Evolution and Analysis of Embodied Spiking Neural Networks Reveals Task-Specific Clusters of Effective Networks

Elucidating principles that underlie computation in neural networks is currently a major research topic of interest in neuroscience. Transfer Entropy (TE) is increasingly used as a tool to bridge the gap between network structure, function, and behavior in fMRI studies. Computational models allow us to bridge the gap even further by directly associating individual neuron activity with behavior. However, most computational models that have analyzed embodied behaviors have employed non-spiking neurons. On the other hand, computational models that employ spiking neural networks tend to be restricted to disembodied tasks. We show for the first time the artificial evolution and TE-analysis of embodied spiking neural networks to perform a cognitively-interesting behavior. Specifically, we evolved an agent controlled by an Izhikevich neural network to perform a visual categorization task. The smallest networks capable of performing the task were found by repeating evolutionary runs with different network sizes. Informational analysis of the best solution revealed task-specific TE-network clusters, suggesting that within-task homogeneity and across-task heterogeneity were key to behavioral success. Moreover, analysis of the ensemble of solutions revealed that task-specificity of TE-network clusters correlated with fitness. This provides an empirically testable hypothesis that links network structure to behavior.Comment: Camera ready version of accepted for GECCO'1

Toward the next generation of research into small area effects on health : a synthesis of multilevel investigations published since July 1998.

To map out area effects on health research, this study had the following aims: (1) to inventory multilevel investigations of area effects on self rated health, cardiovascular diseases and risk factors, and mortality among adults; (2) to describe and critically discuss methodological approaches employed and results observed; and (3) to formulate selected recommendations for advancing the study of area effects on health. Overall, 86 studies were inventoried. Although several innovative methodological approaches and analytical designs were found, small areas are most often operationalised using administrative and statistical spatial units. Most studies used indicators of area socioeconomic status derived from censuses, and few provided information on the validity and reliability of measures of exposures. A consistent finding was that a significant portion of the variation in health is associated with area context independently of individual characteristics. Area effects on health, although significant in most studies, often depend on the health outcome studied, the measure of area exposure used, and the spatial scale at which associations are examined

Understanding Charge Transfer in Donor-Acceptor/Metal Systems: A Combined Theoretical and Experimental Study

We develop an effective potential approach for assessing the flow of charge within a two-dimensional donor-acceptor/metal network based on core-level shifts. To do so, we perform both density functional theory (DFT) calculations and x-ray photoemission spectroscopy (XPS) measurements of the core-level shifts for three different monolayers adsorbed on a Ag substrate. Specifically, we consider perfluorinated pentacene (PFP), copper phthalocyanine (CuPc) and their 1:1 mixture (PFP+CuPc) adsorbed on Ag(111).Comment: 12 pages, 10 figure

Adaptation of Robot Behaviour through Online Evolution and Neuromodulated Learning

Abstract. We propose and evaluate a novel approach to the online syn-thesis of neural controllers for autonomous robots. We combine online evolution of weights and network topology with neuromodulated learn-ing. We demonstrate our method through a series of simulation-based ex-periments in which an e-puck-like robot must perform a dynamic concur-rent foraging task. In this task, scattered food items periodically change their nutritive value or become poisonous. Our results show that when neuromodulated learning is employed, neural controllers are synthesised faster than by evolution alone. We demonstrate that the online evolu-tionary process is capable of generating controllers well adapted to the periodic task changes. An analysis of the evolved networks shows that they are characterised by specialised modulatory neurons that exclusively regulate the output neurons

Neuronal assembly dynamics in supervised and unsupervised learning scenarios

The dynamic formation of groups of neurons—neuronal assemblies—is believed to mediate cognitive phenomena at many levels, but their detailed operation and mechanisms of interaction are still to be uncovered. One hypothesis suggests that synchronized oscillations underpin their formation and functioning, with a focus on the temporal structure of neuronal signals. In this context, we investigate neuronal assembly dynamics in two complementary scenarios: the first, a supervised spike pattern classification task, in which noisy variations of a collection of spikes have to be correctly labeled; the second, an unsupervised, minimally cognitive evolutionary robotics tasks, in which an evolved agent has to cope with multiple, possibly conflicting, objectives. In both cases, the more traditional dynamical analysis of the system’s variables is paired with information-theoretic techniques in order to get a broader picture of the ongoing interactions with and within the network. The neural network model is inspired by the Kuramoto model of coupled phase oscillators and allows one to fine-tune the network synchronization dynamics and assembly configuration. The experiments explore the computational power, redundancy, and generalization capability of neuronal circuits, demonstrating that performance depends nonlinearly on the number of assemblies and neurons in the network and showing that the framework can be exploited to generate minimally cognitive behaviors, with dynamic assembly formation accounting for varying degrees of stimuli modulation of the sensorimotor interactions

