Perceptual Visual Acuity Declines With Age in a Rat Model of Retinitis Pigmentosa While Light Perception is Maintained

Abstract

Purpose: Retinitis pigmentosa (RP) is a leading cause of blindness and genetically induces impairment of the retinal epithelium and photoreceptors. In this study, we investigated the decline in the visual response and visual ability during disease progression. This understanding is crucial for disease staging in patients, establishing therapeutic plans in advance, and evaluating the effects of interventional treatments.

Methods: We used a rat model of inherited RP (Royal College of Surgeons [RCS] rats) and evaluated form visual acuity and light perception using behavioral tests and electrophysiological recordings in the dorsal lateral geniculate nucleus, superior colliculus, and primary visual cortex.

Results: The perceptual form vision (detection of grating stimulus) was attenuated by 9 weeks old. The neural responses in the three early visual areas to flashing grating stimuli with various contrasts and spatial frequencies showed similar degeneration progress as the behavioral evaluations. Light perception (detection of a bright uniform light source) was maintained until at least 11 weeks old. The neural responses to the uniform flashlight stimulus in the three early visual areas were maintained during the same period.

Conclusions: Our findings suggest that form vision is primarily affected by the progression of RP, whereas non-form vision is potentially robust to retinal degeneration. This maintenance of light perception is likely due to the preserved function of intrinsically photosensitive retinal ganglion cells. These results provide useful and fundamental knowledge for evaluating the protective or restorative effects of experimental treatments for RP.

Age-related retinal dysfunction is a growing concern as worldwide populations age. For instance, retinitis pigmentosa (RP) and age-related macular degeneration are degenerative blinding diseases caused by the loss of rods and cones, in which the residual visual system is largely unable to respond to light (dysfunction of form vision).^1–6 Several treatments, including graft experiments,^7–10 optogenetic engineering,^11–17 gene replacement/supplementation therapy,¹⁴ and artificial vision,^18–21 have been investigated; however, none can fully restore vision. 

One animal model used in these studies is the Royal College of Surgeons (RCS) rat model, which was the first reported animal model of inherited RP.²² In these animals, the absence of phagocytosis in retinal pigment epithelial cells causes a progressive loss of rod and cone photoreceptors,^23,24 which occurs primarily in the first few months of life.^25–27 To prevent the blindness of RCS rats, transplantations of several cell lines have been conducted and show preservation of photoreceptors, which results in the maintenance of electrophysiological responses^7,28,29 and expression of optokinetic reactions^7,30,31 to attenuate vision loss. Other approaches, such as optogenetic tool expression and polymeric nanoparticle injection, have also been assessed.^{16,17,32–34} 

To evaluate the protective or restorative effects of different approaches for treating RP, details of how visual function is degraded in relation to the loss of photoreceptors are important. Histological data have demonstrated temporal changes in the thickness of the outer nuclear layer and the accumulation of photoreceptor outer segment debris.^{23–25,27–29} Additionally, electrophysiological studies have shown that the recordings of the visual responses of the retinal ganglion cells (RGCs) and superior colliculus (SC) neurons gradually attenuate in parallel with the degeneration of photoreceptors.^26,27 

On the other hand, there is a significant gap between the reduction in population activity in the primary visual cortex (V1)³⁵ and the loss of visual acuity in RCS rats.³⁶ Although population activity in response to low spatial frequencies decreases by 4 weeks of age, RCS rats can still detect the same level of spatial frequency (approximately 0.2 cycles/degree) until at least 7 months. To resolve this discrepancy and evaluate the protective or restorative effects of RP treatment, it is crucial to measure visual ability accurately in perceptual tasks. However, this is challenging because the training period for RCS rats to learn a task is long, such that the loss of visual function compromises the completion of task learning. 

To address this challenge, our aim was to implement an easily accessible training protocol allowing RCS rats to learn a visual detection task before the onset of visual impairment. Additionally, we conducted extracellular recordings of visual responses from the V1, dorsolateral geniculate nucleus (dLGN), and SC neurons. Furthermore, we investigated light perception-related behavior and neuronal activity, which likely reflect the responses of residual retinal cells, including rods, cones, and intrinsically photosensitive retinal ganglion cells (ipRGCs),^37–41 depending on the progression of RP. Our results suggested that RCS rats maintained light perception even after the complete loss of form vision, likely due to ipRGC function. These data will be useful for evaluating the protective or restorative effects of experimental treatments. 

Materials and Methods

Animals

Tan-hooded, pink-eyed RCS rats (Jcl-rdy/rdy) and congenic control rats (CLEA Japan, Inc., Tokyo, Japan) were kept on 12-hour light/dark cycles. In total, 32 male RCS rats and 10 control rats weighing 40 to 300 g were used (12 RCS rats and 6 control rats for behavioral tests and 20 and 4 for electrophysiological recordings). All the experimental protocols were approved by the Research Ethics Committee of Osaka University, Osaka, Japan. All procedures were performed in accordance with the regulations of the Animal Care Committee of Osaka University Medical School and the National Institutes of Health Guidelines for the care of experimental animals. All efforts were made to reduce the number of animals used in this study. 

Water Control

The animals had ad libitum access to water during weekends, but water was obtained only by performing the task correctly on other days. Signs of possible dehydration were monitored (reduced skin tension, sunken eyes, and marked variations in general behavior), but none were observed in any of the animals. To ensure adequate hydration, we weighed each animal at the beginning and end of each experimental session and compared the weights to a standard weight, which was updated weekly. If the weight measured after the session was < 90% of the standard weight, the animal was temporarily removed from the study and provided ad libitum access to water until the weight recovered. However, this has not occurred throughout the present study. 

Behavioral Training for Measuring Contrast Sensitivity

The choice box (30 cm long × 40 cm high × 55 cm wide) was prepared as described previously^42–44 and is commercially available from Narishige (EDMS13-264, Tokyo, Japan). The front of the box was translucent and faced a liquid crystal display monitor (Princeton HTBTF-24W; mean luminance: 30 cd/m², gamma-corrected; 170 chloropic-lux, 164 rhodopic-lux, 151 melanopic-lux, as estimates^45,46; and https://lucasgroup.lab.manchester.ac.uk/measuringmelanopicilluminance/). The box was partitioned with translucent walls creating three interconnected sections, each of which had a spout lever (Fig. 1A)^47,48 in its center, and each box contained a central lever in the middle area and choice levers in the other two areas. Animals obtained a reward from a choice lever by pulling it upward. The reward volume was changed by controlling the opening time of the solenoid valve, which was manipulated using a personal computer. Speakers attached to the monitor provided signals indicating task initiation and auditory feedback for task errors. The animal behavior was monitored using a webcam. The software for the experimental control and stimulus presentation was developed using MATLAB (MathWorks, Natick, MA, USA) with extensions from the Psychophysics Toolbox.^49,50 

Figure 1.

