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\"The aim of the book is to introduce the state-of-the-art technologies in the field of brain and cognitive intelligence used in robotics control, particularly on studying how brain learns and controls complex motor skills and apply such to robots. This will be the first book that systematically and thoroughly deals with above topics. Advances made in the past decades will be well described in this book. Interesting topics such as human-robot interactions, neurorobotics, Biomechanics in robotic control, robot vision, force control, and control and coordination of humanoid robots are covered\"-- Provided by publisher.

Cognitive control, with a limited capacity, is a core process in human cognition for the coordination of thoughts and actions. Although the regions involved in cognitive control have been identified as the cognitive control network (CCN), it is still unclear whether a specific region of the CCN serves as a bottleneck limiting the capacity of cognitive control (CCC). Here, we used a perceptual decision-making task with conditions of high cognitive load to challenge the CCN and to assess the CCC in a functional magnetic resonance imaging study. We found that the activation of the right anterior insular cortex (AIC) of the CCN increased monotonically as a function of cognitive load, reached its plateau early, and showed a significant correlation to the CCC. In a subsequent study of patients with unilateral lesions of the AIC, we found that lesions of the AIC were associated with a significant impairment of the CCC. Simulated lesions of the AIC resulted in a reduction of the global efficiency of the CCN in a network analysis. These findings suggest that the AIC, as a critical hub in the CCN, is a bottleneck of cognitive control. •Activation of the right anterior insular cortex (AIC) is associated with information rate.•This activation is positively correlated with the capacity of cognitive control.•Lesions of the AIC impair the capacity of cognitive control.•Simulated lesions of the AIC lead to a reduction in the network global efficiency.

\"Brain aging has long been seen as a process of deterioration and decline. Today, this view been challenged with research showing that not all cognitive processes decline with age, that some improve over the course of adulthood, and those that improve can often compensate for those that decline. Chapters in this multidisciplinary volume examine the neural mechanisms underlying changes in the aging brain, changes in learning and memory, risk and protective factors, and the assessment and prevention of cognitive decline\"--Provided by publisher.

This article discusses the concept and applications of cognitive dynamic systems (CDS), which are a type of intelligent system inspired by the brain. There are two branches of CDS, one for linear and Gaussian environments (LGEs), such as cognitive radio and cognitive radar, and another one for non-Gaussian and nonlinear environments (NGNLEs), such as cyber processing in smart systems. Both branches use the same principle, called the perception action cycle (PAC), to make decisions. The focus of this review is on the applications of CDS, including cognitive radios, cognitive radar, cognitive control, cyber security, self-driving cars, and smart grids for LGEs. For NGNLEs, the article reviews the use of CDS in smart e-healthcare applications and software-defined optical communication systems (SDOCS), such as smart fiber optic links. The results of implementing CDS in these systems are very promising, with improved accuracy, performance, and lower computational costs. For example, CDS implementation in cognitive radars achieved a range estimation error that is as good as 0.47 (m) and a velocity estimation error of 3.30 (m/s), outperforming traditional active radars. Similarly, CDS implementation in smart fiber optic links improved the quality factor by 7 dB and the maximum achievable data rate by 43% compared to those of other mitigation techniques.

Robotic vision, the combination of robotics and computer vision, involves the application of computer algorithms to data acquired from sensors. The research community has developed a large body of such algorithms but for a newcomer to the field this can be quite daunting. For over 20 years the author has maintained two open-source MATLAB® Toolboxes, one for robotics and one for vision. They provide implementations of many important algorithms and allow users to work with real problems, not just trivial examples. This book makes the fundamental algorithms of robotics, vision and control accessible to all. It weaves together theory, algorithms and examples in a narrative that covers robotics and computer vision separately and together. Using the latest versions of the Toolboxes the author shows how complex problems can be decomposed and solved using just a few simple lines of code. The topics covered are guided by real problems observed by the author over many years as a practitioner of both robotics and computer vision. It is written in an accessible but informative style, easy to read and absorb, and includes over 1000 MATLAB and Simulink® examples and over 400 figures. The book is a real walk through the fundamentals of mobile robots, arm robots. then camera models, image processing, feature extraction and multi-view geometry and finally bringing it all together with an extensive discussion of visual servo systems. This second edition is completely revised, updated and extended with coverage of Lie groups, matrix exponentials and twists; inertial navigation; differential drive robots; lattice planners; pose-graph SLAM and map making; restructured material on arm-robot kinematics and dynamics; series-elastic actuators and operational-space control; Lab color spaces; light field cameras; structured light, bundle adjustment and visual odometry; and photometric visual servoing. \"An authoritative book, reaching across fields, thoughtfully conceived and brilliantly accomplished!\" OUSSAMA KHATIB, Stanford.

