Applications of the multifocal electroretinogram in the detection of glaucoma


Dr Henry HL Chan
School of Optometry
The Hong Kong Polytechnic University
Hung Hom, Kowloon
Hong Kong SAR


Glaucoma is one of the most important eye diseases resulting in blindness worldwide. It affects the inner retina and is without signs and symptoms in the early stages, making early detection of glaucoma important for eye care professionals. Electroretinography (ERG) is an objective technique used to measure retinal electrical responses, which directly reflect retinal function. The multifocal electroretinogram (mfERG) is a relatively new tool in this area. Various modifications of the mfERG stimulation paradigms such as fast flicker, low contrast, slow sequence, global flash and luminance-modulation have been developed in recent years. Using these techniques and a better understanding of the mfERG characteristics has resulted in greater effectiveness of the mfERG in the diagnosis of glaucoma. It is likely that sensitive clinical mfERG measurement protocols for early detection of glaucomatous damage will be possible in the near future.

Glaucoma primarily affects the inner retina, specifically the retinal ganglion cells, most likely with unremarkable signs or symptoms in the early stages. The damage results in visual field constriction and ultimately in loss of central vision. The traditional technique for detecting this abnormal functional change is visual field testing. Unfortunately, patients with glaucoma may suffer more than 35 per cent loss of retinal ganglion cell axons before a visual field defect is evident.1,2 Currently, optical coherence tomographic (OCT) measurement of retinal nerve fibre layer thickness has become the most common clinical technique for the detection of glaucoma. A recent review stated that the functional loss is linearly related to the structural loss3 and this suggests that neither structural nor functional changes are more useful in glaucoma detection. Recently, another non-invasive in vivo imaging technique has been developed and the apoptotic retinal ganglion cells in an animal eye after attaching fluorescent markers can be visualised by confocal scanning laser ophthalmoscopy or the Heidelberg Retina Angiograph II. If this technique is successfully developed and can be applied clinically, it may give an early identification of structural change in terms of cell loss in glaucoma at the retinal level.4–7 Therefore, an effective clinical test is necessary for detecting or diagnosing glaucoma in the early stages.

Glaucoma refers to a group of eye diseases with a characteristic pattern of optic neuropathy involving loss of retinal ganglion cells. The atrophic change in nerve fibres is accompanied by characteristic alterations in the appearance of the optic nerve head, such as increased cupping of the disc and notching at the retinal neural rim, and subsequent visual field loss.8 Primary open-angle glaucoma (POAG) is the major primary type of glaucoma in most populations worldwide.9,10 POAG is generally bilateral but is not necessarily symmetrical.11–13 The development of the field loss in glaucoma is caused by progressive damage to retinal nerve fibres. The pathophysiology of this complex disease cannot be explained by a single mechanism. Glaucoma appears to be multifactorial in aetiology and different explanations have been proposed for the damage it causes.

The mechanical theory emphasises the structural damage to the optic nerve head at the level of the lamina cribrosa, caused by elevated intraocular pressure (IOP). The elevated IOP exerts a force posteriorly on the lamina cribrosa,14 the weakest part of the sclera, and this may lead to extensive remodelling of the structure of the lamina cribrosa–optic nerve interface. In addition, astrocytes within the optic nerve fibres are subject to the same force and respond to the elevated IOP15 to preserve the integrity of neural tissues. This redistribution and migration of reactive astrocytes into the nerve bundles at the level of the lamina cribrosa and the upregulation of cell surface adhesion molecules15 may alter fascicular support of the lamina cribrosa and make it more susceptible to collapse under elevated pressure.

Glaucomatous damage may also occur without elevation of IOP and thus, the mechanical theory alone is not sufficient as an explanation of glaucoma. The vascular theory suggests that poor vascular supply to the optic nerve head can cause ischaemia and such eyes are predisposed to glaucomatous damage. The suggested causes of poor vascular supply include loss of capillaries, low perfusion pressure, alteration and failure of regulation of capillary blood flow.16 When there is poor vascular supply, endothelial cells play a major role in local regulation by releasing vasodilating factors such as nitric oxide or vasoconstrictor endothelin-1 to maintain a constant oxygen level.17 This regulatory mechanism may fail in patients with glaucoma18 and average ocular blood flow may be decreased even in some patients with normal tension glaucoma.16

