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Phonological working memory (PWM) is the mind's capacity for maintaining and manipulating representations of the sounds important for speech when they are not actively being perceived. It is believed to be a critical component supporting typical language acquisition and vocabulary development, as well as second-language learning. Despite the success of the theoretical framework traditionally used to conceptualize PWM, consensus on its instantiation in the brain remains elusive. In this thesis, I will describe a series of studies designed to interrogate the functionality of the brain regions supporting PWM. In Chapter 1, we compare activation patterns from a canonical PWM task, nonword repetition, to nonword discrimination, a matched task designed to engage core PWM functions, but for the purpose of comparing stimuli, not repeating them. We replicate the findings that PWM during nonword repetition engages speech cortices and show that these cortical regions are also reliably engaged in nonword discrimination, in individual subjects. In Chapter 2, we directly assess the extent to which conjunctive activation between language and working memory paradigms can be interpreted as shared functionality. We find that despite the ability to localize regions in which the majority of subjects show conjunction of significant activation between tasks, the pattern similarity between tasks within those regions vary. We find no pattern similarity between language and spatial working memory, and marginal similarities between language and verbal working memory. Verbal working memory and spatial working memory conjunctions localize a similar network to the multiple demand network and find highly similar patterns of activation in these regions across working memory tasks. Finally, in Chapter 3, we investigate the functional properties of brain areas supporting PWM by comparing activation between nonword repetition, language, verbal working memory, and spatial working memory tasks. We find that PWM shares support with areas involved in spoken language perception, as well as regions engaged by working memory tasks that lie outside of the core language network. Taken together, these studies give a detailed account of the neural bases of PWM, through the lens of shared functionality between this capacity, language, and other domains of working memory.

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The brain is highly efficient at processing complicated patterns of information, filtering ambiguous input it receives from the senses. Competition between these representations is regulated by multiple mechanisms, together forming a coherent percept of our environment. One approach to regulating incoming sensory information is the recruitment of a canonical neural computation: divisive normalization. Another approach to further steer processing towards behaviorally relevant goals is by means of cognitive influences. In this project I examined the degree to which cognitive processes interact with normalization to shape human visual perception. First, a set of fMRI experiments (Exps 1-3: n=6) examined the hypothesis that attention-driven gain modulation within human visual cortex is dependent on the magnitude of normalization. Leveraging the fact that normalization is modulated by similarity of visual features, my results illustrated that attentional modulation of BOLD responses is larger when visual cortex is put under stronger normalization. These results suggest that the degree to which a subpopulation exhibits normalization plays a role in dictating its potential for attentional benefits. Second, I examined how attention modulates visual population responses (n=7). Neurons within visual cortex exhibit a well-characterized relationship between stimulus intensity and the neural response, known as a contrast response function. While animal and psychophysical studies suggest that attention improves visual processing by multiplicatively increasing the gain of the contrast response, human fMRI studies instead report additive attentional effects, which act independently of stimulus contrast. Consistent with prior work, I demonstrated using a fMRI model-based analysis that attentional modulation indeed appears additive within early visual cortex. Lastly, I examined whether perceptual and memory representations are distinct from one another (Exp 1: n=12, Exp 2: n=10). A prevailing theory posits that the retention of visual memories involves maintenance of information within visual cortices. I tested the degree to which representations in visual memory undergo contrast normalization, by leveraging a classic demonstration: center- surround suppression. I obtained psychophysical measurements of perceived contrast and found robust normalization in perception, yet no signature of normalization occurring between visual memory representations. Taken together, this work helps unravel the underlying neural mechanisms by which cognitive influences shape visual perception.

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This dissertation discusses the effects of dyslexia on reading behavior and cognition. It does so by first outlining the overall incidence of dyslexia, providing current definitions, giving a history of scientific inquiry and discussing relevant contemporary research. Thirteen different analyses are then discussed (ten a priori and three post-hoc). Individuals with dyslexia were found to have increased fixation duration, first run dwell time, total dwell time, and refixation probability. The dyslexia group was also highly sensitive to lexical predictability. Within the reading network, the BOLD response was depressed in dyslexia during reading in the following regions: the left medial and inferior temporal gyrus, the left temporal pole, the right cerebellum, right occipital gyrus and the right parahippocampal gyrus. A second regions of interest analysis in the reading network revealed dyslexia was associated with a depressed BOLD response to lexical predictability in the following regions: left supplementary motor area, posterior middle frontal gyrus, and the left temporal pole. A regions of interest analysis in the oculomotor network revealed a depressed BOLD response in the following regions during reading: the left parietal eye fields and the cerebellum. One oculomotor region had a depressed BOLD response to lexical predictability due to dyslexia: the left frontal eye fields. This sensitivity to lexical predictability and depression in the BOLD response is suggestive of reduced input into higher cortical areas. Future study should be focused on finding the common origin of this bottom-up deficit.

