Eye and hand movements during reconstruction of spatial memory

© 2012 a Pion publicationRecent behavioural and biological evidence indicates common mechanisms serving working memory and attention (e.g., Awh et al, 2006 Neuroscience 139 201-208). This study explored the role of spatial attention and visual search in an adapted Corsi spatial memory task. Eye movements and touch responses were recorded from participants who recalled locations (signalled by colour or shape change) from an array presented either simultaneously or sequentially. The time delay between target presentation and recall (0, 5, or 10 s) and the number of locations to be remembered (2-5) were also manipulated. Analysis of the response phase revealed subjects were less accurate (touch data) and fixated longer (eye data) when responding to sequentially presented targets suggesting higher cognitive effort. Fixation duration on target at recall was also influenced by whether spatial location was initially signalled by colour or shape change. Finally, we found that the sequence tasks encouraged longer fixations on the signalled targets than simultaneous viewing during encoding, but no difference was observed during recall. We conclude that the attentional manipulations (colour/shape) mainly affected the eye movement parameters, whereas the memory manipulation (sequential versus simultaneous, number of items) mainly affected the performance of the hand during recall, and thus the latter is more important for ascertaining if an item is remembered or forgotten. In summary, the nature of the stimuli that is used and how it is presented play key roles in determining subject performance and behaviour during spatial memory tasks

Large NN reduction with the Twisted Eguchi-Kawai model

We examine the breaking of $Z_N$ symmetry recently reported for the Twisted Eguchi-Kawai model (TEK). We analyse the origin of this behaviour and propose simple modifications of twist and lattice action that could avoid the problem. Our results show no sign of symmetry breaking and allow us to obtain values of the large $N$ infinite volume string tension in agreement with extrapolations from results based upon straightforward methods.Comment: latex file 14 pages, 4 figure

Gonadotropic activity of a second relaxin-type peptide in starfish.

In starfish, a relaxin-like gonad-stimulating peptide (RGP) acts as a gonadotropin that triggers gamete maturation and spawning. In common with other relaxin/insulin superfamily peptides, RGP consists of an A- and a B-chain, with cross-linkages mediated by one intra- and two inter-chain disulfide bonds. In this study, a second relaxin-like peptide (RLP2) was identified in starfish species belonging to the orders Valvatida, Paxillosida, and Forcipulatida. Like RGP, RLP2 precursors comprise a signal peptide and a C-peptide in addition to the A- and B-chains. However, a unique cysteine motif [CC-(3X)-C-(10X)-C] is present in the A-chain of RLP2, which contrasts with the cysteine motif in other members of the relaxin/insulin superfamily [CC-(3X)-C-(8X)-C]. Importantly, in vitro pharmacological tests revealed that Patiria pectinifera RLP2 (Ppe-RLP2) and Asterias rubens RLP2 (Aru-RLP2) trigger shedding of mature eggs from ovaries of P. pectinifera and A. rubens, respectively. Furthermore, the potencies of Ppe-RLP2 and Aru-RLP2 as gonadotropic peptides were similar to those of Ppe-RGP and Aru-RGP, respectively, and the effect of RLP2 exhibited partial species-specificity. These findings indicate that two relaxin-type peptides regulate spawning in starfish and therefore we propose that RGP and RLP2 are renamed RGP1 and RGP2, respectively

Motor Sequence Learning in the Brain: The Long and Short of It

Motor sequence learning involves predictive processing that results in the anticipation of each component of a sequence of actions. In smooth pursuit, this predictive processing is required to decrease tracking errors between the eye and the stimulus. Current models for motor sequence learning suggest parallel mechanisms in the brain for acquiring sequences of differing complexity. We examined this model by comparing shorter versus longer sequences of pursuit eye movements during fMRI. In this way we were able to identify overlapping and distinct brain areas involved in simple versus more complex oculomotor learning. Participants revealed predictive pursuit eye movements from the second presentation of the stimulus in both short and long sequences. Brain imaging results indicated activation of parallel brain areas for the different sequence lengths that consisted of the Inferior Occipital Gyrus and the Cingulate as areas in common. In addition, distinct activation was found in more working memory related brain regions for the shorter sequences (e.g. the middle frontal cortex and dorsolateral prefrontal cortex), and higher activation in the frontal eye fields, supplementary motor cortex and motor cortex for the longer sequences, independent on the number of repetitions. These findings provide new evidence that there are parallel brain areas that involve working memory circuitry for short sequences, and more motoric areas when the sequence is longer and more cognitively demanding. Additionally, our findings are the first to show that the parallel brain regions involved in sequence learning in pursuit are independent of the number of repetitions, but contingent on sequence complexity