Previous evidence has indicated that in chronic glaucoma, cells with larger axons tend to be affected in early glaucoma.19 As both the superior and inferior poles of the optic nerve head contain more large fibres, these regions seem to be damaged earlier, as seen in human eyes with glaucoma;20 however, the rationale for selective loss of large ganglion cells in early glaucoma has been refuted by more recent evidence indicating that the number of neurons in the magno- and parvo-layers of the lateral geniculate nucleus also show a tendency to decrease with increasing optic nerve fibre loss.21 Evidence based on psychophysical evaluation is also consistent with the hypothesis that there is no selective damage of ganglion cells in early glaucoma.22 Some studies have shown that retinal ganglion cells with both small and large axons undergo shrinkage before cell death in glaucoma23–25 and this has suggested that the apparent selective loss of large ganglion cells in early glaucoma may merely be due to shrinkage of these cells.

The ganglion cells lost due to glaucomatous damage cannot be regenerated but appropriate treatment can be effective for preventing further cell degeneration and death. Early detection is essential to prevent the progression of glaucomatous damage and effective diagnostic techniques are very important to allow early treatment of glaucoma. Thus, a sensitive clinical test that can predict the progression of glaucoma is very important.


Visual electrophysiology provides information about the electrical activity of the visual system. It provides objective functional information regarding the visual pathways, which is effective for the diagnosis and management of various eye diseases.26 The clinical electrophysiological tests for vision include the electroretinogram (ERG), visual evoked potential (VEP) and electro-oculogram (EOG). In this review, we focus on a specific electroretinogram, namely the multifocal electroretinogram (mfERG), for the detection of glaucoma.

In the conventional ERG, all measurements are obtained from a summated response from the entire retina and topographical information about localised damage in the retina is generally not available. In 1992, Sutter and Tran27 introduced a new concept, a multiple-input technique for electroretinographic recording. They developed a new clinical ERG with multiple stimulations (mfERG) to obtain multiple localised retinal responses from a single recording (Figure 1). With the development of this multi-input technology, recording of the physiological topographic responses of the retina became possible. This topographical electrophysiological information augments traditional behavioural visual field testing.28 It gives an objective and quantifiable result, which can be compared from visit to visit or to standard data sets. This technique stimulates multiple retinal areas and gives a response for each measured area.27 During the stimulating period, half of the stimulus elements are at high luminance (bright) and the others are at low luminance (dark). The stimulation rate is the number of display changes per second and that is controlled by the frame rate of the video monitor used as the stimulus display. In order to facilitate the cross-correlation of stimulus (the change in display sequence) with the response (the ERG signal), each stimulus element is driven by the same pseudo-random sequence of stimulation, called ‘maximum-length sequence’ or ‘m-sequence’. For each stimulus location, the m-sequence is delayed by a different amount and the responses associated with these elements are effectively uncorrelated with each other. Consequently, each stimulus element triggers a localised retinal response and thus, localised changes in the mfERG topographical responses due to the dysfunctional areas can be easily detected.29 With 103 hexagonal stimuli used for mfERG measurement, a visual field defect not less than five degrees in diameter can be detected. The sensitivity in the detection of localised defects is somewhat lower, if a small defect is located over two hexagonal stimuli.30 The sensitivity of the mfERG in the detection of a small scotoma can be improved if a higher resolution stimulus pattern (for example, 241 hexagons) is used,31 but these result in long recording times and poor signal-to-noise ratios. The 103 hexagonal pattern has been recommended by the Society for Clinical Electrophysiology of Vision as the stimulus for clinical use.32

Figure 1.

(A) A 103 scaled hexagonal pattern for multifocal electroretinogram (mfERG) measurement. (B) A mfERG first-order kernel trace array (103 waveforms) from a human subject. (C) Ring traces from Ring 1 to Ring 6. (D) A three-dimensional plot of mfERG traces with indicated location of the blind spot.


The mfERG presents its stimulus (bright or dark) based on the ‘pseudo-random m-sequence’, which is a mathematical device that allows the mfERG signal to be quickly extracted from the relationship between the stimulus sequence and the raw ERG response waveform. By performing a cross-correlation of the output signals with the input binary pattern, it is possible to extract the local retinal contribution of different ‘binary kernels’. These are nothing more than direct responses to a flash, first-order kernels, or responses to a flash that has been preceded by a flash, second-order kernels.33,34 Imagine that a series of identical flashes with a high but random frequency of flicker is used as the stimulus; the first flash will generate a signal similar to that produced by a single flash. The signal generated by the following flashes will have different amplitudes and shapes because of the interaction with responses to the preceding flashes (adaptation of the retina). This is a non-linear response.

