Doctor of Philosophy

dissertationThe purpose of this dissertation research was to investigate whether there is an association between exposure to low to moderate levels of arsenic in drinking water in community water systems (CWSs) and small for gestational age birth (SGA), pregnancy-related hypertension, and/or stillbirth. The study included over 633,000 live births and stillbirths to Utah residents during 1989 to 2006 where the maternal addresses recorded on birth and fetal death certificates were within the boundaries of a CWS. Over 97% of the maternal addresses in each county were geocoded and then spatially linked to georeferenced data layers of 476 CWS service areas statewide and to elevation data. Water quality data collected for regulatory purposes were used to estimate annual average arsenic levels for each CWS; these values were assigned to the births and stillbirths based on the first trimester of the year of pregnancy and the CWS providing water to the maternal residence. Arsenic levels were less than 2.5 micrograms per liter (μg/L) for the majority of residences (73.8%); arsenic levels were greater than 10 μg/L at only 3.7% of the residences. There was a small but statistically significant association between arsenic concentration and SGA. Using <2.5 μg/L as the reference, the adjusted odds ratio (aOR) for SGA was 1.04, (95% confidence interval (CI) 1.00, 1.07) when arsenic levels were 5.1 to 9.9 μg/L (p-value 0.03), and aOR 1.07 (CI 1.03, 1.12) when levels were 10 μg/L or greater (p-value 0.002). At arsenic levels from 2.5 to 5 μg/L, there was a small, but not statistically significant (p-value 0.40), increase in SGA (aOR 1.01, CI 0.98, 1.04). Arsenic was not found to be associated with pregnancy-related hypertension, nor was there an association between low to moderate levels of arsenic in drinking water and stillbirth. An additional finding was that, compared with births at elevations less than 3,000 feet(ft), the frequency of SGA increased with every 1,000 ft increase in elevation to an aOR of 1.91 (CI 1.65, 2.22) for women residing above 6,000 ft

Predictive social perception: Towards a unifying framework from action observation to person knowledge

Action observation is central to human social interaction. It allows people to derive what mental states drive others' behaviour and coordinate (and compete) effectively with them. Although previous accounts have conceptualised this ability in terms of bottom-up (motoric or conceptual) matching processes, more recent evidence suggests that such mechanisms cannot account for the complexity and uncertainty of the sensory input, even in cases where computations should be much simpler (i.e., low-level vision). It has therefore been argued that perception in general, and social perception in particular, is better described as a process of top–down hypothesis testing. In such models, any assumption about others—their goals, attitudes, and beliefs—is translated into predictions of expected sensory input and compared with incoming stimulation. This allows perception and action to be based on these expectations or—in case of a mismatch—for one's prior assumptions to be revised until they are better aligned with the individual's behaviour. This article will give a (selective) review of recent research from experimental psychology and (social) neuroscience that supports such views, discuss the relevant underlying models, and current gaps in research. In particular, it will argue that much headway can be made when current research on predictive social perception is integrated with classic findings from social psychology, which have already shown striking effects of prior knowledge on the processing of other people's behaviour

Structural and effective connectivity reveals potential network-based influences on category-sensitive visual areas

Visual category perception is thought to depend on brain areas that respond specifically when certain categories are viewed. These category-sensitive areas are often assumed to be modules (with some degree of processing autonomy) and to act predominantly on feedforward visual input. This modular view can be complemented by a view that treats brain areas as elements within more complex networks and as influenced by network properties. This network-oriented viewpoint is emerging from studies using either diffusion tensor imaging to map structural connections or effective connectivity analyses to measure how their functional responses influence each other. This literature motivates several hypotheses that predict category-sensitive activity based on network properties. Large, long-range fiber bundles such as inferior fronto-occipital, arcuate and inferior longitudinal fasciculi are associated with behavioural recognition and could play crucial roles in conveying backward influences on visual cortex from anterior temporal and frontal areas. Such backward influences could support top-down functions such as visual search and emotion-based visual modulation. Within visual cortex itself, areas sensitive to different categories appear well-connected (e.g., face areas connect to object- and motion sensitive areas) and their responses can be predicted by backward modulation. Evidence supporting these propositions remains incomplete and underscores the need for better integration of DTI and functional imaging

