Characterization of the brain functional architecture of psychostimulant withdrawal using single-cell whole brain imaging

Abstract

Numerous brain regions have been identified as contributing to addiction-like behaviors, but unclear is the way in which these brain regions as a whole lead to addiction. The search for a final common brain pathway that is involved in addiction remains elusive. To address this question, we used male C57BL/6J mice and performed single-cell whole-brain imaging of neural activity during withdrawal from cocaine, methamphetamine, and nicotine. 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- 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 that leads to addiction.Significance StatementA key aspect of treating drug abuse is understanding similarities and differences of how drugs of abuse affect the brain. In the present study we examined how the brain is altered during withdrawal from psychostimulants. We found that each drug produced a unique pattern of activity in the brain, but that brains in withdrawal from cocaine and methamphetamine shared similar features. Interestingly, we found the major common link between withdrawal from all psychostimulants, when compared to controls, was a shift in the broad organization of the brain in the form of reduced modularity. Reduced modularity has been shown in several brain disorders, including traumatic brain injury, and dementia, and may be the common link between drugs of abuse.

Leveraging Neural Networks in Preclinical Alcohol Research

“…This fear network was further examined using in vivo chemogenetic silencing of different network nodes to confirm the importance of the hubs predicted in network models [ 129 ]. Similarly, an unbiased brain-wide Fos protein approach, using the single-cell whole-brain imaging (iDISCO+) method, has been combined with functional connectivity and graph theory to identify changes to neural network structure and function caused by withdrawal from alcohol and psychostimulants [ 99 , 217 ].…”

“…Neural networks associated with withdrawal from individual psychostimulants (cocaine, methamphetamine, and nicotine) were identified in mice by using single-cell whole-brain imaging of neural activity [ 217 ]. While withdrawal from each drug produced a distinct pattern of brain activity, methamphetamine and cocaine had the most overlapping similarities.…”