1.IntroductionAt the population level, astrocytes dynamically interact with neurons.1–3 Astrocytes sense activity within the neuronal network and respond to neural signals by generating activities in vivo.4,5 Simultaneously, astrocyte activation or manipulation modulates neuronal network activity.2,3 This bidirectional, interconnected communication between astrocytes and neurons is collectively termed the “astrocyte-neuronal network.”6,7 Accumulating experimental evidence suggests that various behaviors result from coordinated activity between neurons and astrocytes within these networks.2,8,9 Therefore, deciphering the interaction between astrocytes and neurons within astrocyte-neuronal networks is essential for comprehensively understanding the genesis and dysregulation of behavior.2,3,10 Neurons and astrocytes in the brain exhibit diverse structures, functions, and molecular compositions depending on their respective regions.11–14 These diversities enable them to modulate and support neural circuits in a region-specific manner.15 The brain comprises multiple distinct regions, each characterized by unique combinations of neuronal subtypes and astrocytic populations.12 Previous studies have revealed that astrocyte-neuronal networks can be regionally regulated by noradrenergic terminals.16 However, the mechanisms by which astrocyte-neuronal networks employ region-specific strategies to regulate particular circuits remain not fully understood. Furthermore, behaviors critically depend on the synchronized activity of distinct brain regions.17,18 Recent studies indicate that neurons across various brain areas interact simultaneously and function in parallel during a wide range of behaviors.17 Astrocyte populations in different brain regions can coordinately respond to activity from long-range neuronal projections, thereby influencing brain states and complex behaviors.3 Nevertheless, it remains uncertain whether astrocyte-neuronal networks can generate correlated activity patterns across different regions and facilitate effective communication between them. Therefore, real-time measurement of astrocyte-neuronal network signals from multiple brain regions is essential for understanding the brain as a dynamic system and fully comprehending how circuit activity patterns relate to behavior. Fiber photometry uses a fiber optic cannula to monitor fluorescent signals.19 When combined with genetically encoded calcium indicators (GECIs), it enables real-time monitoring of the population activity of specific cell types in freely behaving mice.20–22 Researchers have employed fiber photometry to explore diverse forms of activity in the brain, including the activity of specific types of neurons, as well as astrocytic activity and neurotransmitter/neuropeptide signals.19 Multi-color fiber photometry is particularly useful for simultaneously monitoring the activities of distinct types of cells.21,23,24 Using green and red GECIs, this technique can measure activities from either two types of neurons23,24 or from neurons and astrocytes simultaneously.21 Moreover, multi-fiber photometry allows the recording of fluorescent activity signals from multiple brain regions in the same freely behaving animal.21,23,25 This technique provides a comprehensive view of neural network activity and helps investigate functional connectivity between brain regions.25 Researchers have utilized dual-site fiber photometry to simultaneously monitor astrocytic activities across two brain regions.16,26 They have observed highly correlated astrocytic activities in response to locomotion in these regions,26 as well as regionally regulated astrocyte-neuronal networks.16 However, current methods for simultaneously measuring astrocytic and neuronal activities across multiple brain regions during behavior are limited. Developing a method to address these limitations will be crucial for fully elucidating the role of the astrocyte-neuronal network in the global brain circuit during complex behavioral processes. In this study, we present a novel approach that combines cell-specific dual-color GECIs with multi-fiber photometry to simultaneously monitor astrocytic and neuronal activities across multiple brain regions in freely behaving mice. Our results validate the effectiveness of this method in investigating the complex interactions between astrocytes and neurons within and between different brain areas during natural behaviors. This technique enables researchers to map and analyze the functional connectivity between astrocytes and neurons across various brain regions while animals perform specific behavioral tasks. 2.Methods2.1.AnimalsC57BL/6 mice were sourced from the Laboratory Animal Center at the Third Military Medical University. We utilized 3- to 5-month-old C57BL/6 mice for our study. The mice were group-housed under a 12-h light/dark cycle and had ad libitum access to food and water. Mice implanted with optical fibers were individually housed. All animal experiments adhered to the guidelines set forth by the Institutional Animal Care and Use Committee of the Third Military Medical University, China (Animal Ethical Statement NO. AMUWEC20230126). 2.2.Viral VectorThe viral vectors used in this study included AAV5-GfaABC1D-cyto-GCaMP6f (52925, titer , Addgene, United States), AAV5-GfaABC1D-Lck-GFP-SV40 (105598, titer , Addgene, United States), AAV9-hSyn-NES-jRGECO1a-WPRE-SV40 (100854, titer , Addgene, United States), and AAV9-hSyn-NES-mCherry-WPRE-SV40 (114472, titer , Addgene, United States). 