Connection Strategies in Associative Memory Models

“The original publication is available at www.springerlink.com”. Copyright Springer.The problem we address in this paper is that of finding effective and parsimonious patterns of connectivity in sparse associative memories. This problem must be addressed in real neuronal systems, so results in artificial systems could throw light on real systems. We show that there are efficient patterns of connectivity and that these patterns are effective in models with either spiking or non-spiking neurons. This suggests that there may be some underlying general principles governing good connectivity in such networks.Peer reviewe

Connectivity in real and evolved associative memories

Peer reviewe

The effects of intrauterine ethanol exposure on the levels of Iron and Copper in Cerebrum and Cerebellum of neonatal Wistar rats

Neurodevelopmental disorders have been reported to be associated with infants exposed to ethanol in utero. The study was aimed at evaluating the effects of intrauterine ethanol exposure on neurobehaviour and the amount of iron and copper in the cerebrum and cerebellum of neonatal Wistar rats at different periods of development. Fourteen (14) female Wistar rats were mated with matured males in ratio 2:1 overnight following determination of oestrous phase. Pregnant dams were divided into 7 groups. Group A served as the control that received distilled water. Groups B, C and D were administered 0.5ml of 20% ethanol equivalent to 1st, 1st and 2nd trimesters and whole gestation period (i.e 1st, 2nd and 3rd trimesters) respectively. Groups E, F and G were given 0.5ml of 30% ethanol accordingly. Following parturition, neurobehavioural assessment on sensory and motor reflexes of the litters were tested on postnatal days 5, 6 and 7. Brain tissues were later excised, homogenised and analysed using Atomic Absorption Spectrophotometry. SPSS V20 was used to compare the mean difference using analysis of variance (ANOVA). The ethanol treated neonates in Groups B, E, F and G showed a statistically significant (p˂0.05) increase in latency to respond to sensory and motor reflexes when compared with Control Group. Interrelated elevation of both iron and copper was observed in the cerebellum while both the amounts of iron and copper in the cerebrum were depleted. It is concluded that intrauterine ethanol exposure has effect on the development of vestibular, postural, sensory and motor coordination. The alterations in the amounts of iron and copper which are important cofactors for certain neurotransmitters and enzymes in the brain could play role in the neurobehavioural deficits observed. Intrauterine ethanol ingestion affects development of sensory and motor reflexes as well as the amounts of iron and copper in both cerebrum and cerebellum in a reciprocal manner. Keywords: ethanol, intrauterine, neurobehaviour, neurochemistr

The brainstem reticular formation is a small-world, not scale-free, network

Recently, it has been demonstrated that several complex systems may have simple graph-theoretic characterizations as so-called ‘small-world’ and ‘scale-free’ networks. These networks have also been applied to the gross neural connectivity between primate cortical areas and the nervous system of Caenorhabditis elegans. Here, we extend this work to a specific neural circuit of the vertebrate brain—the medial reticular formation (RF) of the brainstem—and, in doing so, we have made three key contributions. First, this work constitutes the first model (and quantitative review) of this important brain structure for over three decades. Second, we have developed the first graph-theoretic analysis of vertebrate brain connectivity at the neural network level. Third, we propose simple metrics to quantitatively assess the extent to which the networks studied are small-world or scale-free. We conclude that the medial RF is configured to create small-world (implying coherent rapid-processing capabilities), but not scale-free, type networks under assumptions which are amenable to quantitative measurement

Developmental time windows for axon growth influence neuronal network topology

Early brain connectivity development consists of multiple stages: birth of neurons, their migration and the subsequent growth of axons and dendrites. Each stage occurs within a certain period of time depending on types of neurons and cortical layers. Forming synapses between neurons either by growing axons starting at similar times for all neurons (much-overlapped time windows) or at different time points (less-overlapped) may affect the topological and spatial properties of neuronal networks. Here, we explore the extreme cases of axon formation especially concerning short-distance connectivity during early development, either starting at the same time for all neurons (parallel, i.e. maximally-overlapped time windows) or occurring for each neuron separately one neuron after another (serial, i.e. no overlaps in time windows). For both cases, the number of potential and established synapses remained comparable. Topological and spatial properties, however, differed: neurons that started axon growth early on in serial growth achieved higher out-degrees, higher local efficiency, and longer axon lengths while neurons demonstrated more homogeneous connectivity patterns for parallel growth. Second, connection probability decreased more rapidly with distance between neurons for parallel growth than for serial growth. Third, bidirectional connections were more numerous for parallel growth. Finally, we tested our predictions with C. elegans data. Together, this indicates that time windows for axon growth influence the topological and spatial properties of neuronal networks opening the possibility to a posteriori estimate developmental mechanisms based on network properties of a developed network.Comment: Biol Cybern. 2015 Jan 30. [Epub ahead of print