 

Two-alternative forced-choice (2AFC) task for quantifying daily alteration of structural visual performance in Royal College of Surgeons (RCS) rats. (A) Training sequence consisting of three stages. Left: In stage I, both RSC and control rats (3 weeks old) were habituated to the task environment and learned manipulation of the spout lever, which dispensed a water drop from its tip when pulled up. In stage II, animals (4–5 weeks old) conducted the 2AFC task with a bright-patch stimulus. Animals had to detect stimulus and pull up a corresponding spout lever to obtain a reward water. In stage III (for 6–11 week old animals), a stimulus was switched to a grating patch. The same 2AFC task paradigm was applied. Middle: Example screenshots of RCS rats conducting each task. Right: Illustration of spout lever (stage I) and stimuli (stages II and III). (B) Daily performance (ratio of correct-choice trials in total trials) of RCS (circles) and control rats (squares) during stages II and III. Values are presented as mean ± 1 SEM. The red dashed line indicates a chance level of 50%. The blue dashed line indicates 80%. Performances increased during the first 2 weeks (stage II, 4–5 weeks old) and were maintained around 80% in the first week of stage III (6 weeks old). During 7 to 8 weeks old, performances decreased to the chance level and did not recover during 9 and older weeks of age (9+ weeks old). (C) Example of trial-by-trial contrasts determined by the staircase method in conjunction with the 2AFC task paradigm in stage III (a 7 weeks old RCS rat, spatial frequency [SF] = 0.05 cycles/degree). Following a hit trial, contrast of the grating-patch stimulus decreased, and vice versa. The task session was halted if performance in 10 preceding trials was less than 50%, and contrast value in a last trial was defined as threshold contrast. Contrast sensitivity was defined as the inverse of threshold contrast. (D) Contrast sensitivity functions along with various SF of the grating-patch stimuli in (i) 6, (ii) 7 to 8, and (iii) 9 to 11 week old RCS rats and (iv) age-matched congenic control rats (9+ weeks old). Measurements began after individual RCS rats achieved performance above the criteria in the stage III (> 80%, see Methods for details) and continued until they were 11 weeks old. Values are presented as mean ± 1 SEM. Higher contrast sensitivity means that animals can detect lower-contrast stimuli. Six-week-old RCS rats exhibited clear contrast sensitivity function biased towards low SF, which declined in 7 to 8 weeks old and disappeared in 9+ weeks old rats. Conversely, age-matched congenic control rats maintained contrast sensitivity function, which was biased toward middle SF.

Contrast sensitivity was measured as a metric of form visual ability in a two-alternative forced-choice visual grating detection task (2AFC-VGDT) combined with a staircase method^43,51 that quantifies contrast sensitivity at the spatial frequency (SF) parameter without model fitting. We adopted an efficient training protocol for rapid learning of the 2AFC-VGDT.⁴⁴ Briefly, both the RCS and control rats were trained in three stages (see Figs. 1A, 1B). In the first stage, the rats (3 weeks old) learned to obtain the fluid delivered from the spout lever by pulling up the choice lever. In the second stage, the rats (4–5 weeks old) learned the basic procedure of the 2AFC-VGDT, that is, how to initiate a trial and obtain fluid using the bright patch. This provides a highly salient and effective method for drawing an animal's passive attention. In the third stage (the grating patch detection training stage), the rats (6–11 weeks old) learned that the fluid supply was associated with the grating patch. The viewing distance of the stimulus center from the central lever was 13 cm. The parameters of the horizontal grating (contrast = 100%; spatial frequency = 0.1 cycles/degree; temporal frequency = 0 cycles/sec; diameter = 70 degrees) were determined according to our previous study.⁴³ The stimulus presentation continued until the rat pulled up the corresponding (right/left) choice lever. To measure the contrast sensitivity, the grating location was randomly changed from trial to trial. The stimulus contrast was initially set at 100%, and the level of contrast varied across trials according to the staircase method (1-up/1-down). Upon a correct choice, the rats received a reward of 2 to 3 µL of water, and the stimulus contrast was decreased from the current level in the next trial (Fig. 1C). Upon an incorrect choice, the rats received an audible sound (500 hertz [Hz]) only, and the stimulus contrast was increased in the next trial. The stimulus contrast decreased or increased at 1%, 4%, and 10% contrast steps in the low- (1–10%), middle- (10%–50%), and high-contrast ranges (50%–100%), respectively. Each session lasted until the correct performance of the most recent 10 trials fell below 60% or the rats detected 1% of the stimulus contrast. The threshold contrast (C_threshold) was defined as the final stimulus contrast that the rats could choose correctly. The contrast sensitivity was calculated using the following equation: contrast sensitivity = 100/C_threshold. Measurements began after individual RCS rats achieved performance above the criteria in the third stage (>80%, see the blue dashed line in Fig. 1B) and continued until they were 11 weeks old. For control rats, contrast sensitivity measurements were conducted at 9 to 12 weeks of age. 

Behavioral Analysis for Light Perception

To assess light perception in a perception task, we built another system: the three-alternative forced-choice light perception test, which was conducted in a completely dark room. The apparatus was constructed using a hexagonal box molded with boards of 30 cm width × 40 cm height, 3 light-emitting diodes (LEDs; 5.0 × 10⁴ chloropic-lux; 5.5 × 10⁴ rhodopic-lux; 6.2 × 10⁴ melanopic-lux^45,46 and https://lucasgroup.lab.manchester.ac.uk/measuringmelanopicilluminance/), and 3 spouts. This white light stimulus is believed to activate ipRGCs and induce miosis, based on previous studies.^45,52 It was much more intense (>20 kcd/m²) than the screen used in the 2AFC-VGDT (30 cd/m²) to achieve a much higher contrast relative to the background (a completely dark room). 

The system control and data collection were performed using a custom-made program written in Python (Python Software Foundation, Wilmington, DE, USA). A rat was able to obtain water from the spout as a reward when it licked a spout corresponding to a turned-on LED. In the case of an incorrect spout, the rat received no reward. The LED that was turned on was randomly chosen for each trial. Each session was continued for 1 to 3 hours (6 rats for 63 days; mean ± SD = 376 ± 82 trials). The detectability of non-form vision was assessed as the percentage hit (the hit trial rate in the total trials) and the time elapsed from when the LED was turned on to when the rat licked the spout. This behavioral experiment was not performed in healthy control animals because our primary focus was to confirm that the overaged RCS animals still retain non-form vision ability. 

Preparation for Recordings of Neural Activity

Animal preparation procedures have been described in detail elsewhere.^53,54 Briefly, RCS and congenic control rats of various ages (3–11 weeks of age) were handled before surgery. The rats were anesthetized using a mixture of isoflurane (2–3%; Forane, Abbott Japan, Tokyo, Japan) and N₂O:O₂ (2:1). Then, the animals were placed in a stereotaxic head holder (SR-8N; Narishige, Tokyo, Japan), and their body temperature was maintained at about 37°C using a heating pad. The local anesthetic lidocaine was administered at the pressure points and around the surgical incisions. A lightweight sliding head-holder plate was surgically attached to the skull, and reference electrodes were implanted above the cerebellum. Electrocardiographic images, electroencephalographic recordings, and the heart rate were continuously monitored throughout the surgery. 

After the rats recovered from surgery (2 or 3 days later), we conducted acclimated training based on a previous study⁵⁵ to obtain stable recordings from awake rats. Briefly, the rats were deprived of drinking water in their home cages, although food was provided ad libitum. They were acclimated to head fixation for 30 minutes with sweet water (4% sucrose) at the beginning and end of training. The duration of training was increased over 4 to 5 days until the rats sat comfortably for 2 hours. 

