Adolescence is a sensitive period of life shaped by environmental factors, including socioeconomic status (SES) and early adversity. While previous studies have linked early adversity to cognitive and physical outcomes, it remains unclear how these effects vary by income level or whether physical maturation mediates the influence of early adversity on cognition. This thesis investigates how early adversity—specifically prenatal stress and early life stress (ELS)—impacts adolescent cognitive development across income groups and explores whether physical development mediates these relationships. Using longitudinal data from the Adolescent Brain Cognitive Development (ABCD) Study, I compare cognitive and physical development between high- and low-income adolescents and apply linear mixed-effects models and mediation analyses to examine potential pathways. First, I show that high-income adolescents undergo earlier cognitive development, while low-income adolescents experience earlier physical development. Then, I demonstrate that both prenatal stress and ELS are significantly associated with cognitive and physical development in the high-income group, whereas only prenatal stress is significantly associated in the low-income group. This indicates that among low-income adolescents, the influence of ELS may be overshadowed by broader adversities prevalent in low-income environments. Expanding on this finding, I reveal that prenatal stress exerts a stronger influence than ELS on slowing cognitive development and accelerating physical development in the high-income group. Finally, I show that the timing of physical maturation does not mediate the relationship between early adversity and cognitive outcomes, suggesting that the stress acceleration hypothesis cannot be extended to cognitive development. I conclude by proposing that alternative mechanisms—such as emotional development—may better explain how prenatal stress and ELS shape cognitive trajectories, implying the need for interventions aimed at mitigating the long-term effects of early adversity on adolescent cognitive development.

Artificial neural networks (ANNs), particularly large language models like GPT-2 and BERT, have demonstrated remarkable capabilities in language comprehension and generation, prompting questions about the extent to which their computational processes resemble those of biological neural networks (BNNs)—the dynamic, adaptive systems of the human brain. This thesis investigates whether ANNs and BNNs share fundamental computational strategies in language tasks, specifically differentiating between task-general computations (predictive coding, context-sensitive representations, hierarchical processing) and task-specific ones (task flexibility and latent cause inference). Using methodologies such as encoding models, representational similarity analysis (RSA), attention-head mapping, and zero-shot generalization, the thesis identifies areas of alignment primarily under conditions of restricted modalities. Notably, predictive coding shows strong surface-level similarity between systems; however, deeper exploration reveals significant divergences in context sensitivity, hierarchical processing, and especially task flexibility—where ANNs fail to replicate human-like interpretation. These divergences underscore crucial limitations in current ANN architectures, highlighting their lack of cognitive scaffolding necessary for genuinely flexible comprehension. This thesis concludes by suggesting future research directions, including integrating multimodal inputs and embedding dynamic memory structures into ANN training, to better assess and narrow the cognitive gap between artificial and biological systems.

Early life stress (ELS) is associated with mental health disorders that develop later on in adulthood. Mental health disorders, such as major depressive disorder (MDD) and general anxiety disorder (GAD), affect millions of people worldwide and can potentially give rise to more complicated health issues. A commonly proposed explanation for this has been stress sensitization, whereby ELS primes the adult brain to be either more susceptible or resilient to stress exposure in adulthood. While epigenetic mechanisms previously have been implicated in governing long-lasting changes in the brain, the exact molecular mechanisms mediating ELS to sensitization to stress in adulthood are not fully understood. As N6-Methyladenosine (m6A) is the most abundant RNA modification found on mRNA transcripts and has been shown to play a role in post-transcriptional regulation – including RNA splicing, nuclear export, degradation, and stability – this research investigates the role of m6A RNA modifications in the brain's response to stress as a possible molecular mediator of ELS-induced sensitivity to stress in adulthood. This study examines the effects of ELS exposure and adult stress (AS) exposure on altering global m6A levels in brain regions involved in the brain’s stress response pathway. Briefly, I observed regional differences in the levels of global m6A between the prefrontal cortex, anterior cingulate cortex, basolateral amygdala, ventral tegmental area, nucleus accumbens, and the ventral hippocampus. Further, I provide evidence suggesting ELS primes the adult brain to be more sensitive to AS, as the gene expression of m6A writers (enzymes that deposit m6A) and erasers (enzymes that remove m6A) was found to be dysregulated across all brain regions. By elucidating the molecular mechanisms underlying m6A-mediated gene regulation in response to stress, this research contributes to a better understanding of stress vulnerability and the development of psychiatric disorders such as depression and anxiety.