A simple rule for axon outgrowth and synaptic competition generates realistic connection lengths and filling fractions

Neural connectivity at the cellular and mesoscopic level appears very specific and is presumed to arise from highly specific developmental mechanisms. However, there are general shared features of connectivity in systems as different as the networks formed by individual neurons in Caenorhabditis elegans or in rat visual cortex and the mesoscopic circuitry of cortical areas in the mouse, macaque, and human brain. In all these systems, connection length distributions have very similar shapes, with an initial large peak and a long flat tail representing the admixture of long-distance connections to mostly short-distance connections. Furthermore, not all potentially possible synapses are formed, and only a fraction of axons (called filling fraction) establish synapses with spatially neighboring neurons. We explored what aspects of these connectivity patterns can be explained simply by random axonal outgrowth. We found that random axonal growth away from the soma can already reproduce the known distance distribution of connections. We also observed that experimentally observed filling fractions can be generated by competition for available space at the target neurons--a model markedly different from previous explanations. These findings may serve as a baseline model for the development of connectivity that can be further refined by more specific mechanisms.Comment: 31 pages (incl. supplementary information); Cerebral Cortex Advance Access published online on May 12, 200

Functional EEG network analysis in schizophrenia: Evidence of larger segregation and deficit of modulation

Objective: Higher mental functions depend on global cerebral functional coordination. Our aim was to study fast modulation of functional networks in schizophrenia that has not been previously assessed. Methods: Graph-theory was used to analyze the electroencephalographic (EEG) activity during an odd-ball task in 57 schizophrenia patients (18 first episode patients, FEPs) and 59 healthy controls. Clustering coefficient (CLC), characteristic path length (PL) and small-worldness (SW) were computed at baseline ([−300 0] ms prior to stimulus delivery) and response ([150 450] ms post-stimulus) windows. Clinical and cognitive assessments were performed. Results: CLC, PL and SW showed a significant modulation between baseline and response in controls but not in patients. Patients obtained higher CLC and SW at baseline, lower CLC and higher PL at response, and diminished modulation of CLC and SW as compared to controls. In patients, CLC and SW modulation were inversely associated to cognitive performance in executive tasks and directly associated to working memory. Similar patterns were observed in FEPs. CLC and SW during the baseline were inversely associated to their respective modulation magnitudes. Conclusions: Our results are coherent with a hyper-segregated network at baseline (higher CLC) and a decreased modulation of the functional connectivity during cognition in schizophrenia.This work was supported by the Instituto Carlos III (PI11/02708, PI11/02203 and PI15/00299) and the Gerencia Regional de Salud de Castilla y León (GRS 1134/A/15 and GRS 1263/A/16) grants; the ‘MINECO and FEDER (TEC2014-53196-R), ‘Consejería de Educación de la Junta de Castilla y León’ (VA037U16); and predoctoral fellowships to A. Lubeiro (‘Consejería de Educación Junta de Castilla y León’) and to J. Gomez-Pilar (University of Valladolid)

Assessing Random Dynamical Network Architectures for Nanoelectronics

Independent of the technology, it is generally expected that future nanoscale devices will be built from vast numbers of densely arranged devices that exhibit high failure rates. Other than that, there is little consensus on what type of technology and computing architecture holds most promises to go far beyond today's top-down engineered silicon devices. Cellular automata (CA) have been proposed in the past as a possible class of architectures to the von Neumann computing architecture, which is not generally well suited for future parallel and fine-grained nanoscale electronics. While the top-down engineered semi-conducting technology favors regular and locally interconnected structures, future bottom-up self-assembled devices tend to have irregular structures because of the current lack precise control over these processes. In this paper, we will assess random dynamical networks, namely Random Boolean Networks (RBNs) and Random Threshold Networks (RTNs), as alternative computing architectures and models for future information processing devices. We will illustrate that--from a theoretical perspective--they offer superior properties over classical CA-based architectures, such as inherent robustness as the system scales up, more efficient information processing capabilities, and manufacturing benefits for bottom-up designed devices, which motivates this investigation. We will present recent results on the dynamic behavior and robustness of such random dynamical networks while also including manufacturing issues in the assessment.Comment: 8 pages, 6 figures, IEEE/ACM Symposium on Nanoscale Architectures, NANOARCH 2008, Anaheim, CA, USA, Jun 12-13, 200