WO2009089509A1

WO2009089509A1 - Method for detecting a physiological change in a neuron of a retina

Info

Publication number: WO2009089509A1
Application number: PCT/US2009/030681
Authority: WO
Inventors: Xin-Cheng Yao
Original assignee: The Uab Research Foundation
Priority date: 2008-01-09
Filing date: 2009-01-09
Publication date: 2009-07-16

Abstract

Disclosed is a method for detecting a physiological change in one or more retinal neurons using fast intrinsic optical signals created by a response to visible light as measured by near infrared light.

Description

METHOD FOR DETECTING A PHYSIOLOGICAL CHANGE

IN A NEURON OF A RETINA

Inventor: Xincheng Yao

FIELD OF THE DISCLOSURE

The present disclosure relates to the field of optical imaging of the retina. The present disclosure is also directed to methods of diagnosing disease states and conditions in the retina.

BACKGROUND

As the kernel part of the vision system, the retina is responsible for effective capture of photons and several stages of preliminary processing of visual information (Sterling 2003), Better understanding of dynamic information processing in retina is not only useful for better understanding the nature of vision, but also provides important information for better diagnostics, better designs of artificial retina and simulations of parallel data processing system in the vision system. Because of the complex, layered structure of the retina, 3 -dimensional (3D) mapping of dynamic retinal activation is desirable for study of dynamic visual processing with high resolution. High-density microelectrode array (MEA) techniques promise fast, parallel measurement of neural activities of multiple neurons in isolated retina and other neural tissues, but the spatial resolution is limited by the number and spacing of electrodes and the conductivity properties of neural tissue (Meister 1994). Typically, MEAs can only provide spatial resolution at -100 μm level, but better 3D resolution is required for reliable measurement of neural activities in complex neural networks.

High resolution imaging of retinal function is also desirable for reliable detection of eye diseases and monitoring of treatment outcomes. It is well established that major eye diseases, such as age-related macular degeneration (AMD) (Hogg and Chakravarthy, 2006) , glaucoma (Harwerth and Quigley, 2006; Nickells, 2007) and diabetic retinopathy (DR) (Meyer- Rusenberg et al., 2007; Qin et al, 2006), can cause pathological changes in photoreceptor and/or post-photoreceptor neurons, which ultimately lead vision losses and even total blindness. Early detection of these diseases has been recognized as a critical step in reducing the associated severe vision loss. Optical detection of abnormal structural changes of the retina, such as retinal nerve fiber layer thickness (Machida et al., 2008; Mohammadi et al., 2004), provides useful information for disease detection and diagnosis. However, structural and functional changes of the retina are not always correlated (Falsini et al., 2008; Hogg and Chakravarthy, 2006; Oishi et al., 2008). Electroretinogram (ERG) and relative multifocal ERG (Hood et al., 2003) and pattern ERG (Ventura et al., 2005) can provide objective assessment of retinal function. ERG measurement of stimulus-evoked retinal activation is sensitive and practical for clinic application. Recent ERG investigations have demonstrated the potential for early detection of AMD (Falsini et al., 1999), glaucoma (Ventura et al., 2006), DR (Ng et al., 2008), and other diseases. Early detection of eye diseases can substantially enhance opportunities to prevent or treat visual impairments. There is ample evidence that functional deterioration may precede clinically detectable fundus changes. The electroretinogram (ERG) measurement can provide important information for objective evaluation of retinal neural function, but relatively low spatial resolution and lack of direct morphological information make it difficult to provide accurate identification of localized retinal dysfunction.

Optical recording of neural activity, i.e., electrophysiological response, can offer high spatial resolution, wide field of view and 3D imaging capability. Optical imaging of transient intrinsic optical responses (lORs) in activated neural tissues can eliminate the requirement of exogenous dyes or indicators. In general, both stimulus- evoked retinal neural activity and corresponding hemodynamic and metabolic changes may produce IORs. While hemodynamic and/or metabolic changes associated IORs are relatively slow (slow IOR) and cannot directly track electrophysiological response; fast IOR (FIOR), most likely the result of dynamic volume changes corresponding to ion and water flow across the cell membrane of activated neuron, have time courses comparable to electrophysiological dynamics. Past investigations have demonstrated the feasibility of imaging slow IORs (Abramoff 2006; Tsunoda 2004), which were most likely related to transient changes of blood flow, hemoglobin oxygenation or metabolic processes of the visual system. Fast light scattering responses have been observed in intact and isolated photoreceptors (Harary 1978; Kahlert 1990; Pepperberg 1988) through fast photodiode recording. Those signals might be specifically associated with the fast phototransduction process, and may provide useful information for functional assessment of the photoreceptors. FIORs closely associated with action potentials and postsynaptic potentials were also observed in stimulus activated neural tissues (Cohen 1968; Tasaki 1968). Several biophysical processes (Foots 2007), e.g. neurotransmitter secretion (Salzberg 1985), reorientation of membrane proteins and phospholipids (Pepperberg 1988; Tasaki 1968; Landowne 1993), and refractive index change of neural tissues (Stepnoski 1991), have been proposed as possible mechanisms of the FIORs. Optical imaging of stimulus-evoked FIORs provides new methodology for measurement of retinal function with high spatial resolution. However, the practical application of FIORs has being challenged by low signal-to-noise ratio (SNR), non specificity, and complex signal polarities, i.e., positive and negative responses, of these intrinsic optical signals. Previous investigations have reported inconsistent, in terms of signal polarities and time courses, intrinsic optical responses in visible light activated photoreceptors or intact retina. Both positive and negative intrinsic optical responses have been observed with fast photodiode systems (Harary 1978; Pepperberg 1988; Akimoto 1982), and recently emerging functional optical coherence tomography (OCT) (Srinivasan 2006; Bizheva 2006; Yao 2005). Recent experiments indicated that the SNR of optical measurements of FIORs associated with neural activation could be substantially improved through optimized near infrared (NIR) light illumination and improved spatial resolution, allowing high performance optical imaging of fast intrinsic optical responses with single pass measurements (Yao 2006). Dark-field and polarization- sensitive imaging could further improve the sensitivity of optical detection of retinal activity (Yao 2006). Therefore, the art is lacking methods and apparatus for noninvasive measurement of stimulus-evoked activity of the photoreceptors and post-photoreceptor neurons. Such methods are needed for early detection and diagnosis of disease states and conditions impacting the retina. SUMMARY The present disclosure provides for the use of FIORs for noninvasive measurement of stimulus-evoked activity of the photoreceptors and post-photoreceptor neurons. FIORs have time courses comparable to ERG response of the retina, with sub-cellular resolution. Since FIORs are derived from the NIR light images of the retina, FIOR measurement provides concurrent information of the retinal structure and function. Such structural and functional measurement allow for improved diagnosis of disease states and conditions impacting the retina and provide a novel platform for studying retinal structure and function.

The present disclosure provides methods of diagnosis of a variety of disease states and conditions characterized by decreased retinal function and damage to the retinal structure. Such disease states and conditions, include, but are not limited to, AMD, glaucoma, diabetic retinopathy. In addition, the present disclosure provides methods for monitoring the progress of a disease state or condition characterized by decreased retinal function and damage to the retinal structure in an individual. Such monitoring may be used in conjunction with treatment or prevention strategies to monitor the effectiveness of such strategies. Furthermore, the present disclosure provides methods for identifying new therapeutic targets and diagnostic markers for use in the treatment and/or prevention of disease states and conditions characterized by the above-listed conditions. Apparatus for carrying out such methods are also disclosed. Such methods and apparatus have not been heretofore appreciated in the art.

The present disclosure demonstrates the following:

1) Optical imaging of stimulus-modulated neural activity in isolated retina. We validated NIR light imaging of stimulus-modulated physiological activities in isolated frog retina using transient intrinsic optical responses (TIORs). This work demonstrates the potential of FIORs for concurrent assessment of stimulus-evoked physiological dynamics of photoreceptors and post-photoreceptor neurons by controlling the stimulus strength.

2) Optical imaging of multifocal stimulus-evoked neural activity in isolated retina. Using a microlens array based visible light stimulator, we validated NIR imaging of neural activity in isolated frog retina activated by a patterned stimulus. This work demonstrates the potential of FIORs for rapid, parallel assessment of multiple retinal areas.

3) Depth-resolved imaging of stimulus-evoked neural activity in isolated retina. We validated depth-resolved enface imaging of stimulus-modulated physiological activities in isolated frog retina using transient intrinsic optical responses (TIORs). This work demonstrates the potential of FIORs for direct, three-dimensional (3D) mapping stimulus- evoked physiological dynamics of photoreceptors and post-photoreceptor neurons by depth- resolved imaging.

4) Optical imaging of stimulus-evoked neural activity in intact eye. Using a fundus imager with high-speed CCD (120 Hz) cameras, the present disclosure demonstrates validation of NIR light imaging of FIORs in intact (but isolated) frog eye. This work demonstrates the potential of FIORs for noninvasive evaluation of retinal function in vivo.

5) Time-domain and frequency-domain analysis of FIORs. Functional changes of stimulus-activated retinal cells can be detected by comparison of NIR light images recorded at different times. We validated dynamic reference processing to reduce the effect of slow IORs on the functional images of FIORs. Fast Fourier transform (FFT) analysis of the optical images demonstrates potential of FIORs for assessment of retinal oscillatory response.

6) Inventions for optical imaging of stimulus-evoked neural activity for the in vivo eye. There are disclosed herein full-field and multifocal OCT systems for diagnosing disease states in the retina using the principles stated herein.

The teachings of the present disclosure are applicable to all disease states and conditions characterized by decreased retinal function and damage to the retinal structure. Such disease states and conditions, include, but are not limited to, AMD, glaucoma, and Diabetic Retinopathy. Therefore, the present disclosure provides new therapeutic targets and diagnostic markers for the treatment and/or prevention of disease states and conditions characterized by the above-listed conditions, and the diagnosis of such disease states and conditions.

BRIEF DESCRIPTION OF THE DRAWINGS

The patent or application file contains at least one photograph executed in color. Copies of this patent or patent application publication with color drawings will be provided by the Office upon request and payment of the necessary fee.

