The theme of this dissertation is to improve the exploration of patient subgroups with a precision medicine lens, specifically using repeated measures data to evaluate longitudinal trajectories of clinical, biological, and lifestyle measures. Our proposed methodological contributions fall into two branches of statistical methodology: undirected graphical models and functional data analysis. In the first part of this dissertation, our goal was to study longitudinal networks of brain imaging biomarkers and clinical symptoms during the time leading up to manifest Huntington's disease diagnosis among patients with known genetic risk of disease. Understanding the interrelationships between measures may improve our ability to identify patients who are nearing disease onset and who therefore might be ideal patients for clinical trial recruitment. Gaussian graphical models are a powerful approach for network modeling, and several extensions to these models have been developed to estimate time-varying networks. We propose a time-varying Gaussian graphical model specifically for a time scale that is centered on an anchoring event such as disease diagnosis. Our method contains several novel components intended to 1) reduce bias known to stem from 𝑙₁ penalization, and 2) improve temporal smoothness in network edge strength and structure. These novel components include time-varying adaptive lasso weights, as well as a combination of 𝑙₁, 𝑙₂, and 𝑙₀ penalization. We demonstrated via simulation studies that our proposed approach, as well as more computationally efficient subsets of our full proposed approach, have superior performance compared to existing methods. We applied our proposed approach to the PREDICT-HD study and found that the network edges did change with time leading up to and beyond diagnosis, with change points occurring at different times for different edges. For clinical symptoms, bradykinesia became well-connected with symptoms from several other domains. For imaging measures, we observed a loss of connection over time among gray matter regions, white matter regions, and the hippocampus. In the second part of this dissertation, we consider time-varying network models for settings in which data are not all Gaussian. We sought to compare longitudinal clinical symptom networks between patients with neuropathologically-defined Alzheimer's disease (AD) vs. neuropathologically-defined Lewy body dementia (LBD), two common types of dementia which can often be clinically misdiagnosed. Given that the clinical measures of interest were largely non-Gaussian, we examined the literature for undirected graphical models for mixed data types. We then proposed an extension to the existing time-varying mixed graphical model by adding time-varying adaptive lasso weights, modeling time in reverse in order to treat neuropathological diagnoses as baseline covariates. The proposed adaptive lasso extension serves a two-fold purpose: they alleviate well-known bias of 𝑙₁ penalization and they encourage temporal smoothness in edge estimation. We demonstrated the improved performance of our extension in simulations studies. Applying our method to the National Alzheimer's Coordinating Center database, we found that the edge structure surrounding the Wechsler Memory Scale Revised (WMS-R) Logical Memory parts IA (immediate recall) and IIA (delayed recall) may contain important markers for discriminant analysis of AD and LBD populations. In the third part of this dissertation, we explored a methodologically distinct area of research from the first two parts, moving from graphical models to functional data analysis. Our goal was to extract meaningful chronotypes, or phenotypes of circadian rhythms, from activity count data collected from accelerometers. Existing approaches for analyzing diurnal patterns using these data, including the cosinor model and functional principal components analysis, have revealed and quantified population-level diurnal patterns, but considerable subject-level variability remained uncaptured in features such as wake/sleep times and activity intensity. This remaining informative variability could provide a better understanding of chronotypes, or behavioral manifestations of one’s underlying 24-hour rhythm. Curve registration, or alignment, is a technique in functional data analysis that separates "vertical" variability in activity intensity from "horizontal" variability in time-dependent markers like wake and sleep times. We developed a parametric registration framework for 24-hour accelerometric rest-activity profiles that are represented as dichotomized into epoch-level states of activity or rest. Specifically, we estimated subject-specific piecewise linear time-warping functions parametrized with a small set of parameters. We applied this method to data from the Baltimore Longitudinal Study of Aging and illustrated how estimated parameters can give a more flexible quantification of chronotypes compared to traditional approaches.

