<p> This study examined cultural differences in children's collaborative processes and explored the relationship between these collaborative processes and the children's collaboration in household work. 30 6- to 10-year-old sibling pairs from Mexican-heritage and middle-class European-heritage backgrounds participated in the study. Home visits were conducted using a planning task where dyads planned five grocery-shopping trips using a model store, first creating individual plans and then working together to create a combined plan. After participants completed their individual plans, the research assistant asked them to work together and help each other to make the shortest route to pick up all the items on their shopping list. Using 10-second segments, data were coded in four main categories; fluid ensemble, coming to agreement, one child leads activity, or dividing separate roles (which had several subcategories). Mexican Indigenous-heritage siblings collaborated as an ensemble in a higher proportion of segments than middle-class European-heritage siblings, who spent more segments dividing roles. Specifically, when European-heritage pairs were dividing roles they spent a higher proportion of segments being <i>bossy </i> to their sibling with the sibling <i>implementing</i> their plan, and ignoring their sibling while working on the plan. There was a positive relationship between siblings' collaboration at home and collaboration in the planning task. Siblings who were reported to collaborate with initiative in household work, based on mothers' reports, were more likely to collaborate as fluid ensemble with their sibling in the planning task. In contrast, children that were reported to do household work only when adults managed their chores were more likely to collaborate by being bossy to their sibling or by ignoring their sibling while working on the plan. Findings may help us better understand how cultural practices contribute to children's tendencies to collaborate with others in different contexts, including in the classroom setting where collaboration might be discouraged or managed by adults.</p>

<p>Emotions are pervasive in daily life, and a rich literature has documented how emotional stimuli and events disrupt ongoing processing and place heightened demands on control. Yet the executive control mechanisms that subsequently resolve that interference have not been well characterized. Although many failures of executive control have emotion at their core, numerous questions remain in the field regarding interactions between emotion and executive control. How do executive processes act on affective representations? Are emotional representations less amenable to control? Do distinct processes or neural networks govern their control? The present dissertation addresses these questions by investigating the neural systems and cognitive processes that support executive control in the face of interference from affective sources. Whereas previous research has emphasized the bottom-up impact of emotion on cognition, this dissertation will investigate how top-down executive control signals modulate affect's influence on cognition. Combining behavioral techniques with neuroimaging methodologies, this dissertation characterizes the interactive relationship between affective processes and top-down executive control and the ramifications of that interaction for promoting adaptive behavior.</p><p>Cognitive and behavioral phenomena related to affective interference resolution are explored in a series of research projects spanning attention and memory. Task-irrelevant affective representations may disrupt performance, but this interference appears to be dependent on top-down factors and can be resolved by executive mechanisms. Interference resolution mechanisms act on representations both of stimuli in the environment and information stored in memory. The findings reported here support emotion's capacity to disrupt executive processing but also highlight the role executive control plays in overcoming that interference in order to promote adaptive behavior.</p> / Dissertation

It has been assumed that the social deficits inherent in autism imply that individuals with the condition will be unable fully to appreciate the emotional content of music. My aim was to test this assumption, and to explore more widely the similarities and differences between the experience of music in the normal population and those with autism. My first study used musically-induced mood changes and a behavioural measure to show that music does indeed have a more than superficial effect on cognitive processes in a control group. The second study focused on high-functioning adults on the autism spectrum, using semi-structured interviews to investigate the part that music played in their everyday lives, concluding that autism is no bar to full appreciation of the emotional uses of music, though suggesting a degree of impoverishment in the language they used to describe the emotions. The final set of experiments compared control and autism group directly, using physiological (GSR) measures of arousal together with self-report of the emotions evoked by a set of musical items. Standardised questionnaires were used to measure alexithymia (difficulty in identifying and describing feelings) in individuals. Although the autism group experienced comparable levels of physiological arousal to music, they used fewer words than the control group to describe their emotional responses, a difference which correlated strongly with their level of alexithymia. My results are consistent with the hypothesis that in autism, the basic physiological and emotional component of their reactivity to music is functioning normally, but that their ability to translate these reactions into conventional emotional language is reduced, precisely in line with the extent of their alexithymia. These results suggest that the preserved ability of music to generate emotional arousal in autism may lead to clinical applications for the treatment of alexithymia in autism and other conditions.

