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The Roaring ‘20s Project: Mapping Pre-Renewal Built Environments in Chicago from Sanborn Fire Insurance Maps Using a Computational Workflow
No full textSanborn Fire Insurance maps are some of the most complete records of the historical built environment that researchers have access to, with building-level data for over 12,000 North American cities contained in large atlases that date back more than a century. These maps have become invaluable resources for digital humanities research, helping to visualize, disseminate, and interpret the history of urban environments (Ross, 1971; Krafft, 1993). Figure 1 shows an example of one such map. A key challenge in working with these maps, however, is ensuring the preservation and accessibility of their information through digitization, which has traditionally been largely contained to tedious handtracing methodologies. While there is existing research to extract building information through machine learning, the methodology is costly in both time and processing power due to the need to train large datasets, which can limit its scalability to broader areas (Tollefson et al., 2021; Lin et al., 2023).</p
Mamlūk Studies Review, Vol. XXVIII (2025)
No full text“The Languages of the Mamluk Empire”: Papers presented at the Ninth Conference of the School of Mamluk Studies, Brown University, 202
Cerebellar climbing fibers impact experience-dependent plasticity in the mouse primary somatosensory cortex
No full textIn the cerebellum, climbing fibers (CFs) provide instructive signals for supervised learning at parallel fiber to Purkinje cell synapses. It has not been tested so far whether CF signaling may also influence plasticity in other brain areas. Here, we show that optogenetic CF activation suppresses potentiation of whisker responses in layer 2/3 pyramidal cells in the primary somatosensory (S1) cortex of awake mice that is observed after repeated whisker stimulation. Using two-photon imaging and chemogenetics, we find that CFs control plasticity by modulating SST- and VIP-positive interneurons in S1 cortex. Transsynaptic labeling identifies zona incerta (ZI) to thalamic posterior medial nucleus projections as a pathway for cerebellar output reaching S1 cortex. Chemogenetic inhibition of PV-positive neurons in the ZI prevents CF co-activation effects, identifying the ZI as a critical relay. Our findings demonstrate that CFs impact sensory signal processing and plasticity in S1 cortex and thus may convey instructive signals.</p
Lipid-packing defects are sufficient to modulate membrane insertion and the bound state of α-synuclein
No full textα-Synuclein is an intrinsically disordered neuronal protein that forms an amphipathic helix when it peripherally binds to lipid membranes. This membrane interaction is integral to the protein’s function but is also associated with its dysfunction. Numerous membrane parameters have been identified to promote α-synuclein binding such as high negative charge and low lipid-packing density, which corresponds to greater lipid-packing defects—increased spacing between lipids conferred through curvature, unsaturation, or small headgroups. Despite α-synuclein’s established preference for negatively charged membranes with packing defects, the specific effects that each parameter has on this interaction remains underexplored. With increasing links between α-synuclein-associated diseases and changes in lipid composition, it has become more important to delineate how changes in membrane parameters affect α-synuclein membrane-interactions. Here, we demonstrate using tryptophan fluorescence spectroscopy that while net negative charge does increase the density of α-synuclein bound to a membrane, lipid-packing defects alone are sufficient for α-synuclein to insert. Not only do our results establish a lipid-packing defect requirement for α-synuclein, but they also reveal a packing defect-dependent shift in the ensemble of binding modes of the protein favoring the insertion of the end of its binding domain—a binding mode which has previously been linked to disease mutants of the protein. Overall, this work establishes the significance of lipid-packing defects in contrast to net negative charge for α-synuclein–membrane binding and proposes a lipid-compositionally dependent shift in α-synuclein’s ensemble of bound conformations, which may be relevant for the protein’s function and dysfunction.</p
Song Responses in a Songless Oscine
No full textThis dissertation investigates how female zebra finches, who do not sing, respond to male courtship song. Chapter 1 argues that sexual selection research should integrate neural mechanisms of mate choice. Although male songbird courtship has been extensively characterized, female behavioral and neural responses remain poorly understood despite their importance for reproductive fitness and evolution. Chapter 2 analyzes the temporal structure of male zebra finch song and shows that these songs typically exhibit a hierarchical rhythmic structure that may shape how females perceive and evaluate songs. Chapter 3 shows that females are more behaviorally responsive than males to novel songs and rhythmic song-like stimuli, particularly in social settings, with response strength depending on spectral structure and familiarity. This suggests that females may be especially sensitive to the combination of particular song features and social context. Chapter 4 introduces a new preference assay and shows that females interacting with males under semi-natural, multimodal conditions typically express consistent and moderately repeatable transitive preferences. Females also exhibit context-dependence and individual variability, which may help explain inconsistent results in preference assays. Chapter 5 presents the first extracellular recordings from female HVC (a song control nucleus in males). Results demonstrate robust, heterogeneous, and