The discovery of mirror neurons in monkeys, and the finding of motor activity during action observation in humans are generally regarded to support motor theories of action understanding. These theories take motor resonance to be essential in the understanding of observed actions and the inference of action goals. However, the notions of "resonance," "action understanding," and "action goal" appear to be used ambiguously in the literature. A survey of the literature on mirror neurons and motor resonance yields two different interpretations of the term "resonance," three different interpretations of action understanding, and again three different interpretations of what the goal of an action is. This entails that, unless it is specified what interpretation is used, the meaning of any statement about the relation between these concepts can differ to a great extent. By discussing an experiment we will show that more precise definitions and use of the concepts will allow for better assessments of motor theories of action understanding and hence a more fruitful scientific debate. Lastly, we will provide an example of how the discussed experimental setup could be adapted to test other interpretations of the concepts.
In the past two decades, functional Magnetic Resonance Imaging (fMRI) has been used to relate neuronal network activity to cognitive processing and behavior. Recently this approach has been augmented by algorithms that allow us to infer causal links between component populations of neuronal networks. Multiple inference procedures have been proposed to approach this research question but so far, each method has limitations when it comes to establishing whole-brain connectivity patterns. In this paper, we discuss eight ways to infer causality in fMRI research: Bayesian Nets, Dynamical Causal Modelling, Granger Causality, Likelihood Ratios, Linear Non-Gaussian Acyclic Models, Patel’s Tau, Structural Equation Modelling, and Transfer Entropy. We finish with formulating some recommendations for the future directions in this area.
In analyses of the motor system, two hierarchies are often posited: The first-the action hierarchy-is a decomposition of an action into subactions and sub-subactions. The second-the control hierarchy-is a postulated hierarchy in the neural control processes that are supposed to bring about the action. A general assumption in cognitive neuroscience is that these two hierarchies are internally consistent and provide complementary descriptions of neuronal control processes. In this article, we suggest that neither offers a complete explanation and that they cannot be reconciled in a logical or conceptually coherent way. Furthermore, neither pays proper attention to the dynamics and temporal aspects of neural control processes. We will explore an alternative hierarchical organization in which causality is inherent in the dynamics over time. Specifically, high levels of the hierarchy encode more stable (goal-related) representations, whereas lower levels represent more transient (actions and motor acts) kinematics. If employed properly, a hierarchy based on this latter principle of temporal extension is not subject to the problems that plague the traditional accounts.
a b s t r a c tIntentions are commonly conceived of as discrete mental states that are the direct cause of actions. In the last several decades, neuroscientists have taken up the project of finding the neural implementation of intentions, and a number of areas have been posited as implementing these states. We argue, however, that the processes underlying action initiation and control are considerably more dynamic and context sensitive than the concept of intention can allow for. Therefore, adopting the notion of 'intention' in neuroscientific explanations can easily lead to misinterpretation of the data, and can negatively influence investigation into the neural correlates of intentional action. We suggest reinterpreting the mechanisms underlying intentional action, and we will discuss the elements that such a reinterpretation needs to account for.
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