<p> Within the United States, HIV is a growing epidemic that has important neuropsychological and functional consequences. Early detection and treatment of HIV-associated neurocognitive disorder (HAND) is associated with better outcomes. In major metropolitan areas such Los Angeles County, HIV disproportionately impacts the Latino community. For those individuals who are primarily Spanish-speakers, there may be limited access to comprehensive neuropsychological assessment in the preferred language. Consequently, self-reports of cognitive functioning are often relied on to help determine the presence of HAND. However, self-reports of cognitive decline may be influenced by factors such as depressed mood, variable motivation, and culture, raising important validity questions. To date, relatively few studies have focused on the combined use of Spanish-language, self-report measures of cognitive functioning and mood among primarily Spanish-speaking, HIV-positive individuals. The aim of this study was to explore the relationships among self-reported cognitive decline, neuropsychological functioning, and mood symptoms within this population. Archival data from a sample of 100 HIV+, primarily Spanish-speaking adults who participated in the parent study at a major medical center in Los Angeles were examined. Measures included Spanish-language versions of the Beck Depression Inventory, Cognitive Difficulties Scale-Patient Version, Medical Outcomes HIV Health Survey, and an acculturation measure. An array of neuropsychological measures was used to determine the presence of HAND. It was predicted that depressive symptoms would be positively associated with self-reported cognitive decline. This hypothesis was strongly supported by the results of correlational analysis. The results also showed that for individuals with HAND, the difference in BDI scores between participants with cognitive complaints and those without varied depending on whether the MOS-HIV or the CDS was used to assess cognitive complaints. The analyses revealed no significant impact of acculturation on the relationships among cognitive complaints, neuropsychological functioning, and depressive symptoms. The results of the present study highlight the complex relationship between neuropsychiatric and neuropsychological functioning in Spanish-speaking individuals infected with HIV. Clinical implications and limitations of the study are addressed. Future research that incorporates objective measures of neuropsychological functioning, the input of collateral informants, and self-report measures of mood and functional decline is recommended.</p>

<p> The thesis that perceptual experience is transparent has received considerable air-time in contemporary philosophy of mind and perception. Debate over its truth-value has reached an impasse. I diagnose this mired debate, and pursue a reformulation of the &ldquo;transparency thesis&rdquo; such that it can be more readily evaluated form the perspective of perceptual psychology and related subdisciplines. I argue that the empirical methods characteristic of these disciplines are important for evaluating the transparency thesis. Both historical and contemporary empirical results but substantial pressure on the transparency thesis.</p>

La maladie d’Alzheimer (MA) se caractérise par une incapacité des patients à évoquer consciemment les épisodes du passé. Les patients sont toutefois capables d’accéder à ces expériences par des voies résiduelles de récupération non consciente de l'information. L’objectif de cette thèse est de préciser la nature de ces capacités cognitives résiduelles et des facteurs qui permettent d’optimiser les performances de mémoire des patients. La première étude réalisée a la particularité de montrer que les processus de mémoire implicite sont préservés dans la MA, y compris après des intervalles de temps relativement importants allant jusqu’à trente minutes. D’autre part, les résultats d’une revue systématique des données de la littérature suggèrent que les conditions d’encodage favorisant la génération et l’élaboration sémantique du matériel permettraient d’optimiser les performances de mémoire implicite des patients. Enfin, une dernière étude porte sur les différences de capacités de mémoire de travail visuo-spatiale entre les hommes et les femmes dans la MA. La mise en évidence d’un maintien de l’avantage des hommes atteints de MA sur les femmes dans les capacités à manipuler activement l’information visuo-spatiale suggère que le sexe figure parmi les facteurs contribuant à moduler les manifestations cliniques de la maladie. Ainsi, malgré la sévérité des troubles cognitifs observés dans la MA, ces résultats illustrent l’existence de capacités cognitives résiduelles et de conditions susceptibles d’exploiter ces capacités de façon optimale. Ces résultats ont des applications potentielles, au sein des programmes de revalidation, afin d’améliorer la prise en charge des patients. / Alzheimer’s disease is characterised by severe memory deficits related to the inability to consciously recollect previously encountered information regarding place, people or events. However, some residual cognitive abilities could remain in Alzheimer’s disease allowing the patients to access these past experiences by non-conscious means of recovery. The main objective of this doctoral thesis is to investigate some residual cognitive abilities and the conditions that may optimise patients’ memory performances. The first study conducted provided results showing that implicit memory processes are preserved in Alzheimer’s disease including after quite long delays of about thirty minutes. Furthermore, through a meta-analysis including eighteen studies, we concluded that encoding conditions requiring generation or semantic elaboration processes are likely to optimise patients’ implicit memory processes. Lastly, we conducted a third study investigating the difference in visuo-spatial working memory abilities between men and women in Alzheimer’s disease. The results showing that male patients still present a greater ability than females to actively manipulate visuo-spatial information suggest that sex could figure among the numerous variables contributing to modulate the clinical manifestation of the disease. Despite the severity of the cognitive deterioration in Alzheimer’s disease, these studies illustrate the persistence of some cognitive abilities and also the conditions likely to optimise the enhancement of such residual abilities. These results may have potential clinical application dedicated to improve the cognitive rehabilitation of patients' memory deficits.