Neuroscience, 2017-2025

Treating post-traumatic stress disorder (PTSD) effectively remains a significant challenge, as the efficacy of standard approaches like exposure therapy varies among patients. Exposure therapy aims to mitigate trauma’s impact through gradual re-exposure to the stressor within a safe setting. Despite its use, exposure therapy’s neurobiological foundations behind its beneficial impact on stress recovery are not well understood, primarily because suitable preclinical models that utilize translationally relevant, escalating stress paradigms to inoculate rodents are currently lacking. Furthermore, understanding sex-specific variations in trauma responses is crucial for developing more personalized interventions, yet preclinical work has predominantly focused on male rodents. To address these gaps, we implemented four stress paradigms: no stress (Ctrl), 10 days of social defeat (Reg), 10-day defeat followed by 20-day gradual re-exposure (Reg+Esc; modeling exposure therapy) and 20-day gradual exposure followed by 10-day defeat (Esc+Reg; modeling stress inoculation). Based on pilot data indicating that escalating stress requires environmental enrichment (EE) housing to effectively improve behavior, our Reg+Esc and Esc+Reg cohorts were housed in enriched cages. Our main goal was to clarify how EE and escalating stress (before or after 10-day defeat) impacts behavior and region-specific mRNA expression in male and female C57BL/6 mice. Our findings revealed several sex-, region-, and paradigm-specific results. Notably, EE conferred greater behavioral resilience against chronic stress in females compared to males. While the modeled ‘exposure therapy’ paradigm (Reg+Esc) induced distinct molecular changes in the female nucleus accumbens (elevated Bdnf and Crh mRNA), these changes did not translate into superior outcomes in generalized anxiety or sociability compared to the ‘stress inoculation’ approach (Esc+Reg). We also uncovered complex sex- and region- dependent correlations between specific molecular markers and behavioral phenotypes, highlighting an intricate interplay between environment, stress re-exposure, and neurobiology. This thesis is novel in showing that EE works in combination with gradual re-exposure to shape mRNA expression and associations between various markers and behavior in a sex- and region-dependent manner. Our findings underscore the critical need to incorporate sex- and region-specificity into holistic PTSD-related preclinical research and treatment.

Bisphenol A (BPA), an endocrine-disrupting chemical found in numerous consumer products, has raised concerns about its potential neurotoxicity. We employed an integrative multi-omics approach, using the Neuro-2a mouse neuroblastoma cell line, to investigate the neurotoxic effects of BPA at human-relevant concentrations. This pilot study specifically aimed to determine biologically relevant doses of BPA for the Neuro2a model and characterize an in-vitro neurotoxicity profile. Initial findings indicated that high-dose BPA (100-500 µM) induced significant cytotoxicity, while lower doses (0.1-1 nM), representative of human exposure levels, did not significantly impact cell growth. Metabolomic analysis of chronic BPA exposure at such low doses revealed significant disruptions in energy homeostasis and lipid metabolism. Transcriptomic analysis of chronic low-dose BPA exposures similarly implicated genes involved in metabolic pathways, as well as in methylation and Wnt signaling. In conjunction, these findings highlight potential risk factors for neurological dysfunction and potentially neurodegenerative disorders such as Alzheimer’s disease and Parkinson’s disease given similarly implicated dysregulation in these pathways. Overall, our findings support the idea that BPA may be a significant risk factor for neurological dysfunction and potentially neurodegenerative disorders by affecting key metabolic pathways, even at low, human relevant doses. The final aim of this work was to analyze EDC exposure as a mechanism of environmental racism and slow violence, drawing upon a specific case study involving Indigenous communities living near the Athabasca tar sands region of Alberta, Canada.

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.

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.

Cocaine addiction presents a complex challenge to neuroscience, combining behavioral compulsivity with strong neurobiological disruption. Among the brain regions most consistently implicated in the progression of this disease is the basal ganglia, a system of interconnected nuclei that plays a central role in motor control, reward learning, and the formation of habitual behaviors. While acute cocaine exposure to the basal ganglia primarily influences dopamine transmission, chronic use triggers broader neuroadaptations that functionally disrupt this circuitry over time. This thesis investigates how repeated cocaine intake affects the basal ganglia not only functionally and behaviorally, but also structurally, with particular attention to patterns of gray matter volume (GMV) change. GMV has been studied in a wide range of mental disorders and neurological diseases, including substance use disorders, but the focus has historically not been placed on the basal ganglia, despite its implications in such diseases. Drawing from decades of foundational research and more recent volumetric studies, this work identifies significant yet inconsistent GMV alterations in the basal ganglia during cocaine use disorder (CUD), including both hypertrophy and atrophy of the striatum. These divergent findings are placed within the context of key models of addiction in order to characterize the basal ganglia as a critical location of neuroadaptation in CUD. Understanding these adaptations provides a foundation for future research into biomarkers of addiction that have not been standardized before and potential therapeutic interventions.

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.

Working memory is vital to human cognition, providing us with the ability to temporarily hold and work with information. Deficits in working memory can manifest as attentional issues such as those present in cognitive disorders like ADHD. Higher working memory capacity (WMC) has previously been shown to be protective against the negative effects that auditory distractions can have on our cognition, meaning that the development of working memory has a direct effect on one’s susceptibility to auditory distractions in adulthood. This study specifically investigated how chronic noise exposure during the development of working memory affected one’s susceptibility to different kinds of auditory distractions in adulthood. College-aged participants who grew up in noisy city environments with consistent chronic noise exposure and quieter rural/suburban environments with less chronic noise exposure were recruited and completed an online auditory working memory complex span task with and without auditory distraction. Data analysis focused on participant distractibility in the form of worsened task performance when an auditory distractor was present. The findings showed no consistent significant differences in distractibility between those who grew up in the presence of more chronic noise exposure in cities and those who grew up in quieter environments. All participants, regardless of developmental environment, showed greater distractibility when less familiar, more artificial auditory distractors were present, hinting at a possible desensitization mechanism to familiar auditory distractors. In addition, higher baseline working memory capacity (WMC) was shown to be modestly correlated with increased susceptibility to auditory distractions, contrary to previous literature.

