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

http://ecuanst.weebly.com/uploads/6/0/6/0/60601319/cognitive_rehabilitation-_meta-analysis_and_review.pdf

Evidence-based cognitive rehabilitation: updated review of the literature from 2003 through 2008.

tical perspective. For instance, there are only three passing references to kuru in a book of 650 pages. This edition reflects the renewed interest in the immunological theories of multiple sclerosis. More than half the text is devoted to Professor Lumsden's analysis of the pathoIogy and, in particular, the chemical pathology of the immune response. There is a great deal of original work devoted to the chemistry and behaviour of the immunoglobulins. Much of this appears in specialist journals and one must be grateful for the critical summary provided here. Professor Lumsden unequivocally sees the key to the problem of multiple sclerosis in the study of its immunochemistry, relegating infection by a virus or a slow virus to a quite subsidiary role. The clinical studies drawing on wide practical experience help to get one's prejudices about the illness onto a more reasoned footing. The section on treatment is still sadly limited. Dr. McAlpine found little to add to the regime which he described in 1955. McAlpine, Lumsden, and Acheson's reappraisal is an essential reference for the practising neurologist and the new edition makes important modification of and changes in emphasis from the edition of 1965.

https://jnnp.bmj.com/content/jnnp/36/5/894.3.full.pdf

The assessment of aphasia and related disorders

Research on how the brain processes music is emerging as a rich and stimulating area of investigation of perception, memory, emotion, and performance. Results emanating from both lesion studies and neuroimaging techniques are reviewed and integrated for each of these musical functions. We focus our attention on the common core of musical abilities shared by musicians and nonmusicians alike. Hence, the effect of musical training on brain plasticity is examined in a separate section, after a review of the available data regarding music playing and reading skills that are typically cultivated by musicians. Finally, we address a currently debated issue regarding the putative existence of music-specific neural networks. Unfortunately, due to scarcity of research on the macrostructure of music organization and on cultural differences, the musical material under focus is at the level of the musical phrase, as typically used in Western popular music.

Brain Organization for Music Processing

The study of speech production has largely been divided into investigations of lower-level articulatory motor control and of higher-level linguistic processing, with these research traditions rarely interacting. In this Opinion article, Hickok argues that these approaches have much to offer each other, and he presents a model of speech production that incorporates ideas from both research traditions and findings from neuroscientific studies of sensorimotor integration. Speech production has been studied predominantly from within two traditions, psycholinguistics and motor control. These traditions have rarely interacted, and the resulting chasm between these approaches seems to reflect a level of analysis difference: whereas motor control is concerned with lower-level articulatory control, psycholinguistics focuses on higher-level linguistic processing. However, closer examination of both approaches reveals a substantial convergence of ideas. The goal of this article is to integrate psycholinguistic and motor control approaches to speech production. The result of this synthesis is a neuroanatomically grounded, hierarchical state feedback control model of speech production.

/pdf/computational-neuroanatomy-of-speech-production-4gegz6kngn.pdf

Computational neuroanatomy of speech production

We report the results of a large-scale picture naming experiment in which we evaluated the potential contribution of nine theoretically relevant factors to naming latencies. The experiment included a large number of items and a large sample of participants. In order to make this experiment as similar as possible to classic picture naming experiments, participants were familiarized with the materials during a training session. Speeded naming latencies were determined by a software key on the basis of the digital recording of the responses. The effects of various variables on these latencies were assessed with multiple regression techniques, using a repeated measures design. The interpretation of the observed effects is discussed in relation to previous studies and current views on lexical access during speech production.

/pdf/predictors-of-picture-naming-speed-14y3fw6t7p.pdf

Predictors of picture naming speed.

http://www.brainmusic.org/EducationalActivitiesFolder/DiPietro_amusia2004.pdf

Receptive amusia: temporal auditory processing deficit in a professional musician following a left temporo-parietal lesion.

https://www.unige.ch/fapse/psycholinguistique/files/4614/2183/7392/LaganaroAlarioJML06.pdf

On the locus of the syllable frequency effect in speech production

Most EEG studies analysing speech production with event related brain potential (ERP) have adopted silent metalinguistic tasks or delayed or tacit picture naming in order to avoid possible artefacts during motor preparation. A central issue in the interpretation of these results is whether the processes involved in those tasks are comparable to those involved in overt speech production. In the present study we addressed a methodological issue about the integration of stimulus-aligned and response-aligned ERPs in immediate overt picture naming in comparison to delayed production, coupled with a theoretical point on the effect of word Age of Acquisition (AoA). High density EEG recordings were used and waveform analyses and spatio-temporal segmentation were combined on stimulus-aligned and response-aligned ERPs. The same sequence and duration of topographic maps appeared in the immediate and delayed production until around 350 ms after picture onset, revealing similar encoding processes until the beginning of phonological encoding, but modulations linked to word AoA were only observed in the immediate production. Considering stimulus-aligned and response-aligned ERPs together allowed to identify that a stable topography starting around 350 ms lasts 30 ms longer for late-acquired than for early-acquired words. This difference falls within the time-window of phonological encoding and its modulation can be linked to the longer production latencies for late-acquired words.

/pdf/comparing-electrophysiological-correlates-of-word-production-1il6uxjpnw.pdf

Comparing Electrophysiological Correlates of Word Production in Immediate and Delayed Naming Through the Analysis of Word Age of Acquisition Effects

https://archive-ouverte.unige.ch/unige:27439/ATTACHMENT01

Marina Laganaro

Papers

Predictors of picture naming speed.

Receptive amusia: temporal auditory processing deficit in a professional musician following a left temporo-parietal lesion.

On the locus of the syllable frequency effect in speech production

Comparing Electrophysiological Correlates of Word Production in Immediate and Delayed Naming Through the Analysis of Word Age of Acquisition Effects

Time course of word production in fast and slow speakers: A high density ERP topographic study