2.3.Stereotactic Virus InjectionThe mice underwent anesthesia with 1% to 2% isoflurane in oxygen and were subsequently positioned in a stereotactic head frame on a heating pad (37.5°C to 38°C), following previously established protocols.20 After exposing the skin, the skull was uncovered, and a small craniotomy () was performed directly over the injection site. We utilized specific coordinates for injections: S1 [anterior-posterior (AP) , mediolateral (ML) , dorsoventral (DV) ], M1 (AP 0 mm, ML , DV ), and CA1 (AP , ML , DV ). All injections were administered using a glass micropipette with a tip diameter of 10 to , securely attached to a syringe (#75, Hamilton, United States). The injection volume (150 nl) and flow rate () were controlled via a syringe pump (788130, KD Scientific, United States). After each injection, the micropipette remained in place for 10 min before withdrawal. The scalp incision was closed with tissue glue (1469SB Vetbond, 3M Animal Care Products, United States), and post-injection analgesics were provided for 3 days to aid in recovery. A complete list of all vectors used is detailed above. 2.4.Fiber Photometry SystemWe utilized the R820 dual-color multi-fiber photometry system (RWD Life Science, China) to simultaneously record astrocytic and neuronal transients. This system includes a fluorescence cube, spectrometer, and excitation light components. GCaMP6f fluorescence was excited with a 470-nm light-emitting diode (LED), while jRGECO1a fluorescence was excited with a 560-nm LED.27 A sequence of dichroic mirrors within the fluorescence cube directed the emitted dual-color light, which was focused through a 20× objective at the optic fiber’s end.20,23 The dual-color fluorescence emission was then directed back through the fluorescence cube and focused onto a lens.20,23 A spectrometer with a dichroic mirror separated the emission into green and red light, which were detected simultaneously by two complementary metal oxide semiconductor (CMOS) sensors. The collected dual-color fluorescence signals were digitized at a stable frequency.20,23 2.5.Fiber Photometry Recordings in Freely Behaving MiceMice injected with viral vectors in the S1, M1, and CA1 regions were anesthetized with 1% to 2% isoflurane and positioned in a stereotactic head frame (68001, RWD Life Science, China) atop a heating pad (37.5°C to 38°C).20 Ferrules (907-03007-00, outer diameter: 1.25 mm, core: , NA: 0.39, RWD Life Science, China) were implanted 0.1 mm above the virus injection sites and secured to the mouse skull using dental cement. To simultaneously record transients in astrocytes and neurons across S1, M1, and CA1, bundled optical fibers with ceramic sleeves (, fiber core: diameter, NA 0.37, connectors: 1.25 mm, Inper, China) were connected to the ferrules fixed on the head. Mice were placed in a white square recording chamber () to allow free movement during data collection. signals and behavioral videos were captured simultaneously for 45 min. Each channel of signals was digitized at 30 Hz using fiber photometry recording software (OFRS, RWD Life Science, China). Behavioral videos synchronized with signals were recorded by a camera (MV-SUA502C-T, Mind Vision, China) at 30 Hz, with a spatial resolution of . Offline, all signals and behavioral videos were synchronized using event markers. For footshock experiments, mice were placed in a rectangular chamber where they could freely move. Footshocks (0.6 mA, 1 s) were administered every 5 min. Each mouse underwent continuous recording for four trials to observe footshock-induced astrocytic and neuronal transients. 2.6.Histology and Confocal ImagingFollowing the experiments, we anesthetized the mice with phenobarbital sodium () and performed transcardial perfusion with 4% paraformaldehyde (PFA) in phosphate buffered saline (PBS). The brains were subsequently dehydrated in 15% sucrose PFA solution for 24 h and sectioned into coronal slices. These slices were stained with 4′,6-diamidino-2-phenylindole (DAPI) to visualize the nuclei. Imaging was conducted using a confocal microscope (LSM 980, Zeiss, Germany) equipped with a × 20 air objective (NA 0.85) and a × 40 oil immersion objective (NA 1.25), scanning at a resolution of with increments in -stack. For immunohistochemistry, we employed the following primary antibodies: rabbit anti-NeuN (177487, 1:500, Abcam, United Kingdom), rabbit anti-S100β (287003, 1:500, SYSY, Germany), and chicken anti-GFP (ab13970, 1:500, Abcam, United Kingdom). Secondary antibodies used were Alexa Fluor 488 donkey anti-chicken (A78948, 1:800, Invitrogen, United States) and Alexa Fluor 647 donkey anti-rabbit (A-31573, 1:500, Invitrogen, United States). 2.7.Data AnalysisWe sampled astrocytic transients at a wavelength of 470 nm and neuronal transients at a wavelength of 560 nm using optic fiber-based recordings in behaving mice. -scored values for both astrocytes and neurons were computed using the formula: .27,28 Regions of interest were selected on the grayscale image of the optic fiber bundle, and the average pixel intensity was calculated as a measurement of the raw signal, denoted as . Subsequently, the OFRS software (RWD Life Science, China) was utilized with a moving window to obtain the average of , referred to as . To analyze the data, we converted image frames to binary format to delineate mouse shapes based on image intensities and quantified mouse movement relative to body size from video clips. Traces of astrocytic and neuronal transients were examined concerning the onset of movement or footshock. Data analysis was conducted using custom-written software in MATLAB 2018b.29 2.8.Statistical AnalysisWe expressed the data as the mean standard error of mean (SEM). Investigators conducted data analysis while blinded to group allocation. Two test methods were employed: the Wilcoxon’s signed-rank test for paired two-group comparisons and the Wilcoxon rank-sum test for unpaired two-group comparisons.20,29 To assess the correlation of astrocytic or neuronal transients among the S1, M1, and CA1 regions, we employed the Spearman correlation test. In addition, to examine the correlation between astrocytic and neuronal transients, we utilized the cross-correlation test. 3.Results3.1.Dual-Color Genetically Encoded Calcium Indicators Exhibit Specific and Efficient Expressions in Both Astrocytes and NeuronsGECIs can monitor specific cell types in the brain.30 Using dual-color GECIs that emit at different wavelengths, we can simultaneously track transients