Characterization of the Brain Functional Architecture of Psychostimulant Withdrawal Using Single-Cell Whole-Brain Imaging - PubMed (original) (raw)

Characterization of the Brain Functional Architecture of Psychostimulant Withdrawal Using Single-Cell Whole-Brain Imaging

Adam Kimbrough et al. eNeuro. 2021.

Abstract

Numerous brain regions have been identified as contributing to withdrawal behaviors, but it is unclear the way in which these brain regions as a whole lead to withdrawal. The search for a final common brain pathway that is involved in withdrawal remains elusive. To address this question, we implanted osmotic minipumps containing either saline, nicotine (24 mg/kg/d), cocaine (60 mg/kg/d), or methamphetamine (4 mg/kg/d) for one week in male C57BL/6J mice. After one week, the minipumps were removed and brains collected 8 h (saline, nicotine, and cocaine) or 12 h (methamphetamine) after removal. We then performed single-cell whole-brain imaging of neural activity during the withdrawal period when brains were collected. We used hierarchical clustering and graph theory to identify similarities and differences in brain functional architecture. Although methamphetamine and cocaine shared some network similarities, the main common neuroadaptation between these psychostimulant drugs was a dramatic decrease in modularity, with a shift from a cortical-driven to subcortical-driven network, including a decrease in total hub brain regions. These results demonstrate that psychostimulant withdrawal produces the drug-dependent remodeling of functional architecture of the brain and suggest that the decreased modularity of brain functional networks and not a specific set of brain regions may represent the final common pathway associated with withdrawal.

Keywords: addiction; functional connectivity; graph theory; iDISCO; neural activity; withdrawal.

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Figures

Figure 1.

A, Experimental design. Mice were surgically implanted with an osmotic minipump that contained either saline or a psychostimulant (60 mg/kg/d cocaine, 4 mg/kg/d methamphetamine, or 24 mg/kg/d nicotine). They were then returned to their home cage for one week. After one week, the minipumps were surgically removed, and the mice were returned to their home cage until brain tissue was collected 8 h later (saline, cocaine, nicotine) or 12 h later (methamphetamine). Brains were then processed for whole-brain Fos immunohistochemistry and clearing via iDISCO+ and then imaged on a light-sheet microscope. Fos values were detected and registered to the Allen Brain Atlas using ClearMap Renier et al., 2016. Pearson correlations were then calculated to determine functional coactivation among brain regions. Brain regions were then grouped into modules based on their coactivation patterns through hierarchical clustering. Graph theory analyses was then performed to identify brain regions that are heavily involved in intramodular and intermodular connectivity. B, Workflow diagram of registration to the Allen Brain Atlas using ClearMap. Registration is performed by matching a the autofluorescence to a preregistered two-photon image set that has been matched to brain region delineations of the Allen Brain Atlas. The brain region demarcations mapped to the autofluorescence are then used to map onto the Fos values taken from the corresponding frame. Auto Fluo = Autofluorescence.

Figure 2.

A, Lateral to medial sagittal representative sections of the brain and zoomed in representative hippocampal subsections for each treatment. B, Comparisons of Fos values for saline versus each treatment in the dentate gyrus. See Extended Data Figure 2-2 for raw Fos values and Extended Data Figure 2-1 for comparisons of raw Fos for treatments versus saline.

Figure 3.

A–D, Hierarchical clustering of complete Euclidean distance matrices for each treatment. Modules were determined by cutting each dendrogram at half of the maximal tree height. A, Relative distance of each brain region relative to the others that were examined in saline control mice. In control mice, seven distinct modules of coactivation were identified. B, Relative distance of each brain region relative to the others that were examined in cocaine mice. In cocaine mice, four distinct modules of coactivation were identified. C, Relative distance of each brain region relative to the others that were examined in methamphetamine mice. In methamphetamine mice, three distinct modules of coactivation were identified. D, Relative distance of each brain region relative to the others that were examined in nicotine mice. In nicotine mice, five distinct modules of coactivation were identified. For all distance matrices, each module is boxed in purple. For the individual brain regions that are listed in panels A–D, see Table 6. E, Number of modules in each treatment condition after cutting the hierarchical clustered dendrogram at different percentages of tree height. In all cases (except at extreme cutoff values; e.g., 90–100%), the psychostimulant networks showed lower modularity compared with the control network. See Extended Data Figure 3-1 for correlation matrices for each treatment.

Figure 4.

Intramodular (WMDz) and intermodular (PC) network features of each treatment. A high PC was considered ≥0.30, and a high WMDz was considered ≥0.80. A, Highlights of several regions with high PC in each module of each network (see Table 1 for names of abbreviations). B, Highlights of several regions with high WMDz (red, higher; blue, lower) in each module of each network. Note that the WMDz color intensity is only relative to the other regions within the same network and not other networks (see Table 1 for names of abbreviations). C, Total number of brain regions that accounted for high PC, high WMDz, or both in each network. The control and nicotine networks showed much greater intermodular connectivity and a greater number of regions with both high intermodular and intramodular connectivity. The cocaine and methamphetamine networks showed higher levels of intramodular connectivity and a low number of regions with intermodular connectivity.

Figure 5.

Neural network of control mice thresholded to 0.75R. Nodes/brain regions of the network are represented by circles. The size of the node represents the PC (smaller, lower PC; larger, higher PC). The internal color of each circle represents the WMDz (dark blue, lowest; dark red, highest). The color of the modules that are identified in Figure 1_C_ are represented by different colored edges. See figure key for examples of each representative component of the figure.

Figure 6.

Neural network of cocaine mice during withdrawal thresholded to 0.75R. Nodes/brain regions of the network are represented by circles. The size of the node represents the PC (smaller, lower PC; larger, higher PC). The internal color of each circle represents the WMDz (dark blue, lowest; dark red, highest). The color of the modules that are identified in Figure 1_D_ are represented by different colored edges. See figure key for examples of each representative component of the figure.

Figure 7.

Neural network of methamphetamine mice during withdrawal thresholded to 0.75R. Nodes/brain regions of the network are represented by circles. The size of the node represents the PC (smaller, lower PC; larger, higher PC). The internal color of each circle represents the WMDz (dark blue, lowest; dark red, highest). The color of the modules that are identified in Figure 1_E_ are represented by different colored edges. See figure key for examples of each representative component of the figure.

Figure 8.

Neural network of nicotine mice during withdrawal thresholded to 0.75R. Nodes/brain regions of the network are represented by circles. The size of the node represents the PC (smaller, lower PC; larger, higher PC). The internal color of each circle represents the WMDz (dark blue, lowest; dark red, highest). The color of the modules that are identified in Figure 1_F_ are represented by different colored edges. See figure key for examples of each representative component of the figure.

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Characterization of the Brain Functional Architecture of Psychostimulant Withdrawal Using Single-Cell Whole-Brain Imaging - PubMed (original) (raw)