左侧梭状回内文字的字形加工：中文正常阅读者，中文文盲、非中文母语被试的对比研究

Reading is an important human-specific skill obtained through extensive learning experience and is reliance on the ability to rapidly recognize single words. According to the behavioral studies, the most important stage of reading is the representation of “visual word form”, which is independent on surface visual features of the reading materials. The prelexical visual word form representation is characterized by the abstractive and highly effective and precise processing. Neuroimaging and neuropsychological studies have investigated the neural basis underlying the visual word form processing. On the basis of summary of the existing literature, the current thesis aimed to address three fundamental questions involving neural basis of word recognition. First, is there a dedicated neural network that is specialized for word recognition? Second, is the orthographic information represented in the putative word/character selective region (VWFA)? Third, what is the role of reading experience in the genesis of the VWFA, is experience a main driver to shape VWFA instead of evolutionary selectivity? Nineteen Chinese literate volunteers, 5 Chinese illiterates and 4 native English speakers participated in this study, and performed perceptual tasks during fMRI scanning. To address the first question, we compared the differential responses to three categories of visual objects, i.e., faces, line drawings of objects and Chinese characters, and defined the region of interesting (ROI) for the next experiment. To address the second question, Chinese character orthography was manipulated to reveal possible differential responses to real characters, false characters, radical combinations, and stroke combinations in the regions defined by the first experiment. To examine the role of reading experience in genesis of specialization for character, the responses for unfamiliar Chinese characters in Chinese illiterates and native English speakers were compared with that in the Chinese literates, and tracked the change in cortical activation after a short-term reading training in the illiterates. Data were analyzed in two dimensions. Both BOLD signal amplitude and spatial distribution pattern among multi-voxels were used to systematically investigate the responsiveness of the left fusiform gyrus to Chinese characters. Our results provide strong and clear evidence for the existence of functionally specialized regions in the human ventral occipital-temporal cortex. In the skilled readers a region specialized for written words could be consistently found in the lateral part of the left fusiform gyrus, line drawings in the median part and faces in the middle. Our results further show that spatial distribution analysis, a method that was not commonly used in neuroimaging of reading, appears to be a more effective measurement for category specialization for visual objects processing. Although we failed to provide evidence that VWFA processes orthographic information in terms of signal intensitiy, we do show that response pattern of real characters and radical collections in this area is different from that of false characters and random stroke combinations. Our last set of experiments suggests that the selective bias to reading material is clearly experience dependent. The response to unknown characters in both English speakers/readers and Chinese illiterates is fundamentally different from that of the skilled Chinese readers. The response pattern for unknown characters is more similar to that for line drawings rather as a weak version of character in skilled Chinese readers. Short-term training is not sufficient to produce VWFA bias even when tested with learned characters, rather the learned characters generated a overall upward shift of the activation of the left fusiform region. Formation of a dedicated region specialized for visual word/character might depend on long-term extensive reading experience, or there might be a critical period for reading acquisition.

Recognition by Linear Combinations of Models

Visual object recognition requires the matching of an image with a set of models stored in memory. In this paper we propose an approach to recognition in which a 3-D object is represented by the linear combination of 2-D images of the object. If M = {M1,...Mk} is the set of pictures representing a given object, and P is the 2-D image of an object to be recognized, then P is considered an instance of M if P = Eki=aiMi for some constants ai. We show that this approach handles correctly rigid 3-D transformations of objects with sharp as well as smooth boundaries, and can also handle non-rigid transformations. The paper is divided into two parts. In the first part we show that the variety of views depicting the same object under different transformations can often be expressed as the linear combinations of a small number of views. In the second part we suggest how this linear combinatino property may be used in the recognition process.

Localization and Positioning Using Combinations of Model Views

A method for localization and positioning in an indoor environment is presented. The method is based on representing the scene as a set of 2D views and predicting the appearances of novel views by linear combinations of the model views. The method is accurate under weak perspective projection. Analysis of this projection as well as experimental results demonstrate that in many cases it is sufficient to accurately describe the scene. When weak perspective approximation is invalid, an iterative solution to account for the perspective distortions can be employed. A simple algorithm for repositioning, the task of returning to a previously visited position defined by a single view, is derived from this method.