Electrophysiological Recordings From dLGN, SC, and V1

We then performed extracellular multi-point recordings. The skull was exposed, and a small hole (less than 3 mm in diameter) was made above the monocular region of dLGN (coordinates: antero-posterior [AP] −4.5 mm; medio-lateral [ML] ± 3.5 mm),⁵⁶ SC (coordinates: AP −7 mm; ML ± 1.5 mm),⁵⁶ and V1 (coordinates: AP −7 mm; ML ± 3.5 mm)^56,57 under isoflurane anesthesia. This coordination was modified slightly depending on the age of the rats. A 32 channel-active silicon polytrode (A2 × 16-10 mm-100-500-413-A32; NeuroNexus Technologies, Ann Arbor, MI, USA) was inserted after removing a small portion of the dura. After a 0.5 to 1 hour recovery from anesthesia, the wideband signals were amplified, filtered, and collected using a computer running RASPUTIN (Plexon, Dallas, TX, USA) at 40 kilohertz (kHz). Recordings were performed multiple times in the same rats, with the recording areas changed each time to avoid biases. At the end of the recording, electrolytic lesions were produced by passing tip-negative direct current (intensity = 3–6 µA; duration = 10 seconds) from 2 to 4 separate channels. This enabled the histological verification of the recording sites (Supplementary Figs. S1A–C). 

Form and Non-Form Visual Stimulation in Electrophysiological Rrecordings

To observe a selectivity map in the joint contrast × SF domains, visual stimulation of the flashing grating and reverse correlation analysis were conducted based on previous studies.^58,59 A full-screen stimulus of a flashing sinusoidal grating was generated using custom-made MATLAB programs with Psychtoolbox^49,50 and presented monocularly on a liquid crystal display monitor (ProLite G2773HS; Iiyama, Tokyo, Japan; mean luminance = 30 cd/m²; gamma-corrected) placed 28.5 cm in front of the right or left eye of the rat (eyes contralateral to the recording hemispheres). Sinusoidal grating stimuli with a horizontal orientation at varying stimulus contrasts (1–96%, 9 steps), SFs (0.005–0.5 cycles/degree, 10 steps), and phases (0–270 degrees, 4 steps) as well as single blank stimuli (full-field background gray screen; 9 × 10 × 4 + 1 = 361 conditions in total) were presented at 8 Hz (125 ms/frame), where each parameter combination was repeated 50 times in a randomized order.^58,59 In a subset of experiments, we used drifting grating stimuli to evaluate SF preference (0.005–0.5 cycles/degree at 96% contrast) and contrast preference (1–96% at 0.005 cycles/degree SF). 

In the following recording experiments, we conducted further electrophysiological recordings using a custom-made device that presented high-luminance flash stimuli^60,61 (OptoSupply OSW4XME3C1S, 3-watt white power LED, with a collimator lens; 5.5 × 10⁵ chloropic-lux; 5.4 × 10⁵ rhodopic-lux; 5.2 × 10⁵ melanopic-lux; >400 kcd/m²). The neural response was continually measured during the flash stimulus presentation (100 trials). A flash stimulus was presented for 1, 10, and 50 ms with 4 seconds inter-trial intervals. This experiment with flash stimuli was not performed in healthy control animals because behavioral analysis for light perception confirmed that the overaged RCS animals still retain non-form vision ability. 

Offline Spike Sorting and Screening

After the recordings, raw waveforms were processed using Klusta⁶² to conduct offline spike sorting, where the signals were band-pass filtered (500–5000 Hz, 3-order Butterworth filter) and spike candidates were extracted (hysteresis thresholding, 2 and 4.5 SD, negative trough) and divided into multiple clusters. Quantitative unit screening was conducted on all clusters to exclude noise clusters, where the firing pattern (refractory period), waveform features (spike trough width, signal-to-noise ratio, and peak-to-trough ratio), and spatial pattern among channels (localization) were considered as metrics (Supplementary Fig. S1D). Only the units that fulfilled the following five criteria were selected for further analysis. (i) Refractory period: an inter-spike interval of less than 2 ms must be less than 5% of the total firing. (ii) Spike trough width: full-width at half-maximum of spike trough must be longer than 0.1 ms and shorter than 0.5 ms. (iii) Signal-to-noise ratio: full-height amplitude of mean spike waveform must be 3 times greater than SD among spikes (up to 1000 spike waveforms). (iv) Peak-to-trough ratio: the peak amplitude of the mean spike waveform must be less than 80% of the trough amplitude. (v) Localization: the channel counts recording considerably large waveforms (> 50% of the maximum SD among channels) must be at most five. Additionally, for the recording in the dLGN and SC, we adopted units recorded in specific depths (3400–5000 µm for dLGN and 1600–3200 µm for SC, from cortical surfaces) according to the rat brain atlas.⁵⁶ For the V1 recordings, we did not apply the depth restriction. The recorded depth of the V1 units ranged up to approximately 2000 µm, which was within the range of rat V1 observed in previous studies.⁵⁷ 

Analysis of Neural Responses to Visual Stimulation

After offline spike sorting and screening, the spike-triggered average (STA)⁵⁸ of the grating parameters was calculated for each unit using responses (spike trains) to the flashing grating stimulus sequence. The calculation was conducted from −500 ms (pre-firing) to 500 ms (post-firing) from each firing event in a 10 ms step. The counts of the blank stimuli were subtracted. STA results were converted into signal-to-noise ratios (SNRs; z-score based on post-firing counts): SNR = (STA-µ)/σ, where µ and σ represent mean and SD, respectively, of counts across grating parameters and time in the post-firing period. The maximum SNR was searched from −300 to −20 ms, and a contrast × SF joint preference map was reconstructed, where the time and grating phase parameters were fixed to those inducing the maximum SNR. To define the units that significantly responded to the flashing grating stimuli, we conducted one-sample t-tests that compared the SNRs for the lowest contrast in the contrast × SF joint preference maps with the SNR for the highest contrast and lowest SF condition. If P < 0.05, the units were classified as significantly responsive to the flashing grating stimuli. We constructed a peri-stimulus time histogram (PSTH) of the responses to the full-field flash illumination stimulation from −500 to 500 ms around the stimulation onset in 10 ms steps. Artifacts caused by strong flash stimulation were classified into separate clusters. To exclude these clusters from further analyses in an objective manner, we calculated event counts around stimulation onset (−20 to 20 ms; A) and the pre-stimulation period (−500 to −20 ms; B). Clusters whose count around the stimulation onset was equal to or higher than half of their summation (A/(A+B) ≥ 0.5) were excluded. PSTHs were converted into SNRs (SNR = (PSTH−µ)/σ, where µ and σ represent mean and SD, respectively, of spike counts across the prestimulation period), and significantly responsive units were defined if the SNR exceeding 1.64 retained more than 20 ms across the period from 20 to 300 ms after the stimulation onset. 

Threshold contrast (C_threshold) for each neuron was determined as the lowest contrast value inducing a positive SNR on a contrast tuning curve at each SF (like Fig. 2C) in which a zero-crossing contrast was extracted by using the linear interpolation. Contrast sensitivity was calculated using the same equation as the behavioral contrast sensitivity (1/C_threshold). The highest contrast sensitivity among SFs was determined as the maximum contrast sensitivity. The optimal SFs (opt SFs) were defined as the SF values that elicited the maximum contrast sensitivity. 

Figure 2.

