Itti, Laurent
Professor of Computer Science and Psychology
The main fundamental research focus of the lab is in using computational modeling to gain insight into biological brain function. Thus, we study biologically-plausible brain models, and we compare the predictions of model simulations to empirical measurements from living systems. The brain subsystem towards which most of our efforts are focused is the visual system. Our modeling efforts range from fairly detailed models of small neuronal circuits, such as a single hypercolumn of orientation-selective neurons in primary visual cortex, to large-scale models embodying several million highly-simplified neurons to explore mechanisms of visual attention, gaze control, object recognition, and goal-oriented scene understanding. Further, we strive to employ modeling principles which are mathematically optimal in some task- and goal-dependent sense. Thus, we are interested in investigating the tasks and conditions for which the biological brain approaches the theoretical limits of information processing.
Jakowec, Michael
Professor of Clinical Pharmacy (Teaching)
The primary focus of research in Dr. Jakowec’s laboratory is to better understand the underlying molecular mechanisms involved in neuroplasticity in the injured brain with the emphasis on the basal ganglia and prefrontal cortex, regions of the brain responsible for motor and cognitive behaviors.The overarching goal is to find improved therapeutic approaches for brain disorders especially Parkinson’s disease and drug addiction. For the past 20 years the laboratory has examined the effects of exercise on promoting neuroplasticity, particularly synaptogenesis in animal models of Parkinson’s disease. In addition to non-pharmacological approaches to promote brain repair, ongoing studies are using an experimental therapeutics approach to explore pharmacological interventions to determine if novel drugs can serve as a means to enhance brain repair, especially in the context of exercise. Recent studies have focused on the mechanisms by which astrocytes support neuronal function as well as mechanisms by which boosting mitochondrial integrity can promote improved functional connectivity and restoration of motor and cognitive behaviors.
Kaplan, Jonas
Associate Professor of Psychology
I study self, consciousness, and meaning-making in all of its forms, with a focus on understanding the neural systems that integrate information to form high level models of the world and of the self. This includes a focus on narrative cognition, and naturalistic fMRI methods that allow for the analysis of the real-time, ongoing neural dynamics that support our understanding of the people, events, and stories that make up our worlds.
Kim, Hosung
The Neuroimaging with Deep Learning Lab (NIDLL) focuses on developing and applying advanced artificial intelligence methods to understand brain health, aging, and disease. Our research integrates multimodal neuroimaging, biosignals, and longitudinal clinical data to characterize individual variability in brain structure and function across the lifespan. A central theme of the lab is the use of deep learning and data-driven modeling to derive biologically meaningful markers—such as regional brain age and system-level brain health indices—that can predict clinical outcomes and treatment response. A major emphasis of NIDLL is on sleep, cerebrovascular function, and the glymphatic system as key modulators of brain aging and neurodegeneration. We develop MRI-based metrics to quantify perivascular spaces, cerebrospinal fluid dynamics, and glymphatic function, and study how their disruption relates to poor sleep quality, accelerated brain aging, and neurodegenerative processes. These methods are applied across diverse populations and neurological conditions, including Alzheimer’s disease, Parkinson’s disease, stroke, epilepsy, and sleep disorders, with the goal of identifying early, noninvasive biomarkers of disease vulnerability and progression. Ultimately, NIDLL aims to bridge computational neuroscience and translational medicine by building predictive models that support precision diagnosis and personalized intervention. By combining large-scale neuroimaging datasets, longitudinal designs, and interpretable AI, our work seeks to inform clinical decision-making and optimize therapeutic strategies for neurological and sleep-related disorders. The lab is led by Dr. Hosung Kim, who mentors trainees and collaborators in developing rigorous, impactful research at the intersection of neuroimaging, artificial intelligence, and brain health. We welcome you to join the lab and participate in our valuable research.
Kircanski, Katharina
The Multi-method Emotion Science and Outreach (MESO) Lab integrates affective and cognitive neuroscience, clinical science, and quantitative methods to study mechanisms of mood and anxiety disorders. We are particularly interested in parsing shared vs. specific mechanisms of symptoms that manifest across childhood and adolescence. Our research utilizes a multi-modal approach that includes fMRI, behavioral paradigms, and ecological momentary assessment (EMA).
