Defining, Mining, and Reversing Neurocircuit Adaptions in Addiction

Award: $100,000

Addiction alters the signaling and function of many neurons in the brain. Because drug or alcohol abuse alter our neurocircuitry—the pathways of our brains—reversing the effects of addiction means reversing the patterns our brains learn from substance abuse. With this study, Dr. Stuber proposes to gather data identifying the neurocircuitry of addiction by monitoring the activity of hundreds to thousands of neurons during the transition to addiction.

Garret Stuber, Ph.D.

Need/Problem:  Addiction and related disorders exact a tremendous toll of society, but strategies to define and assess the therapeutic efficacy are currently costly, slow, and difficult to develop.

Grant Summary:  Addiction alters the signaling and function of many neurons in the brain, but strategies to normalize these maladaptive patterns of activity are lacking.

Goals & Projected Outcomes:  In this project we will develop a novel model of addiction that we can combine with in vivo neurocircuit imaging approaches to monitor the activity of 100s to 1000s of mammalian neurons during the transition to addiction.  We will then mine these large-scale datasets to identify neurocircuit signatures of addiction. We will then use this as a platform to screen compounds for potential therapeutic efficacy to treat addiction.

Grant Details:  Addiction is a chronic illness characterized by compulsive drug or alcohol use, despite negative health, behavioral, and societal consequences.  Addiction is highly co-morbid with other neuropsychiatric conditions such as depression and anxiety, and repeated and chronic exposure to virtually all types of drugs of abuse result in semi-permanent to permanent alterations in brain function.  These neuroadaptations are thought to underlie the development of compulsive drug-taking as well as relapse following periods of drug abstinence. Because drugs of abuse effectively remodel existing neurocircuits that are essential for adaptive behavior, novel pharmacotherapies are needed to reverse drug-mediated brain changes to effectively ‘erase’ memories and compulsive behavioral patterns associated with drug taking, while sparing adaptive behavioral function.

Establishing the precise neural underpinnings of compulsive drug use is a first critical step in designing novel therapeutic interventions for addiction and related neuropsychiatric illnesses. Additionally, understanding how neural network activity patterns underlie addiction may translate into the development of novel therapeutic strategies to prevent drug relapse, by acting to normalize aberrant circuit activity.   Using cutting-edge tools to not only record neural circuit dynamics but to also map the molecular phenotypes exclusively in neurons that encode drug-related memories, we aim to generate a comprehensive massive online dataset that can be readily accessed and mined by the larger ‘data science’ research community. This multifaceted and highly interdisciplinary approach is currently unexplored for neuropsychiatric treatment development.  Thus, in conjunction, we will develop a circuit-based pharmacotherapy-screening platform, which through computational algorithms will first detect maladaptive activity patterns, and then determine the efficacy by which a given pharmacological compound can restore adaptive neurocircuit activity. Together, my assembled research team will be able push the currently established limits of what is possible in neuroscience, and generate import mechanistic insight in the biological origins of addiction.