Thesis (M.S.)--University of Wisconsin--Madison, 1969. / eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (Ph. D.)--Oregon Health & Science University, Department of Science & Engineering, August 2008. / Includes bibliographical references (leaves 98 - 106).

Thesis (Ph. D.)--University of Wisconsin--Madison, 1972. / Vita. Description based on print version record. Includes bibliographical references (leaves 59-62).

Thesis (Ph. D.)--University of Wisconsin--Madison, 1971. / Vita. Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1972. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

The Taylor-Spence Drive (D) theory was investigated by comparing performance of high anxiety (HA), medium anxiety (MA) and low anxiety (LA) Ss, as measured by the Children's Manifest Anxiety Scale, on the test list of both a response-equivalence paradigm (A-B, A-C) and a control paradigm (D-B, A-C). The Ss were 60 grade six boys. The paired-associate learning tasks were designed to detect the debilitating effects of associative-stage competition in the experimental group for HA, MA and LA Ss respectively. A two (experimental conditions) by three (anxiety levels) by six (repeated trials) analysis of variance was performed on the data. There is a significant difference in performance between experimental and control groups on the test list (A-C), p < .0005. There are several trends favourable to the Taylor-Spence D theory but chance factors could have been involved since none of the hypotheses generated from the theory reached the .05 significance level. The first favourable trend is that HA and MA Ss' performance tends to be superior to LA Ss' in the control group on the test list (A-C). Also, HA Ss' performance is inferior to LA Ss' in the experimental group on the test list (A-C) giving support to the interaction hypothesis. / Education, Faculty of / Graduate

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Animals have evolved sensory systems that afford innate and adaptive responses to stimuli in the environment. Innate behaviors are likely to be mediated by hardwired circuits that respond to invariant predictive cues over long periods of evolutionary time. However, most stimuli do not have innate value. Over the lifetime of an animal, learning provides a mechanism for animals to update the predictive value of cues through experience. Sensory systems must therefore generate neuronal representations that are able to acquire value through learning. A fundamental challenge in neuroscience is to understand how and where value is imposed in brain during learning. The olfactory system is an attractive sensory modality to study learning because the anatomical organization is concise in that there are relatively few synapses separating the sense organ from brain areas implicated in learning. Thus, the circuits for learned olfactory behaviors appear to be relatively shallow and therefore more experimentally accessible than other sensory systems. The goal of this thesis is to characterize the representation and function of neural circuits involved in olfactory associative learning. Odor perception is initiated by the binding of odors onto olfactory receptors expressed in the sensory epithelium. Each olfactory receptor neuron (ORN) expresses one of 1500 different receptor genes, the expression of which pushes the ORN to project with spatial specificity onto a defined loci within the olfactory bulb, the olfactory glomeruli. Therefore, each and every odor evokes a stereotyped map of glomerular activity in the bulb. The projection neurons of the olfactory bulb, mitral and tufted (M/T) cells, send axons to higher brain areas, including a significant input to the primary olfactory cortex, the piriform cortex. Axons from M/T cells project diffusely to the piriform without apparent spatial preference; as a consequence, the spatial order of the bulb is discarded in the piriform. In agreement with anatomical data, electrophysiological and optical imaging studies also demonstrate that individual odorants activate sparse subsets of neurons across the piriform without any spatial order. Moreover, individual piriform neurons exhibit discontinuous receptive fields that defy chemical or perceptual categorization. These observations suggests that piriform neurons receive random subsets of glomerular input. Therefore, odor representations in piriform are unlikely to be hardwired to drive specific behaviors. Rather, this model suggests that value must be imposed upon the piriform through learning. Indeed, the piriform has been shown to be both sufficient and necessary for aversive olfactory learning without affecting innate odor responses. However, how value is imposed on odor representations in the piriform and downstream associational areas remain largely unknown. We first developed a strategy to track neural activity in a population of neurons across multiple days in deep brain areas using 2-photon endoscopic imaging. This allowed us to assay changes in neural responses to odors during learning in piriform and in downstream associative areas. Using this technique, we first observe that piriform odor responses are unaffected by learning, so learning must therefore impose discernable changes in neural activity downstream of piriform. Piriform projects to multiple downstream areas that are implicated in appetitive associative learning, such as the orbitofrontal cortex (OFC). Imaging of neural activity in the OFC reveal that OFC neurons acquire strong responses to conditioned odors (CS+) during learning. Moreover, multiple and distinct CS+ odors activatethe same population of OFC neurons, and these responses are gated by context and internal state. Together, our imaging data shows that an external and sensory representation in the piriform is transformed into an internal and cognitive representation of value in the OFC. Moreover, we found that optogenetic silencing of the OFC impaired the ability of mice to acquire learned associations. Therefore, the robust representation of expected value of the odor cues is necessary for the formation of appetitive associations. We made an important observation: once the task has been learned with a set of odors, the OFC representation decays after learning has plateaued and remains silent even when mice encounter novel odors they haven’t previously experienced. Moreover, silencing the OFC when it was not actively engaged during the subsequent learning of new odors had no effect on learning. These sets of imaging and silencing experiments reveal that the OFC is only important during initial learning; once task structure has been acquired, it is no longer needed. Task performance after initial task acquisition must therefore be accommodated by other brain regions that can store the learned association for long durations. We therefore searched for other brain regions that held learned associations long-term. In the medial prefrontal cortex (mPFC), we observe that the learned representation persists throughout the entire course of training. Unlike the OFC, not only does this representation encode the positive expected value of CS+ odors, it also encodes the negative expected value of CS- odors in a non-overlapping ensemble of neurons. We further show through optogenetic silencing that this representation is necessary for task performance after the task structure has already been acquired. Therefore, while the OFC representation is required for initial task acquisition, the mPFC representation is required for subsequent appetitive learning and performance. Why would a learned representation vanish in the OFC and betransfered elsewhere? We hypothesize that the brain may allocate a portion of its real estate to be a cognitive playground where experimentation and hypothesis testing takes place. Once this area solves a task, it may unload what it has learned to storage units located elsewhere to free up space to learn new tasks. We further imaged another associative area, the basolateral amygdala (BLA), and found a representation of positive value that appears to be generated from a Hebbian learning mechanism. However, the silencing of this representation during learning had no effect. This suggests that while multiple and distributed brain areas encode cues that predict the reward, not all may be necessary for the learning process or for task performance. In summary, we have described a series of experiments that map the representation and function of different associational areas that underlie learning. The data and the techniques employed have the potential to significantly advance the understanding of learned behavior.

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