Aversive Stimuli and Functional Networks of Fear Learning in PTSD : 734

Background: One characteristic of post traumatic stress disorder is an inability to adapt to a safe environment i.e. to change behavior when predictions of adverse outcomes are not met. Recent studies have also indicated that PTSD patients have altered pain processing, with hyperactivation of the putamen and insula to aversive stimuli (Geuze et al, 2007). The present study examined neuronal responses to aversive and predicted aversive events. Methods: Twenty-four trauma exposed non-PTSD controls and nineteen subjects with PTSD underwent fMRI imaging during a partial reinforcement fear conditioning paradigm, with a mild electric shock as the unconditioned stimuli (UCS). Three conditions were analyzed: actual presentations of the UCS, events when a UCS was expected, but omitted (CS+), and events when the UCS was neither expected nor delivered (CS-). Results: The UCS evoked significant alterations in the pain matrix consisting of the brainstem, the midbrain, the thalamus, the insula, the anterior and middle cingulate and the contralateral somatosensory cortex. PTSD subjects displayed bilaterally elevated putamen activity to the electric shock, as compared to controls. In trials when USC was expected, but omitted, significant activations were observed in the brainstem, the midbrain, the anterior insula and the anterior cingulate. PTSD subjects displayed similar activations, but also elevated activations in the amygdala and the posterior insula. Conclusions: These results indicate altered fear and safety learning in PTSD, and neuronal activations are further explored in terms of functional connectivity using psychophysiological interaction analyses.

Deficits in executive and memory processes in delusional disorder: a case-control study

OBJECTIVE Delusional disorder has been traditionally considered a psychotic syndrome that does not evolve to cognitive deterioration. However, to date, very little empirical research has been done to explore cognitive executive components and memory processes in Delusional Disorder patients. This study will investigate whether patients with delusional disorder are intact in both executive function components (such as flexibility, impulsivity and updating components) and memory processes (such as immediate, short term and long term recall, learning and recognition). METHODS A large sample of patients with delusional disorder (n = 86) and a group of healthy controls (n = 343) were compared with regard to their performance in a broad battery of neuropsychological tests including Trail Making Test, Wisconsin Card Sorting Test, Colour-Word Stroop Test, and Complutense Verbal Learning Test (TAVEC). RESULTS When compared to controls, cases of delusional disorder showed a significantly poorer performance in most cognitive tests. Thus, we demonstrate deficits in flexibility, impulsivity and updating components of executive functions as well as in memory processes. These findings held significant after taking into account sex, age, educational level and premorbid IQ. CONCLUSIONS Our results do not support the traditional notion of patients with delusional disorder being cognitively intact.

Nondeclarative learning in children with Specific Language Impairment: Predicting regularities in the visuomotor, phonological, and cognitive domains.

Ullman (2004) suggested that Specific Language Impairment (SLI) results from a general procedural learning deficit. In order to test this hypothesis, we investigated children with SLI via procedural learning tasks exploring the verbal, motor, and cognitive domains. Results showed that compared with a Control Group, the children with SLI (a) were unable to learn a phonotactic learning task, (b) were able but less efficiently to learn a motor learning task and (c) succeeded in a cognitive learning task. Regarding the motor learning task (Serial Reaction Time Task), reaction times were longer and learning slower than in controls. The learning effect was not significant in children with an associated Developmental Coordination Disorder (DCD), and future studies should consider comorbid motor impairment in order to clarify whether impairments are related to the motor rather than the language disorder. Our results indicate that a phonotactic learning but not a cognitive procedural deficit underlies SLI, thus challenging Ullmans' general procedural deficit hypothesis, like a few other recent studies.

