Challenges for Children and Adolescents with Autism and Their Families during the Covid-19 Pandemic

The restrictions and lockdown measures implemented in response to the Covid-19 pandemic have posed a pronounced risk to the mental health of people with autism and their families. We discuss specific difficulties affecting children and adolescents with autism and their families during the pandemic, drawing on a broad range of recently published research in many countries and regions. A global perspective is adopted to provide an overview of the state of affairs and identify good practices. We consider challenges in four areas: research and practice related to autism, challenges facing children and adolescents with autism, specific difficulties in their education and care, and challenges facing their parents and families. Based on the reviewed work and our experience in group support sessions with parents of children with autism, we conclude that supporting families affected by autism should emphasize promoting the parents\u27 well-being and coping potential to improve their resilience

Why do cats bring you rodents, and what does this have to do with party games and well-being?

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BCI Control of Heuristic Search Algorithms

The ability to develop Brain-Computer Interfaces (BCI) to Intelligent Systems would offer new perspectives in terms of human supervision of complex Artificial Intelligence (AI) systems, as well as supporting new types of applications. In this article, we introduce a basic mechanism for the control of heuristic search through fNIRS-based BCI. The rationale is that heuristic search is not only a basic AI mechanism but also one still at the heart of many different AI systems. We investigate how users’ mental disposition can be harnessed to influence the performance of heuristic search algorithm through a mechanism of precision-complexity exchange. From a system perspective, we use weighted variants of the A? algorithm which have an ability to provide faster, albeit suboptimal solutions. We use recent results in affective BCI to capture a BCI signal, which is indicative of a compatible mental disposition in the user. It has been established that Prefrontal Cortex (PFC) asymmetry is strongly correlated to motivational dispositions and results anticipation, such as approach or even risk-taking, and that this asymmetry is amenable to Neurofeedback (NF) control. Since PFC asymmetry is accessible through fNIRS, we designed a BCI paradigm in which users vary their PFC asymmetry through NF during heuristic search tasks, resulting in faster solutions. This is achieved through mapping the PFC asymmetry value onto the dynamic weighting parameter of the weighted A* (WA*) algorithm. We illustrate this approach through two different experiments, one based on solving 8-puzzle configurations, and the other on path planning. In both experiments, subjects were able to speed up the computation of a solution through a reduction of search space in WA?. Our results establish the ability of subjects to intervene in heuristic search progression, with effects which are commensurate to their control of PFC asymmetry: this opens the way to new mechanisms for the implementation of hybrid cognitive systems

A Mechanism Design Approach to Measure Awareness

In this paper, we study protocols that allow to discern conscious and unconscious decisions of human beings; i.e., protocols that measure awareness. Consciousness is a central research theme in Neuroscience and AI, which remains, to date, an obscure phenomenon of human brains. Our starting point is a recent experiment, called Post Decision Wagering (PDW) (Persaud, McLeod, and Cowey 2007), that attempts to align experimenters' and subjects' objectives by leveraging financial incentives. We note a similarity with mechanism design, a research area which aims at the design of protocols that reconcile often divergent objectives through incentive-compatibility. We look at the issue of measuring awareness from this perspective. We abstract the setting underlying the PDW experiment and identify three factors that could make it ineffective: rationality, risk attitude and bias of subjects. Using mechanism design tools, we study the barrier between possibility and impossibility of incentive compatibility with respect to the aforementioned characteristics of subjects. We complete this study by showing how to use our mechanisms to potentially get a better understanding of consciousness

Anger-based BCI Using fNIRS Neurofeedback

Functional near-infrared spectroscopy (fNIRS) holds increasing potential for Brain-Computer Interfaces (BCI) due to its portability, ease of application, robustness to movement artifacts, and relatively low cost. The use of fNIRS to support the development of affective BCI has received comparatively less attention, despite the role played by the prefrontal cortex in affective control, and the appropriateness of fNIRS to measure prefrontal activity. We present an active, fNIRS-based neurofeedback (NF) interface, which uses differential changes in oxygenation between the left and right sides of the dorsolateral prefrontal cortex to operationalize BCI input. The system is activated by users generating a state of anger, which has been previously linked to increased left prefrontal asymmetry. We have incorporated this NF interface into an experimental platform adapted from a virtual 3D narrative, in which users can express anger at a virtual character perceived as evil, causing the character to disappear progressively. Eleven subjects used the system and were able to successfully perform NF despite minimal training. Extensive analysis confirms that success was associated with the intent to express anger. This has positive implications for the design of affective BCI based on prefrontal asymmetry

