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.^

Formal modeling and analysis techniques for high level Petri nets

Petri Nets are a formal, graphical and executable modeling technique for the specification and analysis of concurrent and distributed systems and have been widely applied in computer science and many other engineering disciplines. Low level Petri nets are simple and useful for modeling control flows but not powerful enough to define data and system functionality. High level Petri nets (HLPNs) have been developed to support data and functionality definitions, such as using complex structured data as tokens and algebraic expressions as transition formulas. Compared to low level Petri nets, HLPNs result in compact system models that are easier to be understood. Therefore, HLPNs are more useful in modeling complex systems. ^ There are two issues in using HLPNs—modeling and analysis. Modeling concerns the abstracting and representing the systems under consideration using HLPNs, and analysis deals with effective ways study the behaviors and properties of the resulting HLPN models. In this dissertation, several modeling and analysis techniques for HLPNs are studied, which are integrated into a framework that is supported by a tool. ^ For modeling, this framework integrates two formal languages: a type of HLPNs called Predicate Transition Net (PrT Net) is used to model a system's behavior and a first-order linear time temporal logic (FOLTL) to specify the system's properties. The main contribution of this dissertation with regard to modeling is to develop a software tool to support the formal modeling capabilities in this framework. ^ For analysis, this framework combines three complementary techniques, simulation, explicit state model checking and bounded model checking (BMC). Simulation is a straightforward and speedy method, but only covers some execution paths in a HLPN model. Explicit state model checking covers all the execution paths but suffers from the state explosion problem. BMC is a tradeoff as it provides a certain level of coverage while more efficient than explicit state model checking. The main contribution of this dissertation with regard to analysis is adapting BMC to analyze HLPN models and integrating the three complementary analysis techniques in a software tool to support the formal analysis capabilities in this framework. ^ The SAMTools developed for this framework in this dissertation integrates three tools: PIPE+ for HLPNs behavioral modeling and simulation, SAMAT for hierarchical structural modeling and property specification, and PIPE+Verifier for behavioral verification.^

Vowels in the 305: A First Pass at Miami Latino English

In this paper, I present preliminary findings of the first-large scale, systematic study of English Latino vowels in Miami. Sociolinguistic interviews were conducted with 25 Miami-born participants: 10 Anglo Whites and 15 Latinos with varying degrees of Spanish fluency. Here I focus on the vowel quality (/i, ɪ, ai, æ, ɔ, u /) in the speech of the 2nd and 3rd generations to examine the nature of influence of Spanish on English in Miami over the past 60 years. I conduct an in-depth analysis of the vowel productions of two female speakers, Maria & Blaze, to show the range of vowel productions in Miami Latino English. The vocalic analysis is comprised of a minimum of 15 non-repeating tokens of each vowel. These vowels were extracted from interview data and analyzed for F1, F2, and F3 values using PRAAT. Two allophones of /æ/ were considered: pre-nasal and pre-non-nasal, since Latinos in other regions have shown to resist pre-nasal /æ/ raising (Thomas 2001).

Formal Modeling and Analysis Techniques for High Level Petri Nets

Petri Nets are a formal, graphical and executable modeling technique for the specification and analysis of concurrent and distributed systems and have been widely applied in computer science and many other engineering disciplines. Low level Petri nets are simple and useful for modeling control flows but not powerful enough to define data and system functionality. High level Petri nets (HLPNs) have been developed to support data and functionality definitions, such as using complex structured data as tokens and algebraic expressions as transition formulas. Compared to low level Petri nets, HLPNs result in compact system models that are easier to be understood. Therefore, HLPNs are more useful in modeling complex systems. There are two issues in using HLPNs - modeling and analysis. Modeling concerns the abstracting and representing the systems under consideration using HLPNs, and analysis deals with effective ways study the behaviors and properties of the resulting HLPN models. In this dissertation, several modeling and analysis techniques for HLPNs are studied, which are integrated into a framework that is supported by a tool. For modeling, this framework integrates two formal languages: a type of HLPNs called Predicate Transition Net (PrT Net) is used to model a system's behavior and a first-order linear time temporal logic (FOLTL) to specify the system's properties. The main contribution of this dissertation with regard to modeling is to develop a software tool to support the formal modeling capabilities in this framework. For analysis, this framework combines three complementary techniques, simulation, explicit state model checking and bounded model checking (BMC). Simulation is a straightforward and speedy method, but only covers some execution paths in a HLPN model. Explicit state model checking covers all the execution paths but suffers from the state explosion problem. BMC is a tradeoff as it provides a certain level of coverage while more efficient than explicit state model checking. The main contribution of this dissertation with regard to analysis is adapting BMC to analyze HLPN models and integrating the three complementary analysis techniques in a software tool to support the formal analysis capabilities in this framework. The SAMTools developed for this framework in this dissertation integrates three tools: PIPE+ for HLPNs behavioral modeling and simulation, SAMAT for hierarchical structural modeling and property specification, and PIPE+Verifier for behavioral verification.

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.