A tutorial review of electrical neuroimaging from group-average to single-trial event-related potentials.

This tutorial review details some of the recent advances in signal analyses applied to event-related potential (ERP) data. These "electrical neuroimaging" analyses provide reference-independent measurements of response strength and response topography that circumvent statistical and interpretational caveats of canonical ERP analysis methods while also taking advantage of the greater information provided by high-density electrode montages. Electrical neuroimaging can be applied across scales ranging from group-averaged ERPs to single-subject and single-trial datasets. We illustrate these methods with a tutorial dataset and place particular emphasis on their suitability for studies of clinical and/or developmental populations.

Assigning and combining probabilities in single-case studies

There is currently a considerable diversity of quantitative measures available for summarizing the results in single-case studies. Given that the interpretation of some of them is difficult due to the lack of established benchmarks, the current paper proposes an approach for obtaining further numerical evidence on the importance of the results, complementing the substantive criteria, visual analysis, and primary summary measures. This additional evidence consists of obtaining the statistical significance of the outcome when referred to the corresponding sampling distribution. This sampling distribution is formed by the values of the outcomes (expressed as data nonoverlap, R-squared, etc.) in case the intervention is ineffective. The approach proposed here is intended to offer the outcome"s probability of being as extreme when there is no treatment effect without the need for some assumptions that cannot be checked with guarantees. Following this approach, researchers would compare their outcomes to reference values rather than constructing the sampling distributions themselves. The integration of single-case studies is problematic, when different metrics are used across primary studies and not all raw data are available. Via the approach for assigning p values it is possible to combine the results of similar studies regardless of the primary effect size indicator. The alternatives for combining probabilities are discussed in the context of single-case studies pointing out two potentially useful methods one based on a weighted average and the other on the binomial test.

Regression-based techniques for statistical decision making in single-case designs

The present study evaluates the performance of four methods for estimating regression coefficients used to make statistical decisions regarding intervention effectiveness in single-case designs. Ordinary least squares estimation is compared to two correction techniques dealing with general trend and one eliminating autocorrelation whenever it is present. Type I error rates and statistical power are studied for experimental conditions defined by the presence or absence of treatment effect (change in level or in slope), general trend, and serial dependence. The results show that empirical Type I error rates do not approximate the nominal ones in presence of autocorrelation or general trend when ordinary and generalized least squares are applied. The techniques controlling trend show lower false alarm rates, but prove to be insufficiently sensitive to existing treatment effects. Consequently, the use of the statistical significance of the regression coefficients for detecting treatment effects is not recommended for short data series.

Assessing functional relations in single-case designs: Quantitative proposals in the context of the evidence-based movement

In the context of the evidence-based practices movement, the emphasis on computing effect sizes and combining them via meta-analysis does not preclude the demonstration of functional relations. For the latter aim, we propose to augment the visual analysis to add consistency to the decisions made on the existence of a functional relation without losing sight of the need for a methodological evaluation of what stimuli and reinforcement or punishment are used to control the behavior. Four options for quantification are reviewed, illustrated, and tested with simulated data. These quantifications include comparing the projected baseline with the actual treatment measurements, on the basis of either parametric or nonparametric statistics. The simulated data used to test the quantifications include nine data patterns in terms of the presence and type of effect and comprising ABAB and multiple baseline designs. Although none of the techniques is completely flawless in terms of detecting a functional relation only when it is present but not when it is absent, an option based on projecting split-middle trend and considering data variability as in exploratory data analysis proves to be the best performer for most data patterns. We suggest that the information on whether a functional relation has been demonstrated should be included in meta-analyses. It is also possible to use as a weight the inverse of the data variability measure used in the quantification for assessing the functional relation. We offer an easy to use code for open-source software for implementing some of the quantifications.

Assigning and combining probabilities in single-case designs: A second study

The present study builds on a previous proposal for assigning probabilities to the outcomes computed using different primary indicators in single-case studies. These probabilities are obtained comparing the outcome to previously tabulated reference values and reflect the likelihood of the results in case there was no intervention effect. The current study explores how well different metrics are translated into p values in the context of simulation data. Furthermore, two published multiple baseline data sets are used to illustrate how well the probabilities could reflect the intervention effectiveness as assessed by the original authors. Finally, the importance of which primary indicator is used in each data set to be integrated is explored; two ways of combining probabilities are used: a weighted average and a binomial test. The results indicate that the translation into p values works well for the two nonoverlap procedures, with the results for the regression-based procedure diverging due to some undesirable features of its performance. These p values, both when taken individually and when combined, were well-aligned with the effectiveness for the real-life data. The results suggest that assigning probabilities can be useful for translating the primary measure into the same metric, using these probabilities as additional evidence on the importance of behavioral change, complementing visual analysis and professional's judgments.

