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Abstract
The lack of a non-invasive or minimally invasive imaging technique has long been a challenge to investigating brain activities in mice. Functional magnetic resonance imaging and the more recently developed diffuse optical imaging both suffer from limited spatial resolution. Photoacoustic (PA) imaging combines the sensitivity of optical excitation to hemodynamic changes and ultrasound detection's relatively high spatial resolution. In this study, we evaluated the feasibility of using a label-free, real-time PA computed tomography (PACT) system to measure visually evoked hemodynamic responses within the primary visual cortex (V1) in mice. Photostimulation of the retinas evoked significantly faster and stronger V1 responses in wild-type mice than in age-matched rod/cone-degenerate mice, consistent with known differences between rod/cone- vs. melanopsin-mediated photoreception. In conclusion, the PACT system in this study has sufficient sensitivity and spatial resolution to resolve visual cortical hemodynamics during retinal photostimulation, and PACT is a potential tool for investigating visually evoked brain activities in mouse models of retinal diseases.
© 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
1. Introduction
Mouse models play a critical role in vision research due to their genetic, physiologic, and anatomic similarity to humans, as well as the availability of various mouse genetics tools [1]. Mapping and modeling cortical responses to visual stimulation in mice have attracted broad research interest [2–4]. Microelectrode systems, which directly measure neurons’ electrical potentials, have been the primary tool for recording neural activities in the mouse brain [5]. However, accurately positioning an electrode within a region-of-interest (ROI) is challenging and requires post-recording histological confirmation. Furthermore, an electrode can typically only record from a small subset of neurons within a brain region (e.g. the primary visual cortex). Given the considerable physiologic heterogeneity among cell types, responses sampled from a few neurons may not be representative of the region’s overall responsivity. Therefore, non-invasive or minimally invasive imaging technologies that can observe neural activities within a large part of the brain are advantageous.
Functional magnetic resonance imaging (fMRI) has been widely used to detect functional changes in the brain by using the blood oxygenation level-dependent (BOLD) effect [6,7]. However, the dependence on the net magnetization of fMRI limits the spatial resolution to millimeters and temporal resolution to hundreds of milliseconds [2–4]. On the other hand, optical brain imaging can provide complementary information to other modalities such as fMRI and offer a low-cost alternative in many settings [8–11]. Diffused optical tomography (DOT), also known as functional near-infrared spectroscopy (fNIRS), is a well-developed brain imaging method [12–14] that has been used to visualize functional modules in the cerebral cortex. DOT has enabled the visualization of functional organization in visual, auditory, and somatosensory cortical areas [15,16]. Such visualization is made through monitoring variations in cerebral blood volume (CBV) and blood oxygenation (sO2) driven by functionally specific neural activity. However, due to strong light scattering in brain tissue, it suffers from poor spatial resolution (∼5 mm), making it hard to resolve the visual cortices in the mouse brain.
Photoacoustic imaging [17], by combining optical sensitivity comparable to DOT, excellent spatial resolution, and rapid frame rate, provides unique solutions to the abovementioned technical barriers. Optical resolution photoacoustic microscopy (OR-PAM), using focused optical energy and raster scanning, resolves micron-scale vasculatures and hemodynamic responses to electrical stimulation at the surface of the mouse brain [18–20]. Photoacoustic computed tomography (PACT), taking advantage of ultrasound beamforming and penetration [21–23], has achieved whole-brain imaging with a high spatial resolution (∼100–300 µm) and imaging depth of a few centimeters [24,25]. PACT has successfully revealed resting-state functional connectivity in multiple cortical areas [26], as well as evoked cortical responses to electrical stimulations with [27] and without an optical contrast agent [25]. Therefore, PACT is a promising tool for observing neural responses at varying depths within the mouse brain [2].
However, few studies have reported PA measurements of subtle hemodynamic changes in response to natural (i.e. non-electrical) sensory stimulation due to the low signal-to-noise ratio caused by laser energy fluctuations and other system noises. This study aims to improve the methodologies of using PACT to observe visual cortical responses to retinal photostimulation in mice. Retinal degeneration and wild-type, control groups were compared to examine the reliability of the quantitative features extracted from the PACT images.
