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Role of connectivity topology in the transition between retrieving and non-retrieving phases in neural networks
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Role of topology in the spontaneous cortical activity
No full textScarpetta et al. BMC Neuroscience 2015, 16(Suppl 1):P6
http://www.biomedcentral.com/1471-2202/16/S1/P
Hysteresis, neural avalanches and critical behaviour near a rst-order transition of a spiking neural network
Full text linkMany experimental results, both in-vivo and in-vitro, support the idea that the brain cortex
operates near a critical point, and at the same time works as a reservoir of precise spatio-temporal
patterns. However the mechanism at the basis of these observations is still not clear. In this paper
we introduce a model which combines both these features, showing that scale-free avalanches are
the signature of a system posed near the spinodal line of a rst order transition, with many spatiotemporal
patterns stored as dynamical metastable attractors. Specically, we studied a network of
leaky integrate and re neurons, whose connections are the result of the learning of multiple spatiotemporal
dynamical patterns, each with a randomly chosen ordering of the neurons. We found that
the network shows a rst order transition between a low spiking rate disordered state (down), and
a high rate state characterized by the emergence of collective activity and the replay of one of the
stored patterns (up). The transition is characterized by hysteresis, or alternation of up and down
states, depending on the lifetime of the metastable states. In both cases, critical features and neural
avalanches are observed. Notably, critical phenomena occur at the edge of a discontinuous phase
transition, as recently observed in a network of glow lamps
Cortical Phase Transitions as an Effect of Topology of Neural Network
No full textUnderstanding the emerging of cortical dynamical state, its functional role, and its relationship with network topology, is one of the most interesting open questions in computational neuroscience. Spontaneous cortical dynamics often shows spontaneous fluctuations with UP/DOWN alternations and critical avalanches which resemble the critical fluctuations of a system posed near a non-equilibrium noise-induced phase transition. A model with structured connectivity and dynamical attractors has been shown to sustain two different dynamic states and a phase transition with critical behaviour is observed. We investigate here which are the features of the connectivity which permit the emergence of the phase transition and the large fluctuations near the critical line. We start from the original connectivity, that comes from the learning of the spatiotemporal patterns, and we shuffle the presynaptic units, leaving unchanged both the postsynaptic units and the value of the connections. The original structured network has a large clustering coefficient, since it has more directed connections which cooperate to activate a precise order of neurons, respect to randomized network. When we shuffle the connections we reduce the clustering coefficient and we destroy the spatiotemporal pattern attractors. We observe that the phase transition is gradually destroyed when we increase the ratio of shuffled connections, and already at a shuffling ratio of 70% both the phase transition and its critical features disappear
Structured Versus Shuffled Connectivity in Cortical Dynamics
No full textAbstract
Previous papers have studied a leaky Integrate-and-Fire (IF) model whose connectivity was designed in such a manner as to favor the spontaneous emergence of collective oscillatory spatiotemporal patterns of spikes. In this model the alternation of up and down states does not depend on a kind of neuron bistability, nor on synaptic depression, but is rather a network effect. In order to check if the transition region with bimodal distribution of the firing rate survive even after changes in the topology of the network, in this work we shuffle all the connections. For each chosen connection we change the presynaptic neuron, choosing as the new presynaptic one a random neuron of the network. After shuffling the connections, not only the number of excitatory and inhibitory connections is the same as before, but also the strengths of the connections are the same, and only the topology is changed. We observe that shuffling the connections changes the features of the dynamics dramatically. Before shuffling the system has a transition from a regime of Poissonian noisy activity to a regime of spontaneous persistent collective replay, and at the transition point the network dynamics shows an intermittent reactivation of the stored patterns, with alternation of up and down state, and bimodal distribution of spiking rate. Shuffling all the connections we observe that the transition region with bimodal distribution disappears, and the dynamics is Poissonian with unimodal rate distribution for all the investigated parameters. These results show the role of topology in dictating the emerging collective dynamics of neural circuits
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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