Handwriting Intervention: Impact on the Reading and Writing Abilities of High School Students

Handwriting is a functional task that is used to communicate thoughts using a written code. Research findings have indicated that handwriting is related to learning to read and learning to write. The purposes of this research project were to determine if a handwriting intervention would increase abilities in reading and writing skills, in graphomotor and visual-motor integration skills, and improve the participants’ self-perceptions and self-descriptions pertaining to handwriting enjoyment, competence, and effort. A single-subject research design was implemented with four struggling high school students who each received 10.5 to 15.5 hours of cursive handwriting intervention using the ez Write program. In summary, the findings indicated that the students showed significant improvements in aspects of reading and writing; that they improved significantly in their cursive writing abilities; and that their self-perceptions concerning their handwriting experience and competence improved. The contribution of handwriting to academic achievement and vocational success can no longer be neglected.

Polyunsaturated fatty acids of the n-6 and n-3 series: effects on postprandial lipid and apolipoprotein levels in healthy men

OBJECTIVE: The present study was carried out to determine effects of test meals of different fatty acid compositions on postprandial lipoprotein and apolipoprotein metabolism. DESIGN: The study was a randomized, single blind design. SETTING: The study was carried out in the Clinical Investigation Unit of the Royal Surrey County Hospital. SUBJECTS: Twelve male normal subjects with an average age of 22.4 +/- 1.4 years (mean +/- SD) were selected from the student population of the University of Surrey; one subject dropped out of the study because he found the test meal unpalatable. INTERVENTIONS: The subjects were given three evening test meals on three separate occasions, in which the oils used were either a mixed oil (rich in saturated fatty acids and approximated the fatty acid intake of the current UK diet), corn oil (rich in n-6 fatty acids), or fish oil (rich in n-3 fatty acids) 40 g of the oil under investigation were incorporated into a rice-based test meal. Triacylglycerol-rich lipoproteins-triacylglycerol (TRL-TAG), TRL-cholesterol (TRL-cholesterol), plasma-TAG, plasma cholesterol (T-C), and serum apolipoprotein A-I and B (apo A-I and B) responses were measured. Postprandial responses were followed for 11 h. RESULTS: Postprandial plasma-TAG responses, calculated as incremental areas under the response curves (IAUC) were significantly reduced following the fish oil meal [365.5 +/- 145.4 mmol/l x min (mean +/- SD)[ compared with the mixed oil meal (552.0 +/- 141.7 mmol/l x min) (P < 0.05) and there was a strong trend towards the same direction in the TRL-TAG responses. In all instances, plasma-and TRL-TAG showed a biphasic response with increased concentrations occurring at 1h and between 3 and 7h postprandially. TRL-cholesterol, T-C, and serum apo A-I and B responses to the three meals were similar. CONCLUSIONS: The findings support the view that fish oils decrease postprandial lipaemia and this may be an important aspect of their beneficial effects in reducing risk of coronary heart disease (CHD). Further work is required to determine the mechanisms responsible for this effect.

Phonological therapy in jargon aphasia: effects on naming and neologisms

Background: Jargon aphasia is one of the most intractable forms of aphasia with limited recommendation on amelioration of associated naming difficulties and neologisms. The few naming therapy studies that exist in jargon aphasia have utilized either semantic or phonological approaches but the results have been equivocal. Moreover, the effect of therapy on characteristics of neologisms is less explored. Aims: This study investigates the effectiveness of a phonological naming therapy (i.e., phonological component analysis, PCA) on picture naming abilities and on quantitative and qualitative changes in neologisms for an individual with jargon aphasia (FF). Methods: FF showed evidence of jargon aphasia with severe naming difficulties and produced a very high proportion of neologisms. A single-subject multiple probe design across behaviors was employed to evaluate the effects of PCA therapy on the accuracy for three sets of words. In therapy, a phonological components analysis chart was used to identify five phonological components (i.e., rhymes, first sound, first sound associate, final sound, number of syllables) for each target word. Generalization effects—change in percent accuracy and error pattern—were examined comparing pre-and post-therapy responses on the Philadelphia Naming Test and these responses were analyzed to explore the characteristics of the neologisms. The quantitative change in neologisms was measured by change in the proportion of neologisms from pre- to post-therapy and the qualitative change was indexed by the phonological overlap between target and neologism. Results: As a consequence of PCA therapy, FF showed a significant improvement in his ability to name the treated items. His performance in maintenance and follow-up phases remained comparable to his performance during the therapy phases. Generalization to other naming tasks did not show a change in accuracy but distinct differences in error pattern (an increase in proportion of real word responses and a decrease in proportion of neologisms) were observed. Notably, the decrease in neologisms occurred with a corresponding trend for increase in the phonological similarity between the neologisms and the targets. Conclusions: This study demonstrated the effectiveness of a phonological therapy for improving naming abilities and reducing the amount of neologisms in an individual with severe jargon aphasia. The positive outcome of this research is encouraging, as it provides evidence for effective therapies for jargon aphasia and also emphasizes that use of the quality and quantity of errors may provide a sensitive outcome measure to determine therapy effectiveness, in particular for client groups who are difficult to treat.

