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Mental illness is currently diagnosed using subjective observational criteria as outlined in the 5th Edition of the Diagnostic and Statistical Manual (DSM-V), yet many have argued for the medicalization of the diagnosis of mental illness by incorporating biomedical and neuroanatomical criteria. The following literature review explores the neural circuit responsible for regulating emotion, as well as the structural and chemical alterations to this circuit that have been shown to correlate with aggressive and/or violent behaviors characteristic of certain types of mental illness. The neural circuit regulating emotion is comprised of the prefrontal cortex, the subcortical limbic system, the dopaminergic pathway, the serotonergic pathway, catecholaminergic neurons, and GABAergic neurons. Alterations to these structures or chemicals have been associated with major depressive disorder, suicidal ideations, substance use disorders, schizophrenia, and personality disorders. Medicalization of mental illness has the potential to serve two purposes – first, to standardize diagnosis and treatment of mental illness, and second, to decrease the stigma often associated with mental illness – and to improve outcomes for those patients living with mental illness.

Behaviors are a product of underlying neural circuits, yet there is a paucity of mechanistic information about how nervous systems contribute to the repeated evolution of similar behaviors. Theoretical studies have predicted that the same behavioral output can be generated by neural circuits with different properties. Here, we test the theory in biological circuits by comparing the central pattern generator (CPG) circuits underlying swimming behaviors in nudibranchs (Mollusca, Gastropoda, Euthyneura, Nudipleura). In comparative studies of neural circuits, neurotransmitter content can serve as landmarks or molecular markers for neuron types. Here, we created a comprehensive map of GABA-immunoreactive neurons in six Nudipleura species. None of the known swim CPG neurons were GABA-ir, but they were located next to identifiable GABA-ir neurons/clusters. Despite strong conservation of the GABA-ergic system, there were differences, particularly in the buccal ganglia, which may represent adaptive changes. We applied our knowledge of neurotransmitter distribution along with morphological traits to identify the neuron type Si1 in Flabellina, a species that swims via whole body left-right (LR) flexions and in Tritonia, a dorsal-ventral (DV) swimming species. Si1 is a CPG member of the LR species Melibe, whereas its homologue in the LR species Dendronotus is not. In Flabellina, Si1 was part of the LR CPG and despite having similar synaptic connections as Flabellina and Melibe, Si1 in Tritonia was not part of its DV swim CPG. Side by side circuit comparison of Flabellina, Melibe and Dendronotus revealed different combinations of circuit architecture and modulation resulting in different circuit configurations for LR swimming. This includes differences in the role and activity pattern of Si1, sensitivity to curare and the effect of homologues of C2, a DV CPG neuron, on the LR motor pattern. These results collectively reveal three different circuit variations for generating the same behavior. It suggests that the neural substrate from which behaviors arise is phylogenetically constrained. While this neural substrate can be configured in multiple different ways to generate the same outcome, the possibilities are finite and, as seen here, similar structural and functional neural motifs are used in the evolution of these circuits.

In mammals, spatial learning and memory depend on neural processing carried out in the hippocampal formation. Interestingly, extracellular recordings from behaving animals have shown that cells in this region exhibit spatially modulated activity patterns, thus providing insights into the neural activity underlying spatial behaviour. One area within the hippocampal formation, layer II of the medial entorhinal cortex, houses cells that encode a grid-like map of space using a firing rate code. At the same time, oscillatory signals at distinct theta (4–12 Hz) and gamma (30–120 Hz) frequencies are also present in layer II, providing a substrate for a timing code. To understand how layer II of the medial entorhinal cortex produces these outputs I sought to characterise the electrical properties and functional computational architecture of its microcircuitry. The functionality of any neural circuit depends on the electrical properties of its constituent cells. Because the grid cells in layer II are likely to be stellate cells, I used the perforated patch-clamp technique to accurately assess the intrinsic excitable properties of this cell type. Compared to whole-cell recordings, these recordings indicate that some intrinsic properties of stellate cells, such as spike clustering, which is revealed to be robust, are more likely to play a functional role in circuit computation. Conversely, other intrinsic properties, such as spontaneous membrane potential fluctuations, which are confirmed to be insufficiently stable to support reliable interference patterns, are revealed to be less likely than other, more robust electrical properties to play a direct role in circuit function. The characteristic connectivity profiles of different cell types are also critical for circuit function. To investigate cell type-specific connectivity in layer II I used optogenetic stimulation in combination with in vitro electrophysiology to record synaptic activity in different cell types while selectively activating distinct subpopulations of cells with light. Using this method I found that connections between stellate cells are absent or very rare and that communication between stellate cells is instead mediated by strong feedback inhibition from fast-spiking interneurons. Dissecting oscillatory activity in neural circuits may be important for establishing functionally relevant circuit architecture and dynamics but is difficult in vivo. I accomplished this in vitro by recapitulating the interacting theta and gamma rhythms that are observed in vivo with an optogenetic method. I found that locally driving a subset of neurons in the layer II microcircuit at theta frequency with a light stimiulus produced a nested field rhythm at gamma frequency that was also evident as rhythmic inhibition onto stellate cells. Critically, these interacting rhythms closely resembled those recorded from behaving animals. In addition, I found that this thetanested gamma is sufficiently regular to act as a clock-like reference signal, indicating its potential role in implementing a timing code. To functionally dissect the circuit I performed multiple simultaneous whole-cell patch-clamp recordings during circuit activation. These recordings revealed how feedback interactions between stellate cells and fast-spiking interneurons underpin the theta-nested gamma rhythm. Together, these results suggest that feedback inhibition in layer II acts as a common substrate for theta-nested gamma oscillations and possibly also grid firing fields, thereby providing a framework for understanding how computations are carried out in layer II of the medial entorhinal cortex.

