The focus of the research in our laboratory is to understand recovery of function after neurological disruption and we focus this work primarily on understanding recovery after severe traumatic brain injury, where individuals experience coma from days to weeks after injury. To achieve this broad goal, we take both a cognitive neuroscience and clinical neuropsychological perspective to understanding recovery after catastrophic injury (see below). The research methods employed in our lab have great range including statistical modeling of brain networks using brain imaging methods and documenting cognitive and emotional functioning via interviews, surveys, and cognitive testing. This research is conducted within the Department of Psychology at University Park (UP) and at Hershey Medical Center (HMC) in Hershey PA. In addition, we have close collaborative relationships with investigators at the Kessler Foundation in New Jersey (Drs. Glenn Wylie and Helen Genova), The Mind Research Network in Albuquerque New Mexico (Dr. Vincent Calhoun), Baylor College of Medicine (Dr. Elisabeth Wilde), and the University of Michigan (Dr. Benjamin Hampstead).
Alzheimer’s Disease Neuroimaging Initiative (ADNI)
The Alzheimer’s Disease Neuroimaging Initiative (ADNI) unites researchers with study data as they work to define the progression of Alzheimer’s disease (AD). ADNI researchers collect, validate and utilize data, including MRI and PET images, genetics, cognitive tests, CSF and blood biomarkers as predictors of the disease. We are working on a few studies examining hyperconnectivity in these data. To learn more about ADNI, click here.
ENIGMA Brain Injury
The ENIGMA consortium is an international effort by leaders worldwide. We are in charge of the North American branch of data collection for moderate to severe TBI. The network brings together researchers in imaging genomics, neurology, and psychiatry to understand brain structure and function, based on MRI, DTI, fMRI, genetic data, and many patient populations. The ENIGMA network has several goals: 1) to create network of like-minded individuals interested in pushing forward the field of imaging genetics, 2) to ensure promising findings are replicated via member collaborations in order to satisfy the mandates of most journals, 3) to share ideas, algorithms, data, and information on promising findings or methods, and 4) to facilitate training, including workshops and conferences on key methods and emerging directions in imaging genetics. To learn more, click here.
Examining Elderly Traumatic Brain Injury and Risk for Neurodegeneration
Data collection is ongoing through a new grant which seeks to understand the risk factors for Alzheimer’s disease after TBI, including timesince diagnosis, ethnicity, and genetic predictors. In Aim 1 the goal is to collect data in a large group of individuals with TBI to understand these interacting factors in predicting cognitive decline. Then in Aim 2, in a sub-group of individuals we use brain imaging methods in order to determine the network response associated with neurodegeneration decades post TBI. Ultimately, the ability to monitor the neural network response to injury-specific factors in combination with risk/resiliency factors (e.g., genetic, health) may bring greater precision to rehabilitation in TBI and aid in identifying patients at risk for neurodegeneration years prior to onset.
Longitudinal Examination of Recovery from Moderate to Severe TBI
While the research in our lab examines a number of TBI-related factors including cognition and outcome, over the past 10 years one important emphasis of the work in our lab has been to understand systems-level plasticity after TBI. In this work, we use both behavioral and functional brain imaging methods in humans and detail cross-sectional approaches with longitudinal designs to understand patient outcome during critical recovery windows.
Pennsylvania Trauma Database
One ongoing study using this database seeks to clarify the discrepancy in incident rate of TBIs in racial and ethnic minorities in the population compared to their inclusion in the literature and add to updated findings about incident rate of TBIs in these populations.
Functional Imaging and Brain Plasticity
Early functional neuroimaging studies in TBI focused on cognitive disruption, with most focused on signal amplitude (i.e., activation) during tasks engaging working memory systems. One primary finding from this work was that TBI often resulted in neural “recruitment” of frontal resources while engaged in cognitive tasks, a phenomenon we summarized in a 2006 paper in Human Brain Mapping and a follow-up paper in 2008 in the Journal of the International Neuropsychological Society. In these papers we challenged the common conclusion that enhanced frontal “activity” after TBI represented “brain reorganization”. Based upon this argument, through a series of papers from 2006-2012, we set out to examine this neural recruitment phenomenon. We created experimental conditions whereby the effect could be temporarily abolished via task practice (see paper by Medaglia et al., 2012 in Human Brain Mapping) and statistically linked PFC recruitment directly to slowed processing speed in TBI. Summaries of these contributions are represented in a book that Dr. Hillary co-edited with Dr. John DeLuca in 2007 (Title: Functional Brain Imaging in Clinical samples) and several chapters in the areas of neuropsychology and rehabilitation.
