We have investigated the role that different connectivity regimes play in the dynamics of a network of Hodgkin-Huxley neurons by computer simulations. The different connectivity topologies exhibit the following features: random topologies give rise to fast system response yet are unable to produce coherent oscillations in the average activity of the network; on the other hand, regular topologies give rise to coherent oscillations, but in a temporal scale that is not in accordance with fast signal processing. Finally, small-world topologies, which fall between random and regular ones, take advantage of the best features of both, giving rise to fast system response with coherent oscillations. PACS numbers: 87.18.Sn, 84.35. + i, 87.18.Bb In a recent Letter by Watts and Strogatz [1] it was shown that small-world (SW) networks enhance signalpropagation speed, computational power, and synchronizability. SW stands for a network whose connectivity topology is placed somewhere between a regular and a completely random connectivity. The main properties of these specific networks are that they can be highly clustered like regular networks and, at the same time, have small path lengths like random ones. Therefore, SW networks may have properties given neither in regular nor in random networks [2]. In this Letter we have extended Watts and Strogatz's general framework by introducing dynamical elements in the network nodes. Our source of inspiration is based on a phenomenon observed in the olfactory antennal lobe (AL) of the locust [3]. The AL is a group of around 800 neurons whose functional role is to relay information from the olfactory receptors to higher areas of the brain for further processing. Two main features have been observed in the dynamics of the AL. First, there is a fast response of the AL when the stimulus is presented. Second, when an odor is presented to the insect, coherent oscillations of 20 Hz in the local field potential (LFP) are measured [3]. Summarizing, fast coherent oscillations are observed. There are also other systems in the brain that present coherent LFP oscillations, hence, hinting to the generality of these phenomena (see [4,5]).The cooperative behavior of large assemblies of dynamical elements has been the subject of many investigations [6][7][8][9][10]. In all of them the connectivity between the elements of the network was either regular (local or global all-to-all) or random. However, none of these studies incorporates a comparative analysis of network dynamics for all the different connectivity topologies.In the present work we want to show that in order to provide fast response and coherent oscillations a SW topology is required. Without the coherent oscillations the AL seems to lose its ability to process the information incoming from the sensors [3]. The model we propose for this study is made of an array of nonidentical Hodgkin-Huxley elements coupled by excitatory synapses. The unit dynamics is described by the following set of coupled ordinary differential equations:ᠨ n a n ͑V ...

A new multimodal biometric database, acquired in the framework of the BiosecurID project, is presented together with the description of the acquisition setup and protocol. The database includes eight unimodal biometric traits, namely: speech, iris, face (still images, videos of talking faces), handwritten signature and handwritten text (on-line dynamic signals, off-line scanned images), fingerprints (acquired with two different sensors), hand (palmprint, contour-geometry) and keystroking. The database comprises 400 subjects and presents features such as: realistic acquisition scenario, balanced gender and population distributions, availability of information about particular demographic groups (age, gender, handedness), acquisition of replay attacks for speech and keystroking, skilled forgeries for signatures, and compatibility with other existing databases. All these characteristics make it very useful in research and development of unimodal and multimodal biometric systems.

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The orientation bandwidth was measured at different spatial frequencies for simple and complex cells. With increasing spatial frequency, the orientation tuning of simple cells became progressively narrower. This tendency was much less marked in complex cells. The results are interpreted in support of geniculate cells with orthogonal orientation biases providing the excitatory and inhibitory inputs to a simple cell.

A central pattern generator (CPG) is built to control a mechanical device (plant) inspired by the pyloric chamber of the lobster. Conductance-based models are used to construct the neurons of the CPG. The plant has an associated function that measures the amount of food flowing through it per unit of time. We search for the best set of solutions that give a high positive flow of food in the maximization function. The plant is symmetric and the model neurons are identical to avoid any bias in the space of solutions. We find that the solution is not unique and that three neurons are sufficient to produce positive flow. We propose an effective principle for CPGs (effective on-off connectivity) and a few predictions to be corroborated in the pyloric system of the lobster.