FIG. l(a) illustrates an alternate embodiment of a device for in vitro investigation of dynamic IORs in the isolated retina 6. The embodiment illustrated was used to collect the data shown in figures 16-18. A NIR light flood-illumination microscope was constructed to measure dynamic IORs associated with retinal activation (Fig. Ia) with a 1OX (NA - 0.3) objective 3 to achieve the required axial resolution. In principle, the axial resolution, i.e., the depth of field, of the 1OX (NA = 0.3) objective is about 10 μ m, and thus allows depth- resolved enface imaging of IORs from different retinal layers. During the experiment, the retina 6 was illuminated continuously with NIR light 9 for recording transient IORs, and a visible light flash was used for retinal stimulation. During the measurement, isolated frog retina was illuminated continuously by the NIR light 9 for recording of stimulus-evoked

IORs. The visible light stimulator was used to produce a visible light flash for retinal stimulation. Concurrent ERG measurement 12 was conducted to record electrophysiological responses associated with retinal activation, At the dichroic mirror (DM) 8, visible stimulus light was reflected and NIR recording light was passed through. The eyepiece camera 13 was used to adjust visible light stimulus aperture at the retina. In order to ensure light efficiency for intrinsic optical signal imaging, the beam splitter (BS) 4 was removed from the optical path after adjusting the visible light stimulator 11. The NIR filter 2 was used to block visible stimulus light, and allow the NIR probe light to reach the CCD/CMOS camera 1. The NIR light was produced by using a halogen lamp with a band-pass filter (wavelength band: 800-1000 nm). The visible light stimulator was a fiber-coupled white light emitting diode (LED) with central wavelength at 550-nm (wavelength band: 450-650nm). At the retina, the diameter of the stimulus aperture was -60 μ m. By adjusting the NIR light imaging depth relative to retinal surface, images were selectively recorded from photoreceptor, inner nuclear (i.e., middle), and ganglion layers of the retina. Images may be recorded with a CCD camera. In one embodiment, the CCD camera was a 14 bit CCD camera (PCO1600, PCO AG, Kelheim, Germany). The CCD camera has 2 GB built-in random-access-memory (RAM) for fast image recording with a transfer speed of 80 MB/s. Although the camera has relatively high resolution (1600 x 1200 pixels), it was often used at a lower resolution employing pixel binning for high frame rate recording. The CCD images presented in this article were recorded with a speed of 80 frames/s, and each frame consists of 320 x 240 pixels. A 10 bit CMOS camera (PCO1200, PCO AG, Kelheim, Germany) was also used to characterize the ON and OFF responses of the IORs associated with the step light stimulus. The CMOS camera also has 2 GB built-in RAM for fast image recording with a transfer speed of 820 MB/s. Because of the ultrafast transfer speed of the CMOS camera, intrinsic optical signal images could be collected with high frame speed with sufficient exposure time to ensure image quality. The CMOS images presented in this article were recorded with a speed of 1000 frames/s, and each frame consists of 160 x 120 pixels. The CMOS camera allowed characterization of fast intrinsic optical responses with millisecond temporal resolution and micrometer spatial resolution. Fig. l(b) is a schematic diagram of the flood-illumination imager for IOR imaging of intact frog eye. During the measurement, the retina was illuminated continuously by the NIR light for recording of stimulus- evoked IORs. The visible stimulus light was used to activate the retina. At the dichroic mirror (DM) 8, visible stimulus light was reflected and NIR recording light was passed through. BS is a 50/50 beam splitter. The NIR filter 2 was used to block reflected visible stimulus light, and allow the NIR probe light to reach the CCD camera. The lenses 3, 13, 14 have focal lengths of 50, 60 and 40 mm respectively. FIG. 2 contains M-sequences for simultaneous depiction of temporal and spatial dynamics of the intrinsic optical responses at a selected line area across the retinal area covered by the visible light stimulus.

FIG. 3 shows high temporal resolution visualization of stimulus evoked FIORs in frog retina.

FIG. 4 depicts the effects of stimulus intensity on the spatiotemporal dynamics of FIORs.

FIG. 5 shows stimulus evoked intrinsic optical responses from the photoreceptor layer with single pass imaging. FIG. 6 is functional imaging of the inner retina.

FIG. 7 contains functional imaging of the ganglion layer.

FIG. 8 contains averaged intrinsic optical images of retinal activity at three levels: photoreceptors, inner layer, and ganglion cells.

FIG. 9 is functional imaging of FIORs in activated frog retina at two levels of stimulus strength.

FIG. 10 is a raw photo of the stimulus and pattern 19 and the retina 20, along with functional imaging of FIORs 21, 22 using a microlens array.

FIG. 11 is functional imaging of FIORs using a microlens array.

FIG. 12 is functional imaging sequence of optical responses (in frog retina) with lower strength stimulus compared to FIG. 14.

FIG. 13 is functional imaging sequence of optical responses (in frog retina) with higher strength stimulus compared to FIG. 13.

FIG. 14 contains FIORs elicited by variable strength stimuli.

FIG. 15 depicts variation of peak amplitude and time delay of positive (associated with post-photoreceptor responses) and negative (associated with photoreceptor responses) FIORs corresponding to stimulus change. This figure is drawn based on the data presented in Table 1. Amplitudes of positive (red empty circles) and negative (blue empty circles) FIOR peaks (Bottom and left axis); times of positive (red solid squares) and negative (blue solid squares) of FIOR peaks (Top and right axis). FIG. 16(a)-(c) For each experimental measurement shown in Fig.l7(a)-(c), the frog retina was activated by a single light flash (125 ms). The stimulus intensity was equivalent to ~ 4.0 x 104 [550-nm photons]/ms-μm-2. This stimulus strength was selected to evoke both negative and positive IORs in isolated frog retina. Under this experimental condition, IORs were robust for at least 1 hour, with a stimulus interval of 2 minutes. In other words, at least 30 imaging passes could be implemented with an isolated frog retina without RPE. In order to ensure the reproducibility of the IORs, two imaging sequences were typically recorded from each retinal layer sequentially, with identical stimulus and recording parameters,

FIG. 16(d): (a-c) Averaged intrinsic optical images of the photoreceptor (a), inner nuclear (b) and ganglion (c) layers.

FIG. 17 (a)-(f) contains Intrinsic Optical Signals with the fast CMOS camera, associated with ON and OFF edges of a visible light stimulus. Figure 18 (g) represents transient intrinsic optical responses of individual pixels.

FIG. 18. Averaged intrinsic optical responses of the retinal area (40 μm x 40 μm) covered by the white block shown in Fig. 1 S Cb).

FIG. 19. is a high resolution IOR imaging of retinal neural activity in isolated eye with intact ocular optics.

Fig. 20. shows positive and negative IORs.

Fig. 21. shows dynamic differential IOR imaging is an effective way to reduce show IORs (from metabolic changes) and enhance fast IORs (from neural activity).

FIG. 22 is a schematic diagram of an electro-optic phase modulator (EOPM) 33 based OCT. NIR light is a superluminescent laser diode for low coherence imaging. Lens Ll, 12, L3, L4 and L5 45,46, 47, 48, 49 are used for light delivery and collection. NPBS is a non-polarizing beam splitter 4. A pair of glass wedges (GW) 29 is used for compensating chromatic aberration of the EOPM. Right-circular polarizer consists of plane polarizer Pl 50 and quarter-wave plate Ql 51. Quarter-wave plate Q2 52 is used to invert the polarity of the reference beam to left-circular. Polarization directions al , a2 and a3 37, 36, 34 are observed in left view. Polarization bl and b2

31,24 are observed in right and bottom views, respectively. A graphic description of the 4 phases of the EOPM in this embodiment is 33. Image plane of the retina is 26, Reference mirror is 32,

FIG. 23 is a schematic diagram of a multifocal OCT. A near infrared light (red lines) is collimated before entering the acousto-optic deflector (AOD) 38. MLA is a microlens array 39 to provide a grid of light focuses (multifocal illumination). The incident angle of the light at MLA can be controlled by the AOD (Note: a pair of green lines represents the focus change due to incident angle change provided by the AOD), and thus change the position of the focuses. Lens Ll , 12, L3, L4 and L5 53, 54, 55, 56, 57 are used for light delivery and collection, BS is a non-polarizing beam splitter. EPOM is an electro-optic phase modulator. A pair of glass wedges (GW) 29 is used for compensating chromatic aberration of the EOPM. Right-circular polarizer consists of plane polarizer Pl 50 and quarter-wave plate Ql 51. Quarter-wave plate Q2 52 is used to invert the polarity of the reference beam to left-circular. The focus plane of the microlens array, sample, reference mirror and CCD/CMOS sensor are on conjugated imaging locations.

FIG. 24 is a schematic diagram of a diffractive optics based, no-mechanical-moving-part scanner. A collimated light beam is shaped by a liquid crystal phase modulator (LCPM) 41. A corresponding modulated light pattern is produced on the later focus plane (P) 43 of Lens Ll 42, Lens L2 44 and an objective (not shown) become an infinity focus imaging system. Fl 60 and f2 61 are the focus length of lens Ll and L2.

DETAILED DESCRIPTION Definitions

"Intrinsic Optical Response" or "IOR" refers to a transient optical change in stimulus-activated neural tissue (such as visible light stimulus activated retina). In general, both stimulus-evoked retinal neural activity and corresponding hemodynamic and metabolic changes may produce IORs. While hemodynamic and metabolic changes associated IORs are relatively slow ("SIORs) and cannot directly track electrophysiological response; fast

IORs ("FIORs) are most likely the result of dynamic volume changes corresponding to ion and water flow across the cell membrane of activated neuron, have time courses comparable to electrophysiological dynamics.

"Intrinsic Optical Signal" or "IOS" can be used interchangeably with "Intrinsic Optical Response" or "IOR."

"Sample" is used interchangeably with "retina" or "retinal."

General Discussion

Near infrared (NIR) light imaging can record stimulus-evoked IORs in isolated amphibian retinas and eyes. Fast IORs have time courses that are comparable to stimulus- evoked ERG responses, and thus may be associated with retinal neural activity. NIR light imaging of fast IORs allows a new methodology for high resolution evaluation of retinal neural function, while concurrently providing high resolution imaging of morphological structure. The current disclosure describes a digital camera based optical coherent tomography (OCT) imager, with high spatial (sub-cellular) and temporal (millisecond) resolution. Unlike conventional single point scanning OCT, the camera based OCT allows simultaneous sampling of multiple retinal points, providing ultrafast ( 1000 Hz) imaging speed. The disclosed OCT is used for three-dimensional (3D) imaging and characterization of stimulus-evoked fast IORs in the retina and in vivo IOR imaging of stimulus-evoked retinal neural activity.

Fast intrinsic optical signals are tightly related to electrophysiological responses of photoreceptor and post-photoreceptor neurons in the retina. Intrinsic optical imaging of physiological responses of photoreceptors and post-photoreceptor neurons may provide important methodology for diagnosis of retinal diseases and advanced studies of retinal function. Near infrared light recording of stimulus-evoked fast intrinsic optical responses associated with retinal activation provides a new method for high spatiotemporal assessment of retinal function. Intrinsic optical imaging can provide concurrent morphological (anatomic) and functional assessment of the retina with single (or) sub-cellular resolution, over a large retinal area simultaneously.

Transient intrinsic optical responses related to retinal photoreceptor and post- photoreceptor responses can be selectively elicited and modulated by controlling the stimulus strength, either by variable stimulus intensity or stimulus duration. In order to assess localized retinal function, a visible stimulus light can be focused to the interested retinal area. Low (short duration and/or low intensity) strength post-photoreceptor response (positive optical signals first, while strengthened (increased stimulus intensity and/or prolonged stimulus duration) stimuli are required to observe robust optical response (negative optical signal) related to retinal photoreceptors. Simultaneous assessment of localized photoreceptor and post-photoreceptor responses can be achieved by using a stimulus, which is strong enough to activate robust intrinsic optical responses associated with photoreceptor activity in the central area covered by the visible light stimulus pattern. The visible light pattern can be homogeneous. In the surrounding area, nearby the edge of a homogenous stimulus pattern, intrinsic optical responses were dominated by projection of post-photoreceptor neurons. In other words, intrinsic optical responses at the retinal area covered by the stimulus pattern and surrounding area can be used to evaluate the localized photoreceptor and post-photoreceptor function, respectively.

