Attention lights up new object representations before the old ones fade away

We investigated how attention shifts from one object to another by recording neuronal activity in the primary visual cortex. Monkeys performed a contour-grouping task in which they had to select a target curve and ignore a distractor curve. Some trials required a shift of attention, because the target and distractor curves were switched during the course of the trial. We monitored the dynamics of this attention shift in area V1, in which neuronal responses evoked by the target curve are stronger than those evoked by the distractor. The reallocation of attention was associated with a rapid and strong enhancement of responses to the newly attended curve, followed, after ∼60 ms, by a weaker suppression of responses to the curve from which attention was removed. We conclude that attention can be rapidly allocated to a new object before it disengages from the previously attended one. Copyright © 2006 Society for Neuroscience

Robinson's Computerized Strabismus Model Comes of Age

In this article we review our further development of D.A. Robinson's computerized strabismus model. First, an extensive literature study has been carried out to get more accurate data on the anatomy of the average eye and the eye muscles, and about how these vary with age and with refraction. Secondly, the force-length relations that represent the mechanical characteristics of the eye muscles in the model have been determined more accurately in vivo recently, and the model was changed accordingly. Thirdly, many parameters that were free in the original model and not derived from in vivo measurements were replaced by derivatives from in vivo measurements or made redundant. Fourthly, the ease of operation was improved greatly and the algorithms were made so much faster that a calculation for nine positions of gaze now takes ten seconds on a handheld HP 200LX Palmtop. The predictions of the model compared well with clinical results in horizontal muscle surgery, oblique muscle surgery, forced duction tests and abducens, oculomotor or trochlear palsies. Consequently, complex strabismus surgery in our clinic is now guided by the predictions of the computerized model

Sixty strabismus cases operated with the Computerized Strabismus Model 1.0: When does it benefit, when not?

While, in routine strabismus surgery, empirical guidelines and experience are the best in judging which eye muscles to operate, a complex case may need a unique surgical approach, the consequences of which cannot always be envisioned in detail. We sought to improve the results of surgery in these cases by preoperative simulation of each case with the Computerized Strabismus Model 1.0 (CSM). The basis of this model was laid by David A. Robinson. It has been improved by us over the past years to the point that it can be used clinically. Improvements concerned, for example, the mechanics of the eye muscles and the anatomy of insertions and origins. The ease of operation has been improved and the algorithms have been made so much faster that a full calculation for 9 positions of gaze now takes 10 seconds on a hand-held Hewlett Packard 200LX Palmtop. From 1994 onwards, all cases to be operated in our department which were more complex than straightforward horizontal rectus muscle surgery were simulated in the model preoperatively. The predictions of the model compared well with the actual result of surgery in most cases. The model was particularly good in handling complex and unique disorders of motility. However, the model could not reliably predict the effect of strabismus surgery in cases with mechanical restrictions of motilit

The effects of pair-wise and higher order correlations on the firing rate of a post-synaptic neuron

Coincident firing of neurons projecting to a common target cell is likely to raise the probability of firing of this post-synaptic cell. Therefore synchronized firing constitutes a significant event for post-synaptic neurons and is likely to play a role in neuronal information processing. Physiological data on synchronized firing in cortical networks is primarily based on paired recordings and cross-correlation analysis. However, pair-wise correlations among all inputs onto a post-synaptic neuron do not uniquely determine the distribution of simultaneous post-synaptic events. We develop a framework in order to calculate the amount of synchronous firing that, based on maximum entropy, should exist in a homogeneous neural network in which the neurons have known pair-wise correlations and higher order structure is absent. According to the distribution of maximal entropy, synchronous events in which a large proportion of the neurons participates should exist, even in the case of weak pair-wise correlations. Network simulations also exhibit these highly synchronous events in the case of weak pair-wise correlations. If such a group of neurons provides input to a common post-synaptic target, these network bursts may enhance the impact of this input, especially in the case of a high post-synaptic threshold. Unfortunately, the proportion of neurons participating in synchronous bursts can be approximated by our method under restricted conditions. When these conditions are not fulfilled, the spike trains have less than maximal entropy, which is indicative of the presence of higher order structure. In this situation, the degree of synchronicity cannot be derived from the pair-wise correlations

Elliptic surface grid generation on minimal and parmetrized surfaces

An elliptic grid generation method is presented which generates excellent boundary conforming grids in domains in 2D physical space. The method is based on the composition of an algebraic and elliptic transformation. The composite mapping obeys the familiar Poisson grid generation system with control functions specified by the algebraic transformation. New expressions are given for the control functions. Grid orthogonality at the boundary is achieved by modification of the algebraic transformation. It is shown that grid generation on a minimal surface in 3D physical space is in fact equivalent to grid generation in a domain in 2D physical space. A second elliptic grid generation method is presented which generates excellent boundary conforming grids on smooth surfaces. It is assumed that the surfaces are parametrized and that the grid only depends on the shape of the surface and is independent of the parametrization. Concerning surface modeling, it is shown that bicubic Hermite interpolation is an excellent method to generate a smooth surface which is passing through a given discrete set of control points. In contrast to bicubic spline interpolation, there is extra freedom to model the tangent and twist vectors such that spurious oscillations are prevented

Desynchronization during anticipatory attention for an upcoming stimulus: A comparative EEG/MEG study

Objectives: Our neurophysiological model of anticipatory behaviour (e.g. Acta Psychol 101 (1999) 213; Bastiaansen et al., 1999a) predicts an activation of (primary) sensory cortex during anticipatory attention for an upcoming stimulus. In this paper we attempt to demonstrate this by means of event-related desynchronization (ERD). Methods: Five subjects performed a time estimation task, and were informed about the quality of their time estimation by either visual or auditory stimuli providing Knowledge of Results (KR). EEG and MEG were recorded in separate sessions, and ERD was computed in the 8± 10 and 10±12 Hz frequency bands for both datasets. Results: Both in the EEG and the MEG we found an occipitally maximal ERD preceding the visual KR for all subjects. Preceding the auditory KR, no ERD was present in the EEG, whereas in the MEG we found an ERD over the temporal cortex in two of the 5 subjects. These subjects were also found to have higher levels of absolute power over temporal recording sites in the MEG than the other subjects, which we consider to be an indication of the presence of a `tau' rhythm (e.g. Neurosci Lett 222 (1997) 111). Conclusions: It is concluded that the results are in line with the predictions of our neurophysiological model