Mathematically, the first-order kernel can be obtained by adding all of the responses, which follow a bright flash to a hexagon and subtracting all of the responses, which follow a dark presentation to the same hexagon. Thus, the response of that hexagon is built up, while the contributed responses from other hexagons will be eliminated (Figure 2A). The second-order kernel measures how responses are influenced by adaptation to successive flashes. The first slice of the second-order kernel response shows the effect of a following flash, the second slice shows the effect of the flash, which is two frames away and so on. In other words, it is obtained by adding all of the responses following a change from either bright to dark or dark to bright and subtracting all of the responses with no change in the stimulus (Figure 2B).

Figure 2.

A schematic diagram showing the calculation of the first- and second-order kernels of the multifocal electroretinogram (mfERG). (A) The first-order kernel is obtained by adding the responses from a hexagon with a bright flash and subtracting the responses from the same hexagon with no flash (dark). (B) The first slice of the second-order kernel is obtained by adding the responses from a hexagon following a change from either bright to dark or dark to bright and subtracting all of the responses from the same hexagon with no change of stimulation.


As with the traditional full-field ERG, the mfERG reflects contributions from various retinal cell types. The overall shape of the first-order kernel in the human mfERG response is attributed mainly to bipolar cell contributions combined with smaller contributions from photoreceptors. This analysis is based on the pharmacological dissection of monkey mfERG35 and pig mfERG.36 The human mfERG is significantly different from that recorded from the monkey;37 however, once the inner retinal components are removed from monkey mfERG responses, the waveform resembles that of humans.37,38 Based on these findings, a proposed model of human mfERG was deduced, which suggests that the major contribution to the human mfERG is from outer retina with a relatively small contribution from the inner retina35 (Figure 3). The onset (hyperpolarisation) of the OFF-bipolar cell starts just before the depolarisation of the ON-bipolar cell. Thus, the leading edge of the N1 is generated by the hyperpolarisation of the OFF-bipolar cell with small contribution from the photoreceptors. The shape of N1 is then altered by the onset of the ON-bipolar response and the recovery of the OFF-bipolar response occurs slightly after the peak of N1. Thus, the leading edge of the P1 contains both the recovery of the OFF-response and the depolarisation of the ON-bipolar cell. The peak of P1 occurs at the time when the recovery of the OFF-response has reached its positive peak and the contribution of the ON-bipolar has also reached its peak. The recovery of the ON-response mainly forms the trailing edge of P1.35,36

Figure 3.

A schematic diagram showing the waveform, timing and cellular contribution of the first-order kernels of the multifocal electroretinogram


The magnitude of the mfERG response decreases with eccentricity and the reduction rate is slightly less in the nasal retina due to the higher cone density.27 Changes of the mfERG response magnitude with eccentricity are well correlated with the cone density. As with many other assessments of visual function, ageing significantly reduces mfERG responses.39 It has been suggested that the most central mfERG responses exhibit the greatest decline with age.40–42 The averaged peak-to-peak amplitude decline rate is approximately 10.5 per cent per decade43 and it is believed that optical factors contribute most to the loss of function.40 A recent study found that neural factors, not optical factors, start to significantly influence the mfERG responses with increased latency after the age of 70 years.44


Data from clinical cases have demonstrated that functional losses due to outer retinal disorders can be well described by conventional mfERG results and that the defect pattern of mfERG activity is similar to the pattern of the visual field defect.45 Previous studies46–48 have evaluated the mfERG characteristics for clinical applications and have found that the first-order kernel responses from the mfERG are sensitive in detecting diseases such as retinitis pigmentosa. The mfERG also allows accurate topographical mapping of focal areas of retinal dysfunction due to age-related macular degeneration,49 retinal vascular occlusion50 and retinal detachment.51 In addition, in some patients with diabetic retinopathy, the second-order kernel responses in mfERG are reduced and delayed52 and the mfERG has been reported to show local retinal dysfunction in diabetic eyes before retinopathy is evident.53 It has been suggested that the second-order kernel responses are sensitive for detection of early changes in the retinal function of diabetes;52 however, for retinal diseases where the disorder is restricted to the inner retina (especially the ganglion cell layer), there is no simple correlation between the mfERG results (either the first-order or second-order kernel response) and the visual field defect.45 This raises questions about how the activity of ganglion cells contributes to the human mfERG and what is the best method to measure this response, as glaucoma appears to result from damage to the retinal ganglion cells.