in astrocytes and neurons.21 Recently, researchers used the green-shifted GECI GCaMP6f alongside red probes such as jRGECO1a to detect transients in different cell populations simultaneously.21,23,24 In our study, we used GCaMP6f and jRGECO1a, differentially expressed in astrocytes and neurons, to effectively achieve dual-color monitoring of both astrocytic and neuronal transients concurrently. In our research, we labeled astrocytes with GCaMP6f and neurons with jRGECO1a. Initially, we administered AAV5-GfaABC1D-cyto-GCaMP6f-SV40 to the specific brain region. Fourteen days later, we injected AAV9-hSyn-NES-jRGECO1a-SV40 into the same brain region [Fig. 1(a) and Fig. S2(a) in the Supplementary Material, strategy 1]. Twenty-one days after the AAV microinjection, we confirmed the expressions of GCaMP6f and jRGECO1a by post hoc histology. We then conducted fiber photometry recordings based on the locations of GECI expression in the subsequent experiments [Fig. 1(b)]. Our findings demonstrated that the above strategy for virus injections [Fig. 1(a)] led to consistent, robust, and specific expressions of GCaMP6f and jRGECO1a in the cortices and hippocampal CA1 region (CA1) of adult mice [Figs. 1(c) and 1(d), Fig. S2(b) in the Supplementary Material]. The GCaMP6f expression closely overlapped with the astrocytic marker , and the jRGECO1a expression closely overlapped with the neuronal marker NeuN [Figs. 1(c) and 1(d)]. Statistical analysis revealed that GCaMP6f expression specificity was in the cortex and in the CA1 region (Table 1). Furthermore, the expression efficiency of GCaMP6f was in the cortex and in the CA1 region (Table 1). By contrast, jRGECO1a expression specificity was in the cortex and in the CA1 region (Table 1), with an expression efficiency of in the cortex and in the CA1 region (Table 1). Further experiments demonstrated that no cells tested positive for , indicating that these cells are not astrocytes [Figs. S1(a) and S1(b) in the Supplementary Material]. This finding suggests that NeuN may not label all neurons. The results confirmed the specific and efficient expressions of the dual-color GECIs in astrocytes and neurons within both cortices and CA1 regions. Table 1Specificity and efficiency of GCaMP6f and jRGECO1a labeling.
Considering the evident leakage observed in astrocytes during transgenic labeling in previous studies,31 we explored two alternative virus injection strategies [Figs. S2(c) and S2(e) in the Supplementary Material, strategies 2 and 3]. One approach involved injecting a mixture of viruses containing GCaMP6f and jRGECO1a [Fig. S2(c) in the Supplementary Material, strategy 2], while the other approach entailed injecting the jRGECO1a virus first, followed by the GCaMP6f virus 14 days later [Fig. S2(e) in the Supplementary Material, strategy 3]. The results indicated that co-staining between GCaMP6f and jRGECO1a was observed in both strategies 2 and 3 [Figs. S2(d) and S2(f) in the Supplementary Material]. The leakage rate was measured at for strategy 2 and for strategy 3. Notably, in strategy 1 [Fig. S2(a) in the Supplementary Material], there was no co-staining between GCaMP6f and jRGECO1a, indicating the absence of leakage [Fig. S2(b) in the Supplementary Material]. In conclusion, when compared with strategies 2 [Fig. S2(c) in the Supplementary Material] and 3 [Fig. S2(e) in the Supplementary Material], strategy 1 [Fig. S2(a) in the Supplementary Material] emerged as the optimal virus injection approach for achieving specific and efficient expression of dual-color GECIs in astrocytes and neurons. 3.2.Simultaneous Recording of Astrocytic and Neuronal Ca2+ Activities is Achieved in Freely Behaving MiceThe fiber photometry system comprises three main components: an excitation light source, a fluorescence cube with exchangeable filters, and a spectrometer [Fig. 2(a)]. To simultaneously measure green and red fluorophores, we employed a 470-nm LED and a 560-nm LED as excitation light sources, along with appropriate dual-band dichroic and emission filters. Each mouse was placed in a white, opaque, rectangular chamber 24 h after fiber probe implantation. During the fiber recording session, the behavior of freely behaving mice was recorded using a camera positioned above the chamber [Fig. 2(a)]. A fiber probe with a diameter of was implanted above GCaMP6f-positive astrocytes and jRGECO1a-positive neurons [Fig. 2(b)], 3 weeks after virus injection (using -GCaMP6f-SV40 and AAV9-hSyn-NES-jRGECO1a-SV40). Using the device shown in Fig. 2(a), we recorded both body movements and the activities of astrocytes and neurons. Figure 2(c) presents a representative example of body movements (black traces) alongside simultaneously recorded astrocytic (green traces) and neuronal (magenta traces) activities during free exploration by mice in the open field. score normalization was utilized to represent the normalized magnitude, mitigating the inherent differences in the dynamic range of GCaMP6f and jRGECO1a. Statistical analysis indicated that astrocytic activities occur less frequently compared with neurons [Fig. 2(d), left], but have longer durations [Fig. 2(d), right]. Furthermore, most astrocytic activities last longer than 20 s, whereas neuronal activities primarily have durations shorter than 20 s [Fig. 2(e)]. To ascertain whether fluorescence signals from GCaMP6f or jRGECO1a recorded by the fiber photometry system faithfully report astrocytic or neuronal transients in freely behaving animals, we conducted in vivo recordings with GCaMP6f expressed in astrocytes and mCherry in neurons [Figs. S3(a) and S3(c) in the Supplementary Material], as well as with jRGECO1a in neurons and green fluorescent protein (GFP) in astrocytes [Figs. S3(e) and S3(g) in the Supplementary Material] within S1 and M1 regions. Our findings revealed frequent and transient increases in fluorescence signals exclusively in GCaMP6f and jRGECO1a, with no corresponding changes observed in mCherry and GFP fluorescence [Figs. S3(b), S3(d), S3(f), and S3(h) in