Beyond behavior: Frontiers of neuroscience research
“Can we bypass behavioral diagnosis altogether,” asks Alan Anticevic, PhD, “if we know what psychosis actually looks like in the brain?”
It’s a question underlying much of the latest clinical research being done by scientists like Anticevic, assistant professor of psychiatry and of psychology in the Yale Department of Psychiatry and co-director, with David Glahn, PhD, of the Division of Neurocognition, Neurocomputation, and Neurogenetics (“N3”).
Driven by scientific curiosity and humanitarian concern, these researchers are trying to understand the mechanisms of the brain in a deeper, more systematic way for the benefit of people with mental health problems.
Behavioral diagnosis in mental health
Since the first conceptualizations of mental illness, a patient’s behavior has been the principle diagnostic tool used by doctors and other mental health professionals to categorize psychiatric disorders and recommend treatment.
Consider the diagnostic criteria for schizophrenia as found in the “DSM V,” the newest Diagnostic and Statistical Manual of Mental Disorders. Like most within the DSM, these criteria are behavior-based. They include hallucinations, disorganized speech, “grossly disorganized or catatonic behavior,” and reduced levels of functioning “in one or more major areas, such as work, interpersonal relations, or self-care.”
Anticevic, whose research focuses on schizophrenia, frames the problem differently.
“Behavior originates in the brain,” he explains. “When brain mechanisms malfunction, those malfunctions give rise to altered behaviors.”
Behavior alone, while providing important clues about a person’s mental state, offers an incomplete measure of brain malfunction. Any number of different processes in the brain could result in similar behaviors.
Moreover behaviors are easy to judge, and the act of judging a person’s behavior takes place within the social, not scientific, realm. While science is not immune to social bias, it is true that non-scientific approaches to dealing with mental health problems have left people with mental disorders vulnerable to being stigmatized, ostracized, and marginalized. Behavior-based approaches do not addressed root causes, which lie within the brain.
Moving beyond behavior
Now imagine a world in which a person with a mental health problem is diagnosed based upon the activity within that person’s brain. Behavior, while important, is only part of the picture. A doctor identifies, using brain scans and other tests, exactly which brain mechanisms are going awry and how. Treatment is highly individualized, targeting specific chemical and neurological systems within the person’s brain.
That may be the future, and the work to bring us there has begun.
Anticevic and his colleagues, including computational neuroscientist John Murray, PhD and others, are part of an elite but growing international research community using a multidisciplinary approach that combines cognitive neuroscience, mathematics, and genetics in order to understand the neurobiology of brain systems. Working with fMRI (functional Magnetic Resonance Imaging), these scientists create sophisticated mathematical models derived from the intricate details of brain scans of patients. In addition to generating their own scans, they use neuroimaging scans now available in shared online international databases to which scientists are contributing rich sets of raw data across the world.
At Yale, the research is largely based within Connecticut Mental Health Center at the Abraham Ribicoff Research Program’s Clinical Neuroscience Research Unit (CNRU). There, scientists are exploring completely new paradigms that they hope will lead to new and better treatments for mental illness. They work with patients and healthy subjects, people who are quietly making their own contributions to the future of neuroscience research by sharing their medical and psychiatric histories and participating in brain scans. (To learn more about participating in a study at the Anticevic Lab within the CNRU, click here.)
One scientist’s journey
Alan Anticevic grew up in Zagreb, the capital city of Croatia. After a rigorous high school education at the 15th Gymnasium, a school with a strong focus on math and science, he moved to the United States to study. He found his academic passion when, in the summer of 2002, he had the opportunity as an undergraduate to work in the lab of Yale Psychiatry professor Dr. John Krystal.
“John was leading a big group in neuroimaging work in PTSD,” recalls Anticevic. “After that summer, I was hooked. I knew that clinical neuroimaging was what I wanted to dedicate my career to.”
At the time, he explains, his mentors helped him develop an intuition that severe mental illness is a brain-based problem affecting the brain’s complicated biochemical circuits. “The brain performs a computation that gives rise to a behavior. There can be complex breakdowns in these computations, just like a brittle bone can break under stress. That has been a guiding principle of my work.”
Early on, Anticevic’s research explored how circuits in the brain responsible for affective computations interact with parts of the brain involved in organizing our thoughts into goals and actions. In other words, how does human emotion intertwine with cognitive capacity in the brain?
“Historically,” he says, “those two areas have been treated as separate disciplines. I wanted to understand the points at which the two interface.”
Eventually he went to Washington University where he earned a PhD in clinical psychology and cognitive neuroscience. There, working with Deanna Barch, a prominent schizophrenia researcher whom he describes as “one of the best clinical neuroimagers in the country and a tremendous mentor,” Anticevic began to study schizophrenia.
Frontiers of schizophrenia research
“Once I got involved in schizophrenia research, there was no turning back,” he recalls. “It’s a fascinating, incredibly complicated problem. Scientists have been working on this for 100 years—since the original conceptualizations of the disorder—and we still don’t have a true neurobiological understanding of the underlying mechanisms.”
“It’s a serious medical problem,” he adds, “and there is a significant public health burden as well. If you want an example of a mental illness that truly robs the individual of his or her capacity to function, schizophrenia is such a disorder. We don’t even know if it’s one disorder. It could be many.”
