A Literature Review of Similarities Between and Among Patients With Autism Spectrum Disorder and Epilepsy.

Autism spectrum disorder (ASD) has been shown to be associated with various other conditions, and most commonly, ASD has been demonstrated to be linked to epilepsy. ASD and epilepsy have been observed to exhibit high rates of comorbidity, even when compared to the co-occurrence of other disorders with similar pathologies. At present, nearly one-half of the individuals diagnosed with ASD also have been diagnosed with comorbid epilepsy. Research suggests that both conditions likely share similarities in their underlying disease pathophysiology, possibly associated with disturbances in the central nervous system (CNS), and may be linked to an imbalance between excitation and inhibition in the brain. Meanwhile, it remains unclear whether one condition is the consequence of the other, as the pathologies of both disorders are commonly linked to many different underlying signal transduction mechanisms. In this review, we aim to investigate the co-occurrence of ASD and epilepsy, with the intent of gaining insights into the similarities in pathophysiology that both conditions present with. Elucidating the underlying disease pathophysiology as a result of both disorders could lead to a better understanding of the underlying mechanism of disease activity that drives co-occurrence, as well as provide insight into the underlying mechanisms of each condition individually.

Critical and Ictal Phases in Simulated EEG Signals on a Small-World Network.

Healthy brain function is marked by neuronal network dynamics at or near the critical phase, which separates regimes of instability and stasis. A failure to remain at this critical point can lead to neurological disorders such as epilepsy, which is associated with pathological synchronization of neuronal oscillations. Using full Hodgkin-Huxley (HH) simulations on a Small-World Network, we are able to generate synthetic electroencephalogram (EEG) signals with intervals corresponding to seizure (ictal) or non-seizure (interictal) states that can occur based on the hyperexcitability of the artificial neurons and the strength and topology of the synaptic connections between them. These interictal simulations can be further classified into scale-free critical phases and disjoint subcritical exponential phases. By changing the HH parameters, we can model seizures due to a variety of causes, including traumatic brain injury (TBI), congenital channelopathies, and idiopathic etiologies, as well as the effects of anticonvulsant drugs. The results of this work may be used to help identify parameters from actual patient EEG or electrocorticographic (ECoG) data associated with ictogenesis, as well as generating simulated data for training machine-learning seizure prediction algorithms.

A health information technology glossary for novices.

To deliver information to providers across the U.S., the Agency for Healthcare Research and Quality's National Resource Center for Health IT (NRC) created a public domain Web site containing a number of tools and resources. Specifically lacking from this Web site is a glossary of health IT terminology. To address this omission and respond to requests from Web site users,the Regenstrief Institute created the Health IT Glossary. This glossary is designed to provide novices, providers and others new to health IT, with a single source to find basic definitions for a broad range of terms, consistent with the Office of the National Coordinator (ONC) effort. The glossary is a living document, and feedback is welcomed from the health informatics community.

Facilitating informatics knowledge dissemination: targeted implementation resources for health care providers.

The AHRQ National Resource Center for Health IT (NRC) maintains a public Web site with a large repository of diverse informatics knowledge resources. The NRC recently added a new tool -- the Health IT Bibliography -- to better disseminate key resources to health care organizations. The bibliography filters resources from the NRC's larger online knowledge library, providing quicker access for those who desire to learn more about implementing clinical IT applications.