Loss of the low-frequency component of the global-flash multifocal electroretinogram in primate eyes with experimental glaucoma

Abstract

Purpose: To study relationships between glaucoma-sensitive components identified with frequency-domain analysis of global-flash multifocal electroretinogram (mfERG), regional retinal nerve fiber layer thickness (RNFLT), and local visual field sensitivity (VS).

Methods: Eleven macaque monkeys, including four controls and seven with unilateral laser-induced trabecular meshwork scarification and ocular hypertension, were observed with optical coherence tomography (OCT), full-field light-adapted flash ERG, 103-hexagon global-flash mfERG (MFOFO), and static perimetry. The effects of experimental glaucoma on mfERG were assessed in the frequency domain. Relations between root mean square (RMS) amplitude of a glaucoma-sensitive frequency range and peripapillary RNFLT (standard 12° OCT circular scan), and between RMS amplitude and VS were studied.

Results: Experimental glaucoma led to a dramatic and consistent power loss in the low-frequency (<25 Hz) band of mfERG. The RMS of this low-frequency component (LFC) correlated significantly with the regional RNFLT. The r(2) of linear fits was 0.39 (P < 0.001) for cross-sectional group data and 0.60 after correction for intersubject variability. The r(2) of linear fits for longitudinal data from individual animals was as high as 0.78 (P < 0.001). Local LFC RMS amplitude also correlated significantly with interpolated VS for hexagons. The r(2) for exponential fits of hexagon LFC RMS amplitudes (inner three rings) versus VS (dB) was 0.29 to 0.52 (P < 0.001) for the group and up to 0.95 in individuals.

Conclusions: The significant correlations between regional measures of global-flash mfERG, RNFLT, and VS suggest that LFC RMS amplitude provides a useful index for objective quantification of local RGC function and monitoring of early changes in glaucoma.

Figure 1.

(A) The two-global-flash paradigm used in this study. (B) Testing area of a 24-2 standard automated perimeter and the 103-element array used for mfERG shown for the left eye with retinal orientation. Ellipse: the ONH: dashed circle around the ONH: a standard 12° OCT circular scan. Shaded area: rings 1 and 3. Central hexagons show larger response amplitudes, while nasotemporal asymmetry is easier to identify in larger rings. (C) The axon course map based on Shields, used for analysis of conduction velocity illustrated in Figure 5 and indicating, for the correlation analysis illustrated in Figure 7, the hexagons and peripapillary arcs (portions of the dashed circle defined by the axons projecting from the highlighted hexagons) that were used.

Figure 2.

Relations between average RNFLT, VS, and PhNR amplitudes (measured for the response to a flash of 2.84 cd · s/m²). (A–C) Data from multiple imaging and recording sessions for subject OHT-53 only; (D–F) data from the last session of each animal (main panels) and all sessions of all animals (insets). Open circles: data from control (Con) eyes; gray circles: data from fellow Exp eyes. Solid lines: linear fits and 95% PI for data from both eyes. There were only five PhNR recordings available for each eye of subject OHT-53, as indicated in Table 1.

Figure 3.

Loss of nasotemporal asymmetry in experimental glaucoma. (A) Trace arrays from the Con and Exp eyes of subject OHT-48 with third-ring responses highlighted, and six-corner hexagons marked on the trace array. (B) Left: traces from six-corner hexagons of the third ring of the Con eye (OD); right: and the Exp eye (OS; black traces). The systematic change in implicit time of a negative component is highlighted in the Con eye recordings (left) with an open circle and a gray line. The gray traces in the left column represent extracted ONHCs from the same Con eye recordings. The gray traces in the right column represent RCs from the Con eye recordings in the left column. The numbers in parentheses show the corresponding hexagon numbers for the third-ring traces. P1 and N2: the first peak and second trough in the ONHC; SN, superonasal; ST, superotemporal; T, temporal; IT: inferotemporal; IN, inferonasal; N, nasal.

Figure 4.

Effects of experimental glaucoma on mfERG signals. (A) Left: power spectra of the summed mfERG recordings from each eye of subject OHT-48; right: LL subjects with unilateral glaucoma. The red lines for Con eyes and the gray shading for the Exp eye indicate ±1 SEM. Insets: frequency range of high-frequency OPs. (B) 3D surface plot for the third-ring responses from the Con eye of OHT-48. (C) 3D surface plot for the third-ring responses from the Exp eye of OHT-48. (D, E) 3D surface plots for third-ring LFCs obtained by passing responses in (B) and (C) through a 25-Hz low-pass filter. The red lines in (B) and (D) are drawn parallel to the linear fits of P1 implicit time of the ONHCs (not shown).

Figure 5.

Axon conduction velocity estimated with two different methods (n = 7 normal eyes from seven macaques). (A) Axonal conduction velocity estimated from third-ring ONHC extracted with the algorithm. (B) Axonal conduction velocity estimated from cross-correlating third-ring LFCs. Open squares and error bars in both (A) and (B) represent the mean and 95% confidence interval, respectively. Velocity was calculated by dividing implicit time changes or time bin shifts by the distance from the ONH.

Figure 6.

Correlation between LFC RMS amplitude of the mfERG signal averaged over the entire hexagon array and other global structure and function measures. (A–C) Data from all sessions for OHT-53; (D–F) data from the last session for each animal (main panels) and all sessions for all the animals (insets). Solid lines: linear fits and 95% PI for data from Exp eyes.

Figure 7.

Relation between LFC RMS and peripapillary RNFLT in experimental glaucoma. (A) Projection of a hexagon onto a group of OCT scan pixels in the peripapillary circular scan. As described in the text, an LFC RMS “partial circular scan” was generated. Comparisons between the RNFLT and LFC RMS circular scans were restricted to two temporal regions (twelve 7° sectors) (B) Average sectoral RNFLT and LFC RMS amplitude profiles, both of which show changes as the location changes. (C) Relation between sectoral LFC RMS and RNFLT revealed with the data from all sessions for OHT-53. (D) Improved relation between sectoral LFC RMS and RNFLT, as data shown in (C) were normalized. (E, F) Relation between the LFC RMS and RNFLT before and after the data from the last session of each animal was normalized. (G, H) Distribution of LFC RMS and RNFLT measures before and after the data from all sessions for all the animals was normalized. Solid lines: linear fits and 95% PI for data from both Con and Exp eyes.

Figure 8.

Relation between local LFC RMS amplitude and VS revealed with the data from the last experimental sessions (main panels) and all sessions (insets) of all the animals. (A) Data in the hexagons were from the three central rings of the global flash mfERG. (B) Data from all three rings and an exponential fit: LFC RMS amplitude = exp[a(total deviation in dB)] + b). (C–E) Data from the each of the three rings plotted separately. Solid lines: represent exponential fits and 95% PI for data from both Con and Exp eyes.