Many current neurophysiological, psychophysical, and psychological approaches to vision rest on the idea that when we see, the brain produces an internal representation of the world. The activation of this internal representation is assumed to give rise to the experience of seeing. The problem with this kind of approach is that it leaves unexplained how the existence of such a detailed internal representation might produce visual consciousness. An alternative proposal is made here. We propose that seeing is a way of acting. It is a particular way of exploring the environment. Activity in internal representations does not generate the experience of seeing. The outside world serves as its own, external, representation. The experience of seeing occurs when the organism masters what we call the governing laws of sensorimotor contingency. The advantage of this approach is that it provides a natural and principled way of accounting for visual consciousness, and for the differences in the perceived quality of sensory experience in the different sensory modalities. Several lines of empirical evidence are brought forward in support of the theory, in particular: evidence from experiments in sensorimotor adaptation, visual \"filling in,\" visual stability despite eye movements, change blindness, sensory substitution, and color perception.

A sensorimotor account of vision and visual consciousness-Authors' Response-Acting out our sensory experience

Thank you very much for downloading biomechanics and motor control of human movement. Maybe you have knowledge that, people have search hundreds times for their favorite books like this biomechanics and motor control of human movement, but end up in infectious downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they juggled with some malicious virus inside their laptop.

Biomechanics And Motor Control Of Human Movement

The complete title of this book runs ‘Analyzing Linguistic Data: A Practical Introduction to Statistics using R’ and as such it very well reflects the purpose and spirit of the book. The author guides the reader in about 350 pages from descriptive and basic statistical methods over classification and clustering to (generalised) linear and mixed models. Each of the methods is introduced in the context of concrete linguistic problems and demonstrated on exciting datasets from current research in the language sciences. In line with its practical orientation, the book focuses primarily on using the methods and interpreting the results. This implies that the mathematical treatment of the techniques is held at a minimum if not absent from the book. In return, the reader is provided with very detailed explanations on how to conduct the analyses using R [1]. The first chapter sets the tone being a 20-page introduction to R. For this and all subsequent chapters, the R code is intertwined with the chapter text and the datasets and functions used are conveniently packaged in the languageR package that is available on the Comprehensive R Archive Network (CRAN). With this approach, the author has done an excellent job in enabling researchers and students alike to reproduce the analyses and learn by doing. Another quality as a textbook is the fact that every chapter ends with Workbook sections where the user is invited to exercise his or her analysis skills on supplemental datasets. Full solutions including code, results and comments are given in Appendix A (30 pages). Instructors are therefore very well served by this text, although they might want to balance the book with some more mathematical treatment depending on the target audience. After the introductory chapter on R, the book opens on graphical data exploration. Chapter 3 treats probability distributions and common sampling distributions. Under basic statistical methods (Chapter 4), distribution tests and tests on means and variances are covered. Chapter 5 deals with clustering and classification. Strangely enough, the clustering section has material on PCA, factor analysis, correspondence analysis and includes only one subsection on clustering, devoted notably to hierarchical partitioning methods. The classification part deals with decision trees, discriminant analysis and support vector machines. The regression chapter (Chapter 6) treats linear models, generalised linear models, piecewise linear models and a substantial section on models for lexical richness. The final chapter on mixed models is particularly interesting as it is one of the few text book accounts that introduce the reader to using the (innovative) lme4 package of Douglas Bates which implements linear mixed-effects models. Moreover, the case studies included in this

Analyzing linguistic data: a practical introduction to statistics using R

Evidence-based guidelines on the therapeutic use of transcranial direct current stimulation (tDCS)

The design and use of materials in the nanoscale size range for addressing medical and health-related issues continues to receive increasing interest. Research in nanomedicine spans a multitude of areas, including drug delivery, vaccine development, antibacterial, diagnosis and imaging tools, wearable devices, implants, high-throughput screening platforms, etc. using biological, nonbiological, biomimetic, or hybrid materials. Many of these developments are starting to be translated into viable clinical products. Here, we provide an overview of recent developments in nanomedicine and highlight the current challenges and upcoming opportunities for the field and translation to the clinic.