the Supplementary Material]. This observation indicates that the fluorescence transients in GCaMP6f and jRGECO1a reflect influx associated with astrocytic or neuronal activity, rather than being artifacts of movement. Considering the heterogeneity of astrocytic transients, which include both microdomain and cell-wide scales,4 we next assessed the sensitivity of fiber photometry in detecting these transients. Previous studies have demonstrated that the majority of astrocytic transients in quiet awake mice are microdomain transients,32 whereas those observed in moving mice are primarily cell-wide “global” transients.26 Therefore, we utilized fiber photometry to record astrocytic transients in both stationary and moving mice. The results indicate that fiber photometry can effectively detect astrocytic transients under both conditions [Figs. S4(a)–S4(d) in the Supplementary Material]. The amplitude of astrocytic transients during movement states is approximately ten times greater than that observed in stationary states [Figs. S4(b) and S4(d) in the Supplementary Material]. Thus, the data validate its capability to identify both microdomain and cell-wide “global” astrocytic transients. To investigate the role of astrocytic and neuronal activities in cognitive functions such as spatial exploration and memory, simultaneous recording of astrocytic and neuronal activity alongside mouse position in real time is essential. In this study, we concurrently recorded activities in astrocytes and neurons along with the movements of freely behaving mice [Fig. 2(c)]. The precise onset and cessation of neuronal activities could be clearly identified within the mouse trajectories as depicted in the simultaneously recorded videos [Figs. 2(f) and 2(g)]. Moreover, the real-time body movement status could be correlated with specific behavioral patterns of the mouse at these locations [Figs. 2(f) and 2(g)]. 3.3.Movement Evokes Correlated Astrocytic and Neuronal Ca2+ Transients in Freely Behaving MicePrevious studies have demonstrated that movement can elicit transients not only in neurons33 but also in astrocytes.20,26,29 However, there is currently no suitable technique to investigate the correlation between movement-evoked transients in astrocytes and neurons during free behaviors. In this study, we utilized the dual-color fiber photometry system [Fig. 2(a)] to concurrently record transients in both astrocytes and neurons in the primary motor cortex (M1) of freely behaving mice. We then examined the dynamic relationship of movement-evoked transients in astrocytes and neurons. The results demonstrated that movement could trigger simultaneous transients in astrocytes and neurons [Fig. 3(a)]. Importantly, the temporal patterns of transients differed between astrocytes and neurons [Fig. 3(b)]. Specifically, movement-evoked astrocytic transients exhibited significantly longer latencies compared with those in neurons. In addition, the peak of astrocytic transients occurred later than that of neurons [Fig. 3(c)]. Statistical analysis indicated that the latency of movement-evoked transients was in astrocytes, compared with in neurons [Fig. 3(d), left]. This delay in astrocytic transients was compared with neurons [Fig. 3(d), middle and right]. The peak time of movement-evoked astrocytic transients was in astrocytes and in neurons [Fig. 3(e), left]. Furthermore, the astrocytic peak time was delayed by about 4.73 s compared with neurons [Fig. 3(e), middle and right]. We found a close association between the continuous increase in astrocytic transients and the decrease in neuronal transients, resulting in the inter-locking of the astrocytic peak with the neuronal valley [Fig. 3(a)]. Statistical analysis indicates that the peak of astrocytic transients occurred before the valley of neuronal transients [Fig. 3(f), left and right]. The distinct temporal patterns of transients between astrocytes and neurons suggest unique mechanisms governing signaling in each cell type, as well as potential interactions between astrocytes and neurons. Using in vivo two-photon imaging, a previous study suggested an increased correlation of astrocytic and neuronal transients during the movement state, compared with the stationary state.29 To further validate this observation in freely moving mice, we employed a fiber photometry system to record transients in astrocytes and neurons during both stationary and movement states. Subsequently, we evaluated the correlation between astrocytic and neuronal transients in these two states. Our results demonstrated that in the stationary state, there was no synchronization between astrocytic and neuronal transients [Fig. 3(g)]. By contrast, during the movement state, astrocytic and neuronal transients fluctuated concurrently with the animal’s movements [Fig. 3(h)]. Statistical analysis revealed a significantly higher correlation between astrocytic and neuronal transients during the movement state () compared with the stationary state [, Fig. 3(i)]. To further investigate the effects of neuronal activity on astrocytic transients, we employed random forest regression to predict astrocyte levels [Fig. S5(a) in the Supplementary Material]. This approach enabled us to account for approximately of the variance in astrocyte during the stationary state and of the variance during the movement state [Fig. S5(a) in the Supplementary Material]. These results corroborate the earlier study conducted in head-fixed mice using in vivo two-photon imaging,29 indicating a more interconnected relationship between astrocytic and neuronal transients during movement than during stationary states. 