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

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

How does our motor system determine its learning rate?

Motor learning is driven by movement errors. The speed of learning can be quantified by the learning rate, which is the proportion of an error that is corrected for in the planning of the next movement. Previous studies have shown that the learning rate depends on the reliability of the error signal and on the uncertainty of the motor system’s own state. These dependences are in agreement with the predictions of the Kalman filter, which is a state estimator that can be used to determine the optimal learning rate for each movement such that the expected movement error is minimized. Here we test whether not only the average behaviour is optimal, as the previous studies showed, but if the learning rate is chosen optimally in every individual movement. Subjects made repeated movements to visual targets with their unseen hand. They received visual feedback about their endpoint error immediately after each movement. The reliability of these error-signals was varied across three conditions. The results are inconsistent with the predictions of the Kalman filter because correction for large errors in the beginning of a series of movements to a fixed target was not as fast as predicted and the learning rates for the extent and the direction of the movements did not differ in the way predicted by the Kalman filter. Instead, a simpler model that uses the same learning rate for all movements with the same error-signal reliability can explain the data. We conclude that our brain does not apply state estimation to determine the optimal planning correction for every individual movement, but it employs a simpler strategy of using a fixed learning rate for all movements with the same level of error-signal reliability

Under-five mortality: spatial-temporal clusters in Ifakara HDSS in South-eastern Tanzania.

BACKGROUND\ud \ud Childhood mortality remains an important subject, particularly in sub-Saharan Africa where levels are still unacceptably high. To achieve the set Millennium Development Goals 4, calls for comprehensive application of the proven cost-effective interventions. Understanding spatial clustering of childhood mortality can provide a guide in targeting the interventions in a more strategic approach to the population where mortality is highest and the interventions are most likely to make an impact.\ud \ud METHODS\ud \ud Annual child mortality rates were calculated for each village, using person-years observed as the denominator. Kulldorff's spatial scan statistic was used for the identification and testing of childhood mortality clusters. All under-five deaths that occurred within a 10-year period from 1997 to 2006 were included in the analysis. Villages were used as units of clusters; all 25 health and demographic surveillance sites (HDSS) villages in the Ifakara health and demographic surveillance area were included.\ud \ud RESULTS\ud \ud Of the 10 years of analysis, statistically significant spatial clustering was identified in only 2 years (1998 and 2001). In 1998, the statistically significant cluster (p < 0.01) was composed of nine villages. A total of 106 childhood deaths were observed against an expected 77.3. The other statistically significant cluster (p < 0.05) identified in 2001 was composed of only one village. In this cluster, 36 childhood deaths were observed compared to 20.3 expected. Purely temporal analysis indicated that the year 2003 was a significant cluster (p < 0.05). Total deaths were 393 and expected were 335.8. Spatial-temporal analysis showed that nine villages were identified as statistically significant clusters (p < 0.05) for the period covering January 1997-December 1998. Total observed deaths in this cluster were 205 while 150.7 were expected.\ud \ud CONCLUSION\ud \ud There is evidence of spatial clustering in childhood mortality within the Ifakara HDSS. Further investigations are needed to explore the source of clustering and identify strategies of reaching the cluster population with the existing effective interventions. However, that should happen alongside delivery of interventions to the broader population

Early star-forming galaxies and the reionization of the Universe

Star forming galaxies represent a valuable tracer of cosmic history. Recent observational progress with Hubble Space Telescope has led to the discovery and study of the earliest-known galaxies corresponding to a period when the Universe was only ~800 million years old. Intense ultraviolet radiation from these early galaxies probably induced a major event in cosmic history: the reionization of intergalactic hydrogen. New techniques are being developed to understand the properties of these most distant galaxies and determine their influence on the evolution of the universe.Comment: Review article appearing in Nature. This posting reflects a submitted version of the review formatted by the authors, in accordance with Nature publication policies. For the official, published version of the review, please see http://www.nature.com/nature/archive/index.htm

Proton acceleration enhanced by a plasma jet in expanding foils undergoing relativistic transparency

Ion acceleration driven by the interaction of an ultraintense (2x10^20 Wcm^-2) laser pulse with an ultrathin (40nm) foil target is experimentally and numerically investigated. Protons accelerated by sheath fields and via laser radiation pressure are angularly separated and identified based on their directionality and signature features (e.g. transverse instabilities) in the measured spatial-intensity distribution. A low divergence, high energy proton component is also detected when the heated target electrons expand and the target becomes relativistically transparent during the interaction. 2D and 3D particle-in-cell (PIC) simulations indicate that under these conditions a plasma jet is formed at the target rear, supported by a self-generated azimuthal magnetic field, which extends into the expanded layer of sheath-accelerated protons. Electrons trapped within this jet are directly accelerated to super-thermal energies by the portion of the laser pulse transmitted through the target. The resulting streaming of the electrons into the ion layers enhances the energy of protons in the vicinity of the jet. Through the addition of a controlled prepulse, the maximum energy of these protons is demonstrated experimentally and numerically to be sensitive to the picosecond rising edge prole of the laser pulse

Electrophysiological Heterogeneity of Fast-Spiking Interneurons: Chandelier versus Basket Cells

In the prefrontal cortex, parvalbumin-positive inhibitory neurons play a prominent role in the neural circuitry that subserves working memory, and alterations in these neurons contribute to the pathophysiology of schizophrenia. Two morphologically distinct classes of parvalbumin neurons that target the perisomatic region of pyramidal neurons, chandelier cells (ChCs) and basket cells (BCs), are generally thought to have the same "fast-spiking" phenotype, which is characterized by a short action potential and high frequency firing without adaptation. However, findings from studies in different species suggest that certain electrophysiological membrane properties might differ between these two cell classes. In this study, we assessed the physiological heterogeneity of fast-spiking interneurons as a function of two factors: species (macaque monkey vs. rat) and morphology (chandelier vs. basket). We showed previously that electrophysiological membrane properties of BCs differ between these two species. Here, for the first time, we report differences in ChCs membrane properties between monkey and rat. We also found that a number of membrane properties differentiate ChCs from BCs. Some of these differences were species-independent (e.g., fast and medium afterhyperpolarization, firing frequency, and depolarizing sag), whereas the differences in the first spike latency between ChCs and BCs were species-specific. Our findings indicate that different combinations of electrophysiological membrane properties distinguish ChCs from BCs in rodents and primates. Such electrophysiological differences between ChCs and BCs likely contribute to their distinctive roles in cortical circuitry in each species. © 2013 Povysheva et al

Regeneration versus scarring in vertebrate appendages and heart

Injuries to complex human organs, such as the limbs and the heart, result in pathological conditions, for which we often lack adequate treatments. While modern regenerative approaches are based on the transplantation of stem cell-derived cells, natural regeneration in lower vertebrates, such as zebrafish and newts, relies predominantly on the intrinsic plasticity of mature tissues. This property involves local activation of the remaining material at the site of injury to promote cell division, cell migration and complete reproduction of the missing structure. It remains an unresolved question why adult mammals are not equally competent to reactivate morphogenetic programmes. Although organ regeneration depends strongly on the proliferative properties of cells in the injured tissue, it is apparent that various organismic factors, such as innervation, vascularization, hormones, metabolism and the immune system, can affect this process. Here, we focus on a correlation between the regenerative capacity and cellular specialization in the context of functional demands, as illustrated by appendages and heart in diverse vertebrates. Elucidation of the differences between homologous regenerative and non-regenerative tissues from various animal models is essential for understanding the applicability of lessons learned from the study of regenerative biology to clinical strategies for the treatment of injured human organs