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Over the course of a typical night, sleep is comprised of multiple different stages that involve changes in brainwave patterns. Intracranial EEG (iEEG) is an invasive brain recording technique used in hospital settings in epileptic patients to determine the focus of their seizure activity. The intracranial data recorded allows one to directly observe the neural activity of deep brain structures such as the hippocampus and to detect single unit activity and local field potentials, thus providing a level of physiological detail normally available only in animal studies. In this thesis we employ intracranial data to advance our understanding of sleep neural dynamics in humans, and to this end its focus is in two areas : (1) developing a way of sleep scoring iEEG data and (2) investigating the neural dynamics of a particular waveform found during sleep, the sleep spindle, and its role in memory consolidation. Typically, iEEG recordings do not include electrooculogram or electromyogram recordings, which are normally needed for sleep scoring—especially for scoring rapid-eye movement (REM) sleep. We identified differences in alpha power between wake and REM sleep to develop a methodological way to reliably differentiate between wake and REM sleep states. We also wanted to investigate the neural dynamics involved with a particular brainwave seen during sleep, the sleep spindle, which is thought to be important for sleep-mediated memory consolidation. Historically, sleep spindles were thought to occur synchronously across the cortex, but recent findings using iEEG have identified that sleep spindles can also be local. We utilized intracranial EEG to confirm previous findings that iEEG can identify local sleep spindles. In addition to identifying local sleep spindles, we aimed to investigate the potential role that sleep spindles have on learning and memory using standard targeted memory reactivation paradigms for iii both procedural and declarative memories. We found that local sleep spindles occurred at a specific time following auditory stimulation for both procedural and declarative memories. This work has opened up the use of iEEG recordings to investigations of REM sleep dynamics and laid the groundwork for examining the role of local sleep spindles in memory consolidation. Master of Science During a night of sleep, our brain goes through different stages that exhibit changes in brainwave patterns. Intracranial EEG (iEEG) is an invasive brain recording technique used in hospital settings in epileptic patients to determine the focus of their seizure activity; this particular brain recording technique allows one to observe the brain activity of deep brain structures. By using iEEG data, we aimed to (1) develop a way of sleep scoring iEEG data and (2) investigate the neural dynamics of a particular waveform found during sleep, the sleep spindle, and its role in memory consolidation. Electrooculograms (EOG) are used to record the electrical activity of eye movements, and electromyograms (EMG) are used to measure muscle activity. Both of these recording techniques, in addition to EEG, are needed for sleep scoring, especially rapid eye movement (REM) sleep. However, typical iEEG recordings do not have EOGs and EMGs applied to the patient. Using iEEG data, we were able to identify differences in a specific brainwave, the alpha rhythm, between wakeful brain activity and REM sleep brain activity. Furthermore, we were able to use this difference to reliably score REM sleep in iEEG data without the need for EOGs and EMGs. We also wanted to investigate the brainwave changes in a particular waveform, the sleep spindle, that has been thought to be important for sleep-mediated memory consolidation. Previous research using typical EEG recordings showed that sleep spindles occur synchronously across the cortex, but recent findings using iEEG have identified that sleep spindles can also occur asynchronously across the cortex. We replicated previous research showing that these local sleep spindles are identifiable using iEEG recordings. In addition to identifying local sleep spindles, we investigated the potential role that sleep spindles have on learning and memory. To do so, we used standard targeted memory reactivation paradigms for two types of memory: declarative and procedural memory. We found that local sleep spindles occurred at a specific time following auditory stimulation for both procedural and declarative memories. This work has opened up the use of iEEG recordings to investigations of REM sleep dynamics and laid the groundwork for examining the role of local sleep spindles in memory consolidation.

Understanding how different regions of the central nervous system (CNS) are affected by genetic insults is critical to advancing the study of CNS pathologies. The cerebellum is one such region which is disproportionately hypoplastic in the majority of cases of CASK gene mutation in humans. CASK is an enigmatic multi-domain scaffolding protein which plays a vital role in organizing protein complexes at the pre-synapse through interactions with both active zone proteins and trans-synaptic adhesion molecules such as liprins-α and neurexins. Mutations in the X-linked CASK gene in humans are largely post-natally lethal in the hemizygous condition and result in microcephaly with pontine and cerebellar hypoplasia (PCH) and also optic nerve hypoplasia (ONH) in heterozygous mutations. Herein, I used various molecular and genetic strategies to uncover the role of the CASK protein in brain function and pathogenesis of cerebellar hypoplasia associated with CASK mutations/deletions. First, using the face- and construct-validated heterozygous CASK knockout (Cask+/-) murine model, I conducted bulk RNA-sequencing and proteomics experiments from whole brain lysates to uncover changes in the Cask+/- brain. RNA-sequencing revealed the majority of changes to be broadly categorized into metabolic, nuclear, synaptic, and extracellular-matrix associated transcripts. Proteomics revealed the majority of changes cluster as synaptic proteins, metabolic proteins, and ribosomal subunits. Thus, absence of CASK in half of brain cells seems to affect synaptic protein content, cell metabolism, and protein homeostasis. Extending these observations, I conducted GFP-trap immunoprecipitation followed by tandem mass spectroscopy to reveal protein complexes in which CASK participates. Commensurate with proteomic changes, CASK was found to complex with synaptic proteins, metabolic proteins, cytoskeletal elements, ribosomal subunits, and protein folding machinery. Next, in order to investigate the pathogenesis of CASK-linked cerebellar hypoplasia, I utilized a human case of early truncation wherein the 27th arginine of CASK is converted to a