No description available.

Sensory overload is the feeling of over-stimulation that may lead to increased anxiety and panic in individuals with psychiatric disorders such as autism, post traumatic stress disorder, etc. Understanding visual processing is crucial to enhancing our treatments for disorders where sensory overload is a symptom. How do changes in internal states such as stress or hunger alter visual processing? This project aims to explore how visual processing is affected by signaling in the hypothalamus, an area of the brain regulating changes in internal states and stress. Preliminary studies revealed there are a number of neurons projecting from the lateral area of the hypothalamus to the visual cortex. We want to understand the specific location, identity, and neural circuits of these neurons. Visual cortex neurons were retrogradely traced to identify which inputs originate from the hypothalamus, and the geographical location of these cells was mapped out. The molecular identities of these projection neurons was further explored using specific RNAScope probes to check if those cells are expressing any of four genes most commonly expressed in the hypothalamus: Gal, Crh, Hcrt, and Pmch. This exploration will help us understand the type of signals communicated from the hypothalamic nuclei to the visual cortex to modulate visual processing.

The alpha-, beta-, and gamma-Protocadherins (gamma-Pcdhs) are cadherin superfamily adhesion molecules encoded by clustered gene families. The 22 gamma-Pcdhs are combinatorially expressed in the central nervous system (CNS) by neurons and astrocytes, and play critical roles in synaptogenesis, dendrite arborization, and the survival of subsets of neurons. The gamma-Pcdhs promiscuously form cis-multimers that interact strictly homophilically in trans (Molumby et al., 2016; Schreiner and Weiner, 2010); the alpha- and beta-Pcdhs were subsequently shown to interact in a similar homophilic manner (Rubinstein et al., 2015; Thu et al., 2014). The Pcdh gene clusters thus have the potential to generate millions of distinct adhesive interfaces, providing CNS cells with molecular identities that shape neuronal morphology. We demonstrated previously that, in mice lacking the gamma-Pcdhs in the cerebral cortex, pyramidal neurons exhibit severely reduced dendrite arborization (Garrett et al., 2012a). This, combined with many studies of gamma-Pcdh interactions in vitro, suggests that homophilic, adhesive gamma-Pcdh interactions between neurons, and between neurons and glia, provide a positive signal for dendrite growth. However, in retinal starburst amacrine cells and cerebellar Purkinje cells, loss of the gamma-Pcdhs resulted in aberrant dendrite fasciculation and self-crossing (Lefebvre et al., 2012), suggesting that these molecules can mediate repulsive self-avoidance between a neuron’s own dendrites. In Chapter I of this thesis I utilized transgenic mice to manipulate expression in vivo, to show that the complexity of a cortical neuron’s dendritic arbor is determined by homophilic gamma-Pcdh isoform matching with other cells. Expression of the same single isoform in a neuron can result in either exuberant, or minimal, dendrite complexity depending on whether surrounding cells express the same isoform. Additionally, loss of gamma-Pcdh in astrocytes, or induced astrocyte-neuron mis-matching, reduces dendrite complexity cell non-autonomously. This indicates a neuron’s pattern of connectivity is indeed regulated by specific interactions between cells that are distinct from the repulsive self-avoidance seen in isoneuronal processes of planar cell types. In addition to modulating dendrite branch development, the gamma-Pcdhs have been shown to regulate the progression of spinal cord synaptogenesis (Garrett and Weiner, 2009). A role for these molecules in cortical dendritic spines and synapses, however, had yet not been examined. In Chapter II of this thesis, I provide evidence that the gamma-Pcdhs negatively regulate synapse formation and spine morphogenesis in forebrain neurons. Mice lacking all gamma-Pcdhs in the cortex exhibit significantly increased spine and synapse density in vivo, while spine density is significantly decreased in mice overexpressing one of the 22 gamma-Pcdh isoforms. To explain this functional result, we present in vitro evidence to show that gamma-Pcdhs physically and functionally interact with the synaptic cell adhesion molecule neuroligin-1. This work suggests a potential new mechanism by which gamma-Pcdhs regulate the “choice” between dendrite arbor growth and formation and/or stabilization of dendritic spines and synapses in the developing brain. Given that disruptions in the pattern and density of dendritic arbors and spines are a hallmark of neurodevelopmental disorders such as autism and Down, Rett, and fragile X syndromes, my work may provide the basic science foundation for future therapeutic approaches focused on Pcdhs and their associated signaling pathways.