3.4.Sensory Stimulation Induces Inter-Locked Astrocytic and Neuronal Ca2+ Transients in Freely Behaving MiceAstrocytes demonstrate stimulus-dependent responses to sensory input,7 influencing neuronal network activity and modulating the overall dynamic range of cortical network activity.7,34 However, it remains unclear whether and how astrocytic and neuronal transients are correlated in response to sensory stimuli in freely behaving animals. By employing a two-channel fiber photometry system [Fig. 4(a)] and utilizing two different GECIs (jRGECO1a and GCaMP6f) in the primary somatosensory cortex (S1) [Fig. 4(b)], we investigated these questions while delivering electrical stimuli to the hind paws of freely behaving mice. This approach allowed precise stimulation of sensory inputs in a controlled manner [Fig. 4(a)]. As depicted in Figs. 1(c) and 1(d), astrocytes were labeled with GCaMP6f and neurons with jRGECO1a, followed by placement of the fiber photometry probe above these GECI-labeled cells [Fig. 4(b)]. Our study demonstrates that astrocytes and neurons exhibit concurrent responses to sensory stimuli in S1 [Fig. 4(c)]. In addition, we observed an inter-locked relationship between neuronal and astrocytic transients induced by sensory stimuli, revealing a hysteresis pattern indicative of a negative feedback loop [Fig. 4(d)]. We further analyzed the temporal patterns of astrocytic and neuronal transients triggered by sensory stimuli. Similar to the findings with movement-evoked transients [Fig. 3(c)], our results indicated that sensory stimuli-induced astrocytic transients have significantly longer latencies compared with neurons. Furthermore, we observed that the peak of astrocytic transients occurred later than that of neurons [Fig. 4(e)]. Statistical analysis revealed that the latency of sensory stimuli-induced transients in astrocytes was , whereas it was in neurons [Fig. 4(f), left]. Specifically, the latency of astrocytic transients was delayed by compared with neurons [Fig. 4(f), middle and right]. The peak time of sensory stimuli-induced transients was in astrocytes and in neurons [Fig. 4(g), left]. In addition, the astrocytic peak time was delayed by about 0.60 s compared with neurons [Fig. 4(g), middle and right]. We also noted that the increase in astrocytic transients coincides with the decrease in neuronal transients [Fig. 4(d)]. Statistical analysis indicated that the peak of astrocytic transients preceded the valley of neuronal transients by [Fig. 4(h) left and right]. This pattern exhibited hysteresis, suggesting a potential negative regulatory mechanism between astrocytic and neuronal signaling. In addition, the duration of sensory stimuli-induced transients was in astrocytes, which was notably longer than in neurons () [Fig. 4(i), left and right]. Next, we evaluated the correlation between astrocytic and neuronal transients both during free behavior and sensory stimulation (footshok). Statistical analysis demonstrated a significantly higher correlation between astrocytic and neuronal transients during sensory stimuli () compared with freely behaving conditions () [Fig. 4(j)]. To gain a better understanding of the impact of neuronal activity on astrocytic transients, we utilized random forest regression to forecast the levels of in astrocytes [Fig. S5(c) in the Supplementary Material]. This methodology allowed us to explain around of the variance in astrocyte during free behavior and about of the variance in response to sensory stimuli [Fig. S5(c) in the Supplementary Material]. These results indicate a more interconnected relationship between astrocytic and neuronal transients during sensory stimuli than during free behavior. 3.5.Multi-Regional Measurement of Astrocytic and Neuronal Ca2+ Transients Reveals the Movement-Enhanced Astrocyte-Neuronal Networks on a Brain-Wide ScaleReal-time measurement of astrocyte-neuronal network signals from multiple brain regions is crucial for understanding how circuit activity patterns influence behavior. However, current techniques for simultaneously assessing these dynamics in behaving animals remain limited. In this study, we developed an optical setup for parallel fluorescence recordings using multi-fiber photometry [Fig. 5(a)] and employed cell-specific dual-color GECIs [GCaMP6f and jRGECO1a, Fig. 5(b)]. This setup enabled simultaneous recording of astrocytic and neuronal transients from multiple brain regions in freely behaving mice. The optical setup comprised a three-fiber patchcord, tightly bundled at one end and branching into three at the other [Fig. 5(a)]. This setup served to both deliver excitation and collect emitted light. Each fiber branch is connected to a fiber optic interface inserted into distinct brain regions. Signal recording utilized two CMOS cameras, capturing two fluorescence emissions simultaneously from all three fibers at the bundled end [Fig. 5(a)]. For cell-specific transients, astrocytes were labeled with GCaMP6f and neurons with jRGECO1a. Subsequently, we surgically implanted three optical fibers to target three specific brain regions: S1, M1, and CA1 regions [Fig. 5(b)]. These regions were previously virally injected with GCaMP6f and jRGECO1a, and post hoc histology confirmed the positions of fiber tips and GECI labeling [Fig. 5(b)]. We then conducted simultaneous recordings of astrocytic and neuronal transients across these brain regions using all three optical fibers in freely behaving mice. Robust transients were observed in both astrocytes and neurons during stationary and movement states [Fig. 5(c)]. Importantly, during movement states, we observed increased synchronization of astrocytic and neuronal transients compared with stationary states [Fig. 5(c)]. These findings suggest a potential relationship between movement and the coordination of astrocytic and neuronal transients across distinct brain regions. Multi-fiber photometry facilitates the reconstruction of astrocyte-neuronal networks in the brain associated with behavior. We assessed brain-wide functional connectivity by calculating the Spearman correlation coefficient () of astrocytic and neuronal transients between different regions during stationary and movement states [Figs. 5(d) and 5(e), top panels]. Connections between brain regions were represented with varying link thicknesses based on correlation strength [Figs. 5(d) and 5(e), bottom panels]. Notably, thicker