Instead of a stimulus light with homogenous intensity distribution, a stimulus light that is heterogenous (e.g., with gradient, either linear or nonlinear or Gaussian) can be used to do simultaneous assessment of localized photoreceptor and post-photoreceptor function. With a stimulus which is strong enough to activate robust intrinsic optical responses associated with photoreceptor activity in the central area covered by the visible light stimulus pattern, post-photoreceptor responses will dominate the surrounding area. The contribution ratio of the photoreceptor and post-photoreceptor responses to the intrinsic optical signals will be gradually changed from center of the stimulus pattern to surrounding area. In addition to stimulus-modulated activation of intrinsic optical responses associated with retinal photoreceptor and post-photoreceptor neurons, depth-resolved imaging can also separate stimulus-evoked intrinsic optical responses from photoreceptor and post- photoreceptor neurons. The established 3D ophthalmoscopic imaging techniques, such as optical coherence tomography (OCT) and laser scanning ophthalmoscopes, can be readily adapted/modified to do noninvasive, accurate assessment of localized retinal function using the fast intrinsic optical responses in activated retina.

For in vivo detection, dynamic blood changes may contribute to the transient optical responses during retinal activation. Because the transient optical responses associated with hemodynamic (and metabolic) changes are relatively slow, digital filter methodology can be used to block (or selectively pick up) the effects of relatively slow intrinsic optical responses from hemodynamic changes.

In order to investigate the IORs with opposite (i.e., positive and negative) polarities, it is possible to separate IOR patterns with positive (Fig. 22a) and negative (Fig. 22b) optical changes. The dynamic fractional ratios of the activated retinal areas with positive and negative optical signals were also quantitatively analyzed (Fig. 22c). Differential IOR images (Fig. 22a) were used to minimize the effect of slow optical responses on the fast IORs. The construction of differential IOR images were calculated as follows:

IORf (_Xiy) = h(x.y)^~zJj-ef(x.v)

where / ₁( x, y) is the intensity value of a pixel (x, y) at a time point t; / _ref ( x, y) is the averaged intensity value, which can be quantified by:

It served as the dynamic reference baseline for the calculation of the differential IOR at pixel (x, y). In other words, the averaged pixels values of m frames recorded before the time point t is used as a reference baseline to calculate the differential IOR. Based on the differential images (Fig. 23a), percentage ratio of the image area with optical response IOR > 2.5% Δ I/I was calculated to show dynamic fractional change of the activated retinal area (Fig. 23b). A magnitude threshold, IOR > 2.5% Δ I/I, was used to reduce the effect of background noise.

Given the fact that the intrinsic optical responses associated with hemodynamic (and metabolic) changes related can spread to a relatively larger area, spatially differential detection can be used to assess the contribution/effect of the hemodynamic (and metabolic) changes. In other words, intrinsic optical responses from the area relatively far away from the stimulus pattern will represent the hemodynamic (and metabolic) changes. These hemodynamic (and metabolic) changes can be simultaneously recorded by the intrinsic optical imager. These slow, well spread, intrinsic optical responses can be used to assess the hemodynamic (or metabolic) performance of the retina, or can be subtracted from the intrinsic optical responses recorded at the stimulus covered (near surrounding) area to cut off the effects of hemodynamic (or metabolic) changes on the assessment of photoreceptor and post-photoreceptor function. Fast intrinsic optical signals track the time courses of corresponding electrophysiological, i.e. ERG, response. Although the biophysical mechanisms of the observed intrinsic optical responses associated with retinal activation are not fully understood, previous studies with other neural tissues have suggested several possible processes (Foust 2007), such as neurotransmitter secretion (Salzberg 1985), reorientation of membrane proteins and phospholipids (Cohen 1968; Tasaki 1968; Landowne 1993), and refractive index change of neural tissues (Stepnoski 1991), to produce transient optical changes during neural activation. FIORs most likely result from dynamic volume changes of activated neurons corresponding to ion and water flow across the cell membrane (Yao 2003; Yao 2005). Water influx in response to ionic currents through gated channels during depolarization causes cellular swelling that can produce changes in tissue light scattering (Kim 2007; Tasaki 2001; Yao 2003; Cohen 1973), and also polarization changes (Yao 2005).

Both positive- and negative-going transient optical changes were observed. Given that nonlinear amplification mechanism in the retina (Baylor 1974; Mizunami 1990; Dong 2000), the positive- going responses activated by low light stimulus likely result from second- or third-order neurons. Negative- going responses elicited by strengthened stimuli likely reflect increasing contribution of dynamic intrinsic optical responses associated with phototransduction procedures in activated photoreceptors (Harary 1978; Pepperberg 1988). In fact, previous optical measurement with single channel detector, i.e. a fast photodiode, has disclosed negative-going optical responses from single or multiple photoreceptors activated by visible light flashes (Harary 1978; Pepperberg 1988). The complex kinetics of the intrinsic optical responses evoked by different stimuli (FIG.2) suggested variable contributions of the negative and positive responses associated with activities of photoreceptors and inner neurons, respectively. Dynamic patterns and spreading waves of fast neural activity may reflect involvements of the feedback mechanisms, e.g. light adaptation and center-surround antagonism, of the retina. Intrinsic optical imaging of FIORs is comparable to traditional ERG measurement of retinal function. However, intrinsic optical imaging provides feasibility of noninvasive imaging of retinal function with high spatial resolution in three dimensions.

At the photoreceptor layer, negative IORs dominated the center area illuminated by the stimulus light spot, while positive IORs dominated the surrounding area. In contrast, at inner nuclear and ganglion layers, positive IORs dominated the center area covered by the stimulus light spot, and negative IORs were mainly observed in the surrounding area.

Different center- surround distributions of the positive and negative IORs at the photoreceptor and inner retinal layers support the hypothesis that the negative IORs are mainly associated with photoreceptor response and the positive IORs result primarily from dynamic changes of post-photoreceptor response during retinal activation. In principle, when the NIR probe light is focused at the photoreceptor layer, intrinsic optical signal image should be dominated by the IORs produced by the photoreceptors. Although cross-talk response (defocused transmitted or scattered light) of the IORs from other layers may also enter the CCD/CMOS imager, these light photons should be spread blurred) into a relatively larger area. In comparison, the IORs directly initiated from the photoreceptor layer are in focus. On the other hand, when the NIR probe light is focused at the inner retinal layers, the intrinsic optical signal image should be dominated by the IORs initiated at the corresponding retinal depth. Thus, the positive IORs in the surrounding area of the photoreceptor layer may result from the defocused IORs associated with the responses of inner retinal neurons; while the negative IORs in the surrounding area of the inner retinal layers may result from the defocused IORs associated with photoreceptor response. In comparison with the inner nuclear layer, the negative IORs at the ganglion layer spread into a relatively larger area, but with decreased signal amplitude. This agrees with the fact that the ganglion layer has a relatively larger distance from the photoreceptor layer, and thus the light from the photoreceptor layer may be defocused (blurred) over a relatively larger area. Moreover, the optical wave guiding property of photoreceptors and other cells may also produce cross-talk of the IORs among different retinal layers. The optical wave-guiding property of the retina has directional dependence, i.e., optical Stile-Crawford effect, and thus may also affect the center- surround distribution of the IORs.

From the above discussion, it is likely that the major part of the positive IORs observed at the photoreceptor layer, particularly at the retinal area outside of the stimulus light spot, may result from cross-talk IORs from inner retina. However, both positive and negative IORs, particularly inside the stimulus area, may also relate to phototransduction procedures. Previous studies with isolated photoreceptor outer segments and isolated retinas have demonstrated transient IORs associated with phototransduction. Both binding and release of G-proteins to photo-excited rhodopsin may contribute to the IORs. While the negative IORs may result from the binding of photoexcited rhodopsin to G-proteins; some part of the positive IORs may relate to the dissociation of the complex upon GDP/GTP exchange. The transient optical patterns of the IORs at the photoreceptor layer may partially result from antagonistic contributions of the negative and positive IORs associated with dynamic redistribution of G proteins during retinal activation. Further study is required for investigating possible effect of center- surround antagonism of the retina on the observed center- surround distribution of IORs with positive and negative polarities. Although biophysical mechanisms of the observed fast IORs at inner retinal layers are not well known, previous studies with eyecup slices have demonstrated transient scattering changes at inner retina. The studies with other neural tissues have suggested several possible processes, such as neurotransmitter secretion, reorientation of membrane proteins and phospholipids, and refractive index change of neural tissues, to produce transient IORs during neural activation. It is likely that the fast IORs may, at least partially, result from dynamic volume changes of activated neurons corresponding to ion and water flow across the cell membrane. Methods of Diagnosis

The present disclosure also provides methods for diagnosis for determining if a subject is suffering from or at risk for disease states and conditions associated with or characterized by reduced retinal cell function. Such disease states and conditions, include, but are not limited to, AMD, glaucoma, and diabetic retinopathy. In one embodiment, the methods for diagnosis involve the use of homogenous light or heterogenous light.

In another embodiment, diagnostic methods involve the use of a single beam of light delivered to the retina. In another embodiment, diagnostic methods involve the use of a microlens array to deliver a single beam of light to multiple regions of the retina.

In another embodiment, diagnostic methods involve the use of a beam of light focused on or more layers of the retina including, without limitation, the photoreceptor layer, the inner layer (including, without limitation, horizontal, bipolar, and amacrine) and the ganglion cell layer.

In another embodiment, diagnostic methods involve the use of one or more constant beams of light.

In another embodiment, diagnostic methods involve the use of one or more transient beams of light. In another embodiment, diagnostic methods involve the use of one or more beams of light of changing intensity or wavelength.

In another embodiment, diagnostic methods involve the use of different intensities and wavelengths of light to detect functional differences in different layers of the retina, including greater intensities for photoreceptors and lesser intensities for non-photoreceptors. In another embodiment, diagnostic methods involve the use of dynamically filtering slow intrinsic optical responses.

In another embodiment, diagnostic methods involve the use of one or more IOR combined with hemodynamic (and metabolic) changes.

In another embodiment, diagnostic methods involve the use of one or more IOR with an ERG response.

EXAMPLES

Results and Discussion

Figure 2

When rapid, such as 1 ms and 10 ms, visible light flashes were used to activate the retina, stimulus evoked FIORs were dominated by positive signals in the area covered by the visible light stimulus pattern (FIG.2 c_; d). In contrast, prolonged stimuli activated strong negative-going responses (FIG.2 e). The negative-going responses reduced gradually if the retina was stimulated with repetitive prolonged stimuli (FIG.2 f). However, robust, positive responses were remained consistently. Functional images of FIORs in frog retina activated by white light flash with circular aperture in FIG. 2 subparts: (a) Representative raw picture of the isolated retina, (b) Enlarged picture of the third frame of sequence e. The retina was activated by a 1 ms (c); 10 ms (d); 100 ms (e) visible light flash. Functional imaging sequence (f) was recorded after sequence (e), under same stimulation condition as sequence

(e). Each image of Figs. 2 (c-g) was an average over 80 frames within 1 s. First two images of each imaging sequences show the 2 s pre-baseline background. The white line indicates the retinal area for high temporal resolution M-sequence visualization of FIORs in FIG. 3.

Figure 3

In FIG. 3, the M- sequences (FIGS.3a-d) correspond to the central retinal area (white line marked retinal area in FIG. 2a) covered by the stimulus light, and the functional images (FIG.3e to 3h) indicate averaged FIORs over 25 ms, following the delivery onset of visible light stimulus. The bottom series of traces in FIGS. 3i to 3k are aligned with the functional images directly above, with the same stimulus. FIGS. 3a to 3d are M-sequences of the retinal area marked by the white line in FIG. 2, corresponding to functional image sequences c, d, e, and f of figure 2, respectively. Vertical line indicates the delivery time of visible light stimulus, (e), (f), (g), and (h) show high temporal resolution functional images of FIORs, which were averaged over 25 ms after the onset of visible light stimulus delivery, corresponding to the image sequences c, d, e, and f of figure 3, respectively. Figures (i), (j), (k), and (1) indicate temporal changes (corresponding to M-sequences a, b, c and d, respectively) of averaged FIORs over retinal area covered by the stimulus light. 0.5 s pre- stimulus baselines are shown here. Vertical line indicates the delivery time of visible light stimulus.

