganglion cells (see chapter on circuitry for rod signals).
Among primate horizontal cells there are at least two major classes. One class receives its input overwhelmingly from Land M-cones. A second class receives its input from all three cones but much more from short wave ones (Fig. 22) (Ahnelt
and Kolb, 1994; Dacey, 1996). It is thought that horizontal cells feedback antagonistically on cones. The specificity of the
feedback is not clearly defined. It is possible that the horizontal cells receiving inputs from short wave cones only exert
feedback on to short wave cones, even though they receive inputs from L- and M-cones. I favor this hypothesis because one
does not see any input from short wave cones in ganglion cells receiving inputs from L- and M-cones. If the horizontal cells
receiving inputs from short wave cones were to feedback on to L- and M-cones, short wave cone inputs would be found in
all retinal ganglion cells, which is not the case.
Fig. 22. The cone and rod inputs to the three horizontal cell types of the primate retina (Ahnelt and Kolb, 1994) (39 K jpeg
image)
What is the role of horizontal cells? It would seem that the negative feedback they exert on the cones is to control
overdriving of the cones by large energy gradients in both space and time. Over-stimulation of the cones would be curtailed
and response speed increased. Spatial contrast could also be facilitated (Ratliff, 1960). The horizontal cell feedback is only
brought into action by strong stimuli that affect large groups of neighboring cones. This could also enhance spectral
contrast. The depolarization that yellow light would exert on S-cones through horizontal cells could enhance any
subsequent hyperpolarization produced by short wave light. This would augment responses to short wave light on long
wave backgrounds and facilitate successive color contrast.
The amacrine cells are less understood than horizontal cells. It is reasonable to assume that most transmit antagonistic
interactions to bipolar and ganglion cells. The amacrine cell interaction occurs after the on- and off- systems of bipolar
cells are established. This allows separate channels of antagonism to be mediated by on- and off- amacrine cells. Their role
would be similar to horizontal cells but at the inner plexiform layer (Fig. 23).
Fig. 23. The midget bipolar to ganglion cell pathways and proposed horizontal and amacrine cells that could form
antagonistic surrounds in the primate retina (39 K jpeg image)
Another role of the amacrine cell system is to help establish the functional differences in the tonic and phasic ganglion cell
systems. The complete circuitry of these two systems is not known. It is likely that the phasic system has separate on- and
off- bipolars that transmit signals from cones to the ganglion cell layer (Fig.13) because midget cone bipolars synapse only
on midget ganglion cells and not on other ganglion cells (Kolb, 1994; Boycott and Wassle,1999). Therefore, another system
of L- and M-cone bipolars, presumably diffuse cone bipolar types, (see chapter on cone pathways through the retina) must
transmit cone signals to phasic ganglion cells. It would be at these bipolars and/or ganglion cells that amacrine cells
establish the phasicity of the phasic ganglion cells (Werblin, 1991; Slaughter et al., 1995; Cook and McReynolds, 1998). Land M-cone signals reach these ganglion cells faster than they reach the tonic ganglion cells (Gouras, 1968), which also
suggests a separate bipolar system.
14. The Role of Phasic Ganglion Cells
The first recordings from cells in the magno-cellular layers of the lateral geniculate of monkeys were by Wiesel and Hubel
(1966). The sample of cells they encountered in these layers was relatively small. They described cells that were tonically
inhibited by red light, a phenomenon not found in their more extensive sampling of the parvo-cellular layers.
Two different classes of ganglion cells occur next to each other in monkey retina, one phasic, the other tonic (Gouras, 1968;
DeMonasterio and Gouras, 1975). These differences are striking in the retina where these two different types of cells can be
recorded from simultaneously. Antidromic driving showed that phasic cells have faster conduction velocities than tonic
ones and therefore were presumably larger cells, suggesting a link with the magno- and parvo-cellular layers of the
geniculate, respectively. The antidromic field potential of these two cell groups revealed that the tonic cell system was
concentrated around the fovea while the phasic system was evident perifoveally and peripherally (Gouras, 1969).