2. Materials and methods
2.1 Mouse preparation
All animal procedures were approved by the Institutional Animal Care and Use Committee at the University of Michigan. We used 4- to 7-month-old C57BL/6 wild-type mice and homozygous rd1 retinal degenerate mice, maintaining them in a 12 h light/dark cycle and performing PACT imaging during the light phase. Before imaging, each mouse was dark-adapted overnight and anesthetized by 1% isoflurane at an airflow rate of 1.5 L/min in conjunction with an intraperitoneal injection of acepromazine (5 mg/kg) [28]. The scalp of the animal was removed to minimize optical and acoustic attenuation. The mouse was then secured to a multi-axis translation stage, and the cortex surface aligned with the imaging plane. At the end of the experiments, the mouse was euthanized by carbon dioxide inhalation and bilateral pneumothorax.
2.2 Imaging system
Figure 1(A) shows a schematic of our photoacoustic computed tomography (PACT) system for real-time mouse brain imaging. An Nd:YAG laser (Quantel, Brillant B) at 1064 nm was used as the excitation source (pulse duration 4-6 ns, pulse repetition rate 10 Hz, pulse energy variation < 5%). This wavelength was chosen for the following reasons. First, mouse retinal photoreceptors are insensitive to near-infrared (NIR) light [29,30], so the imaging illumination will not interfere with the visual stimulation. Second, pioneer brain PA imaging studies [24] showed that, at 1064 nm, HbO2 possesses sufficient optical absorption for observing hemodynamics and the limited water attenuation allows for reasonable optical penetration in the mouse brain [31]. Finally, the low variation in pulse energy minimizes measurement fluctuation, thereby facilitating the detection of the true signals correlated to cortical responses. The laser beam was expanded by a pair of concave and convex lenses to 1 cm in diameter to cover the whole horizontal surface of the brain. The optical fluence at the skull surface was approximately 50 mJ/cm2, well below the safety limit of 100 mJ/cm2 at 1064 nm established by the American National Standards Institute. A customized 256-element full-ring ultrasonic transducer array with a 5 cm inner diameter captured the excited PA signals. The array has an 80% bandwidth at a central frequency of 10 MHz. Within the 2-cm-diameter field of view at the center of the array, the system has an axial resolution of 400 µm and a lateral resolution of 200 µm. The PA signals were digitalized and sampled at 40 MHz using a Vantage 256 ultrasound research system (Verasonics, Redmond, WA).
Fig. 1. System overview. (A) Schematic of the PACT system. (B) Photograph of the cortical vasculature of a mouse brain with the scalp removed. (C) The representative PACT image using 1064 nm excitation light. (VSX: Verasonics system, SSS: the superior sagittal sinus, TS: the transverse sinus, and CoS: the confluence of sinuses)
2.3 Retinal photostimulation
The visual stimulus was broadband white light generated by a fiber-optic halogen illuminator (HL150-B, AmScope) flickering at 1 Hz and positioned about 5 cm from each eye, producing an irradiance of approximately 16 mW/cm2 at the cornea. Before photostimulation, the mouse was kept in constant darkness for baseline measurement. Then, both eyes were simultaneously exposed to the flickering stimulus for 20 sec, followed by another 10 min in darkness, during which PACT imaging continued to monitor hemodynamic recovery from the photoresponse.
2.4 Image reconstruction and signal processing
The PACT images were reconstructed using a delay-and-sum beamforming algorithm from the acquired signals. To compensate for brain movement due to animal breathing or heartbeats, the frames of the time-lapsed PACT video were co-registered by landmarks such as the major blood vessels, including the superior sagittal sinus (SSS), the transverse sinus (TS), and the confluence of sinuses (CoS) (Fig. 1(B), (C)). The temporal trace of each pixel was always extracted from the PACT video as 600 consecutive frames covering a 1-min period, consisting of 200 frames (i.e. 20 sec) before stimulation, 200 frames during stimulation, and 200 frames right after stimulation (Fig. 2(A)). Each 600-frame trace was first detrended by subtracting the linear fitting line of the pre-stimulation temporal trace to remove the systematic shift from the detected signal. Then, it was normalized by the root-mean-square of the signal strength of the original pre-stimulation temporal trace before subtraction, resulting in the baseline-subtracted and normalized PA signals (ΔPA/PA). A spatial moving average of 3×3 pixels and a temporal forward-moving average of 25 frames (2.5 sec) were also applied to filter out the noise from random fluctuations (Fig. 2(B)).