The retina contains neural circuits that carry out computations as complex as object motion sensing, pattern recognition, and position anticipation. Models of some of these circuits have been recently discovered. A remarkable outcome of these efforts is that all such models can be constructed out of a limited set of components such as linear filters, instantaneous nonlinearities, and feedback loops. The present study explores the consequences of assuming that these components can be used to construct models for all retinal circuits. I recorded extracellularly from several retinal ganglion cells while stimulating the photoreceptors with a movie rich in temporal and spatial frequencies. Then I wrote a computer program to fit their responses by searching through large spaces of anatomically reasonable models built from a small set of circuit components. The program considers the input and output of the retinal circuit and learns its behavior without over-fitting, as verified by running the final model against previously unseen data. In other words, the program learns how to imitate the behavior of a live neural circuit and predicts its responses to new stimuli. This technique resulted in new models of retinal circuits that outperform all existing ones when run on complex spatially structured stimuli. The fitted models demonstrate, for example, that for most cells the center--surround structure is achieved in two stages, and that for some cells feedback is more accurately described by two feedback loops rather than one. Moreover, the models are able to make predictions about the behavior of cells buried deep within the retina, and such predictions were verified by independent sharp-electrode recordings. I will present these results, together with a brief collection of ideas and methods for furthering these modeling efforts in the future. / Physics

Mice display robust and stereotyped behaviors towards pups: virgin males typically attack pups, while virgin females and sexually experienced males display parental care. I show here that virgin males that are genetically impaired in vomeronasal sensing do not attack pups and are parental, suggesting a key role of the vomeronasal system in controlling male infanticide. In addition, we have identified putative vomeronasal receptors (or receptor groups) for the detection of pup odors, thus uncovering new tools for the molecular and genetic dissection of male infanticide. Further, we have uncovered galanin-expressing neurons in the medial preoptic area (MPOA) as key regulators of male and female parental behavior. Genetic ablation of MPOA galanin- neurons results in dramatic impairment of parental responses in both virgin females and sexually experienced males. In addition, optogenetic activation of these cells in virgin males suppresses infanticide and induces pup grooming. Thus, MPOA galanin-expressing neurons emerge as an essential node of regulation of innate behavior in the hypothalamus that orchestrates male and female parenting while opposing vomeronasal circuits underlying infanticide. Our results provide an entry point for the genetic and circuit-level dissection of mouse parental behavior and its modulation by social experience.

A central theme of this dissertation is nervous system plasticity. Activity-dependent plasticity and dopaminergic modulation are two processes by which neural circuits adapt their function to developmental and environmental changes. These processes are involved in basic cognitive functions and can contribute to neurological disorder. An important goal in modern neurobiology is understanding how genotypic variation influences plasticity, and leveraging the quantitative genetics resources in model organisms is a valuable component of this endeavor. To this end I investigated activity-dependent plasticity and dopaminergic modulation in Drosophila melanogaster larvae using neurobiological and genetic approaches. Larval mechanosensory behavior is described in Chapter 2. The behavioral experiments in that chapter provide a system to study mechanisms of plasticity and decision-making, while the electrophysiological characterization shows that sensory-motor output depends on neural activity levels of the circuit. This system is used to investigate activity-dependent plasticity in Chapter 3, i.e., habituation to repetitive tactile stimuli. In Chapter 4, those assays are combined with pharmacological manipulations, genetic manipulations, and other experimental paradigms to investigate dopaminergic modulation. Bioinformatics analyses were used in Chapter 5 to characterize natural genetic variation and the influence of single nucleotide polymorphisms on dopamine-related gene expression. The impact and suggested future directions based on this work are discussed in Chapter 6. Dopamine also modulates cardiomyocytes. Chapter 7 describes biochemical pathways that mediate dopaminergic modulation of heart rate. The final two chapters describe neurobiology research endeavors that are separate from my work on dopamine. Experiments that have helped characterize a role for Serf, a gene that codes for a small protein with previously unknown function, are described in Chapter 8. In the final chapter I describe optogenetic behavioral and electrophysiology preparations that are being integrated into high school classrooms and undergraduate physiology laboratories. Assessment of student motivation and learning outcomes in response to those experiments is also discussed.