Retinal signal processing involves different levels of adaptation processing and these adaptations start in the photoreceptor layer followed by post-receptoral feedback mechanisms. It has been claimed that the non-linear mechanisms in the retina arise predominantly from the inner retina.54 Although the second-order kernel response reflects the mechanisms of temporal interactions in the retina, there is still conflict over the hypothesis that the components in the second-order kernel response reflect the activities of the retinal ganglion cells.55,56

Nevertheless, several studies have used the mfERG to access the physiological response of the (presumably damaged) ganglion cells to detect signs of glaucomatous damage in terms of amplitude57 and implicit time.58 In addition, the changes in amplitude primarily affect the central retina,57 where the latency of mfERG responses showed a significant negative correlation with the mean sensitivity (dB) of static perimetry.58 The amplitude of the mfERG response is also reduced in patients with ocular hypertension59 and the second-order kernel response is also abnormal even in patients with glaucoma or glaucoma suspects with a normal visual field.60 Sakemi, Yoshii and Okisaka61 found that neither the first- nor the second-order kernels of the mfERG showed any changes correlated with glaucomatous visual field abnormalities and questioned its relationship with inner retinal responses. In fact, outer retinal activity has also been found to make a contribution to second-order responses,36,62 and this contribution may complicate the interpretation of the retinal changes in glaucoma. Even though the latency changes have been reported to be more sensitive than amplitude changes in showing glaucomatous visual field defects,58 it has been noted that mfERG changes do not precede glaucomatous defects diagnosed using static perimetry.

How do the retinal ganglion cells contribute to the mfERG response? This is an important question to consider before applying the mfERG to the detection of glaucoma. An experimental model of glaucoma in primates resulting in a loss of retinal ganglion cells showed a marked attenuation of both the first- and second-order mfERG responses63 and the mfERG amplitudes were highly correlated with the density of the surviving retinal ganglion cells. Other studies37,64 demonstrated the inner retinal contribution to the monkey mfERG by recording before and after intra-vitreal injections of N-methyl-D-aspartic acid (NMDA) and tetrodotoxin. Tetrodotoxin blocks the sodium-based action potentials of ganglion and amacrine cells and substantially alters the mfERG from monkeys.62 Further treatment with NMDA removes amacrine cell activity and feedback components, as it depolarises the post-synaptic membranes of ganglion and amacrine cells. These studies support the view that mfERG responses reflect the contribution from the ganglion cells. The mfERG waveform in the monkey is quite different from that in humans even for the first-order kernel response. The first-order kernel responses in the monkey have large naso-temporal variation with double peaks in the waveform,35 but these are not obvious in the human mfERG.

The effects of experimental glaucoma in the monkey on first-order and second-order mfERG responses were similar to those seen under the effects of tetrodotoxin and NMDA.37 The naso-temporal variation and oscillatory potentials also disappeared in the experimental glaucomatous eyes. This suggests that the spiking activity of inner retinal neurons is the cause of the naso-temporal variation across the retina. As shown by a comparison of first- and second-order kernels in primate mfERG, the inner retina has a relatively greater input into the second-order mfERG response.62 In a laser-induced experimental glaucoma model, the second-order mfERG responses were more sensitive to glaucomatous changes.65 Therefore, a sound approach in modification of the protocol or analysis of the mfERG would be to enhance the contribution of inner retinal activity in the mfERG to detect glaucomatous defects.

Optic nerve head component in mfERG

Most previous studies have applied the conventional (fast flickering) mfERG with high contrast stimulation to test for glaucomatous dysfunction;57,59 however, no simple correlation of the topographical mfERG changes and the retinal dysfunction observed in visual field defects has been found.61,66 Thus, a range of stimulation paradigms has been proposed to improve the situation.

