Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 1993. / Includes bibliographical references (leaves 257-263). / by Michael Thomas Ullman. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 1989. / Includes bibliographical references (leaves 85-90). / by Kyle R. Cave. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 1995. / Includes bibliographical references (leaves 156-163). / by William Brandon Snyder. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 1996. / Includes bibliographical references (leaves 131-147). / by Hemai Bharati Parthasarathy. / Ph.D.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 1998. / Includes bibliographical references (leaves 82-86). / by Susanna Tsivkin. / S.M.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2010. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 117-126). / Bayesian Decision Theory describes optimal methods for combining sparse, noisy data with prior knowledge to build models of an uncertain world and to use those models to plan actions and make novel decisions. Bayesian computational models correctly predict aspects of human behavior in cognitive domains ranging from perception to motor control and language. However the predictive success of Bayesian models of cognition has highlighted long-standing challenges in bridging the computational and process levels of cognition. First, the computations required for exact Bayesian inference are incommensurate with the limited resources available to cognition (e.g., computational speed; and memory). Second, Bayesian models describe computations but not the processes that carry out these computations and fail to accurately predict human behavior under conditions of cognitive load or deficits. I suggest a resolution to both challenges: The mind approximates Bayesian inference by sampling. Experiments across a wide range of cognition demonstrate Monte-Carlo-like behavior by human observers; moreover, models of cognition based on specific Monte Carlo algorithms can describe previously elusive cognitive phenomena such as perceptual bistability and probability matching. When sampling algorithms are treated as process models of human cognition, the computational and process levels can be modeled jointly to shed light on new and old cognitive phenomena.. / by Edward Vul. / 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. / From yeast to humans, the fusion of vesicles with target membranes is driven by the formation of a parallel four-helix bundle of SNARE proteins that are present on both the vesicular (v-SNAREs) and target plasma membranes (t-SNAREs). The full zippering of this bundle is thought to provide the driving force for membrane fusion. At synapses, vesicle fusion is exquisitely regulated by Ca2+ such that neurotransmitter release can occur within 1 ms of an action potential reaching the presynaptic terminal. This feat implies the presence of both a Ca2+ sensor and a fusion clamp that prevents vesicles from fusing in the absence of Ca2+. The presynaptic Ca2+ sensor for synchronous vesicle release is widely accepted to be Synaptotagmin-1 (Syt1), and there is growing evidence that Complexin (Cpx), which binds to the SNARE complex with high affinity and 1:1 stoichiometry, can act as a vesicle fusion clamp. As suggested by its name, however, Cpx appears to play a more complex role in vesicle release, carrying out different functions in spontaneous vs. evoked fusion events. Here we show the Drosophila express at least two Cpx isoforms that differ in the C-terminus (Cpx7A and Cpx7B) and can be further regulated by RNA editing and phosphorylation. These isoforms show different effects on spontaneous vs. evoked neurotransmitter release, with Cpx7A being a better fusion clamp and Cpx7B being a better fusion promoter. In addition, these isoforms have different effects on synaptic growth, which may be linked to their effects on synaptic physiology. / by Lauren Kaye Buhl. / Ph.D.

Thesis: S.M., Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2015. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 50-56). / To optimize survival, organisms must be able to learn contingencies between external stimuli and rewards and appropriately respond to these associations. Deficits in reward-related learning or reward-seeking are thought to occur in a host of psychopathologies, including depression (Drevets, 2001), eating disorders (Wagner et al., 2007), and substance abuse (Wrase et al., 2007), such that improved understanding of reward processing could potentially aid in the development of therapies. Two neural regions, the basolateral amygdala (BLA) and lateral hypothalamus (LH), are both implicated in reward processing (Adamantidis et al., 2007; Anand and Brobeck, 1951; Brobeck, 1946; Gutierrez et al., 2011; Hoebel and Teitelbaum, 1962; Kempadoo et al., 2013; Margules and Olds, 1962; Muramoto et al., 1993; Sakurai, 2007; Schoenbaum et al., 1998; Tye and Janak, 2007; Tye et al., 2008, 2010), but the role of the BLA's projection to LH in appetitive conditioning and reward-seeking remains unclear. Through the use of optogenetic techniques in mice, I have investigated the influence of LH-projecting BLA neurons upon motivated behavioral responding, which has indicated that the projection may support intracranial self-stimulation (ICSS). Further experiments with in vivo extracellular electrophysiological recordings from LH-projecting BLA neurons may also shed light on the encoding properties of these neurons during appetitive learning. / by Christine Eckhardt. / S.M.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2005. / Includes bibliographical references. / Faces each have distinct pigmentation as well as shape, which suggests that both cues may play a role in the perception of faces. However, there is a common implicit assumption that pigmentation cues are relatively unimportant, and so the role pigmentation plays in face perception has gone largely unexplored. This thesis is a systematic investigation of the role of pigmentation in face recognition, facial sex classification, and facial attractiveness. The present studies present evidence that pigmentation cues are in fact quite important for face perception. For face recognition, pigmentation cues are about as important as shape cues. Male and female faces differ consistently in their pigmentation, with female faces having more luminance contrast between the eyes and lips and the rest of the face than do male faces. This sex difference in pigmentation is used as a cue for judgments of facial sex classification and facial attractiveness. Together, these results implicate an important role for pigmentation, and open new avenues of research in the perception of faces. / by Richard Russell. / 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. / A key requirement from cognitive models of language comprehension is that they specify the distinct computational mechanisms that are engaged in language processing and the division of linguistic labor across them. Here, I address this requirement from a cognitive neuroscience perspective by employing functional MRI to study the neural implementation of comprehension processes. My experimental approach, unprecedented in studies of language, combines available methods to simultaneously achieve (i) increased functional resolution, via localization of functional brain regions at the single-participant level; (ii) ecological validity, through datadriven, model-free paradigms using naturalistic stimuli; and (iii) statistical rigor, by explicit comparison of functional profiles across regions. Using this approach, I first contrast two cortical networks engaged in comprehension: one, the "high-level language network", is selectively recruited by linguistic processing but not by other cognitive functions; another, the "multiple-demand network", is recruited across diverse cognitive tasks, both linguistic and non-linguistic. I show that, during naturalistic cognition, each network shows high synchronization amongst its constituent regions, whereas regions across the two networks are functionally dissociated. Thus, these two systems likely play distinct roles in comprehension, which I then characterize by demonstrating that the language network closely tracks linguistic input whereas the multiple-demand network does not. This finding critically constrains the possible contributions of the multiple-demand system to comprehension. Next, I focus on the high-level language network and examine two current hypotheses about its internal structure. In one study, I find that activity elicited by syntactic processing is not localized to focal language regions but is instead distributed throughout the network, suggesting that syntax is cognitively inseparable from other aspects of language. In another study, I estimate the timescales over which different language regions integrate linguistic information and find that they share a common profile of temporal integration. Therefore, the topographic division of linguistic labor across this network is not organized along distinct integration timescales. Collectively, these results account for crucial inconsistencies in the literature and challenge common theoretical views. By characterizing the fundamental functional architecture of comprehension mechanisms, these results provide novel insights into the ontology of linguistic mechanisms that give rise to human language. / by Idan Blank. / Ph. D.