Diazepam induced sleep spindle increase correlates with cognitive recovery in a child with epileptic encephalopathy.

BACKGROUND: Continuous spike and wave of sleep with encephalopathy (CSWS) is a rare and severe developmental electroclinical epileptic encephalopathy characterized by seizures, abundant sleep activated interictal epileptiform discharges, and cognitive regression or deceleration of expected cognitive growth. The cause of the cognitive symptoms is unknown, and efforts to link epileptiform activity to cognitive function have been unrevealing. Converging lines of evidence implicate thalamocortical circuits in these disorders. Sleep spindles are generated and propagated by the same thalamocortical circuits that can generate spikes and, in healthy sleep, support memory consolidation. As such, sleep spindle deficits may provide a physiologically relevant mechanistic biomarker for cognitive dysfunction in epileptic encephalopathies. CASE PRESENTATION: We describe the longitudinal course of a child with CSWS with initial cognitive regression followed by dramatic cognitive improvement after treatment. Using validated automated detection algorithms, we analyzed electroencephalograms for epileptiform discharges and sleep spindles alongside contemporaneous neuropsychological evaluations over the course of the patient's disease. We found that sleep spindles increased dramatically with high-dose diazepam treatment, corresponding with marked improvements in cognitive performance. We also found that the sleep spindle rate was anticorrelated to spike rate, consistent with a competitively shared underlying thalamocortical circuitry. CONCLUSIONS: Epileptic encephalopathies are challenging electroclinical syndromes characterized by combined seizures and a deceleration or regression in cognitive skills over childhood. This report identifies thalamocortical circuit dysfunction in a case of epileptic encephalopathy and motivates future investigations of sleep spindles as a biomarker of cognitive function and a potential therapeutic target in this challenging disease.

Noninvasive neuroimaging enhances continuous neural tracking for robotic device control.

Brain-computer interfaces (BCIs) utilizing signals acquired with intracortical implants have achieved successful high-dimensional robotic device control useful for completing daily tasks. However, the substantial amount of medical and surgical expertise required to correctly implant and operate these systems significantly limits their use beyond a few clinical cases. A noninvasive counterpart requiring less intervention that can provide high-quality control would profoundly impact the integration of BCIs into the clinical and home setting. Here, we present and validate a noninvasive framework utilizing electroencephalography (EEG) to achieve the neural control of a robotic device for continuous random target tracking. This framework addresses and improves upon both the "brain" and "computer" components by respectively increasing user engagement through a continuous pursuit task and associated training paradigm, and the spatial resolution of noninvasive neural data through EEG source imaging. In all, our unique framework enhanced BCI learning by nearly 60% for traditional center-out tasks and by over 500% in the more realistic continuous pursuit task. We further demonstrated an additional enhancement in BCI control of almost 10% by using online noninvasive neuroimaging. Finally, this framework was deployed in a physical task, demonstrating a near seamless transition from the control of an unconstrained virtual cursor to the real-time control of a robotic arm. Such combined advances in the quality of neural decoding and the practical utility of noninvasive robotic arm control will have major implications on the eventual development and implementation of neurorobotics by means of noninvasive BCI.

Factors affecting the measurement of size and CT number in computed tomography.

Computed tomography scanners may be used to make anatomic size measurement; however, manipulating the viewer controls (especially the window center) can have a significant influence on the apparent size of structures in the image. A special phantom was constructed to study the effect of window center adjustments on the apparent size of lone cylindrical objects (no variation within slice thickness) and also for spherical objects (maximum variation within slice thickness). Using this phantom, the authors were able to identify several commonly encountered situations in which both the apparent size and CT numbers may be seriously in error. It was found that for cylindrical objects larger than about one transverse resolution element and aligned with the scanner axis, CT numbers may be determined accurately; however, the apparent diameter changes by several millimeters as the window center setting is changed. CT numbers for spheres are inaccurate when the diameter is comparable to or less than the slice thickness and, as a result, diameters of spheres cannot be measured accurately with fixed window center settings. Diameters of spheres can be measured accurately (+/- 1 mm) if the sphere is centered in the slice and the full width at half maximum of the CT number profile is used.

Fast FFT-based algorithm for phase estimation in speckle imaging.

This paper describes a fast direct algorithm for obtaining least-squares phase estimates from arrays of noisy phase differences. The algorithm uses the fast Fourier transform to diagonalize and decouple the system of equations which results from the application of the least-squares criterion. It is accurate and stable, and is perhaps an order of magnitude faster than the best iterative method. The effectiveness of the algorithm has been demonstrated by using it in connection with the Knox-Thompson speckle-imaging procedure to restore an optical object perturbed by simulated atmospheric turbulence. Representative results are discussed in the paper.

A distribution system for digital images from diverse image sources. Incorporating a local area network in an imaging environment.

This paper proposes a unified image-processing and viewing system as a viewing station and initially as the central file server in a unified digital image distribution and processing network, linking various digital image sources through a high speed data link and a common image format. The network allows for viewing and processing of all images produced within the complex and for locating viewing stations in any number of convenient areas. The system proposed can be slowly expanded to include all the digital images produced within the department of institution.