Randy Buckner, Ph.D.
Psychiatry, Mass General Research Institute
Professor of Psychology in the Department of Psychiatry
Harvard Medical School
|PhD Washington University School of Medicine in St. Louis 1995|
Using multiple behavioral, neuroimaging and computational approaches our laboratory explores human brain network organization and how genetic variation gives rise to differences that affect behavior, including dysfunction in neuropsychiatric illness. Research in the laboratory involves five interrelated research themes.
(1) The Architecture of Human Brain Networks (Example Pubs)
Until recently, the barrier to understanding the human brain was that invasive techniques could be used only with animals, causing a gap between the understanding of neural circuits being unraveled using animal models and the study of the human brain. Human imaging technologies changed that, and today, images of activity in the thinking brain are a familiar sight. However a gap still remains.
We are actively working with engineering efforts to improve human imaging technologies that can provide increasingly detailed information about the organization and function of brain networks. In a series of recent studies, we comprehensively characterized the organization of the cortex, striatum, and cerebellum with a particular focus on brain networks important to memory and cognitive control.
Current projects include using novel approaches based on high gradient strength diffusion tractography and high field strength functional MRI to resolve organizational details of cortical association networks and limbic networks (amygdala, hippocampus). The technologies are being developed as part of the NIH Human Connectome Project and involve collaborations with the Harvard Center for Brain Science and Athinoula A. Martinos Center for Biomedical Imaging.
(2) Dysfunction in Neuropsychiatric and Neurodegenerative Illness (Example Pubs)
The human brain is fragile. Development of abnormal function in childhood or adolescence, or disruption in advanced aging leads to disorders of affect and cognition. Thus, in addition to the great intrinsic interest in unraveling how the human brain works, understanding how brains become disordered may shed light on neuropsychiatric and neurodegenerative disorders.
Using our understanding of the typical human brain as the foundation, we are exploring disturbances in network organization in a range of neuropsychiatric and neurodegenerative illnesses. Current projects seek to relate disturbances in brain circuitry to symptoms that span traditional diagnostic categories and to determine whether dysfunction can be detected prior to clinical symptoms in individuals at risk for illness. Genetic variations that put individuals at risk for illness anchor this work.
Projects focus on schizophrenia, bipolar disorder, autism, anxiety and depression, and clinically normal older adults who harbor preclinical markers of Alzheimer’s pathology. This work is conducted in collaboration with the MGH Psychiatric Neuroimaging Research Division, the McLean Psychotic Disorders Division, and the Harvard Aging Brain Study.
(3) Deep Phenotyping in the Individual (Example Pubs)
No two individuals are exactly the same, and each person experiences transitions over time that can affect brain function and behavior. In the past, human neuroimaging techniques have had to combine measurements from many people, providing a fictional “average brain” that collapses meaningful variation.
Recently our work has turned to exploring the detailed organization of individual brains and how that organization differs across people and changes over time. This push toward the individual brain is critical for clinical translation as well as a number of open questions about how transient brain states influence behavior.
Three broad questions drive this work. First, are there differences in network organization that link to individual differences in behavior and, in their extreme, risk for psychiatric illness? Second, are the dynamics of brain activity organized into stable functional network configurations (i.e., states) with distinct information processing modes that affect behavior? And do certain brain states predict transition to clinical impairment in neuropsychiatric illness?
This work anchors on recent advances in imaging technologies to make sensitive measures within individual participants at low burden as well as web and mobile technologies able to track behavior over time.
(4) Genetic Mechanisms of Individual Differences (Example Pubs)
Many neuropsychiatric disorders run in families, suggesting a strong genetic component. For example, a child with an autistic sibling is 25 times more likely to develop the disorder than his peers.
We are actively exploring the links between genetic variation and brain network organization to better understand the underlying mechanisms that influence brain function and risk for neuropsychiatric disorders.
Our initial foray into this domain began with an effort to build a large sample of brain, genetic, and behavioral data. This project, the Brain Genomics Superstruct Project, collected data from over 3,000 individuals on a uniform imaging protocol combined with DNA and web-based behavioral testing.
Discoveries arising from this work include identification of links between structural variation in an amygdala-cingulate circuit and affective traits, novel genetic loci associated with psychiatric illness, and links between genetic loci and variation in brain structure.
Work on this front is just beginning. The genetic architecture of individual differences and risk for psychiatric illness are rapidly being unraveled. Using methods to characterize brain organization in the individual, we are taking a genetics-first approach to better understand how genetic variation leads to individual differences in circuit function. This work is conducted in collaboration with the MGH Psychiatric and Neurodevelopmental Genetics Unit and the Broad Institute of Harvard and MIT.
(5) The Ancient Brain in the Modern World (Example Pubs)
The human brain evolved into a hunter-gatherer environment where our ancestors lived in tight-knit groups, worked together to tediously gather and prepare food, and learned from older group members through hands-on activities and story telling. It is interesting to consider the possibility that mismatches may exist between the ancestral environment and life in the modern world. Food is now abundant.
We communicate through text messaging and learn from images and stories on small screens. And our decisions are often about abstract events far in time from the immediate environment. The hypothesis guiding this work is that aspects of brain function and individual differences may best be understood as how brain circuits, evolved for a quite different ancestral environment, are mismatched to the task demands of the modern world.
This is a new line of work for the laboratory. We are embarking on this project by developing mobile applications and web-based technologies to monitor behavior in the real world as well as strategies for mimicking real-world situations in the controlled laboratory environment of the brain-imaging scanner. Study of mismatches may provide insight into counterintuitive behaviors as well as neuropsychiatric and neurodegenerative illness.