links were observed in the astrocytic and neuronal networks during movement states compared with stationary states [Figs. 5(d) and 5(e), bottom panels]. Statistical analysis revealed significantly higher correlation coefficients of astrocytic or neuronal transients between brain regions during movement states (astrocyte: ; neuron: ) compared with stationary states [astrocyte: ; neuron: , Fig. 5(f)]. In addition, to explore the relationship between movement-induced transients in astrocytes and nearby neurons, cross-correlations between astrocytic and neuronal transients across different brain regions during stationary and movement states were analyzed. Results demonstrated a pronounced increase in cross-correlations during movement states (S1: ; M1: ; CA1: ) compared with stationary states [S1: ; M1: ; CA1: , Figs. 5(g) and 5(h)]. Moreover, we employed neuronal activity data to predict astrocytic transients using random forest regression. The results indicate that the predictable percentages of variance in astrocyte levels are elevated across various brain regions during the movement state [Fig. S5(b) in the Supplementary Material, S1: ; M1: ; CA1: ] compared with the stationary state [Fig. S5(b) in the Supplementary Material, S1: ; M1: ; CA1: ]. Thus, this method provides deeper insights into the interactions between astrocytes and neurons across and within brain regions during different behavioral states. 3.6.Multi-regional Measurement of Astrocytic and Neuronal Transients Illuminates Heightened Functional Brain-Wide Astrocyte-Neuronal Networks during Sensory StimuliTo explore astrocytic and neuronal responses to sensory stimulation at a whole-brain level, we employed dual-color multi-fiber photometry techniques to monitor transients in astrocytes and neurons across brain-wide networks [Fig. 6(a)]. In this investigation, we simultaneously recorded astrocytic and neuronal transients in response to footshock in three distinct brain regions: S1, M1, and CA1 region [Fig. 6(a)]. Our results reveal consistent and synchronized transients in both astrocytes and neurons elicited by sensory stimuli (footshock) across these brain regions [Figs. 6(b) and 6(c)]. To evaluate brain-wide functional connectivity in response to sensory stimulation, we computed Spearman correlation coefficients () of astrocytic and neuronal transients between different brain regions during both freely behaving and footshock stimulation [Figs. 6(d) and 6(e), top panels]. The strength of these correlations was depicted by varying link thicknesses connecting the brain regions in our analysis [Figs. 6(d) and 6(e), bottom panels]. This method enabled visualization and quantitative assessment of astrocytic and neuronal functional connectivity across brain regions in response to sensory stimuli. Notably, we observed increased connectivity in both astrocytic and neuronal networks during footshock stimulation compared with freely behaving conditions [Figs. 6(d) and 6(e), bottom panels]. Statistical analysis demonstrated a significant rise in the correlation coefficients of astrocytic and neuronal transients across brain regions during footshock stimuli (astrocyte: ; neuron: ) compared with freely behaving [astrocyte: ; neuron: ; Fig. 6(f)]. In addition, we investigated cross-correlations between astrocytic and neuronal transients in various brain regions during both freely behaving and footshock stimuli to explore the relationship between sensory stimulation-induced dynamics. Our findings revealed a significant increase in cross-correlations across all brain regions during footshock stimulation (S1: ; M1: ; CA1: ) compared with freely behaving conditions [S1: ; M1: ; CA1: ; Figs. 6(g) and 6(h)]. Moreover, we utilized neuronal activity data to predict astrocytic transients through random forest regression. The results demonstrate that the percentage of variance in astrocyte levels that can be predicted is significantly higher across various brain regions during sensory stimuli [Fig. S5(d) in the Supplementary Material, S1: ; M1: ; CA1: ] in comparison to free behavior [Fig. S5(b) in the Supplementary Material; S1: ; M1: ; CA1: ]. Thus, this approach provides comprehensive insights into the dynamics of astrocyte-neuronal networks in response to sensory stimulation across multiple brain areas. 4.DiscussionIn this study, we integrated cell-specific dual-color GECIs and fiber photometry to concurrently capture astrocytic and neuronal transients in freely behaving mice. This innovative approach enables the examination of astrocyte-neuronal networks across various behavioral patterns, shedding light on their functional dynamics. Moreover, by utilizing multi-fiber photometry and cell-specific dual-color GECIs, we achieved real-time recording of astrocytic and neuronal transients across multiple brain regions. This methodology is crucial for deciphering the intricate interactions between astrocytes and neurons within and across different brain regions in the context of specific behaviors. Furthermore, it facilitates the exploration of the roles played by astrocyte-neuronal networks at a comprehensive, whole-brain level. Known as the “astrocyte-neuronal network,” the two-way communication between astrocytes and neurons plays a crucial role in various behaviors and brain functions.6,7 Astrocytes, furthermore, detect and integrate arousal states and sensory inputs through changes in intracellular , which are essential for optimizing behavior.35 Several techniques are currently employed to simultaneously monitor astrocytic and neuronal activities, including in vivo two-photon imaging,29 the combination of two-photon imaging with electrophysiological recording,6 and fiber photometry.21 However, it remains unclear whether there is an optimal method to accurately record the responses of astrocyte-neuronal networks to specific behaviors. In this study, we utilized dual-color fiber photometry to simultaneously track astrocytic and neuronal transients during spontaneous movement (Fig. 