 

Evaluation of the neuronal preference in the joint contrast and spatial frequency (SF) domain. (A) Schema of electrophysiological experiments. The visual responses to flashing grating were recorded from dLGN, SC, and V1 of head-restrained rats. A selectivity map in the contrast × SF domains (contrast × SF joint preference map) was obtained using the reverse correlation method. (B) An example of neural preference to grating stimuli with various contrast and SF combinations. Reddish and bluish colors correspond to firing increase and decrease relative to baseline, respectively. (C) Extracted contrast tuning curve from an SF eliciting the maximum response increase (SF = 0.014 cycles/degree, the green area in the inset). Zero (horizontal dotted line) crossing contrast was used as a metric of threshold contrast of neural response for calculating the contrast sensitivity function (inverse of the threshold contrast). (D) SF tuning curve was reconstructed using data obtained from the highest contrast visual gratings presentation (contrast = 96%, green area in the inset).

Statistical Analysis

To compare the SNRs, maximum contrast sensitivities, and opt SFs of neurons in the early visual systems across age groups (4–5, 6, 7–8, and 9–17 weeks), one-way analysis of variance (ANOVA) was conducted. A post hoc Tukey's honestly significant difference (HSD) test was applied if a statistically significant difference was revealed by one-way ANOVA. To identify the neural units that responded significantly to the flashing grating stimuli, one-sample t-tests were used, which compared the SNR to the highest contrast and lowest SF stimuli with SNRs to the lowest contrast stimuli. 

The Spearman's rank correlation coefficient was used to quantify the chronological trends in the behavioral performance of light perception. To compare the SNRs, latencies, and firing rates of neural responses to the flashlight stimulus across age groups, the Kruskal-Wallis H test followed by the post hoc Dunn’s test was conducted. Neural units that responded significantly to the flashlight stimulus were identified using the z-test (z > 1.64, corresponding to P < 0.05). 

Histology

After the recording experiments, electrolytic lesions (3 µA for 10 seconds) were made for some RCS rats to confirm the probe locations (see Supplementary Figs. S1A–C). The animals were deeply anesthetized with urethane (Kishida Chemical Co., Ltd, Osaka, Japan; 2–3 g/kg, intraperitoneal [IP]) and perfused transcardially with 0.1 M phosphate-buffered saline (PBS; pH 7.4) followed by 4% paraformaldehyde in 0.1 M PBS. Whole brains were obtained and immersed in 30% sucrose in PBS for 36 to 48 hours. Sixty-micrometer-thick frozen parasagittal sections were sliced on a microtome, kept in PBS, and stained for cytochrome oxidase.⁶³ For identification of the recording-site, images from the brain sections were captured by a camera (DS-Ri1, Nikon Co., Tokyo, Japan) mounted on a light microscope at 10 × magnification (ECLIPSE 80i, Nikon Co.). Shrinking in the sagittal tissues was corrected by taking the ratio of the measured distance of electrolytic lesions and the distance between the channels used for making the electrolytic lesions.⁵⁷ In the other rats, we prevented the electrolytic lesioning in order to minimize the effect of lesioning damage in one region on the neural activity in the other regions. Instead, the recording depths of each channel were considered (“offline spike sorting and screening”). We excluded data obtained from off-target brain areas, such as the hippocampus. 

Results

Perceptual Spatial Vision in the RCS Rats Declines by 9 Weeks of Age

To measure the contrast sensitivity of freely behaving RCS rats before their visual ability completely declined, we trained the rats using an easy-to-learn training protocol⁴⁴ (see Fig. 1A; see Materials and Methods), consisting of three stages to enable the rats to gradually learn the task paradigm. In the first stage, the rats were allowed free access to a spout lever that supplied a water drop from its tip when pulled up. The rats were then rewarded by performing the 2AFC task with detection of bright or grating patch stimuli in the second and third stages, respectively. We successfully trained six RCS rats to habituate to the task apparatus in the first stage within 1 week (3 weeks of age) and performed the 2AFC task in the second stage within 2 weeks (4–5 weeks of age). The RCS rats exhibited an elevated bright-patch detection performance (see Fig. 1B, open circles), surpassing the chance level (50%). We continued to monitor the performance of the visual grating patch detection up to 11 weeks of age. In the first week after the transition to the third stage (6 weeks of age), RCS rats maintained a relatively stable performance, fluctuating around 80% (see Fig. 1B, filled circles). In the following 2 weeks (7–8 weeks of age), their performance level rapidly decreased to the chance level. Even in the older age groups (9+ weeks of age), although RCS rats performed the 2AFC task, they were unable to detect the grating patch stimulus. On the other hand, control rats retained the ability to detect grating stimuli until 11 weeks of age (see Fig. 1B). 

After completion of the learning task for grating patch detection (>80% hit), we continuously measured the contrast sensitivity of the 6 to 11-week-old RCS rats. By changing the stimulus contrast according to the staircase method,⁴³ the RCS rats were able to detect the grating patch stimulus above chance level until it fell below a specific contrast, which determined the animal’s limit contrast value (see Fig. 1C). When the contrast was high, the rat easily chose the correct lever (green dots, trials 1 and 2) but frequently failed to detect the stimulus when the contrast level was around the limit of sensitivity (blue dots, trials 25–27). Contrast sensitivity was defined as the inverse of the limit contrast value, where a higher contrast sensitivity indicated that the rat could detect a lower-contrast (faint) grating patch stimulus. We reconstructed the contrast sensitivity function along with various grating spatial frequencies (0.02–0.5 cycles/degree) using data obtained from the RCS rats at 6, 7 to 8, and 9+ weeks of age (Fig. 1D). Similar to other kinds of rodents,^43,64 the contrast sensitivity function of 6-week-old RCS rats was low-pass SF tuning (see Fig. 1Di). For the 7 to 8-week-old RCS rats, this function showed a longitudinal decrease in sensitivity but no remarkable change compared with that of the 6-week-old RCS rats (see Fig. 1D, ii). However, for the 9+-week-old RCS rats, it had completely disappeared (see Fig. 1D, iii). We also trained six congenic control rats using the same paradigm to perform the 2AFC with grating patch detection and measured contrast sensitivity. In the same age range (9+ weeks of age), the congenic control rats maintained their perceptual form vision (see Fig. 1D, iv). These findings indicate that the decline in visual ability in RCS rats is attributed to inherent retinal degeneration and not just from aging. Taken together, our results indicate that retinal degeneration in RCS rats affects their perceptual visual ability to detect structured stimuli by 9 weeks of age. 

Neural Spatial Visual Ability Declined With a Similar Tendency to Perceptual Visual Ability

RCS rats have progressive dysfunction of the retina.^25–27 With a similar time course, they showed a progressive decline in the perceptual ability of form vision (see Fig. 1). Next, by utilizing the extracellular neurophysiological recording with offline spike sorting and screening (see Supplementary Fig. S1D), we sought neural response alterations over several days in the early visual systems of RCS rats, which received signals directly or indirectly from the degenerating retina, and compared them with aged congenic-control rats. 

To examine the age-related deterioration of visual responses in the early visual systems, we conducted extracellular recordings of neurons in the dLGN, SC, and V1 of head-restrained awake RCS rats (Fig. 2A, see Supplementary Figs. S1A–C). Visual responses were evoked by presenting a sequence of flashing grating stimuli for which the parameters were set within the same range as the stimuli used in the grating patch detection task (see Fig. 1D). Using the reverse correlation method after spike sorting followed by quantitative unit screening based on the spike waveform and spatiotemporal firing pattern, we obtained a selectivity map for the joint contrast and SF domains (Fig. 2B). The short recording time (typically less than 1 hour) was intended to remarkably alleviate stress in the rats. An example contrast × SF joint preference map reconstructed from a V1 neuron of a 6-week-old RCS rat indicated a remarkable bias of responses to high-contrast and low-to-middle SF grating stimuli (see Figs. 2C, 2D), similar to the contrast sensitivity function obtained in the behavioral task (see Fig. 1D). 