Fig. 24. Electrophysiological recordings from phasic ganglion cells in the monkey perifovea (DeMonasterio and Gouras,
1975) (59 K jpeg image)
It is difficult to know what visual sensation the phasic system mediates. It has been suggested that it is responsible for
luminance (Lee et al., 1990). Luminance is an additive quality, which has an action spectrum reflecting the combined L-and
M- cone systems but not short wave cones. It has also been suggested that the phasic system detects movement. One of the
reasons for this hypothesis is that the phasic ganglion cell system projects to the magno-cellular layers of the lateral
geniculate nucleus, which in turn projects through striate cortex to a visual area MT, where cells sensitive to movement
and the direction of movement seem to be found. This idea is not completely accepted. It is also possible that the phasic
system mediates the signal for the optokinetic reflex, responding to very slow retinal movements (unpublished
observations).
The phasic system is not involved in color vision because it synergistically mixes the signals of L- and M-cones, which is not
what one expects from a system involved in color vision. It is possible that the signal of the phasic system is used for blueyellow contrast. However, I doubt this hypothesis because 1) the retinal distribution of the phasic ganglion cells is not in
register with that of the tonic system and 2) their latencies and conduction velocities are out of phase with those of the tonic
system.
Why should one visual pathway be phasic and the other tonic? This is an intriguing question that awaits more research. It
has been suggested that the foveally oriented tonic pathway plays a more dominant role in conscious perception in which
tonic responses may be an advantage (Martinez-Conde et al., 1999).
15. The Lateral Geniculate Nucleus
The lateral geniculate nucleus (see Fig. 3) forms the main stream of visual information to the cerebral cortex. It is a
transfer center that disentangles the various retinal subsystems serving the contralateral visual fields and organizes their
projections to striate cortex.
Fig. 25. The projections of the major ganglion cell
classes of the retina to the layers of the lateral
geniculate nucleus in the primate (59 K jpeg image)
Fig. 26. Histological section through the primate lateral
geniculate nucleus (LGN) to show the layering of the neurons
into 4 parvocellular layers, 2 magnocellular layers and 6
koniocellular layers (59 K jpeg image)
The tonic system, carrying cone specific channels for both high visual resolution and color vision, is confined to the parvocellular layers (Fig. 25). The phasic system is confined to the magno-cellular layers (Fig. 25). The signals from each eye are
kept separate in order to combine them appropriately for stereoscopic vision, where different combinations reflect
different depth planes. Similarly on-cells are separated from off-cells and cone specific responses are kept separate for
color vision. There are non-retinal inputs to the lateral geniculate nucleus that must modulate the flow of information but
they are poorly understood. They may play a role in attention and sleep.
16. Color Vision in Visual Cortex
The cerebral cortex mediates conscious perception. In striate cortex there are local zones called blobs (Fig. 27) that contain
cells that exhibit double-opponent behavior (Michael, 1977; Livingstone and Hubel, 1988). We assume double-opponency is
an essential stage in color vision. Double-opponency is not introduced at an earlier stage because a commitment to color
contrast cannot be made until the achromatic information is extracted from the tonic L- and M-cone input channels.
Fig. 27. Diagram of a slab of striate cortex (V1) of primate brain to show the composition of a hypercolumn. A
hypercolumn consists of two ocular dominace columns (one from each eye) each containing stacks of orientation columns.
A blob is a cylinder of cells running from I to IVB which receives direct input from blue/yellow cells of the koniocellular
layers of the LGN, and the color-opponent red and green cells of the parvocellular layers of the LGN. The latter
projections are secondary to the first synapses in layer IVCb. Magnocellular cells from the LGN project to layer IVCa (59
K jpeg image)
Achromatic and chromatic information is considered to be multiplexed in the tonic L- and M-cone system, which is
demultiplexed before chromatic contrast is established. By demultiplexing is meant that chromatic information is
transmitted to different neural circuits than those for achromatic information (Fig. 27). The L-and M-cone on- and offchannels are used synergistically for achromatic contrast detectors. These same channels are used antagonistically for
chromatic contrast detectors. Achromatic contrast involves larger populations of neurons located outside the smaller blob
areas (Fig. 27, achromatic and oriented).
