This is a summary of a book titled “Elusive Cures: Why neuroscience hasn’t solved brain disorders – and how we can change that” written by accomplished neuroscientist Nicole Rust and published by Princeton University Press in 2025. She invites readers to reconsider the foundations of brain research and treatment. Drawing on decades of experience, Rust explores why the promise that a deeper understanding of the brain would lead to effective treatments for disorders like Alzheimer’s, depression, and schizophrenia has not been fulfilled. Her book is both a critique of prevailing scientific dogma and a call for a new way of thinking about the brain.

Rust begins by examining the “bench to bedside” approach that has dominated neuroscience for generations. This model assumes that discoveries at the molecular level—such as identifying genes or proteins involved in brain function—will naturally translate into clinical therapies. The narrative is so deeply ingrained in research culture that it is rarely questioned. Yet, Rust points out, despite enormous investments and scientific advances, reliable treatments for major brain disorders remain elusive.

Alzheimer’s disease serves as a cautionary tale. Researchers identified rare genetic mutations that increase risk and theorized that the accumulation of amyloid plaques in the brain was the root cause of neurodegeneration. Pharmaceutical companies poured billions into developing drugs to clear these plaques, only to find that, while the drugs worked as intended, they did not meaningfully slow the disease’s progression. By 2011, many companies had abandoned their efforts, having little to show for their investment.

Rust argues that the failure of these efforts stems from a narrow focus on molecular mechanisms. Brain dysfunction, she suggests, is influenced by a web of factors—genetic, environmental, socioeconomic, and behavioral. Non-pharmaceutical interventions can affect outcomes, and knowledge of molecular processes alone is insufficient for developing systematic treatments.

The book then delves into the rise of “molecular medicine,” which became central to neuroscience after the discovery of the genetic code in the 1950s. Researchers would identify a gene linked to a disorder, mutate it in animal models, and attempt to develop drugs to correct the resulting dysfunction. This “domino chain” approach, Rust explains, is tempting because it is simple and linear. But the brain is not a set of dominoes. It is a dynamic, adaptive organ, constantly responding to changing circumstances and regulating itself to optimize performance.

Rust highlights the limitations of reductionist thinking. Emergent properties like mood or consciousness arise from interactions among brain components, not from the components themselves. She suggests that it may be more fruitful to start with the behavior or disorder in question and work downward to the molecular level, rather than the other way around.

The history of psychiatric drugs further illustrates the unpredictability of progress. Many effective medications, such as Thorazine for schizophrenia and Ritalin for ADHD, were discovered by accident, not through targeted molecular research. Rust notes that the biggest obstacle to developing new treatments is our limited understanding of the causes of brain dysfunction. We may know what degenerates in diseases like Alzheimer’s, but not why degeneration occurs.

Recent advances in artificial intelligence have enabled scientists to build sophisticated models of brain activity, but linking mental disorders to specific genetic mutations remains a daunting challenge. Disorders like schizophrenia involve hundreds of genes, and technologies like fMRI have proven unreliable for diagnosis. Rust concludes that neither genes nor scans can credibly identify types of brain dysfunction, and a new model is needed.

One promising direction is to think of the brain as a computer—a system that processes information, makes decisions, and adapts to its environment. In this analogy, neurons are the hardware and the mind is the software. While this metaphor is useful, Rust cautions that it must be formalized into mathematical models to be truly explanatory. The gap between molecular effects and mental states remains vast.

Rust’s central thesis is that the brain is a complex adaptive system. Like the body, it seeks not just stability (homeostasis) but anticipates and adapts to future changes (allostasis). Feedback loops within the brain can lead to emergent properties and, sometimes, maladaptive patterns. For example, anxiety can spiral into a cycle of worry and demotivation, making it difficult for the brain to “relearn” healthier states.

Interventions in such a complex system are unpredictable. Treating disorders like depression or schizophrenia means regulating a dynamic network that can recalibrate itself in unexpected ways. Rust draws on models from recurrent neural networks, where feedback among neurons can push the system to the edge of chaos—a state that may be necessary for optimal function but is difficult to control.

Rust argues that effective treatment demands a precise understanding of what distinguishes healthy from unhealthy brains. Measuring consciousness and mental states is a major challenge, as these are not reducible to specific neural circuits. Research into brain activity patterns in patients with severe damage may help, but much remains unknown.

For future, Rust suggests that scientists may need to simplify their models, focusing on the most relevant variables for each disorder. Complex conditions may require clusters of treatments, and increasing brain plasticity to break maladaptive feedback patterns could be key. Her book is a call to embrace complexity, rethink old assumptions, and pursue new paths in the quest to cure brain disorders.