From FIGS. 2 and 3, it was observed that negative responses were well confined in the area covered by the visible stimulus, but positive responses can spread to surrounding area, at least 50 μm beyond the edge of the stimulus spot. Although negative responses dominated the central area of the functional images (FIG. 2e), a rapid, but small amplitude, positive signal was observed before the strong negative- going responses (FIGS, c and 3g) with high temporal resolution (25 ms). The rapid positive response reached the peak within 50 ms after the delivery (onset) of stimulus light. Figure 4

Consistent positive FIORs (FIG. 4a) were observed when the retina was activated by a low strength stimulation. However, negative optical responses would dominate the central area of activated retina with either increased stimulus intensity (FIG. 4b) or prolonged delivery duration (FIGS. 4c and 4d). A rapid (peak: < 100 ms), small amplitude, positive peak was observed when the retina was activated by a moderate power intensity (0.08 μW), but long stimulus duration (1000 ms) (FIG. 4b). The rapid positive response reached its peak with time course similar to corresponding a-wave of ERG response, and was followed by a strong negative-going signal. The rapid positive peak disappeared when the stimulus intensity was enhanced to 0.7 μW (FIG. 4c). However, a clear OFF change (flexural point) with time course similar to d- wave of ERG response, and enhanced edge response was observed (FIGS.4c and 4f). With same stimulus duration, increased stimulus intensity elicited dynamic FIORs with increased speed (sharper slope), and advanced amplitude peaks. Functional images of FIORs activated by variable stimulus duration and intensity. In these experiments, the retina was activated by visible light flashes of 1 ms_: 0.08 μW (FIG. 4a), 1 s, 0.08 μW (FIG. 4b), 1 s, 0.7 μW (c), and 1 ms, 12.1 μW (d). (e) - (h) are temporal changes of averaged FIORs over the stimulus covered (black traces), stimulus uncovered (red traces) areas, and ERG responses (grey traces), corresponding to the M-sequence a-d, respectively. The vertical lines indicate the onsets of the stimulation flashes. Figure 5

At the photoreceptor layer, rapid intrinsic optical responses were observed in the area covered by the visible light spot (FIG.5). (a) Representative raw image of retinal photoreceptor layer, (b) Picture of the stimulus pattern, (c) Intrinsic optical responses. The frog retina was activated by a 125 ms, visible light flash delivered with 2 s pre-stimulus baseline recording. Each illustrated frame is an average over a one second interval, (d) Intrinsic optical responses of the area covered by the white block in the third function image of sequence (c). First 500 ms responses are showed after the visible light stimulus. Each illustrated frame is an average over 100 ms interval, (e) Fast optical responses of representative local areas with 5 μ. m x 5 μ m resolution (average of 25 pixels). Lines I₁ 2, 3 and 4 indicate the optical response at retinal areas marked by the black arrows in the first frame of sequence (d). Lines 5, 6, and 7 indicate the optical responses at retinal areas marked by the black arrows in the second frame of sequence (d). Lines 8, 9, 10, and 11 indicate the optical responses at retinal areas marked by the purple arrows in the second frame of sequence (d). Line 12 indicates averaged optical responses at retinal area covered by the visible light stimulus. Line 13 indicates averaged optical responses at retinal area covered by the red block in the third function image of sequence (c), ERG is corresponding electrophysiological change. Vertical line indicates the delivery time of light stimulus. From FIG.5 e, one can see that the rapid intrinsic optical responses can directly track the time courses of a- and b-waves of corresponding ERG response. These rapid intrinsic optical responses reached the amplitude peak within 50 to 100 ms (lines 1-4 and 8, FIG.5 e). Most of the central area covered by the visible light stimulus quickly changed polarity to negative, and reached another amplitude peak or flexural point with similar time course of b-wave of ERG response. Negative ongoing optical responses, with amplitude peak or flexural point with similar time course of b-wave, were also observed (lines 5-7, FIG. 5e). From the averaged optical signal (line 12, FIG.5 e) of the stimulated retinal area (50 μ m diameter), the rapid positive peak with time course of a-wave could be still clearly observed, and was followed by a negative response. However, the amplitude of the averaged intrinsic optical signal was one fold of smaller in comparison with the localized optical responses (lines 1-11, FIG. 5e) because of the polarity, i.e. positive and negative, changes of the signals in adjacent areas (FIG. 5d). At the edge area of the stimulus pattern, robust enhanced positive optical responses were observed, and the time of amplitude peak was also similar to the peak of b-wave (lines 5-7). Slow intrinsic optical response was observed in surrounding area with peak at -3.5 s after the stimulus delivery (line 13, Fig 5. e).Slow components, which could not resettled back to the pre-stimulus baseline during the recording period, were also recorded in the stimulus light covered area (Fig 5 c and d). Figures 6 and 7 In the following example (FIGS. 6 and 7), the rapid intrinsic optical responses tightly correlated to the a-wave of ERG response disappeared when the IR imaging plane was focused to the middle of the retina (FIG.6) or ganglion (FIG.7) layers. Both positive and negative intrinsic optical responses, with time courses similar to the b-wave of ERG response, were observed from inner retina and ganglion layers. However, fast imaging sequences disclose distinct patterns of neural activity at the inner (FIG.6) and ganglion layer (FIG.7). While intrinsic optical imaging of inner retina disclosed soma and synapse alike patterns of postsynaptic neurons (Fig 6. b), dendrite alike pattern of intrinsic optical signals was observed at the ganglion layer (FIG. 7. b). In Figure 6 the following applies, (a) Each illustrated frame is an average over a one second interval, (b) Intrinsic optical responses of the area covered by the white block in the third function image of sequence (a). First Is responses, flowing the visible light stimulus, are showed. Each illustrated frame is an average over 100 ms interval, (c) Representative raw image of inner retina, (d) Line 1-6 indicate fast optical responses of representative local areas with 5 μ m x 5 μ, m resolution. Line 7 indicates averaged optical responses at retinal area covered by the visible light stimulus. ERG is corresponding electrophysiological change. Vertical line indicates the delivery time of light stimulus.

In Figure 7 the following applies, (a) Each illustrated frame is an average over a one second interval, (b) Intrinsic optical responses of the area covered by the white block in the third function image of sequence (a). First Is responses, flowing the visible light stimulus, are showed. Each illustrated frame is an average over 100 ms interval, (c) Representative raw image of ganglion layer, (d) Lines 1 -7 indicate fast optical responses of representative local areas with 5 μ m x 5 μ m resolution. Line 9 indicates averaged optical responses at retinal area covered by the visible light stimulus. ERG is corresponding electrophysiological change. Vertical line indicates the delivery time of light stimulus. Figure 8

In figure 8 the following applies, (a) Functional images of photoreceptor layer (b) Functional images of inner retina, (c) Functional images of ganglion layer. The frog retinas were activated by a 125 ms, visible light flash delivered with 2 s prestimulus baseline recording. Functional images show averaged optical responses of 6 dynamic imaging sequences recorded from 3 frog retinas under the same experimental condition. The averaged functional images further confirm that at the stimulus spot covered area photoreceptor layer was dominated by negative optical responses, inner and ganglion layers were dominated by positive optical responses. However, both slightly positive and negative optical changes with complex patterns were observed in surrounding area of the activated retina

Although the biophysical mechanisms of the observed intrinsic optical responses associated with retinal activity are not well understood, previous studies with other neural tissues have suggested several possible processes (Foust and Rector, 2007), such as neurotransmitter secretion (Salzberg, et al., 1985), reorientation of membrane proteins and phospholipids (Cohen et al., 1968; Landowne, 1993; Tasaki et al., 1968), and refractive index change of neural tissues (Stepnoski et al., 1991), to produce transient optical changes during neural activation. The present disclosure supports that the fast intrinsic optical responses may result from dynamic volume changes of activated neurons corresponding to ion and water flow across the cell membrane (Yao et al., 2005a; Yao et al., 2003). While intrinsic optical imaging of photoreceptor layer disclosed rapid intrinsic optical signals tightly coupled with a- and b-waves of ERG response, functional imaging of inner retinal layers disclosed optical responses with time course similar to the b-wave (peak: ~250 ms). The range (peak: 50-100 ms) of the a-wave related intrinsic optical signals may reflect the existence of different types of photoreceptors or varying contributions from secondary and third neurons. At the edge of the stimulus activated retinal area (FIG.5 c and d, and Fig 8 a), enhanced positive optical responses were observed, and the time of amplitude peak was also similar to the peak of b-waye. Since these areas were not directly covered by the visible light stimulus, these signals might reflect projection linkages of postsynaptic neurons. The gradient patterns of intrinsic optical responses and dynamic changes over time might reflect the involvement of retinal feedback mechanisms, such as center-surround antagonism for edge enhancement (Jacobs and Werblin, 1998). Slow components of intrinsic optical responses were also observed. These slow optical responses could last at least several seconds, and may reflect stimulus associated metabolic changes of the retina.

Rapid intrinsic optical responses tightly correlated to the a-wave of ERG response were not detected from the intrinsic optical images of the inner retina and ganglion layer. The rapid intrinsic optical response of photoreceptor layer is tightly associated with fast responses of the photoreceptors. A variety of electrophysiological experiments have been conducted to study the a-wave of ERG responses, and previous investigation suggested that the a-wave is related to the early stages of phototransduction (Barraco et al., 2006). The observed intrinsic optical responses (FIG.5) tightly correlated to the a-wave of ERG response might result from locally integrated signals of early photoreceptors and secondary neurons. Previous studies have demonstrated the existence of intrinsic optical signals correlated with phototransduction processes in visible light activated photoreceptors (Harary et al., 1978; Kahlert et al., 1990; Pepperberg et al., 1988), but these studies failed to detect rapid optical response directly correlated with a-wave of ERG response. The most likely reason was that previous measurement with single channel detector, i.e. photodiode, recorded an assumed signal of stimulated retina, and lacked the necessary spatial resolution to disclose localized rapid intrinsic optical responses associated with a-wave. Following the a-wave related responses, negative response dominated the retinal area covered by the visible light stimulus. These slow negative optical responses might result from the transmission change of photoreceptor during later stages of phototransduction (Harary et al., 1978).

Although both intrinsic optical images of inner retina and ganglion layers disclosed b-wave related responses, the patterns of these intrinsic signals were different. While intrinsic optical imaging of inner retina disclosed soma and synapse alike patterns of postsynaptic neurons, a dendrite like pattern of intrinsic optical signals of ganglion layer might reflect the neural activity of ganglion cells. Previous investigations suggested that b- wave of ERG response might mostly result from postsynaptic neurons, such as ON-bipolar (Green and Kapousta-Bruneau, 1999; Karwoski and Xu, 1999; Sieving et al., 1994) and Mύller (glial) cells (Miller and Dowling, 1970). However, recent study suggested that third- order neurons might also make significant contribution to the amplitude and kinetics of b- wave (Dong and Hare, 2000). This may be the reason why fast intrinsic optical responses with time course similar to the b-wave of ERG response can be observed in both inner retina and ganglion layer. However, based upon current observations, one can not reject the possibility that the depth resolution of the imaging system used is limited for accurate differentiation of the optical signals from different layers.