There is no multiplexing for the short wave channel because it is totally committed to color. Thus this channel goes directly
from LGN to the blobs (Fig. 27). Double-opponency involving the short wave cone system also depends on the
demultiplexing of the longer wave cone system's signal before a comparison is made for chromatic contrast.
We assume that chromatic contrast begins with double-opponent cells (Fig. 11). Double-opponency establishes wavelength
contrast independently of brightness contrast. These two forms of contrast become independent neural entities in
establishing borders of contrast.
Orientation selectivity, undoubtedly essential for form vision, could be based on either or both of these forms of contrast.
The greater spatial resolution of achromatic contrast appears to involve more orientation selective cells in visual cortex
than color contrast does.
17. Color Vision beyond Striate Cortex
Knowledge of the physiology of color vision beyond striate cortex is sketchy because of the difficulty in exciting cortical
cells in anesthetized monkeys. Post striate visual cortex is composed of a number of separate areas. One area, called MT,
appears to receive its major input from the magno-system. Several other areas, called visual areas 2, 3 and 4 receive their
input from the parvo-system. The role of these different areas is unclear (Schiller and Lee, 1991). Color selective cells have
been found in areas 1, 2, 3 and 4 (Kruger and Gouras, 1979), although Zeki (1993) has maintained that they are much more
numerous in visual area 4 (V4).
Using three projectors to control the spectral reflectance of objects in a Mondrian-like display, Zeki (1993) reported a
major difference between striate cortex and visual area 4. Spectrally selective cells in striate cortex of an anesthetized
monkey responded to the energies reflected from the objects and not to their color. In other words, objects with different
colors but reflecting identical energies from their surface evoked the same response when presented to such neurons. On
the other hand, spectrally selective cells in area V4 responded to the colors and not to the energies. This implies that color
is not established in striate cortex but at a later stage in vision.
Zeki has raised the interesting hypothesis that V4 is the visual center for color and is not represented in a retinotopic but in
a chromatic coordinate system. An object's shape would be defined in area V1 (striate cortex) and perhaps V2 where the
anatomy reflects a retinotopic plan, and its color would be defined in V4 following a chromatic plan. In V4 colors would be
distributed in an orderly way over the structure somewhat like a chromaticity diagram (Fig. 27). This is a radical view of
cortical processing that needs more research. A problem with this hypothesis is how a neural response that represents an
object in one cortical area can be linked with its color response in another area. Color is complex depending not only on
hue, defined by the chromaticity diagram but also by achromatic cues such as shadowing and texture. Another view is that
chromatic contrast detectors are ubiquitous in all visual areas, providing parallel cues to borders with achromatic contrast
detectors. The remapping of visual space, occurring in these multiple visual areas may increase the universe of forms and
objects distinguishable (Fig. 28).
Fig. 27. The CIE chromaticity diagram which is a standard
method for specifying colored lights or light reflected from
materials (from Normann et al., 1991) (59 K jpeg image)
Fig. 28. Proposed cortical areas and interactions between
them for processing of color vision (59 K jpeg image)
The Commision Internationale d'Elairage (CIE) chromaticity diagram (Figure 27) defines human trivariant color
experience in a quantitative way, which allows standards for color comparisons worldwide. It is defined by three spectral
variables, which can be combined to mimic any color. The values of the three standards have been normalized so that they
always add up to 1.0. In this way the color diagram can be plotted in two dimensions, those of the long (red) and middle
(green) wave standards. What does not equal 1.0 on the diagram represents the short wave standard. In the middle of the
diagram, where the three standards are all 0.33, the color is white (gray or black). Moving up the diagram makes the color
green, right makes the color red and down makes it blue. The value 1.0 can never be reached because the absorption
spectra of the three cone opsins overlap so much that the standards stimulate more than one cone mechanism. Therefore,
all colors are to some extent desaturated. Perhaps if one could find a way to stimulate only one class of cones, more
saturated colors might be perceived. Normal humans can perceive about a million different colors but this number depends
on the right conditions. The illumination must be bright and the size of the color stimulus must be large, at least 20 degrees
of visual angle to appreciate such a large universe of colors. Why very large stimuli create a much greater palette of colors
must depend on spatial summation in visual cortex (Figure 28).