class-selective auditory responses to conspecific songs as well as premotor activity preceding calls. These findings indicate that female HVC participates in complex perceptual processes as well as vocal production, challenging the view that it is merely vestigial. Chapter 6 shows that song system nuclei are embedded in broader associative and social networks, with major hub regions like NCL, located immediately ventral to HVC, providing anatomical context for how female HVC could interact with higher-order decision-making circuits. Chapter 7 argues for a revised view of the female song system, in which female HVC is a functional node in a distributed, socially oriented network that supports flexible, attention- and state-dependent integration of vocalizations, social context, and internal factors rather than simple detection of fixed preferences. Altogether, the results suggest that females primarily assess whether males express species-typical development, condition, and social competence, with individual variation in female behavior and neural adaptation helping to explain inconsistent laboratory preference measures. By complementing prior work on male song production with analyses of female behavioral and neural responses, this dissertation offers a more complete account of zebra finch courtship and supports an integrative understanding of how receivers shape evolution
Computational Approaches To Detecting Risk Variants And Genes Of Complex Traits
No full textGenome-wide association studies (GWAS) have identified thousands of genetic associations with complex human traits and diseases, yet most of them map to non-coding regions of the genome, making it difficult to identify causal variants, understand their regulatory effects, and link them to the genes through which they act. This thesis addresses these challenges through computational approaches aimed at improving post-GWAS interpretation at both the variant and gene levels. First, it leverages DNA sequence–based deep learning models to prioritize functional non-coding variants and characterize their regulatory effects in disease-relevant cellular contexts. By evaluating predicted effects in neuropsychiatric cell types, this work demonstrates that predicted regulatory effects capture biologically meaningful signals and can be used to prioritize likely causal variants within GWAS loci. Second, this thesis develops a statistical genetics framework that integrates multi-omics and multi-tissue QTL data with GWAS summary statistics to identify causal genes underlying complex traits. The proposed method jointly models multiple molecular traits while accounting for correlations among them, enabling gene-level fine-mapping. In simulations and real data analyses, this framework substantially reduces false positive discoveries compared to existing approaches and increases power to identify candidate genes. Together, these approaches advance the functional interpretation of GWAS by bridging the gap between non-coding genetic variations and complex traits, providing scalable computational tools for prioritizing regulatory variants and risk genes, elucidating underlying molecular mechanisms and revealing genetic architecture of complex human traits
Effects of methamphetamine on two measures of reward: Euphoria and neural activation to reward cues
No full textStimulants enhance dopamine function, affecting diverse aspects of reward function from neural processing of reward cues to feelings of well-being in humans. However, little is known about the relationships among different measures of reward function. Understanding relationships among different indices of reward processing could provide insight into the processes that control motivated behavior. The present study examined the effects of a single dose of methamphetamine on two measures of reward in healthy adults: feelings of well-being and neural activation with reward-related stimuli. In a randomized, within-subject, double-blind study, 88 healthy men and women received a single 20 mg oral dose of methamphetamine (MA) and placebo, across two sessions. Regional activations to reward-related cues were assessed using fMRI during the Monetary Incentive Delay task, and positive subjective effects of MA were assessed using standardized questionnaires. As expected, MA increased euphoria and feelings of well-being. MA had minimal effects on neural activation during either anticipation or receipt of reward, but it significantly increased ventral striatal activation during anticipation of monetary loss, suggesting heightened salience of loss-related cues. As reported previously, caudate activation during reward anticipation during the non-drug (placebo) session was correlated with euphoria induced by MA (on the MA session). However, this correlation between cue-induced neural activation and euphoria was not apparent on the MA session. Thus, MA-induced euphoria was related to reward cue-elicited neural activation only when participants were tested without the drug. MA increased neural reactivity to loss, and this was not correlated with euphoria. These findings suggest that MA can dampen reward-related neural activity normally detected in the drug-free state, and that it enhances brain responses to loss. Further research is needed to determine how neural responses to reward or loss cues are related to feelings of well-being, and how either of these affect reward-related behavior.</p
Schooling in Displacement: How Syrian Refugee Students, Educators, and Nonprofits Navigate Barriers in Chicago Public Schools