Effectiveness of instructional strategies based on schema theory on attention deficit disorder children

A review of the literature reveals that there are a number of children in the educational system who are characterized by Attention Deficit Disorder. Further review of the literature reveals that there are information processing programs which have had some success in increasing the learning of these children. Currently, an information processing program which is based on schema theory is being implemented in Lincoln County. Since schema theory based programs build structural, conditional, factual, and procedural schemata which assist the learner in attending to salient factors, learning should be increased. Thirty-four children were selected from a random sampling of Grade Seven classes in Lincoln County. Seventeen of these children were identified by the researcher and classroom teacher as being characterized by Attention Deficit Disorder. From the remaining population, 17 children who were not characterized by Attention Deficit Disorder were randomly selected. The data collected were compared using independent t-tests, paired t-tests, and correlation analysis. Significant differences were found in all cases. The Non-Attention Deficit Disorder children scored significantly higher on all the tests but the Attention Defici t Disorder children had a significantly higher ratio of gain between the pretests and posttests.

Exploring an emotion intervention for preschoolers with autism spectrum disorder /

The purpose of this multiple case study was 1) to explore the effectiveness of an emotions recognition program for preschoolers with Autism Spectrum Disorders (ASD), and 2) to investigate one parent's perception of the emotions program. To address these objectives, the emotion unit scores of 7 preschoolers with ASD aged 3 to 5 years old (1 female, 6 males) were graphed and analyzed using visual inspection. In addition, the mother of 1 participant was interviewed to explore her perceptions of the emotions program and emotional learning. Overall, results revealed that participants' emotion recognition scores increased over the course of the emotions unit. The parent reported improvements in her son's expression and understanding of emotion, but noted that he continued to have difficulty with regulation of emotion. Implications for theory, education, and future research are discussed.

Perspectives of Parents of Children with Autism Spectrum Disorder on a Community-Based Parent Education Program

In 2012 a community-based agency that oversees Intensive Behaviour Intervention services for young children diagnosed with Autism Spectrum Disorder (ASD) began delivering newly developed curricula to parents of eligible children. The curricula’s intent was to inform parents about ASD and Applied Behaviour Analysis, to increase their awareness of available community resources, and assist them to be active and engaged in their child’s learning. This mixed-method study used a program-specific survey and focus groups to explore the perspectives parents had on their involvement in these education sessions. Through constant comparison analysis 4 major and 3 minor themes emerged. In general, parents acknowledged that this parent education program included relevant content and a favourable delivery format. The study summarized a number of well-articulated, practical suggestions parents provided. Implications for practice would be applicable to educators interested in providing quality group-based education to parents of young children with ASD.

Statistical Machine Learning Techniques for the Prediction of Learning Disabilities in School-Age Children

Learning Disability (LD) is a general term that describes specific kinds of learning problems. It is a neurological condition that affects a child's brain and impairs his ability to carry out one or many specific tasks. The learning disabled children are neither slow nor mentally retarded. This disorder can make it problematic for a child to learn as quickly or in the same way as some child who isn't affected by a learning disability. An affected child can have normal or above average intelligence. They may have difficulty paying attention, with reading or letter recognition, or with mathematics. It does not mean that children who have learning disabilities are less intelligent. In fact, many children who have learning disabilities are more intelligent than an average child. Learning disabilities vary from child to child. One child with LD may not have the same kind of learning problems as another child with LD. There is no cure for learning disabilities and they are life-long. However, children with LD can be high achievers and can be taught ways to get around the learning disability. In this research work, data mining using machine learning techniques are used to analyze the symptoms of LD, establish interrelationships between them and evaluate the relative importance of these symptoms. To increase the diagnostic accuracy of learning disability prediction, a knowledge based tool based on statistical machine learning or data mining techniques, with high accuracy,according to the knowledge obtained from the clinical information, is proposed. The basic idea of the developed knowledge based tool is to increase the accuracy of the learning disability assessment and reduce the time used for the same. Different statistical machine learning techniques in data mining are used in the study. Identifying the important parameters of LD prediction using the data mining techniques, identifying the hidden relationship between the symptoms of LD and estimating the relative significance of each symptoms of LD are also the parts of the objectives of this research work. The developed tool has many advantages compared to the traditional methods of using check lists in determination of learning disabilities. For improving the performance of various classifiers, we developed some preprocessing methods for the LD prediction system. A new system based on fuzzy and rough set models are also developed for LD prediction. Here also the importance of pre-processing is studied. A Graphical User Interface (GUI) is designed for developing an integrated knowledge based tool for prediction of LD as well as its degree. The designed tool stores the details of the children in the student database and retrieves their LD report as and when required. The present study undoubtedly proves the effectiveness of the tool developed based on various machine learning techniques. It also identifies the important parameters of LD and accurately predicts the learning disability in school age children. This thesis makes several major contributions in technical, general and social areas. The results are found very beneficial to the parents, teachers and the institutions. They are able to diagnose the child’s problem at an early stage and can go for the proper treatments/counseling at the correct time so as to avoid the academic and social losses.

