Deployment of spatial attention towards locations in memory representations: an EEG study

Recalling information from visual short-term memory (VSTM) involves the same neural mechanisms as attending to an actually perceived scene. In particular, retrieval from VSTM has been associated with orienting of visual attention towards a location within a spatially-organized memory representation. However, an open question concerns whether spatial attention is also recruited during VSTM retrieval even when performing the task does not require access to spatial coordinates of items in the memorized scene. The present study combined a visual search task with a modified, delayed central probe protocol, together with EEG analysis, to answer this question. We found a temporal contralateral negativity (TCN) elicited by a centrally presented go-signal which was spatially uninformative and featurally unrelated to the search target and informed participants only about a response key that they had to press to indicate a prepared target-present vs. -absent decision. This lateralization during VSTM retrieval (TCN) provides strong evidence of a shift of attention towards the target location in the memory representation, which occurred despite the fact that the present task required no spatial (or featural) information from the search to be encoded, maintained, and retrieved to produce the correct response and that the go-signal did not itself specify any information relating to the location and defining feature of the target

Exploring Symmetry of Binary Classification Performance Metrics

Selecting the proper performance metric constitutes a key issue for most classification problems in the field of machine learning. Although the specialized literature has addressed several topics regarding these metrics, their symmetries have yet to be systematically studied. This research focuses on ten metrics based on a binary confusion matrix and their symmetric behaviour is formally defined under all types of transformations. Through simulated experiments, which cover the full range of datasets and classification results, the symmetric behaviour of these metrics is explored by exposing them to hundreds of simple or combined symmetric transformations. Cross-symmetries among the metrics and statistical symmetries are also explored. The results obtained show that, in all cases, three and only three types of symmetries arise: labelling inversion (between positive and negative classes); scoring inversion (concerning good and bad classifiers); and the combination of these two inversions. Additionally, certain metrics have been shown to be independent of the imbalance in the dataset and two cross-symmetries have been identified. The results regarding their symmetries reveal a deeper insight into the behaviour of various performance metrics and offer an indicator to properly interpret their values and a guide for their selection for certain specific applications.University of Seville (Spain) by Telefónica Chair “Intelligence in Networks

An integrated approach to global synchronization and state estimation for nonlinear singularly perturbed complex networks

This paper aims to establish a unified framework to handle both the exponential synchronization and state estimation problems for a class of nonlinear singularly perturbed complex networks (SPCNs). Each node in the SPCN comprises both 'slow' and 'fast' dynamics that reflects the singular perturbation behavior. General sector-like nonlinear function is employed to describe the nonlinearities existing in the network. All nodes in the SPCN have the same structures and properties. By utilizing a novel Lyapunov functional and the Kronecker product, it is shown that the addressed SPCN is synchronized if certain matrix inequalities are feasible. The state estimation problem is then studied for the same complex network, where the purpose is to design a state estimator to estimate the network states through available output measurements such that dynamics (both slow and fast) of the estimation error is guaranteed to be globally asymptotically stable. Again, a matrix inequality approach is developed for the state estimation problem. Two numerical examples are presented to verify the effectiveness and merits of the proposed synchronization scheme and state estimation formulation. It is worth mentioning that our main results are still valid even if the slow subsystems within the network are unstable

Smarandache Sequences: Explorations and Discoveries with a Computer Algebra System

We study Smarandache sequences of numbers, and related problems, via a Computer Algebra System. Solutions are discovered, and some conjectures presented.Comment: To appear in the 2003 December issue of the Smarandache Notions Journa

Smarandache Sequences: Explorations and Discoveries with a Computer Algebra System

Study of Smarandache sequences of numbers, and related problems, via a Computer Algebra. Sy::;tem. Solutions are di::;covered, and some conjectures presented

Object-based target templates guide attention during visual search

During visual search, attention is believed to be controlled in a strictly feature-based fashion, without any guidance by object-based target representations. To challenge this received view, we measured electrophysiological markers of attentional selection (N2pc component) and working memory (SPCN) in search tasks where two possible targets were defined by feature conjunctions (e.g., blue circles and green squares). Critically, some search displays also contained nontargets with two target features (incorrect conjunction objects, e.g., blue squares). Because feature-based guidance cannot distinguish these objects from targets, any selective bias for targets will reflect object-based attentional control. In Experiment 1, where search displays always contained only one object with target-matching features, targets and incorrect conjunction objects elicited identical N2pc and SPCN components, demonstrating that attentional guidance was entirely feature-based. In Experiment 2, where targets and incorrect conjunction objects could appear in the same display, clear evidence for object-based attentional control was found. The target N2pc became larger than the N2pc to incorrect conjunction objects from 250 ms post-stimulus, and only targets elicited SPCN components. This demonstrates that after an initial feature-based guidance phase, object-based templates are activated when they are required to distinguish target and nontarget objects. These templates modulate visual processing and control access to working memory, and their activation may coincide with the start of feature integration processes. Results also suggest that while multiple feature templates can be activated concurrently, only a single object-based target template can guide attention at any given time

The cotangent complex and Thom spectra

We first prove, in the context of $\infty$-categories and using Goodwillie's calculus of functors, that various definitions of the cotangent complex of a map of $E_\infty$-ring spectra that exist in the literature are equivalent. We then prove the following theorem: if $R$ is an $E_\infty$-ring spectrum and $f:G\to \mathrm{Pic}(R)$ is a map of $E_\infty$-groups, then the cotangent complex over $R$ of the Thom $E_\infty$-$R$-algebra of $f$ is equivalent to the smash product of $Mf$ and the connective spectrum associated to $G$.Comment: 19 page