A Computational Model of Skill Acquisition

This thesis confronts the nature of the process of learning an intellectual skill, the ability to solve problems efficiently in a particular domain of discourse. The investigation is synthetic; a computational performance model, HACKER, is displayed. Hacker is a computer problem-solving system whose performance improves with practice. HACKER maintains performance knowledge as a library of procedures indexed by descriptions of the problem types for which the procedures are appropriate. When applied to a problem, HACKER tries to use a procedure from this "Answer Library". If no procedure is found to be applicable, HACKER writes one using more general knowledge of the problem domain and of programming techniques. This new program may be generalized and added to the Answer Library.

A cognitive approach to identifying measurable milestones for programming skill acquisition

Mead, J., Gray, S., Hamer, J., James, R., Sorva, J., Clair, C. S., and Thomas, L. 2006. A cognitive approach to identifying measurable milestones for programming skill acquisition. SIGCSE Bull. 38, 4 (Dec. 2006), 182-194.

Physically-Based Combinations of Views: Representing Rigid and Nonrigid Motion

Nonrigid motion can be described as morphing or blending between extremal shapes, e.g., heart motion can be described as transitioning between the systole and diastole states. Using physically-based modeling techniques, shape similarity can be measured in terms of forces and strain. This provides a physically-based coordinate system in which motion is characterized in terms of physical similarity to a set of extremal shapes. Having such a low-dimensional characterization of nonrigid motion allows for the recognition and the comparison of different types of nonrigid motion.

Combinations of Deformable Shape Prototypes

We propose to investigate a model-based technique for encoding non-rigid object classes in terms of object prototypes. Objects from the same class can be parameterized by identifying shape and appearance invariants of the class to devise low-level representations. The approach presented here creates a flexible model for an object class from a set of prototypes. This model is then used to estimate the parameters of low-level representation of novel objects as combinations of the prototype parameters. Variations in the object shape are modeled as non-rigid deformations. Appearance variations are modeled as intensity variations. In the training phase, the system is presented with several example prototype images. These prototype images are registered to a reference image by a finite element-based technique called Active Blobs. The deformations of the finite element model to register a prototype image with the reference image provide the shape description or shape vector for the prototype. The shape vector for each prototype, is then used to warp the prototype image onto the reference image and obtain the corresponding texture vector. The prototype texture vectors, being warped onto the same reference image have a pixel by pixel correspondence with each other and hence are "shape normalized". Given sufficient number of prototypes that exhibit appropriate in-class variations, the shape and the texture vectors define a linear prototype subspace that spans the object class. Each prototype is a vector in this subspace. The matching phase involves the estimation of a set of combination parameters for synthesis of the novel object by combining the prototype shape and texture vectors. The strengths of this technique lie in the combined estimation of both shape and appearance parameters. This is in contrast with the previous approaches where shape and appearance parameters were estimated separately.

THE EFFECT OF A PROGRAM OF PORTABLE ELECTRONIC PIANO KEYBOARD EXPERIENCE ON THE ACQUISITION OF SIGHT-SINGING SKILL IN THE NOVICE HIGH SCHOOL CHORUS