Traumatic brain injury (TBI) is the leading cause of disability in young adults and a major public health problem. Persistent cognitive impairments are common, and constitute a significant source of long-term disability. The specific pathophysiological mechanisms underlying these impairments remain poorly understood. As it disconnects brain networks, white matter damage can be a key determinant of cognitive impairment after TBI. Neuroimaging and neuropsychological methods were employed to explore the relationships between indices of brain structure and cognitive function. The participants were 40 TBI patients and 40 healthy controls. First, relationships between focal lesions and cognitive performance were investigated using structural magnetic resonance imaging (MRI) and a battery of neuropsychological tests. The results demonstrated that lesion location and load are not good indices of the cognitive deficits - probably because diffuse axonal injury is poorly assessed by standard MRI. By contrast, diffusion tensor imaging (DTI) can be used to quantify the microstructure of white matter. A ‘whole-brain’ technique, tract-based spatial statistics (TBSS), was used to flexibly analyse the structure of white matter tracts. Despite only small amounts of focal damage observed using standard MRI, TBSS revealed widespread white matter abnormalities after TBI. White matter damage was found in patients with no evidence of focal damage, and in patients classified as ‘mild’ clinically. Relationships between white matter tract structure and specific cognitive functions were then explored. The structure of the fornix, an important white matter pathway of the hippocampus, correlated with verbal associative memory across the patient and control groups. By contrast, structure of frontal lobe connections showed distinct relationships with executive function in these two groups. The results emphasise the importance of white matter pathology after TBI and suggest that disruption to specific white matter tracts is associated with particular patterns of cognitive impairment, but also highlight the complexity of these relationships.

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Background: Cognitive remediation is a behavioural intervention that aims to improve cognitive functioning with the goal of durability and generalisation. Although evidence suggests that computer-assisted cognitive remediation (CACR) improves cognitive functioning in individuals with schizophrenia, it remains unclear whether these effects generalise and lead to improvements in clinical symptoms and psychosocial functioning. The current study aimed to investigate the effects of CACR on clinical symptoms, cognitive functioning and psychosocial functioning in individuals with schizophrenia or schizoaffective disorder. Method: A systematic review was performed using the quality assessment criteria defined by Scottish Intercollegiate Guidelines Network (SIGN 50) to investigate the effects of CACR on clinical symptoms in individuals with a diagnosis of schizophrenia or schizoaffective disorder. Additionally, a within subjects repeated measures design was used to investigate the effects of CACR on cognitive functioning, functional capacity and everyday social functioning. Results: There was some evidence to suggest that CACR improves clinical symptoms, but the majority of studies reviewed did not report a significant effect, and a number of methodological weaknesses were identified in the literature. Results of the experimental study revealed improvements in speed of processing, reasoning and problem solving and the overall composite score for cognition, but these improvements could not be attributed solely to the CACR intervention. No improvements in functional capacity or everyday social functioning were observed. Conclusions: Further, more rigorous research is required to develop a clearer understanding of the effects of CACR on clinical symptoms. The results of the experimental study support previous literature which has identified that a pure CACR intervention does not improve psychosocial functioning. The results are discussed in relation to the relevant literature.

The organization of taking turns at talk is an important part of any verbal interaction such as conversation, particularly in groups. Sociologists and psycholinguists have been studying turn-taking in conversation through empirical and statistical analysis, and identified some systematics in it. But to my knowledge no detailed computational modelling of verbal turn-taking has yet been attempted. This thesis describes one such attempt, for a simulation of small group discussion— that is, engaged conversation in groups of up to seven participants, which researchers have found to be much like two-person dialogues with overhearers. The group discussion is simulated by a simple multi-agent framework with a blackboard architecture, where each agent represents a participant in the discussion and the blackboard is their channel of communication, or ‘environment’ of the discussion. Agents are modelled with just a set of probabilistic parameters that give their likelihood of doing the various turn-taking decisions in the simulation: when to talk, when to continue talking, when to interrupt, when to give feedback (“uh huh”), and so on. The simulation, therefore, consists of coordinating a one-at-a-time talk (symbolic talk) with speaker transitions, hesitation, yielding or keeping the floor, and managing simultaneous talk which occurs mostly around speaker transitions. The turn-taking modelling considers whether participants are talking or not, and when they reach points of possible completion in their utterances that correspond to the places of transition-relevance, TRPs, where others could start to speak in attempts to take a new turn of talk. The agent behaviours (acts), their internal states and procedures are then described. The model is expanded with elaborate procedures for the resolution of simultaneous talk, for speaking hesitations and their potential interruption, and for the constraints of the different ‘sorts’ of utterance with respect to turn-taking: whether the TRP is free, or the speaker has selected someone to speak next, has encouraged anyone to speak, or has indicated the course of an extended multi-utterance turn at talk as in sentence beginnings like “first of all,” or “let me tell you something:. . . ”. The model and extensions are then comprehensively analysed through a series of large quantitative evaluations computing various aggregate statistics such as: the total times of single talk, multiple talk and silences; total occurrences of utterances, silences, simultaneous talk, multiple starts, middle-of-utterance attempts at talking, false-starts, abandoned utterances (interrupted by others), and more.