Enhancing stress resilience could prevent a variety of stress-induced disorders and thus reduce the global burden of psychiatric disease. It was previously reported that a single administration of the N-methyl-D-aspartate receptor (NMDAR) antagonist (R,S)-ketamine prior to stress could prevent stress-induced fear and behavioral despair in male mice, suggesting the possibility of developing prophylactic drugs to prevent psychiatric disorders. However, it was still unknown whether prophylactic agents could be effective in female mice, if other drugs could exert prophylactic actions, and how prophylactics could alter mechanisms in the brain to increase stress resilience. We hypothesized that targeting different receptors that could significantly alter neuroplasticity in the hippocampus (HPC) would be protective against stress. We first sought to determine whether stereospecific metabolites of (R,S)-ketamine, (2S,6R)-hydroxnorketamine ((2S,6S)-HNK) and (2R,6R)-hydroxynorketamine ((2R,6R)-HNK), could attenuate stress-induced behaviors in male and female mice. Next, we aimed to test the prophylactic efficacy of fluoroethylnormemantine (FENM), a novel-composition NMDAR antagonist derived from memantine. Subsequently, we examined the protective effects of 3 different serotonin type IV receptor (5-HT4R) agonists against stress. Finally, we sought to determine whether dual targeting of the NMDAR and 5-HT4R could exert additive effects in enhancing resilience to stress against a wide variety of stress-induced behaviors. Drug efficacy was assayed in male and female mice using a battery of stress models and behavioral tests including: contextual fear conditioning (CFC), cued fear conditioning, contextual fear discrimination (CFD), learned helplessness (LH), chronic immobilization stress (CIS), paired-pulse inhibition (PPI), the forced swim test (FST), sucrose splash test (SST), open field (OF), elevated plus maze (EPM), marble burying (MB), and novelty-suppressed feeding (NSF). Liquid chromatography-mass spectrometry (LC-MS), immunohistochemistry, Western blotting, patch clamp electrophysiology, ovariectomy (OVX), and hormone replacement techniques were used to examine how prophylactic drugs alter brain function and test whether ovarian hormones mediate the protective effects of prophylactic compounds in female mice. We show that (R,S)-ketamine, (2S,6S)-HNK, (2R,6R)-HNK, FENM, and 3 different 5-HT4R agonists are protective against specific stress-induced behaviors when administered in both male and female mice. We demonstrate that multimodally targeting NMDARs and 5-HT4Rs can broadly enhance resilience to protect against a variety of stressinduced maladaptive behaviors in both sexes. Finally, we determine a common mechanism by which various prophylactic compounds, despite targeting different receptors, attenuate bursts of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR)-mediated activity to exert their protective effects. Together, these data: 1) uncover a variety of novel drug candidates for further preclinical and clinical development, 2) indicate a potential neural substrate underlying resilience to stress, and 3) reveal neurobiological mechanisms contributing to the psychopathology of psychiatric disease.

The question of how we form memories has fascinated scientists for decades. The hippocampus and surrounding medial-temporal-lobe (MTL) structures are critical for both memory and spatial navigation, yet we do not fully understand the neuronal representations used to support these behaviors. Much research has examined how the MTL neurally represents spatial information, such as with “place cells” that represent an animal’s current location or “head-direction cells” that code for an animal’s current heading. In addition to attending to current spatial locations, navigating to remote destinations is a common part of daily life. In this dissertation I investigate how the human MTL represents the relevant information in a goal-directed spatial-memory task. Specifically, I analyze single-neuron and local field potential (LFP) data from neurosurgical patients with respect to their spatial navigation and memory behavior, with a focus on probing the link between neuronal firing, oscillations, and memory. In Chapter 2, I find that the firing rates of many MTL neurons during navigation significantly change depending on the position of the current spatial target. In addition, I observe neurons whose firing rates during navigation are tuned to specific heading directions in the environment, and others whose activity changes depending on the timing within the trial. By showing that neurons in our task represent remote locations rather than the subject’s own position, my results suggest that the human MTL can represent remote spatial information according to task demands. In Chapter 3, I find that during encoding the left hippocampus exhibits greater low theta power for subsequently recalled items compared to unrecalled items. I also find that high frequency activity and neuronal firing in the hippocampus distinguish between item-filled compared to empty chests. Finally, I find that MTL cells’ firing rates and the differential timing of spikes relative to low frequency oscillations in the LFP distinguish between subsequent recall conditions. These results provide evidence for a distinct processing state during the encoding of successful spatial memory in the human MTL. Overall, in this thesis I show new aspects of the neural code for spatial memories, and how the human MTL supports these representations.

