Operant and respondent procedures to establish social stimuli as reinforcers in children with autism

According to the DSM-IV- TR (American Psychiatric Association, 2000), one of the core deficits in autism is in the impairment of social interaction. Some have suggested that underlying these deficits is the reality that individuals with autism do not find social stimuli to be as reinforcing as other types of stimuli (Dawson, 2008). An interesting and growing body of literature supports the notion that symptoms in autism may be caused by a general reduction in social motivation (Chevallier et al., 2012). A review of the literature suggests that social orienting and social motivation are low in individuals with autism, and including social motivation as a target for therapeutic intervention should be pursued (Helt et al., 2008). Through our understanding of learning processes, researchers in behavior analysis and related fields have been able to use conditioning procedures to change the function of neutral or ineffective stimuli, including tokens (Ayllon & Azrin, 1968), facial expressions (Gewirtz & Pelaez-Nogueras, 1992) and praise (Dozier et al., 2012). The current study aimed to use operant and respondent procedures to condition social stimuli that were empirically shown to not be reinforcing prior to conditioning. Further, this study aimed to compare the two procedures in their effectiveness to condition social stimuli to function as reinforcers, and in their maintenance of effects over time. Using a multiple-baseline, multi-element design, one social stimulus was conditioned under each procedure to compare the different response rates following conditioning. Finally, the study sought to determine if conditioning social stimuli to function as reinforcers had any effect on the social functioning of young children with autism. Six children diagnosed with autism between the ages of 18 months and 3 years participated. Results show that the respondent procedure (pairing) resulted in more robust and enduring effects than the operant procedure (Sd procedure). Results of a social communication assessment (ESCS, Mundy et al., 2003) before and after conditioning demonstrate gains in all areas of social communication, particularly in the areas of initiating and responding to joint attention.^

Learning Data-Driven Models of Non-Verbal Behaviors for Building Rapport Using an Intelligent Virtual Agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness. Evidence-based patient-centered Brief Motivational Interviewing (BMI) interven- tions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary. Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems. To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].

Learning data-driven models of non-verbal behaviors for building rapport using an intelligent virtual agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness.^ Evidence-based patient-centered Brief Motivational Interviewing (BMI) interventions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary.^ Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems.^ To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].^

Operant and Respondent Procedures to Establish Social Stimuli as Reinforcers in Children with Autism

According to the DSM-IV- TR (American Psychiatric Association, 2000), one of the core deficits in autism is in the impairment of social interaction. Some have suggested that underlying these deficits is the reality that individuals with autism do not find social stimuli to be as reinforcing as other types of stimuli (Dawson, 2008). An interesting and growing body of literature supports the notion that symptoms in autism may be caused by a general reduction in social motivation (Chevallier et al., 2012). A review of the literature suggests that social orienting and social motivation are low in individuals with autism, and including social motivation as a target for therapeutic intervention should be pursued (Helt et al., 2008). Through our understanding of learning processes, researchers in behavior analysis and related fields have been able to use conditioning procedures to change the function of neutral or ineffective stimuli, including tokens (Ayllon & Azrin, 1968), facial expressions (Gewirtz & Pelaez-Nogueras, 1992) and praise (Dozier et al., 2012). The current study aimed to use operant and respondent procedures to condition social stimuli that were empirically shown to not be reinforcing prior to conditioning. Further, this study aimed to compare the two procedures in their effectiveness to condition social stimuli to function as reinforcers, and in their maintenance of effects over time. Using a multiple-baseline, multi-element design, one social stimulus was conditioned under each procedure to compare the different response rates following conditioning. Finally, the study sought to determine if conditioning social stimuli to function as reinforcers had any effect on the social functioning of young children with autism. Six children diagnosed with autism between the ages of 18 months and 3 years participated. Results show that the respondent procedure (pairing) resulted in more robust and enduring effects than the operant procedure (Sd procedure). Results of a social communication assessment (ESCS, Mundy et al., 2003) before and after conditioning demonstrate gains in all areas of social communication, particularly in the areas of initiating and responding to joint attention.

