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We perform a systematic data analysis on high resolution (0.5–12 kHz) multiarray microelectrode recordings from an animal model of spontaneous limbic epilepsy, to investigate the role of high frequency oscillations and the occurrence of early precursors for seizures. Results of spectral analysis confirm the importance of very high frequency oscillations (even greater than 600 Hz) in normal (healthy) and abnormal (epileptic) hippocampus. Furthermore, we show that the measures of Recurrence Quantification Analysis (RQA) and Recurrence Time Statistics (RTS) are successful in indicating, rather uniquely, the onset of ictal state and the occurrence of some warnings/precursors during the pre-ictal state, in contrast to the linear measures investigated.

Manufacturers and the media have raised the possibility that viewing stereoscopic 3D television (S3D TV) may cause temporary disruption to balance and visuomotor coordination. We looked for evidence of such effects in a laboratory-based study. Four hundred and thirty-three people aged 4–82 years old carried out tests of balance and coordination before and after viewing an 80 min movie in either conventional 2D or stereoscopic 3D, while wearing two triaxial accelerometers. Accelerometry produced little evidence of any change in body motion associated with S3D TV. We found no evidence that viewing the movie in S3D causes a detectable impairment in balance or in visuomotor coordination.

An essential requirement for the representation of functional patterns in complex neural networks, such as the mammalian cerebral cortex, is the existence of stable network activations within a limited critical range. In this range, the activity of neural populations in the network persists between the extremes of quickly dying out, or activating the whole network. The latter case of large-scale activation is visible in the transition to the epileptic state. After describing the shift to large-scale synchronization we study the role of network topology on this transition. Whereas standard explanations for balanced activity involve populations of inhibitory neurons for limiting activity, we observe how network topology limits activity spreading. A random or small-world topology results in low or high levels of activation. In contrast, a cluster hierarchy based on neuroanatomical knowledge—from cortical clusters such as the visual cortex at the highest level, to individual columns at the lowest level—enables sustained activity in neural systems and prevents large-scale activation as observed during epileptic seizures. The containment of activation critically depends on the ratio of inter-cluster connections. Such topological inhibition by means of a modular hierarchy, in addition to neuronal inhibition, might help to maintain healthy levels of neural activity.

Selecting signal processing parameters in optical imaging by utilizing the change in Determinism, a measure introduced in Recurrence Quantification Analysis, provides a novel method using the change in residual noise Determinism for improving noise quantification and removal across signals exhibiting disparate underlying tissue pathologies. The method illustrates an improved process for selecting filtering parameters and how using measured signal-to-noise ratio alone can lead to improper parameter selection.

In recent years radiofrequency energy sources have been utilized in patients with atrial fibrillation to ablate atrial tissue and restore normal sinus rhythm. Radiofrequency ablations significantly minimize time in surgery, and hence postoperative complications, but as yet do not duplicate the ablation transmurality achieved by "cut and sew" techniques. Studies of post-operative fibrillation recurrence attribute treatment failures to the lack of obtaining full lesion transmurality at the time of surgery. Unfortunately, no method or standard exists for validating in-vivo ablation transmurality. Using high-resolution optical mapping studies with Langendorff perfused heart preparations, we are able to correlate spatiotemporal electrical activity with ablation line transmurality, thus providing a means for validating ablation transmurality in order to quantify the type and number of ablation lines used in order to tailor ablation therapies to individual patient needs.

We examine data from a stimulated Brillouin scattering experiment with very small feedback (<

Background: During early development, neural circuits fire spontaneously, generating activity episodes with complex spatiotemporal patterns. Recordings of spontaneous activity have been made in many parts of the nervous system over the last 20 years, reporting developmental changes in activity patterns and the effects of various genetic perturbations. Results: We present a curated repository of multielectrode array recordings of spontaneous activity in developing mouse and ferret retina. The data have been annotated with minimal metadata and converted into the HDF5 format. This paper describes the structure of the data, along with examples of reproducible research using these data files. We also demonstrate how these data can be analysed in the CARMEN workflow system. This article is written as a literate programming document; all programs and data described here are freely available. Conclusions: 1. We hope this repository will lead to novel analysis of spontaneous activity recorded in different laboratories. 2. We encourage published data to be added to the repository. 3. This repository serves as an example of how multielectrode array recordings can be stored for long-term reuse.

Of clinical interest are methods and tools to differentiate and localize epileptic foci, for surgical (and possibly other forms of intervention in the future) intervention. Previously, high frequency events, ripples (80-200 Hz) and fast ripples (200-500 Hz), were identified from both in vitro and in vivo recordings of epileptic foci tissue [1], but results were limited in that the data acquired was from single electrodes, and so simultaneous recordings of network activity were not obtained, and thus network dynamics within such regions were not analyzed. Using a 10 x10 grid Utah array electrodes for recording from focal epileptic and control slices of human tissue (control tissue being non-epileptic cortical tissue excised during extraction of a sub-cortical tumor or focus area), we are able to probe the network microstructure and, more critically, how these networks (epileptic focus and control) differ from each other. For analysis, we used standard low-frequency bands (theta, delta, alpha, gamma) as well as higher frequency bands (80-200 Hz, 200-500 Hz) for characteristic signals differentiating the epileptic and control populations. The raw data was filtered at these separate bands and networks were extracted from the filtered data using phase synchronization and cross-correlation as a means to detect phase and amplitude signal similarities, respectively. Once the networks were extracted, we could examine different network measures to determine if network properties were statistically different or not. We measured small-worldness characteristics such as the Clustering Coefficient (which measures how similar a reference node’s neighbour’s connectivity are to the reference node), Characteristic Path Length (which measures how many connections it takes on average to get from any one node to any other node in the network), degree (number of connections each node has), % change of network volatility, Small Worldness coefficient (Normalized Clustering Coefficient/Normalized Characteristic Path Length), modularity Q, and statistical information such as the number and size of (unthresholded) network clusters were extracted and compared across datasets and population.