About the role of visual field defects in pure alexia

Pure alexia is an acquired reading disorder characterized by a disproportionate prolongation of reading time as a function of word length. Although the vast majority of cases reported in the literature show a right-sided visual defect, little is known about the contribution of this low-level visual impairment to their reading difficulties. The present study was aimed at investigating this issue by comparing eye movement patterns during text reading in six patients with pure alexia with those of six patients with hemianopic dyslexia showing similar right-sided visual field defects. We found that the role of the field defect in the reading difficulties of pure alexics was highly deficit-specific. While the amplitude of rightward saccades during text reading seems largely determined by the restricted visual field, other visuo-motor impairments-particularly the pronounced increases in fixation frequency and viewing time as a function of word length-may have little to do with their visual field defect. In addition, subtracting the lesions of the hemianopic dyslexics from those found in pure alexics revealed the largest group differences in posterior parts of the left fusiform gyrus, occipito-temporal sulcus and inferior temporal gyrus. These regions included the coordinate assigned to the centre of the visual word form area in healthy adults, which provides further evidence for a relation between pure alexia and a damaged visual word form area. Finally, we propose a list of three criteria that may improve the differential diagnosis of pure alexia and allow appropriate therapy recommendations.

Event-relating to potential dementia. Semantic processing in the course of healthy and pathological aging

While most healthy elderly are able to manage their everyday activities, studies showed that there are both stable and declining abilities during healthy aging. For example, there is evidence that semantic memory processes which involve controlled retrieval mechanism decrease, whereas the automatic functioning of the semantic network remains intact. In contrast, patients with Alzheimer’s disease (AD) suffer from episodic and semantic memory impairments aggravating their daily functioning. In AD, severe episodic as well as semantic memory deficits are observable. While the hallmark symptom of episodic memory decline in AD is well investigated, the underlying mechanisms of semantic memory deterioration remain unclear. By disentangling the semantic memory impairments in AD, the present thesis aimed to improve early diagnosis and to find a biomarker for dementia. To this end, a study on healthy aging and a study with dementia patients were conducted investigating automatic and controlled semantic word retrieval. Besides the inclusion of AD patients, a group of participants diagnosed with semantic dementia (SD) – showing isolated semantic memory loss – was assessed. Automatic and controlled semantic word retrieval was measured with standard neuropsychological tests and by means of event-related potentials (ERP) recorded during the performance of a semantic priming (SP) paradigm. Special focus was directed to the N400 or N400-LPC (late positive component) complex, an ERP that is sensitive to the semantic word retrieval. In both studies, data driven topographical analyses were applied. Furthermore, in the patient study, the combination of the individual baseline cerebral blood flow (CBF) with the N400 topography of each participant was employed in order to relate altered functional electrophysiology to the pathophysiology of dementia. Results of the aging study revealed that the automatic semantic word retrieval remains stable during healthy aging, the N400-LPC complex showed a comparable topography in contrast to the young participants. Both patient groups showed automatic SP to some extent, but strikingly the ERP topographies were altered compared to healthy controls. Most importantly, the N400 was identified as a putative marker for dementia. In particular, the degree of the topographical N400 similarity was demonstrated to separate healthy elderly from demented patients. Furthermore, the marker was significantly related to baseline CBF reduction in brain areas relevant for semantic word retrieval. Summing up, the first major finding of the present thesis was that all groups showed semantic priming, but that the N400 topography differed significantly between healthy and demented elderly. The second major contribution was the identification of the N400 similarity as a putative marker for dementia. To conclude, the present thesis added evidence of preserved automatic processing during healthy aging. Moreover, a possible marker which might contribute to an improved diagnosis and lead consequently to a more effective treatment of dementia was presented and has to be further developed.

Automatic Labeling of Software Components and their Evolution using Log-Likelihood Ratio of Word Frequencies in Source Code

As more and more open-source software components become available on the internet we need automatic ways to label and compare them. For example, a developer who searches for reusable software must be able to quickly gain an understanding of retrieved components. This understanding cannot be gained at the level of source code due to the semantic gap between source code and the domain model. In this paper we present a lexical approach that uses the log-likelihood ratios of word frequencies to automatically provide labels for software components. We present a prototype implementation of our labeling/comparison algorithm and provide examples of its application. In particular, we apply the approach to detect trends in the evolution of a software system.

