BME PhD Thesis Defense: "Development of Automated Analysis Methods for Identifying Behavioral and Neural Plasticity in Sleep and Learning in C.Elegans" by Daniel Lawler, PhD Student

Thursday, October 24, 2019
10:00 am to 11:00 am
Floor/Room #: 
GP1002

Abstract: Neuropsychiatric disorders severely impact quality of life in millions of patients, contributing more Disease Affected Life Years (DALYs) than cancer or cardiovascular disease. The human brain is a complex system of 100 billion neurons connected by 100 trillion synapses, and human studies of neural disease focus on network-level circuit activity changes, rather than on cellular mechanisms. To probe for neural dynamics on the cellular level, animal models such as the nematode C. elegans have been used to investigate the biochemical and genetic factors contributing to neurological disease. C. elegans are ideal for neurophysiological studies due to their small nervous system, neurochemical homology to humans, and compatibility with non-invasive neural imaging. To better study the cellular mechanisms contributing to neurological disease, we developed automated analysis methods for characterizing the behaviors and associated neural activity during learning and sleep in C. elegans: two neural functions that involve a high degree of behavioral and neural plasticity. Traditionally, the study of learning in C. elegans observes taxis on agar plates which present variable environmental conditions that can lead to a reduction in test-to-test reproducibility. We translated the butanone enhancement learning assay such that animals can be trained and tested all within the controlled environment of a microfluidic device. Using this system, we demonstrated that C. elegans are capable of associative learning by observing stimulus evoked behavioral responses, rather than taxis. This system allows for more reproducible results and can be used to seamlessly study stimulus-evoked neural plasticity associated with learning. We also developed two methods to study previously uncharacterized spontaneous adult sleep in C. elegans. A large microfluidic device facilitates population-wide assessment of long-term sleep behavior over 12 hours including effects of fluid flow, oxygen, feeding, odors, and genetic perturbations. Smaller devices allow simultaneous recording of sleep behavior and neuronal activity. Since the onset of adult sleep is stochastically timed, we developed a closed-loop sleep detection system that delivers chemical stimuli to individual animals during sleep and awake states to assess state-dependent changes to neural responses. Sleep increased the arousal threshold to aversive chemical stimulation, yet sensory neuron (ASH) and first-layer interneuron (AIB) responses were unchanged. This localizes adult sleep-dependent neuromodulation within interneurons presynaptic to the AVA premotor interneurons, rather than afferent sensory circuits. Together, these systems provide platforms for studying the connections between behavioral plasticity and neural circuit modulation in sleep and learning. We can use systems to further our understanding of the mechanisms underlying neural regulation, function, and disorder using human disease models in C. elegans.

Defense Committee:
Dirk Albrecht, PhDAssociate Professor, Biomedical Engineering, WPI (Thesis Advisor)
Songbai Ji, PhDAssociate Professor, Biomedical Engineering, WPI (Chair)
Kwonmoo Lee, PhD, Assistant Professor, Biomedical Engineering, WPI
Jagan Srinivasan, PhD, Associate Professor, Biology and Biotechnology, WPI
William Schafer, PhD, Program Leader, Neurobiology Division, MRC Laboratory of Molecular Biology

 

 

 

                                                                                                                       

DEPARTMENT(S): 
Name: 
Department of Biomedical Engineering
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