The practical application of intrinsic optical signals has been challenged by low reproducibility, non specificity, and complex signal polarities, i.e. positive and negative responses, of these intrinsic optical signals. Previous investigations have reported inconsistent, in terms of signal polarities and time courses, intrinsic optical responses in visible light activated photoreceptors or intact retina. Both positive and negative intrinsic optical responses have been reported with fast photodiode systems [Harary 1978; Akimoto 1982; Pepperberg 1988], and recently emerging functional optical coherence tomography (OCT) [Srinivasan 2006; Bizheva 2006; Yao 2005 Appl. Opt.]. The complex and inconsistent reports of intrinsic optical signals may result from differences of retinal species, recording systems and experimental conditions. Previous studies suggested that transient intrinsic optical signal could be affected significantly by detection angle [Pepperberg 1988] and numerical aperture (NA) of the optics lens [Harary 1978]. Because of the complex, layered structure of the retina, the angle- and NA-dependent optical changes support the hypothesis that the positive- and negative-ongoing components of stimulus evoked intrinsic optical signals may result from different retinal layers, and the observed optical changes can be assumed signals of these positive and negative responses over the whole depth of the retina.

It is well known that ERG is an integral measurement of electrophysiological responses over the whole depth of the retina, which consists of multiple functional layers and cells. Previous studies indicate that the dynamics, i.e. time courses, amplitudes and polarities, of ERG response are stimulus dependent [Perlman 1983; Baylor 1974; Mizunami 1990]. While low strength visible light stimulus only elicit a positive ongoing b-wave, additional a-wave preceding the b-wave can be evoked with enhanced stimulus[PerIman 1983]. The underlying physiological mechanisms are the relatively linear response of the phototransduction process of photoreceptors, and the nonlinear characteristics of the signaling responses in post-synaptic neurons [Dong 2000; Baylor 1974; Mizunami 1990]. Previous studies have approved that the a-wave reflects the early phase response of light phototransduction of activated photoreceptor, and the b-wave reflect the dynamic neural activities of postsynaptic neurons, such as ON-bipolar cells. Here, it is likely that the components of the FIORs in retina can be modulated by stimulus strength, allowing assessment of selective retinal cells, i.e. photoreceptors and inner neurons. Figure 9

A fast near infrared light microscope with details in Yao 2006 was developed for the functional imaging work. A 4* objective (NA=O.13) was used in this study. White light flashes from a light-emitting diode (LED) with variable intensity were used to activate the retinas. Instead of the light stimulus with an iris aperture in previous studies, here a visible light stimulus with slit aperture was used to activate the retinas. Figure 9 shows functional

-6 images of a frog retina activated by visible light stimuli with optical energies of 8x 10 μJ

-2

(FIG. c) and 8x10 μJ (FIG. d), respectively. The functional images of FIORs are presented with unit of dl/I, where dl is the dynamic change of optical signal and / is the background intensity. In the stimulus light covered area, while FIORs activated by the low light stimulus were dominated by positive signals (FIG. 9 c), they could change polarity to negative when the stimulus were enhanced (FIG.9 d).

In Figure 9 the following applies, (a) Representative raw picture of the isolated retina, (b) Photograph of the white light stimulus aperture, (c) Functional imaging sequence of FIORs with low strength stimulus. The retina was activated by a white light flash with

-6 optical energy of 8x 10 μJ. (d) Functional imaging sequence of FIORs with enhanced -2 stimulus. The same retina was activated by a white light flash with energy of 8x 10 μi. Each image of (c) and (d) was an average over 80 frames within 1 s. The stimulus is delivered at the time of 2 second, and the first two images show the pre-baseline background. Given the fact of the nonlinear amplification mechanisms in the retina [Dong 2000;

Baylor 1974; Mizunami 1990], the positive-going responses activated by low light stimulus may mainly result from the second- or third-order neurons. Negative-going responses elicited by enhanced stimulus may reflect increasing contribution of dynamic intrinsic optical responses associated with light phototransduction procedures in activated photoreceptors [Harary 1978; Pepperberg 1988], Figure 10

It is also possible to employ the same principles to retinal investigation, discussed above, with a microlens array. An advantage of the microlens array is that it provides parallel investigation using the same stimulation throughout the retina at multiple sites, as shown in FIG. 10. Unlike a single point stimulation, microlens array based stimulator can provide parallel stimulation of multiple retinal areas, and thus ensure improved screening speed of the retinal function. Improved screening speed will shorten the test time, and thus reduce noises, such as effects of eye movement.

The microlens array illuminator can be used to deliver multiple stimulus focused points for parallel assessment of retinal (photoreceptor and post-photoreceptor) function over a large retinal area. Alternatively, a single focused stimulus can be scanned to assess localized retinal function over a large retinal area. The microlens array can also be concurrently used for patterned NIR light illumination to adapt previously reported virtual pinhole confocal imaging strategy (see Scanned Computed Confocal Imager, U.S. Patent 6038067) for an advanced microlens array confocal functional ophthalmoscope. In coordination with advanced computer processing, concurrent spatially registered near infrared (probe light) and visible (stimulus light) microlens array illumination/imaging can provide accurate stimulation control and reliable recording of transient intrinsic optical responses associated with localized retinal responses over a large area. Figure 12

Under lower strength visible light stimuli, the stimulus-evoked transient intrinsic optical responses results primarily from the post-photoreceptor (inner) neurons. One can expect to activate robust post-photoreceptor responses with a low strength stimulus no more than 8^χl 0^~s μJ. A functional image sequence was recorded with a visible light stimulus of 8*10^~6 μJ, as shown in FIG. 12. The retina was activated by a white light flash with optical energy of 8*10^~6 μJ. Each image was an average over 1 s interval. Light stimulus was delivered at the time indicated by the arrows, and 2 s of pre-stimulus baseline images are shown.

Figure 13

With high strength visible light stimuli, the stimulus-evoked transient intrinsic optical responses results primarily from photoreceptors. One can expect to record robust photoreceptor responses with a high strength stimulus. The following functional image sequence was recorded with a visible light stimulus of 8x10^"2 μJ, as in FIG. 14. The retina was activated by a white light flash with optical energy of 8x10^"2 μJ. Each image was an average over 1 s interval. Light stimulus was delivered at the time indicated by the arrows, and 2 s of pre-stimulus baseline images are shown. Figure 14 Using a visible light stimulator with variable light strength, it is likely that the transient intrinsic optical responses associated with photoreceptor and post-photoreceptor will have opposite (positive/increased and negative/decreased) optical changes with different time courses. FIG. 14 is an example of the transient intrinsic optical recorded from a frog retina activated by a visible light with variable stimulus strength. One can expect to activate robust post-photoreceptor responses with a low strength stimulus no more than 8x10^~5 μJ (FIG. 14 a and b). The peak response of the post-photoreceptor neurons is indicated by a green arrow (FIG. 14). When the stimulus is strengthened gradually, one will expect to see an additional amplitude peak (with opposite polarity of post-photoreceptor response), which is indicated by a Blue arrow. Left: M-sequence images of FIORs. Right: Black traces and red traces represent temporal changes of averaged FIORs of the stimulus covered retinal area (the area between the two longitudinal dashed lines indicated in the left of panel a) and not stimulus covered area, respectively. Raw CCD images were acquired at 80 frames/s. The exposure time of the CCD camera was 1 ms. Irradiances of the visible light stimuli were 8 x 10^"6 μJ (a), 8x10^~5 μJ (b), 8xlO^"4 μJ (c), 8x10^~3 μJ (d), and 8^χl 0^~2 μJ (e), respectively. The top image sequence, (a) was recorded first and the following sequences were recorded at 2-min intervals. The vertical gray lines indicate the delivery time of the stimuli. Green and blue arrows in the right panels indicate amplitude peaks of positive and negative FIORs, respectively. Table 1 and Figure 14 show corresponding variation of peak amplitudes and times of transient intrinsic optical response (FIG. 14). As given in Table 1 and shown by Figs. 14 and 15, both the amplitudes and temporal positions of the optical signals associated with post-photoreceptor responses reduce with the increase of the stimulus strength. For the optical signals associated with photoreceptor response, the peak amplitude is enhanced and time delay (relative to the stimulus delivery time) is shortened when increasing the strength.

Stimulus strength {normalized) 1 x10° 1 *10¹ 1 *10² 1 x10³ 1 x10⁴

Positive peak amplitude (Δl/I, %) 0.32 0.31 0.28 0.11 0.1 Positive peak time (ms) 980 750 270 90 10

Negative peak amplitude (Δl/I, %) -0.17 -0.26 -1.13 Negative peak time (ms) 1670 1300 950

Table 1. Peak amplitudes and times of positive optical responses (associated with post-photoreceptor neurons) and negative responses (associated with photoreceptor responses) evoked by stimuli with different strengths.

The experiments described herein show that high spatial resolution is required to differentiate transient IORs with opposite signal polarities. Recording at a low spatial resolution would pool responses of opposite polarity together and thus would reduce recorded fast IOR magnitude or even fail to record and fast IOR.

The insensitivity of the positive FIORs on stimulus strength agrees with the nonlinear amplification mechanisms of the retinal signaling in second and third neurons, and therefore it is likely the positive signals may mainly result from inner retinal neurons. With such an automatic adaptation mechanism, the photoreceptor signal can be moderated or amplified depending on the lighting conditions, allowing signaling to be less sensitive in bright light and more sensitive in low light environment. The negative FIORs, which responded sensitively to the stimulus strength, may reflect significant contribution of activated photoreceptors associated with photo transduction. In fact, previous optical measurement with single channel detector, i.e. a fast photodiode, has disclosed negative-going optical responses from photoreceptors activated by visible light flashes [Harary 1978; Pepperberg 1988]. The phenomenon that stronger stimulus evokes faster or earlier negative-going signal, as shown in figure 14, agrees well with the transduction model proposed by Lamb et al. 1992.

Moreover, shown by the images in FIG. 14, although strong optical responses were primarily defined in the retinal area covered by visible stimulus light, slight, but robust, positive optical response were observed in the surrounding area, i.e. retinal area uncovered by the stimulus light. Given that the photoreceptors in the surrounding area were not directly illuminated by the stimulus light, the observed positive signals in the surrounding area might result from the projections of the second- or third-order neurons, which further supports the hypothesis that positive signals dominate the intrinsic optical responses of inner layers of the retina. In summary, the present disclosure demonstrates near infrared light recording of fast intrinsic optical responses in activated retina. While the positive- going signal may mainly result from the responses of second- or third-order neurons in the retina, negative-going response may reflect the dynamic phototransduction in activated photoreceptors. The complex dynamics of the intrinsic optical responses evoked by different stimuli (FIG.14) suggested variable contributions of the negative and positive responses associated with activities of photoreceptors and inner neurons, respectively. Intrinsic optical imaging of FIORs is comparable to traditional ERG measurement of retinal function but is noninvasive imaging of retinal function with high spatial resolution in three dimensions. In cooperation with sophisticated design of visible light stimulation protocols, near infrared imaging of FIORs provides better understanding of dynamic information processing in isolated retina, and may also provide new methodology for noninvasive diagnosis of retinal diseases. Figure 16 16 (a): (a) Representative CCD image sequence of photoreceptor layer, without differential processing. The white spot in the second frame shows the visible stimulus pattern. At the photoreceptor layer, the diameter of the stimulus aperture was ~60 μ m. (b) and (c) intrinsic optical signals elicited by a 125 ms visible light flash. Each illustrated frame is an average over 100 ms interval (8 frames). 100 ms pre-stimulus and 500 ms after- stimulus images are shown in each imaging sequence. The imaging sequence c was recorded after the imaging sequence b, with a time interval of 2 minutes, (d) Temporal change of intrinsic optical responses. The numbered tracings 1-6 are corresponding to the arrows pointed retinal areas (average of 5 x 5 pixels) in sequence b. Vertical lines indicate the stimulus onset and offset, (e) (2.06 MB, MPEG) video showing dynamic intrinsic optical signal patterns at the photoreceptor layer. This video is from the same image sequence shown in b. 0.5 s (40 frames) pre-stimulus baseline and 5 s (400 frames) after- stimulus images are shown.