Response to neoadjuvant treatment of invasive ductal breast carcinomas including outcome evaluation: MRI analysis by an automatic CAD system in comparison to visual evaluation

BACKGROUND The aim of this study was to evaluate imaging-based response to standardized neoadjuvant chemotherapy (NACT) regimen by dynamic contrast-enhanced magnetic resonance mammography (DCE-MRM), whereas MR images were analyzed by an automatic computer-assisted diagnosis (CAD) system in comparison to visual evaluation. MRI findings were correlated with histopathologic response to NACT and also with the occurrence of metastases in a follow-up analysis. PATIENTS AND METHODS Fifty-four patients with invasive ductal breast carcinomas received two identical MRI examinations (before and after NACT; 1.5T, contrast medium gadoteric acid). Pre-therapeutic images were compared with post-therapeutic examinations by CAD and two blinded human observers, considering morphologic and dynamic MRI parameters as well as tumor size measurements. Imaging-assessed response to NACT was compared with histopathologically verified response. All clinical, histopathologic, and DCE-MRM parameters were correlated with the occurrence of distant metastases. RESULTS Initial and post-initial dynamic parameters significantly changed between pre- and post-therapeutic DCE-MRM. Visually evaluated DCE-MRM revealed sensitivity of 85.7%, specificity of 91.7%, and diagnostic accuracy of 87.0% in evaluating the response to NACT compared to histopathology. CAD analysis led to more false-negative findings (37.0%) compared to visual evaluation (11.1%), resulting in sensitivity of 52.4%, specificity of 100.0%, and diagnostic accuracy of 63.0%. The following dynamic MRI parameters showed significant associations to occurring metastases: Post-initial curve type before NACT (entire lesions, calculated by CAD) and post-initial curve type of the most enhancing tumor parts after NACT (calculated by CAD and manually). CONCLUSIONS In the accurate evaluation of response to neoadjuvant treatment, CAD systems can provide useful additional information due to the high specificity; however, they cannot replace visual imaging evaluation. Besides traditional prognostic factors, contrast medium-induced dynamic MRI parameters reveal significant associations to patient outcome, i.e. occurrence of distant metastases.

A Fully Automatic Calibration Framework for Navigated Ultrasound Imaging

Navigated ultrasound (US) imaging is used for the intra-operative acquisition of 3D image data during imageguided surgery. The presented approach includes the design of a compact and easy to use US calibration device and its integration into a software application for navigated liver surgery. User interaction during the calibration process is minimized through automatic detection of the calibration process followed by automatic image segmentation, calculation of the calibration transform and validation of the obtained result. This leads to a fast, interaction-free and fully automatic calibration procedure enabling intra-operative

Core networks for visual-concrete and abstract thought content: a brain electric microstate analysis

Commonality of activation of spontaneously forming and stimulus-induced mental representations is an often made but rarely tested assumption in neuroscience. In a conjunction analysis of two earlier studies, brain electric activity during visual-concrete and abstract thoughts was studied. The conditions were: in study 1, spontaneous stimulus-independent thinking (post-hoc, visual imagery or abstract thought were identified); in study 2, reading of single nouns ranking high or low on a visual imagery scale. In both studies, subjects' tasks were similar: when prompted, they had to recall the last thought (study 1) or the last word (study 2). In both studies, subjects had no instruction to classify or to visually imagine their thoughts, and accordingly were not aware of the studies' aim. Brain electric data were analyzed into functional topographic brain images (using LORETA) of the last microstate before the prompt (study 1) and of the word-type discriminating event-related microstate after word onset (study 2). Conjunction analysis across the two studies yielded commonality of activation of core networks for abstract thought content in left anterior superior regions, and for visual-concrete thought content in right temporal-posterior inferior regions. The results suggest that two different core networks are automatedly activated when abstract or visual-concrete information, respectively, enters working memory, without a subject task or instruction about the two classes of information, and regardless of internal or external origin, and of input modality. These core machineries of working memory thus are invariant to source or modality of input when treating the two types of information.