Until 6 weeks of age, neurons in all 3 regions of RCS rats maintained clear visual responses, where the preferences were biased at higher contrast and low-to-middle spatial frequencies (Figs. 3A–C, i, ii). These preferred contrast and spatial frequencies are within the range reported in previous studies.⁴³ In the 7 to 8-week-old RCS rats, although only the dLGN neurons maintained some sort of response to the flashing grating, which was biased at high-contrast and low-SF combinations, the overall response magnitudes in the other 2 regions showed clear reductions (see Figs. 3A–C, iii). In older RCS rats (9+ weeks of age), clear visual responses to the grating stimuli were not observed in the three regions (see Figs. 3A–C, iv), where weak biases toward high contrast and low SF still existed in V1. We confirmed that this reduction in visual responses was due to retinal degenerative disease, not aging, by recording the visual responses in age-matched congenic control rats, where noticeable visual responses were recorded in all 3 regions even at 9+ weeks of age (see Figs. 3A–C, v). We also confirmed a chronological reduction in the visual responses using the conventional method of drifting grating stimuli (see Supplementary Figs. S2, S3). 

Figure 3.

 

Contrast × spatial frequency (SF) joint preference map in the early visual regions over retinal degeneration progression. (A–C) Neural preference of dLGN (A), SC (B), and V1 (C) neurons in response to the flashing grating stimuli with various contrast and SF combinations. Average across neurons (numbers shown at the upper left corner). Ages were divided into four groups (i to iv, 4–5, 6, 7–8, and 9–17 weeks old, respectively) by corresponding to the behavioral task progression. Recordings for the control rats (v) were done at 9+ weeks old. Reddish and bluish colors represent SF (x-axis) and contrast (y-axis) combinations inducing spike increase and decrease relative to baseline firings, respectively (signal-to-noise ratio, z-score relative to baseline; see Analysis of neural responses to visual stimulation). Insets indicate the preferences normalized to a maximum value of each recording site and age group for visualization purpose. Until 6 weeks old, the neurons maintained the preferences for the flashing grating stimuli with low-to-middle SF (0.005–0.1 cycles/degree) at 50% to 96% of contrast. After 7 weeks old, these preferences got weak and eventually disappeared. Neurons in the control rats maintained the preferences even after 9 weeks old. (D) Response value at lowest SF (0.005 cycles/degree) and highest contrast condition (96%) of each neuron in dLGN (i), SC (ii), and V1 (iii) at different age groups (4–5, 6, 7–8, and 9+ weeks old) and control group (CTL). Values represent the mean ± 1 SEM across neurons (signal-to-noise ratio, z-score relative to baseline; see Analysis of neural responses to visual stimulation). Responses significantly decreased in 7 to 8- and 9+-week-old Royal College of Surgeons (RCS) rats, compared to younger RCS rats and aged congenic control rats. Asterisks with horizontal lines indicate P < 0.05 per pairwise comparison of post hoc Tukey's honestly significance difference (HSD) following one-way analysis of variance (ANOVA). (E) Proportion of neurons exhibiting significant response to the lowest SF and highest contrast grating patch stimulus compared to responses to lowest contrast grating patch stimuli (one-tailed one-sample t-test, P < 0.05). Filled area and inset number indicate a ratio of the responding neurons, and open area indicates a ratio of the non-responding neurons. Aged RCS rats tended to exhibit fewer neurons that maintain visual responses.

Given that the neurons in the early visual systems of RCS rats exhibited clear chronological reductions in the response to grating stimuli, we quantified these tendencies (Figs. 3D, 3E). We compared the maximum response value across the age groups and found that the neurons of the RCS rats exhibited statistically significant reductions in the visual response, especially at 7 to 8 weeks of age and older (see Figs 3D; dLGN, one-way ANOVA, F = 15.33, P = 2.88 × 10⁻¹²; SC, F = 34.35, P = 4.75 × 10⁻²⁶; V1, F = 23.59, P = 1.02 × 10⁻¹⁸; Supplementary Tables S1–S3 for post hoc Tukey's HSD test). We also counted the neurons exhibiting marked visual responses to the grating stimulus (see Figs 3E; lowest-SF highest-contrast condition versus lowest-contrast conditions, one-tailed one-sample t-test; see Materials and Methods), where the ratio of responding neurons tended to decrease with age in the RCS rats. These results indicate that neural responses in the early stages of the visual pathways are also reduced in a time course similarly to perceptual visual ability. 

Neural Contrast Sensitivity of RCS Rats Declined Over the Degeneration Progress

Given that gross response strength and the presence of visual neurons declined as the degeneration progressed, we subsequently explored whether neurons still maintaining visual responses alter their preferences. To address this, we extracted neurons that exhibited remarkable visual responses (see the filled bars in Fig. 3E) and reconstructed neural contrast sensitivity functions (Figs. 4A–C). The contrast sensitivity functions of the responding neurons exhibited biases towards low SF in all regions and age groups, as well as in the congenic control rats. The magnitude of the contrast sensitivity tended to decrease with age. We quantified and compared the contrast sensitivity across age groups with respect to the maximum contrast sensitivity value and optimal SF (Figs. 4D, 4E). Kruskal-Wallis H test revealed significant differences in these measurements across the age groups in all regions (dLGN, H_maxCS = 21.04, p_maxCS = 3.11 × 10⁻⁴, H_optSF = 16.16, p_optSF = 2.82 × 10⁻³; SC, H_maxCS = 18.95, p_maxCS = 8.04 × 10⁻⁴, H_optSF = 22.78, p_optSF = 1.40 × 10⁻⁴; V1, H_maxCS = 92.28, p_maxCS = 4.32 × 10⁻¹⁹, H_optSF = 10.39, p_optSF = 3.43 × 10⁻²). After conducting additional post hoc testing, specifically Dunn's test with Bonferroni correction, we found that: (1) the congenic control rats (CTL) exhibited significantly higher neural contrast sensitivity (dLGN, p_{9+ vs CTL} = 1.15 × 10⁻⁴; SC, p_{7–8 vs CTL} = 3.71 × 10⁻², p_{9+ vs CTL} = 3.13 × 10⁻²; V1, p_{4–5 vs CTL} = 2.24 × 10⁻⁷, p_{6 vs CTL} = 1.00 × 10⁻⁸, p_{7–8 vs CTL} = 4.51 × 10⁻¹⁷, p_{9+ vs CTL} = 4.70 × 10⁻¹¹), (2) neurons of the 7 to 8- and 9+-week-old RCS rats exhibited significantly lower contrast sensitivities (SC, p_{6 vs 7–8} = 3.14 × 10⁻², p_{6 vs 9+} = 3.43 × 10⁻²; V1, p_{4–5 vs 7–8} = 2.13 × 10⁻³, p_{6 vs 7–8} = 2.50 × 10⁻⁴), and (3) neurons of the 7 to 8- and 9+-week-old RCS rats exhibited significantly higher optimal SFs (dLGN, p_{4–5 vs 9+} = 3.74 × 10⁻³, p_{9+ vs CTL} = 2.47 × 10⁻²; SC, p_{6 vs 7–8} = 6.00 × 10⁻⁵). These findings suggest that, although the remaining visual responses retained remarkable strength, they were impaired. Additionally, neurons with a higher SF preference were less affected by retinal degeneration. Note that Figure 4E does not represent the contrast sensitivity value itself. Although the relative number of neurons preferring low SF decreased in aged RCS rats, the overall contrast sensitivity at low SF remained high. 