In recent years, Generative-AI (GenAI) has entered the public lexicon, growing in popularity via its widespread accessibility and use. In the art domain, the use of GenAI technologies has sparked debates, ranging from copyright concerns to philosophical debates concerning whether GenAI’s creative capabilities can match that of humans. Recent psychological surveys reveal a consistent bias against artwork labeled AI-generated, though these studies fail to capture how such negative preconceptions shape how people visually process these works. Under the neuroaesthetic triad model—which links aesthetic perception to knowledge-meaning, emotion-valuation, and sensory-motor circuits—this study investigates the possibility that labeling artwork as AI-generated not only triggers a cognitive bias, leading to more critical subjective judgments, but further alters viewing behavior. To investigate this research question, a between-subjects eye-tracking experiment was conducted in which participants saw artwork under one of three viewing conditions: 1) all of the artwork was labeled AI-generated, 2) all of the artwork was labeled human-created, and 3) no origin information was provided. After viewing each artwork, subjects answered a series of Likert survey questions to gauge their perceptions, aesthetic, and emotional valuations of the work. The findings suggest that although AI-generated labels lead to more critical, subjective evaluations of the work, such evaluations do not correlate with a generalized change in viewing strategies—measured as various saccade and fixation metrics—compared to human-created and unlabeled artwork. However, there were observable viewing behavioral differences across groups for a small subset of images, suggesting that contextual label effects might be subtle, image-dependent, or reliant on obvious or salient visual anomalies. Preliminary results from a within-subjects pilot study largely replicate these findings, offering additional nuance to the interpretations of the main study and informing future research with considerations of inherent individual variability in eye-movement behavior.

Aedes aegypti is a highly effective vector of mosquito-borne diseases such as Dengue, Zika, Chikungunya, and Yellow Fever. Its strong preference for human hosts is largely driven by olfactory cues, making the mosquito’s olfactory system a critical area of study for understanding and mitigating disease transmission. This thesis investigates the organization of olfactory sensory neurons (OSNs) and their projections to specific glomeruli in the antennal lobe, with a focus on five odorant receptors (Or6, Or16, Or23, Or52, and Or94) that may play roles in human odor detection. Using transgenic mosquito lines generated through CRISPR and the Q-binary expression system, fluorescently labeled olfactory sensory neurons (OSNs) were visualized via confocal microscopy. Glomerular positions were mapped and compared to existing anatomical and molecular atlases to propose new receptor–glomerulus pairings. Additionally, glomerular volumes were calculated using 3D reconstructions in ImageJ, and receptor expression was quantified across antennal segments to examine spatial distribution patterns. Results show preliminary evidence for assigning Or6 and Or94 to glomeruli PD1 and V3, respectively, and suggest revised candidate glomeruli for Or16, Or23, and Or52 based on anatomical alignment and RNA expression data. These findings contribute to a more comprehensive understanding of the Ae. aegypti olfactory system and offer valuable targets for future studies exploring host-seeking behavior and vector control. By identifying key olfactory circuits involved in human odor detection, this work supports the broader goal of disrupting mosquito-human interactions to reduce disease burden.