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2019 / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 179-192). / From riding a bike to brushing our teeth, we learn many of our motor skills through trial and error. Many biologically based trial and error learning models depend on a teaching signal from dopamine neurons. Dopamine neurons increase their firing rates to signal outcomes that are better than expected and decrease their firing rates to signal outcomes that are worse than expected. This dopamine signal is thought to control learning by triggering synaptic changes in the basal ganglia. What are the origins of this dopaminergic teaching signal? How do synaptic changes in the basal ganglia lead to changes in behavior? In this thesis, I study these questions in a model of skill learning - the songbird. In the first part of my thesis, I develop a computational model of song learning. This model incorporates a dopaminergic reinforcement signal in VTA and dopamine-dependent synaptic plasticity in the singing-related part of the basal ganglia. / I demonstrate that this model can provide explanations for a variety of experimental results from the literature. In the second part of my thesis, I investigate a potential source of the dopaminergic error signal in VTA. I performed the first recordings from one cortical input to VTA: the dorsal intermediate arcopallium (AId). Previous studies disagree on the role of Ald in behavior. Some studies argue that AId contributes vocal error information to VTA. Other studies suggest that AId is not involved in the computation of error signals, but is instead responsible for controlling head and body movements. I directly tested these hypotheses by recording single neurons in AId during singing and during natural movements. My results support a motor role for AId - AId neurons had highly significant changes in activity during head and body movements. Meanwhile, following vocal errors Aid neurons had small but marginally significant decrease in firing rate. / In a more detailed analysis, I developed an automated behavior classification algorithm to categorize zebra finch behavior and related these behavior classes to the activity of single units in Aid. My results support the hypothesis that AId is part of a general-purpose motor control network in the songbird brain. / by Michael E. Stetner. / Ph. D. / Ph.D. Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2019 / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 123-130). / Humans are remarkable in their ability to rapidly learn complex tasks from little experience. Recent successes in Al have produced algorithms that can perform complex tasks well in environments whose simple dynamics are known in advance, as well as models that can learn to perform expertly in unknown environments after a great amount of experience. Despite this, no current AI models are able to learn sufficiently rich and general representations so as to support rapid, human-level learning on new, complex, tasks. This thesis examines some of the epistemic practices, representations, and algorithms that we believe underlie humans' ability to quickly learn about their world and to deploy that understanding to achieve their aims. In particular, the thesis examines humans' ability to effectively query their environment for information that helps distinguish between competing hypotheses (Chapter 2); children's ability to use higher-level amodal features of data to match causes and effects (Chapter 3); and adult human rapid-learning abilities in artificial video-game environments (Chapter 4). The thesis culminates by presenting and testing a model, inspired by human inductive biases and epistemic practices, that learns to perform complex video-game tasks at human levels with human-level amounts of experience (Chapter 5). The model is an instantiation of a more general approach, Theory-Based Reinforcement Learning, which we believe can underlie the development of human-level agents that may eventually learn and act adaptively in the real world. / by Pedro A. Tsividis. / Ph. D. / Ph.D. Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2019 / Cataloged from PDF version of thesis. "Some pages in the original document contain text that runs off the edge of the page. See Appendix A - pages 162-171"--Disclaimer Notice page. / Includes bibliographical references (pages 147-159). / It is commonly assumed that there is a reliable one-to-one mapping between a certain configuration of facial movements and the specific emotional state that is supposedly signals. One common way to test this one-to-one hypothesis is to ask people to deliberately pose the facial configurations that they believe they use to express emotions. Participants are randomly sampled, without concern for their emotional expertise, and are given a single emotion word or a single, brief statement to describe each emotion category. They then deliberately pose the facial configuration that they believe they make when expressing instances of this category. Such studies routinely find that participants from different countries show moderate to strong evidence for a one-to-one mapping between an emotion category and a single facial configuration (its presumed facial expression). / In Study 1, we examined the facial configurations posed by emotion experts - famous actors who were provided with a diverse sample of richly described scenarios, full of context. Participants inferred the emotional meaning