Towards empathic neurofeedback for interactive storytelling

Interactive Narrative is a form of digital entertainment based on AI techniques which support narrative generation and user interaction. Despite recent progress in the field, there is still a lack of unified models integrating narrative generation, user response and interaction. This paper addresses this issue by revisiting existing Interactive Narrative paradigms, granting explicit status to users’ disposition towards story characters. We introduce a novel Brain-Computer Interface (BCI) design, which attempts to capture empathy for the main character in a way that is compatible with filmic theories of emotion. Results from two experimental studies with a fully-implemented system demonstrate the effectiveness of a neurofeedback-based approach, showing that subjects can successfully modulate their emotional support for a character who is confronted with challenging situations. A preliminary fMRI analysis also shows activation during user interaction, in regions of the brain associated with emotional control

Phenotypic convergence of Menkes and Wilson disease.

Menkes disease is an X-linked multisystem disorder with epilepsy, kinky hair, and neurodegeneration caused by mutations in the copper transporter ATP7A. Other ATP7A mutations have been linked to juvenile occipital horn syndrome and adult-onset hereditary motor neuropathy.1,2 About 5%-10% of the patients present with "atypical Menkes disease" characterized by longer survival, cerebellar ataxia, and developmental delay.2 The intracellular copper transport is regulated by 2 P type ATPase copper transporters ATP7A and ATP7B. These proteins are expressed in the trans-Golgi network that guides copper to intracellular compartments, and in copper excess, it relocates copper to the plasma membrane to pump it out from the cells.3ATP7B mutations cause Wilson disease with dystonia, ataxia, tremor, and abnormal copper accumulation in the brain, liver, and other organs.4

Affective interaction with a virtual character through an fNIRS brain-computer interface

Affective brain-computer interfaces (BCI) harness Neuroscience knowledge to develop affective interaction from first principles. In this article, we explore affective engagement with a virtual agent through Neurofeedback (NF). We report an experiment where subjects engage with a virtual agent by expressing positive attitudes towards her under a NF paradigm. We use for affective input the asymmetric activity in the dorsolateral prefrontal cortex (DL-PFC), which has been previously found to be related to the high-level affective-motivational dimension of approach/avoidance. The magnitude of left-asymmetric DL-PFC activity, measured using functional near infrared spectroscopy (fNIRS) and treated as a proxy for approach, is mapped onto a control mechanism for the virtual agent’s facial expressions, in which action units (AUs) are activated through a neural network. We carried out an experiment with 18 subjects, which demonstrated that subjects are able to successfully engage with the virtual agent by controlling their mental disposition through NF, and that they perceived the agent’s responses as realistic and consistent with their projected mental disposition. This interaction paradigm is particularly relevant in the case of affective BCI as it facilitates the volitional activation of specific areas normally not under conscious control. Overall, our contribution reconciles a model of affect derived from brain metabolic data with an ecologically valid, yet computationally controllable, virtual affective communication environment

Levosimendan Administration in Limb Ischemia: Multicomponent Signaling Serving Kidney Protection

AIMS AND OBJECTIVES: Acute renal failure is a severe complication of lower extremity major arterial reconstructions, which could even be fatal. Levosimendan is a dual-acting positive inotropic and vasodilatory agent, which is suspected to have protective effects against cardiac ischemia. However, there is no data available on lower limb or remote organ ischemic injuries therefore the aim of the study was to investigate the effect of levosimendan on lower limb ischemia-reperfusion injury and the corollary renal dysfunction. METHODS: Male Wistar rats underwent 180 min bilateral lower limb ischemia followed by 4 or 24 hours of reperfusion. Intravenous Levosimendan was administered continuously (0.2mug/bwkg/min) throughout the whole course of ischemia and the first 3h of reperfusion. Results were compared with sham-operated and ischemia-reperfusion groups. Hemodynamic monitoring was performed by invasive arterial blood pressure measurement. Kidney and lower limb muscle microcirculation was registered by a laser Doppler flowmeter. After 4h and 24h of reperfusion, serum, urine and histological samples were collected. RESULTS: Systemic hemodynamic parameters and microcirculation of kidney and the lower limb significantly improved in the Levosimendan treated group. Muscle viability was significantly preserved 4 and 24 hours after reperfusion. At the same time, renal functional laboratory tests and kidney histology demonstrated significantly less expressive kidney injury in Levosimendan groups. TNF-alpha levels were significantly less elevated in the Levosimendan group 4 hours after reperfusion. CONCLUSION: The results claim a protective role for Levosimendan administration during major vascular surgeries to prevent renal complications