This thesis examines the intersection of neuroscience and musical theatre by analyzing how A Life Worth Living—an original musical centered on adolescent mental health—both represents and modulates the Default Mode Network (DMN), a brain system associated with self-referential thought, memory, and identity (Raichle et al., 2001). Drawing on current research in cognitive neuroscience, the thesis outlines the DMN’s role in depression, suicidality, and cognitive rigidity, then explores how these processes are externalized and represented on stage through character arcs, design elements, and musical structure. Chapter 1 traces the creative development of A Life Worth Living, from its initial inspiration to its full production and reception. Chapter 2 presents a neuroscience-based literature review on the DMN, synthesizing findings from clinical research to explain its role in psychiatric disorders and therapeutic intervention. Chapter 3 uses the musical as a case study to analyze how the DMN is portrayed onstage through character psychology, sound, design, and narrative structure, while Chapter 4 expands the discussion to consider how theater itself can modulate DMN activity. Through processes like narrative therapy, emotional rehearsal, and audience empathy, theatrical storytelling is shown to activate and potentially reshape DMN-related cognitive processes. Ultimately, this thesis proposes that theater can do more than represent the mind—it can participate in changing it. By combining scientific insight with personal narrative and artistic practice, this project suggests that interdisciplinary storytelling holds unique promise for mental health education, intervention, and healing.

Working memory enables the brain to store and manipulate information across time, yet the neural mechanisms that support this function remain debated. This study examines the causal role of the prefrontal cortex in working memory by employing optogenetic inhibition in mice engaged in a Parametric Working Memory task. In this task, head-fixed mice compare the temporal frequencies of two sequential visual stimuli separated by a delay period, turning left or right in a virtual T-maze based on the comparison. Using temporally targeted optogenetic suppression of inhibitory interneurons, we tested three hypotheses: (1) whether the PFC is necessary for task performance; (2) whether it specifically supports memory retention during the delay period; and (3) whether its contributions are magnified under high task difficulty. Surprisingly, PFC inactivation did not significantly impair behavioral accuracy, shift choice patterns, or disrupt stimulus-guided decision-making—even under cognitively demanding conditions. Logistic regression and psychometric analyses revealed preserved decision strategies and stimulus sensitivity during PFC suppression. Although subtle modulations in decision dynamics were observed, they did not reach statistical significance. These results suggest that the PFC may play a modulatory—but not essential—role in working memory, with core memory representations likely maintained by distributed circuits.

Children learn to talk through feedback loops of social interaction that drive them towards further language development. When engaged in this social interaction, the brains of children and their caregivers become coupled. One hypothesis for the origin of this coupling is the development of a shared understanding between communication partners. If true, it stands to reason that coupling would increase within dyads where children have greater command of their language and can easily convey complex ideas. To test this hypothesis, we simultaneously recorded the brains of caregivers and their 2- to 4-year-old children (N = 55) using functional Near-Infrared Spectroscopy (fNIRS). We identified each child utterance within the session, and classified its maturity. We then analyzed relationships between children’s participation in conversation (frequency and duration of utterances) and their vocal maturity (frequency, duration, and proportion of each utterance type). We found that coupling in the prefrontal cortex (PFC) was significantly increased in response to increased child laughter. Additionally, we found that the PFC of both children and their caregivers experienced an increase in activity in the moments surrounding instances of child laughter. Furthermore, we observed that language maturity does not have an effect on coupling in the PFC. We therefore suggest that coupling in the PFC may not not arise from the development of a shared understanding between interaction partners, but from moments of positive emotion within an interaction. Our study represents the first characterization of the neural dynamics of both children and their caregivers in response to child utterances of different maturities, and points towards new directions for the determination of the behavioral correlates of brain coupling.

Schizophrenia is a chronic psychiatric disorder characterized by positive and negative symptoms. While recent research has extensively explored working memory deficits in schizophrenia, few studies have investigated how continuous memories evolve within working memory. This study aims to address this gap by investigating how task performance errors and attractor dynamics (stable memory states within mnemonic space) in visual working memory relate to symptom severity in schizophrenia. We used a continuous color report task with varying memory loads (1-3 items) and delay durations (500ms, 4000ms) in 47 individuals with schizophrenia and 33 healthy controls. Results demonstrated that both memory load and delay duration significantly increased angular error, with each additional memory item increasing error by approximately 7 degrees. Mean angular error significantly predicted symptom severity as measured by the Positive and Negative Syndrome Scale (PANSS) (p = 0.0207). Analysis of bias patterns across color space revealed greater variability in individuals with schizophrenia, suggesting possible disrupted attractor dynamics that warrant further research.