Lattice Mismatch Drives Spatial Modulation of Corannulene Tilt on Ag(111)

We investigated the adsorption of corannulene (C20H10) on the Ag(111) surface by experimental and simulated scanning tunneling microscopy (STM), X-ray photoemission (XPS), and near-edge X-ray absorption fine structure (NEXAFS). Structural optimizations of the adsorbed molecules were performed by density functional theory (DFT) and the core excited spectra evaluated within the transition-potential approach. Corannulene is physisorbed in a bowl-up orientation displaying a very high mobility (diffusing) and dynamics (tilting and spinning) at room temperature. At the monolayer saturation coverage, molecules order into a close-compact phase with an average intermolecular spacing of 3c10.5 \ub1 0.3 \uc5. The lattice mismatch drives a long wavelength structural modulation of the molecular rows, which, however, could not be identified with a specific superlattice periodicity. DFT calculations indicate that the structural and spectroscopic properties are intermediate between those predicted for the limiting cases of an on-hexagon geometry (with a 3-fold, 3c8.6 \uc5 unit mesh) and an on-pentagon geometry (with a 4-fold, 3c11.5 \uc5 unit mesh). We suggest that molecules smoothly change their equilibrium configuration along the observed long wavelength modulation of the molecular rows by varying their tilt and azimuth in between the geometric constraints calculated for molecules in the 3-fold and 4-fold phases

Conservation of Nickel Ion Single-Active Site Character in a Bottom-Up Constructed π-Conjugated Molecular Network

On-surface chemistry holds the potential for ultimate miniaturization of functional devices. Porphyrins are promising building-blocks in exploring advanced nanoarchitecture concepts. More stable molecular materials of practical interest with improved charge transfer properties can be achieved by covalently interconnecting molecular units. On-surface synthesis allows to construct extended covalent nanostructures at interfaces not conventionally available. Here, we address the synthesis and properties of covalent molecular network composed of interconnected constituents derived from halogenated nickel tetraphenylporphyrin on Au(111). We report that the π-extended two-dimensional material exhibits dispersive electronic features. Concomitantly, the functional Ni cores retain the same single-active site character of their single-molecule counterparts. This opens new pathways when exploiting the high robustness of transition metal cores provided by bottom-up constructed covalent nanomeshes

From bi-layer to tri-layer Fe nanoislands on Cu3Au(001)

Self assembly on suitably chosen substrates is a well exploited root to control the structure and morphology, hence magnetization, of metal films. In particular, the Cu3Au(001) surface has been recently singled out as a good template to grow high spin Fe phases, due to the close matching between the Cu3Au lattice constant (3.75 Angstrom) and the equilibrium lattice constant for fcc ferromagnetic Fe (3.65 Angstrom). Growth proceeds almost layer by layer at room temperature, with a small amount of Au segregation in the early stage of deposition. Islands of 1-2 nm lateral size and double layer height are formed when 1 monolayer of Fe is deposited on Cu3Au(001) at low temperature. We used the PhotoElectron Diffraction technique to investigate the atomic structure and chemical composition of these nanoislands just after the deposition at 140 K and after annealing at 400 K. We show that only bi-layer islands are formed at low temperature, without any surface segregation. After annealing, the Fe atoms are re-aggregated to form mainly tri-layer islands. Surface segregation is shown to be inhibited also after the annealing process. The implications for the film magnetic properties and the growth model are discussed.Comment: Revtex, 5 pages with 4 eps figure

Quantifying through-space charge transfer dynamics in \u3c0-coupled molecular systems

understanding the role of intermolecular interaction on through-space charge transfer characteristics in \u3c0-stacked molecular systems is central to the rational design of electronic materials. However, a quantitative study of charge transfer in such systems is often difficult because of poor control over molecular morphology. Here we use the core-hole clock implementation of resonant photoemission spectroscopy to study the femtosecond chargetransfer dynamics in cyclophanes, which consist of two precisely stacked \u3c0-systems held together by aliphatic chains. We study two systems, [2,2]paracyclophane (22PCP) and [4,4]paracyclophane (44PCP), with inter-ring separations of 3.0 and 4.0 \uc5, respectively. We find that charge transfer across the \u3c0-coupled system of 44PCP is 20 times slower than in 22PCP. We attribute this difference to the decreased inter-ring electronic coupling in 44PCP. These measurements illustrate the use of core-hole clock spectroscopy as a general tool for quantifying through-space coupling in \u3c0-stacked systems