The human brain relies on the complex interactions of distinct brain regions to support cognitive processes. The interplay between the hippocampus and neocortical regions plays a key role in the formation, storage, and retrieval of long-term episodic memories. Oscillatory activities during sleep are a fundamental mechanism that binds distributed neuronal networks into functionally coherent ensembles. However, the large-scale hippocampal-neocortical oscillatory mechanisms that support flexible modulation of long-term memory remain poorly understood. Furthermore, alterations to physiologic spatiotemporal patterns that are essential for intact memory function can result in pathophysiology in brain disorders such as focal epilepsy. Investigating how epileptic network activity disrupts connectivity in distributed networks and the organization of oscillatory activity are additional crucial areas that require further research. Our experiments on rodents and human patients with epilepsy have provided valuable insights into these mechanisms. In rodents, we used high-density microelectrode arrays in tandem with hippocampal probes to analyze intracranial electroencephalography (iEEG) from multiple cortical regions and the hippocampus. We identified key hippocampal-cortical oscillatory biomarkers that were differentially coordinated based on the age, strength, and type of memory. We also analyzed iEEG from patients with focal epilepsy and demonstrated how individualized pattern of pathologic-physiologic coupling can disrupt large-scale memory circuits. Our findings may offer new opportunities for therapies aimed at addressing distributed network dysfunction in various neuropsychiatric disorders.

In the mammalian brain, information is believed to be encoded at the cellular level through alterations in synaptic weights. Furthermore, changes in synaptic strength are correlated with structural changes at dendritic spines, such as growth and shrinkage, which may serve to shape inputs into functional domains and increase the computational power of neurons. Neuroanatomical alterations in dendritic spines have been described in humans with intellectual disability, further supporting the relationship between neuronal structure and function. Fragile X Syndrome (FXS) is the most common single-gene neurodevelopmental disorder, and a hallmark feature of this disorder is the increased density of long spines in several brain regions including the hippocampus. Identification of FXS spines as filopodia-like has led to the theory that these spines are immature, and that altered spine development underlies the cognitive dysfunction in this disorder. However, the functional capacity of the long spines observed in FXS is not well understood. For my thesis work, I used two photon imaging, glutamate uncaging and electrophysiology to perform a high-resolution characterization of dendritic spine structure, function, and plasticity in the hippocampus of the FXS mouse model in order to determine what gives rise to these alterations and how this contributes to the observed neuronal dysfunction in this disorder. From my dissertation research, I find that while Fmr1 KO neurons have region-specific alterations in both dendrite and spine morphology, the functional responses of single synapses in FXS mutant neurons are grossly normal. FXS spines respond proportionally to increased levels of glutamate release, and the linear relationship between structure and function is preserved at these synapses. In addition, structural plasticity, both growth and shrinkage, at single inputs is similar in magnitude to control neurons following synaptic potentiation and depression, respectively. However, upon more detailed examination of structural plasticity, either at single or multiple inputs, I find several deficits. First, following structural plasticity, I observe aberrant heterosynaptic plasticity in Fmr1 KO neurons, where unstimulated mutant spines located in close proximity to activated spines become significantly larger compared to neighboring spines in control neurons, which showed no significant change in size. Next, competition for mGluR-LTD does not occur in Fmr1 KO neurons, leading to an increase in spines that undergo spine shrinkage. I conclude from this work that while spine morphology is altered in FXS, spines develop with functional synapses that have the capacity to express bidirectional forms of structural plasticity. However, these spines undergo abnormal structural plasticity across stimulated inputs, leading to the expression of aberrant heterosynaptic structural plasticity. As activity is integrated across a dendritic branch, such excess plasticity observed in Fmr1 KO neurons could contribute to the altered spine morphology as well as cognitive dysfunction observed in FXS.