Capacitated Center Problems with Two-Sided Bounds and Outliers

In recent years, the capacitated center problems have attracted a lot of research interest. Given a set of vertices $V$, we want to find a subset of vertices $S$, called centers, such that the maximum cluster radius is minimized. Moreover, each center in $S$ should satisfy some capacity constraint, which could be an upper or lower bound on the number of vertices it can serve. Capacitated $k$-center problems with one-sided bounds (upper or lower) have been well studied in previous work, and a constant factor approximation was obtained. We are the first to study the capacitated center problem with both capacity lower and upper bounds (with or without outliers). We assume each vertex has a uniform lower bound and a non-uniform upper bound. For the case of opening exactly $k$ centers, we note that a generalization of a recent LP approach can achieve constant factor approximation algorithms for our problems. Our main contribution is a simple combinatorial algorithm for the case where there is no cardinality constraint on the number of open centers. Our combinatorial algorithm is simpler and achieves better constant approximation factor compared to the LP approach

Three-Dimensional Spectral-Domain Optical Coherence Tomography Data Analysis for Glaucoma Detection

Purpose: To develop a new three-dimensional (3D) spectral-domain optical coherence tomography (SD-OCT) data analysis method using a machine learning technique based on variable-size super pixel segmentation that efficiently utilizes full 3D dataset to improve the discrimination between early glaucomatous and healthy eyes. Methods: 192 eyes of 96 subjects (44 healthy, 59 glaucoma suspect and 89 glaucomatous eyes) were scanned with SD-OCT. Each SD-OCT cube dataset was first converted into 2D feature map based on retinal nerve fiber layer (RNFL) segmentation and then divided into various number of super pixels. Unlike the conventional super pixel having a fixed number of points, this newly developed variable-size super pixel is defined as a cluster of homogeneous adjacent pixels with variable size, shape and number. Features of super pixel map were extracted and used as inputs to machine classifier (LogitBoost adaptive boosting) to automatically identify diseased eyes. For discriminating performance assessment, area under the curve (AUC) of the receiver operating characteristics of the machine classifier outputs were compared with the conventional circumpapillary RNFL (cpRNFL) thickness measurements. Results: The super pixel analysis showed statistically significantly higher AUC than the cpRNFL (0.855 vs. 0.707, respectively, p = 0.031, Jackknife test) when glaucoma suspects were discriminated from healthy, while no significant difference was found when confirmed glaucoma eyes were discriminated from healthy eyes. Conclusions: A novel 3D OCT analysis technique performed at least as well as the cpRNFL in glaucoma discrimination and even better at glaucoma suspect discrimination. This new method has the potential to improve early detection of glaucomatous damage. © 2013 Xu et al

Risk factors for dementia development, frailty, and mortality in older adults with epilepsy – A population-based analysis

Objective: Although the prevalence of comorbid epilepsy and dementia is expected to increase, the impact is not well understood. Our objectives were to examine risk factors associated with incident dementia and the impact of frailty and dementia on mortality in older adults with epilepsy. Methods: The CALIBER scientific platform was used. People with incident epilepsy at or after age 65 were identified using Read codes and matched by age, sex, and general practitioner to a cohort without epilepsy (10:1). Baseline cohort characteristics were compared using conditional logistic regression models. Multivariate Cox proportional hazard regression models were used to examine the impact of frailty and dementia on mortality, and to assess risk factors for dementia development. Results: One thousand forty eight older adults with incident epilepsy were identified. The odds of having dementia at baseline were 7.39 [95% CI 5.21–10.50] times higher in older adults with epilepsy (n = 62, 5.92%) compared to older adults without epilepsy (n = 88, 0.86%). In the final multivariate Cox model (n = 326), age [HR: 1.20, 95% CI 1.09–1.32], Charlson comorbidity index score [HR: 1.26, 95% CI 1.10–1.44], and sleep disturbances [HR: 2.41, 95% CI 1.07–5.43] at baseline epilepsy diagnosis were significantly associated with an increased hazard of dementia development over the follow-up period. In a multivariate Cox model (n = 1047), age [HR: 1.07, 95% CI 1.03–1.11], baseline dementia [HR: 2.66, 95% CI 1.65–4.27] and baseline e-frailty index score [HR: 11.55, 95% CI 2.09–63.84] were significantly associated with a higher hazard of death among those with epilepsy. Female sex [HR: 0.77, 95% CI 0.59–0.99] was associated with a lower hazard of death. Significance: The odds of having dementia were higher in older adults with incident epilepsy. A higher comorbidity burden acts as a risk factor for dementia, while prevalent dementia and increasing frailty were associated with mortality