Social anxiety disorder (SAD) interferes with everyday life. It can, for instance, hinder careers, relationships, and leisure time. It is a common anxiety disorder that was neglected for decades. SAD individuals crave and fear social interactions simultaneously, leading to isolation in our highly social world. Therefore, research surrounding these kinds of disorders is essential. This systematic review has focused on the neural aspects and differences between SAD and healthy controls surrounding amygdala activation and connectivity. Functional magnetic resonance imaging (fMRI) studies conducted using social and emotional tasks were included. Findings include increased amygdala activation to fearful faces and words and a positive correlation between amygdala activation and symptom severity. Further, deficits in emotion regulation and a finding of gradual habituation have been found in SAD compared to healthy controls. Some limitations to this research are the small sample sizes used in the included articles and the use of both SAD and individuals with generalized SAD. The study is essential to assess future questions and directions regarding diagnosis, treatment, and understanding of SAD.

Magnetic resonance imaging of neuronal activity is one of the most promising techniques in modern psychiatric research. While clear functional links with phenotypic variables have been established and detailed networks of activity robustly identified, fMRI scans have not yet yielded the robust biomarkers of psychiatric diseases, such as schizophrenia, which would allow for their use as a clinical diagnostic tool. One possible explanation for the lack of such results is that neural activity is highly non- stationary, whereas most analysis techniques assume that signal properties remain relatively static over time. Time-frequency analysis is a family of analytic techniques which do not assume that data is stationary, and thus is well suited to the analysis of neural time series. Resting state fMRI scans from a publicly available dataset were decomposed using the Wavelet transform and Hilbert Huang Transform, techniques from time-frequency analysis. The results of these processes were then used as the basis for calculating several properties of the fMRI signal within each voxel. The wavelet transform, a simpler technique, generated measures which showed broad differences between patients with schizophrenia and healthy controls but failed to reach statistical significance in the vast majority of situations. The Hilbert Huang transform, in contrast, showed significant increases in certain measures throughout areas associated with sensory processing, dysfunction in which is a symptom of schizophrenia. These results support the use of analysis techniques able to capture the nonstationarities in neural data and encourages the use of such techniques to explore the nature of the neural differences in psychiatric disorders.

In many regions worldwide, older adults now form the fastest growing portion of the population. As such, aging research has seen tremendous growth in recent years, with a focus on identifying early biomarkers of age-related disease. However, crucial to understanding age-related disease is to identify what constitutes normal brain aging, and the life-course factors associated with positive outcomes in later life. In support of this goal, the current dissertation is comprised of three manuscripts that aim to investigate the functional and structural correlates of normal aging in a sample of community-dwelling younger and older adults, from both a multimodal and multi-analysis perspective. Study 1: The first study examined how cumulative cardiovascular risk and self-reported levels of physical, social, and cognitive activity are associated with differences in hippocampal volumes in early and later adulthood. Results indicated that greater cumulative cardiovascular risk was associated with smaller hippocampal volumes across age cohorts. Moreover, a negative association found between frequency of social activities and bilateral hippocampal volumes in older adults, suggesting that social activities with a low cognitive load may not be beneficial to structural brain outcomes in older age. Study 2: This study employed novel advances in functional magnetic resonance imaging (fMRI) to study fluctuations in the blood-oxygen-level dependent (BOLD) signal in relation to age and markers of brain health. Specifically, the study examined the relationship between resting-state BOLD variability and markers of both vascular health and lifestyle activity levels. Results indicated that resting-state BOLD variability is increased in older relative to younger adults. The findings also suggest that the association between BOLD variability and lifestyle activity levels may differ depending on age. Study 3: The final study aimed to further investigate the origins of the BOLD variability signal by examining the feasibility of combining functional near infrared spectroscopy (fNIRS) with fMRI brain signal fluctuation data. In addition to providing proof of concept of combining fNIRS hemoglobin metrics with fMRI BOLD variability maps, the results of this study also indicate that the patterns of regional association between resting hemoglobin concentrations and BOLD fluctuations may vary according to age cohort. Together, the three studies comprising this dissertation illustrate the value of adopting a multimodal, life-course perspective in the study of normal aging. These findings also support increasing evidence of a relationship between the BOLD variability signal and age. Given the limitations of cross-sectional designs for demonstrating change over time, longitudinal investigations with larger sample sizes across multiple age groups are needed to further the development of public health measures aimed at promoting successful aging from early adulthood. / Graduate / 2022-12-08

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