On Being Responsible

Joint responsibility is a mental and behavioural state which captures and formalizes many of the intuitive underpinnings of collaborative problem solving. It defines the pre-conditions which must hold before such activity can commence, how individuals should behave (in their own problem solving and towards others) once such problem solving has begun and minimum conditions which group participants must satisfy

BEHAVIOURAL STATE CYCLING AND RELATED CHANGES IN THE CEREBRAL BLOOD FLOW IN THE OVINE FETUS NEAR TERM

The low voltage (LV)/rapid eye movement (REM) behavioural state the high voltage(HV)/non-rapid eye movement (NREM) behavioural state are each suggested to have a unique functional role in fetal neurodevelopment, therefore requiring the existence of both behavioural states in appropriate proportions for optimal maturation. The present study examined the behavioural state cycling pattern in the ovine fetus near term and characterized the related changes in cerebral blood flow velocity (CBFV), utilizing a 20-MHz piezoelectric Doppler crystal transducer. Our results demonstrated the HV/NREM epoch duration to be positively correlated with that of the prior LV/REM epoch, as well as with that of the subsequent LV/REM epoch, suggesting a possible homeostatic behavioural state control mechanism in the fetus. Changes in CBFV were consistent with those previously demonstrated, suggesting the piezoelectric Doppler crystal transducer may be used to continuously measure CBFV under resting conditions and provide a relative measure of cerebral blood flow changes

Doppler colour flow imaging of fetal intracerebral arteries relative to fetal behavioural states in normal pregnancy

In 14 normally developing term fetuses, the relationship between the blood flow velocity waveforms at cerebral arterial level (internal carotid artery, anterior, middle and posterior cerebral artery) and fetal behavioural states was studied using Doppler colour flow imaging. Behavioural state dependent changes in absolute flow velocities occurred in all vessels, except for the middle cerebral artery. These changes suggest preferential blood flow to the left heart resulting in increased flow to the cerebrum during fetal behavioural state 2F (active sleep) when compared with fetal behavioural state 1F (quiet sleep). The middle cerebral artery supplies the neocerebrum. This developing part of the cerebrum does not seem to take part in the regulation of fetal behaviour. In the internal carotid artery, an inverse relationship between peak systolic velocity and fetal heart rate could be established, which can be explained by a shorter rapid filling phase at raised fetal heart rate according to the Frank-Starling Law

The development of a rich multimedia training environment for crisis management: using emotional affect to enhance learning

PANDORA is an EU FP7-funded project developing a novel training and learning environment for Gold Commanders, individuals who carry executive responsibility for the services and facilities identified as strategically critical e.g. Police, Fire, in crisis management strategic planning situations. A key part of the work for this project is considering the emotional and behavioural state of the trainees, and the creation of more realistic, and thereby stressful, representations of multimedia information to impact on the decision-making of those trainees. Existing training models are predominantly paper-based, table-top exercises, which require an exercise of imagination on the part of the trainees to consider not only the various aspects of a crisis situation but also the impacts of interventions, and remediating actions in the event of the failure of an intervention. However, existing computing models and tools are focused on supporting tactical and operational activities in crisis management, not strategic. Therefore, the PANDORA system will provide a rich multimedia information environment, to provide trainees with the detailed information they require to develop strategic plans to deal with a crisis scenario, and will then provide information on the impacts of the implementation of those plans and provide the opportunity for the trainees to revise and remediate those plans. Since this activity is invariably multi-agency, the training environment must support group-based strategic planning activities and trainees will occupy specific roles within the crisis scenario. The system will also provide a range of non-playing characters (NPC) representing domain experts, high-level controllers (e.g. politicians, ministers), low-level controllers (tactical and operational commanders), and missing trainee roles, to ensure a fully populated scenario can be realised in each instantiation. Within the environment, the emotional and behavioural state of the trainees will be monitored, and interventions, in the form of environmental information controls and mechanisms impacting on the stress levels and decisionmaking capabilities of the trainees, will be used to personalise the training environment. This approach enables a richer and more realistic representation of the crisis scenario to be enacted, leading to better strategic plans and providing trainees with structured feedback on their performance under stress

Adaptive probability scheme for behaviour monitoring of the elderly using a specialised ambient device

A Hidden Markov Model (HMM) modified to work in combination with a Fuzzy System is utilised to determine the current behavioural state of the user from information obtained with specialised hardware. Due to the high dimensionality and not-linearly-separable nature of the Fuzzy System and the sensor data obtained with the hardware which informs the state decision, a new method is devised to update the HMM and replace the initial Fuzzy System such that subsequent state decisions are based on the most recent information. The resultant system first reduces the dimensionality of the original information by using a manifold representation in the high dimension which is unfolded in the lower dimension. The data is then linearly separable in the lower dimension where a simple linear classifier, such as the perceptron used here, is applied to determine the probability of the observations belonging to a state. Experiments using the new system verify its applicability in a real scenario

Behavioural State Neuromodulation of Early Visual Processing in the Dragonfly Brain

This item is only available electronically.Thesis (BHlthMSc(Hons)) -- University of Adelaide, Adelaide Medical School, YEA

Lessons from integrating behaviour and resource selection: activity-specific responses of African wild dogs to roads

Understanding how anthropogenic features affect species' abilities to move within landscapes is essential to conservation planning and requires accurate assessment of resource selection for movement by focal species. Yet, the extent to which an individual's behavioural state (e.g. foraging, resting, commuting) influences resource selection has largely been ignored. Recent advances in Global Positioning System (GPS) tracking technology can fill this gap by associating distinct behavioural states with location data. We investigated the role of behaviour in determining the responses of an endangered species of carnivore, the African wild dog Lycaon pictus, to one of the most widespread forms of landscape alteration globally: road systems. We collected high‐resolution GPS and activity data from 13 wild dogs in northern Botswana over a 2‐year period. We employed a step selection framework to measure resource selection across three behavioural states identified from activity data (high‐speed running, resting and travelling) and across a gradient of habitats and seasons, and compared these outputs to a full model that did not parse for behaviour. The response of wild dogs to roads varied markedly with both the behavioural and the landscape contexts in which roads were encountered. Specifically, wild dogs selected roads when travelling, ignored roads when high‐speed running and avoided roads when resting. This distinction was not evident when all movement data were considered together in the full model. When travelling, selection for roads increased in denser vegetative environments, suggesting that roads may enhance movement for this species. Our findings indicate that including behavioural information in resource selection models is critical to understanding wildlife responses to landscape features and suggest that successful application of resource selection analyses to conservation planning requires explicit examination of the behavioural contexts in which movement occurs. Thus, behaviour‐specific step selection functions offer a powerful tool for identifying resource selection patterns for animal behaviours of conservation significance