Natürliches Verhalten findet in diversen sensorischen und motorischen Modalitäten statt, und hängt vom sensorischen Feedback ab, welches das Verhalten kontinuierlich anpasst. Um die zu Grunde liegenden neuronalen Korrelate natürlichen Verhaltens untersuchen zu können, ist die Nutzung moderner Aufnahmetechniken notwendig, die oft die Kopffixierung des Tieres erfordern. Diese Einschränkung wurde mit verschiedenen Methoden angegangen, unter anderem mit virtueller Realität in Kombination mit einem luftgelagerten Ball oder Laufradsystemen. Diese Systeme haben jedoch zahlreiche Nachteile. Wir haben das Air-Track-System entwickelt, eine neue Methode für eine leicht zu bauende und nur minimale Computerverarbeitung erfordernde Verhaltensumgebung. Der Air-Track ist ein leichtgewichtiges physisches Labyrinth, das auf einem Lufttisch schwebt und alle Eigenschaften der "echten" Welt hat, einschließlich mehrerer sensorischer Modalitäten, die eng an die motorischen Handlungen gekoppelt sind. Um dieses System zu testen, trainierten wir Mäuse in Go/No-Go- und two-alternative forced choice-Aufgaben. Mäuse wählten Arme und unterschieden. Ein Kamerasystem mit eigens entwickelter Kontrolle zeichnete die Position des Tieres auf und generierte Daten, die zur Berechnung von Reaktionszeiten in den visuellen und somatosensorischen Unterscheidungsaufgaben verwendet werden konnten. Um die Bewegung des Air-Track-Systems aufzuzeichnen, entwickelten wir ein "Pixy"-System zur Bewegungsverfolgung. Wir erweiterten die Entwicklung dann zu einer allgemeinen und automatisierten optischen Methode für die Echtzeit- ebenso wie die nachträgliche Verfolgung der Mausbewegungen, und zwar sowohl für kopffixierte als auch frei bewegliche Tiere. Das Air-Track-System und die Pixy-Bewegungsverfolgung sind zweckdienliche Einheitslösungen, die die Kombination von quantitativem natürlichen Verhalten mit nahezu jedem System zur Aufzeichnung und Manipulation der Hirnaktivität in einem Hirnforschungs-Labor ermöglichen. / Natural behavior occurs in multiple sensory and motor modalities and is dependent on sensory feedback that constantly adjusts behavior. To investigate the underlying neuronal correlates of natural behavior, it is useful to have access to state-of-the-art recording equipment that frequently requires head-fixation. This limitation has been addressed with various approaches such as virtual reality with air ball or treadmill systems. However, these systems have several disadvantages. Here we developed a novel tool, the Air-Track system, an easy to build, head-fixed behavioral environment that requires only minimal computational processing. The Air-Track is a lightweight, physical maze floating on an air table that has all the properties of the “real” world, including multiple sensory modalities tightly coupled to motor actions. To test this system, we trained mice in Go/No-Go and two-alternative forced choice tasks. A custom-controlled camera system monitored animal location, and generated data that could be used to calculate reaction times in the visual and somatosensory discrimination tasks. To track the motion of the Air Track system we developed a “Pixy” tracking system based on an off-the-shelf camera system (Pixy). We then expanded the development into a generalized and automated optical method for real-time and post-hoc tracking of mice motor behavior in both head-fixed and freely moving conditions. Air-Track and Pixy-Tracking systems are convenient “one-size-fits-all” solutions that facilitate the combination of quantitative natural behavior with virtually any system for monitoring or manipulating brain activity in a neuroscience laboratory.

Little is understood about off-host behavior and ecology of immature Amblyomma maculatum Koch (Gulf Coast tick). A more complete understanding of this tick is essential to protect human and animal health. My research focused on seasonality and distribution of immatures in Mississippi, potential suitability of some insect and human hosts to larvae, and aspects of nymphal questing behavior. A single larva was collected (third off-host collection reported) when sampling A. maculatum habitat using a novel device. Collection of this larva in November expands the stage’s known seasonality and confirmed a prediction concerning seasonality of larval A. maculatum. Low frequency of immatures (8.3%) confirmed that they’re incredibly difficult to collect off-host. Nymphal collections peaked in March, and known seasonality was extended for both nymphs and adults. I examined known records, elucidating seasonality and distribution of A. maculatum in Mississippi. Either multiple generations per year or diapause are responsible for observed bi-modal distribution of immature collections. Additionally, I compiled the most extensive host record of immature A. maculatum in Mississippi and investigated seasonality patterns using USDA plant hardiness zones. I compiled the most complete record of ticks found on arthropods. Amblyomma americanum and A. maculatum were both confirmed to crawl onto arthropods, giving support to occasional, unintentional dispersal by phoresy. There was no conclusive evidence that larval A. maculatum feed on arthropods, however data supported feeding by larval A. americanum. These results have interesting implications regarding evolution of pathogens/endosymbionts. I provided the first evidence that larval A. maculatum can attach to humans. Rickettsia parkeri, a human pathogen transmitted by this species has recently been shown to be capable of transovarial transmission. Therefore, larval A. maculatum may provide another avenue of transmission. I have demonstrated that A. maculatum are difficult to collect off-host in part because they prefer to quest low to the ground. In choice studies, 5-cm-tall stems were most likely to be occupied by nymphs released into an array of stems. Low vapor pressure deficit encouraged questing, while higher VPD and warmer temperature increased questing height. These results may have implications in understanding host-seeking behavior in other tick species as well.