Morbidade psiquiátrica em crianças com alterações neurológicas

Universidade Federal de São Paulo (UNIFESP) Escola Paulista de Medicina Departamento de PsiquiatriaInstitute of Psychiatry at the Maudsley Child and Adolescent Psychiatry DepartmentUNIFESP, EPM, Depto. de PsiquiatriaSciEL

A counterfactual simulation model of causal judgments for physical events

How do people make causal judgments about physical events? We introduce the counterfactual simulation model (CSM) which predicts causal judgments in physical settings by comparing what actually happened with what would have happened in relevant counterfactual situations. The CSM postulates different aspects of causation that capture the extent to which a cause made a difference to whether and how the outcome occurred, and whether the cause was sufficient and robust. We test the CSM in several experiments in which participants make causal judgments about dynamic collision events. A preliminary study establishes a very close quantitative mapping between causal and counterfactual judgments. Experiment 1 demonstrates that counterfactuals are necessary for explaining causal judgments. Participants' judgments differed dramatically between pairs of situations in which what actually happened was identical, but where what would have happened differed. Experiment 2 features multiple candidate causes and shows that participants' judgments are sensitive to different aspects of causation. The CSM provides a better fit to participants' judgments than a heuristic model which uses features based on what actually happened. We discuss how the CSM can be used to model the semantics of different causal verbs, how it captures related concepts such as physical support, and how its predictions extend beyond the physical domain. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

Eye-Tracking Causality

How do people make causal judgments? What role, if any, does counterfactual simulation play? Counterfactual theories of causal judgments predict that people compare what actually happened with what would have happened if the candidate cause had been absent. Process theories predict that people focus only on what actually happened, to assess the mechanism linking candidate cause and outcome. We tracked participants' eye movements while they judged whether one billiard ball caused another one to go through a gate or prevented it from going through. Both participants' looking patterns and their judgments demonstrated that counterfactual simulation played a critical role. Participants simulated where the target ball would have gone if the candidate cause had been removed from the scene. The more certain participants were that the outcome would have been different, the stronger the causal judgments. These results provide the first direct evidence for spontaneous counterfactual simulation in an important domain of high-level cognition

Aligned Drawings of Planar Graphs

Let $G$ be a graph that is topologically embedded in the plane and let $\mathcal{A}$ be an arrangement of pseudolines intersecting the drawing of $G$. An aligned drawing of $G$ and $\mathcal{A}$ is a planar polyline drawing $\Gamma$ of $G$ with an arrangement $A$ of lines so that $\Gamma$ and $A$ are homeomorphic to $G$ and $\mathcal{A}$. We show that if $\mathcal{A}$ is stretchable and every edge $e$ either entirely lies on a pseudoline or it has at most one intersection with $\mathcal{A}$, then $G$ and $\mathcal{A}$ have a straight-line aligned drawing. In order to prove this result, we strengthen a result of Da Lozzo et al., and prove that a planar graph $G$ and a single pseudoline $\mathcal{L}$ have an aligned drawing with a prescribed convex drawing of the outer face. We also study the less restrictive version of the alignment problem with respect to one line, where only a set of vertices is given and we need to determine whether they can be collinear. We show that the problem is NP-complete but fixed-parameter tractable.Comment: Preliminary work appeared in the Proceedings of the 25th International Symposium on Graph Drawing and Network Visualization (GD 2017

Two-photon interference with true thermal light

Two-photon interference and "ghost" imaging with entangled light have attracted much attention since the last century because of the novel features such as non-locality and sub-wavelength effect. Recently, it has been found that pseudo-thermal light can mimic certain effects of entangled light. We report here the first observation of two-photon interference with true thermal light.Comment: 4 pages, 5 figures, PRA72, 043805 (2005

Breaking the Treadmill? : Climate Change Policy Networks and the Prospects for Low Carbon Futures in Australia and Finland

The Treadmill of Production Theory (TPT) argues that in advanced capitalist societies, business organizations, trade unions, and state actors form a constellation that prioritizes economic growth over environmental concerns. We combine this perspective with the Advocacy Coalition Framework (ACF) and use methods of social network analysis, survey data on key organizations in Finland and Australia, and in-depth interviews to map the policy network structures that resist low carbon transitions, and identify potential for change in these structures. We find that a coalition of economic, labor, and governmental organizations resists a low carbon transition in both countries. However, we also find several possible avenues of incremental change through changes in the network structures and the beliefs held by actors in the networks. Theoretically, this suggests that the TPT is correct in its diagnosis of the current situation, but the ACF may be a more fruitful perspective for identifying potential for change.Peer reviewe

SpikingLab: modelling agents controlled by Spiking Neural Networks in Netlogo

The scientific interest attracted by Spiking Neural Networks (SNN) has lead to the development of tools for the simulation and study of neuronal dynamics ranging from phenomenological models to the more sophisticated and biologically accurate Hodgkin-and-Huxley-based and multi-compartmental models. However, despite the multiple features offered by neural modelling tools, their integration with environments for the simulation of robots and agents can be challenging and time consuming. The implementation of artificial neural circuits to control robots generally involves the following tasks: (1) understanding the simulation tools, (2) creating the neural circuit in the neural simulator, (3) linking the simulated neural circuit with the environment of the agent and (4) programming the appropriate interface in the robot or agent to use the neural controller. The accomplishment of the above-mentioned tasks can be challenging, especially for undergraduate students or novice researchers. This paper presents an alternative tool which facilitates the simulation of simple SNN circuits using the multi-agent simulation and the programming environment Netlogo (educational software that simplifies the study and experimentation of complex systems). The engine proposed and implemented in Netlogo for the simulation of a functional model of SNN is a simplification of integrate and fire (I&F) models. The characteristics of the engine (including neuronal dynamics, STDP learning and synaptic delay) are demonstrated through the implementation of an agent representing an artificial insect controlled by a simple neural circuit. The setup of the experiment and its outcomes are described in this work