The cognitive control network (CCN) that comprises regions of the frontoparietal network, the cingulo-opercular network, and other sub-cortical regions as core structures is commonly activated by events with an increase in information uncertainty. However, it is not clear whether this CCN activation is associated with both information entropy that represents the information conveyed by the context formed by a sequence of events and the surprise that quantifies the information conveyed by a specific type of event in the context. We manipulated entropy and surprise in this functional magnetic resonance imaging study by varying the probability of occurrence of two types of events in both the visual and auditory modalities and measured brain response as a function of entropy and surprise. We found that activation in regions of the CCN increased as a function of entropy and surprise in both the visual and auditory tasks. The frontoparietal network and additional structures in the CCN mediated the relationship between these information measures and behavioral response. These results suggest that the CCN is a high-level modality-general neural entity for the control of the processing of information conveyed by both context and event.

\"In spite of improved access to psychosocial interventions, many people with psychosis continue to experience persistent problems which act as significant barriers to their recovery. This book investigates risk and problem behaviours in psychosis including staff and service factors that can impede the delivery of effective care. Working with Problematic Behaviour in Psychosis provides a new approach for assessment formulation and intervention with such problem behaviours in a team context. Of particular interest will be: an outline of the SAFE (Shared Assessment, Formulation and Education) approach an integrative model for understanding risk and problematic behaviour shared risk assessment and management processes the use of CBT in day-to-day interactions with clients a set of formulation driven strategies for managing problematic behaviours case studies and vignettes providing guidance and highlighting the benefits of the approach. This book will have particular appeal to professionals working in residential care for those with complex mental health problems as well as those working in intensive community based services. It is also an excellent resource for those training in psychological therapies for complex mental health problems, risk assessment and management\"--Provided by publisher.

This trial examines the effect of delirium preventive measures on the incidence of postoperative cognitive dysfunction in older adults. In a randomised approach, a delirium prevention and a standard care group were compared regarding manifestation of postoperative cognitive dysfunction at seven days, three and twelve months postoperatively (primary outcome). To correct for practice effects and age-depended cognitive decline, a control group of age-matched healthy subjects was included. The trial was conducted at the University Medical Centre Hamburg between 2014 and 2018, data assessment took place in the Anaesthesia Outpatient Clinic and on the surgical ward. A total of 609 patients ≥60 years scheduled for cardiovascular surgery were enrolled, allocated treatment was received by 284 patients in the delirium prevention and 274 patients in the standard care group. The intervention consisted of a delirium prevention bundle including reorientation measures, sleeping aids and early mobilisation. Measurements: Cognitive functions were assessed via neuropsychological testing of attention, executive functions including word fluency, and verbal memory utilizing a computerised test of attentional performance, the trail making test, the digit span subtest from the Wechsler Adult Intelligence Scale-IV, the verbal learning and memory test, and the Regensburg Word Fluency Test. Assessments were performed preoperatively and at three time points postoperatively (one week, three months and 12 months). Postoperative cognitive dysfunction was defined as a clinically meaningful decline in at least two out of nine chosen test parameters compared to the preoperative level (reliable change index ≤ − 1.96). The rates of postoperative cognitive dysfunction were 25.9% (delirium prevention group, n = 284) vs. 28.1% (standard care group, n = 274) [X2(1,n = 433) = 0.245;p = 0.621] at postoperative day seven and declined to 7.8% vs. 6.8% [X2(1,n = 219) = 0.081;p = 0.775] and 1.3% vs. 5.6% (p = 0.215, Fisher's exact test) at three and 12 months following surgery, respectively. The postoperative delirium rates did not differ between the two groups (delirium prevention group: 13.4% vs. standard care group: 17.3%). Attentional performance was impaired shortly after surgery, whereas verbal delayed recall was most frequently affected over the whole postoperative period. These findings suggest that an intervention combining specific measures extracted from established postoperative delirium prevention programs did not reduce the rate of postoperative cognitive dysfunction in older adults. •Delirium prevention measures do not prevent postoperative cognitive dysfunction•Pattern of postoperative cognitive dysfunction is highly individual•Most patients recover from postoperative cognitive dysfunction within one year

The human ability to flexibly adapt to novel circumstances is extraordinary. Perhaps the most illustrative, yet underappreciated, form of this cognitive flexibility is rapid instructed task learning (RITL)—the ability to rapidly reconfigure our minds to perform new tasks from instructions. This ability is important for everyday life (e.g., learning to use new technologies) and is used to instruct participants in nearly every study of human cognition. We review the development of RITL as a circumscribed domain of cognitive neuroscience investigation, culminating in recent demonstrations that RITL is implemented via brain circuits centered on lateral prefrontal cortex. We then build on this and the recent discovery of compositional representations within lateral prefrontal cortex to develop an integrative theory of cognitive flexibility and cognitive control that identifies mechanisms that may enable RITL within the human brain. The insights gained from this new theoretical account have important implications for further developments and applications of RITL research.