Figure 4.

 

Decrease of contrast sensitivity along with retinal degeneration progress. (A–C) Neural contrast sensitivity function of neurons exhibiting significant visual response (Fig 3E, filled area) in dLGN (A), SC (B), and V1 (C) at different age groups (i = 4–5 weeks old; ii = 6 weeks old; iii = 7–8 weeks old; and iv = 9+ weeks old) and control group (v). Contrast sensitivity functions were calculated from joint contrast × spatial frequency (SF) preference of neurons. In each SF, a zero-crossing contrast in a contrast tuning curve was determined with linear interpolation. After which, the inverse of the zero-crossing contrast was defined as a contrast sensitivity value. Solid lines indicate medians among neurons. Lower and upper dashed lines indicate 25% and 75% quantiles, respectively. Furthermore, visually responding neurons tended to exhibit attenuated contrast sensitivity functions upon aging. (D) Maximum contrast sensitivity value of each visually responding neuron in dLGN (i), SC (ii), and V1 (iii) at different age groups (4–5, 6, 7–8, and 9+ weeks old) and control group (CTL). Median and 25%/75% quantiles across neurons are presented. Neurons from aged Royal College of Surgeons (RCS) rats (7–8 and 9+ weeks old) exhibited significantly decreased contrast sensitivities compared to younger RCS rats (4–5 and 6 weeks old) and aged congenic control rats (CTL). (E) Optimal SF value eliciting the maximum contrast sensitivity value. Median and 25%/75% quantiles across neurons are presented. Neurons exhibiting visual responses preferred higher SF upon aging. Asterisks with solid lines indicate P < 0.05 per pairwise comparison of post hoc Tukey's honestly significance difference (HSD) following one-way analysis of variance (ANOVA). Asterisks with dashed lines indicate P < 0.05 for one-way ANOVA.

Perceptual Visual Ability to Detect Non-Structured Bright Spot was Maintained Over the Process of Retinal Degeneration

We found that some neurons of the aged RCS rats (7–8 and 9+ weeks of age) maintained their responses to the high-contrast and low-SF grating stimuli (see the insets in Figs. 3A–C) and that neural contrast sensitivity functions, under the lowest SF condition, were still observable in the aged RCS rats. Based on these observations, we subsequently investigated whether the behavioral detection ability of the non-structured bright spotlight was maintained in RCS rats of different ages (Fig. 5). This behavioral experiment was not performed in healthy control animals, as our primary focus was to confirm that overaged RCS rats still retain non-form vision ability. We trained six RCS rats to detect the LED turning on and lick the corresponding spout out of the three spouts to receive a water drop reward (see Fig. 5A). We tracked the correct-choice ratio and the time elapsed from LED turning on to rat licking in daily sessions as performance metrics (see Fig. 5B). In terms of the correct-choice ratio, all RCS rats exhibited higher values than the chance level (33%), which increased rapidly in the first week (3 weeks of age) and gradually in the next 2 weeks (4–5 weeks of age) and were maintained at around 80% throughout the experimental period until 11 weeks of age (see Fig. 5Bi). The time that elapsed from lighting to licking decreased rapidly in the first week (3 weeks of age; see Fig. 5Bii). This rapid reduction in the time elapsed from lighting to licking, as well as the rapid increase in the correct-choice ratio in the first week, likely reflected the animals’ learning progress. After 4 weeks of age, the RCS rats exhibited a gradually and significantly increasing trend of the time from lighting to licking (Spearman's rank correlation coefficient, ρ = 0.96, P < 0.001). These results suggest that the perceptual visual ability to detect non-structured stimuli was weakened but was retained until at least 11 weeks of age. 

Figure 5.

 

Light perception was maintained in aged Royal College of Surgeons (RCS) rats. (A) Three-alternative forced choice (3AFC) task sequence for evaluating detectability of bright light spot. (i) To initiate each trial, a rat must wait for 5 seconds without licking any spouts otherwise the wait-time count is reset. (ii) One of three LEDs is randomly chosen to turn on. (iii) The rat licks one of the three spouts. Licking the spout corresponding to the turned-on LED dispenses a small water drop as a reward. No matter which spouts the rat licks, the sequence returns to (i) and the next trial starts. The whole session continued for 1 to 3 hours. (B) The light perception of 6 individual RCS rats (gray lines) was assessed with the 3AFC task paradigm. All rats retained perceptual ability above chance level (red horizontal dashed line, 33% hit) at least until 11 weeks old (i), but the ability decreased, as indicated by the delayed times in licking the spout (ii). Black lines with circles indicate the mean across rats.

Neural Responses to Non-Structured Visual Stimuli Were Maintained Over the Process of Retinal Degeneration

Given that perceptual vision to detect a non-structured bright spotlight was maintained in aged RCS rats, we investigated neural responses to the non-structured flashlight visual stimulus in the early stages of the visual pathways during the retinal degeneration period (Fig. 6). We used a 1-ms flashlight stimulus to illuminate the entire contralateral visual field of the recording hemisphere. The heatmap of time course for SNR (see Figs. 6A–C; Supplementary Fig. S4 for firing rate in spk/sec; see Analysis of neural responses to visual stimulation) clearly showed the maintenance of the visual responses to the flashlight until at least 9 weeks of age in the 3 visual regions, except for neurons in the SC of 7 to 8- and 9+-week-old RCS rats, in which only slight increases in the pooled SNR time course were observed around 100 ms after stimulation onset. Similar trends were observed in the responses to long-duration flashlight stimulation (Supplementary Figs. S5, S6). 

Figure 6.

 

Neural responses to full-field uniform visual stimulation were maintained in aged Royal College of Surgeons (RCS) rats. (A–C) Z-scored peri-stimulus time histogram (signal-to-noise ratio [SNR] relative to baseline; see Analysis of neural responses to visual stimulation) of responses to the flashing light that illustrates the entire contralateral visual field obtained from neurons (vertical axes) in dLGN (A), SC (B), and V1 (C) at different age groups: (i) 4 to 5, (ii) 6, (iii) 7 to 8, and (iv) 9+ weeks old (weeks old) are presented. The black-and-white color bar next to the heatmap represents the response significance (white indicates a significant response; see Methods for the criteria). Neurons exhibited clear responses to the uniform flashlight stimulus even at 9+ weeks old. (D) Maximum SNR of each neuron in dLGN (i), SC (ii), and V1 (iii) at different age groups. Median and 25%/75% quantiles across neurons are presented. Asterisks with horizontal lines indicate P < 0.05 per pairwise comparison of post hoc Dunn's test. Neurons in aged Royal College of Surgeons (RCS) rats exhibited significantly decreased responsiveness. (E) proportions of neurons that exhibited significant visual responses to the flashlight stimuli (white stripes in A–C). Filled area and inset number indicate a ratio of the responding neurons, and the open area indicates a ratio of the non-responding neurons. Although there is a trend that the ratios decreased along with age, more than 50% of neurons in 9+-week-old RCS rats maintained their responsiveness to the uniform visual stimulation.

