Researchers in our laboratory are focused on discovering the fundamental organization of large-scale human brain networks. A core motivation that drives this work is the search for specific network-level signatures, or “fingerprints”, that co-vary with heritable behavioral variation in the general population and mark vulnerability for psychiatric illness onset.


Current projects encompass three complementary domains.

Functional Architecture of the Human Brain

The human brain is a complex web of interdigitated networks. Substantial progress has been made delineating the structure and function of aspects of this intricate architecture through post-mortem dissections in humans and invasive tract tracing and lesion studies in animals. Yet there are many gaps in our understanding of how the brain’s functional connectivity and network properties influence behavior. Recent advances in imaging technologies allow us to study network function in vivo, in a rapid and non-invasive manner, across large numbers of participants. Leveraging these non-invasive techniques, our lab works to characterize the organization of functional and anatomical brain networks. Information gained through these approaches is applied to the study of individual differences and risk for the development of psychiatric illness.

Goal Pursuit
The ability to pursue goals through an ever shifting and uncertain environment is core to human survival. To accomplish this, the brain must integrate internal and external stimuli across multiple time scales. Prior work based on descriptions of discrete moments during reward anticipation and consumption has greatly advanced understanding of the cortico-striatal circuits that support motivated behavior. However, relatively little is known about the dynamic neural mechanisms that underlie sustained goal pursuit in humans. In order to inform our understanding of how motivated behavior is directed and maintained over time, researchers in our lab are studying the processes through which dynamic goal monitoring is instantiated in the brain. Investigators: Kevin Anderson and Lauren Patrick
Network Dynamics

Human thought and behavior emerge from the integration and coordination of distributed brain networks. Traditional static descriptions of network coupling have provided foundational discoveries, characterizing core aspects of brain function. However, the brain is a dynamic system and recent work has demonstrated time-varying fluctuations in network coherence. A current line of work in our lab explores the dynamic aspects of network function. The study of dynamic flexibility in the coordination of neural systems has the potential to improve our understanding of how the brain adaptively supports state dependent shifts in behavior. Investigators: Jenna Reinen – In collaboration with Thomas Yeo and Randy Buckner

Genetic and Brain Bases of Individual Differences

Identical experiences can produce drastically different behavioral and emotional responses across time, space and person. While these responses arise in a seemingly effortless manner, the ease with which they are experienced masks the intricate neural circuitry supporting their expression and regulation. A fundamental question facing researchers is how such marked behavioral variability is instantiated in the brain. Additionally, although individual differences in brain structure and function are readily observable in the general population, open questions surround both their origins and functional significance. While some variance may reflect the gradual accumulation of a lifetime of experience, other differences are highly heritable, suggesting a strong genetic component. Ongoing work in our lab seeks to establish reliable links between genetic variation, system-level brain function, and behavior in the general population.

Brain Anatomy and Behavior
We are pursing a series of studies that aim to characterize how subtle variability in the physical structure of the brain might influence complex cognitive and affective functions. Research in this area is just beginning. Initial projects established relations linking structural variation in an amygdala-medial prefrontal cortex (mPFC) circuit with the presentation of affective and social traits in healthy young adults. Subsequent work uncovered associations between amygdala-mPFC circuit anatomy and the presence of both isolated and polygenic vulnerabilities for the onset of psychiatric illness and chronicity in patients with depression. – In collaboration with Randy Buckner, Joshua Roffman, and Jordan Smoller
Individualized Network Topographies

Population-level variability in cognition and behavior likely reflect shifts in the network architecture of individuals, particularly in the higher order association regions. Mapping functional network topography down to the level of a single person is critical for clinical intervention and the study of individual differences. Ongoing work in our lab explores functional and structural network organization at the individual level. The capacity to identify the unique functional architecture of a subject’s brain is a critical step towards personalized medicine as well as understanding the neural basis of variations in human cognition and behavior. It is our hope that the knowledge gained through this approach can provide novel biological targets for therapeutic interventions and predictive markers of clinical course. – In collaboration with Hesheng Liu

Neurobiological Markers of Psychiatric Illness

The brain’s exquisite complexity allows for the staggering diversity of human behavior. However, the evolutionary forces that enabled complex cognitive functions have also pushed our capabilities to their limits, increasing vulnerability for psychiatric illness. Using our understanding of the genetic and brain bases of individual differences in behavior as a foundation, we are exploring links between disturbances in network organization and clinical presentation in patient populations. Recent work from our group focused on the manner in which functional connectivity and network coherence is altered in the presence of affective and psychotic illnesses, emphasizing brain networks believed to support core cognitive control functions. Ongoing projects seek to characterize the discrete and transdiagnostic features of schizophrenia, bipolar disorder, anxiety, depression and how these differ from healthy functioning. Through this approach we hope to facilitate earlier and more accurate diagnoses, improve treatment outcomes, and enable the detection of illness risk in healthy populations

Cognitive Control in Depression

One essential aspect of cognition is the ability to flexibly modify behaviors based on negative outcomes and unexpected changes in the environment. These core cognitive control processes are supported through the function of a distributed network of interconnected regions that encompass the anterior cingulate and the dorsolateral prefrontal cortex. Patients with depression display deficits in cognitive control, including difficulty coping with change and abnormal reactions to errors and negative feedback. Prior work from our lab established a rapid downward spiral in performance following error commission, an inability to account for shifting task incentives, and dysregulated fronto-cingulate interactions in patients with depression. Ongoing studies are exploring the diagnostic specificity of cognitive control impairments across psychiatric populations. Additional lines of research examine relations between impaired cognitive control system functioning and illness risk.

Network-Level Fingerprints of Unipolar and Bipolar Depression

Psychiatric diagnoses describe clusters of frequently co-occurring symptoms that recur across multiple diagnostically distinct illnesses. The issues inherent in this complexity are particularly evident when considering the gaps in our knowledge of illness etiology. For instance, impaired frontoparietal network integrity has been observed in bipolar disorder. However, it is not yet clear if this reflects a specific vulnerability factor, or a general marker, for psychiatric illnesses with an affective component. In responding to these challenges, our lab is seeking to characterize the shared and unique features of network function that track symptom severity in unipolar and bipolar depression. The information gained through this research will be applied to the study neurogenetic factors that influence clinical course and risk for illness onset. – In collaboration with Dost Öngür and Justin Baker

Risk for Affective Illness

Over one third of adults will experience an anxiety or mood disorder in their lifetime, making these illnesses a leading cause of global disease burden. Chronic or severe anxiety and negative affect predict subsequent clinical diagnoses, but many people with such symptoms never develop full-blown anxiety or mood disorders. This suggests that diagnosable illnesses lie at the extreme end of a continuum encompassing health and disease. Despite this possibility, research on the neuroanatomical basis of negative affect has most often focused on animal models or clinically ill patients. While this approach has been highly productive, the importance of establishing the predictive utility of brain phenotypes during the prodromal stages preceding illness onset has been overlooked. Current work in our lab studies relations linking brain structure and function with illness risk in healthy young adults. Through this work we seek to establish which neurobiological markers of affective illness reflect current episode severity, the cumulative effects of a chronic course, or premorbid trait vulnerabilities.  – In collaboration with Daphne Holt