With recent emphasis on achieving a human connectome, brain imaging work in both the cognitive and clinical neurosciences has seen a dramatic shift toward understanding how complex networks give rise to complex human behavior. In lock-step with this conceptual change, we pioneered the first TBI studies using resting connectivity and graph theory as well as many of the few studies in the literature examining connectivity changes longitudinally. In the first study in TBI to use resting fMRI and graph theory, we examined recovery from TBI at 3 and 6 months post injury revealing that injury resulted in a paradoxical increase in connectivity (see appended reprint, Nakamura, Hillary & Biswal, 2009; PLOS ONE). Since this first paper, we have published the few longitudinal studies in the moderate and severe TBI literature documenting using connectivity modeling and fMRI datasets. This work was also the basis for our recently proposed hyperconnectivity hypothesis which was born from our earlier work using focused analysis of frontal lobe subnetworks. Frontal lobe dysfunction is pathognomonic after TBI and our 2011 paper in Brain provided the first analysis of frontal hyperconnectivity using detailed modeling of frontal lobe connections to test specific hypotheses about how frontal systems adapt to TBI both locally and in connection with posterior attention networks (see reprint). We examined the hyperconnectivity hypothesis in a follow-up paper in 2014 in PLOS ONE and based upon these findings, we refined the parameters of a hyperconnectivity hypothesis in a critical review published in 2014 in Neuropsychology. Through longitudinal designs our current work aims to understand the brain changes occurring in traumatic brain injury over the life span including recovery and decline and we are integrating datasets with collaborators at the University of Michigan (PI: Benjamin Hampstead) to examine the expression of network plasticity in individuals diagnosed with mild cognitive impairment or prodromal Alzheimer’s disease. We are currently working to test hypotheses regarding genetic vulnerability to brain connectivity changes within central brain network regions as predictors of neurodegeneration over the life span. In sum, the use of resting connectivity methods in the study of plasticity after TBI and in aging continues to be a powerful approach for understanding the consequences of brain injury and the research in the lab has been at the forefront of this literature.
One additional area of our work has been to develop MRI-based methods for appropriate application to the study of TBI. Most recently my focus on methods has turned toward testing functional connectivity procedures, including examining the relationships between signal amplitude (i.e., activation) and connectivity after brain injury (Medaglia et al., 2014) to provide context for our studies. At the same time, we have applied a novel structural equation modeling technique developed by Drs. Kathleen Gates and Peter Molenaar to advance study of effective connectivity (see papers in NeuroImage 2010, 2011). Most recently, Dr. Hillary worked with his post-doctoral fellow and Drs. Peter Molenaar and Reka Albert to devise whole-brain parcellation methods for documenting network change in multiple-time-point data (see appended paper by Rajtmajer et al., 2015 in Frontiers in Neuroanatomy and Roy et al., 2016 in Frontiers in Neuroscience). These approaches have been designed specifically to provide our lab with greater sensitivity to individual differences in the expression of network plasticity over time.
Cognitive and Emotional Consequences of TBI
In tandem with research focusing on functional brain changes over the lifespan in TBI, our lab has a longstanding focus on the cognitive and emotional consequences of TBI. Most recently this work has shifted to understanding the interactions between personality and demographic factors (age) that influence outcome after TBI. The work in our lab has expanded the study of behavioral deficits beyond the common cognitive constructs, allowing for focus on higher-order cognitive deficits as well as mood and other behavioral disturbances after TBI (see papers by Chiou et al., 2011 in JINS). Important points of emphasis for our lab include the combined effects of aging and TBI, including the increased rate of elderly TBI over the past 20 years in Pennsylvania and the distinct relationships between age and mechanism of injury (see Ramanathan et al., 2012, in J. Neurotrauma). Moreover, we are interested in comorbidities associated with TBI such as health and alcohol use at the time of injury; recently a graduate student in the lab Rachel Bernier published a paper examining changes in demography and alcohol use at the time of TBI over a 20-year period (see Bernier et al., 2016).