Next, we quantified the strength and presence of the neural responses to the flashlight stimulus (see Figs. 6D, 6E). Although the majority of neurons in all age groups and regions exhibited clear responses that fulfill the criteria (see the Methods section), the SNRs were significantly smaller in the 7 to 8- and 9+-week-old groups (see Fig. 6D; Kruskal-Wallis H test, dLGN, H = 23.99, P = 2.51 × 10⁻⁵; SC, H = 53.68, P = 1.31 × 10⁻¹¹; V1, H = 108.26, P = 2.60 × 10⁻²³; see Supplementary Tables S4–S6 for post hoc Dunn's test). However, over half of the identified neurons exhibited significant responses to the flashlight stimulus even after 9 weeks of age (see Fig. 6E), which was clearly higher than that in the presence of a response to structured visual stimuli (see Fig. 3E). These results indicate that neural responses to non-structured visual stimuli are robust against retinal degeneration. 

Next, we investigated how the maintained response properties changed (Fig. 7). Similar to the above analysis comparing the SNRs of all identified units among the age groups (see Fig. 6), especially in the SC and V1, the peak SNRs of the maintained visual responses to the flashlight stimulus decreased in older RCS rats (see Figs. 7A–C, left; dLGN, Kruskal-Wallis H test, H = 6.66, P = 0.08; SC, H = 28.75, P = 2.52 × 10⁻⁶; V1, H = 94.80, P = 2.04 × 10⁻²⁰; see Supplementary Tables S7, S11, and S15 for post hoc Dunn's test). Concurrently, the peak latency of the flashlight response increased with age, especially in the dLGN (see Figs. 7A–C, second left; dLGN, H = 26.54, P = 7.35 × 10⁻⁶; SC, H = 0.60, P = 0.90; V1, H = 6.14, P = 0.11; see Supplementary Tables S8, S12, S16 for post hoc Dunn’s test). These results suggest that non-form visual responses are robust to retinal degeneration. 

Figure 7.

 

Flash responses of neurons weakened and slowed in conjunction with age-related decline. (A–C) Peri-stimulus time histograms (PSTHs) of neural responses in dLGN (A), SC (B), and V1 (C) to the uniform visual stimulation were assessed in terms of (left) peak signal-to-noise ratio (SNR), (second from the left) peak latency, (second from the right) peak firing rate, and (right) spontaneous (500-ms pre-stimulation) firing rate. Only visually responding neurons (Fig. 6E, filled area) were analyzed. Median and 25%/75% quantiles across neurons are presented. Asterisks with solid lines indicate P < 0.05 per pairwise comparison of post hoc Tukey's honestly significant difference (HSD) test. Neurons of aged Royal College of Surgeons (RCS) rats exhibited significantly lower SNRs and longer latencies, which were accompanied by significant decreases in the evoked firing rate.

Photoreceptor loss leads to a spontaneous activity increase in RGCs.⁶⁵ To clarify if the reduction of SNRs in the early visual areas following the RGCs is associated with the decrease in evoked firing and/or the increase in spontaneous firing, we measured peak firing rates 20 to 300 ms after the flashlight stimulation onset and mean firing rates across the 500 ms prestimulation period (see Figs. 7A–C, right two columns). The peak firing rates, especially in the SC and V1, significantly decreased with age (dLGN, H = 1.78, P = 0.62; SC, H = 13.53, P = 3.62 × 10⁻³; V1, H = 28.76, P = 2.52 × 10⁻⁶; see Supplementary Tables S9, S13, S17 for post hoc Dunn’s test). In contrast, the prestimulation firing rates did not change with age (dLGN, H = 3.68, P = 0.30; SC, H = 2.34, P = 0.51; V1, H = 5.28, P = 0.15; see Supplementary Tables S10, S14, S18 for post hoc Dunn’s test). These findings indicate that the reduced SNR could be attributed to a decrease in evoked responses rather than an increase in spontaneous activity. These altered responses are primarily associated with the progression of retinal degeneration in the early visual system, which directly or indirectly receives inputs from RGCs. In other words, the changes in visual parameters in response to non-form stimuli may be attributed to the gradual loss of residual rod/cone cells in the early stage of RP, whereas the maintenance of light responses in the late stage of RP is due to the function of ipRGCs. 

Discussion

In this study, we evaluated both form and non-form vision in RCS rats using behavioral psychological and electrophysiological techniques. We found that perceptual and neural form visual abilities declined by 9 weeks of ages, whereas light perception was retained until at least 11 weeks of age. 

RCS rats have been used to study several experimental treatments for blindness.^{16,17,25–31,66} In these studies, the reflexive visual ability of form vision was assessed using optokinetic reactions.^7,16,30,31 This method is rapid and allows for repeated measurements of contrast and SF sensitivity without animal training. Therefore, it can measure the progressive loss of reflexive visual ability from an early period of life (e.g. from 8 weeks of age).³⁰ In a perception task, the visual water maze task has been used to measure visual ability.^36,67 In this method, visual ability can be measured after a short training period,⁶⁷ but it is difficult to measure visual acuity accurately because of the faltering viewing distance in the pool and the range of contrast × SF parameters. Although combining the 2AFC-VGDT with the staircase method would eliminate these problems, the 2AFC method requires a long training period,⁶⁸ which makes it impossible to measure the visual ability of RCS rats before they develop RP. In response, we adopted a rapid and efficient training protocol for RCS rats, successfully measured perceptual but not reflexive contrast sensitivity in 6-week-old RCS rats, and continuously monitored the progressive loss of form vision (see Fig. 1). Therefore, this system is useful for assaying the protective or restorative effects of various experimental treatments for RP, including biomedical engineering^25,66 as well as exogenous expression of optogenetic tools^16,17 and cell grafts.^7,28–31 

In addition to the contrast sensitivity function in RCS rats, we investigated the neural responses to structured stimuli in the dLGN, SC, and V1 neurons in RCS rats (see Figs. 2–4). Given that retinal input prior to P14 is sufficient to specify the basic visual circuits in rodents,^69,70 our results indicate that the basic visual circuits for expressing visual response properties, that is SF selectivity, develop until the early postnatal period in RCS rats. However, after this period, neural responses to structured stimuli began to decline and were finally lost after 9+ weeks of age (see Figs. 3, 4). 

This progressive loss of structural visual ability was accompanied by an increase in optimal SF (see Fig. 4E). This finding led us to another interesting hypothesis: retinal neurons with a lower SF preference are selectively affected by retinal degeneration in RCS rats. In mice, sustained ON alpha RGCs, recognized as a major RGC type that conveys visual information to the brain, are densely distributed around the temporal retinal region corresponding to the binocular visual field, where their dendritic fields are smaller,⁷¹ probably leading to finer spatial structure tuning in the temporal retina. If a similar RGC property is observed in the rat retina, the elevation of the optimal SF in our results may be due to selective degeneration of the nasal retina, which may correspond to the peripheral visual field. In human RP, degeneration occurs in the peripheral retina (peripheral visual field), and the central retina (central visual field) is relatively preserved.⁷² Thus, the RP rat model may also exhibit a similar degeneration pattern in terms of the visual field. In addition, several subtypes of mouse RGCs are remodeled through retinal degeneration, in which dendritic fields become smaller and simpler in the central retina.⁷³ Additionally, in patients with RP, V1 remodeling occurs, where the peripheral cortical regions that lose visual inputs begin to receive signals corresponding to the central retinal region.⁷⁴ Central retinal ganglion cells typically have smaller receptive fields.^75,76 Therefore, if a similar reconnection mechanism occurs in RCS rats, the remaining cells in V1 may exhibit finer SF selectivity. Further evaluation of the dendritic/receptive field location and the size of preserved neurons will clarify this point. Thus, progressive loss of the spatial profile depends on photoreceptor dysfunction and remodeling of peripheral and central cells. The protective effects of cell grafts have been demonstrated at the neural^7,28,29 and reflexive^27,30,31 levels. It is also important to confirm that RP treatment is effective in perceptual tasks, such as the 2AFC-VGDT. Our method allows for such an evaluation. 

