There was a high prevalence of cluster seizures in dogs with idiopathic epilepsy. Neutering status appears to influence cluster seizure occurrence with intact females more likely to experience more frequent episodes. Euthanasia is associated with frequency of cluster seizure episodes.

No abstract

recovery; Pakozdy and others (2011) reported that four cats survived and two of those cats were seizure-free, despite an initial resistance to antiepileptic therapy. In summary, necrosis of the hippocampus and piriform lobe may be a consequence of prolonged complex partial and generalised seizures in cats rather than representing a disease entity and, based on the recent literature and our personal experience, cats treated aggressively earlier on have a better prognosis. We have identified a cluster of affected cats in the Midlands and we want to alert colleagues to this clinical presentation and the need to recognise and control the seizures as soon as possible.

Imagery of facial expressions in Autism Spectrum Disorder (ASD) is likely impaired but has been very difficult to capture at a neurophysiological level. We developed an approach that allowed to directly link observation of emotional expressions and imagery in ASD, and to derive biomarkers that are able to classify abnormal imagery in ASD. To provide a handle between perception and action imagery cycles it is important to use visual stimuli exploring the dynamical nature of emotion representation. We conducted a case-control study providing a link between both visualization and mental imagery of dynamic facial expressions and investigated source responses to pure face-expression contrasts. We were able to replicate the same highly group discriminative neural signatures during action observation (dynamical face expressions) and imagery, in the precuneus. Larger activation in regions involved in imagery for the ASD group suggests that this effect is compensatory. We conducted a machine learning procedure to automatically identify these group differences, based on the EEG activity during mental imagery of facial expressions. We compared two classifiers and achieved an accuracy of 81% using 15 features (both linear and non-linear) of the signal from theta, high-beta and gamma bands extracted from right-parietal locations (matching the precuneus region), further confirming the findings regarding standard statistical analysis. This robust classification of signals resulting from imagery of dynamical expressions in ASD is surprising because it far and significantly exceeds the good classification already achieved with observation of neutral face expressions (74%). This novel neural correlate of emotional imagery in autism could potentially serve as a clinical interventional target for studies designed to improve facial expression recognition, or at least as an intervention biomarker.

No abstract