Humans frequently attribute consciousness and human-like qualities to non-human entities, such as puppets, robots, and animated shapes. This tendency, known as anthropomorphism, is rooted in social cognition and perceptual mechanisms, and has important implications for empathy, interaction, and the development of artificial agents. This study investigated how motion characteristics and contextual priming influence the perception of consciousness in non-human animated objects. In a behavioral survey, participants (N = 77) viewed four short videos depicting geometric shapes engaging in different motion patterns—random, goal-directed, socially interactive, and reactive—and rated each on perceived consciousness, intentionality, social attribution, and lifelikeness. Participants were randomly assigned to one of three priming conditions: anthropomorphic, mechanistic, or neutral. Results showed that motion type strongly influenced consciousness-related ratings, with goal-directed and socially interactive motions eliciting significantly higher attributions of agency and lifelikeness than random or reactive motion. In contrast, priming conditions did not produce statistically significant effects. Autism Spectrum Quotient (ASQ) scores were included as an exploratory variable but were not significantly associated with consciousness ratings. These findings underscore the salience of motion dynamics in shaping intuitive mind perception and offer empirical support for motion-based models of agency attribution in non-human forms.

Addiction remains a complex and persistent public health crisis, often framed through the Brain Disease Model of Addiction (BDMA), which conceptualizes addiction as a chronic, relapsing brain disorder rooted in pathological changes. While the BDMA has contributed valuable insights into neurobiological mechanisms like dopamine dysregulation, prefrontal cortex impairments, and stress system activation, it has been critiqued for reducing addiction to individual pathology and sidelining social and environmental factors. This thesis critically evaluates the BDMA’s core assumptions– not to reject the model, but to extend it– arguing that addiction is best understood as a multi-systemic condition shaped by dynamic interactions between neurobiological, social, environmental, and stress-related systems. Drawing on neuroscience, epigenetics, and stress physiology, this thesis explores how these systems co-regulate each other through recursive feedback loops that drive both the biological and behavioral dimensions of addiction Rather than viewing social and environmental factors as peripheral risk contributors, this work positions them as core mechanisms that actively shape addiction’s neurobiology and behavioral patterns. By integrating these perspectives, the thesis moves beyond linear disease frameworks, proposing a dynamic systems model that aims to reflect the complex realities of addiction and offer a new pathway for research and intervention.

COVID-19 significantly impacted human health globally, with consequences that continue well beyond the pandemic. It has left 17% of the United States’ adult population with long COVID, a condition with symptoms that include those similar to myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Key characteristics of ME/CFS include metabolic reductions, changes in brain morphology, and, namely, post-exertional malaise (PEM). The biological underpinnings of the syndrome are largely unknown, and research in humans has been limited. While other animal models rely on complex interventions to induce ME/CFS-like symptoms, Caenorhabditis elegans (C. elegans) naturally transition into dauer, a unique developmental stage that is hypothesized to parallel the metabolic reductions and lethargy found in individuals with ME/CFS. My thesis aims to investigate the behavioral changes occurring in C. elegans post-exertion, using the dauer stage as a model for humans with ME/CFS. Developed is a behavioral swim assay aimed to trigger PEM in dauer C. elegans and non-dauer counterparts. Also developed is a modified high-throughput computer vision assisted behavioral assay, utilized to track multiple C. elegans at once post-exertion. Findings suggest that dauer C. elegans experience PEM to a greater extent than non-dauer C. elegans. Dauer C. elegans exhibited reduced movement post-exertion relative to non-dauer C. elegans, visible both over the five-day behavioral assay and on a day-to-day basis. Additionally, exercised dauer C. elegans showed less spatial deviation from their starting point over time compared to controls. Thus, these findings propose that dauer C. elegans may serve as a useful developmental stage for investigating aspects of PEM relevant to ME/CFS.

