Monitor Neural Activity

Over the past 15 years, new microscope technologies and methods for high throughput imaging have revolutionized structural biology by extending the resolution and scale of datasets in 3 dimensions. The resulting image volumes are more typically hundreds of GB to even tens of TB and for large volume electron microscope images of brain, can approach PB sizes. These file sizes pose challenges for image analysis, and communication of a representative set of raw data and quantification.

Abstract Microelectrode arrays (MEAs) have great potential for therapeutic use in direct brain-computer interface (BCI) control of robotic prostheses to improve the lives of patients suffering from debilitating conditions related to loss of limbs or limb function. MEAs also have the potential to restore loss of sensory perception in vision, hearing, and tactile sensation by applying patterned current stimulation to sensory neurons.

Project Summary Learning and performing complex skills such as speech or music requires precise control of motor variability. While elevated motor variability can spur the learning of new behaviors, excessive variability can impair performance of learned skills. How the brain controls motor variability during learning and in expert performance remains unclear. Intriguingly, the basal ganglia (BG) is an important source of motor variability in both health and disease, and is a key site where dopamine (DA) reinforces more successful behaviors.

Decision making is a fundamental cognitive process, and many decisions are based on gradually accumulated evidence. Thus, it is critical to understand the mechanistic basis underlying this accumulation process. Traditional models of evidence accumulation are based on low-dimensional attractors where individual neurons show ramping activity throughout a trial. However, an increasing number of studies have observed choice-selective sequences in their neural recordings, in which neurons fire transiently and sequentially with the subset of neurons that fires indicative of the animal’s choice.

PROJECT SUMMARY Animals can exhibit goal-directed behaviors in novel environments, despite limited experience with them. How does the brain make and use inferences about the underlying statistics and generative structure of environments to guide behavior? The field of reinforcement learning refers to this capacity as “model-based” reasoning, meaning that it relies on an internal model of the structure of the world. Critically, this internal model can be used to flexibly estimate the best actions by mental simulation or planning, without direct experience.

TITLE: IDENTIFYING THE NEURAL MECHANISMS OF GOAL-DIRECTED DECISION-MAKING IN PARKINSON’S DISEASE USING CLOSED-LOOP DEEP BRAIN STIMULATION PROJECT SUMMARY People with Parkinson’s disease commonly suffer from non-motor symptoms, including motivation deficits, that impact quality of life more than classical

Electrostimulation (ES) is a versatile and efficient tool for interrogating, altering, and manipulating neural activities in health and disease. Deep brain ES delivered with implanted electrodes requires an elaborate neurosurgery and carries risks of tissue damage, bleeding, stroke, infection, and inflammation. This limits the use of deep brain ES for disease diagnostics and conditions that may not justify the risks. Non-invasive targeted deep brain ES has long been a major quest, with countless potential applications.

The exponential surge in the prevalence of neurological diseases/disorders, partly due to the rapid growth in the aged population, poses a significant challenge to the prevention and treatment of impairments in cognitive, sensory, and motor functions. However, our insufficient understanding of the mechanisms underlying the pathogenesis of many neurological diseases delays the development of effective treatments to address this challenge. Recent advances in optogenetics have provided novel tools to investigate complex neural circuits and brain functions.

Abstract Optical methods provide high-resolution, non-invasive measurement of neural function, ranging from single neurons to entire populations, in the intact brain. Nevertheless, limited penetration depth, spatial scale and temporal resolution remain the main challenges for optical imaging. Laser scanning multiphoton microscopy is the main technology used for cellular-level imaging in scattering brains.

Electrophysiology is a critical technology in neuroscience as a direct measure of neuronal functions. It has become routine for scientists to record and stimulate neuron populations in different brain regions in awake behaving animals, correlating activity with behavior. However, it has been insurmountable for the same electrophysiology to perform well in the spinal cord of behaving animals.