Effects of pramipexole on the processing of rewarding and aversive taste stimuli

Rationale: Pramipexole, a D2/D3 dopamine receptor agonist, has been implicated in the development of impulse control disorders in patients with Parkinson's disease. Investigation of single doses of pramipexole in healthy participants in reward-based learning tasks has shown inhibition of the neural processing of reward, presumptively through stimulation of dopamine autoreceptors. Objectives: This study aims to examine the effects of pramipexole on the neural response to the passive receipt of rewarding and aversive sight and taste stimuli. Methods: We used functional magnetic resonance imaging to examine the neural responses to the sight and taste of pleasant (chocolate) and aversive (mouldy strawberry) stimuli in 16 healthy volunteers who received a single dose of pramipexole (0.25 mg) and placebo in a double-blind, within-subject, design. Results: Relative to placebo, pramipexole treatment reduced blood oxygen level-dependent activation to the chocolate stimuli in the areas known to play a key role in reward, including the ventromedial prefrontal cortex, the orbitofrontal cortex, striatum, thalamus and dorsal anterior cingulate cortex. Pramipexole also reduced activation to the aversive condition in the dorsal anterior cingulate cortex. There were no effects of pramipexole on the subjective ratings of the stimuli. Conclusions: Our results are consistent with an ability of acute, low-dose pramipexole to diminish dopamine-mediated responses to both rewarding and aversive taste stimuli, perhaps through an inhibitory action of D2/3 autoreceptors on phasic burst activity of midbrain dopamine neurones. The ability of pramipexole to inhibit aversive processing might potentiate its adverse behavioural effects and could also play a role in its proposed efficacy in treatment-resistant depression.

Novel flavours paired with glutamate condition increased intake in older adults in the absence of changes in liking

Previous research on the repeat exposure to a novel flavour combined with monosodium glutamate (MSG) has shown an increase in liking and consumption for the particular flavour. The aim of the current work was to investigate whether this could also be observed in the case of older people, since they are most affected by undernutrition in the developed world and ways to increase consumption of food are of significant importance for this particular age group. For this study, 40 older adults (age 65-88) repeatedly consumed potato soup with two novel flavours (lemongrass and cumin) which were either with or without a high level of MSG (5%w/w). A randomized single blind within-subject design was implemented, where each participant was exposed to both soup flavours three times over 6 days, with one of the soup flavours containing MSG. After three repeat exposures, consumption increased significantly for the soups where the flavours had contained MSG during the repeated exposure (mean weight consumed increased from 123 to 164 g, p=0.017), implying that glutamate conditioned for increased wanting and consumption, despite the fact that the liking for the soup had not increased.

Method for exploratory cluster analysis and visualisation of single-trial ERP ensembles

Background: The validity of ensemble averaging on event-related potential (ERP) data has been questioned, due to its assumption that the ERP is identical across trials. Thus, there is a need for preliminary testing for cluster structure in the data. New method: We propose a complete pipeline for the cluster analysis of ERP data. To increase the signalto-noise (SNR) ratio of the raw single-trials, we used a denoising method based on Empirical Mode Decomposition (EMD). Next, we used a bootstrap-based method to determine the number of clusters, through a measure called the Stability Index (SI). We then used a clustering algorithm based on a Genetic Algorithm (GA)to define initial cluster centroids for subsequent k-means clustering. Finally, we visualised the clustering results through a scheme based on Principal Component Analysis (PCA). Results: After validating the pipeline on simulated data, we tested it on data from two experiments – a P300 speller paradigm on a single subject and a language processing study on 25 subjects. Results revealed evidence for the existence of 6 clusters in one experimental condition from the language processing study. Further, a two-way chi-square test revealed an influence of subject on cluster membership.

