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

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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

Transcranial Magnetic Stimulation (TMS) is a non-invasive technique that produces excitatory depolarization in the neurons located in the cerebral cortex. In order to proficiently stimulate a specific cerebral area it is of main importance the correct positioning and maintaining of the magnetic coil, while avoiding the mismatch due to subject head-coil relative movement.

Hot spot hound: A novel robot-assisted platform for enhancing TMS performance

Heart rate variability (HRV) indexes are becoming useful in various applications, from better diagnosis and prevention of diseases to predicting stress levels. Typically, HRV indexes are retrieved from the heart’s electrical activity collected with an electrocardiographic signal (ECG). Heart-induced mechanical signals recorded from the body’s surface can be utilized to record the mechanical activity of the heart and, in turn, extract HRV indexes from interbeat intervals (IBIs). Among others, accelerometers and gyroscopes can be used to register IBIs from precordial accelerations and chest wall angular velocities. However, unlike electrical signals, the morphology of mechanical ones is strongly affected by body posture. In this paper, we investigated the feasibility of estimating the most common linear and non-linear HRV indexes from accelerometer and gyroscope data collected with a wearable skin-interfaced Inertial Measurement Unit (IMU) positioned at the xiphoid level. Data were collected from 21 healthy volunteers assuming two common postures (i.e., seated and lying). Results show that using the gyroscope signal in the lying posture allows accurate results in estimating IBIs, thus allowing extracting of linear and non-linear HRV parameters that are not statistically significantly different from those extracted from reference ECG.

/pdf/linear-and-non-linear-heart-rate-variability-indexes-from-3itysk09.pdf

Linear and Non-Linear Heart Rate Variability Indexes from Heart-Induced Mechanical Signals Recorded with a Skin-Interfaced IMU

We present a system to provide the user with real time proprioceptive feedback regarding the state of a supernumerary robotic limb (SRL). The system converted the robot kinematics into a vibration amplitude-frequency value, using a custom electronic board. Four eccentric-motors placed on the leg delivered the vibrotactile pattern to subjects. We measured the accuracy in real-time tracking of the robot end-effector position and the delay from the robot movement onset. We tested four subjects in a preliminary study, and we found an average Position Error and a Delay of 0.084 ± 0.010 m and 1.169 ± 0.408 s respectively, which validated the feasibility of the presented setup. Increasing the learning phase duration should further improve subject performance. Additionally, the present platform could easily be employed to test the efficacy of different feedbacks (such as joint angles and torques) for real time tracking of SRL.

Cartesian Space Feedback for Real Time Tracking of a Supernumerary Robotic Limb: a Pilot Study

In the present paper we describe an instrumented toy to study auditory preferences in young children. After brief considerations on the theoretical framework, the design of the mechanical, electronic and software components of the system is presented. The system allows for: (a) producing audio stimuli according to how children play with the toy; (b) assessing children's motor behaviour during the interaction. The device is provided with a sensor core enabling the assessment of manipulation in terms of angular displacement with errors lower than 1°. The laboratory validation is presented and discussed in details. Moreover, a pilot trial on two children aged 34 and 35 months is described and discussed. Results show the appropriateness of the technology to the experimental aims, and encourage research on methods based on the interaction between perception and action to investigate music preferences in young listeners.

A sensor-based approach to study sound perception in children

This study focuses on the development of a noninvasive system for monitoring the force exerted by the anesthesiologist on the syringe during peripheral nerve blocks (PNBs). During this procedure, local anesthetic solutions are injected around a specific peripheral nerve. The injection pressure, and in turn the force exerted by the anesthesiologist may be related to the efficacy and safety of PNBs. The proposed system is based on i) a mechanical part fixed to the syringe used for the injection; ii) three piezoresistive force sensors which measure the force exerted by the anesthesiologist to inject the anesthetic solution. Indeed, the clinician performs the PNB by pushing with three fingers on three different parts of the syringe; iii) a custom printed circuit board, which pre-processes, collects and transmits the relevant signals.During the calibration of the three sensors, the clinical scenario has been mimicked by interposing the finger of a volunteer between the indenter of the testing machine and the active area of each sensor. These experiments provide the calibration curve of the system (for each sensor), which allows estimating the force exerted by the anesthesiologist during the injection of the anesthetic solution during PNB. Finally, the system has been tested on a patient undergoing PNB on adductor canal. During the whole experiment, the system was able to correctly follow the force exerted by the three fingertips of the clinician. These results are promising, but they can be considered just a first step toward the development of a system for supporting the clinician during PNB.

Domenico Formica

Papers

Hot spot hound: A novel robot-assisted platform for enhancing TMS performance

Linear and Non-Linear Heart Rate Variability Indexes from Heart-Induced Mechanical Signals Recorded with a Skin-Interfaced IMU

Cartesian Space Feedback for Real Time Tracking of a Supernumerary Robotic Limb: a Pilot Study

A sensor-based approach to study sound perception in children

Force monitoring during Peripheral Nerve Blocks: design and feasibility assessment of a new noninvasive system