Neuroscience Faculty

Andy Alexander is interested in interactions between the neocortex, thalamus, and extended hippocampal formation that subserve spatial cognition and mnemonic processes.

Professor Ashby is interested in the basic cognitive and neural mechanisms that mediate human learning. His approach combines experimental psychology, cognitive neuroscience, and mathematical modeling.

Computational Vision, Computational Neuroscience, Neuroengineering, Human-Computer Interaction.

Cognitive neuroscience, learning, memory, categorization, decision processes in perception and cognition.

Dr Clegg's research focuses on developing cures for blindness using embryonic, iPS, and adult stem cells.

Neural & cardiovascular tissue engineering/regenerative medicine. Stem cells, mechanobiology, molecular control systems.

Dr. Eckstein is interested in how biological organisms and artificial intelligent agents visually sense the world and make decisions. He uses computational modeling, cognitive neuroscience and behavioral measurement techniques.

Normal and Pathological Action of the Microtubule-Associated Protein Tau; Alzheimer’s and related dementias.

Structure and function in the vertebrate retina with an emphasis on mechanisms underlying photoreceptor degeneration and the role of glial cells in normal and injured or diseased retina.

Dr. Gazzaniga is currently engaged in several scholarly projects examining how codes play a role in understanding how neurons become mind.

Visual attention; Cognitive neuroscience; Brain Imaging; Exercise physiology.

The Goard lab focuses on how the mammalian neocortex processes and stores incoming sensory information.

Professor Grafton is interested in how people organize movement into goal-oriented action.

Uses human brain imaging techniques (fMRI) and endocrinology to determine the impact of sex steroid hormones on brain morphology and function.

Spatial and temporal organization of stochastic axon systems in the brain.

Neural circuits of appetitive associative learning and decision-making; Circuits alterations in maladaptive behaviors (e.g. addiction)

Neural circuit dynamics and behavior; navigation in a visual environment; neural mechanisms of object selection and decision-making.

Our lab focuses on the factors that lead to drug addiction and the impact of substance abuse on the brain. A major component of our research is development of biosensors to enhance our understanding of neurochemistry and pharmacology.

Neural plasticity including the molecular basis of plasticity and neurodegenerative disease-related impairments related to plasticity and proteostasis. Neural development and evolution from a molecular and genetic perspective.

Our lab uses neuroimaging and causal methods to investigate neural mechanisms underlying emotion perception, metacognition and emotion regulation.

Combining theory and experimentation to understand how navigational decisions come about in terms of neural-circuit computation.

Dr. Miller is interested in the psychological and neural processes underlying human memory and decision-making.

Nina directs the Geometric Intelligence Lab, whose goal is to reveal the geometric signatures of natural and artificial intelligence and to build next–generation intelligent systems: Geometric AI.

Molecular and cellular basis of animal behavior in flies and mosquitoes.

Kyle investigates how biological systems interact with social contexts to influence perceptions of the self and others.

Organization, development and plasticity of the retina and visual pathway.

Systems neuroscience, neuroethology, and genetics, applied to dissecting the neural circuits that control a flexible motor sequence of grooming in fruit flies.

Information processing by neural circuitry with a special focus on the role of active dendrites in nonlinear modes of synaptic integration.

Exploring neural circuitry and illuminating its function, using new neurotechnology.

We research in two primary areas: (1) the mechanisms of neural tube closure in Xenopus and Ciona; (2) and behavior and neural circuity in Ciona.

In the Perception, Cognition, and Action Lab (PCA Lab), we seek to understand how the brain encodes and transforms neural representations of sensory information in service of dynamic behavioral demands.

Dr. Szumlinski’s major research interest concerns the biochemical mechanisms underlying the changes in brain and behavior produced by chronic exposure to drugs of abuse, in particular psychomotor stimulants and alcohol.

In the Media Neuroscience Lab (MNL) we study attention disorders and media-multitasking, aggressive conduct disorders and media violence, moral conflict and narrative performance, and the neural mechanisms of persuasion, flow experiences, and general cognitive control.

We study evolutionary questions using comparative genomic and epigenomic methods. A main research goal of the Yi lab is to understand how epigenetic regulatory mechanisms evolve and impacts phenotypes, such as gene expression, phenotypic plasticity, and diseases.

Dr. Yu combines behavioral experiments, neuroscience and computational modeling to understand the relationship between emotion (e.g., guilt, gratitude) and morality and their neural representations.

Mechanistic and functional study of viral host interaction.

Statistical Methods and Data Analyses, Including For Brain Imaging and Other Neuroscience Data; Statistical Methods for Analyzing Spatial and Temporal Processes; Computational Statistics and Machine Learning; Uncertainty Quantification.

Dynamics and control of neural populations for treatment of Parkinson's disease, coupled oscillators, synchronization, decision making, biological dynamics, machine learning.

Combination of molecular, genetic, and state-of-the-art imaging approaches to define and solve fundamental questions in cell and developmental biology with implications for neurodegenerative disease, ischemic diseases and cancer.

Neuroimaging, MRI, biochemical imaging of the GI tract.

Macroevolution, phylogenetics, bioluminescence, vision, molecular evolution, complexity, marine organismal biology.

Computational methods, mathematical modeling, and machine learning, with application to a wide range of problems from systems biology, neuroscience and engineering.

Regulation of development and differentiation; regulation of programmed cell death and cell division; mechanisms of tumorigenesis.

Data-centric modeling of systems and he focuses on the development of new methods that can be applied to real-world applications.

We use ideas and concepts from physics, computer science, and mathematics to ask how embryos get in shape, and how organs function.

Novel reporters for neural activity, CMOS image sensors and circuits for neurotechnology.

Mechanics of cells and tissues; design of bio-inspired materials with applications to packaging, healthcare and robotics; instrument development.

Molecular mechanisms underlying polycystic kidney disease, and SNARE fusion proteins.

Mechanism and regulation of microtubule polymerization and dynamics; mechanism of action of microtubule-targeted anticancer drugs and microtubule-regulatory proteins.

Combines tools from Biology, Engineering, and Physics to understand the cell’s perceptual field.