Electrophysiological and behavioral correlates of stable automatic semantic retrieval in aging

Previous studies have shown both declining and stable semantic-memory abilities during healthy aging. There is consistent evidence that semantic processes involving controlled mechanisms weaken with age. In contrast, results of aging studies on automatic semantic retrieval are often inconsistent, probably due to methodological limitations and differences. The present study therefore examines age-related alterations in automatic semantic retrieval and memory structure with a novel combination of critical methodological factors, i.e., the selection of subjects, a well-designed paradigm, and electrophysiological methods that result in unambiguous signal markers. Healthy young and elderly participants performed lexical decisions on visually presented word/non-word pairs with a stimulus onset asynchrony (SOA) of 150 ms. Behavioral and electrophysiological data were measured, and the N400-LPC complex, an event-related potential component sensitive to lexical-semantic retrieval, was analyzed by power and topographic distribution of electrical brain activity. Both age groups exhibited semantic priming (SP) and concreteness effects in behavioral reaction time and the electrophysiological N400-LPC complex. Importantly, elderly subjects did not differ significantly from the young in their lexical decision and SP performances as well as in the N400-LPC SP effect. The only difference was an age-related delay measured in the N400-LPC microstate. This could be attributed to existing age effects in controlled functions, as further supported by the replicated age difference in word fluency. The present results add new behavioral and neurophysiological evidence to earlier findings, by showing that automatic semantic retrieval remains stable in global signal strength and topographic distribution during healthy aging.

The word-length effect in acquired alexia, and real and virtual hemianopia

A word-length effect is often described in pure alexia, with reading time proportional to the number of letters in a word. Given the frequent association of right hemianopia with pure alexia, it is uncertain whether and how much of the word-length effect may be attributable to the hemifield loss. To isolate the contribution of the visual field defect, we simulated hemianopia in healthy subjects with a gaze-contingent paradigm during an eye-tracking experiment. We found a minimal word-length effect of 14 ms/letter for full-field viewing, which increased to 38 ms/letter in right hemianopia and to 31 ms/letter in left hemianopia. We found a correlation between mean reading time and the slope of the word-length effect in hemianopic conditions. The 95% upper prediction limits for the word-length effect were 51 ms/letter in subjects with full visual fields and 161 ms/letter with simulated right hemianopia. These limits, which can be considered diagnostic criteria for an alexic word-length effect, were consistent with the reading performance of six patients with diagnoses based independently on perimetric and imaging data: two patients with probable hemianopic dyslexia, and four with alexia and lesions of the left fusiform gyrus, two with and two without hemianopia. Two of these patients also showed reduction of the word-length effect over months, one with and one without a reading rehabilitation program. Our findings clarify the magnitude of the word-length effect that originates from hemianopia alone, and show that the criteria for a word-length effect indicative of alexia differ according to the degree of associated hemifield loss.

Semi-automatic segmentation of fetal cardiac cavities: progress towards an automated fetal echocardiogram

OBJECTIVE: To develop a novel application of a tool for semi-automatic volume segmentation and adapt it for analysis of fetal cardiac cavities and vessels from heart volume datasets. METHODS: We studied retrospectively virtual cardiac volume cycles obtained with spatiotemporal image correlation (STIC) from six fetuses with postnatally confirmed diagnoses: four with normal hearts between 19 and 29 completed gestational weeks, one with d-transposition of the great arteries and one with hypoplastic left heart syndrome. The volumes were analyzed offline using a commercially available segmentation algorithm designed for ovarian folliculometry. Using this software, individual 'cavities' in a static volume are selected and assigned individual colors in cross-sections and in 3D-rendered views, and their dimensions (diameters and volumes) can be calculated. RESULTS: Individual segments of fetal cardiac cavities could be separated, adjacent segments merged and the resulting electronic casts studied in their spatial context. Volume measurements could also be performed. Exemplary images and interactive videoclips showing the segmented digital casts were generated. CONCLUSION: The approach presented here is an important step towards an automated fetal volume echocardiogram. It has the potential both to help in obtaining a correct structural diagnosis, and to generate exemplary visual displays of cardiac anatomy in normal and structurally abnormal cases for consultation and teaching.