No description available.

No description available.

Food-caching birds like black-capped chickadees offer unique advantages for studying neural processes underlying episodic memory. Chickadees exhibit prodigious memories—they can cache thousands of food items throughout their environment and use memory to navigate back to these hidden food stores. Additionally, their hippocampal circuit is simplified relative to that of mammals, containing far fewer inputs and outputs. However, little work had been done to understand the neural processes underlying these animal’s memory abilities. This thesis details several projects that aimed to better establish food-caching birds as an animal model of memory for systems neuroscience. In Chapter 2, we described the creation of behavioral tasks to utilize the chickadees’ natural memory behavior. Here, we monitored chickadees’ behavior while they cached food into a grid of sites covered by rubber flaps. We then applied probabilistic modeling to examine how different strategies guided birds’ choices during caching and retrieval. Chickadees used memories of the contents of individual cache sites in a context-dependent manner, avoiding sites that contained food during caching and returning to those same sites during retrieval. These results demonstrate memory flexibility in an animal in a tractable spatial paradigm. In Chapter 3, we asked whether the bird brain had a region that was similar to the entorhinal cortex. We found that the dorsal lateral hippocampal formation (DL/CDL), one of the main inputs to the chickadee hippocampus, sharded marked anatomical and physiological similarities to the mammalian entorhinal cortex. We first used retrograde and anterograde tracing to examine the connectivity between DL/CDL and the hippocampus, as well as DL and the rest of the pallium. We found that the topographic patterns of DL/CDL input were similar to those of the mammalian entorhinal cortex. We next examined the physiology of DL, using 1-photon calcium imaging to monitor neural activity while birds performed a random foraging task. Like the entorhinal cortex, DL contained multi-field ‘grid-like’ spatial neurons, as well as border cells, head direction cells and speed-tuned cells. Collectively, these results establish DL/CDL as an entorhinal cortex analog. In Chapter 4, we expanded the anatomical analysis to examine all of the inputs to the hippocampal formation. We varied our injections of retrograde tracers along the hippocampal long and transverse axes to examine if, like in mammals, there were topographic input patterns along these major axes. We found many patterns in input that were highly reminiscent of mammalian connectivity: like in rodents, visual pallial input preferentially innervated the septal portion of the hippocampus, while amygdala input preferentially targeted the temporal portion. These results further solidify the homology between the mammalian and avian hippocampal formations. Collectively, through these sets of experiments, we have laid the groundwork for studying the black-capped chickadee in a modern neuroscience context.

