The behaviors generated by neural circuits are constrained by the connectivity pattern among the neurons involved. Determining this connectivity pattern for circuits involving more than a handful of neurons becomes infeasible for physiological approaches that measure how the membrane potential of one neuron is affected by currents elicited in another. On the other hand, determining connectivity by anatomically discovering synapses is difficult due to the complicated and intertwining arbors that neurons possess. One approach to unravel this knotty problem is to image serial thin sections of neural tissue with an electron microscope. In this thesis, I describe the first application of large scale serial electron microscopy to the ganglion of the medicinal leech, Hirudo verbana. The leech ganglion is an ideal preparation for this experiment as it is compact enough in size that it is feasible to collect images spanning an entire ganglion. Here, I discuss results we collected from two image volumes of leech tissue. One spans a small region of adult ganglion neuropil, while the other includes an entire ganglion belonging to a juvenile leech. In these volumes, I reconstruct three-dimensional representations of neuronal arbors and locate the synapses between them. In Chapter 2, I show that we can differentiate neurons on the basis of where synaptic input and output sites are distributed throughout their arbors. In Chapter 3, I show that we can locate the synapses between pairs of neurons previously known to be connected, and that we can discover new synapses anatomically that are then recovered physiologically. Together, these results demonstrate the potential that this “connectomics” approach has when applied to the already physiologically accessible leech ganglion.

Neural circuits represent and process information using large numbers of component neurons. In this thesis, I describe the current theories of how information is processed by nervous systems, biophysical models of the basic mechanisms of population coding, and experimental techniques and computational algorithms to collect and synthesize the data necessary to understand neural computation in simple nervous systems. The leech nervous system is an ideal system for study, because it is readily accessible and consists of core neural structure, the ganglion, built of only a few hundred neurons. Even though this system is simple compared to mammalian nervous systems, it is still remarkably complex. To understand this complexity and make sense of the patterns of neurons, large-scale recordings of neural activity are required. We have developed a new Voltage-Sensitive Dye to record from a significant fraction of the nervous system simultaneously during behavioral states. This type of large-scale data presents entirely new challenges to overcome, and we developed computational tools to visualize and stitch-together these large-scale recordings. By imaging from a ganglion in several animals and recording neural responses during several different behaviors, we have developed a system for scalable and rapid identification of dozens of individual neurons. With these tools and techniques, we have mapped out the activity of a significant fraction of the leech's nervous system and have identified dozens of novel cells. Many of these cells are part of two canonical networks in the leech nervous system: the swim and preparatory networks. We further show that the preparatory network is mediated by the S cell, and we use computationally guided electrophysiology to target and verify that the S cell drives the activity of other cells in the preparatory network. These tools enable us to study the nervous system at scale for the first time, and we have mapped out the roles of a significant fraction of the neurons during the production of behaviors. These are just the first steps necessary to build a complete picture of how leech neurons produce behavior and make decisions.

The ability to accurately determine when to perform actions is a fundamental function of the nervous system and vital to shaping behavioral responses that achieve there intended outcome. Fixed-interval reinforcement schedules require animals to respond following a specified interval duration in order to obtain a reward. When reinforcement trials are interleaved with non-rewarded, or probe, trials during training, animals develop peak press distributions in these omission trials around the reinforced time. This peak press distribution under omission conditions indicates animals can correctly start and stop responding in a manner according to when the reward outcome would be expected. The cortex and striatum have been canonically implicated in action timing and behavioral models have proposed the idea that action behavioral states during motor timing performance could play a role in the pacing of action with respect to time. In this dissertation, I describe a sensorimotor feedback mechanism in which modal cortical activation by action-derived sensory cues is utilized to shape response dynamics in a self-paced fixed-interval timing task. Acute deprivation of the action-cued sensory modality, but not other action-based senses, is sufficient to disrupt timing dynamics in trained animals. Staining for immediate early gene protein expression in animals that performed the motor timing task revealed active populations in a modal cortical region related to pressing. Using an activity-dependent labeling system that exploits the cFos promoter, action-triggered optical activation of these populations via channelrhodopsin, partially rescues the key features of learned action timing behavior under sensory deprivation. Finally, using a viral activity-dependent labeling strategy in combination with the retrograde adeno-associated virus serotype, I demonstrate a role of layer V, striatal-projecting populations in task performance also under a sensory deprived state. These data point toward a feedback component of motor timing control in which modal cortices and the basal ganglia transduce self-generated sensory cues to assist in performing complex motor timing patterns.