Fig. 2. Demonstration of the pair-wise correlation map. (A-C) The procedure of the production of a pair-wise correlation map. Consecutive frames covering a 1-min period were detrended and normalized. The temporal trace of each pair of pixels was then correlated pair-wise to produce the correlation map. (D) A representative correlation map during visual stimulation. (M1: primary motor cortex, M2: secondary motor cortex, S1: primary somatosensory cortex, S2: secondary somatosensory cortex, Au: auditory cortex, and V1: primary visual cortex) (E) The temporal traces of the background-subtracted and normalized PA signals (ΔPA/PA) for a single pixel at the highest correlation coefficient located in V1 in (D) from both left (red) and right (green) hemispheres. (F) The average temporal traces of ΔPA/PA for all pixels within V1 from both left (red) and right (green) hemispheres. The shaded area represents the period of visual stimulation.
2.5 Pair-wise correlation map and temporal trace analysis
To extract the hemodynamic response to retinal photostimulation with higher confidence, we introduced the concept of a pair-wise correlation map. First, the PACT images of the brain were separated into left and right hemispheres, and the pixels equidistant from the midline were paired (Fig. 2(C)). The correlation coefficient between the left-hemisphere and right-hemisphere temporal traces was then calculated and a pair-wise correlation map was generated for each pair of pixels. Since both mouse eyes were stimulated during the experiment, the hemodynamic response was expected to occur on both sides of the brain. If the PA signal change originated from the hemodynamic response, the changes from both sides should have similar amplitudes and kinetics, thus producing high correlation coefficients. On the other hand, if the PA signal changes were from random fluctuation, the changes would have random intensity fluctuation, and this pair of temporal traces would only have low correlation coefficients. This approach effectively enhances the detection of true hemodynamic response over stochastic fluctuations in the background, as shown in Fig. 2(D). The hemodynamic response can be obtained by extracting the temporal traces at the locations with the highest left vs. right correlation coefficients (Fig. 2(E)). The fluctuations were suppressed compared to the average temporal traces in the left and right primary visual cortex (V1) region (Fig. 2(F)). The response amplitude and peak latency of the visually evoked hemodynamic response were quantified, verified with a Shapiro-Wilk test for normality, and compared between wild-type and rd1 mice using a two-tailed Student’s t-test. Potential male vs. female differences was also examined.
3. Results
3.1 Pair-wise correlation map
Figure 2(D) shows a representative correlation map generated from a wild-type mouse during visual stimulation. The correlation map was symmetrical along the midline of the brain because it was correlated pair-wise for pixels equidistant from the midline. Among the major cortical areas (the motor cortices, the somatosensory cortices, the auditory cortex, and the primary visual cortex), only the primary visual cortex (V1) showed correlation coefficients exceeding 0.2 within most of its total area. The temporal traces at the locations with the highest correlation coefficient on both left and right hemispheres in the correlation map are shown in Fig. 2(E). Much stronger hemodynamic responses were obtained than the average responses in V1 (Fig. 2(F)), which validates the effectiveness of this method.
3.2 Retinal photostimulation procedure and time-lapsed correlation maps
Figure 3 shows the timeline of the retinal photostimulation procedure. The pair-wise correlation maps derived from wild-type mice at multiple time points are shown in Fig. 3(B). Because the differences of the PACT images between each time points were not significant, we utilized correlation maps to show the effect of stimulation throughout the procedure. The first two time points showed low correlation coefficients at the pre-stimulation stage. During the stimulation (time point 3), the highest correlation occurred in V1, and the correlation decreased shortly after the stimulation (time point 4). 10 min post-stimulation (time point 5), the correlation values throughout the observed regions had returned to pre-stimulation levels.
Fig. 3. The timeline of retinal photostimulation and the corresponding pair-wise correlation maps at each time point for wild-type and rd1 mice. (A) Each time point is a 1-min period. Time point 1: pre-stimulation (0m0s–1m0s); time point 2: shortly before the stimulation (8m40s–9m40s); time point 3: during the stimulation, including 20 sec of pre-stimulation, 20 sec of flickering stimulus, and 20 sec of post-stimulation (9m40s–10m40s); time point 4: shortly after the stimulation (10m40s–11m40s); time point 5: post-stimulation (19m–20 m). (B) Average photoacoustic images and pair-wise correlation maps of wild-type and (D) rd1 mice at each time point.
For the comparison of pair-wise correlation maps of wild-type and rd1 mice (Fig. 3(B) and 3(C)), the two strains showed similar trends in their correlation map changes along the experimental timeline. The main difference between the two correlation maps is that the highest correlation coefficients in rd1 mice were lower than those in wild-type mice.