Online unit clustering in higher dimensions

We revisit the online Unit Clustering and Unit Covering problems in higher dimensions: Given a set of $n$ points in a metric space, that arrive one by one, Unit Clustering asks to partition the points into the minimum number of clusters (subsets) of diameter at most one; while Unit Covering asks to cover all points by the minimum number of balls of unit radius. In this paper, we work in $\mathbb{R}^d$ using the $L_\infty$ norm. We show that the competitive ratio of any online algorithm (deterministic or randomized) for Unit Clustering must depend on the dimension $d$. We also give a randomized online algorithm with competitive ratio $O(d^2)$ for Unit Clustering}of integer points (i.e., points in $\mathbb{Z}^d$, $d\in \mathbb{N}$, under $L_{\infty}$ norm). We show that the competitive ratio of any deterministic online algorithm for Unit Covering is at least $2^d$. This ratio is the best possible, as it can be attained by a simple deterministic algorithm that assigns points to a predefined set of unit cubes. We complement these results with some additional lower bounds for related problems in higher dimensions.Comment: 15 pages, 4 figures. A preliminary version appeared in the Proceedings of the 15th Workshop on Approximation and Online Algorithms (WAOA 2017

Evaluation of the effect of different wheats and xylanase supplementation on performance, nutrition and energy utilisation in broiler chicks

The aim of this study was to evaluate the performance, nutrient utilisation and energy metabolism of broiler chicks fed 8 different wheat samples, supplemented or not with xylanase. Seven-hundred sixty eight male broilers (1-day-old) were distributed to 16 experimental treatments (6 replicates per treatment). The treatments were in a factorial arrangement with 8 different wheats and 2 levels of xylanase (0 or 16,000 BXU/kg). The predicted apparent metabolisable energy (AME) of the wheat samples ranged from 13.0 to 13.9 MJ/kg and all diets were formulated to contain the same amount of wheat. Body weight gain (BWG) and feed intake (FI) were measured at 21 d, as was jejunal digesta viscosity, and feed conversion ratio (FCR) calculated. On day 24, one representative bird per pen was selected to calculate whole body energetics. At 21 d, 3 chicks per replicate were randomly allocated to metabolism cages for energy and nutrient utilisation determinations, and were continued on the experimental diets until 24-d-old. No interactions were observed for any performance response variables, ileal nutrient utilisation or digesta viscosity. Xylanase improved BWG and reduced FCR and digesta viscosity (P < 0.05). Wheat influenced dry matter (DM) utilisation and xylanase increased ileal digestible energy (P = 0.04). Xylanase also improved (P < 0.05) DM and nitrogen retention. Apparent metabolisable energy and AME corrected for nitrogen (AMEn) were subject to an interaction whereby wheats 2 and 6, which returned the lowest AME and AMEn values, responded to xylanase supplementation and the remainder did not. Net energy for production and the efficiency of energy use for production were not influenced by xylanase, but were affected by wheat (P < 0.05). Despite the significant differences between wheats with regards to their nutrient utilisation and energy metabolism in birds, xylanase removed this variance and resulted in more homogeneous performance

The Maximal U(1)LU(1)_L Inverse Seesaw from d=5d=5 Operator and Oscillating Asymmetric Sneutrino Dark Matter

The maximal $U(1)_L$ supersymmetric inverse seesaw mechanism (M$L$SIS) provides a natural way to relate asymmetric dark matter (ADM) with neutrino physics. In this paper we point out that, M$L$SIS is a natural outcome if one dynamically realizes the inverse seesaw mechanism in the next-to minimal supersymmetric standard model (NMSSM) via the dimension-five operator $(N)^2S^2/M_*$, with $S$ the NMSSM singlet developing TeV scale VEV; it slightly violates lepton number due to the suppression by the fundamental scale $M_*$, thus preserving $U(1)_L$ maximally. The resulting sneutrino is a distinguishable ADM candidate, oscillating and favored to have weak scale mass. A fairly large annihilating cross section of such a heavy ADM is available due to the presence of singlet.Comment: journal versio