16(b): (a) Representative CCD image sequence of inner nuclear layer, without differential processing. The white spot in the second frame shows the visible stimulus pattern. At the photoreceptor layer, the diameter of the stimulus aperture was -60 μ m, (b) and (c) Intrinsic optical signals elicited by a 125 ms visible light flash. Each illustrated frame is an average over 100 ms interval (8 frames). 100 ms pre-stimulus and 500 ms after- stimulus images are shown in each imaging sequence. The imaging sequence c was recorded after the imaging sequence b, with a time interval of 2 minutes, (d) Temporal change of intrinsic optical responses. The numbered tracings 1-6 are corresponding to the arrows pointed retinal areas (average of 5 x 5 pixels) in sequence b. Vertical lines indicate the stimulus onset and offset, (e) (2.06 MB, MPEG) video showing dynamic intrinsic optical patterns at the inner nuclear layer. This video is from the same image sequence shown in b. 0.5 s (40 frames) pre-stimulus baseline and 5 s (400 frames) after-stimulus images are shown.

16(c): (a) Representative CCD image sequence of ganglion layer, without differential processing. The white spot in the second frame shows the visible stimulus pattern. At the photoreceptor layer, the diameter of the stimulus aperture was -60 μ m. (b) and (c) Intrinsic optical signals elicited by a 125 ms visible light flash. Each illustrated frame is an average over 100 ms interval (8 frames). 100 ms pre-stimulus and 500 ms after- stimulus images are shown in each imaging sequence. The imaging sequence c was recorded after the imaging sequence b, with a time interval of 2 minutes, (d) Temporal change of intrinsic optical responses. The numbered tracings 1-6 are corresponding to the arrows pointed retinal areas (average of 5 x 5 pixels) in sequence b. Vertical lines indicate the stimulus onset and offset, (e) (2.06 MB, MPEG) video showing dynamic intrinsic optical patterns at the ganglion layer. This video is from the same image sequence shown in b. 0.5 s (40 frames) pre-stimulus baseline and 5 s (400 frames) after-stimulus images are shown. 16(d) The white spot in the first frame of sequence (a) shows the stimulus pattern.

At the photoreceptor layer, the diameter of the stimulus spot was -60 μ m. Each image sequence is an average of 12 experimental passes, and each illustrated frame is an average over 100 ms interval (8 frames). 100 ms pre-stimulus and 500 ms after-stimulus images are shown in each imaging sequence, (d-f) Statistics of positive and negative optical responses at the photoreceptor (d), inner nuclear (e), and ganglion (f) layers, corresponding to the areas marked by the square blocks shown in the third frames of sequences a-c. Frames (d-f) show the statistics of retinal area with positive (> 0,3% Δ I/I) and negative (< - 0.3% Δ I/I) responses. A threshold (0.3% Δ I/I) was used to reduce the effect of background noises on the statistics. From Fig. 5 (d-f), one can see that the stimulus-activated retina area with negative optical changes consistently approach an amplitude peak within 200-300 ms after the stimulus onset, although the amplitude peak degrade from photoreceptor to ganglion layer. For the stimulus-activated retinal area with positive optical signals, the amplitude peaks are at 500-1000 ms after the stimulus onset. The ganglion layer shows the largest amount of retinal area with positive optical signals. Figure 17

In order to assess dynamic optical changes associated with retinal ON and OFF responses, a prolonged (500 ms) step stimulus was used for the experiment shown in Fig. 18. The three imaging sequences shown in Fig. 18 were recorded from the photoreceptor, inner nuclear, and ganglion layers sequentially, with a time interval of 5 minutes. The intrinsic optical images presented in this article show dynamic optical changes with unit of ΔI/I, where ΔI is dynamic optical response associated with retinal activation and I is background light intensity. The intrinsic optical signal images were reconstructed from the CCD/CMOS images as follows; 1) The pre-stimulus baseline images were averaged, pixel by pixel, and were taken as the background light intensity I of each pixel; 2) The background light intensity I was subtracted from each recorded frame, pixel by pixel, to get the dynamic change ΔI of each pixel of the images. 3) Image sequence of ΔI/I was reconstructed to show the stimulus evoked transient intrinsic optical changes in the retina. Fast IORs typically reached the amplitude peak (black arrows) within 50-200 ms after the stimulus onset. A flexural point (green arrows) was observed at the OFF edge of the stimulus, and an additional amplitude peak (purple arrows) was also occasionally observed after the stimulus offset. Figure 18 represents IORs elicited by a 500 ms step stimulus. The stimulus light intensity was 1.0 x l05 [550-nm photons]/ms' μ m-2. The raw CMOS images were captured with an imaging speed of 1000 frames/s, and thus provided a 1 ms temporal resolution to characterize the ON and OFF responses, (a-c) Representative CMOS images of the photoreceptor (a), inner nuclear (b), and ganglion (c) layers of the retina before differential processing. Each CMOS frame consists of 160 x 120 pixels. The left-top and bottom right corners are Pixel (0, 0) and Pixel (159, 119), respectively. The white spot in (a) shows the stimulus pattern. At the photoreceptor layer, the diameter of the stimulus spot was ~60 μm. (d-f) (2.3 MB MPEG) Video clips of dynamic intrinsic optical changes recorded from the photoreceptor (d), middle (e), and ganglion (f) layers. The retina was activated by a 500 ms step light stimulus. The raw CMOS images were recorded with a speed of 1000 frame/s. Each illustrated frame of the videos is an average over 10 ms interval (10 frames). 200 ms pre-stimulus and 1000 ms after-stimulus images are shown in each video. The imaging sequences d, e, and f were recorded sequentially, with a time interval of 5 minutes, (g) Transient intrinsic optical changes of individual pixels. In each subpanel, Pixel (x, y) indicates the location of each representative pixel. Black, blue, and red tracings correspond to the intrinsic optical signal images recorded from photoreceptor layer (PRL), inner nuclear layer (INL), and ganglion layer (GL). Vertical lines indicate the stimulus onset and offset. Black arrows point to ON response of the IORs corresponding to the stimulus onset. Green and purple arrows point to OFF response of the IORs corresponding to the stimulus offset. Figure 18

Black, blue, and red tracings correspond to the imaging sequences of the photoreceptor layer (PRL), inner nuclear layer (INL), and ganglion layer (GL) shown in Fig, 19 (d-f). Vertical lines indicate the stimulus onset and offset. Black arrows point to ON response of the IORs corresponding to the stimulus onset. Green and purple arrows point to OFF response of the IORs corresponding to the stimulus offset. Figure 19 shows averaged IORs of the center retinal area marked by a white square in Fig. 19 (b). With improved SNR of the averaged optical signals, one can observe that the on- going phase of the IORs began within 5 ms after the stimulus onset (Fig. 19), and both ON (black arrows) and OFF (green arrows) responses were consistently observed, particularly at the inner retinal layers. Figure 19

Raw frames were acquired with a frame speed of 120 frames/s. (a) IOR image sequence shows dynamic optical responses of the retina. Each illustrated frame is an average of 120 frames over one second interval. The visible light stimulus was delivered at time 0, and lasted for 1 s. (b) Enlarged picture of the third frame of in a. (c) M-sequence of the retinal area indicated by the white line in b. (d) Temporal changes of IORs of representative pixels. Black tracings 1-6 correspond to the areas pointed by arrowheads 1-6 in c. Gray tracing 7 is averaged signal of the image area. Note that large IORs of single pixels (tracings 1-6) can be > 10%. Transient IORs tightly correlated with ON and OFF edges of the light stimulus. Fast IORs occurred rapidly (< 10 ms) after the stimulus onset. Most of the fast IORs could reach the maximum magnitude (black arrowheads in Fig. 2Id) within 100 ms after the stimulus onset. An additional change of responses was typically observed within Is after the stimulus offset (gray arrowheads in Fig. 2Id). IORs at adjacent retinal locations could be both positive and negative going. The IORs of individual pixels (tracings 1-6 in Fig. 2Id) could often exceed 10% Δ I/I. However, when signals of an extended retinal area was averaged (tracing 7 in Fig. 2Id), the response was at least one order of magnitude smaller, due to the cancellation of positive and negative signals.

Figure 20

(a) Dynamic optical patterns of positive IORs. (b) Dynamic optical patterns of negative IORs. (c) Statistics of image area with positive and negative IORs. After the stimulus onset, early positive and negative optical response (such as the third frames of Fig. 22 a and b) had similar spatial distribution. After the stimulus offset, however, the positive signal pattern shrunk gradually (Fig. 3 a), while the negative signal pattern expanded over time (Fig. 22b). The expanding process of the negative pattern could last at least 6s. Overall, the early optical response was dominated by positive optical signals; while the later optical response was dominated by negative signals (Fig. 22c). Figure 21

(a) Differential IORs, Raw frames were acquired with a frame speed of 120 frames/s. Each illustrated frame is an average of 24 frames over 200 ms interval. 1 s (5 frames) pre-stimulus baseline images are presented, (b) Statistics of activated retinal area that has optical response with magnitude IOR > 2.5% Δ I/I. Inset panel shows an enlarged display of the early optical response. Fig. 23 shows differential IOR images recorded from the same frog eye used for the experiment shown in Figs. 21 and 22. Given the fact that the dynamic differential processing acted as a high-pass filter, the slow component of the IORs shown in Figs.21 and 22 was reduced; while fast optical responses associated with the ON and OFF edges of the visible light stimulus were enhanced. Fig. 23b shows the statistics of activated retinal area. A threshold (IOR > 2.5% ΔI/I) was used to reduce the effect of background noises on the statistics. From Fig.23, it can be observed that transient IORs occurred immediately after stimulus onset, and the statistics of activated retinal area could reach a magnitude peak within 50 ms (black arrowhead in Fig. 23b) after the stimulus onset. An additional peak (gray arrowhead in Fig. 23b) was observed within 0.5 s after the stimulus offset.

Experimental Methods

Isolated Retina The experiments described in the present disclosure were done in accordance with

Yao et al., 2005b, which is hereby incorporated by reference for this teaching. While the retina was illuminated continuously with NIR light (800-1000 nm) for recording of dynamic intrinsic optical changes, a white light flash was used to activate the retina. The visible stimulus light with a circular (or slit aperture) was projected to the sample plane. A 14 bit CCD camera (PCO 1600, PCO AG, Kelheim, Germany) was used for fast optical imaging of neural activity, and simultaneous ERG response was measured with a multichannel electrode array system (Multichannel Systems, ALA Scientific). The CCD camera featured a 2 GB built-in random-access-memory (RAM) for fast image recording with a transfer speed of 80 MB/s. Although the camera has relatively high resolution (1600 x 1200 pixels), it was often used at a lower resolution by employing pixel binning for high frame rate. Frame rate can be further increased by reading out only a specified area of interest. The optical images presented in this article were recorded with speed of 80 frames/s, and each frame consists of 320 x 240 pixels. A lO s image sequence was typically recorded with 2 s pre-stimulus baseline recording. A CMOS camera was used to adjust the visible light stimulus aperture at the photoreceptor layer. In order to ensure the light efficiency for NIR CCD imaging, the beam splitter (BS) was removed from the optical path after setting up the visible light stimulator.

