Precision Brain Stimulation to Reduce Cannabis Craving in Schizophrenia

Cannabis use is highly prevalent in schizophrenia and has devastating consequences but no current treatments. Psychotic disorders such as schizophrenia are disabling, lifelong illnesses that afflict over three million people in the US. Cannabis is the second-most commonly used substance by people with schizophrenia (SZ) after tobacco. Up to 43% of people with SZ meet criteria for cannabis use disorder (CUD), a rate 15 times that in the general population of 3%. Recent evidence suggests cannabis use and SZ have bidirectional causal relationships. Co-occurring SZ with CUD has a significantly worse prognosis than SZ alone, as CUD is associated with symptom exacerbation, risk of psychotic relapse, treatment nonadherence, and poorer overall functioning. Cannabis use is a frequent cause of medication nonadherence, psychotic decompensation, and psychiatric hospitalization. Cannabis use in adolescence commonly occurs prior to the onset of psychosis, and there is growing evidence that cannabis may cause schizophrenia in vulnerable individuals. Recent evidence shows that cannabis use triggers brain changes linked to psychosis. However, the underlying pathophysiology of SZ with CUD remains unknown, and there are no approved treatments for SZ with CUD, leaving patients and their families struggling to stop their cannabis use without any effective treatments.

Cannabis Use in Schizophrenia is Based in Brain Network Pathology. Despite the magnitude of cannabis use and its devastating consequences, there are no approved treatments for cannabis use in any population. This study team seeks to investigate if this vulnerability to cannabis use in schizophrenia is based in brain pathology. The human brain is organized into networks of connected regions. In cannabis users, a region of these networks is chronically hyperconnected, but cannabis use transiently corrects this network pathology. This suggests cannabis users are using cannabis to self-medicate a network pathology problem. Function of brain networks can be measured in the MRI scanner.

This study seeks to use functional connectivity as a measure of neural function. The human brain has evolved to perform different behaviors under different sets of conditions and as such must flexibly combine the functional processing capabilities of disparate neuroanatomical regions. Collections of structurally interconnected brain areas must interact dynamically to process a large and ever-changing set of inputs in the ultimate attempt to generate an appropriate behavioral output. Functional networks can therefore be defined as the collection of interconnected brain areas that interact to perform these circumscribed functions.

To identify the critical nodes involved in these different functional networks, much of the work in the field of functional neuroimaging has used the fMRI blood-oxygen-level-dependent (BOLD) signal as a marker of cerebral perfusion, which in turn is known to reflect cerebral activity. fMRI BOLD activation patterns have revealed network nodes that are involved in such cognitive functions as attention working memory, language, and others.

In the resting state--while a participant is asked simply to look straight without performing a specific task in the MRI--analyses of the time-course of BOLD activation have revealed that activity patterns of several of these cerebral nodes exhibit coordinated fluctuations. As such, the activity patterns between particular nodes appear to be highly correlated in time while others seem relatively independent of one another. Taken together, these coordinated nodes can be thought of as a coupled functional network. The correlations between the activity patterns of cerebral nodes are termed "functional connectivity."