Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 1996. / Includes bibliographical references (leaves 160-166). / by Eric Peter Loeb. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2010. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references. / One of the great puzzles of vision science is how, over the course of development, the complex visual array comprising many regions of different colors and luminances is transformed into a sophisticated and meaningful constellation of objects. Gestaltists describe some of the rules that seem to govern a mature parsing of the visual scene, but where do these rules come from? Are they innate--endowed by evolution, or do they come somehow from visual experience? The answer to this question is usually confounded in infant studies as the timelines of maturation and experience are inextricably linked. Here, we describe studies with a special population of late--onset vision patients, which suggest a distinction between those capabilities available innately and those which are crafted via learning from the visual environment. We conclude with a hypothesis, based on these findings and other evidence, that early-available common fate motion cues provide a level of perceptual organization which forms the basis for the learning of subsequent cues. / by Yuri Ostrovsky. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2011. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 179-191). / This thesis develops the hypothesis that key aspects of learning and development can be understood as rational statistical inferences over a compositionally structured representation system, a language of thought (LOT) (Fodor, 1975). In this setup, learners have access to a set of primitive functions and learning consists of composing these functions in order to created structured representations of complex concepts. We present an inductive statistical model over these representations that formalizes an optimal Bayesian trade-off between representational complexity and fit to the observed data. This approach is first applied to the case of number-word acquisition, for which statistical learning with a LOT can explain key developmental patterns and resolve philosophically troublesome aspects of previous developmental theories. Second, we show how these same formal tools can be applied to children's acquisition of quantifiers. The model explains how children may achieve adult competence with quantifiers' literal meanings and presuppositions, and predicts several of the most-studied errors children make while learning these words. Finally, we model adult patterns of generalization in a massive concept-learning experiment. These results provide evidence for LOT models over other approaches and provide quantitative evaluation of different particular LOTs. / by Steven Thomas Piantadosi. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 1995. / Includes bibliographical references. / by Bard J. Geesaman. / Ph.D.

Thesis: S.M., Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 24-27). / Stressors are known to impact eating behaviors. However, recapitulating the intricate interplay between chronic stress and aberrant human eating patterns in an animal model remains a challenge. Notably, binge eating, a diagnostic feature associated with many types of eating abnormalities, particularly pertains to the binge eating disorder. To more closely investigate the etiology underlying eating behavior-associated maladaptation, the present study provides a novel and ethologically relevant animal model based on predatory odor stress. My data show that chronic stress in female mice selectively increases consumption of highly palatable, but not the regular, diet, when it is presented during a limited time following stress exposure. In addition, the nucleus accumbens (NAc), a key component in the neural circuitry of reward, is also an established neural substrate susceptible to the effects of stress. Given the cellular complexity in NAc, identifying the neuronal subtypes that are selectively involved in chronic stress-elicited physiological and behavioral alterations will provide grounds for further understanding in the underlying cellular changes. Because deficits in the somatostatin (SOM) neurons have been implicated in mice exhibiting traits of anxiety and depression, this neuron subtype may play an important role in modulating negative behavioral emotionality. Here I report an abundance of somatostatin neurons, majority of which are located in the rostral-ventral region of the NAc and are activated by chronic stress exposure. Together, these results provide the first line of evidence in linking chronic stress and the somatostatin neurons within the NAc to binge eating. Further fluorescent labeling quantification and cell-type-specific optogenetic manipulation will be needed to further delineate the role of SOM neurons in orchestrating the inhibitory components of stress-modulated reward circuitry. / by Elizabeth Liu. / S.M.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 1989. / Includes bibliographical references (leaves 80-83). / by Steven M. Drucker. / M.S.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, February 2005. / Includes bibliographical references (leaves [143]-148). / (cont.) baseline, and that some coherence-based approaches best predict the human data. However, coherence-based algorithms that operate on trees did not perform as well as coherence-based algorithms that operate on more general graphs. It is suggested that that might in part be due to the fact that more general graphs are more descriptively adequate than trees for representing discourse coherence. / The general topic of this thesis is coherence in natural language, where coherence refers to informational relations that hold between segments of a discourse. More specifically, this thesis aims to (1) develop criteria for a descriptively adequate data structure for representing discourse coherence; (2) test the influence of coherence on psycholinguistic processes, in particular, pronoun processing; (3) test the influence of coherence on the relative saliency of discourse segments in a text. In order to address the first aim, a method was developed for hand-annotating a database of naturally occurring texts for coherence structures. The thus obtained database of coherence structures was used to test assumptions about descriptively adequate data structures for representing discourse coherence. In particular, the assumption that discourse coherence can be represented in trees was tested, and results suggest that more powerful data structures than trees are needed (labeled chain graphs, where the labels represent types of coherence relations, and an ordered array of nodes represents the temporal order of discourse segments in a text). The second aim was addressed in an on-line comprehension and an off-line production experiment. Results from both experiments suggest that only a coherence-based account predicted the full range of observed data. In that account, the observed preferences in pronoun processing are not a result of pronoun-specific mechanisms, but a byproduct of more general cognitive mechanisms that operate when establishing coherence. In order to address the third aim, layout-, word-, and coherence-based approaches to discourse segment ranking were compared to human rankings. Results suggest that word-based accounts provide a strong / by Florian Wolf. / Ph.D.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 131-143). / By kindergarten, our knowledge of agents has unfolded into a powerful intuitive theory that enables us to thrive in our social world. In this thesis I propose that children build their commonsense psychology around a basic assumption that agents choose goals and actions by quantifying, comparing, and maximizing utilities. This naive utility calculus generalizes infants' expectation that agents navigate efficiently, and captures much of the rich social reasoning we engage in from early childhood. I explore this theory in a series of experiments looking at children's ability to infer costs and rewards given partial information, their reasoning about knowledgeable versus ignorant agents, and their reasoning about the moral status of agents. Moreover, a formal model of this theory, embedded in a Bayesian framework, predicts with quantitative accuracy how humans make cost and reward attributions. / by Jose Julian Jara-Ettinger. / Ph. D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 1995. / Includes bibliographical references (p. 153-158). / by Gavin Huntley-Fenner. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 1995. / Includes bibliographical references. / by Louis J. Toth. / Ph.D.