Frontal cortex stroke-induced impairment in spatial working memory on the trial-unique nonmatching-to-location task in mice.

Stroke-induced cognitive impairments are of significant concern, however mechanisms that underpin these impairments remain poorly understood and researched. To further characterise cognitive impairments in our frontal cortex stroke model, and to align our assessments with what is used clinically, we tested young C57BL/6J mice trained in operant touchscreen chambers to complete the trial-unique nonmatched-to-location (TUNL) task. Based on baseline performance, animals were given either stroke (n = 12) or sham (n = 12) surgery using a photothrombosis model, bilaterally targeting the frontal cortex.

Stroke Induces a BDNF-Dependent Improvement in Cognitive Flexibility in Aged Mice.

Stroke remains a leading cause of disability worldwide. Recently, we have established an animal model of stroke that results in delayed impairment in spatial memory, allowing us to better investigate cognitive deficits. Young and aged brains show different recovery profiles after stroke; therefore, we assessed aged-related differences in poststroke cognition.

Very fast best-fit circular and elliptical boundaries by chord data.

Many machine vision tasks require objects to be delineated during image segmentation that have shapes that are well approximated by circles or ellipses. Due to their computational efficiency least-squares, algebraic methods are a popular choice for fitting an elliptic primitive to noisy image data when real-time processing is required. These methods, however, suffer from biased estimates and sensitivity to outlier data.

Increasing the information acquisition volume in iris recognition systems.

A significant hurdle for the widespread adoption of iris recognition in security applications is that the typically small imaging volume for eye placement results in systems that are not user friendly. Separable cubic phase plates at the lens pupil have been shown to ameliorate this disadvantage by increasing the depth of field. However, these phase masks have limitations on how efficiently they can capture the information-bearing spatial frequencies in iris images.

Efficient metric for pupil-phase engineering.

Pupil-phase engineering is a design process in which pupil-phase masks are optimized for performance characteristics by minimizing a cost function. To reduce computational complexity for optimizing focal depth, a cost function based on the second derivative of the optical transfer function with respect to misfocus at the origin is proposed. Efficient formulas for computing this metric are derived, and a design is presented to demonstrate that this metric can be used to predict insensitivity of the system to large values of misfocus.