It is considered that excessive extracellular matrix (ECM) content, specifically an increase in collagen concentration, may be causing the disruption of normal muscle mechanics in disorders presenting muscular stiffness. A clinical example is cerebral palsy (CP), caused by a neurological pathology, that results in muscle spasticity, uncontrolled movements, and/or contractures. An example of excess ECM is also known as skeletal muscle fibrosis. Thus we used both cerebral palsy muscles and fibrotic mouse muscles as our models for muscle stiffness. Our aim was to elucidate the collagen environment in stiff muscles compared to control muscles, in order to find a functional relationship to stiffness. Collagen content was quantified via ELISA and was found that all of the four main stiffness collagen isoforms have a 2.46 ± 0.19 fold increase in CP. However, these increases are at ratios proportional to concentrations found in control. Further investigations on the structure of collagen tendrils in a fibrotic environment are currently underway utilizing a new imaging technique referred to as Serial Block Face Scanning Electron Microscopy (SBFSEM), which gives a 3D reconstruction of the ultrastructure. Preliminary data is showing a trend towards an increase in fibroblasts as the cause of the collagen increase in the fibrotic mouse model. More human model samples will have to be tested for further conclusions on collagen packing and fibroblast number. Bearing in mind that muscle function is highly correlated with the ECM network, these findings may suggest that increased stiffness in fibrosis could be due to irregular ECM remodeling.

Time is a fundamental dimension of decision-making. When to perform an action is often as important as what action to take, and thus our sense of time is essential for guiding everyday behavior. Our perception of time allows us to form temporal associations between events and to detect irregularities in our environment; it allows us to optimize our choices and anticipate future consequences. However, unlike other sensory modalities, our sense of time appears to be entirely self-generated, as if our brain possesses—as some researchers have supposed—an “internal clock.” We clearly have a sense of time, yet how time is tracked and encoded by the brain remains mysterious. Animal behavior demonstrates features of timing across many timescales, from milliseconds to months. This dissertation focuses on timing on the scale of seconds-to-minutes, most commonly known as interval timing. Basal ganglia circuits are essential for motor control, action selection, and reinforcement learning. However, numerous lines of evidence also suggest that the basal ganglia –in particular the dorsal striatum and nigrostriatal dopamine – play a central role in interval timing. Does the basal ganglia serve a motor-independent function during interval timing, or is its role in timing fundamentally intertwined with action? In animal models of interval timing, researchers widely observe the development of non-instrumental, collateral behaviors as animals learn to time under operant conditioning. This dissertation explores the idea that these collateral behaviors can act as a functional mechanism to support timekeeping. We suggest that the basal ganglia’s role in interval timing may indeed be tied to these collateral behaviors. Chapter 1 reviews modern conceptions of how interval timing can be categorized, as well as the lines of evidence suggesting a role for motor-related brain regions in interval timing. In Chapter 2, I discuss the peak-interval operant task used throughout our experiments, I provide an analysis of the emergent behavior, and finally suggest a metric by which to assess timing accuracy on a trial-by-trial basis. In Chapter 3, I describe our optogenetic methodology for disrupting collateral behavior by disrupting striatal activity, and I demonstrate how these behavioral disruptions subsequently affect temporal decisions. In Chapter 4, I disrupt collateral pressing behavior by optogenetically manipulating a brainstem motor output nucleus. I demonstrate that the effects of disrupting action in the brainstem result in similar timing deficits as does disrupting action via the dorsal striatum. In Chapter 5, I assess how stimulating dopamine neurons in the SNc affects timing performance, and validate our methodology and nigrostriatal dopamine release using fast-scan cyclic voltammetry. I demonstrate that dopaminergic stimulation in these experiments only affects timing behavior insofar as collateral pressing behavior is also disrupted.

The principal purpose of this work, jointly funded by the US Geological Survey, Biological Resources Division, and the California Department of Fish and Game, was to establish quantifiable baseline information on habitat associations and environmental variables that may be useful in predicting the presence or absence of a variety of birds and small mammals in coastal sage scrub of southern California.

The primary database consisted of four sets of data associated with up to 240 replicate points at a up to 22 coastal sage scrub sites in Riverside, Orange, and San Diego counties (not all points and sites were sampled in all years for all attributes).  For each point, we collected information on:  (1)  the species composition and structure of vegetation in the near vicinity of the point, (2) the landscape context of each point (for example, the proportion of urban land use within a 500-1000m radius), (3) the species of birds recorded at each point during spring and fall censuses in 1995, 1996, and 1997 (spring only), and (4)  the species and number of individuals of small mammal species recorded at each point during spring and fall live-trapping censuses in 1995 and 1996.  Most of the analyses focused on the habitat and landscape associations of individual species, and of communities.