Application of Imagery Theory to Sport Psychology: Some Preliminary Findings

Bioinformational theory has been proposed by Lang (1979a), who suggests that mental images can be understood as products of the brain's information processing capacity. Imagery involves activation of a network of propositionally coded information stored in long-term memory. Propositions concerning physiological and behavioral responses provide a prototype for overt behavior. Processing of response information is associated with somatovisceral arousal. The theory has implications for imagery rehearsal in sport psychology and can account for a variety of findings in the mental practice literature. Hypotheses drawn from bioinformational theory were tested. College athletes imagined four scenes during which their heart rates were recorded. Subjects tended to show increases in heart rate when imagining scenes with which they had personal experience and which would involve cardiovascular activation if experienced in real life. Nonsignificant heart rate changes were found when the scene involved activation but was one with which subjects did not have personal experience.

Should Psychotherapy Consider Reincarnation?

There is increasing recognition of the need to take into account the cultural environment and belief systems of psychotherapy patients because these values reflect basic assumptions about man's nature and the cognitive references used to cope with psychological difficulties. Currently accepted psychotherapeutic approaches take no account of the belief in life after death held by most of the world's population. The World Values Survey (http://www.worldvaluessurvey.org) showed that there are large numbers of reincarnationists around the world, and whatever the reasons for believing in reincarnation, psychotherapeutic approaches should not ignore this significant group of people. Respect for patient opinions and subjective realities is a therapeutic need and an ethical duty, even though therapists may not share the same beliefs. Guidelines are suggested for professionals to develop collaborative models that help patients mobilize their intrinsic intelligence to find solutions to their complaints.

Treatment modalities of female Operation Iraqi Freedom/Operation Enduring Freedom Veterans with posttraumatic stress disorder: A systematic review of the literature

Objective. To review professional literature regarding treatment modalities of post-traumatic stress disorder (PTSD) amongst female Operation Iraqi Freedom (OIF) and Operation Enduring Freedom (OEF) veterans, to assess the efficacy of these treatment options, and to summarize implications of the findings from this literature. Design. Systematic review of published literature. Data sources. Medline, Pubmed, Psycinfo. Review Methods. Articles selected for the literature review pertain to the treatment options of female OIF or OEF veterans who have a diagnosis of PTSD. In addition, other relevant articles, such as articles that discuss the prevalence of the problem, access to care, and similar treatment modalities for PTSD in other war settings, were selected for background information for the review. Results. The search strategy identified 1,305 potential journal articles, taken from thorough searches in Medline, Pubmed, and Psycinfo. These articles were then imported into Refworks. Following final screening, there were 18 articles included in the systematic review and 28 articles used as background information. The remaining articles were excluded following screening of abstract and/or full text of articles. Treatment modalities presented in these trials include: Exposure Therapy (average of 68% reduction in PTSD symptoms), Imagery Rehearsal Therapy (23% reduction), Body-Oriented Therapy (57% reduction), Electroconvulsive Therapy (35% reduction), Holographic Reprocessing (47% reduction), a self-defense training program (13% reduction), Cognitive Behavioral Therapy (65% reduction) and a variety of pharmacotherapies (antipsychotics at 81% reduction, sympatholytic drug at 100% reduction). Outcomes of the studies included in this systematic review were measured by using personal assessment of whether there was a reduction in symptoms of PTSD, based on the results in each study. Conclusion. Overall, all of the treatment modalities investigated in the systematic review proved to be somewhat effective in relieving the burden of symptoms of PTSD amongst female veterans of OIF/OEF. In addition to pharmacotherapy, which had the highest reduction in PTSD symptoms, both the Exposure Therapy and the Cognitive Behavioral Therapy techniques proved to have the most positive results. As all of the therapies had a positive effect on this population, to some degree, a study needs to be done in the future to compare and contrast the efficacy of each therapy intervention when applied to a standardized population.^

Automatic Detection of Marine Mammal from Aerial Imagery

The following technical report describes the approach and algorithm used to detect marine mammals from aerial imagery taken from manned/unmanned platform. The aim is to automate the process of counting the population of dugongs and other mammals. We have developed and algorithm that automatically presents to a user a number of possible candidates of these mammals. We tested the algorithm in two distinct datasets taken from different altitudes. Analysis and discussion is presented in regards with the complexity of the input datasets, the detection performance.