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Diverse Applications of Nanomedicine

In this article the design and fabrication of a new mechatronic platform (called “Mechatronic Board”) for behavioral analysis of children are presented and discussed. The platform is the result of a multidisciplinary design approach which merges input coming from neuroscientists, psychologists, roboticians and bioengineers, with the main goal of studying learning mechanisms driven by intrinsic motivations and curiosity. A detailed analysis of the main features of the mechatronic board is provided, focusing on the key aspects which allow studying intrinsically motivated learning in children. Finally preliminary results on curiosity-driven learning, coming from a pilot study on children are reported

/pdf/a-mechatronic-platform-for-behavioral-studies-on-infants-2rwm5yitxg.pdf

A mechatronic platform for behavioral studies on infants

In this work a novel unobtrusive technology-aided system is presented and tested for the assessment of newborns' oral-motor behavior and coordination during bottle feeding. A low-cost monitoring device was designed and developed in order to record Suction (S) and Expression (E) pressures from a typical feeding bottle. A software system was developed to automatically treat the data and analyze them. A set of measures of motor control and coordination has been implemented for the specific application to the analysis of sucking behavior. Experimental data were collected with the developed system on two groups of newborns (Healthy vs. Low Birth Weight) in a clinical setting. We identified the most sensitive S features to group differences, and analyzed their correlation with S/E coordination measures. Then, Principal Component Analysis (PCA) was used to explore the system suitability to automatically identify peculiar oral behaviors. Results suggest the suitability of the proposed system to perform an objective technology-aided assessment of the newborn's oral-motor behavior and coordination during the first days of life.

An automated system for quantitative analysis of newborns' oral-motor behavior and coordination during bottle feeding

This study analyzes motor adaptation during a redundant tasks with the wrist. The goal is threefold: (i) understanding if motor adaptation also occurs when CNS is involved in the solution of the redundancy problem; (ii) addressing whether motor strategies used to solve redundancy (i.e Donders' law) are disrupted or not during adaptation; (iii) verifying if motor strategies remain the same during adaptation and washout or they themselves adapt. First of all, our data confirm that CNS adapts its movements to the perturbation also when it is committed in the execution of a redundant task. Secondly, we showed that motor strategies used to solve redundancy (i.e Donders' law) are not disrupted during adaptation, since absolute values of thickness during the whole protocol remain in the range of physiological values. Lastly, analysis of the curvature of Donders' surfaces suggests that motor strategies, such as Donders' law, remain invariant during motor adaptation in redundant tasks.

Motor adaptation during redundant tasks with the wrist

In recent years, ever more workers are employed in sedentary jobs spending many hours sitting at video terminals. Discomfort office furniture and incorrect video screen positioning, as well as bad postural attitudes lead to the occurrence of back musculoskeletal disorders. Low back pain is one of the most widespread disease which causes a heavy socio- economic burden as it leads to absence from workplace and use of the National Health Service. In this scenario, being able to continuously evaluate poor postural attitudes may be beneficial to correct postural habits, and so to reduce the incidence of such a disease. For this purpose, many technologies capable to detect the spinal range of motions (ROMs) have been developed. Among others, the use of optical fiber sensors is gaining momentum, since these sensors allow the development of wearable, light and non-invasive monitoring systems. The present work aims at assessing the capability of a custom-made smart textile based on FBG sensors in detecting back dorsal flexion-extension (F/E) movements. Experimental results show high sensitivity to strain of the smart textile and confirm the system capability of monitoring back dorsal F/E movements in time.

Feasibility Assessment of an FBG-based Wearable System for Monitoring Back Dorsal Flexion-Extension in Video Terminal Workers

Estimating joint stiffness is of paramount importance for studying human motor control and for clinical assessment of neurological diseases. Usually stiffness estimation is performed using cumbersome instrumentations (e.g. robots), and by approximating robot joint angles and torques to the human ones. This paper proposes a methodology and an experimental setup to measure wrist joint stiffness in unstructured environments, with the twofold aim of: 1) providing a geometric framework in order to derive angular displacements and torques at the wrist Flexion/Extension (FE) and Radial/Ulnar Deviation (RUD) axes of rotation, using a subject specific kinematic model; 2) suggesting an experimental setup made of two portable sensors for motion tracking and one load cell, to allow for measurements in out-of-the-lab scenarios. We tested our method on a hardware mockup of wrist kinematics, providing a ground truth for estimated angles and torques at FE and RUD joints. The experimental validation showed average absolute errors in FE and RUD angles of 0.005 rad and 0.0167 rad respectively, and an average error of FE and RUD torques of 0.006 Nm and 0.003 Nm.

Domenico Formica

Papers

A mechatronic platform for behavioral studies on infants

An automated system for quantitative analysis of newborns' oral-motor behavior and coordination during bottle feeding

Motor adaptation during redundant tasks with the wrist

Feasibility Assessment of an FBG-based Wearable System for Monitoring Back Dorsal Flexion-Extension in Video Terminal Workers

A geometric framework for the estimation of joint stiffness of the human wrist