3.3 Temporal traces of visually evoked hemodynamic changes in the primary visual cortex
We imaged a total of 3 male and 3 female wild-type mice, as well as 3 male and 3 female rd1 mice. Figure 4(A) and 4(B) show each mouse's temporal traces of hemodynamic change at the V1 locations with the highest left vs. right correlation coefficients. The population-averaged temporal traces from all 6 wild-type mice and 6 rd1 mice are shown in Fig. 4(C) and 4(D), respectively. Though there were individual differences, wild-type mice generally had responses with higher response amplitudes and shorter peak latencies (∼5–15 sec for wild-type, ∼10–35 sec for rd1).
Fig. 4. PACT imaging of visually evoked hemodynamic change in vivo. (A & B) The individual temporal traces of the background-subtracted and normalized PA signals (ΔPA/PA) for a single pixel located in V1 on both left and right hemispheres from wild-type and rd1 mice. (C & D) The mean temporal trace of ΔPA/PA for single pixels located in V1 from both left and right hemispheres of 6 wild-type mice and 6 rd1 mice. Dark control recordings obtained without photostimulation are shown in light red or light green. Shaded areas represent the period of stimulation. The red and green dots indicate the peak responses for the calculation of response amplitudes and peak latencies. The response amplitude was calculated by measuring the difference between the peak intensity and the mean pre-stimulation intensity. The peak latency was calculated from the time when the signal reached the maximum intensity after the onset of photostimulation.
Two-tailed Student’s t-test showed that these differences were significant, with p = 0.0075 for response amplitude and p < 0.001 for peak latency (Fig. 5(A)). Figure 5(B) shows that the two sexes had comparable response amplitudes and peak latencies for wild-type and rd1 mice.
Fig. 5. Statistical analysis. (A) Comparing the response amplitude and peak latency for wild-type and rd1 mice. **, p<0.01 (n = 6,6); ***, p<0.005 (n = 6,6); (B) Comparisons between male and female wild-type and rd1 mice.
4. Discussion
The methodologies presented in this study successfully resolved visual cortical responses to retinal photostimulation in the mouse brain. Although raw photoacoustic signals suffered from low signal-to-noise ratios, the bilateral correlation mapping assisted in localizing cortical areas with visually evoked hemodynamic activities. Quantitative analysis of the temporal traces at those locations showed significant differences between rd1 retinal degeneration and normal control mice. Compared to wild-type mice with all retinal photoreceptors intact, rod/cone-degenerate rd1 mice detecting light via only melanopsin demonstrated attenuated and delayed photoresponses, which is consistent with our electrophysiological recordings from retinal ganglion cells [32] and with recordings from the visual thalamus [33]. Therefore, this imaging method may facilitate less invasive cortical measurements in vision research.
By using a laser with higher repetition rates, the data acquisition system in this study should be able to provide sampling frame rates up to 10 kHz [34] on the same scale as electrophysiological measurements [5]. The imaging plane covers the brain’s surface and can observe visually evoked activities in the superficial V1 cortices. However, this imaging geometry limited resolution in the deep brain where other visual nuclei such as the lateral geniculate nucleus (LGN) and superior colliculus (SC) are located. Linear, curved, and even hemispherical arrays may be used in our future work to image these deeper brain regions and thereby enable a more comprehensive analysis of the mouse visual system. Besides, the system can utilize multiple optical wavelengths for detecting changes in blood oxygenation (sO2), which is another measure of the cortical response to stimulation.
The central line in the correlation map is always bright (Fig. 2(C), Fig. 3) because it divides the superior sagittal sinus, which is at the center of the brain, in half. The high correlation between the two halves of the same vessel serves to validate our method. One limitation of this method is that the bilateral correlation map is based on simultaneous photostimulation of both eyes. Although this is acceptable for studying mouse models with bilaterally symmetrical visual function, this method may have to be adjusted for disease models with unilateral vision loss. We are developing unilateral correlation calculation methods to generalize the imaging system to all mouse models.
5. Conclusions
In summary, we have built a label-free, high-resolution PACT system for imaging the mouse brain and monitoring the hemodynamic response in real-time throughout different brain regions. Hemodynamic changes within the primary visual cortex (V1) in response to retinal photostimulation have been observed while other regions remained largely at rest. The responses of rod/cone-degenerate mice (rd1) were also compared with those of wild-type mice to confirm that this technique is sufficiently sensitive to detect significant differences in the amplitude and latency of these responses. This shows the potential of our system for studying the connectivity between early visual processing in the retina and higher-level visual processing in the cortex.
Funding
MCubed, University of Michigan; National Institute of Diabetes and Digestive and Kidney Diseases (R01DK125687); National Cancer Institute (R37CA222829).
Disclosures
The authors declare no conflicts of interest.
Data availability
Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.
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