Imagery and strength of craving for eating, drinking and playing sport

The elaborated intrusion (EI) theory of desire (Kavanagh, Andrade, & May, 2005) attributes the motivational force of cravings to cognitive elaboration, including imagery, of apparently spontaneous thoughts that intrude into awareness. We report a questionnaire study in which respondents rated a craving for food or drink. Questionnaire items derived from EI theory formed a single factor alongside factors for anticipated reward/relief, resistance, and opportunity. In a multiple regression predicting strength of craving, the first three factors accounted for 36% of the variance. Opportunity did not enter the model. In a second study, the difference between individuals' strong and weak cravings to take part in a sporting activity was shown to be related to visual, auditory, and general imagery, and to anticipated reward or relief from engaging in the activity. Implications for treatment of craving-related disorders are discussed in the light of these results and of other research indicating that interference with imagery can reduce the strength of craving.

Eye-movements and visual imagery : a working memory approach to the treatment of post-traumatic stress disorder

It has been claimed that the symptoms of post-traumatic stress disorder (PTSD) can be ameliorated by eye-movement desensitization-reprocessing therapy (EMD-R), a procedure that involves the individual making saccadic eye-movements while imagining the traumatic event. We hypothesized that these eye-movements reduce the vividness of distressing images by disrupting the function of the visuospatial sketchpad (VSSP) of working memory, and that by doing so they reduce the intensity of the emotion associated with the image. This hypothesis was tested by asking non-PTSD participants to form images of neutral and negative pictures under dual task conditions. Their images were less vivid with concurrent eye-movements and with a concurrent spatial tapping task that did not involve eye-movements. In the first three experiments, these secondary tasks did not consistently affect participants' emotional responses to the images. However, Expt 4 used personal recollections as stimuli for the imagery task, and demonstrated a significant reduction in emotional response under the same dual task conditions. These results suggest that, if EMD-R works, it does so by reducing the vividness and emotiveness of traumatic images via the VSSP of working memory. Other visuospatial tasks may also be of therapeutic value.

Enhancing digital road map with lane details extracted from large-scale stereo aerial imagery using object-oriented image analysis

Precise, up-to-date and increasingly detailed road maps are crucial for various advanced road applications, such as lane-level vehicle navigation, and advanced driver assistant systems. With the very high resolution (VHR) imagery from digital airborne sources, it will greatly facilitate the data acquisition, data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lane information from aerial images with employment of the object-oriented image analysis method. Our proposed algorithm starts with constructing the DSM and true orthophotos from the stereo images. The road lane details are detected using an object-oriented rule based image classification approach. Due to the affection of other objects with similar spectral and geometrical attributes, the extracted road lanes are filtered with the road surface obtained by a progressive two-class decision classifier. The generated road network is evaluated using the datasets provided by Queensland department of Main Roads. The evaluation shows completeness values that range between 76% and 98% and correctness values that range between 82% and 97%.

Extraction of road lanes from high-resolution stereo aerial imagery based on maximum likelihood segmentation and texture enhancement

Accurate road lane information is crucial for advanced vehicle navigation and safety applications. With the increasing of very high resolution (VHR) imagery of astonishing quality provided by digital airborne sources, it will greatly facilitate the data acquisition and also significantly reduce the cost of data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lanes from aerial images with employment of the image analysis procedures. This algorithm starts with constructing the (Digital Surface Model) DSM and true orthophotos from the stereo images. Next, a maximum likelihood clustering algorithm is used to separate road from other ground objects. After the detection of road surface, the road traffic and lane lines are further detected using texture enhancement and morphological operations. Finally, the generated road network is evaluated to test the performance of the proposed approach, in which the datasets provided by Queensland department of Main Roads are used. The experiment result proves the effectiveness of our approach.

Incorporating uncertainty in environmental models informed by imagery

In this thesis, the issue of incorporating uncertainty for environmental modelling informed by imagery is explored by considering uncertainty in deterministic modelling, measurement uncertainty and uncertainty in image composition. Incorporating uncertainty in deterministic modelling is extended for use with imagery using the Bayesian melding approach. In the application presented, slope steepness is shown to be the main contributor to total uncertainty in the Revised Universal Soil Loss Equation. A spatial sampling procedure is also proposed to assist in implementing Bayesian melding given the increased data size with models informed by imagery. Measurement error models are another approach to incorporating uncertainty when data is informed by imagery. These models for measurement uncertainty, considered in a Bayesian conditional independence framework, are applied to ecological data generated from imagery. The models are shown to be appropriate and useful in certain situations. Measurement uncertainty is also considered in the context of change detection when two images are not co-registered. An approach for detecting change in two successive images is proposed that is not affected by registration. The procedure uses the Kolmogorov-Smirnov test on homogeneous segments of an image to detect change, with the homogeneous segments determined using a Bayesian mixture model of pixel values. Using the mixture model to segment an image also allows for uncertainty in the composition of an image. This thesis concludes by comparing several different Bayesian image segmentation approaches that allow for uncertainty regarding the allocation of pixels to different ground components. Each segmentation approach is applied to a data set of chlorophyll values and shown to have different benefits and drawbacks depending on the aims of the analysis.