Functional images of FIORs recorded show transient optical changes with units of dl/I, where dl is dynamic optical response associated with neural activities and I is background light intensity. The intrinsic optical images were reconstructed as follows: 1) 2s (160 frames) pre-stimulus baseline images were averaged, pixel by pixel, and was taken as the background light intensity ϊ of each pixel; 2) The background light intensity I was subtracted from each recorded frame, pixel by pixel, to get dl of each pixel of the 10s image sequence. 3) Image sequence of dl/I was reconstructed to show the dynamic intrinsic optical changes of activated retina.

Intact Eye A NIR light flood-illumination imager was constructed for IOR imaging of isolated frog eye (Fig.l(c)). During the recording, intact frog eye was immersed in the recording chamber filled with Ringer's solution. The recording chamber was placed into a customer- designed holder, which allowed easy adjustment of the optical axis of frog eye relative to NIR illumination light. While the retina was illuminated continuously with a NIR light (785 nm) for recording of IORs, a white light flash (1 s) was used to activate the retina. A fast CCD camera was used to record IORs. The optical images presented in this article were recorded with a speed of 120 frames/s, and each frame consists of 640 x 480 pixels. The optical magnification, M, of the imaging system shown in Fig. l(c) can be calculated as follows:

f2 ^xfeye

where /_/ (50 mm), f₂ (60 mm), /j (40 mm), and ^ are the focal lengths of the lens Ll, L2, L3, and frog eye, respectively. We assume that = 2.87 / eye mm (28), and thus M ~ 11.6. In theory, each CCD pixel ( 7.4 μ m X IΛμ m) corresponded to a 0.64 μ m X 0.64 μ m area at the frog retina, although practical imaging resolution can be reduced due to optical aberrations of the lenses and frog ocular optics. In vivo Eye

A system for use in vivo is a fast EOPM based, no-mechanical-scanning-part, full- field OCT. A fast digital (CCD/CMOS) camera is used for parallel recording of multiple sampling volumes (compared to single point scanning in conventional time-domain OCT). The enface OCT system employs an EOPM demonstrated in an earlier prototype OCT system (Yao 2005 Appl. Optics).

The full-field OCT consists of a Michelson interferometer, a near infrared light source, a fast digital camera, an EOPM based vibration-free phase modulator, an optical aberration compensation system of the phase modulator, and data processing software for reconstruction of OCT images. A prior system demonstrated the feasibility of fast, no- mechanical-moving-part, phase modulation of the reference beam in a single channel photo- detector (i.e. photodiode) based OCT. To achieve this it was necessary to find a solution to the problem of spectral dispersion and loss of axial resolution introduced by the EOPM. This general strategy can be extended by employing parallel scanning with a camera-based detector. Unlike the lock-in amplifier used in other configurations, the digital camera is a discrete frame detector. Instead of sinusoidal modulation of the EOPM in our prototype OCT, it is possible to produce the phase shift of the reference arm in a series of discrete steps. In addition to the capabilities for enface imaging of intensity and phase imaging; polarization-sensitive imaging can also be integrated (Fig. 24).

In figure 24, the components of the basic enface full-field OCT are depicted in black color, and additional parts for polarization-sensitive OCT (Pl, Ql, and Q2) are green. The imaging system is highly compatible for multi-modal imaging without complicated changes of optical components. The arrangement of the polarization components for polarization OCT imaging are shown in figure 24. When polarization-sensitive imaging is not required, these polarization components do not have to be physically removed from the light path. It is possible to align the polarization plane of the polarizer Ll, the slow (or fast) axes of quarter- wave plates, and the transmission direction of the EOPM in the same plane. Instead of using conventional linear-polarization sensitive imaging, circular-polarization sensitive imaging may be used to avoid the orientation dependence of microstructures, such as microtubules and neural axons in biological specimens.

For an NIR light source it is desirable to use a broadband (~100 nm bandwidth) super luminescent laser diode (SLD) with center wavelength around 800 nm as the low coherence NIR light source. There are several manufactures, such as Superlum Inc., that can provide robust, low cost SLD based broadband light source (compared to the expensive pulse laser based light sources). In theory, the axial resolution of the planned OCT (800 nm central wavelength, 100 nm bandwidth) is within 3 μm (for a round trip reflected light imaging). Effective resolution can be degraded by optical aberrations in the system. Previous work has demonstrated the feasibility to balance the optical aberration between the sample and reference beam, so it is possible to achieve the planned 3 μm axial resolution for imaging biological specimens with sub-cellular resolution in three dimensions.

For CCD/CMOS cameras, there are several desirable high speed CCD cameras including (PCO1600 and AVT Pik F-032). The PCO1600 camera offers 1600 x 1200 pixels, 14 bit digitizing, and 2 gigabytes of on-board image memory, and 80MB/s readout speed. The PCOl 600 camera can offer a 30 frames/s imaging with full frame (1600 x 1200 pixels) resolution, and it can also be used at a lower resolution employing pixel binning for high frame rate (e.g., 100 frames/s with 300 x 200 pixels resolution) imaging. Another one, 16 bit CCD camera (AVT Pik F-032), can provide >200 frames/s imaging speed at full frame resolution (648 x 488 pixels). In addition to these fast CCD cameras, there is also a PCO 1200 CMOS camera, which has an imaging speed of more than 1000 frames/second (Fig. 7). The PCO 1200 offers 1280 x 1024ρixel, 10 bit, and 820 MB/s readout speed. Using a demo PCO 1200 camera from The Cooke Corporation, it is possible to image fast retinal activation at 1000 frames/s (Fig. 7). It is possible to use a CCD or CMOS camera with this invention, although the CMOS cameras provide greater speed.

Stepped phase-shifting and extraction of coherence intensity and phase changes are performed as follows. For the photodiode based OCT system (Yao 2005 Appl. Optics), a lock-in-amplifier was used to retrieve the envelope of the interference fringe. Instead of the lock-in-amplifier, it is possible to use an optical phase shifting technique to retrieve the interference envelope for the proposed camera-based OCT. The detected signal at the detector follows the usual phase-shifting interferometry equation:

J(O = /, +!, + 2ψ_rl, cos[Φ(r) + «4(03 (1 )

where I_r and are I₀ the intensities of the reference and sample beams, t is the sequence number (t=0, 1, 2, ..., n-1), n is the number of measurements, Φ(t) is the phase of the sample beam and φ(t) is the phase shift produced by the EOPM which follows the repetitive cycle (0, τ/2, τ , 3τr/2). Regardless of the integral multiples of 2π, the φ(t) can be formulated as τrt/2. According to the standard four-step phase- shifting algorithm, the low coherence scattering intensity can be expressed as:

,S-(D = ΛJΪX = J[Hf)-Ut - 2)]^: +[/(/ - 1) - Ht - 3)j- (2)

and the Φ(t) can be expressed as:

Φ(r) = arctaα{[ J(; - 1) - I(r - 3)] ■ [I(f) - lit - 2)]} (3)

Equations 2 and 3 imply that the OCT imaging speed can be as same as that of the CCD/COMS camera because any recorded image, i.e. I(t), can be used to reconstruct an intensity/phase OCT image in coordination with previous three images (i.e. I(t-3), I(t-2), I(t- I)) in the image sequence. From equations 2 and 3, the intensity and phase information can be computed from the same image sequence and thus recorded simultaneously. The optical phase of the reference beam is periodically modulated by the EOPM. The stepped phase- shifting methodology discussed above allows the CCD/CMOS images to be converted to simultaneous coherence intensity and phase images.

It is also possible to have a polarization-sensitive OCT. In comparison with traditional intensity imaging, polarization-sensitive techniques can provide more sensitive measurement for a variety of biological specimens, such as microtubule polymers, actin bundles, and muscles. Our recent cross-polarized imaging of retina function shows improved sensitivity for intrinsic optical imaging of neural tissues. The multi-modal OCT can be used for polarization- sensitive measurement. In order to eliminate the orientation dependence of microstructures in biological specimens, it is possible to use circular polarizer and analyzer for polarization-sensitive OCT imaging (Figs. 22, 23).

In figures 22 and 23, a right-circular polarized incident light can be achieved by adjusting the angle of the transmission plane of polarizer Pl and the slow axis of quarter-

0 wave plate Ql to 45 . The angle of the slow axis of quarter- wave plate Q2 and the transmission axis of the EPOM is also 45 . Q2 converts the right-circular incidence light into a plane-polarized light that passes through EPOM, and converts the light reflected from reference mirror into left-circular polarized.

In principle, two beams are to interfere only when they have identical polarization, frequency and are in-phase with each other. Some of the right-circular light may be depolarized to left-circular due to scattering, birefringence, or dichroism of the specimen, and can interfere to the left-circular reference beam.

Beyond the full field OCT shown in figure 22, a Multifocal OCT integrates microlens array based multifocal illumination and virtual pinhole confocal configuration for further improvement of the spatial resolution in both lateral and axial directions. Figure 23 is a schematic diagram of a multifocal OCT. In figure 23, the focus plane of the microlens array is located in a conjugated position with the specimen, and thus the specimen is illuminated by a grid of NIR light focuses. An AOD scanner is placed in front of the microlens array to control the deflection angle of the collimated illumination, and thus allows rapid, non-mechanical-moving-part, scanning of the multifocal illumination pattern. The combination of the virtual pinhole confocal configuration and full-field OCT provide a two-stage 'filtering' system to reject the possible noise light as follows:

1) Rejection of out-of-focus noise light: The virtual pinhole confocal configuration acts as a first-stage filter to reject the out-of-focus light. Each focus of the microlens array acts as a point illumination (as the illumination pinhole in a conventional confocal microscope), and computer-synthesized virtual pinholes are constructed by selecting conjugated area (pixels) of the CCD/CMOS image. Based on the principle of confocal imaging, only the light from the sampling volumes (such as the sampling volumes 1 ', 2', and 3' in Fig. 23) can reach the corresponding virtual pinholes (such as the virtual pinholes 1", 2", and 3" in Fig. 23). However, if the scattered light photons from one illuminated volume happen to be diffused into an adjacent sampling volume, they are also collected by that virtual pinhole. In other words, the scattered/diffused light in the specimen, particularly highly scattering objects, may produce cross-talk noise among adjacent sampling (illuminated) volumes. Although the cross-talk noise can be reduced by increasing the distance between two adjacent focuses (sampling volumes), this will increase the scanning steps required for reconstruction of high resolution image, thus will reduce the practical OCT imaging speed. For instance, if the distance of two adjacent focuses is 5 μm, a 5 x 5 -step scanning (25 sub-images) is needed to achieve a 1 μm resolution in the enface plane (with two dimensions). However, if the distance of two adjacent focuses is increased to 10 μm, a 10 x 10 -step scanning (100 sub-images) is necessary to achieve the same (1 μm) spatial resolution.