of the scenarios, which were then grouped into categories. Systematic coding of the facial poses for each emotion category revealed little evidence for the hypothesis that each category has a diagnostic facial expression. Instead, we observed a high degree of variability among expert's facial poses for any given emotion category, and little specificity for any pose. Furthermore, an unsupervised statistical analysis discovered 29 novel emotion categories with moderately consistent facial poses. In Study 2, participants were asked to infer the emotional meaning of each facial pose when presented alone, or when presented in the context of its eliciting scenario. / In fact, the majority of studies designed to test the one-to-one hypothesis ask people from various cultures to judge posed configurations of facial movements, such as a scowl (the proposed facial expression for anger), a frown (the proposed expression for sadness), and so on, on the assumption that these facial configurations, as universal expressions of emotional states, co-evolved with the ability to recognize and read them. These studies routinely show participants one facial configuration posed by multiple posers for each emotion category and observe variable findings, depending on the experimental method used. Our analyses indicated that participants's inferences about the emotional meaning of the facial poses were influenced more by their eliciting scenarios than by the physical morphology of the facial configurations. / These findings strongly replicate emerging evidence that the emotional meaning of any set of facial movements may be much more variable and context-dependent than hypothesized by the common one-to-one view which continues to influence the public understanding of emotion, and hence education, clinical practice, and applications in government and industry. Although more ecologically valid research on how people actually move their faces to express emotion is urgently needed, doing so was immensely difficult without the right tools that support the process of capturing facial data in real life, automatically processing these data, and finally supporting data verification and analysis. We developed a system of technological tools to support the investigations of facial movements during emotional episodes in naturalistic settings with the use of dynamic and longitudinal facial data. We then collected, pre-processed, verified and analyzed data from Youtube using our newly-developed tools. / In particular, we examined two talk show hosts and presented preliminary insights on the answers to questions that were previously very difficult to investigate. / by Tuan Le Mau. / Ph. D. / Ph.D. Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2019 / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 91-100). / Neural networks and probabilistic models have different and in many ways complementary strengths and weaknesses: neural networks are flexible and support efficient inference, but rely on large quantities of labeled training data. Probabilistic models can learn from fewer examples, but in many cases remain limited by time-consuming inference algorithms. Thus, both classes of models have drawbacks that both limit their engineering applications and prevent them from being fully satisfying as process models of human learning. This thesis aims to address this state of affairs from both directions, exploring case studies where we make neural networks that learn from less data, and in which we design more efficient inference procedures for generative models. First, we explore recurrent neural networks that learn list-processing procedures (sort, reverse, etc.), and show how ideas from type theory and programming language theory can be used to design a data augmentation scheme that enables effective learning from small datasets. Next, we show how error-driven proposal mechanisms can speed up stochastic search for generative model inversion, first developing a symbolic model for inferring Boolean functions and Horn clause theories, and then a general-purpose neural network model for doing inference in continuous domains such as inverse graphics. / by Owen Lewis. / Ph. D. / Ph.D. Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences

The purpose of this study was to explore adaptation through the manipulation of perceived task difficulty and self-efficacy to challenge the concepts postulated by the two-perception probabilistic concept of the adaptation phenomenon (TPPCA) conceptual framework. The TPPCA considers the sources of perceived task difficulty (δi) and self-efficacy (βv) as the core relationship that influences adaptation. Twenty-four participants were randomized into one of 4-order groups to manipulate the level of difficulty for a handgrip and putting task. Within each task, 3 separate difficulty levels were presented to each participant in a counterbalanced order. The order of tasks and difficulty levels was counterbalanced between each of the 4-order groups. The performers completed both tasks, at each of the 3 difficulty levels, to assess their δi and βv gap effect on motivations, affect, and performances. The perceptual gap between δi and βv envisioned in the TPPCA was partially confirmed in both the handgrip and putting tasks. Specifically, as the task difficulty level increased, βv [less than] δi resulted in increased arousal and decreased pleasantness, along with declined performance. There was no solid support that motivational adaptations were congruent with the TPPCA. The theoretical and practical implications of the study are discussed along with suggestions for future research. / A Thesis submitted to the Department of Educational Psychology and Learning Systems in partial fulfillment of the Master of Science. / Fall Semester 2015. / November 10, 2015. / Adaptation, Athletics, Performers, Self-efficacy, Sport psychology, Task difficulty perception / Includes bibliographical references. / Gershon Tenenbaum, Professor Directing Thesis; Graig Chow, Committee Member; Allan Jeong, Committee Member.