stop codon. Immunohistochemical analysis of this brain revealed an upregulation of glial fibrillary acidic protein, a common marker for degenerative cell death. To mechanistically test the hypothesis that cerebellar hypoplasia results from cell death rather than developmental failure, I created a murine model wherein CASK is deleted from the majority of cerebellar cells post-development using Cre recombinase driven by the Calb2 promoter. Deleting CASK from all cerebellar granule neurons post-migration indeed leads to degeneration of the cerebellum via massive depletion of granule cells while sparing Purkinje cells. Overall, the cerebellum shrinks by approximately half in cross-sectional area and degeneration is accompanied by a collapsing of the molecular layer and of Purkinje cell dendrites. In addition, cerebellar degeneration presents with a profound locomotor ataxia. In conclusion, CASK seems to be affecting brain energy homeostasis and synaptic connections via interactions with metabolic proteins, synaptic proteins, and protein homeostatic elements. Further, alterations in brain volume associated with CASK-linked disorders is the result of degenerative cell death rather than developmental failure as previously posited. Doctor of Philosophy One of the main challenges facing modern neuroscience is the question of how constitutive mutations in genes present in every cell can cause different effects on different parts of the brain. CASK is one such gene which is expressed in every cell of the brain and, when mutated, typically results in an overall smaller brain volume. However, the cerebellum is one region of the brain involved in motor coordination which is disproportionately smaller than the rest of the brain. Through this gene, I investigate here two questions principally: (1) what is the role of the CASK protein in cells? And (2) how is the cerebellum differentially affected? Firstly, I conduct a molecular investigation into what changes in the brain of a mouse model of CASK deletion which recapitulates the majority of human cases found in girls. This genetic model results in half of cells in the body lacking CASK and leads to smaller brain volume with disproportionate reduction in cerebellum size, as in the human subjects. Using a variety of molecular and biochemical methods, I uncover that several classes of proteins are changed in this brain, primarily those associated metabolism and cell-to-cell communication. Further, my experiments indicate that CASK interacts with many of these proteins. Next, I use human cases as well as a novel mouse model to uncover the trajectory of CASK-linked reduction in cerebellar size. The human case indicates molecular signatures of cell death, a surprising finding given that CASK-linked disorders are thought to result from developmental failure. Investigating this mechanistically in a mouse model, I uncover that when CASK is deleted after development, cerebellar cells still die and the cerebellum actually shrinks. Thus, my work herein elucidates potential roles for the CASK molecule in cells and shows, for the first time, that CASK-linked cerebellar size diminishment is degenerative in nature rather than developmental. This degeneration of the cerebellum occurs very early on in infancy and so was missed until now. The most important implication is that a degenerative process could be halted with therapies other than relying exclusively on genetic therapies.

Modifiable health behaviors are a leading cause of mortality and chronic disease in the United States. Engagement in maladaptive health behaviors is linked to poor physical, psychological, and cognitive outcomes including increased risk of cardiovascular disease, Alzheimer's disease, anxiety, and depression. Using a neurobehavioral approach, I examined the hypothesis that neurobehaviors are impaired in clinical populations, and that exercise improves these neurobehaviors as well as the underlying mechanisms. In the first study, I found that a range of neurobehaviors are affected in individuals with obesity, indicating hyperactivity of the reward system and hypoactivity of the executive system. Using these neurobehaviors as predictors, I created a neurobehavioral model predicting obesity with an accuracy of 65%. In the second study, I examined neurobehaviors in a population of individuals in recovery from substance misuse. I found that neurobehaviors are altered in this population suggesting heightened activity of the executive system supports success in recovery. In the third study, I examined the effects of a long-term exercise program on a range of neurobehaviors and neurophysiology as measured through electroencephalography. I found that long-term exercise improved psychological state, memory, and attention. Additionally, I found that decreased cortical activity in response to exercise is associated with improvements in psychological state. Collectively, these findings suggest that there is a bi-directional relationship between the body and brain, with optimal physical health promoting optimal mental functioning. Additionally, these findings suggest that interventions that support improved neurobehaviors and neural circuitry are critical to promote engagement in positive health behaviors. Doctor of Philosophy Modifiable health behaviors are a leading cause of mortality and chronic disease in modern industrialized societies. Engagement in poor health behaviors is linked to increased risk of chronic disease affecting the body and brain including cardiovascular disease, Alzheimer's disease, anxiety, and depression. This dissertation explores the psychological and cognitive factors influencing engagement in healthy behaviors, and the ability of an exercise intervention to improve these factors as well as the underlying mechanisms. In the first study, I found that a range of neurobehavioral factors are impaired in individuals with obesity, and that these factors can be used to predict obesity. In the second study, I examined similar outcomes in a population of individuals in recovery from substance misuse, and found that neurobehaviors are altered in this population suggesting heightened activity of the executive system which supports successful recovery. In the third study I found that long-term exercise improved psychological and cognitive outcomes. Additionally, I found that changes in the electrical activity of the brain in response to exercise are associated with improvements in psychological state. Collectively, these findings suggest that there is a bi-directional relationship between the body and brain, with optimal physical health promoting optimal mental functioning. Additionally, these findings suggest that interventions that support improved neurobehaviors and neural circuitry are critical to promote engagement in positive health behaviors.