An Information Theory framework for two-stage binary image operator design

The design of translation invariant and locally defined binary image operators over large windows is made difficult by decreased statistical precision and increased training time. We present a complete framework for the application of stacked design, a recently proposed technique to create two-stage operators that circumvents that difficulty. We propose a novel algorithm, based on Information Theory, to find groups of pixels that should be used together to predict the Output Value. We employ this algorithm to automate the process of creating a set of first-level operators that are later combined in a global operator. We also propose a principled way to guide this combination, by using feature selection and model comparison. Experimental results Show that the proposed framework leads to better results than single stage design. (C) 2009 Elsevier B.V. All rights reserved.

Organizational design as an enabler for innovation: evidence from a German Mechanical Engineering Company

Over the past two decades there has been a profusion of empirical studies of organizational design and its relationship to efficiency, productivity and flexibility of an organization. In parallel, there has been a wide range of studies about innovation management in different kind of industries and firms. However, with some exceptions, the organizational and innovation management bodies of literature tend to examine the issues of organizational design and innovation management individually, mainly in the context of large firms operating at the technological frontier. There seems to be a scarcity of empirical studies that bring together organizational design and innovation and examine them empirically and over time in the context of small and medium sized enterprises. This dissertation seeks to provide a small contribution in that direction. This dissertation examines the dynamic relationship between organizational design and innovation. This relationship is examined on the basis of a single-case design in a medium sized mechanical engineering company in Germany. The covered time period ranges from 1958 until 2009, although the actual focus falls on the recent past. This dissertation draws on first-hand qualitative empirical evidence gathered through extensive field work. The main findings are: 1. There is always a bundle of organizational dimensions which impacts innovation. These main organizational design dimensions are: (1) Strategy & Leadership, (2) Resources & Capabilities, (3) Structure, (4) Culture, (5) Networks & Partnerships, (6) Processes and (7) Knowledge Management. However, the importance of the different organizational design dimensions changes over time. While for example for the production of simple, standardized parts, a simple organizational design was appropriate, the company needed to have a more advanced organizational design in order to be able to produce customized, complex parts with high quality. Hence the technological maturity of a company is related to its organizational maturity. 2. The introduction of innovations of the analyzed company were highly dependent on organizational conditions which enabled their introduction. The results of the long term case study show, that some innovations would not have been introduced successfully if the organizational elements like for example training and qualification, the build of network and partnerships or the acquisition of appropriate resources and capabilities, were not in place. Hence it can be concluded, that organizational design is an enabling factor for innovation. These findings contribute to advance our understanding of the complex relationship between organizational design and innovation. This highlights the growing importance of a comprehensive, innovation stimulating organizational design of companies. The results suggest to managers that innovation is not only dependent on a single organizational factor but on the appropriate, comprehensive design of the organization. Hence manager should consider to review regularly the design of their organizations in order to maintain a innovation stimulating environment.

Análise dos efeitos de um plano educacional individualizado no desenvolvimento acadêmico e funcional de um aluno com transtorno do espectro do autismo

Given the paradigm of inclusive education, the presence of students with autism spectrum disorder in regular schools has become more significant in recent years. Studies have revealed, however, deficits in academic participation of these students in these settings. Among the factors contributing to this phenomenon include poor teacher training and the lack of strategies to promote curriculum access. The aim of this study was to develop an instrument that would promote academic inclusion of a student with autism through procedures that could simultaneously empower the teacher. In this perspective, the study aimed to analyze the effects of an Individualized Educational Plan (IEP), developed collaboratively with teachers, on the academic and functional development of a student with autism in an early childhood education setting. Data were collected in a private school located in the city of Natal in Rio Grande do Norte, in the course of the academic year 2012. In addition to the student with autism, one teacher, a specialized educator, and four teacher aides participated in the study. The research used a single subject quasi-experimental design (AB) as well as qualitative methods of data analysis. The study was conducted in three phases: characterization, baseline and intervention. The first comprised interviews with the child´s parents and teachers, as well as the identification of two routines focus of intervention. In the second phase, the amount of time the student spent engaged in the selected routines during baseline was analyzed. In the third phase, the researcher prepared, collaboratively with the teachers, an individualized educational plan (IEP) for the student. Finally, the IEP was implemented by the teachers. The results indicated qualitative and quantitative changes in student´s participation in academic and functional tasks after the intervention program

Ensino e aprendizagem de avaliação funcional descritiva na atuação profissional de professores de ciências no ensino fundamental

Pós-graduação em Educação para a Ciência - FC