Spinal cord injury therapy through active learning

Therapy employing epidural electrostimulation holds great potential for improving therapy for patients with spinal cord injury (SCI) (Harkema et al., 2011). Further promising results from combined therapies using electrostimulation have also been recently obtained (e.g., van den Brand et al., 2012). The devices being developed to deliver the stimulation are highly flexible, capable of delivering any individual stimulus among a combinatorially large set of stimuli (Gad et al., 2013). While this extreme flexibility is very useful for ensuring that the device can deliver an appropriate stimulus, the challenge of choosing good stimuli is quite substantial, even for expert human experimenters. To develop a fully implantable, autonomous device which can provide useful therapy, it is necessary to design an algorithmic method for choosing the stimulus parameters. Such a method can be used in a clinical setting, by caregivers who are not experts in the neurostimulator's use, and to allow the system to adapt autonomously between visits to the clinic. To create such an algorithm, this dissertation pursues the general class of active learning algorithms that includes Gaussian Process Upper Confidence Bound (GP-UCB, Srinivas et al., 2010), developing the Gaussian Process Batch Upper Confidence Bound (GP-BUCB, Desautels et al., 2012) and Gaussian Process Adaptive Upper Confidence Bound (GP-AUCB) algorithms. This dissertation develops new theoretical bounds for the performance of these and similar algorithms, empirically assesses these algorithms against a number of competitors in simulation, and applies a variant of the GP-BUCB algorithm in closed-loop to control SCI therapy via epidural electrostimulation in four live rats. The algorithm was tasked with maximizing the amplitude of evoked potentials in the rats' left tibialis anterior muscle. These experiments show that the algorithm is capable of directing these experiments sensibly, finding effective stimuli in all four animals. Further, in direct competition with an expert human experimenter, the algorithm produced superior performance in terms of average reward and comparable or superior performance in terms of maximum reward. These results indicate that variants of GP-BUCB may be suitable for autonomously directing SCI therapy.

Binding Studies of Neuronal Nicotinic Acetylcholine Receptors Expressing Unnatural Amino Acids

Nicotinic acetylcholine receptors are pentameric ligand-gated ion channels mediating fast synaptic transmission throughout the peripheral and central nervous systems. They have been implicated in various processes related to cognitive functions, learning and memory, arousal, reward, motor control and analgesia. Therefore, these receptors present alluring potential therapeutic targets for the treatment of pain, epilepsy, Alzheimer’s disease, Parkinson’s disease, Tourette’s syndrome, schizophrenia, anxiety, depression and nicotine addiction. The work detailed in this thesis focuses on binding studies of neuronal nicotinic receptors and aims to further our knowledge of subtype specific functional and structural information.

Chapter 1 is an introductory chapter describing the structure and function of nicotinic acetylcholine receptors as well as the methodologies used for the dissertation work described herein. There are several different subtypes of nicotinic acetylcholine receptors known to date and the subtle variations in their structure and function present a challenging area of study. The work presented in this thesis deals specifically with the α4β2 subtype of nicotinic acetylcholine receptor. This subtype assembles into 2 closely related stoichiometries, termed throughout this thesis as A3B2 and A2B3 after their respective subunit composition. Chapter 2 describes binding studies of select nicotinic agonists on A3B2 and A2B3 receptors determined by whole-cell recording. Three key binding interactions, a cation-π and two hydrogen bonds, were probed for four nicotinic agonists, acetylcholine, nicotine, smoking cessation drug varenicline (Chantix®) and the related natural product cytisine.

Results from the binding studies presented in Chapter 2 show that the major difference in binding of these four agonists to A3B2 and A2B3 receptors lies in one of the two hydrogen bond interactions where the agonist acts as the hydrogen bond acceptor and the backbone NH of a conserved leucine residue in the receptor acts as the hydrogen bond donor. Chapter 3 focuses on studying the effect of modulating the hydrogen bond acceptor ability of nicotine and epibatidine on A3B2 receptor function determined by whole-cell recording. Finally, Chapter 4 describes single-channel recording studies of varenicline binding to A2B3 and A3B2 receptors.