Building on his previous work, Anticevic first focused on the interface of cognition and emotion in patients with schizophrenia. How do motivational deficits impact patients’ ability to function on a daily basis? Do schizophrenia patients perceive affect the same way as people who are healthy and functioning normally? His doctoral work showed that ‘in-the-moment’ responses to emotional information seem to be relatively intact in individuals with schizophrenia. Instead, studies suggest that there are breakdowns in patients’ processing of rewarding information over time. This breakdown impacts their ability to pursue future goals, a core ‘negative’ symptom known as amotivation.
Eventually, says Anticevic, “It became evident to me that fMRI, while very powerful, is a readout tool. It provides an indirect method to measure neural activity. But in and of itself, it does not guarantee a good clinical experiment. I needed more tools to try to understand the cause and effect of how these circuits work, and to translate findings from the level of local circuits in the brain, to systems, to behaviors.”
So he returned to Yale, first as an intern and later a junior faculty member, to work with John Krystal and others using pharmacological neuroimaging.
Schizophrenia and pharmacological research
Dr. Krystal and colleagues had done groundbreaking work in the 1980s-90s in which they attempted to produce symptoms of schizophrenia in the laboratory safely and transiently in individuals using the drug ketamine. Their research focused on the “circuit level” of the brain; later teams in Dr. Krystal’s lab, including Anticevic, worked to characterize the impact of ketamine at the cellular level. The ultimate goal was to understand how disturbances at the cellular level impact larger systems in the brain and ultimately, affect the behaviors that can go awry in complex mental illness.
Paradoxically, their results showed elevations in glutamate and increases in brain activation in individuals given ketamine.
“There was evidence that there might be a neural dis-inhibition at play, almost like lifting a brake on the system and creating too much aberrant communication in the brain,” Anticevic explains.
This didn’t reconcile with traditional assumptions about schizophrenia.
“Schizophrenia had always been thought of as causing a reduction in function,” he says, “a reduction in connectivity in the brain, a loss of dendritic spines, a loss of neuron density.”
However, most previous research had looked at patients with chronic schizophrenia—those who have been diagnosed as having the illness for multiple years and received multiple medications and treatments. So Anticevic and colleagues set about to analyze the brain scans of patients at different stages of the illness, including longitudinally through collaborations with colleagues in China.
“To our surprise,” he explains, “we observed that earlier stages of the illness mimic what we see in humans who are safely administered a low dose of ketamine.” As predicted by the computational modeling, the brains of early schizophrenia patients showed an abnormal spike in neural connectivity.
It’s evidence, he says, “of aberrantly elevated communication between certain brain regions, not necessarily reductions. Reductions may be there, or they may follow later, but this work confirmed our hypotheses that the earlier stages of the illness might show important functional differences from later stages.” (To read more about that study, click here; for additional schizophrenia findings here.)
Questions lead to more questions. How do we understand cognitive deficits from circuits to system to behavior? How do we develop better imaging markers that are truly grounded in computational models and a mechanistic understanding of the brain?
Anticevic and his colleagues are actively pursuing a few research areas based on the recent findings on schizophrenia. For example, is the abnormal spike in neural connection causing schizophrenia, or is it a “fever effect” or secondary marker of illness developing? If the latter, what is the underlying mechanism? Are mechanisms causing cognitive deficits in schizophrenia really schizophrenia-specific?
“It’s very much an open question,” Anticevic notes, “as to whether there are multiple mechanisms either at the genetic or cellular level that lead to one common pathway of psychosis—so you could get to psychosis through several distinct neural pathways—or whether there are separate types of schizophrenias, each with a distinct neurobiological process.”
On the mathematical front, the team is trying to improve its computational models to mimic more precisely the neuroimaging disturbances they see. This multidisciplinary work is accomplished in close collaboration with Dr. John Murray, newly appointed assistant professor of psychiatry.
“There are some real challenges facing the field because we don’t have the data to address all of the questions we have,” Anticevic explains. “We can formulate hypotheses but collecting an adequate sample size of individuals with sufficient clinical variability properly characterized with the proper imaging measures that are also genotyped—this is a huge undertaking.”
Ultimately, unlocking the secrets of brain malfunction will require time, resources, and imagination.
“For me,” Anticevic says, “the creativity comes from sitting down with my close colleagues who are wonderful to talk to but may have a different perspective on the issue. I deeply enjoy and welcome the productive debate to conceptualize the issue from different angles. That basic curiosity is one of the most rewarding aspects about my work—being surrounded by brilliant people who do amazing things and being able to knock on somebody’s office door and brainstorm through a problem with them and build new insight.”
Expanding the boundaries of computational neuropsychiatry may sound abstract, but for Anticevic and colleagues it is fundamentally about improving people’s lives through more accurate diagnosis and better treatment development. Their research will continue to evolve as data from around the world becomes increasingly available and accessible. As they bring their skills and imaginations to bear upon the data, the hope is that eventually, people in recovery will have new and better options.
“If you do good work, if you execute solid experiments, you’ll get an answer. Even if it is not what you predicted,” Anticevic concludes, “you will know a little bit more every time. That’s what our lab is focused on accomplishing.”