18. Color and Form
One of the most impressive facts about the physiology of visual cortex is the relatively small proportion of cells that have
any striking wavelength selectivity. This is in marked contrast to the retino-geniculate pathway where many cells show
wavelength selectivity. This suggests that much of the neural machinery in visual cortex is used for pattern recognition
rather than color vision, and that wavelength selectivity plays only a minor role in the response repertoire of cortical visual
neurons. Evidently the processing of a black and white (achromatic) image requires almost as much neural power as the
processing of a color image: perhaps like a color television, where much more information is transmitted for the pattern
than for the color of the image.
Just where color enters into pattern recognition will require a better understanding of the latter. It would seem that objects
are identified by connected groups of orientation selective neurons having appropriate contrasts (Marr, 1982) and these
objects are reinforced by their structural stability with movement in space. In this, light, dark and shading have
considerable impact on contour stability and structure as evidenced by the pattern recognition possible in black and white
photographs. Color adds an important but minor frill to this complex neural construct but because of its limited
dimensionality (only two or three dimensions), it has become an alluring femme fatale to many of us.
19. References.
Ahnelt, P. and Kolb, H. (1994) Horizontal cells and cone photoreceptors in human retina: A Golgi-electron microscopic
study of spectral connectivity. J. Comp. Neurol. 343, 406-427.
Bowmaker, J. K. (1998) Evolution of color vision in vertebrates. Eye 12,541-547.
Boycott, B. B. and Wassle, H. (1999) Parallel processing in the mammalian retina. Invest. Ophthal. Vis. Sci. 40,113-1327.
Cook, P. B., and McReynolds, J. S. (1998) Lateral inhibition in the inner retina is important for spatial tuning of ganglion
cells. Nature Neuroscience 1, 714-9.
Dacey, D. M. (1996) Circuitry for color coding in the primate retina. Proc. Nat. Acad. Sci. 93, 582-588.
Dacey, D. M. and Lee, B. B. (1997) Cone inputs to the receptive fields ofmidget ganglion cells in the periphery of Macaque
retina. Invest. Ophthal. Vis. Sci 38, S708.
Dacey, D. M. and Lee, B. B. (1994) The blue-on opponent pathways in primate retina originates from a distinct bistratified
ganglion cell. Nature 367, 731-735.
DeMonasterio F. M. and Gouras, P. (1975) Functional properties of ganglion cells of the rhesus monkey retina. J. Physiol.
(Lond) 251,167-95.
DeValois, R. L., Abramov, I. and Jacobs, G. H. (1966) Analysis of response patterns of LGN cells. J. Opt. Soc. Am. 56, 966977.
Dowling, J. E. (1987) The Retina: an approachable part of the brain. The Belknap Press, Harvard University Press
Cambridge, Massachusetts.
Evers, H. and Gouras, P. (1986) Three cone mechanisms in the primate electroretinogram: two with and one without offcenter bipolar responses. Vision Res. 26, 245-254.
Gouras, P. (1968) Identification of cone mechanisms in monkey ganglion cells. J. Physiol. 199, 533-547.
Gouras, P. (1969) Antidromic responses of orthodromically identified ganglion cells in monkey retina. J. Physiol. 204, 407419.
Gouras, P. and Zrenner E. (1981) Color vision: a review from a neurophysiological perspective. Prog. in Sens. Physiol.
1,139-179.
Hering, E. (1964) Outlines of a theory of the light sense. Translated by L.M. Hurvich & D. Jameson. Cambridge, MA:
Harvard University Press.
Hurvich, L.M. (1981) Color Vision. Sunderland, MA: Sinauer Assoc.Inc.
Kaiser, P. and Boynton, R. M. (1996) Human Color Vision. Opt. Soc. of Amer.
Kaplan, E. and Shapley, R. M. (1986) The primate retina contains two groups of ganglion cells, with high and low contrast
sensitivity. Proc. Natn. Acad. Sci. USA 83, 2755-2757.
Kolb, H. (1994) The architecture of functional neural circuits in the vertebrate retina. Invest. Ophthal. Vis. Sci. 35, 23852404.
Kolb, H., Goede, P., Roberts, S., McDermott, R., and Gouras, P. (1997) Uniqueness of the S-cone pedicle in the human
retina and consequences for color processing. J. Comp. Neurol. 386, 443-460.