Although there is a positive correlation between histological retinal degeneration and retinal neural activity,^25,26 a significant gap exists between perceptual visual acuity (maintained until 7 months of age) and cortical neural activity (maintained only until 4 weeks of age).^35,36 In this study, cortical and subcortical neurons showed a progressive decrease in visual responses with age across all measured visual areas (see Figs. 3, 4), paralleling the progressive decline in contrast sensitivity (see Fig. 1). This age-dependent reduction of visual sensitivity to gratings in both neural responses and behavioral levels exhibited a time scale similar to a previous histological study that reported that the mean thickness of the outer nuclear layer in 9-week-old RCS rats was nearly one quarter that of 5-week-old rats.²⁵ Thus, the nearly complete loss of perceptual ability in form vision seemed to occur after 9 weeks of age. 

The time courses for the preservation of neural and perceptual form vision observed in this study differ from results in some previous studies (e.g. Ref. 35, 36). These discrepancies may be attributed to differences in task structures and recording paradigms. In the visual water task, animals must pay close attention to the cue to find the platform and survive, potentially driving their visual performance to its limit. Conversely, in our task, animals can repeat trials and receive a water reward, which could make them less attentive (in a more natural state) and result in an underestimation of their performance. In our study, we used head-fixed, awake animals for neural activity recordings, a condition that likely provides a better correlation to behavioral performance compared with neural activities obtained from urethane-anesthetized animals,³⁵ where neural activity is significantly reduced. Because it is relatively easier to record neural activities during the assessment of visual acuity in our task compared to the visual water task, future studies will aim to clarify the correlation between perceptual visual acuity and neural activities. 

As for non-form vision, residual rod/cone cells and ipRGCs can elicit visual responses to high-luminance visual stimuli in the RGC^26,40 or SC²⁷ neurons of RCS rats, even after 9 weeks of age. Accordingly, compared to the structured stimulus, high contrast non-form stimulus evoked visual responses in greater population of neurons from the dLGN, SC, and V1 regardless of the rat’s age (see Fig. 6), accompanied by the prolongation of peak latency and a decrease in the peak firing rate (see Fig. 7). Our results indicate that visual responses are elicited in all visual areas until at least 11 weeks of age. These visual responses were sufficient to express the light-evoked perceptual behaviors (see Fig. 5). This maintenance of light perception in the late stage of RP is may due to ipRGCs functions.^38,40,41,77 

We observed a positive correlation between the time elapsed from the LED emitting light to a rat licking the spout and the latency of visual responses (see Figs. 5, 7). However, we cannot conclude whether these changes are due to RP progression or aging, as we did not measure both parameters in non-RP animals in this study. Further recordings of visual responses in these model animals during visual-cue-guided tasks are necessary to clarify this aspect. 

We found that the structural visual response in the early stages of the visual pathway declined by 9 weeks of age (see Figs. 3, 4). In terms of intra-retinal,⁷⁸ retinogeniculate,⁷⁹ and geniculocortical⁸⁰ connections, convergent projections have been observed; single neurons in higher visual regions receive input from multiple neurons in lower visual regions. Thus, the loss of response in lower regions will “virtually” impair the spatial integrity of neural responses in higher regions, even if the responsiveness of neurons in higher regions is maintained. Do the response reductions in our results reflect scattered and lost signal inputs caused by retinal degeneration, which lead to the impaired formation of spatial vision? Or is neural responsiveness in the early stages of the visual pathway also degraded during retinal degeneration, like glaucoma?⁸¹ Using voltage-sensitive dye imaging and intracortical microstimulation, Miyamoto et al. showed that completely blind (99-week-old) RCS rats maintained cortical neural responsiveness to electrical stimulation.⁸² Given their findings, the reduced visual responses in the early stages of visual pathways may reflect impaired inputs from the degenerated retina. In addition to preserving neural responsiveness, cortical plasticity is preserved after retinal degradation. For example, a mouse model of retinal degeneration exhibited visual cortical plasticity to monocular deprivation (ocular dominance plasticity) at post-natal day (P) 60 and synaptic plasticity induced by theta burst stimulation (long-term potentiation) at P60 and P180, where the levels of plasticity were comparable to those in wild-type mice.⁸³ In addition, taken together, these results further suggest that visual cortical neurons, at least, preserve the basic level of neurophysiological functions during and even after retinal degeneration. Therefore, the visual cortex can be an effective target for visual prostheses in the treatment of severe or end-stage RP. However, we need to carefully consider the long-term plasticity observed in human patients.⁷⁴ 

In conclusion, treatments for age-related visual dysfunctions, such as RP and age-related macular degeneration, have been gaining attention as the frequency of these diseases increases. In such cases, the evaluation of perceptual and reflexive visual abilities is important. In this study, we demonstrated the chronological changes in the response to visual stimuli, both structured and non-structured, in RP model rats. These findings offer valuable criteria for assessing visual recovery resulting from experimental treatments.^{7–21,32–34} Although the findings in the current study are limited to the single rat strain (RCS rat), RP is a heterogeneous disease.⁸⁴ To further elucidate the effect of RP on perception and neural activity and generalize the findings across strains, future studies must be done with other RP model animals like rd10 mouse^83,85 and S334ter-line-3 rat.^86–88 In such scenarios, our task could be useful for testing the contrast sensitivity, which could further aid in the development of new therapies. 

Acknowledgments

The authors thank H. Sawai, T. Miyoshi, H. Osaki, M. Midorikawa, and H. Sato for their helpful suggestions and discussions. Furthermore, we sincerely appreciate the technical assistance of Y. Yamamoto and R. Tatsuta. 

Supported by Grants-in-Aid for Young Scientists (JP20K15934 to S. Soma), Scientific Research on Innovative Areas (JP20H05069 to S. Soma), Challenging Research (Exploratory) (JP 24K22276 to S. Soma); and Scientific Research (JP22H03255 to S. Soma), from JSPS; by the Japanese Retinitis Pigmentosa Society (S. Soma); by the AMO Japan (S. Soma); by the Takeda Science Foundation (S. Soma); by the Uehara Memorial Foundation(S. Soma); and by the Senri Life Science Foundation (S. Soma). 

Author Contributions: N.S. and S. Soma designed the research; N.S., A.Y.S., A.K., S. Shimegi, and S. Soma performed the research; N.S., A.Y.S., A.K., and S. Soma analyzed the data; and N.S. and S. Soma wrote the manuscript with input from all authors. 

Disclosure: N. Suematsu, None; A.Y. Sato, None; A. Kimura, None; S. Shimegi, None; S. Soma, None