Paul Richard Carney - US grants

Epilepsy is a common neurological disorder that causes spontaneous recurrent seizures. In spite of major advances in pharmacology, neuroimaging, clinical neurophysiology, and neurosurgery, many patients remain disabled due to uncontrolled seizures. We propose to develop novel diagnostic and therapeutic tools, based on recent discoveries regarding dynamical mechanisms initiating epileptic seizures. We have found characteristic preictal dynamical changes, detectable in the electroencephalogram (EEG), preceding seizures by over 30 minutes (preictal transition, PT). More recently, other investigators have confirmed the presence of PDT. Our research indicates that the PT is demonstrable in the EEG in approximately 90 percent of seizures and that automated paradigms can be used to predict seizures. The potential to predict seizures in advance provides an opportunity to develop innovative diagnostic and therapeutic approaches. Our specific aims are: (1) Specific Aim 1. To continue the development of dynamic measures for the quantification of the spatiotemporal properties of the epileptic transition (years 1-3); (2) To develop specific pattern recognition algorithms for a seizure warning system (SWS) based upon the on-line features of the dynamical properties of brain electrical activity (years 1-4); To implement the dynamic features and pattern recognition algorithms in a SWS for on-line, real-time detection of the preictal dynamical transition (years 2-4); and (4) To evaluate the effects of therapeutic interventions during the preictal transition (years 1-5). The specific spatiotemporal patterns of the PT vary from seizure to seizure and patient to patient. Thus, a sensitive and reliable SWS will require sophisticated signal processing techniques. Dynamical measures will be augmented by other powerful analytic approaches, including multivariate time-series analysis, pattern recognition algorithms, and optimization techniques. To this end, we have gathered experts in signal processing, optimization, V.L.S.I., neurophysiology, neuroanatomy, epilepsy, and neurosurgery. The work will involve the coordination of several research sites throughout the University of Florida Campus including the Brain Dynamics Laboratory (Malcolm Randall V.A. Medical Center), Computer NeuroEngineering Laboratory College of Engineering), Center for Applied Optimization (College of Engineering), an In vitro Neurophysiology Research Laboratory (University of Florida Brain Institute), an In Vivo Neurophysiology Laboratory (Department of Pediatrics) and the Epilepsy Monitoring Laboratory (Shands Hospital). We anticipate that the proposed efforts will result in prototype diagnostic software and devices by the end of year 5. We also will obtain preliminary data that will be used for the design and testing of implantable devices that will activate pulsed therapeutic interventions during the preictal transition.

PROJECT SUMMARY The most recent statistics indicate that one out of 45 children is now diagnosed with an autism spectrum disorder (ASD). ASD individuals express a range of conditions from mild-to-severe intellectual disability, sleep disturbances, anxiety/mood disorders, self-injurious behavior, psychosis, and over 25% suffer from seizures. The complex comorbidities accompanying ASD challenge our ability to identify effective treatments. Cannabidiol (CBD) is considered as a potential medication to alleviate various ASD comorbidities. CBD has been reported to alleviate psychosis, anxiety, facilitate REM sleep, and suppress seizure activity, which are all outcomes that may benefit individuals with an ASD. A long-term objective of the proposed research is to characterize the in vivo effects of chronic CBD treatment in control rats and in an animal model showing well- defined and -characterized ASD-like neurobiological alterations and behavioral symptoms. The main hypothesis to be investigated is that CBD normalizes structural and functional deficits in this animal model. The present proposal will use the rat valproic acid (VPA) model of ASD to explore this hypothesis. Two specific aims are proposed. Specific aim 1 will determine the time-dependent effects of CBD on resting state functional connectivity in control and VPA rats. Studies will be accompanied by behavioral assessments to characterize the pharmacotherapeutic effects of CBD on ultrasonic vocalizations, motor activity, and social interactions. Specific aim 2 will determine the time-dependent effects of CBD on white and grey matter structural integrity, structural connectivity, and regional brain volumes in control and VPA rats. We will focus our investigation on critical brain regions affected in ASD, such as the amygdala, ventral hippocampus, mediodorsal thalamus, and temporal and anterior cingulate cortices. The long-term impact on public health of the proposed experiments will be: (1) a fully characterized relationship between changes in ASD behaviors, neural circuitry changes, and CBD treatment, (2) specific in vivo neurobiological data on the effects of CBD on neuronal connectivity and growth in the ASD brain, and (3) preclinical imaging biomarkers for in-depth magnetic resonance microscopic- level assessment of the effects of CBD treatment on changes in neural pathways in ASD and control brains.