Neuroscience
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Detecting errors in one's own and other's actions is a crucial ability for learning and adapting behavior to everchanging, highly volatile environments. Studies in healthy people demonstrate that monitoring errors in one's own and others' actions are underpinned by specific neural systems that are dysfunctional in a variety of neurological disorders. In this review, we first briefly discuss the main findings concerning error detection and error awareness in healthy subjects, the current theoretical models, and the tasks usually applied to investigate these processes. ⋯ Also theta activity was reduced in some neurological groups, but consistent evidence on the oscillatory activity has not been provided thus far. Behaviorally, we did not observe relevant patterns of pronounced dysfunctional (post-) error processing. Finally, we discuss limitations of the existing literature, conclusive points, open questions and new possible methodological approaches for clinical studies.
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Detecting errors in one's own and other's actions is a crucial ability for learning and adapting behavior to everchanging, highly volatile environments. Studies in healthy people demonstrate that monitoring errors in one's own and others' actions are underpinned by specific neural systems that are dysfunctional in a variety of neurological disorders. In this review, we first briefly discuss the main findings concerning error detection and error awareness in healthy subjects, the current theoretical models, and the tasks usually applied to investigate these processes. ⋯ Also theta activity was reduced in some neurological groups, but consistent evidence on the oscillatory activity has not been provided thus far. Behaviorally, we did not observe relevant patterns of pronounced dysfunctional (post-) error processing. Finally, we discuss limitations of the existing literature, conclusive points, open questions and new possible methodological approaches for clinical studies.
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Feedback on success or failure is critical to increase rewards through behavioral adaptation or learning of dependencies from trial and error. Learning from reward feedback is thereby treated as embedded in a reinforcement learning framework. Due to temporal discounting of reward, learning in this framework is suspected to be vulnerable to feedback delay. ⋯ Performance in tasks that require implicit processing is affected by the delayed availability of feedback compared to tasks that can be accomplished with explicit processing. At the same time, the feedback related negativity, an event related potential component in the electroencephalogram that is associated with feedback processing, is affected by feedback delay similarly independent of task type. With the idea of fully implicit or explicit processing as opposite endpoints of a continuum of reciprocal shares of the implicit and explicit processing systems with feedback delay as the determinant of where on this continuum processing can be located, a common explanatory approach of both, behavioral and electrophysiological findings, is suggested.
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The primary motor cortex, a dynamic center for overall motion control and decision making, undergoes significant alterations upon neural stimulation. Over the last few decades, data from numerous studies using rodent models have improved our understanding of the morphological and functional plasticity of the primary motor cortex. ⋯ However, whether the modifications of specific synapses are associated with motor learning should be studied further. In this review, we summarized the findings of prior studies on the features and dynamics of the primary motor cortex in rodents.
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Closed-loop approaches, setups, and experimental designs have been applied within the field of neuroscience to enhance the understanding of basic neurophysiology principles (closed-loop neuroscience; CLNS) and to develop improved procedures for modulating brain circuits and networks for clinical purposes (closed-loop neuromodulation; CLNM). The contents of this review are thus arranged into the following sections. First, we describe basic research findings that have been made using CLNS. ⋯ Finally, we summarize methodological concerns and critics in clinical practice of neurofeedback and novel applications of closed-loop perspective and techniques to improve and optimize its experiments. Moreover, we outline the theoretical explanations and experimental ideas to test animal models of neurofeedback and discuss technical issues and challenges associated with implementing closed-loop systems. We hope this review is helpful for both basic neuroscientists and clinical/ translationally-oriented scientists interested in applying closed-loop methods to improve mental health and well-being.