Theoretical and applied evaluations of facial composite systems

Police often use facial composites during their investigations, yet research suggests that facial composites are generally not effective. The present research included two experiments on facial composites. The first experiment was designed to test the usefulness of the encoding specificity principle for determining when facial composites will be effective. Instructions were used to encourage holistic or featural cues at encoding. The method used to construct facial composites was manipulated to encourage holistic or featural cues at retrieval. The encoding specificity principle suggests that an interaction effect should occur. If the same cues are used at encoding and retrieval, better composites should be constructed than when the cues are not the same. However, neither the expected interaction nor the main effects for encoding and retrieval were significant. The second study was conducted to assess the effectiveness of composites generated by two different facial composite construction systems, E-Fit and Mac-A-Mug Pro. These systems differ in that the E-Fit system uses more sophisticated methods of composite construction and may construct better quality facial composites. A comparison of E-Fit and Mac-A-Mug Pro composites demonstrated that E-Fit composites were of better quality than Mac-A-Mug Pro composites. However, neither E-Fit nor Mac-A-Mug Pro composites were useful for identifying the target person from a photograph lineup. Further, lineup performance was at floor level such that both E-Fit and Mac-A-Mug Pro composites were no more useful than a verbal description. Possible limitations of the studies are discussed, as well as suggestions for future research. ^

Thermal imaging as a biometrics approach to facial signature authentication

This dissertation develops an image processing framework with unique feature extraction and similarity measurements for human face recognition in the thermal mid-wave infrared portion of the electromagnetic spectrum. The goals of this research is to design specialized algorithms that would extract facial vasculature information, create a thermal facial signature and identify the individual. The objective is to use such findings in support of a biometrics system for human identification with a high degree of accuracy and a high degree of reliability. This last assertion is due to the minimal to no risk for potential alteration of the intrinsic physiological characteristics seen through thermal infrared imaging. The proposed thermal facial signature recognition is fully integrated and consolidates the main and critical steps of feature extraction, registration, matching through similarity measures, and validation through testing our algorithm on a database, referred to as C-X1, provided by the Computer Vision Research Laboratory at the University of Notre Dame. Feature extraction was accomplished by first registering the infrared images to a reference image using the functional MRI of the Brain’s (FMRIB’s) Linear Image Registration Tool (FLIRT) modified to suit thermal infrared images. This was followed by segmentation of the facial region using an advanced localized contouring algorithm applied on anisotropically diffused thermal images. Thermal feature extraction from facial images was attained by performing morphological operations such as opening and top-hat segmentation to yield thermal signatures for each subject. Four thermal images taken over a period of six months were used to generate thermal signatures and a thermal template for each subject, the thermal template contains only the most prevalent and consistent features. Finally a similarity measure technique was used to match signatures to templates and the Principal Component Analysis (PCA) was used to validate the results of the matching process. Thirteen subjects were used for testing the developed technique on an in-house thermal imaging system. The matching using an Euclidean-based similarity measure showed 88% accuracy in the case of skeletonized signatures and templates, we obtained 90% accuracy for anisotropically diffused signatures and templates. We also employed the Manhattan-based similarity measure and obtained an accuracy of 90.39% for skeletonized and diffused templates and signatures. It was found that an average 18.9% improvement in the similarity measure was obtained when using diffused templates. The Euclidean- and Manhattan-based similarity measure was also applied to skeletonized signatures and templates of 25 subjects in the C-X1 database. The highly accurate results obtained in the matching process along with the generalized design process clearly demonstrate the ability of the thermal infrared system to be used on other thermal imaging based systems and related databases. A novel user-initialization registration of thermal facial images has been successfully implemented. Furthermore, the novel approach at developing a thermal signature template using four images taken at various times ensured that unforeseen changes in the vasculature did not affect the biometric matching process as it relied on consistent thermal features.

The African Roots of Cuban Culture : Artistic and Religious Expressions, A Symposium

This flyer promotes the event "The African Roots of Cuban Culture: Artistic and Religious Expressions, A Symposium", cosponsored by the Frost Art Museum and the African & African Diaspora Studies Program at FlU.