3) and footshock stimulation (Fig. 4). The findings reveal synchronized responses from both astrocytes and neurons to these stimuli. Notably, the temporal patterns of astrocytic and neuronal transients exhibit a hysteresis pattern, indicating a bidirectional interaction where neurons initially facilitate astrocytes and subsequently astrocytes inhibit neurons. This observation aligns with previous studies utilizing electrophysiology34 and two-photon imaging techniques.7,29 Our study offers real-time and precise quantification of responses in astrocyte-neuronal networks in freely behaving mice, providing insights into the roles of this network in responding to specific behaviors. The adult brain consists of multiple regions, each characterized by its unique combination of neuronal subtypes and distinct astrocytes.12 This suggests potential regional specialization within the astrocyte-neuronal network. Furthermore, behaviors critically rely on synchronized activity across multiple brain regions, where both neurons and astrocytes operate concurrently and in parallel during various behavioral contexts.3,17,18 It is established that astrocytic and neuronal transients are influenced by and adapted to activity patterns within local neuronal circuits.35 Thus, simultaneous recording of astrocytic and neuronal transients across multiple brain regions provides a valuable metric for evaluating the diversity and coordination of the astrocyte-neuronal network at a functional level. Yang and colleagues have introduced the multiarea two-photon real-time in vivo explorer, which enables the investigation of multiarea neuronal transients in head-fixed mice with single-cell resolution.36 Furthermore, researchers can record transients from multiple brain regions simultaneously in freely behaving mice,23,25 using either frame-projected independent-fiber photometry or arrays of optical fibers. However, there remains a lack of suitable methods for concurrently recording astrocytic and neuronal transients across multiple brain regions. In this study, we have successfully demonstrated the capability of combining multi-fiber photometry with cell-type specific dual-color GECIs to monitor transients in both astrocytes and neurons in freely behaving mice across multiple brain regions. Importantly, this methodology is not limited to mice but can also be effectively applied to other mammalian species, including rats and non-human primates.37 Previous research24 and our current findings (Fig. 2) support the feasibility of utilizing multiple indicator systems simultaneously through multi-color approaches. Therefore, the full potential of multi-fiber photometry with multi-color techniques can be realized by integrating multiple GECIs for specific labeling of cell types or pathways. This advancement allows researchers to monitor the activities of different cell types or pathways in various brain regions simultaneously. Behavioral patterns in animals arise from neuronal activity that is distributed across brain networks.25 Specifically, many perceptual, cognitive, and motor functions rely not only on the neuronal activity spread throughout various regions of the brain but also on the effective communication of this activity between these areas. Consequently, to understand the neural substrates of complex behaviors, it is essential to comprehend the factors that regulate signal transmission across multiple brain regions and how this communication is orchestrated to facilitate adaptable behavior.18,38,39 Temporal coordination serves as a crucial indicator of the robustness of functional connectivity within neural networks.18 Neurons tend to respond more robustly to synchronous inputs from presynaptic neurons rather than asynchronous inputs, as they integrate synaptic inputs within defined time windows.40–42 In addition, the coherence of activity serves as a pivotal metric for assessing communication between different brain regions, as optimal inter-regional communication occurs when activity phases are well-synchronized.18,43 In this study, we have observed that spontaneous movement and sensory stimulation induce synchronous and coherent activity within astrocytic and neuronal networks across multiple brain regions, including S1, M1, and CA1 [Figs. 5(d)–5(f) and 6(d)–6(f)]. This indicates heightened astrocyte-neuronal communication between different brain regions during arousal states and sensory inputs. The underlying mechanism involves astrocytes in various brain regions sensing transient arousal states through neuromodulator release and responding to sensory inputs via local synaptic activity.35 This leads to concurrent increases in astrocytic transients that propagate44 and result in synchronized and coherent neuronal activities across diverse brain regions. Furthermore, subtle variations in astrocytic and neuronal activity patterns are evident among different brain regions. Specifically, astrocytic and neuronal transients in S1 exhibit closer coordination with those in M1 compared with CA1 (Figs. 5 and 6). This distinction may stem from a greater similarity in astrocytic and neuronal properties between S1 and M1, contrasting with CA1.12 The combination of multi-fiber photometry with cell-specific dual-color GECIs has facilitated the simultaneous recording of astrocytic and neuronal transients across diverse brain regions in freely behaving mice. By applying this technique, we can explore deeper insights into brain-wide astrocyte-neuronal networks in freely behaving animals, an area that has previously been inaccessible to investigation. First, researchers can examine alterations in the functional connectivity patterns of astrocyte-neuronal networks across multiple brain regions during various behaviors and distinct external stimuli. Accumulating experimental evidence suggests that diverse behaviors arise from the coordinated activity of astrocyte-neuronal networks across multiple brain regions.2,3,8 However, it remains uncertain how astrocyte-neuronal networks across