Unsupervised learning to cluster the disease stages in parkinson's disease

Parkinson's disease (PD) is the second most common neurodegenerative disorder (after Alzheimer's disease) and directly affects upto 5 million people worldwide. The stages (Hoehn and Yaar) of disease has been predicted by many methods which will be helpful for the doctors to give the dosage according to it. So these methods were brought up based on the data set which includes about seventy patients at nine clinics in Sweden. The purpose of the work is to analyze unsupervised technique with supervised neural network techniques in order to make sure the collected data sets are reliable to make decisions. The data which is available was preprocessed before calculating the features of it. One of the complex and efficient feature called wavelets has been calculated to present the data set to the network. The dimension of the final feature set has been reduced using principle component analysis. For unsupervised learning k-means gives the closer result around 76% while comparing with supervised techniques. Back propagation and J4 has been used as supervised model to classify the stages of Parkinson's disease where back propagation gives the variance percentage of 76-82%. The results of both these models have been analyzed. This proves that the data which are collected are reliable to predict the disease stages in Parkinson's disease.

ICT as a tool in English teaching : A literature review on the use of ICT for Swedish students with learning difficulties and their literacy learning in grades 7-9

Information and communication technology (ICT) is a subject that is being discussed as a tool that is used within education around the world. Furthermore it can be seen as a tool for teachers to individualize students´ education. Students with literacy difficulties, such as dyslexia, are in constant need of new ways to learn, and new ways to be motivated to learn. The aim of this study is to see what research says in regard to how ICT can be used as a tool to help students with literacy difficulties. Literacy difficulties can be due to a number of things, such as the student has not been taught how to read, trouble within the family which can cause distress, or a neurological disorder such as dyslexia. Furthermore, the main research questions will focus on how ICT can be compared to traditional education forms, such as books and a more teacher centered education within the classroom, and whether ICT can be preferred. The results of this literature review indicates that ICT can be seen as a way for teachers to help students with literacy difficulties gain more self-esteem – something the literature tells us students with learning difficulties lack. The results also show how ICT can lead to a more individualized education. This is due to tools that increase reading comprehension and tools that give direct response when working with ICT, which helps students work more independently.

Aquatic weed automatic classification using machine learning techniques

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A newly recognized syndrome of marfanoid habitus; Long face; Hypotelorism; Long, thin nose; Long, thin hands and feet; and a specific pattern of language and learning disabilities

Here, we report on a newly recognized syndrome in a Brazilian family with three affected women, who had a Marfanoid habitus; long face; hypotelorism; long, thin nose; long, thin hands and feet; and language and learning disabilities. The disorder is compatible with autosomal dominant inheritance. (C) 2007 Wiley-Liss, Inc.

The Dorsolateral Periaqueductal Gray and Its Role in Mediating Fear Learning to Life Threatening Events

