CAREER: Enhancing perception and cognition while minimizing side effects through closed-loop peripheral neural stimulation

Perception, cognition, and behavioral performance are heavily influenced by arousal level. For example, a student will likely perform much better on exams when alert than when drowsy or overly anxious. Arousal is regulated by several neuromodulatory systems, including the locus coeruleus (LC), which is a cluster of neurons in the brainstem whose damage often leads to neurodegenerative diseases. Thus, from an engineering standpoint, it is plausible that control of LC activity could maximize behavioral performance in healthy individuals and treat LC related disorders. However, the small size and deep location of the LC in the brainstem makes it challenging to access and manipulate. To overcome this challenge, this project will use peripheral vagus nerve stimulation (VNS) to control LC activity. The vagus nerve, which runs from the brainstem to the colon area, is easy to access non-invasively, and the LC is the main brain structure that mediates the effect of VNS on brain activity. Using cutting-edge machine learning and nonlinear control theory, this project aims to develop an engineering framework for controlling LC activity via periphery VNS and measuring pupil size, which is also an indicator of arousal level. The success of this project will lead to the development of non-invasive methods to enhance human perception and cognition and treat LC-related brain disorders, e.g., Alzheimer's disease, bipolar disorder, depression and Attention Deficit Hyperactivity Disorder (ADHD). Research activities in the planned studies will enrich the undergraduate curriculum and provide interdisciplinary research opportunities for undergraduates and graduate students, who will contribute to the national highly-qualified workforce in the rapidly-growing biotechnology and biomedical engineering field. Moreover, the project is expected to broaden the participation in STEM of under-represented minority and female students with social-economically disadvantaged backgrounds. The proposed educational curriculum and outreach activities will also engage the general public to increase their awareness of how STEM disciplines can be applied to solve problems in the nervous system.

The PI's long-term career research goal is to enhance human perception and cognition through control of population activities within the nervous system. Toward this goal, this project is to develop an engineering framework that uses peripheral nerve stimulation to control neural population activity to achieve optimal behavioral performance while minimizing unintended side effects and to functionally validate this technology in an animal model. The vagus nerve-to-locus coeruleus (LC) pathway will be used as a model system to develop and test the technology. This pathway was chosen because an FDA approved non-invasive vagus nerve stimulator exists and the LC plays a pivotal role in modulating brain functions through regulation of arousal levels. Studies will include assessment of LC spiking activity and pupil size, which is a noninvasive proxy of LC activity that will be useful in future translation of the technology developed. The Research Plan is organized under three objectives. The FIRST OBJECTIVE is to identify the optimal parameter space of VNS (vagus nerve stimulation) for selectively modulating LC activity/pupil size while minimizing side effects on heart rate using Bayesian active learning. A cohort of animals will be implanted with electrodes for left VNS at the level of the carotid artery (blunt dissection) and with a wireless electrocardiography (ECG) transmitter to monitor heart rate. A genetically-encoded calcium indicator will be selectively expressed in LC neurons using viral vectors, enabling calcium imaging of the activity of LC populations of neurons. The average spiking activity of the LC neurons will then be inferred from the fluorescence signals. Bayesian active learning will be used to discover the VNS parameter spaces in which VNS has high efficacy in driving LC activity/pupil size while leaving minimal effects on heart rate. Stimulation will be presented in the form of bursts of charge-balanced bi-phasic current pulses with short inter-pulse intervals. The parameter space will include current amplitude of the higher amplitude phase of the pulses, pulse width of the higher amplitude phase, pulse polarity (i.e. cathode-leading or anode-leading), pulse waveform, asymmetry ratio, inter-pulse interval, number of pulses per burst, and inter-burst interval. The SECOND OBJECTIVE is to synthesize a nonlinear closed-loop controller for control of LC population activity/pupil size while minimizing changes in heart rate through VNS. Non-parametric Gaussian Process (GP) models will be used to model the nonlinear synamics of the vagus nerve-to-LC and vagus nerve-to-pupil circuitry. A nonlinear predictive model controller based on the GP models will be synthesized to control LC population activity/pupil size through VNS in a closed-loop fashion. Different nonlinear optimization methods will be tested in the controller, and extensive simulations will be conducted to evaluate its performance. The THIRD OBJECTIVE is to functionally validate the technology in awake behaving animals. The extent to which the controller is able to maintain optimal behavioral performance while producing minimal side effects for animals in real-world applications will be examined. Rats instrumented for monitoring the spiking performance of neurons in the LC will be trained to perform a tactile detection task, e.g., licking a water spout in response to a whisker deflection. Their behavioral performance will be quantitatively evaluated from the probabilities of their correct and incorrect responses to sensory stimuli. The behavioral performance and heart rate of animals in sessions with the stimulator on will be compared to those in sessions with the stimulator off. Different firing rates will be tested to determine which firing rate results in optimal behavior performance. The successful completion of the above objectives will provide, for the first time, an engineering framework to guide the design and validation of optimal, closed-loop stimulation for enhancing behavior.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.