Automatic algorithm for monitoring systolic pressure variation and difference in pulse pressure

BACKGROUND: Difference in pulse pressure (dPP) reliably predicts fluid responsiveness in patients. We have developed a respiratory variation (RV) monitoring device (RV monitor), which continuously records both airway pressure and arterial blood pressure (ABP). We compared the RV monitor measurements with manual dPP measurements. METHODS: ABP and airway pressure (PAW) from 24 patients were recorded. Data were fed to the RV monitor to calculate dPP and systolic pressure variation in two different ways: (a) considering both ABP and PAW (RV algorithm) and (b) ABP only (RV(slim) algorithm). Additionally, ABP and PAW were recorded intraoperatively in 10-min intervals for later calculation of dPP by manual assessment. Interobserver variability was determined. Manual dPP assessments were used for comparison with automated measurements. To estimate the importance of the PAW signal, RV(slim) measurements were compared with RV measurements. RESULTS: For the 24 patients, 174 measurements (6-10 per patient) were recorded. Six observers assessed dPP manually in the first 8 patients (10-min interval, 53 measurements); no interobserver variability occurred using a computer-assisted method. Bland-Altman analysis showed acceptable bias and limits of agreement of the 2 automated methods compared with the manual method (RV: -0.33% +/- 8.72% and RV(slim): -1.74% +/- 7.97%). The difference between RV measurements and RV(slim) measurements is small (bias -1.05%, limits of agreement 5.67%). CONCLUSIONS: Measurements of the automated device are comparable with measurements obtained by human observers, who use a computer-assisted method. The importance of the PAW signal is questionable.

A Food Recognition System for Diabetic Patients based on an Optimized Bag of Features Model

Computer vision-based food recognition could be used to estimate a meal's carbohydrate content for diabetic patients. This study proposes a methodology for automatic food recognition, based on the Bag of Features (BoF) model. An extensive technical investigation was conducted for the identification and optimization of the best performing components involved in the BoF architecture, as well as the estimation of the corresponding parameters. For the design and evaluation of the prototype system, a visual dataset with nearly 5,000 food images was created and organized into 11 classes. The optimized system computes dense local features, using the scale-invariant feature transform on the HSV color space, builds a visual dictionary of 10,000 visual words by using the hierarchical k-means clustering and finally classifies the food images with a linear support vector machine classifier. The system achieved classification accuracy of the order of 78%, thus proving the feasibility of the proposed approach in a very challenging image dataset.

Impacts of a word-picture training on literacy skills in elementary school children and youths with intellectual disabilities

Objective: There is convincing evidence that phonological, orthographic and semantic processes influence children’s ability to learn to read and spell words. So far only a few studies investigated the influence of implicit learning in literacy skills. Children are sensitive to the statistics of their learning environment. By frequent reading they acquire implicit knowledge about the frequency of letter patterns in written words, and they use this knowledge during reading and spelling. Additionally, semantic connections facilitate to storing of words in memory. Thus, the aim of the intervention study was to implement a word-picture training which is based on statistical and semantic learning. Furthermore, we aimed at examining the training effects in reading and spelling in comparison to an auditory-visual matching training and a working memory training program. Participants and Methods: One hundred and thirty-two children aged between 8 and 11 years participated in training in three weekly session of 12 minutes over 8 weeks, and completed other assessments of reading, spelling, working memory and intelligence before and after training. Results: Results revealed in general that the word-picture training and the auditory-visual matching training led to substantial gains in reading and spelling performance in comparison to the working-memory training. Although both children with and without learning difficulties profited in their reading and spelling after the word-picture training, the training program led to differential effects for the two groups. After the word-picture training on the one hand, children with learning difficulties profited more in spelling as children without learning difficulties, on the other hand, children without learning difficulties benefit more in word comprehension. Conclusions: These findings highlight the need for frequent reading trainings with semantic connections in order to support the acquisition of literacy skills.