In motor skill learning, two different types of prediction errors have been identified: Sensory prediction errors (SPEs) and reward prediction errors (RPEs). SPEs occur when the predicted sensory consequence of a movement does not align with the observed consequence, while RPEs occur when the result of said movement deviates from the desired goal. These errors were previously believed to be processed independently, with SPEs driving implicit sensorimotor adaptation in the cerebellum and RPEs driving explicit decision-making in the striatum. Recent research, however, has suggested otherwise, finding that SPEs influence decision-making by elevating risk tolerance, while RPEs influence implicit adaptation by increasing recalibration. What remains unclear is whether RPEs influencing SPE-driven adaptation extends to the neuroanatomical level. To explore this, we utilized the visuomotor reach adaptation task, which enables isolation of SPEs and RPEs and their subsequent effects on implicit adaptation behavior. Using fMRI, we asked if cerebellar activity associated with SPEs is modulated by RPEs when both error signals are experienced in tandem compared to just SPEs alone. From this, we replicated previous behavioral findings that RPEs are insufficient to drive implicit adaptation while SPEs can regardless of RPE presence. We also observed a numerical trend consistent with literature that the combination of SPEs and RPEs drive greater adaptation than SPEs alone. While strictly exploratory and below threshold due to a limited sample size, we observed preliminary evidence of cerebellar activity associated with RPEs when both error signals were experienced. This pattern may suggest that RPEs modulate SPE processing, which could explain the enhanced adaptation when both error signals are experienced together. These results overall support the viability of our MRI-adapted task for future prediction error imaging studies, and that the current trends may manifest under more conventional thresholds with a complete sample size.

Social behavior, such as investigation or interest, mating, and aggression, drives day to day interactions. The choice to interact with a conspecific or social subject over a nonsocial subject is known as a social reward. The social reward circuit has been extensively studied and involves various subcortical and mesolimbic structures, such as the ventral tegmental area, nucleus accumbens, medial preoptic area, and the ventromedial hypothalamus ventrolateral area. Previous studies have also pointed to the role of sex hormones in mediating social behavior. This paper utilizes a two-choice social operant with automated reward (SOAR) paradigm to investigate how social behavior is altered in mice following testosterone injection. Additionally, we record neural activity from the ventromedial hypothalamus ventrolateral area to understand how neural activity in the region is affected under the influence of testosterone. Our results show successful learning on the operant task for social reward, decreased poke rates for social reward and an overall decrease in neural activity under the influence of testosterone, suggesting a decrease in social motivation. Further understanding of the potential role of the ventromedial hypothalamus and sex hormones drive social reward is crucial for understanding social motivation.

Consider a child who hears “dog” for the first time in reference to a dalmatian. How do they come to understand that “dog” refers to any dog but not any animal or just dalmatians? This example highlights a challenge all language learners face: what is the range of objects that a novel word can refer to (i.e., its extension)? Despite this challenge, children can quickly learn to properly extend novel words. We suggest that active learning plays an important role in this process, allowing children the opportunity to test their hypotheses about word extensions and clarify ambiguous cases. In this present study, we tasked children (5 to 8 years of age) and adults with learning novel words and provided them a chance to actively learn through sampling, where participants could select an object and learn if the novel word could be extended to it. We assessed participants’ sampling behaviors and found that children, similar to adults, favored conservative sampling choices that confirmed a novel word’s known extension, as opposed to exploring broader possible extensions. We also found that, with age, children more frequently explored word extension ambiguity by sampling objects that could potentially provide them with new information about the breadth or specificity of a novel word’s extension. However, overall, children were still less exploratory than prior studies might suggest. Taken together, these findings advance our understanding of how children learn word extensions by introducing active learning as a facilitator of this learning process.

Sensorimotor learning involves the dynamic interplay between implicit recalibration and explicit strategic control. While prior work has distinguished between cognitive strategies such as mental rotation (MR) and response caching (RC), it remains unclear how task structure shapes their engagement during adaptation. This study examined how target set size and perturbation schedule influence strategy use in a visuomotor rotation task. Eighty-five participants performed center-out reaching movements under conditions varying in the number of target locations (2 vs. 12) and the rotation schedule (abrupt vs. gradual). Response times and movement angles were analyzed across distinct learning phases.