The dorsolateral column of the periaqueductal gray (dlPAG) integrates aversive emotional experiences and represents an important site responding to life threatening situations, such as hypoxia, cardiac pain and predator threats. Previous studies have shown that the dorsal PAG also supports fear learning; and we have currently explored how the dlPAG influences associative learning. We have first shown that N-methyl-D-aspartate (NMDA) 100 pmol injection in the dlPAG works as a valuable unconditioned stimulus (US) for the acquisition of olfactory fear conditioning (OFC) using amyl acetate odor as conditioned stimulus (CS). Next, we revisited the ascending projections of the dlPAG to the thalamus and hypothalamus to reveal potential paths that could mediate associative learning during OFC. Accordingly, the most important ascending target of the dlPAG is the hypothalamic defensive circuit, and we were able to show that pharmacological inactivation using beta-adrenoceptor blockade of the dorsal premammillary nucleus, the main exit way for the hypothalamic defensive circuit to thalamo-cortical circuits involved in fear learning, impaired the acquisition of the OFC promoted by NMDA stimulation of the dlPAG. Moreover, our tracing study revealed multiple parallel paths from the dlPAG to several thalamic targets linked to cortical-hippocampal-amygdalar circuits involved in fear learning. Overall, the results point to a major role of the dlPAG in the mediation of aversive associative learning via ascending projections to the medial hypothalamic defensive circuit, and perhaps, to other thalamic targets, as well. These results provide interesting perspectives to understand how life threatening events impact on fear learning, and should be useful to understand pathological fear memory encoding in anxiety disorders.

Investigation of auditory processing disorder and language impairment using the speech-evoked auditory brainstem response

This study investigated whether there are differences in the Speech-Evoked Auditory Brainstem Response among children with Typical Development (TD), (Central) Auditory Processing Disorder (C) APD, and Language Impairment (LI). The speech-evoked Auditory Brainstem Response was tested in 57 children (ages 6-12). The children were placed into three groups: TD (n = 18), (C)APD (n = 18) and LI (n = 21). Speech-evoked ABR were elicited using the five-formant syllable/da/. Three dimensions were defined for analysis, including timing, harmonics, and pitch. A comparative analysis of the responses between the typical development children and children with (C)APD and LI revealed abnormal encoding of the speech acoustic features that are characteristics of speech perception in children with (C)APD and LI, although the two groups differed in their abnormalities. While the children with (C)APD might had a greater difficulty distinguishing stimuli based on timing cues, the children with LI had the additional difficulty of distinguishing speech harmonics, which are important to the identification of speech sounds. These data suggested that an inefficient representation of crucial components of speech sounds may contribute to the difficulties with language processing found in children with LI. Furthermore, these findings may indicate that the neural processes mediated by the auditory brainstem differ among children with auditory processing and speech-language disorders. (C) 2012 Elsevier B.V. All rights reserved.

Neuropsychological predictors of response to randomized treatment in obsessive-compulsive disorder

Objective: To identify neuropsychological predictors of treatment response to cognitive-behavioral therapy (CBT) and fluoxetine in treatment-naive adults with obsessive-compulsive disorder (OCD). Method: Thirty-eight adult outpatients with OCD underwent neuropsychological assessment, including tasks of intellectual function, executive functioning and visual and verbal memory, before randomization to a 12-week clinical trial of either CBT or fluoxetine. Neuropsychological measures were used to identify predictors of treatment response in OCD. Results: Neuropsychological measures that predicted a better treatment response to either CBT or fluoxetine were higher verbal IQ (Wechsler Abbreviated Scale of Intelligence) (p = 0.008); higher verbal memory on the California Verbal Learning Test (p = 0.710); shorter time to complete part D (Dots) (p<0.001), longer time to complete part W (Words) (p = 0.025) and less errors on part C (Colors) (p<0.001) in the Victoria Stroop Test (VST). Fewer perseverations on the California Verbal Learning Test, a measure of mental flexibility, predicted better response to CBT, but worse response to fluoxetine (p = 0.002). Conclusion: In general, OCD patients with better cognitive and executive abilities at baseline were more prone to respond to either CBT or fluoxetine. Our finding that neuropsychological measures of mental flexibility predicted response to treatment in opposite directions for CBT and fluoxetine suggests that OCD patients with different neuropsychological profiles may respond preferentially to one type of treatment versus the other. Further studies with larger samples of OCD patients are necessary to investigate the heuristic value of such findings in a clinical context. (C) 2012 Elsevier Inc. All rights reserved.