31,435 research outputs found
Dopamine-modulated dynamic cell assemblies generated by the GABAergic striatal microcircuit
The striatum, the principal input structure of the basal ganglia, is crucial to both motor control and learning. It receives convergent input from all over the neocortex, hippocampal formation, amygdala and thalamus, and is the primary recipient of dopamine in the brain. Within the striatum is a GABAergic microcircuit that acts upon these inputs, formed by the dominant medium-spiny projection neurons (MSNs) and fast-spiking interneurons (FSIs). There has been little progress in understanding the computations it performs, hampered by the non-laminar structure that prevents identification of a repeating canonical microcircuit. We here begin the identification of potential dynamically-defined computational elements within the striatum. We construct a new three-dimensional model of the striatal microcircuit's connectivity, and instantiate this with our dopamine-modulated neuron models of the MSNs and FSIs. A new model of gap junctions between the FSIs is introduced and tuned to experimental data. We introduce a novel multiple spike-train analysis method, and apply this to the outputs of the model to find groups of synchronised neurons at multiple time-scales. We find that, with realistic in vivo background input, small assemblies of synchronised MSNs spontaneously appear, consistent with experimental observations, and that the number of assemblies and the time-scale of synchronisation is strongly dependent on the simulated concentration of dopamine. We also show that feed-forward inhibition from the FSIs counter-intuitively increases the firing rate of the MSNs. Such small cell assemblies forming spontaneously only in the absence of dopamine may contribute to motor control problems seen in humans and animals following a loss of dopamine cells. (C) 2009 Elsevier Ltd. All rights reserved
Perceived Environmental Supportiveness Scale: Portuguese Translation, Validation and Adaptation to the Physical Education Domain
Aim: Grounded on Self-Determination Theory, this study aimed to translate, adapt and validate the
Perceived Environmental Supportiveness Scale (PESS) in a sample of Portuguese physical education students.
Methods: The global sample was comprised of 964 students (518 females), divided in two groups: the calibration (n
= 469) and the validation one (n = 483), all of them enrolled in two Physical Education (PE) classes/week. Results: The analysis provided support for a one factor and 12 items model, which are in line with the values adopted in the methodology (χ² = 196.123, df = 54, p = <.001, SRMR = .035, NNFI = .943, CFI = .954, RMSEA = .074, 90% CI .063-.085). Results express that the models are invariant in all analysis (i.e., calibration vs. validation, male vs. female,and 3rd vs. secondary cycle; three and single factor models). Conclusion: The present study suggests that the PESS with one factor and 12 items has good psychometric properties and can be used to assess perceived need supportive motivational environments provided by PE teachers. Additionally, invariance analysis showed support for the use of the scale in both genders and in the 3rd and secondary cycles.info:eu-repo/semantics/publishedVersio
Generating and Adapting to Diverse Ad-Hoc Cooperation Agents in Hanabi
Hanabi is a cooperative game that brings the problem of modeling other
players to the forefront. In this game, coordinated groups of players can
leverage pre-established conventions to great effect, but playing in an ad-hoc
setting requires agents to adapt to its partner's strategies with no previous
coordination. Evaluating an agent in this setting requires a diverse population
of potential partners, but so far, the behavioral diversity of agents has not
been considered in a systematic way. This paper proposes Quality Diversity
algorithms as a promising class of algorithms to generate diverse populations
for this purpose, and generates a population of diverse Hanabi agents using
MAP-Elites. We also postulate that agents can benefit from a diverse population
during training and implement a simple "meta-strategy" for adapting to an
agent's perceived behavioral niche. We show this meta-strategy can work better
than generalist strategies even outside the population it was trained with if
its partner's behavioral niche can be correctly inferred, but in practice a
partner's behavior depends and interferes with the meta-agent's own behavior,
suggesting an avenue for future research in characterizing another agent's
behavior during gameplay.Comment: arXiv admin note: text overlap with arXiv:1907.0384
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The factors driving online shopping in Saudi Arabia: Gender differences and behavior
Purpose—This study proposes a revised technology acceptance model that integrates expectation confirmation theory to measure gender differences with regard to continuance online shopping intentions in Saudi Arabia.