The problem was to determine whether a method of aural and visual vocal training that included a program of portable electronic piano keyboard experience would be more effective in teaching sight-singing skills to novice high school chorus students than a method that included only aural and visual vocal training. A sub-problem was to determine whether novice chorus students enjoyed playing electronic keyboards in chorus as a reinforcement experience in sight-singing training. Students were randomly assigned to two treatment groups, tested with the Musical Aptitude Profile, Tonal Imagery, part A, and then trained separately. The experimental group sang repetitions of melodic patterns and utilized techniques associated with the Kodály Method while simultaneously playing keyboard. The comparison group received a similar treatment without using keyboards. The students were pre- and post-tested in sight-singing using the Vocal Sight-Reading Inventory. Results of the Analysis of Covariance using MAP scores as the covariate revealed no significant difference (p<.05) between post-test scores of the two groups. Improvement was noted in 96% of students from pre-test to post-test regardless of grouping. The repeated measures ANOVA revealed a significant relationship (p<.006) between aptitude group and post-test score. High aptitude students in both groups were found to benefit more from the training than low aptitude students. High aptitude keyboard group students achieved an average gain score that was 8.67 points higher than the comparison group. Of the total experimental group, 92% enjoyed playing keyboards in chorus. It is recommended that future research be undertaken to study the use of keyboards with advanced high school choruses and with uncertain singers in the high school chorus. Research is also needed to develop graded, valid, and reliable sight-singing tests for use in high school chorus. Techniques of the Kodály Method should be further investigated for use in high school sight-singing training.

Contribution of the North Atlantic subtropical high to regional climate model (RCM) skill in simulating southeastern United States summer precipitation

© 2014, Springer-Verlag Berlin Heidelberg.This study assesses the skill of advanced regional climate models (RCMs) in simulating southeastern United States (SE US) summer precipitation and explores the physical mechanisms responsible for the simulation skill at a process level. Analysis of the RCM output for the North American Regional Climate Change Assessment Program indicates that the RCM simulations of summer precipitation show the largest biases and a remarkable spread over the SE US compared to other regions in the contiguous US. The causes of such a spread are investigated by performing simulations using the Weather Research and Forecasting (WRF) model, a next-generation RCM developed by the US National Center for Atmospheric Research. The results show that the simulated biases in SE US summer precipitation are due mainly to the misrepresentation of the modeled North Atlantic subtropical high (NASH) western ridge. In the WRF simulations, the NASH western ridge shifts 7° northwestward when compared to that in the reanalysis ensemble, leading to a dry bias in the simulated summer precipitation according to the relationship between the NASH western ridge and summer precipitation over the southeast. Experiments utilizing the four dimensional data assimilation technique further suggest that the improved representation of the circulation patterns (i.e., wind fields) associated with the NASH western ridge substantially reduces the bias in the simulated SE US summer precipitation. Our analysis of circulation dynamics indicates that the NASH western ridge in the WRF simulations is significantly influenced by the simulated planetary boundary layer (PBL) processes over the Gulf of Mexico. Specifically, a decrease (increase) in the simulated PBL height tends to stabilize (destabilize) the lower troposphere over the Gulf of Mexico, and thus inhibits (favors) the onset and/or development of convection. Such changes in tropical convection induce a tropical–extratropical teleconnection pattern, which modulates the circulation along the NASH western ridge in the WRF simulations and contributes to the modeled precipitation biases over the SE US. In conclusion, our study demonstrates that the NASH western ridge is an important factor responsible for the RCM skill in simulating SE US summer precipitation. Furthermore, the improvements in the PBL parameterizations for the Gulf of Mexico might help advance RCM skill in representing the NASH western ridge circulation and summer precipitation over the SE US.

A comparison between randomly alternating imaging, normal laparoscopic imaging, and virtual reality training in laparoscopic psychomotor skill acquisition

Objectives: To evaluate virtual reality as a laparoscopic training device in helping surgeons to automate to the “fulcrum effect” by comparing it to time-matched training programs using randomly alternating images (ie, y-axis inverted and normal laparoscopic) and normal laparoscopic viewing conditions.

Methods: Twenty-four participants (16 females and 8 males), were randomly assigned to minimally invasive surgery virtual reality (MIST VR), randomly alternating (between y-axis inverted and normal laparoscopic images), and normal laparoscopic imaging condition. Participants were requested to perform a 2-minute laparoscopic cutting task before and after training.

Results: In the test trial participants who trained on the MIST VR performed significantly better than those in the normal laparoscopic and randomly alternating imaging conditions.

Conclusion: The results show that virtual reality training may provide faster skill acquisition with particular reference to automation of the fulcrum effect. MIST VR provides a new way of training laparoscopic psychomotor surgical skills.