Kolb, H., DeKorver, L., Church, J., Crooks, J., Jacoby, R. and Marshak, D. (1998) P cells of the primate retina. Invest.
Ophthal. Vis. Sci. 39, S563.
Kruger, J. and Gouras, P. (1979) Spectral selectivity of cells and its dependence on slit length in monkey visual cortex. J.
Neurophysiol. 43, 1055-1069.
Ladd-Franklin (1929)
Land, E. (1986) Recent advances in retinex theory. Vision Res. 26.7-21.
Lee, B. B., Pokorny, J., Smith, V. C., Martin, P. R., and Valberg, A. (1990) Luminance and chromatic modulation
sensitivity of macaque ganglion cells and human observers. J. Opt. Soc. Am. 7, 2223-2236.
Lee, B. B., Valberg, A., Tigwell, D. A. and Tryti, J. (1987) An account of spectrally opponent neurons in macque lateral
geniculate nucleus to successive contrast. Proc. Roy. Soc. (Lond.) B 230, 293-314.
Livingstone, M. S. and Hubel, D. H. (1988) Segregation of form, color, movement and depth: Anatomy, physiology and
perception. Science 240, 740-749.
Malpeli, J. G. and Schiller, P. (1978) Lack of blue off-center cells in the visual system of the monkey. Brain Res. 141. 385389.
Marr, D. (1982) Vision. San Francisco W. H. Freeman & Co.
Martinez-Conde, S., Macknik, S. L. and Hubel, D. H. (1999) Bursts of spikes in the LGN and area V-1 are correlated with
microsaccades during visual fixation in the behaving monkey. Invest. Ophthalmol. Vis. Sci. 40, S642.
Michael, C. (1977) Color vision mechanisms in monkey striate cortex: dual opponent cells with concentric receptive fields.
J. Neurophysiol. 41, 572-588, 1987.
Mollon, J. D. and Polden, P. G. (1977) An anomaly in the response of the eye to light of short wavelength. Phil. Trans. Roy.
Soc. (Lond.) B 238 207-240.
Mullen, K. T. (1985) The contrast sensitivity of human colour vision to red-green and blue-yellow chromatic gratings. J.
Physiol. 359, 381-400.
Nathans, J., Thomas, D., and Hogness, D. S. (1986) Molecular genetics of human color vision: The genes encoding blue,
green and red pigments. Science 232, 203-210.
Ratliff, F. (1960) Mach Bands: Quantitative studies on neural networks in the retina. Holden Day Inc. San Francisco.
Rodieck, R. W. (1998) The First Steps in Seeing. Sunderland, MA: Sinauer Assoc.
Schiller, P. H. and Lee, K. (1991) The role of primate area V4 in vision. Science 251,1251-1253.
Schiller, P. H., Logothetis, N. K. and Charles, E. R. (1990) Functions of the the color-opponent and the broad-band
channels in vision. Visual Neurosci. 5, 321-346.
Schiller, P. H., Logothetis, N. K. and Charles, E. R. (1991) Parallel pathways in the visual system: their role in perception.
Neuropsychologia 29, 433-442.
Slaughter, M.M, Zhang, J. & Tian, N. (1995) Ramifications of GABA receptor subtypes on retinal information processing.
In J. Robbins (ed): Basic and Cilinical Perspectives in Vision Research. New York: Plenum Press, pp. 115-124.
Stiles, W.S. (1949) Increment thresholds and the mechanisms of colour vision. Documenta Ophth. 3,138-165.
Walls, G. L. (1942) The vertebrate retina and its adaptive radiation. Cranbrook Press, Michigan.
Werblin F. S. (1991) Synaptic connections, receptive fields, and patterns of activity in the tiger salamander retina. Invest.
Ophthal. Vis. Sci., 32, 459-483.
Wiesel, T. and Hubel, D. H. (1966) Spatial and chromatic interactions in the lateral geniculate body of the rhesus monkey.
J. Neurophysiol. 29,1115-1156.
Zeki, S. A (1993) Vision of the Brain. Oxford, Blackwell Scientific. < From: http://webvision.med.utah.edu/color.html>