As predicted, low set size conditions exhibited substantial reductions in response time across training, consistent with a shift from MR to RC strategies. High set size conditions maintained elevated response times, suggesting sustained reliance on parametric computation. All groups improved in movement accuracy over time; however, larger aftereffects were observed in the low set size groups, aligning with use-dependent learning. Rotation schedule had comparatively smaller effects on both response times and accuracy.

These findings underscore the role of environmental structure in guiding cognitive strategy selection during motor adaptation and suggest implications for optimizing performance in applied settings such as neurorehabilitation and brain-machine interface design.

Autism spectrum disorders (ASDs) are heterogeneous disorders that are associated with social, affective, cognitive and motor abnormalities. Phelan-McDermid Syndrome, a neurodevelopmental disorder that is accompanied by autistic behavioral phenotypes, has been shown to develop with Shank3 heterozygous deletion in humans. Comparing mouse and marmoset models of a highly penetrant risk gene such as Shank3 using RNA-FISH will lead to a better understanding of the differences between primate and non-primate animal models for studying autism and its behavioral phenotypes. In this project, census data from mice and marmosets across different regions and cell types will be analyzed to understand differences in the expression of Shank2 and Shank3 between cell types and regions. Then, RNA-FISH experiments will be run based on the cell types and regions identified from the census data. Identifying these differences in expression could inform on developing better ASD models and potentially inform gene-targeted approaches in the future. I will analyze key brain structures implicated in autism, such as neocortex, striatum and thalamus, comparing regions and cell types specific expressions between mice and marmosets.

Double consciousness, as articulated by W.E.B. Du Bois, encapsulates the lived experience of African Americans navigating self-perception through both an intrinsic awareness of the self and the external gaze of a society shaped by racial ontologies. This duality is not just a psychological phenomenon, but a product of historical and structural forces—the lasting ramifications of slavery and systemic oppression. Slavery established a framework of domination that not only depersonalized Black bodies but embedded notions of Black inferiority into the very fabric of American society. This legacy created an epistemic burden, an ongoing cognitive adaptation, where Black individuals are forced to see themselves ‘through the revelation of the other world’—through the distorted eyes of a society that devalues them. This partition between the true self and the imposed identity creates a dissonance, a ‘twoness,’ that fractures the Black psyche, shaping how Black individuals navigate and understand the world, as well as their relationship to it. Thus, Africana philosophy sees double consciousness not only as a psychological condition but as an existential struggle against identity constructs imposed by society—tensions that reverberate through the enduring legacies of coloniality and slavery. This thesis explores the neural mechanisms underlying double consciousness through the lens of Michael Graziano’s Attention Schema Theory (AST), proposing that racialized self-awareness modulates attentional control, introspection, and cognitive performance. Using a modified Posner cueing paradigm, the study investigates how sociohistorical architectures of race shape attentional processing, reaction time, and self-reflection in Black Princeton students. The results reveal that negative racial priming—exposure to imagery of racialized social contexts—significantly impairs cognitive performance, with marked differences between negative priming and both neutral and positive priming conditions. External racial stimuli serve as primes, triggering shifts in the participant’s internal state, activating self-representations tied to Black identity and collective memories of historical oppression, which then influence cognitive performance. These findings suggest that racialized stimuli lead to the differential allocation of cognitive resources, particularly activating self-referential processing networks, such as the mPFC and TPJ, more intensely than other types of stimuli. While positive primes, associated with socially validated institutional affiliations, did influence performance, the effect was not statistically significant. These results support the hypothesis that attentional shifts, driven by race-related imagery, are intricately tied to self-representation and regulation, highlighting how double consciousness engages neural processes governing attention and self-perception. Furthermore, the research explores how deep Q-learning models can simulate these attentional shifts, integrating a neural network framework that incorporates identity-related stimuli. This study provides empirical evidence linking social identity with attentional mechanisms, contributing to neuroscience, social psychology, and the philosophy of race. It establishes the view that double consciousness is not merely a sociocultural concept but a neurocognitive reality, with profound implications for how Black individuals perceive themselves, the world, and their interactions within it—shaping their perception, cognition, self-concept, and behavior.