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.

Adeno-associated viruses have revolutionized neuroscience research by enabling precise delivery of genetic cargo and facilitating targeted application of techniques such as optogenetics and chemogenetics. Clinically, AAV-mediated gene therapy has recently been approved by the FDA to treat nervous system disorders. However, recent evidence unexpectedly shows that AAVs can trigger innate immune responses through activation of Toll-like receptor 9 by unmethylated CpG motifs within the viral genome, leading to dendritic loss and synaptic weakening. As AAV-based therapies continue to gain clinical approval, further characterization of AAV-induced side effects — particularly behavioral outcomes — is crucial. To protect against these effects, strategies such as systemic TLR9 inhibitors have shown promise; however, challenges remain regarding immunosuppression, specificity, efficacy, and clinical applicability. This study aims to address these two major gaps in the field. To explore the link between AAV-induced functional and structural disruptions and behavioral outcomes, I investigated the behavioral consequences of AAV administration in the central nervous system, using a modified novel object recognition and whisker nuisance assay. To protect against AAV-induced circuit damage, I developed novel candidate oligodeoxynucleotide TLR9 inhibitors, and encoded one candidate TLR9 inhibitor directly in the AAV genome. This approach targets TLR9 inhibition to only those cells that are transduced with AAV, potentially improving efficacy and reducing immunosuppression compared to systemic TLR9 inhibitors. Together, these studies aim to improve the safety and efficacy of AAV-mediated gene delivery and to expand its therapeutic potential for treating neurological diseases.

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.

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.

Spontaneous thought is defined as internally generated, task-unrelated mental activity that plays a foundational role in processes such as imagination, emotion regulation, and memory retrieval. While music is well-established to elicit spontaneous thought, the extent to which these experiences are shaped by cultural background remains unclear. The present study investigates the role of enculturation (the acquisition of culturally specific aesthetic and structural expectations through lived experience, media exposure, education, and geography) in shaping music-evoked narrative imagination. We focus on Indian classical music (North Indian, Hindustani, and South Indian, Carnatic), a tradition defined by the rāga system: highly codified melodic frameworks culturally associated with specific times of day, emotional states, and even physical phenomena (e.g., rain or the seasons). These culturally significant associations make rāgas, and by extension Indian classical music, an ideal system for examining how shared musical meaning informs spontaneous narrative construction.Participants (N = 229), categorized as Enculturated or Non-Enculturated based on their familiarity with Indian classical music, listened to eight rāga excerpts and indicated whether they imagined a narrative in response. When applicable, they provided written descriptions, which were analyzed across several dimensions: narrative engagement (vividness, clarity, temporal alignment, and familiarity), subjective enjoyment, elaboration, and semantic content. Although narrative frequency was similar across groups, Enculturated participants demonstrated significantly higher engagement, familiarity, and enjoyment for specific rāgas (notably Mishra Bhairavi and Revati), and showed a stronger correlation between enjoyment and engagement. Narrative content was further evaluated using natural language processing techniques, including TF-IDF, sentence embeddings derived from SBERT, and unsupervised clustering. Enculturated participants produced narratives that were not only more semantically coherent but also clustered by rāga, reflecting shared associative frameworks. These patterns were confirmed using permutation-based null models. In contrast, Non-Enculturated participants displayed more diffuse and less structured narrative patterns. Together, these findings provide robust evidence that spontaneous thought in response to music is culturally bounded: shaped by aesthetic priors from lived experience rather than universally abstract processes. By extending prior work in music cognition and narrative imagination, this study also points toward culturally informed therapeutic applications, particularly in contexts where spontaneous thought is clinically disrupted (e.g., MDD, ADHD).

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.

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.

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.

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.

This study examined whether local hippocampal place cell activity could function as an effective state representation in reinforcement learning for a spatial navigation task. In order to address this question, this study first investigated how hippocampal place cells would potentially represent state. While it was predicted that place cells would encode distance geodesically, as this would reflect how rats behaviorally take map distance into account during value computation (Krausz et al., 2023), no evidence was found that place cells represent map distance. This does not necessarily mean that place cells cannot function as an effective neural correlate of state. Indeed, it may be possible that place cells simply reflect important properties of value computation in another way. Beyond examining place cell properties, this study directly tested the use of local hippocampal place cell activity as the state representation in a reinforcement learning model. Specifically, the "Dual-component hex-value learner" (Krausz et al., 2023), which originally relies on manually designed bins (i.e. hexes) to represent the state, was adapted by this study. Contrary to expectations, adapted models incorporating place cell activity either as a partial or full state representation did not perform significantly differently than the original Krausz et al. (2023) hex state model. However, the fact that such adapted models performed comparably to the original model suggests that local hippocampal place cell activity could function as an alternative state representation without reducing the effectiveness of the reinforcement learning model. Moreover, there were certain limitations to the data and methodology of this study that, when addressed, could potentially result in better performance from adapted models which use hippocampal place cell activity to represent the state.