No full textThe civil war and invasions in Syria have led to dire humanitarian consequences, with millions of Syrians facing poverty, food insecurity, and displacement. As of March 2024, over 16.7 million people in Syria need humanitarian assistance, with more than 90 percent of the population living below the poverty line and 12.9 million facing food insecurity (UNHCR, 2024). Within this context, 7.2 million Syrians have been internally displaced due to violence, destruction, and persecution. As a result of this crisis, the number of Syrian refugees resettling in the United States, particularly in cities like Chicago, has been steadily increasing. Through 14 qualitative semi-structured interviews with students, educators, and nonprofit representatives, this study examined the educational, cultural, financial, and mental health challenges faced by Syrian refugee students in Chicago Public Schools, and evaluated the interventions implemented by teachers, schools, and nonprofit organizations to address these needs. Findings suggested that Syrian refugee students in CPS experience a range of challenges, particularly related to disciplinary practices, misalignment between their academic background and the school curriculum, cultural and religious adaptation, and financial/welfare-related stress. While collaborative efforts between schools and nonprofits play a crucial role in addressing these barriers, significant gaps remain in individualized instruction and structural accommodations, resulting in supplementary initiatives by teachers and nonprofit staff
Novel Computational and Geometric Frameworks for Manifold Learning, Riemannian Optimization, and Feature Selection
No full textIn machine learning, Riemannian manifolds offer a useful abstraction for approximating commonly encountered, non-Euclidean empirical data distributions and optimization state spaces. Further, the “manifold hypothesis”, which states that the support of an empirical data distribution can be modeled as a low-dimensional submanifold of the ambient space, is increasingly accepted as an integral part of data analysis across domains. This is particularly true in the biological sciences, where unifying a framework across orders of magnitude of spatial resolution (e.g., from cells to organoids to organisms) requires intelligible simplification and abstraction at each scale. While researchers assume the manifold hypothesis in various domains, techniques that infer manifold approximations forfeit geometric and topological ground truth in simple test cases. Generalizing machine learning techniques to manifolds is a major challenge, even when an underlying manifold structure is known, as is the case in several machine learning tasks. This is largely due to the difficulty of computing exponential maps and parallel transports, the natural differential-geometric forms of first-order updates. Here, we present simple, novel approaches for representing and learning submanifolds embedded in Euclidean space or in the space of positive measures on a compact metric space. These approaches are theoretically motivated, interpretable, and amenable to downstream applications of Riemannian machine learning. Concretely, first, we present algorithms for learning manifolds from point cloud data and efficiently approximating differential-geometric primitives on them via construction of an "Atlas" object. We then give an approach to learn representations of low-dimensional submanifolds in an optimal transport geometry, which we use to study morphological variation in Drosophila melanogaster wings. Lastly, we describe a hybrid quantum-classical feature selection method, inspired by the phenomenon of parameter transfer in the recursive quantum approximate optimization algorithm (RQAOA); parameter transfer provides a mapping between RQAOA subproblems, which, by extending the support to the unit hypercube, induces a manifold alignment
Refashioning Campaign Justice: Amateur Investigators and the Making of a Counterrevolutionary Clique in Maoist China, 1955-1957
No full textThis thesis examines the local production of investigative practices during late 1950s Maoist political campaigns through a micro-historical study of the case of Du Gao, a young playwright accused of organizing a counterrevolutionary “clique” within Beijing’s literary and art circles between 1955 and 1957. Drawing primarily on the recovered parts of Du Gao’s personal dossiers – a collection of case files containing interrogation records, confessions and investigation reports – this study analyzes how cadres and other activists of Du’s work unit learned to create coherent narratives of counterrevolutionary crimes in response to the Party’s call for mass participation in political movements. The case of Du Gao demonstrates the unexpected outcomes brought about by the employment of non-professional investigators with vested interests. Charges of counterrevolutionary activity were inherently vague, and the official criteria by which such charges could be evaluated changed radically at different junctures. Faced with ideologically confusing official guidelines, these amateur investigators trained themselves by officially promoted model cases and often took the initiative to determine how suspects’ actions should be interpreted and categorized when Party directives proved insufficient. In some cases, investigators were also required to turn investigation reports into didactic materials for broader distribution, and in doing so, they actively promoted their own interpretations of the ideological principles underlying the campaigns. By tracing the evolution of Du Gao’s case across successive campaigns, this study highlights how personal relationships and professional rivalries contributed to and were in turn reshaped by decentralized practices of campaign justice, as well as the process through which investigators were motivated to help flesh out the controversial official concepts of “clique” and “factionalism” in order to legitimatize their own appropriation of the terms. At the same time, investigations also generated an overflow of information from the suspects’ past and present, which provided potentially incriminating materials that could easily be recycled in future campaign that supported a stricter understanding of the past