2) Rejection of cross-talk noise light: The optical coherence gating mechanism acts as a second-stage filter to reject the possible cross-talk (scattered/diffused) light noise. Because of the limited coherence length (such as 5 μm) of the reference and sample beams, only the light (the photons collected by a virtual pinhole from corresponding sampling volume) which has an optical path difference within the coherence length can have practical contribution to the OCT images. The light which has an optical path difference larger that the coherence length will only produce addition background light intensity (i.e. an additional constant item in the equation 1), and will be automatically cancelled during reconstruction of the OCT intensity-sensitive and phase-sensitive images (Equations 2, and 3). In comparison with the reflected/scattered light directly from a sampling volume associated with the corresponding illumination focus, the diffused light from adjacent illumination focuses produces additional optical path difference, at least not less than the distance between the two illumination focuses. In other words, if the distance between adjacent focuses is larger than the coherence length of the light source, the cross-talk noise is automatically 'filtered' during the reconstruction of the OCT images.

The combination of the virtual pinhole confocal imaging and low coherence optical gating improves spatial resolution in both lateral and axial directions, with fast imaging speed. Because of the improved ability of rejecting noise light, the effective penetrating/imaging depth also improves. In principle, the light coherence length of a near infrared light with 100 nm (800-900 nm) band width is ~ 6 μm (single light trip), thus this produces a 3 μm (round light trip for reflected light imaging) penetration depth. In principle, the lateral resolution of the imaging system is optical diffraction limited, and thus 1 μm lateral resolution can be achieved by using a regular objective with NA larger than 0.5. However, since the discrete sampling mechanism (corresponding to the discrete multifocal illumination), the effective lateral resolution also depends on the distance between illumination focuses and scanning resolution. A minimum focus distance, 6 μm, can effectively avoid cross-talk noise. With a 6 μm focus distance (the pitch dimension of the microlens at the specimen), the lateral resolution of the OCT image will be 6 μm without scanning system, and the OCT speed is the same as that of the digital camera (refer to the four-step phase shifting mechanism, Equations 1 - 3). If we need to increase the lateral resolution to 1 μm, a 6 x 6-step scanning will be required, and thus the effective imaging speed will be 1/36 of the speed of the digital camera. Using the above mentioned PCO CCD 1600, we expect to achieve 100 Hz and 5 Hz OCT (300 x 200 pixels) imaging speeds with 6 μm and 1 μm lateral resolutions, respectively. For the PCO1200 CMOS, we expect to achieve 1000 Hz and 30 Hz (video rate) OCT (800 x 600 pixels) imaging speeds with 6 μm and 1 μm lateral resolutions, respectively. A vibration-free scanned multifocal illuminator in the multifocal OCT can employ a

NIR SLD light source. This uses an acousto-optic deflector (AOD) system, consisting of two orthogonal AODs, for rapid, vibration-free scanning of the multifocal illumination in two dimensions {enface plane). The incident angle of the light at MLA can be controlled by the AOD, and thus change the position of the focuses (Fig. 23). An alternative strategy for a vibration-free scanner is to use a liquid crystal phase modulator (LCPM) to drive a diffractive optics system (Fig. 26). Holographic diffraction is a well established technique to produce low-loss reconfiguration of incident light, A holographic phase pattern corresponding to a desired modulated light pattern can be computer-generated and imparted to the LCPM. By the principles of diffraction optics, the phase pattern can be transferred back to a light pattern by implementing the Fourier transform. In figure 24, the lens Ll acts as a Fourier converter to convert the phase pattern on LCPM to the desired light pattern on its focus plane P. Lens L2 and objective become an infinite-distance imaging system to image the modulated light pattern of sample. For the OCT multifocal image reconstruction, the synthetic aperture employed by the virtual pinhole confocal imager can be constructed by a variety of techniques of greater or less sophistication, In general, each pixel within the target composite image array is defined as a weighted linear combination of one or more elements of one image. It is possible to place a mirror at the sample plane to collect a reference image for registration of the locations of 'virtual pinholes'. It is also possible to use a reference-free algorithm to construct the OCT images by implementing the following procedures:

1) An intensity threshold can be used to cut off the background of an image collected with multifocal illumination, and only leave the brightest points/pixels, which are assumed to be the virtual pinholes. Some of the 'pinholes' may be missed from the virtual pinhole pattern because of low image contrast of these areas.

2) Based on the imaged focus pattern of the microlens array, an automatic pattern matching processing can be performed to add the missed 'pinholes' to the virtual pinhole pattern constructed based on procedure 1. 3) An OCT images can be constructed using the virtual pinhole pattern (constructed based on procedures 1 and 3) and the phase-shifting equations 2 and 3. It is possible to use computer-processing based techniques to further improve spatial resolution by implementing digital compensation of optical aberrations of the imaging system and biological specimens. It is also possible to use structured illumination techniques employed in the multifocal OCT to sample the image in such a way that we can track the contribution of each illumination pixel to each pixel in the imager. If aberrations are small, it is possible to employ a fixed grid illumination scheme such as that provided by the above-mentioned microlens array illuminator. If the aberrations are more severe it is also possible to sort out the errant contributions using time domain correlation techniques employing a light spatial modulator based scanning techniques. Accurate spatially and temporally modulated illumination allows computer-processing based virtual adaptive optics to further improve the OCT imaging quality. References:

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Claims

What is claimed is:

1. An optical coherence tomography system for detecting a physiologic change in one or more retinal neurons comprising: a. a non-stimulatory light source, b. a non-polarizing beam splitter for splitting the non-stimulatory light into a sample beam focused continually on a retina and a reference beam continually focused on a reference mirror, c. a stimulatory light source capable of stimulating a photoreceptor in a retina, the stimulatory light source capable of being focused intermittently on the retina, d. the reference mirror for reflecting the reference beam, e. a camera for receiving non-stimulatory reflected from the retina and from the reference mirror, said camera transmitting data to a computer, f. the computer for receiving data from the camera, g. a phase modulator for the reference beam, h. an optical aberration compensation system for the reference beam, and i. at least one algorithm located on the computer for processing of optical coherence tomography images received by the camera.

2. The optical coherence tomography system as in claim 1, in which the physiologic change in one or more retinal neurons is represented by a change in the light reflectance or polarization of one or more retinal neurons.

3. The optical coherence tomography system as in claim 1, in which the physiologic change in one or more retinal neurons is represented by a change in the light reflected from or transmitted through one or more retinal neurons.

4. The optical coherence tomography system as in claim 1, in which the non- stimulatory light comprises a wavelength of light which does not stimulate the photoreceptors in a retina

5. The optical coherence tomography system as in claim 1, in which the non- stimulatory light comprises a near infrared light which does not stimulate the photoreceptors in a retina.

6. The optical coherence tomography system as in claim 1, in which the stimulatory light comprises any light which does stimulate the photoreceptors in a retina.

7. The optical coherence tomography system as in claim 1, in which the function of one or more retinal neurons can be diagnosed based upon the physiologic change.

8. The optical coherence tomography system as in claim 1, in which disease states of one or more retinal neurons can be diagnosed based upon the physiologic change.

9. The optical coherence tomography system as in claim 1, in which the phase modulator comprises a vibration-free electro optic phase modulator.

10. The optical coherence tomography system as in claim 1 in which the phase modulator employs an optical phase shifting algorithm.

11. The optical coherence tomography system as in claim 1 in which the phase modulator employs an optical phase shifting algorithm with discrete steps.

12. The optical coherence tomography system as in claim 1 in which the phase modulator employs a four step optical phase shifting algorithm.

13. The optical coherence tomography system as in claim 1 in which the camera comprises a CCD camera.

14. The optical coherence tomography system as in claim 1 in which the camera comprises a CMOS device.

15. The optical coherence tomography system as in claim 1 in which the stimulatory light source is homogenous.

16. The optical coherence tomography system as in claim 1 in which the stimulatory light source is heterogeneous.

17. The optical coherence tomography system as in claim 1, in which the stimulatory light source can be timed intermittently.

18. The optical coherence tomography system as in claim 1 , in which one or more layers of the retina may be observed.

19. The optical coherence tomography system as in claim 1 which allows viewing the retina in its full field.

20. The optical coherence tomography system as in claim 1 which allows viewing the retina in multiple fields.

21. The optical coherence tomography system as in claim 1 in which the non- stimulatory light is separated into multiple fields before reaching the retina.

22. The optical coherence tomography system as in claim 1 in which the stimulatory light is separated into multiple fields before reaching the retina.

23. The optical coherence tomography system as in claim 1 in which the non- stimulatory light passes through a microlens array to produce multiple focal illumination at the retina.

24. The optical coherence tomography system as in claim 1 in which the non- stimulatory light received by the camera passes through one or more virtual pinholes.

25. The optical coherence tomography system as in claim 1 comprising polarization optics.

26. The optical coherence tomography system as in claim 1 comprising circular polarizers which are comprised of linear polarizers and quarter wavelength retarders.

27. The optical coherence tomography system as in claim I₅ in which one of the algorithms located on the computer for producing optical coherence tomography images comprises a optical phase shifting algorithm with discrete steps.

28. The optical coherence tomography system as in claim 1, in which one of the algorithms located on the computer for processing of optical coherence tomography images received by the camera comprises the following steps: a. averaging a given number (m) of pre-stimulus baseline images of a visual field, pixel by pixel, to obtain a background light intensity of each pixel of the image of the visual field, b. subtracting the background light intensity of each pixel of the image of a the visual field from a post-stimulus image of a visual field, pixel by pixel, to obtain a change in intensity of each pixel of the image of the visual field, and c. dividing the change in intensity of each pixel of the visual field, pixel by pixel, by the background light intensity of each pixel of the image to obtain a number which is i. positive, ii. negative, or iii. zero.

29. The optical coherence tomography system as in claim 1, in which one of the algorithms located on the computer for processing of optical coherence tomography images received by the camera is for subtracting slow intrinsic optical responses from the optical coherence tomography images, comprising the following steps: a. obtaining at a given time (u) the intensity of each pixel of an image of a post- stimulus visual field; b. averaging a given number (ή) of images recorded sequentially before time («) of the visual field, pixel by pixel, to obtain a dynamic reference image, c, subtracting the intensity of each pixel of the dynamic reference image of the visual field from each pixel of the image at the given time (u), pixel by pixel, and d. dividing the intensity of each pixel of the visual field, pixel by pixel, in step 29 c by the light intensity of each pixel of the dynamic reference image of the field obtained in step 29 b to obtain a value which is i. positive, ii. negative, or iii. zero.

30. A method of detecting a physiologic change in one or more retinal neurons by exposing the retina to a stimulatory light source, the method comprising: a. exposing the retina to a non-stimulatory light source comprising a wavelength of light that does not stimulate the photoreceptors in a retina, b. detecting at least a portion of the non-stimulatory source reflected from the retina to generate a first measurement; c. exposing the retina to a stimulatory light source comprising a wavelength of light that stimulates photoreceptors, d. detecting at least a portion of the non-stimulatory source reflected from the retina after exposure to the stimulatory light source to generate a second measurement; and e. using the first and second measurements to determine the physiologic change in the retinal neuron.

31. The method as in claim 30, with the addition of comparing the results in step 30 e in the same person over a period of months.

32. The method as in claim 30, with the addition of comparing the results in step 30 e in the same person over a period of years.

33. The method as in claim 30, with the addition of comparing the results in step 30 e in a group of people with healthy retinas versus a group of people with diseased retinas.

34. The method as in claim 30 in which the stimulatory light intensity is homogenous.

35. The method as in claim 30 in which the stimulatory light intensity is heterogeneous.

36. The method as in claim 30 in which the stimulatory light can be timed intermittently.

37. The method as in claim 30 in which the function of one or more retinal neurons can be diagnosed based upon the physiologic change.

38. The method as in claim 30 in which disease states of one or more retinal neurons can be diagnosed based upon the physiologic change,