Systems Neuroscience and Neuroengineering Laboratory
We are continually in motion. The central goal of Dr. Cullen’s lab’s research is to understand how the brain integrates multisensory information to ensure the maintenance of balance and posture, as well as perceptual stability in everyday life. Specifically, the Cullen lab studies the neural encoding of vestibular information, and how this information is combined with proprioceptive, visual, and motor signals to generate neural representations of our motion. Our work has significant implications for both understanding and advancing the treatment of vestibular and other motor disorders. Our experimental approach is multidisciplinary and includes a combination of behavioral, neurophysiological and computational approaches in alert behaving non-human primates and mice. Funding for the laboratory is provided by The National Institutes of Health (NIH), the Kavli Discovery Institute, and Johns Hopkins University.
The neural encoding of self-motion
A primary focus of our lab is to understand how the vestibular system encodes self-motion information, and how it uses that information to produce behavior and perception. However, behavior and perception are not shaped by a single sensory system; rather, these functional outcomes result from the brain combining sensory information from multiple modalities. Such multisensory integration is a key feature of many vestibular brain areas. Our laboratory is currently exploring how vestibular and extra-vestibular (i.e., somatosensory, visual) input is integrated in the vestibular brainstem, cerebellum, and cortex using a combination of high-density electrophysiological recordings, behavioral tracking, and modeling. The goal of this research is to build a better understanding of how information from multiple senses is used to update internal models of self-motion.
Restoring vestibular function during natural self-motion
Profound vestibular loss causes postural imbalance, dizziness, and blurry vision. The combination of these symptoms leaves affected individuals at significantly higher risk of falls and severely impacts quality of life. Another major goal of our research group is to understand how the brain recovers function following vestibular loss, as well as developing new approaches for prosthetic-based stimulation that have the potential to maximise quality of life for disabled individuals. Our recent experiments have provided insight into how we can leverage what is known about the natural dynamics of vestibular afferents to better restore functional outcomes. Further, we are working to explore how the brain adapts to and processes signals from the prosthesis, and how these approaches can be applied to more naturalistic behaviours in the lab to better reflect the daily lives of those who can be helped by this technology.
Predictive Coding and internal models of self motion
Integrating sensory with motor signals during voluntary behavior is essential for distinguishing stimuli that are a consequence of intended actions from those that are externally generated. This ability enables the brain to flexibly fine-tune motor actions based on sensory feedback, a computation necessary for subjective awareness of the effects of movements. Our research explores the neural circuits that perform this computation, highlighting the cerebellum’s role in building predictive models of self-generated movement as individuals explore the world. Our recent findings advance our understanding of how the cerebellum computes expected consequences of self-motion in everyday life, where predictions are learned, adapted, and flexibly implemented.
Advancing Vestibular Diagnosis and Rehabilitation: Integrating AI and Clinical Collaboration for Enhanced Patient Outcomes
The vestibular system is essential for stabilizing gaze, maintaining balance, and accurately perceiving head motion and orientation. Patients with vestibular impairment often suffer from disrupted vision, imbalance, and distorted motion perception, severely affecting daily activities. In collaboration with clinical partners, our research combines traditional assessments with innovative measures, such as analyzing head movement kinematics during daily tasks, to evaluate peripheral vestibular function and central compensation. Using AI-driven databases and algorithms, we aim to uncover insights that improve patient evaluation and optimize interventions to enhance recovery and outcomes.
Resources
Click here For An Introduction to the Vestibular System
Click here For a Comprehensive Scholarpedia Article