One of the most important studies was done by Sutter and Bearse,54 who demonstrated that the human mfERG response contained a component attributable to ganglion cell activity. They used a mathematical algorithm to extract a component with a latency, which increased in proportion to the estimated length of the ganglion cell axons from the site of stimulation to the optic nerve head. They speculated that this component (the so-called optic nerve head component) originated from the ganglion cell axons. They found that glaucomatous damage can reduce the magnitude of this component. This optic nerve head component theory was supported by data from the monkey, where the tetrodotoxin-sensitive component from the mfERG waveform was similar to the optic nerve head component.67 In addition, the marked naso-temporal variation of the monkey mfERG was eliminated by pharmacological suppression of inner retinal activity,37 suggesting that the optic nerve head component derived from ganglion cells is likely to be related to the naso-temporal variation of the mfERG. Although this component exists in the mfERG response, it is quite difficult to observe in most records because it varies in appearance and it is not easy to extract it from the complex waveform of the first-order kernel.

Low contrast mfERG

Several previous studies have reported that the contrast sensitivity in glaucoma is significantly affected, especially at low contrast.68,69 A low contrast stimulus presentation has been proposed for the mfERG and when the stimulus contrast is reduced to 50 per cent, the naso-temporal variation in the first-order kernel in human mfERG becomes obvious.38 As naso-temporal variations in waveform have been hypothesised to arise from ganglion cell activity, it appears that contrast attenuation of the stimulus can increase the relative proportion of the responses coming from the inner retina in the human mfERG.70 Therefore, in an attempt to obtain a better mfERG response from the inner retina, mfERG recordings with reduced stimulus contrast have been applied to detect glaucomatous changes.71 At this contrast level, the human mfERG waveform is similar to that of the monkey, with oscillatory components on the ascending and descending limbs of the first positive peak of the low contrast mfERG. Additionally, for subjects with glaucoma, the later oscillatory component (that is, the one on the descending limb) seems to be reduced in magnitude71,72 (Figure 4). This is not a universal finding and in those with clear abolition of oscillatory components in the mfERG waveform, the changes do not correspond to the localised visual field losses. Although the first-order kernel responses for low-stimulus contrast recordings show obvious changes in glaucoma,73 the sensitivity of these recordings is insufficient to detect inner retinal disease. In addition, the second-order kernel responses are very noisy for low contrast stimulation and are very difficult to study.

Figure 4.

(A) Visual field results from two patients with glaucoma (G1 and G2) using the Humphrey Field Analyser II (Central 30-2 threshold measurement). (B) Diminished oscillatory component on the descending limb of the low contrast multifocal electroretinogram waveform (grey circle) from glaucomatous patients compared with that from normal subject (N1).60

Slow-sequence (slow flash stimulation) mfERG

In the conventional fast mfERG, the stimulus is generally displayed on a monitor with a frame rate of 75 Hz, which means that the time interval between two successive flickering stimuli is approximately 13.3 ms. In 1995, Wu and Sutter74 introduced a slow multifocal stimulation to analyse the topographic distribution and non-linearities of oscillatory potentials (OP) in the retinal response. The OP generated from slow multifocal stimulation are likely to be related to feedback from the inner retina. Sano and colleagues75 further modified this slow mfERG paradigm (that is, slow-sequence mfERG) and observed a new wavelet in the mfERG, as the m-sequence presentation for mfERG is slowed by interleaving three grey frames between the presentations of flickering stimuli (Figure 5). The insertion of these additional frames increases the time interval between two successive m-sequence frames by a factor of four. The reported positive wavelet appeared on the descending limb of the first positive peak of this slow-sequence mfERG. The amplitude of this wavelet increased significantly when 30 further grey frames were added between the m-sequence frames. Furthermore, the amplitudes of this unmasked wavelet obtained from the nasal retina were significantly larger than those from the temporal retina, and this naso-temporal variation is considered to be related to the distance of the stimulated area from the optic nerve head. The characteristic of this small wavelet, the so-called s-wave, was not observed in eyes with optic neuritis in mfERG recordings at any presentation frame rate; however, it was shown in unaffected eyes in all patients with unilateral optic neuritis. This wavelet reappeared with recovery from the disease and its recovery was significantly correlated with the recovery of visual acuity. Thus, these findings support the idea that the new wavelet originates from the ganglion cells.75 The oscillatory component on the descending limb of the low contrast mfERG waveform and the new wavelet generated from the slow-sequence mfERG are very similar in terms of the appearance, amplitude and implicit time. This suggests that both applications enhance or unmask inner retinal activity and are most likely to measure the same response in the mfERG, although the stimulation protocols are totally different.