Design/Methodology—The 465-respondent sample consists of 68.8% women and 31.4% men. A structural equation model confirms model fit.
Findings—Perceived usefulness, enjoyment, and subjective norms are determinants of online shopping continuance in Saudi Arabia. Both male and female groups are equivalent. The structural weights are also largely equivalent, but the regression paths from perceived usefulness to subjective norms and to continuous intention are not invariant between men and women.
Originality—This research moves beyond online shopping intentions and includes factors affecting online shopping continuance. The research model explains 65% of the intention to continue shopping online.
Research Implications—This research suggests that online strategies cannot ignore either the direct and indirect gender differences on continuance intentions in Saudi Arabia. The model can be generalized across Saudi Arabia
Resilience and Controllability of Dynamic Collective Behaviors
The network paradigm is used to gain insight into the structural root causes
of the resilience of consensus in dynamic collective behaviors, and to analyze
the controllability of the swarm dynamics. Here we devise the dynamic signaling
network which is the information transfer channel underpinning the swarm
dynamics of the directed interagent connectivity based on a topological
neighborhood of interactions. The study of the connectedness of the swarm
signaling network reveals the profound relationship between group size and
number of interacting neighbors, which is found to be in good agreement with
field observations on flock of starlings [Ballerini et al. (2008) Proc. Natl.
Acad. Sci. USA, 105: 1232]. Using a dynamical model, we generate dynamic
collective behaviors enabling us to uncover that the swarm signaling network is
a homogeneous clustered small-world network, thus facilitating emergent
outcomes if connectedness is maintained. Resilience of the emergent consensus
is tested by introducing exogenous environmental noise, which ultimately
stresses how deeply intertwined are the swarm dynamics in the physical and
network spaces. The availability of the signaling network allows us to
analytically establish for the first time the number of driver agents necessary
to fully control the swarm dynamics
Driving online shopping: Spending and behavioral differences among women in Saudi Arabia
This study proposes a revised technology acceptance model that integrates expectation confirmation theory to measure gender differences with regard to continuance online shopping intentions in Saudi Arabia. The sample consists of 650 female respondents. A structural equation model confirms model fit. Perceived enjoyment, usefulness, and subjective norms are determinants of online shopping continuance in Saudi Arabia. High and low online spenders among women in Saudi Arabia are equivalent. The structural weights are also largely equivalent, but the regression paths from perceived site quality to perceived usefulness is not invariant between high and low e-shoppers in Saudi Arabia. This research moves beyond online shopping intentions and includes factors affecting online shopping continuance. The research model explains 60% of the female respondents’ intention to continue shopping online. Online strategies cannot ignore either the direct and indirect spending differences on continuance intentions, and the model can be generalized across Saudi Arabia
A Local-Dominance Theory of Voting Equilibria
It is well known that no reasonable voting rule is strategyproof. Moreover,
the common Plurality rule is particularly prone to strategic behavior of the
voters and empirical studies show that people often vote strategically in
practice. Multiple game-theoretic models have been proposed to better
understand and predict such behavior and the outcomes it induces. However,
these models often make unrealistic assumptions regarding voters' behavior and
the information on which they base their vote.
We suggest a new model for strategic voting that takes into account voters'
bounded rationality, as well as their limited access to reliable information.
We introduce a simple behavioral heuristic based on \emph{local dominance},
where each voter considers a set of possible world states without assigning
probabilities to them. This set is constructed based on prospective candidates'
scores (e.g., available from an inaccurate poll). In a \emph{voting
equilibrium}, all voters vote for candidates not dominated within the set of
possible states.
We prove that these voting equilibria exist in the Plurality rule for a broad
class of local dominance relations (that is, different ways to decide which
states are possible). Furthermore, we show that in an iterative setting where
voters may repeatedly change their vote, local dominance-based dynamics quickly
converge to an equilibrium if voters start from the truthful state. Weaker
convergence guarantees in more general settings are also provided.
Using extensive simulations of strategic voting on generated and real
preference profiles, we show that convergence is fast and robust, that emerging
equilibria are consistent across various starting conditions, and that they
replicate widely known patterns of human voting behavior such as Duverger's
law. Further, strategic voting generally improves the quality of the winner
compared to truthful voting
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