different regions coordinate to respond to changes in behavior or sensory stimuli. In the present study, we found that the functional connectivity of astrocyte-neuronal networks across multiple brain regions increased during movement states or sensory stimulation compared with stationary states or freely behaving conditions [Figs. 5(d)–5(f) and 6(d)–6(f)]. This indicates that animals adopt optimized patterns of brain-wide astrocyte-neuronal network functional connectivity to modulate behaviors or respond to external stimuli. Second, using this method, region-specific changes within astrocyte-neuronal networks can be detected. Neurons and astrocytes in the brain exhibit diverse properties depending on their respective regions.12 Nonetheless, the question of whether and how astrocyte-neuronal networks employ region-specific mechanisms for the regulation of distinct neural circuits is not fully understood. In our present investigation, we found that changes in astrocyte-neuronal network activities were more similar between S1 and M1 compared with CA1 [Figs. 5(d)–5(f) and 6(d)–6(f)]. This suggests that brain regions composed of similar astrocytic and neuronal properties are likely to exhibit more comparable responses to changes in intrinsic states or external stimuli. Finally, the interactions between astrocytes and neurons, both across and within various brain regions, can be investigated in the context of different behavioral states and external stimuli. It is well established that astrocytes and neurons can communicate bidirectionally at the tripartite synapse.1 On the one hand, astrocytes sense neuronal network activity by responding with activity to neural signals in vivo; on the other hand, astrocyte activation or manipulation modulates neural network activity.1,3 However, how interaction patterns between astrocytes and neurons are modified in response to various behaviors or external stimuli remains an unresolved issue. Our study demonstrated a significant increase in cross-correlations between astrocytic and neuronal transients during movement [Figs. 5(g) and 5(h)] and footshock stimulation [Figs. 6(g) and 6(h)] across all brain regions. These findings indicate that communication between astrocytes and neurons is heightened by body locomotion and footshock, suggesting that bidirectional astrocyte-neuron communication can be modulated by both instinctual arousal states and external stimuli. Looking forward, significant advancements are anticipated in several critical areas. First, further research is required to expand the repertoire of genetically encoded indicators (GEIs) to encompass various biological molecules, particularly neurotransmitters and neuropeptides.45,46 Coupled with these GEIs, observing direct interactions between astrocytes and neurons will provide valuable insights into the physiological mechanisms of astrocyte-neuronal networks. Moreover, high-density multi-fiber arrays have proven invaluable for studying large-scale brain dynamics during behaviors.25 Utilizing such arrays enables researchers to monitor and analyze activities within astrocyte-neuronal networks across numerous brain regions in mammals, covering 12 to 48 regions.25 This advanced technology facilitates a comprehensive understanding of the intricate astrocyte-neuronal networks and the transmission of signals across brain regions. Finally, integrating other modalities such as electrophysiology47,48 is crucial to overcome the limitations of photometry technology in studying brain signals. Combining these techniques allows researchers to complement and augment data obtained from photometry, thereby enhancing our understanding of neural activity on a broader scale. One limitation of this method that should be noted is the potential formation of glial scars resulting from fiber photometry implantation. Increased reactive astrogliosis and a compromised immune microenvironment are the primary factors contributing to the development of glial scars.49,50 To mitigate their formation, we employed several strategies: (1) we controlled the insertion speed during fiber implantation to a maximum of to minimize tissue damage that could lead to reactive astrogliosis, (2) we ensured the sterilization of fiber photometry and surgical instruments and promptly addressed any tissue bleeding during surgery to improve the immune microenvironment following fiber implantation, and (3) we recorded astrocytic transients over a period of 21 days following fiber photometry implantation, allowing sufficient time for recovery from the associated injury. Through these methods, we effectively reduced the formation of glial scars during the surgery. We anticipate that the combination of multi-fiber photometry with cell-specific dual-color GEIs will be crucial for examining the intricate functional structure of astrocyte-neuronal networks. This technique not only enables the investigation of bidirectional communication between neurons and astrocytes but also facilitates the reconstruction of functional networks associated with specific behaviors. Furthermore, by employing advanced network analysis techniques, data obtained from this technique should contribute significantly to mapping multi-regional functional connectivity of astrocyte-neuronal networks during behavioral tasks. The diversity and complexity of astrocyte-neuron signaling provide a high degree of flexibility to the networks that underlie brain function. Code and Data AvailabilityThe data supporting the results presented in this paper are available from the corresponding author upon reasonable request. AcknowledgmentsWe acknowledge Jia Lou for the technical assistance and Sai Te Xin Si (AI tool) for the assistance with language editing. This work received support from the National Natural Science Foundation of China (Grant No. 82371485) and the Natural Science Foundation of Chongqing, China (Grant No. CSTB2024NSCQ-JQX0024). ReferencesJ. F. Oliveira and A. Araque,
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