Figure 5.

(A) Schematic diagram showing the flash stimulation sequence of the slow-sequence (slow flickering stimulation, MOOO) multifocal electroretinogram (mfERG). (B) The first-order kernel of the slow-sequence mfERG from the central (rings 1 to 2) and peripheral (rings 3 to 6) regions.

Recently, a series of high frequency oscillatory potentials following the dominant component of the first-order kernel response was found in the slow-sequence mfERG stimulation with three dark frames76 (Figure 5). This protocol is different from the above as the luminance of the inserted frames is different, that is, one using grey frames (about 60 cd/m2)75 and the other using dark frames (less than 1.0 cd/m2).76 Under this protocol, a change of the oscillatory potentials was observed in patients with glaucoma. The oscillatory potentials reduced significantly in the central field and in the nasal field for patients with normal tension glaucoma, allowing 85 per cent sensitivity for differentiation from normal subjects. The oscillatory potentials can be divided into fast (143 Hz) and slow (77 Hz) wavelets.77 In monkeys, the fast oscillatory potentials are significantly larger in the temporal than in the nasal retina77,78 and they are reduced in experimental glaucoma with moderate correlation with local visual field sensitivity.77 This suggests that the fast oscillatory potentials are also likely to be related to the activity of retinal ganglion cells.79 All of these slow-sequence mfERG protocols with the insertion of a number of blank frames can minimise the involvement of second-order or higher-order kernel responses and provide an uncontaminated first-order kernel response. This relatively clean first-order kernel response contains less temporal interaction from the retina but probably has a degree of non-linear activity due to spatial interaction. Hence, it can provide different results in glaucoma detection compared with flash ERG without non-linear interaction.

Global flash stimulation mfERG

The above-mentioned applications show a degree of effectiveness in the detection of glaucomatous defects; the higher order interactions involving temporal processing of retinal responses leading to adaptation are of interest. These interactions are one of the core strengths of the mfERG.

The use of higher-order kernels is a method by which the interaction of successive flashes may be examined. The second-order kernel is the simplest analysis containing non-linearity in the retina. A previous study80 suggested that the inner retina involves adaptation mechanism(s) and thus dysfunction of the inner retina may alter the adaptation mechanism(s). The second-order kernel response, depending on the effect of the preceding flash, has also been applied to the study of glaucomatous damage;81 however, it does not show a correlation to visual field loss in glaucoma.

The first-order kernel response is more complex than it appears as the second-order kernel response contributes to the later part of the first-order kernel response81 due to the adaptation influences from the preceding flash. If this non-linear response in the first-order kernel can be enhanced and measured, it would be useful for recording inner retinal activity. Hence, an alternative mfERG protocol using a global flash, which provokes an interaction containing an enhanced non-linearity has been developed.80 The hypothesis here is that if the global flash does not produce an adaptive effect, it would not contribute to the mfERG response because its contribution would be cancelled when the focal responses are extracted (Figure 6).

Figure 6.

Schematic diagram for the signal derivation of the first-order kernels of the global flash stimulation (MOF) in the multifocal electroretinogram (mfERG). The bottom waveform is the first-order kernel of the global flash mfERG. It contains two components: direct component (DC) and induced component (IC).

In this global flash stimulation, there are two components in the mfERG response: a direct component (DC) and an induced component (IC) (Figure 6). The direct component is assumed analogous to a conventional mfERG response, while the induced component is the change of the response to the global flash produced by the prior local flash. This non-linear induced component represents adaptive changes in the response and the changes may be generated by the inner retina.80 Different protocols have been proposed to enhance this non-linear component in the retina and most studies have used one periodic global flash interposed between two consecutive focal flashes,82–86 while others have used two87 or three periodic global flashes88 between consecutive focal flash stimulations. Although there are different ways of inserting the global flash in the m-sequence, the aims are the same, namely, to enhance the adaptive effect in the retina so as to measure the inner retinal contribution. It has been claimed that the global flash technique exhibits a large optic nerve head component80,89 and the naso-temporal asymmetry of the induced component response is observed in the human global flash mfERG.83 It has also been shown that the optic nerve head component can be extracted from the induced component epoch and that the loss of the optic nerve head component in glaucoma is more apparent when using the technique. In other studies, the induced component has been shown to be reduced in glaucoma.87,88 Although the amplitude of the induced component response from the nasal retina was most affected in glaucoma,88 a small oscillation in the induced component from the temporal retina was also found to be sensitive in the detection of glaucoma.83 A recent study reported that the induced component of the superior temporal retinal region is the most sensitive parameter for glaucoma differentiation.87 The similar outcomes obtained from different studies indicate that the various global flash protocols can enhance adaptation in the retina for the detection of glaucomatous defects.