Cognitive transforms in perception and memory

Visual perception seems to provide a direct and immediate view onto the outside world. In reality, it is an active and adaptive process. Cognitive factors, such as our prior knowledge and goals, transform the information streaming in from the retina to create a reconstruction of our environment tailored to our needs. The study of these cognitive influences on perception and their underlying mechanisms falls within the purview of visual cognition. If the principles gleaned from these studies can inform our understanding of cognition more generally, however, it is necessary to test if these principles generalize to domains beyond visual perception (and, if not, to understand if these principles can at least provide a useful basis for comparison and understanding). Towards that end, the work in this thesis examines how expectation and attention influence visual perception and additionally interrogates these same processes in the context of working memory. In the realm of expectation, we show that percepts reflect a weighted average of sensory information and prior knowledge, biasing percepts towards expected values. We find that these biases persist in working memory, accumulating over time to counteract memory noise. In the realm of attention, we find that, once attended, both percepts and memories are represented using radically different (i.e. orthogonal) patterns of neural activity relative to their unattended state. Furthermore, in this new post-attentional subspace, perceptual and mnemonic codes are reorganized in a way that allows task-relevant features to be decoded and task-irrelevant features to be abstracted away. This transform may selectively gate the influence of perceptual and mnemonic representations on other cognitive processes. In both the case of expectation and attention, these common principles uniting perception and memory coexist with key differences. For instance, learning modifies the influence of expectations on memory faster than on perception, and attention biases competition between perceptual but not mnemonic representations. Together, these results suggest that while the cognitive transforms observed in perception do generalize to other domains, they may be actualized by distinct mechanisms

Predictive feedback and conscious visual experience

The human brain continuously generates predictions about the environment based on learned regularities in the world. These predictions actively and efficiently facilitate the interpretation of incoming sensory information. We review evidence that, as a result of this facilitation, predictions directly influence conscious experience. Specifically, we propose that predictions enable rapid generation of conscious percepts and bias the contents of awareness in situations of uncertainty. The possible neural mechanisms underlying this facilitation are discussed

Internal valence modulates the speed of object recognition

Brain regions that process affect are strongly connected with visual regions, but the functional consequences of this structural organization have been relatively unexplored. How does the momentary affect of an observer influence perception? We induced either pleasant or unpleasant affect in participants and then recorded their neural activity using magnetoencephalography while they completed an object recognition task. We hypothesized, and found, that affect influenced the speed of object recognition by modulating the speed and amplitude of evoked responses in occipitotemporal cortex and regions important for representing affect. Furthermore, affect modulated functional interactions between affective and perceptual regions early during perceptual processing. These findings indicate that affect can serve as an important contextual influence on object recognition processes

Delay-period activity in frontal, parietal, and occipital cortex tracks noise and biases in visual working memory.

Working memory is imprecise, and these imprecisions can be explained by the combined influences of random diffusive error and systematic drift toward a set of stable states ("attractors"). However, the neural correlates of diffusion and drift remain unknown. Here, we investigated how delay-period activity in frontal and parietal cortex, which is known to correlate with the decline in behavioral memory precision observed with increasing memory load, might relate to diffusion and drift. We analyzed data from an existing experiment in which subjects performed delayed recall for line orientation, at different loads, during functional magnetic resonance imaging (fMRI) scanning. To quantify the influence of drift and diffusion, we modeled subjects' behavior using a discrete attractor model and calculated within-subject correlation between frontal and parietal delay-period activity and whole-trial estimates of drift and diffusion. We found that although increases in frontal and parietal activity were associated with increases in both diffusion and drift, diffusion explained the most variance in frontal and parietal delay-period activity. In comparison, a subsequent whole-brain regression analysis showed that drift, rather than diffusion, explained the most variance in delay-period activity in lateral occipital cortex. These results are consistent with a model of the differential recruitment of general frontoparietal mechanisms in response to diffusive noise and of stimulus-specific biases in occipital cortex