The benefits of exercise on cognitive functioning are well established. One population that especially benefits from exercise is older adults. Research has demonstrated that chronic exercise in older adults improves cognitive functioning; especially executive functioning. One limitation of the current literature is that researchers have almost exclusively relied on well-controlled laboratory tasks to assess cognition. Moreover, the effects of a single bout of exercise in older adults have received limited attention. The proposed study addresses these limitations by (1) introducing a more ecologically valid, real-life task relevant to the older population (i.e., driving), and (2) assessing the effects of an acute bout of aerobic exercise on driving performance and executive functioning. This study employed a randomized controlled design and compared the effects of 20min cycling at moderate intensity vs. sitting and watching driving videos on driving performance. Driving performance was measured with three different scenarios assessing variables such as decision making, driving errors, reaction time, and attention. On a subsequent session, all participants performed a submaximal fitness test. This fitness test served as exercise and executive functioning was assessed before and after this exercise by counterbalancing two commonly used measures of executive functions: The Trail Making Test (TMT) and the Stroop test. Non-significant effects of exercise were observed on driving performance across all three scenarios. These results might be explained in terms of differences in expectations, as the video control group had higher expectations, compared to the exercise group, for the effects of the intervention on driving performance. An additional possible explanation is that participants were experienced drivers and the driving task was not challenging enough to benefit from exercise. However, a significant effect of exercise on more traditional executive functions tasks (i.e., TMT and Stroop test) emerged. Participants had a better performance on the TMT and Stroop test after exercise compared to before exercise. These results demonstrate the difficulty of using a more ecologically valid task and challenges the transfer of the current laboratory results in exercise psychology to everyday life functioning. This study also highlights the importance of assessing expectations as a possible moderator of the effects of acute aerobic exercise on cognitive functioning. Future studies should examine other relevant ecologically valid tasks and insure similar expectations between experimental and control groups to further advance the knowledge base in the field. / A Dissertation submitted to the Department of Educational Psychology and Learning Systems in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Summer Semester 2017. / July 6, 2017. / acute exercise, driving, executive functions, older adults / Includes bibliographical references. / Gershon Tenenbaum, Professor Directing Dissertation; Lynn B. Panton, University Representative; Graig M. Chow, Committee Member; Jeannine Turner, Committee Member.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2014. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 211-220). / People can learn a new concept almost perfectly from just a single example, yet machine learning algorithms typically require hundreds or thousands of examples to perform similarly. People can also use their learned concepts in richer ways than conventional machine learning systems - for action, imagination, and explanation suggesting that concepts are far more than a set of features, exemplars, or rules, the most popular forms of representation in machine learning and traditional models of concept learning. For those interested in better understanding this human ability, or in closing the gap between humans and machines, the key computational questions are the same: How do people learn new concepts from just one or a few examples? And how do people learn such abstract, rich, and flexible representations? An even greater puzzle arises by putting these two questions together: How do people learn such rich concepts from just one or a few examples? This thesis investigates concept learning as a form of Bayesian program induction, where learning involves selecting a structured procedure that best generates the examples from a category. I introduce a computational framework that utilizes the principles of compositionality, causality, and learning-to-learn to learn good programs from just one or a handful of examples of a new concept. New conceptual representations can be learned compositionally from pieces of related concepts, where the pieces reflect real part structure in the underlying causal process that generates category examples. This approach is evaluated on a number of natural concept learning tasks where humans and machines can be compared side-by-side. Chapter 2 introduces a large-scale data set of novel, simple visual concepts for studying concept learning from sparse data. People were asked to produce new examples of over 1600 novel categories, revealing consistent structure in the generative programs that people used. Initial experiments also show that this structure is useful for one-shot classification. Chapter 3 introduces the computational framework called Hierarchical Bayesian Program Learning, and Chapters 4 and 5 compare humans and machines on six tasks that cover a range of natural conceptual abilities. On a challenging one-shot classification task, the computational model achieves human-level performance while also outperforming several recent deep learning models. Visual "Turing test" experiments were used to compare humans and machines on more creative conceptual abilities, including generating new category examples, predicting latent causal structure, generating new concepts from related concepts, and freely generating new concepts. In each case, fewer than twenty-five percent of judges could reliably distinguish the human behavior from the machine behavior, showing that the model can generalize in ways similar to human performance. A range of comparisons with lesioned models and alternative modeling frameworks reveal that three key ingredients - compositionality, causality, and learning-to-learn - contribute to performance in each of the six tasks. This conclusion is further supported by the results of Chapter 6, where a computational model using only two of these three principles was evaluated on the one-shot learning of new spoken words. Learning programs with these ingredients is a promising route towards more humanlike concept learning in machines. / by Brenden M. Lake. / Ph. D.