The induced component response in the ‘two global flash’ stimulation paradigm can provide a sensitivity of 85 per cent and a specificity of 80 per cent in the detection of POAG.87 This finding is similar to another study83 using a ‘one global flash’ stimulation protocol, which reported a sensitivity of 75 per cent and a specificity of 83 per cent. Thus, the induced component response in the human mfERG has been confirmed to be efficient in detecting glaucoma but the correlation of the induced component response with the corresponding visual field defects in glaucoma is not yet well defined.83,88 In addition, the relatively large inter-subject variation of the induced component response limits its possibility for the assessment of localised glaucomatous damage in individual patients.82

In contrast, the characteristics of the direct component in the global flash mfERG have not been widely studied. The direct component is sensitive to changes in diabetic retinopathy82 and age-related maculopathy84 and it has been suggested to show a contribution from the optic nerve head component.80 Although the direct component has been suggested to be analogous to a conventional mfERG response,80 the direct component also reflects a certain level of adaptive change produced by the periodic global flashes85 because there are temporal interactions between the focal flashes and the periodic global flashes in this paradigm. These interactions are reflected in the change of shape of the direct component from the response of the conventional mfERG.83

A mfERG protocol combining both luminance-modulation (contrast) stimulation and global flash stimulation has recently been proposed.90 This modified global flash mfERG paradigm with various contrast stimuli has been designed to measure temporal adaptive changes in the retina (Figure 7). The low contrast stimulation unmasks the oscillatory component from the inner retina and the global flash stimulation enhances the temporal adaptation in the retina. This combination protocol is believed to further advance the mfERG in the detection of glaucomatous damage. The direct and induced components of the contrast response functions in this modified global flash mfERG showed different characteristics. The direct component responses in normal subjects remain steady at mid- and high-contrast levels, but in subjects with glaucoma the direct component responses show a significant reduction in amplitude at mid-contrast levels and a mild reduction at high-contrast levels (Figure 8); however, the induced component responses show a larger reduction in amplitude only under high-contrast conditions. Subjects with glaucoma showed a loss of contrast saturation in the direct component contrast response function, which is most likely caused by impairment of the fast-adaptation mechanism in the retina. Quantifying this loss by calculating the area under the direct component contrast response function (adaptive index) provides a measure of the intrinsic response changes with contrast levels. Moreover, the adaptive index factors out baseline response amplitude variation and minimises the effect of inter-subject variation of the response amplitude. The adaptive index has been shown to provide good differentiation between normal subjects and glaucomatous patients with a sensitivity of 93 per cent and a specificity of 95 per cent.90 The adaptive index also illustrated a good correlation with the glaucomatous visual field defects and this has not been reported previously.

Figure 7.

(A) Schematic diagram showing the luminance modulation (contrast) for the global flash multifocal electroretinogram (mfERG) stimulation (MOFO). (B) The first-order kernel of the global flash mfERG at different contrast levels. Both the direct component (DC) and the indirect component (IC) increase in magnitude as the stimulus contrast increases.

Figure 8.

The luminance-modulated (contrast) response function of the grouped average (A) direct component (DC) and (B) indirect component (IC) responses (ring 4 to ring 6) from normal subjects and glaucomatous patients. The luminance-modulated response function for the DC in normal subjects shows a saturation characteristic as the stimulus contrast increases; the response function for the IC increases linearly with the stimulus contrast. Glaucoma subjects show a decrease in both DC and IC response amplitudes at all contrast levels. Bars indicate standard deviation.