Neuronal culture systems have many applications, such as basic research into neuronal structure, function, and connectivity as well as research into diseases, conditions, and injuries affecting the brain and its components. In vitro dissociated neuronal systems have typically been derived from embryonic brain tissue, most commonly from the hippocampus of E18 rats. This practice has been motivated by difficulties in supporting regeneration, functional recovery and long-term survival of adult neurons in vitro. The overall focus of this dissertation research was to develop a dissociated neuronal culture system from human and animal adult brain tissue, one more functionally and developmentally correlative to the mature brain. To that end, this work was divided into five interrelated topics: development of an adult in vitro neuronal culture system comprised of electrically functional, mitotically stable, developmentally mature neurons from the hippocampus of adult rats; creation of stable two-cell neuronal networks for the study of synaptic communication in vitro; coupling of electrically active adult neurons to microelectrode arrays for high-throughput data collection and analysis; identification of inadequacies in embryonic neuronal culture systems and proving that adult neuronal culture systems were not deficient in similar areas; augmentation of the rat hippocampal culture system to allow for the culture and maintenance of electrically active human neurons for months in vitro. The overall hypothesis for this dissertation project was that tissue engineered in vitro systems comprised of neurons dissociated from mature adult brain tissue could be developed using microfabrication, defined medium formulations, optimized culture and maintenance parameters, and cell-cycle control. Mature differentiated glutamatergic neurons were extracted from hippocampal brain tissue and processed to purify neurons and remove tissue debris. Terminally differentiated rat hippocampal neurons recovered in vitro and displayed mature neuronal morphology. Extracellular glutamate in the culture medium promoted neuronal recovery of electrical function and activity. After recovery, essential growth factors in the culture medium caused adult neurons to reenter the cell cycle and divide multiple times. Only after reaching confluence did some neurons stop dividing. Strategies for inhibition of neuronal mitotic division were investigated, and manipulation of the cdk5 pathway was ultimately found to prevent division in vitro. Prevention of mitotic division as well as optimization of culture and maintenance parameters resulted in a neuronal culture system derived from adult rats in which the neuronal morphology, cytoskeleton and surface protein expression patterns, and electrical activity closely mirrored mature, terminally differentiated adult neurons in vivo. Improvements were also made to the growth surfaces on which neurons attached, regenerated, and survived long-term. Culture surfaces, in this case glass cover slips, were modified with the chemical substrate N-1 (3-(trimethoxysilyl) propyl)-diethylenetriamine (DETA) to create a covalently modified interface with exposed cell-adhesive triamine groups. DETA chemical surfaces were also further modified to create high-resolution patterns, useful in creating engineered two-cell networks of adult hippocampal neurons. Adult hippocampal neurons were also coupled to microelectrode array systems (MEAs) and recovered functionally, fired spontaneously, and reacted to synaptic antagonists in a manner consistent to adult neurons in vivo. Last, neurons from the brains of deceased Alzheimer's disease (AD) patients and from brain tissue excised during surgery for Parkinson's disease (PD), Essential Tremor (ET), and brain tumor were isolated and cultured, with these neurons morphological regenerating and electrically recovering in vitro.

Memory-related disorders, such as Alzheimer’s disease and dementia, are devastating and often irreparable given our limited knowledge of how to effectively treat them. Animal studies have made significant advances in identifying neural correlates of memory, but in order to develop better interventions for memory loss, we need a deeper understanding of the neural basis of memory in the human brain. The main focus of my research is examining large-scale electrophysiological correlates of memory and learning in humans. In my studies, I recorded local field potential (LFP) data directly from the brains of neurosurgical patients performing memory tasks. First, in Chapter 2, I investigated the prevalence of sharp-wave ripples—synchronous high-frequency bursts of LFP activity—in the human hippocampus and cortex. I found that spectral characteristics of detected ripples closely matched those of other previously described high-frequency patterns in the human brain, thus raising important considerations for the detection and definition of ripple-like activity in humans. For my second study, in Chapter 3, I examined the impact of scopolamine, a cholinergic blocker, in the human hippocampal area during episodic memory. I found that the memory impairment caused by scopolamine was coupled to disruptions of both the amplitude and phase alignment of theta oscillations (2-10 Hz) during encoding. These findings suggest that cholinergic circuits support memory by coordinating the temporal dynamics of theta oscillations. Finally, in Chapter 4, I explored how brain oscillations in the medial temporal lobe (MTL) support learning. I found that subjects’ accuracy in a spatial memory task improved significantly within and across sessions, and that these short- and long-term learning effects were predicted by greater theta synchrony. My research translates important memory- and learning-related signals from animal studies, and extends those findings by revealing spectral patterns that are specifically relevant to humans. Together, my studies point to a key electrophysiological phenomenon underlying memory and learning in humans: the synchrony of neuronal activity in the brain. In particular, my results suggest that the temporal coordination of neuronal activity offered by brain oscillations, especially those in the theta frequency band, is vital for successful memory and learning. These findings expand our mechanistic understanding of the neurophysiology of human memory and learning, and suggest that improving the temporal coordination of neuronal activity in the MTL may provide a novel route to treating memory- and learning-related disorders.