Furthermore, clinically normal fellow eyes of patients with unilateral glaucoma were found to have impaired adaptation in the retina.91 The adaptive index in the fellow eyes was severely reduced and close to the value from the glaucomatous eyes. Thus, fellow eyes that were clinically normal had already shown abnormal changes in the retinal adaptive mechanism and this allows these fellow eyes to be differentiated from normal by the value of the adaptive index. Significant reductions in the adaptive index occur before any defined visual field loss in the fellow eyes of patients with unilateral glaucoma.92 These findings confirm that an impaired retinal adaptive mechanism occurs before observed visual field abnormalities in patients at high risk of glaucoma. As the mfERG is a tool used to study the temporal processing of the retinal responses leading to adaptation, appropriate protocols in mfERG measurement can help to advance the detection of glaucomatous defects as well as assist in early diagnosis.

A question is raised of how the induced component could be useful in assessing inner retinal function if the direct component is also reduced. Since the direct component is believed to come from the outer to mid-retinal layers and the induced component is believed to come from the inner retinal layers,93 the magnitude of the direct component should have an influence on the magnitude of the induced component; however, the characteristics of the direct component and the induced component in the contrast response functions in glaucoma patients are totally different compared with normal subjects. The function of the direct component in glaucomatous subjects was significantly decreased at the mid-contrast level, while the function of the induced component in glaucomatous subjects was found to have a significant reduction at the high-contrast level. The different patterns in response reduction of direct and induced components imply that the changes of these two components in glaucoma have a certain level of independence. A recent study investigated the cellular contributions to the global flash mfERG by pharmacological dissection in porcine eyes.93 The inner retinal activity partially contributes to the direct component with superimposed regular oscillation-like wavelets. Hence, eye diseases (such as glaucoma) involving damage to the inner retinal layers may reduce oscillation-like wavelets contributing to the direct component and ultimately alter the characteristics of the direct component contrast response function. For retinal diseases with outer retinal dysfunction it cannot be excluded that the magnitude of the induced component may be affected primarily by the direct component.

Time-frequency analysis of the mfERG

Recently, another approach has been taken to the analysis of mfERG data. The usual analysis is the measurement of the response in terms of peak-to-peak or root-mean-square of the amplitude. The more recent analysis is a wavelet analysis, in which the oscillatory potentials are extracted from the mfERG waveform. The frequency of the oscillatory potentials are studied as an indicator of glaucomatous damage.79,94 This analytic method can apply in different stimulation protocols of mfERG, for example, slow-sequence stimulation79 and global flash stimulation.94 Although there are different methods for wavelet analysis, oscillatory potentials are the target of the mfERG response and these are most likely to be contributed from the inner retina74 and related to glaucoma.76

Comparison with mfVEP

Another multifocal technique for the detection of glaucoma is the multifocal visual evoked potentials (mfVEP), which was introduced in 1994.95 Numerous studies have reported good correlation between the results of mfVEP and the findings of visual field defects in glaucoma.96–105 There is no evidence to demonstrate the superiority of mfVEP over mfERG in the detection of glaucoma. The mfERG and the mfVEP are objective perimetric techniques, which measure responses from the retina and from the retina through to the visual cortex, respectively. They are limited by different factors, which affect sensitivity and specificity. Therefore, various approaches and protocols have been introduced to improve their usage in a clinical situation. In addition, both techniques are influenced by other physiological changes, for example, outer retinal changes would affect the findings of mfERG as well as mfVEP, and optic nerve or optic tract lesions other than glaucoma would affect the results of mfVEP. At present, neither mfERG nor mfVEP can give an adequate diagnosis of glaucoma. With further advances and in conjunction with other clinical tests, both techniques will help to provide accurate diagnosis and monitoring of glaucoma.


The mfERG has been applied in an attempt to detect early glaucomatous changes for a number of years and its effectiveness has improved dramatically over the past years with better knowledge of its cellular components and the non-linear mechanisms involved in the mfERG response. With a range of modifications of the parameters or the protocols in the stimulation pattern, the inner retinal contribution to the mfERG has been enhanced. Although a reliable quantitative clinical measurement using mfERG for early discrimination of glaucomatous damage has not yet been established, the application of mfERG in the early diagnosis of glaucoma should be possible in the near future with improvements in its paradigms.


The present study was supported by the Competitive Earmark Research Grants (PolyU 5415/06M) from The Research Grants Committee of the Hong Kong SAR, the Internal Research Grant (G-U585) and the Niche Areas—Glaucoma Research (J-BB76) from The Hong Kong Polytechnic University.